Author: "Jordan W. Smoller" / Topic: business - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Jordan W. Smoller"' showing total 181 results

Start Over Author "Jordan W. Smoller" Topic business

181 results on '"Jordan W. Smoller"'

1. Neptune: an environment for the delivery of genomic medicine

Author: Venner Eric, Victoria Yi, David Murdock, Sara E. Kalla, Tsung-Jung Wu, Aniko Sabo, Shoudong Li, Qingchang Meng, Xia Tian, Mullai Murugan, Michelle Cohen, Christie Kovar, Wei-Qi Wei, Wendy K. Chung, Chunhua Weng, Georgia L. Wiesner, Gail P. Jarvik, Donna Muzny, Richard A. Gibbs, Debra Abrams, Samuel E. Adunyah, Ladia Albertson-Junkans, Berta Almoguera, Darren C. Ames, Paul Appelbaum, Samuel Aronson, Sharon Aufox, Lawrence J. Babb, Adithya Balasubramanian, Hana Bangash, Melissa Basford, Lisa Bastarache, Samantha Baxter, Meckenzie Behr, Barbara Benoit, Elizabeth Bhoj, Suzette J. Bielinski, Sarah T. Bland, Carrie Blout, Kenneth Borthwick, Erwin P. Bottinger, Mark Bowser, Harrison Brand, Murray Brilliant, Wendy Brodeur, Pedro Caraballo, David Carrell, Andrew Carroll, Lisa Castillo, Victor Castro, Gauthami Chandanavelli, Theodore Chiang, Rex L. Chisholm, Kurt D. Christensen, Wendy Chung, Christopher G. Chute, Brittany City, Beth L. Cobb, John J. Connolly, Paul Crane, Katherine Crew, David R. Crosslin, Jyoti Dayal, Mariza De Andrade, Jessica De la Cruz, Josh C. Denny, Shawn Denson, Tim DeSmet, Ozan Dikilitas, Michael J. Dinsmore, Sheila Dodge, Phil Dunlea, Todd L. Edwards, Christine M. Eng, David Fasel, Alex Fedotov, Qiping Feng, Mark Fleharty, Andrea Foster, Robert Freimuth, Christopher Friedrich, Stephanie M. Fullerton, Birgit Funke, Stacey Gabriel, Vivian Gainer, Ali Gharavi, Andrew M. Glazer, Joseph T. Glessner, Jessica Goehringer, Adam S. Gordon, Chet Graham, Robert C. Green, Justin H. Gundelach, Heather S. Hain, Hakon Hakonarson, Maegan V. Harden, John Harley, Margaret Harr, Andrea Hartzler, M. Geoffrey Hayes, Scott Hebbring, Nora Henrikson, Andrew Hershey, Christin Hoell, Ingrid Holm, Kayla M. Howell, George Hripcsak, Jianhong Hu, Elizabeth Duffy Hynes, Joy C. Jayaseelan, Yunyun Jiang, Yoonjung Yoonie Joo, Sheethal Jose, Navya Shilpa Josyula, Anne E. Justice, Divya Kalra, Elizabeth W. Karlson, Brendan J. Keating, Melissa A. Kelly, Eimear E. Kenny, Dustin Key, Krzysztof Kiryluk, Terrie Kitchner, Barbara Klanderman, Eric Klee, David C. Kochan, Viktoriya Korchina, Leah Kottyan, Emily Kudalkar, Alanna Kulchak Rahm, Iftikhar J. Kullo, Philip Lammers, Eric B. Larson, Matthew S. Lebo, Magalie Leduc, Ming Ta (Michael) Lee, Niall J. Lennon, Kathleen A. Leppig, Nancy D. Leslie, Rongling Li, Wayne H. Liang, Chiao-Feng Lin, Jodell E. Linder, Noralane M. Lindor, Todd Lingren, James G. Linneman, Cong Liu, Wen Liu, Xiuping Liu, John Lynch, Hayley Lyon, Alyssa Macbeth, Harshad Mahadeshwar, Lisa Mahanta, Bradley Malin, Teri Manolio, Maddalena Marasa, Keith Marsolo, Michelle L. McGowan, Elizabeth McNally, Jim Meldrim, Frank Mentch, Hila Milo Rasouly, Jonathan Mosley, Shubhabrata Mukherjee, Thomas E. Mullen, Jesse Muniz, David R. Murdock, Shawn Murphy, Melanie F. Myers, Bahram Namjou, Yizhao Ni, Robert C. Onofrio, Aniwaa Owusu Obeng, Thomas N. Person, Josh F. Peterson, Lynn Petukhova, Cassandra J. Pisieczko, Siddharth Pratap, Cynthia A. Prows, Megan J. Puckelwartz, Ritika Raj, James D. Ralston, Arvind Ramaprasan, Andrea Ramirez, Luke Rasmussen, Laura Rasmussen-Torvik, Soumya Raychaudhuri, Heidi L. Rehm, Marylyn D. Ritchie, Catherine Rives, Beenish Riza, Dan M. Roden, Elisabeth A. Rosenthal, Avni Santani, Schaid Dan, Steven Scherer, Stuart Scott, Aaron Scrol, Soumitra Sengupta, Ning Shang, Himanshu Sharma, Richard R. Sharp, Rajbir Singh, Patrick M.A. Sleiman, Kara Slowik, Joshua C. Smith, Maureen E. Smith, Duane T. Smoot, Jordan W. Smoller, Sunghwan Sohn, Ian B. Stanaway, Justin Starren, Mary Stroud, Jessica Su, Casey Overby Taylor, Kasia Tolwinski, Sara L. Van Driest, Sean M. Vargas, Matthew Varugheese, David Veenstra, Eric Venner, Miguel Verbitsky, Gina Vicente, Michael Wagner, Kimberly Walker, Theresa Walunas, Liwen Wang, Qiaoyan Wang, Scott T. Weiss, Quinn S. Wells, Peter S. White, Ken L. Wiley, Janet L. Williams, Marc S. Williams, Michael W. Wilson, Leora Witkowski, Laura Allison Woods, Betty Woolf, Julia Wynn, Yaping Yang, Ge Zhang, Lan Zhang, and Hana Zouk
Subjects: Computer science, business.industry, Process (engineering), MEDLINE, High-Throughput Nucleotide Sequencing, Genomics, Data science, Article, Personalization, Variety (cybernetics), Workflow, Neptune, Pharmacogenomics, Health care, Electronic Health Records, Humans, business, Software, Genetics (clinical)
Abstract: Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .
Published: 2021

2. Polygenic risk for major depression is associated with lifetime suicide attempt in <scp>US</scp> soldiers independent of personal and parental history of major depression

Author: Murray B. Stein, Karmel W. Choi, Joel Gelernter, Robert J. Ursano, Sonia Jain, Laura Campbell-Sills, Tian Ge, Ronald C. Kessler, Erin B. Ware, Feng He, and Jordan W. Smoller
Subjects: Parents, Poison control, Suicide, Attempted, behavioral disciplines and activities, Suicide prevention, Article, Cellular and Molecular Neuroscience, Risk Factors, Injury prevention, medicine, Humans, Prospective Studies, Family history, Genetics (clinical), Depression (differential diagnoses), Depressive Disorder, Major, Suicide attempt, Depression, business.industry, medicine.disease, Psychiatry and Mental health, Military Personnel, Cohort, Major depressive disorder, business, Demography
Abstract: Suicide is a major public health problem. The contribution of common genetic variants for major depressive disorder (MDD) independent of personal and parental history of MDD has not been established. Polygenic risk score (using PRS-CS) for MDD was calculated for US Army soldiers of European ancestry. Associations between polygenic risk for MDD and lifetime suicide attempt (SA) were tested in models that also included parental or personal history of MDD. Models were adjusted for age, sex, tranche (where applicable), and 10 principal components reflecting ancestry. In the first cohort, 417 (6.3%) of 6,573 soldiers reported a lifetime history of SA. In a multivariable model that included personal [OR = 3.83, 95% CI:3.09-4.75] and parental history of MDD [OR = 1.43, 95% CI:1.13-1.82 for one parent and OR = 1.64, 95% CI:1.20-2.26 for both parents), MDD PRS was significantly associated with SA (OR = 1.22 [95% CI:1.10-1.36]). In the second cohort, 204 (4.2%) of 4,900 soldiers reported a lifetime history of SA. In a multivariable model that included personal [OR = 3.82, 95% CI:2.77-5.26] and parental history of MDD [OR = 1.42, 95% CI:0.996-2.03 for one parent and OR = 2.21, 95% CI:1.33-3.69 for both parents) MDD PRS continued to be associated (at p = .0601) with SA (OR = 1.15 [95% CI:0.994-1.33]). A soldier's PRS for MDD conveys information about likelihood of a lifetime SA beyond that conveyed by two predictors readily obtainable by interview: personal or parental history of MDD. Results remain to be extended to prospective prediction of incident SA. These findings portend a role for PRS in risk stratification for suicide attempts.
Published: 2021

3. Hematopoietic mosaic chromosomal alterations increase the risk for diverse types of infection

Author: Seyedeh M. Zekavat, Iuliana Ionita-Laza, Pradeep Natarajan, Zhaolong Yu, Kaavya Paruchuri, Akhil Pampana, Eric A. Engels, Scott T. Weiss, Steven A. McCarroll, Shu-Hong Lin, Matthew S. Lebo, Mark J. Daly, Mitchell J. Machiela, Muredach P. Reilly, Romit Bhattacharya, Puja Kohli, Xiaoxi Liu, Mesbah Uddin, Jordan W. Smoller, Robert C. Green, Chen Wang, James P. Pirruccello, Alexander G. Bick, Yixuan Ye, Andrea Ganna, Aoxing Liu, Po-Ru Loh, Benjamin M. Neale, Giulio Genovese, Patrick T. Ellinor, Elizabeth W. Karlson, Chikashi Terao, Krzysztof Kiryluk, Yoichiro Kamatani, Hongyu Zhao, Benjamin L. Ebert, and Derek Brown
Subjects: 0301 basic medicine, business.industry, Cancer, Genome-wide association study, General Medicine, medicine.disease, Article, General Biochemistry, Genetics and Molecular Biology, Sepsis, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Immune system, Infectious disease (medical specialty), 030220 oncology & carcinogenesis, Genotype, Immunology, medicine, Risk factor, business, Genotyping
Abstract: Age is the dominant risk factor for infectious diseases, but the mechanisms linking the two are incompletely understood1,2. Age-related mosaic chromosomal alterations (mCAs) detected from blood-derived DNA genotyping, are structural somatic variants associated with aberrant leukocyte cell counts, hematological malignancy, and mortality3-11. Whether mCAs represent independent risk factors for infection is unknown. Here we use genome-wide genotyping of blood DNA to show that mCAs predispose to diverse infectious diseases. We analyzed mCAs from 767,891 individuals without hematological cancer at DNA acquisition across four countries. Expanded mCA (cell fraction10%) prevalence approached 4% by 60 years of age and was associated with diverse incident infections, including sepsis, pneumonia, and coronavirus disease 2019 (COVID-19) hospitalization. A genome-wide association study of expanded mCAs identified 63 significant loci. Germline genetic alleles associated with expanded mCAs were enriched at transcriptional regulatory sites for immune cells. Our results link mCAs with impaired immunity and predisposition to infections. Furthermore, these findings may also have important implications for the ongoing COVID-19 pandemic, particularly in prioritizing individual preventive strategies and evaluating immunization responses.
Published: 2021

4. Dissecting the heterogeneity of posttraumatic stress disorder: differences in polygenic risk, stress exposures, and course of PTSD subtypes

Author: Karmel W. Choi, Laura Campbell-Sills, Ronald C. Kessler, Joel Gelernter, Sonia Jain, Xiaoying Sun, Daniel F. Levey, Robert J. Ursano, Jordan W. Smoller, Murray B. Stein, and Feng He
Subjects: Typology, Persistence (psychology), business.industry, Anhedonia, medicine.disease, Comorbidity, Latent class model, 030227 psychiatry, 03 medical and health sciences, Psychiatry and Mental health, Posttraumatic stress, 0302 clinical medicine, mental disorders, medicine, medicine.symptom, Prospective cohort study, business, 030217 neurology & neurosurgery, Applied Psychology, Depression (differential diagnoses), Clinical psychology
Abstract: BackgroundDefinition of disorder subtypes may facilitate precision treatment for posttraumatic stress disorder (PTSD). We aimed to identify PTSD subtypes and evaluate their associations with genetic risk factors, types of stress exposures, comorbidity, and course of PTSD.MethodsData came from a prospective study of three U.S. Army Brigade Combat Teams that deployed to Afghanistan in 2012. Soldiers with probable PTSD (PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition ≥31) at three months postdeployment comprised the sample (N = 423) for latent profile analysis using Gaussian mixture modeling and PTSD symptom ratings as indicators. PTSD profiles were compared on polygenic risk scores (derived from external genomewide association study summary statistics), experiences during deployment, comorbidity at three months postdeployment, and persistence of PTSD at nine months postdeployment.ResultsLatent profile analysis revealed profiles characterized by prominent intrusions, avoidance, and hyperarousal (threat-reactivity profile; n = 129), anhedonia and negative affect (dysphoric profile; n = 195), and high levels of all PTSD symptoms (high-symptom profile; n = 99). The threat-reactivity profile had the most combat exposure and the least comorbidity. The dysphoric profile had the highest polygenic risk for major depression, and more personal life stress and co-occurring major depression than the threat-reactivity profile. The high-symptom profile had the highest rates of concurrent mental disorders and persistence of PTSD.ConclusionsGenetic and trauma-related factors likely contribute to PTSD heterogeneity, which can be parsed into subtypes that differ in symptom expression, comorbidity, and course. Future studies should evaluate whether PTSD typology modifies treatment response and should clarify distinctions between the dysphoric profile and depressive disorders.
Published: 2021

5. Prevalence and risk factors of psychiatric symptoms and diagnoses before and during the COVID-19 pandemic: findings from the ELSA-Brasil COVID-19 mental health cohort

Author: Lais B. Razza, Pamela Marques Forte, Maria Angélica Nunes, Pedro Starzynski Bacchi, Leonardo Afonso Dos Santos, Marcia Cristina de Altisent Oliveira Cardoso, Leandro Valiengo, Sarah Bauermeister, Paulo Jeng Chian Suen, Priscila V. Bueno, Paulo A. Lotufo, Maria Carmen Viana, Izio Klein, Isabela M. Benseñor, Márcio Sommer Bittencourt, Bianca Silva Pinto, Ives Cavalcante Passos, Jordan W. Smoller, Helena Bellini, Andre R. Brunoni, Marina Moreno, Jose Gallucci-Neto, Juliana Pereira de Sousa, Luciana Lima de Siqueira, Larissa de Cássia Silva Félix, Daniel Fatori, Giovanni Abrahão Salum, Itamar S. Santos, and Rebeca Pelosof
Subjects: medicine.medical_specialty, Longitudinal study, Anxiety, 03 medical and health sciences, 0302 clinical medicine, cohort study, Medicine, 030212 general & internal medicine, Psychiatry, Applied Psychology, Depression (differential diagnoses), business.industry, pandemic, COVID-19, Mental health, Confidence interval, Psychiatry and Mental health, depression, Cohort, Original Article, medicine.symptom, business, mental health, 030217 neurology & neurosurgery, Psychopathology, Cohort study
Abstract: Background There is mixed evidence on increasing rates of psychiatric disorders and symptoms during the coronavirus disease 2019 (COVID-19) pandemic in 2020. We evaluated pandemic-related psychopathology and psychiatry diagnoses and their determinants in the Brazilian Longitudinal Study of Health (ELSA-Brasil) São Paulo Research Center. Methods Between pre-pandemic ELSA-Brasil assessments in 2008–2010 (wave-1), 2012–2014 (wave-2), 2016–2018 (wave-3) and three pandemic assessments in 2020 (COVID-19 waves in May–July, July–September, and October–December), rates of common psychiatric symptoms, and depressive, anxiety, and common mental disorders (CMDs) were compared using the Clinical Interview Scheduled-Revised (CIS-R) and the Depression Anxiety Stress Scale-21 (DASS-21). Multivariable generalized linear models, adjusted by age, gender, educational level, and ethnicity identified variables associated with an elevated risk for mental disorders. Results In 2117 participants (mean age 62.3 years, 58.2% females), rates of CMDs and depressive disorders did not significantly change over time, oscillating from 23.5% to 21.1%, and 3.3% to 2.8%, respectively; whereas rate of anxiety disorders significantly decreased (2008–2010: 13.8%; 2016–2018: 9.8%; 2020: 8%). There was a decrease along three wave-COVID assessments for depression [β = −0.37, 99.5% confidence interval (CI) −0.50 to −0.23], anxiety (β = −0.37, 99.5% CI −0.48 to −0.26), and stress (β = −0.48, 99.5% CI −0.64 to −0.33) symptoms (all ps < 0.001). Younger age, female sex, lower educational level, non-white ethnicity, and previous psychiatric disorders were associated with increased odds for psychiatric disorders, whereas self-evaluated good health and good quality of relationships with decreased risk. Conclusion No consistent evidence of pandemic-related worsening psychopathology in our cohort was found. Indeed, psychiatric symptoms slightly decreased along 2020. Risk factors representing socioeconomic disadvantages were associated with increased odds of psychiatric disorders.
Published: 2021

6. Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information

Author: Alma Dzubur Kulenovic, Michael J. Lyons, Elizabeth A. Bolger, Kenneth J. Ruggiero, Zhewu Wang, Laramie E. Duncan, Bozo Lugonja, Joanne Voisey, José Miguel Caldas-de-Almeida, Regina E. McGlinchey, Laura J. Bierut, Michael A. Hauser, Jean C. Beckham, Dan J. Stein, Alexander C. McFarlane, Elbert Geuze, Victoria B. Risbrough, Douglas Maurer, Christy A. Denckla, Seth G. Disner, William P. Milberg, Erika J. Wolf, Scott R. Sponheim, Caroline M. Nievergelt, Henry R. Kranzler, Clement C. Zai, Antonia V. Seligowski, Miro Jakovljević, Katharina Domschke, Paul A. Arbisi, Thomas Werge, Vasiliki Michopoulos, Joel Gelernter, Sarah D. Linnstaedt, Nastassja Koen, Sonya B. Norman, Nicholas G. Martin, Janine D. Flory, Meghan M Brashear, Melissa A. Polusny, Nathan A. Kimbrel, Douglas L. Delahanty, Milissa L. Kaufman, Peter Roy-Byrne, Magali Haas, Monica Uddin, Matig R. Mavissakalian, William S. Kremen, Ole A. Andreassen, Marco P. Boks, Matthew S. Panizzon, Christiaan H. Vinkers, Bart P. F. Rutten, Heather Lasseter, Richard A. Shaffer, Aferdita Goci, Jessica L. Maples-Keller, Israel Liberzon, Melanie E. Garrett, Alicia K. Smith, Catrin Lewis, Dewleen G. Baker, Murray B. Stein, Xuejun Qin, Nikolaos P. Daskalakis, Sherry Winternitz, Douglas E. Williamson, Alex O. Rothbaum, David Forbes, Leigh van den Heuvel, Scott D. Gordon, Edward J. Trapido, Marti Jett, Ole Mors, Adam X. Maihofer, Christina M. Sheerin, Lori A. Zoellner, A.C. Bustamante, David M. Hougaard, Alexandra Evans, Chia-Yen Chen, Robert H. Pietrzak, Rachel Yehuda, Allison C. Provost, Matthew Peverill, Aarti Gautam, Bruce R. Lawford, Derrick Silove, Bekh Bradley, Gerome Breen, Charles F. Gillespie, Allison E. Ashley-Koch, Kerry J. Ressler, Christiane Wolf, Renato Polimanti, Jonathan Ian Bisson, Adriana Lori, Lynn M. Almli, Norah C. Feeny, Jonas Bybjerg-Grauholm, Guia Guffanti, Søren Bo Andersen, Anders D. Børglum, Elizabeth Ketema, Andrea L. Roberts, Marie Bμkvad-Hansen, Ross McD. Young, Jürgen Deckert, Jonathan Sebat, Rajendra A. Morey, P. B. Mortensen, Lindsay A. Farrer, Yunpeng Wang, Karestan C. Koenen, Joseph R. Calabrese, Bizu Gelaye, Jurjen J. Luykx, Andrew Ratanatharathorn, Charles P. Morris, S. Bryn Austin, Miranda Van Hooff, Edward S. Peters, Katie A. McLaughlin, Anthony P. King, Jonathan R. I. Coleman, Holly K. Orcutt, Keith A. Young, Samuel A. McLean, Jennifer S. Stevens, Rasha Hammamieh, Robert J. Ursano, Mark W. Miller, Allison E. Aiello, Charles R. Marmar, Esmina Avdibegović, Katy Torres, Elliot C. Nelson, Rany M. Salem, Martin H. Teicher, Rebecca Mellor, Karen-Inge Karstoft, Aliza P. Wingo, Alaptagin Khan, Michelle A. Williams, Dick Schijven, Merete Nordentoft, Ananda B. Amstadter, Shareefa Dalvie, Michelle F. Dennis, Mark J. Daly, Mark W. Logue, Soraya Seedat, Julia S. Seng, Carol E. Franz, Stephan Ripke, Karmel W. Choi, Sandro Galea, Richard A. Bryant, Ian Jones, Anders M. Dale, Wesley K. Thompson, Lauren A.M. Lebois, Sixto E. Sanchez, Ronald C. Kessler, Tanja Jovanovic, Divya Mehta, Jordan W. Smoller, Eric O. Johnson, John P. Rice, Andrew C. Heath, Nancy L. Saccone, Barbara O. Rothbaum, Alan L. Peterson, Meaghan O'Donnell, Sian M. J. Hemmings, Eric Vermetten, Dragan Babić, Hongyu Zhao, Tianying Wu, Christopher R. Erbes, Ariane Rung, NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM), Centro de Estudos de Doenças Crónicas (CEDOC), Psychiatrie & Neuropsychologie, RS: MHeNs - R3 - Neuroscience, MUMC+: MA Psychiatrie (3), Anatomy and neurosciences, Psychiatry, and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep
Subjects: Oncology, Multivariate analysis, LD SCORE REGRESSION, Genome-wide association study, THOUSANDS, Medical and Health Sciences, Stress Disorders, Post-Traumatic, GWAS, Stress Disorders, Psychiatry, Genome-Wide Association Study / methods, Traumatic stress, PROLIFERATION, PTSD, Single Nucleotide, Biological Sciences, Post-Traumatic Stress Disorder (PTSD), Anxiety Disorders, Mental Health, Phenotype, Cohort, Polymorphism, Single Nucleotide / genetics, medicine.medical_specialty, Stress Disorders, Post-Traumatic / genetics, Quantitative trait locus, Polymorphism, Single Nucleotide, Genetic correlation, behavioral disciplines and activities, Trauma, Heritability, Internal medicine, PSYCHIATRIC GENOMICS, mental disorders, medicine, Genetics, Humans, Genetic Predisposition to Disease, Polymorphism, GENOME-WIDE ASSOCIATION, METAANALYSIS, Biological Psychiatry, Genetic association, business.industry, Prevention, Human Genome, Psychology and Cognitive Sciences, PheWAS, Brain Disorders, Post-Traumatic, RISK-FACTORS, business, Genome-Wide Association Study
Abstract: Funding Information: This work was supported by the National Institute of Mental Health / U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium ), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience . Statistical analyses were carried out on the LISA/Genetic Cluster Computer ( https://userinfo.surfsara.nl/systems/lisa ) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. Funding Information: MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc., RallyPoint Networks, Inc., Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled “Genotype-guided dosing of opioid agonists,” filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Funding Information: This work was supported by the National Institute of Mental Health/ U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience. Statistical analyses were carried out on the LISA/Genetic Cluster Computer (https://userinfo.surfsara.nl/systems/lisa) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. This material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting true views of the U.S. Department of the Army or the Department of Defense. We thank the investigators who comprise the PGC-PTSD working group and especially the more than 206,000 research participants worldwide who shared their life experiences and biological samples with PGC-PTSD investigators. We thank Mark Zervas for his critical input. Full acknowledgments are in Supplement 1. MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc. RallyPoint Networks, Inc. Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled ?Genotype-guided dosing of opioid agonists,? filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: © 2021 Society of Biological Psychiatry Background: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods. publishersversion published
Published: 2022

7. Socio-demographic and trauma-related predictors of PTSD within 8 weeks of a motor vehicle collision in the AURORA study

Author: Lauren A. Hudak, Francesca L. Beaudoin, William F. Peacock, Leon D. Sanchez, Jutta Joormann, Donglin Zeng, Sarah D. Linnstaedt, M Deanna, Steven E. Harte, Nancy A. Sampson, Jennifer S. Stevens, Kerry J. Ressler, Elizabeth M. Datner, Xinming An, Thaddeus W.W. Pace, John P. Haran, Brittany E. Punches, Lauren A.M. Lebois, Alan B. Storrow, Robert M. Domeier, Stacey L. House, Diego A. Pizzagalli, Ronald C. Kessler, Niels K. Rathlev, Irving Hwang, Sanne J.H. van Rooij, James M. Elliott, Samuel A. McLean, Sophia Sheikh, Nathaniel G. Harnett, Thomas C. Neylan, Mark W. Miller, Laura Germine, Claire Pearson, Steven E. Bruce, Kamran Mohiuddin, Jordan W. Smoller, John F. Sheridan, Meghan E. McGrath, Christopher W. Jones, Phyllis L. Hendry, Karestan C. Koenen, Nina T. Gentile, David A. Peak, and Paul I. Musey
Subjects: 0301 basic medicine, Longitudinal study, business.industry, Socio demographics, Emergency department, Acute Stress Disorder, 03 medical and health sciences, Cellular and Molecular Neuroscience, Psychiatry and Mental health, Posttraumatic stress, 030104 developmental biology, 0302 clinical medicine, mental disorders, Medicine, business, Molecular Biology, Socioeconomic status, 030217 neurology & neurosurgery, Motor vehicle crash, Clinical psychology
Abstract: This is the initial report of results from the AURORA multisite longitudinal study of adverse post-traumatic neuropsychiatric sequelae (APNS) among participants seeking emergency department (ED) treatment in the aftermath of a traumatic life experience. We focus on n = 666 participants presenting to EDs following a motor vehicle collision (MVC) and examine associations of participant socio-demographic and participant-reported MVC characteristics with 8-week posttraumatic stress disorder (PTSD) adjusting for pre-MVC PTSD and mediated by peritraumatic symptoms and 2-week acute stress disorder (ASD). Peritraumatic Symptoms, ASD, and PTSD were assessed with self-report scales. Eight-week PTSD prevalence was relatively high (42.0%) and positively associated with participant sex (female), low socioeconomic status (education and income), and several self-report indicators of MVC severity. Most of these associations were entirely mediated by peritraumatic symptoms and, to a lesser degree, ASD, suggesting that the first 2 weeks after trauma may be a uniquely important time period for intervening to prevent and reduce risk of PTSD. This observation, coupled with substantial variation in the relative strength of mediating pathways across predictors, raises the possibility of diverse and potentially complex underlying biological and psychological processes that remain to be elucidated with more in-depth analyses of the rich and evolving AURORA data.
Published: 2020

8. Evidence in the UK Biobank for the underdiagnosis of erythropoietic protoporphyria

Author: Hetanshi Naik, John Phillips, Yen-Chen Anne Feng, Manisha Balwani, Herbert L. Bonkovsky, Xihong Lin, David C. Christiani, Jordan W. Smoller, Sarah Ducamp, Amy K. Dickey, Bruce Wang, Zhaozhong Zhu, Mark D. Fleming, Karl E. Anderson, Brendan M. McGuire, Daniel I. Chasman, Corbin Quick, and Lina Rebeiz
Subjects: 0301 basic medicine, medicine.medical_specialty, ferrochelatase, Protoporphyria, Erythropoietic, Anemia, erythropoietic protoporphyria, Erythropoietic protoporphyria (EPP), Clinical Sciences, prevalence, 030105 genetics & heredity, Article, ferrochelatase (FECH), 03 medical and health sciences, Clinical Research, Internal medicine, Genetics, mean corpuscular volume (MCV), Medicine, 2.1 Biological and endogenous factors, Humans, Protoporphyria, Allele, Aetiology, Exome, Genetics (clinical), Biological Specimen Banks, Genetics & Heredity, biology, mean corpuscular volume, business.industry, Erythropoietic, Ferrochelatase, medicine.disease, Biobank, anemia, Confidence interval, United Kingdom, Minor allele frequency, Europe, 030104 developmental biology, Mutation, biology.protein, Erythropoietic protoporphyria, business, Digestive Diseases
Abstract: PurposeErythropoietic protoporphyria (EPP), characterized by painful cutaneous photosensitivity, results from pathogenic variants in ferrochelatase (FECH). For 96% of patients, EPP results from coinheriting a rare pathogenic variant in trans of a common hypomorphic variant c.315-48T>C (minor allele frequency 0.05). The estimated prevalence of EPP derived from the number of diagnosed individuals in Europe is 0.00092%, but this may be conservative due to underdiagnosis. No study has estimated EPP prevalence using large genetic data sets.MethodsDisease-associated FECH variants were identified in the UK Biobank, a data set of 500,953 individuals including 49,960 exome sequences. EPP prevalence was then estimated. The association of FECH variants with EPP-related traits was assessed.ResultsAnalysis of pathogenic FECH variants in the UK Biobank provides evidence that EPP prevalence is 0.0059% (95% confidence interval [CI]: 0.0042-0.0076%), 1.7-3.0 times more common than previously thought in the UK. In homozygotes for the common c.315-48T>C FECH variant, there was a novel decrement in both erythrocyte mean corpuscular volume (MCV) and hemoglobin.ConclusionThe prevalence of EPP has been underestimated secondary to underdiagnosis. The common c.315-48T>C allele is associated with both MCV and hemoglobin, an association that could be important both for those with and without EPP.
Published: 2020

9. Limitations of Contemporary Guidelines for Managing Patients at High Genetic Risk of Coronary Artery Disease

Author: George Hindy, Lu-Chen Weng, Patrick T. Ellinor, Kumardeep Chaudhary, Phoebe Finneran, Girish N. Nadkarni, Anthony A. Philippakis, Amanda Dobbyn, Ruth J. F. Loos, Andrew Cagan, Jeffrey S. Reid, Renae Judy, Rachel L. Kember, Jordan W. Smoller, Amit Khera, Sekar Kathiresan, Daniel J. Rader, Scott T. Weiss, Aris Baras, John D. Overton, Krishna G. Aragam, Ron Do, Steven A. Lubitz, Pradeep Natarajan, Scott M. Damrauer, Mark Chaffin, Elizabeth W. Karlson, and Judy H. Cho
Subjects: Adult, Male, Multifactorial Inheritance, medicine.medical_specialty, Statin, Databases, Factual, medicine.drug_class, primary prevention, CAD, Coronary Artery Disease, 030204 cardiovascular system & hematology, genetic risk, Article, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Primary prevention, Health care, medicine, Electronic Health Records, Humans, Genetic Predisposition to Disease, cardiovascular diseases, 030212 general & internal medicine, Genetic risk, Intensive care medicine, Aged, Aged, 80 and over, business.industry, statin, Disease Management, Guideline, Odds ratio, Middle Aged, medicine.disease, Practice Guidelines as Topic, Female, Cardiology and Cardiovascular Medicine, business, Delivery of Health Care
Abstract: Polygenic risk scores (PRS) for coronary artery disease (CAD) identify high-risk individuals more likely to benefit from primary prevention statin therapy. Whether polygenic CAD risk is captured by conventional paradigms for assessing clinical cardiovascular risk remains unclear.This study sought to intersect polygenic risk with guideline-based recommendations and management patterns for CAD primary prevention.A genome-wide CAD PRS was applied to 47,108 individuals across 3 U.S. health care systems. The authors then assessed whether primary prevention patients at high polygenic risk might be distinguished on the basis of greater guideline-recommended statin eligibility and higher rates of statin therapy.Of 47,108 study participants, the mean age was 60 years, and 11,020 (23.4%) had CAD. The CAD PRS strongly associated with prevalent CAD (odds ratio: 1.4 per SD increase in PRS; p 0.0001). High polygenic risk (top 20% of PRS) conferred 1.9-fold odds of developing CAD (p 0.0001). However, among primary prevention patients (n = 33,251), high polygenic risk did not correspond with increased recommendations for statin therapy per the American College of Cardiology/American Heart Association (46.2% for those with high PRS vs. 46.8% for all others, p = 0.54) or U.S. Preventive Services Task Force (43.7% vs. 43.7%, p = 0.99) or higher rates of statin prescriptions (25.0% vs. 23.8%, p = 0.04). An additional 4.1% of primary prevention patients may be recommended for statin therapy if high CAD PRS were considered a guideline-based risk-enhancing factor.Current paradigms for primary cardiovascular prevention incompletely capture a polygenic susceptibility to CAD. An opportunity may exist to improve CAD prevention efforts by integrating both genetic and clinical risk.
Published: 2020

10. Resilience to mental disorders in a low-income, non-Westernized setting

Author: Kate M. Scott, Stephanie Chardoul, Jordan W. Smoller, Dirgha J. Ghimire, Yang Zhang, and William G. Axinn
Subjects: medicine.medical_specialty, Bipolar Disorder, Psychological intervention, Article, 03 medical and health sciences, 0302 clinical medicine, Prevalence of mental disorders, Prevalence, medicine, Humans, 030212 general & internal medicine, Bipolar disorder, Psychiatry, Applied Psychology, Depressive Disorder, Major, business.industry, Mental Disorders, Panic disorder, medicine.disease, Health Surveys, Mental health, 030227 psychiatry, Psychiatry and Mental health, Mental Health, Mood, Major depressive disorder, Anxiety, medicine.symptom, business
Abstract: BackgroundCross-national studies have found, unexpectedly, that mental disorder prevalence is higher in high-income relative to low-income countries, but few rigorous studies have been conducted in very low-income countries. This study assessed mental disorders in Nepal, employing unique methodological features designed to maximize disorder detection and reporting.MethodsIn 2016–2018, 10714 respondents aged 15–59 were interviewed as part of an ongoing panel study, with a response rate of 93%. The World Mental Health version of the Composite International Diagnostic Interview (WMH-CIDI 3.0) measured lifetime and 12-month prevalence of selected anxiety, mood, alcohol use, and impulse control disorders. Lifetime recall was enhanced using a life history calendar.ResultsLifetime prevalence ranged from 0.3% (95% CI 0.2–0.4) for bipolar disorder to 15.1% (95% CI 14.4–15.7) for major depressive disorder. The 12-month prevalences were low, ranging from 0.2% for panic disorder (95% CI 0.1–0.3) and bipolar disorder (95% CI 0.1–0.2) to 2.7% for depression (95% CI 2.4–3.0). Lifetime disorders were higher among those with less education and in the low-caste ethnic group. Gender differences were pronounced.ConclusionsAlthough cultural effects on reporting cannot be ruled out, these low 12-month prevalences are consistent with reduced prevalence of mental disorders in other low-income countries. Identification of sociocultural factors that mediate the lower prevalence of mental disorders in low-income, non-Westernized settings may have implications for understanding disorder etiology and for clinical or policy interventions aimed at facilitating resilience.
Published: 2020

11. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Author: Niamh Mullins, JooEun Kang, Adrian I. Campos, Jonathan R.I. Coleman, Alexis C. Edwards, Hanga Galfalvy, Daniel F. Levey, Adriana Lori, Andrey Shabalin, Anna Starnawska, Mei-Hsin Su, Hunna J. Watson, Mark Adams, Swapnil Awasthi, Michael Gandal, Jonathan D. Hafferty, Akitoyo Hishimoto, Minsoo Kim, Satoshi Okazaki, Ikuo Otsuka, Stephan Ripke, Erin B. Ware, Andrew W. Bergen, Wade H. Berrettini, Martin Bohus, Harry Brandt, Xiao Chang, Wei J. Chen, Hsi-Chung Chen, Steven Crawford, Scott Crow, Emily DiBlasi, Philibert Duriez, Fernando Fernández-Aranda, Manfred M. Fichter, Steven Gallinger, Stephen J. Glatt, Philip Gorwood, Yiran Guo, Hakon Hakonarson, Katherine A. Halmi, Hai-Gwo Hwu, Sonia Jain, Stéphane Jamain, Susana Jiménez-Murcia, Craig Johnson, Allan S. Kaplan, Walter H. Kaye, Pamela K. Keel, James L. Kennedy, Kelly L. Klump, Dong Li, Shih-Cheng Liao, Klaus Lieb, Lisa Lilenfeld, Chih-Min Liu, Pierre J. Magistretti, Christian R. Marshall, James E. Mitchell, Eric T. Monson, Richard M. Myers, Dalila Pinto, Abigail Powers, Nicolas Ramoz, Stefan Roepke, Vsevolod Rozanov, Stephen W. Scherer, Christian Schmahl, Marcus Sokolowski, Michael Strober, Laura M. Thornton, Janet Treasure, Ming T. Tsuang, Stephanie H. Witt, D. Blake Woodside, Zeynep Yilmaz, Lea Zillich, Rolf Adolfsson, Ingrid Agartz, Tracy M. Air, Martin Alda, Lars Alfredsson, Ole A. Andreassen, Adebayo Anjorin, Vivek Appadurai, María Soler Artigas, Sandra Van der Auwera, M. Helena Azevedo, Nicholas Bass, Claiton H.D. Bau, Bernhard T. Baune, Frank Bellivier, Klaus Berger, Joanna M. Biernacka, Tim B. Bigdeli, Elisabeth B. Binder, Michael Boehnke, Marco P. Boks, Rosa Bosch, David L. Braff, Richard Bryant, Monika Budde, Enda M. Byrne, Wiepke Cahn, Miguel Casas, Enrique Castelao, Jorge A. Cervilla, Boris Chaumette, Sven Cichon, Aiden Corvin, Nicholas Craddock, David Craig, Franziska Degenhardt, Srdjan Djurovic, Howard J. Edenberg, Ayman H. Fanous, Jerome C. Foo, Andreas J. Forstner, Mark Frye, Janice M. Fullerton, Justine M. Gatt, Pablo V. Gejman, Ina Giegling, Hans J. Grabe, Melissa J. Green, Eugenio H. Grevet, Maria Grigoroiu-Serbanescu, Blanca Gutierrez, Jose Guzman-Parra, Steven P. Hamilton, Marian L. Hamshere, Annette Hartmann, Joanna Hauser, Stefanie Heilmann-Heimbach, Per Hoffmann, Marcus Ising, Ian Jones, Lisa A. Jones, Lina Jonsson, René S. Kahn, John R. Kelsoe, Kenneth S. Kendler, Stefan Kloiber, Karestan C. Koenen, Manolis Kogevinas, Bettina Konte, Marie-Odile Krebs, Mikael Landén, Jacob Lawrence, Marion Leboyer, Phil H. Lee, Douglas F. Levinson, Calwing Liao, Jolanta Lissowska, Susanne Lucae, Fermin Mayoral, Susan L. McElroy, Patrick McGrath, Peter McGuffin, Andrew McQuillin, Sarah E. Medland, Divya Mehta, Ingrid Melle, Yuri Milaneschi, Philip B. Mitchell, Esther Molina, Gunnar Morken, Preben Bo Mortensen, Bertram Müller-Myhsok, Caroline Nievergelt, Vishwajit Nimgaonkar, Markus M. Nöthen, Michael C. O’Donovan, Roel A. Ophoff, Michael J. Owen, Carlos Pato, Michele T. Pato, Brenda W.J.H. Penninx, Jonathan Pimm, Giorgio Pistis, James B. Potash, Robert A. Power, Martin Preisig, Digby Quested, Josep Antoni Ramos-Quiroga, Andreas Reif, Marta Ribasés, Vanesa Richarte, Marcella Rietschel, Margarita Rivera, Andrea Roberts, Gloria Roberts, Guy A. Rouleau, Diego L. Rovaris, Dan Rujescu, Cristina Sánchez-Mora, Alan R. Sanders, Peter R. Schofield, Thomas G. Schulze, Laura J. Scott, Alessandro Serretti, Jianxin Shi, Stanley I. Shyn, Lea Sirignano, Pamela Sklar, Olav B. Smeland, Jordan W. Smoller, Edmund J.S. Sonuga-Barke, Gianfranco Spalletta, John S. Strauss, Beata Świątkowska, Maciej Trzaskowski, Gustavo Turecki, Laura Vilar-Ribó, John B. Vincent, Henry Völzke, James T.R. Walters, Cynthia Shannon Weickert, Thomas W. Weickert, Myrna M. Weissman, Leanne M. Williams, Naomi R. Wray, Clement C. Zai, Allison E. Ashley-Koch, Jean C. Beckham, Elizabeth R. Hauser, Michael A. Hauser, Nathan A. Kimbrel, Jennifer H. Lindquist, Benjamin McMahon, David W. Oslin, Xuejun Qin, Esben Agerbo, Anders D. Børglum, Gerome Breen, Annette Erlangsen, Tõnu Esko, Joel Gelernter, David M. Hougaard, Ronald C. Kessler, Henry R. Kranzler, Qingqin S. Li, Nicholas G. Martin, Andrew M. McIntosh, Ole Mors, Merete Nordentoft, Catherine M. Olsen, David Porteous, Robert J. Ursano, Danuta Wasserman, Thomas Werge, David C. Whiteman, Cynthia M. Bulik, Hilary Coon, Ditte Demontis, Anna R. Docherty, Po-Hsiu Kuo, Cathryn M. Lewis, J. John Mann, Miguel E. Rentería, Daniel J. Smith, Eli A. Stahl, Murray B. Stein, Fabian Streit, Virginia Willour, Douglas M. Ruderfer, Manuel Mattheisen, Abdel Abdellaoui, Mark J. Adams, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Jane Hvarregaard Christensen, Toni-Kim Clarke, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Nick Craddock, Gregory E. Crawford, Gail Davies, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Valentina Escott-Price, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Josef Frank, Héléna A. Gaspar, Michael Gill, Fernando S. Goes, Scott D. Gordon, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Volker Arolt, Dorret I. Boomsma, Udo Dannlowski, E.J.C. de Geus, J. Raymond Depaulo, Enrico Domenici, Katharina Domschke, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Stefan Herms, Ian B. Hickie, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Howard, Rick Jansen, Eric Jorgenson, James A. Knowles, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Wolfgang Maier, Jonathan Marchini, Hamdi Mbarek, Christel M. Middeldorp, Evelin Mihailov, Lili Milani, Francis M. Mondimore, Grant W. Montgomery, Sara Mostafavi, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O’Reilly, Hogni Oskarsson, Caroline Hayward, Andrew C. Heath, Glyn Lewis, Pamela A.F. Madden, Patrik K. Magnusson, Andres Metspalu, Sara A. Paciga, Nancy L. Pedersen, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Wouter J. Peyrot, Danielle Posthuma, Jorge A. Quiroz, Per Qvist, John P. Rice, Brien P. Riley, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Engilbert Sigurdsson, Grant C.B. Sinnamon, Johannes H. Smit, Hreinn Stefansson, Stacy Steinberg, Jana Strohmaier, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, Vassily Trubetskoy, André G. Uitterlinden, Daniel Umbricht, Albert M. van Hemert, Alexander Viktorin, Peter M. Visscher, Yunpeng Wang, Bradley T. Webb, Roy H. Perlis, David J. Porteous, Catherine Schaefer, Kari Stefansson, Henning Tiemeier, Rudolf Uher, Patrick F. Sullivan, Kevin S. O’Connell, Brandon Coombes, Zhen Qiao, Thomas D. Als, Sigrid Børte, Alexander W. Charney, Ole Kristian Drange, Michael J. Gandal, Saskia P. Hagenaars, Masashi Ikeda, Nolan Kamitaki, Kristi Krebs, Georgia Panagiotaropoulou, Brian M. Schilder, Laura G. Sloofman, Bendik S. Winsvold, Hong-Hee Won, Liliya Abramova, Kristina Adorjan, Mariam Al Eissa, Diego Albani, Ney Alliey-Rodriguez, Verneri Antilla, Anastasia Antoniou, Ji Hyun Baek, Michael Bauer, Eva C. Beins, Sarah E. Bergen, Armin Birner, Erlend Bøen, Murielle Brum, Ben M. Brumpton, Nathalie Brunkhorst-Kanaan, William Byerley, Murray Cairns, Miquel Casas, Pablo Cervantes, Cristiana Cruceanu, Alfredo Cuellar-Barboza, Julie Cunningham, David Curtis, Piotr M. Czerski, Anders M. Dale, Nina Dalkner, Friederike S. David, Amanda L. Dobbyn, Athanassios Douzenis, Torbjørn Elvsåshagen, I. Nicol Ferrier, Alessia Fiorentino, Tatiana M. Foroud, Liz Forty, Oleksandr Frei, Nelson B. Freimer, Louise Frisén, Katrin Gade, Julie Garnham, Ian R. Gizer, Katherine Gordon-Smith, Tiffany A. Greenwood, José Guzman-Parra, Kyooseob Ha, Magnus Haraldsson, Martin Hautzinger, Urs Heilbronner, Dennis Hellgren, Peter A. Holmans, Laura Huckins, Jessica S. Johnson, Janos L. Kalman, Yoichiro Kamatani, Sarah Kittel-Schneider, Maria Koromina, Thorsten M. Kranz, Michiaki Kubo, Ralph Kupka, Steven A. Kushner, Catharina Lavebratt, Markus Leber, Heon-Jeong Lee, Shawn E. Levy, Catrin Lewis, Martin Lundberg, Sigurdur H. Magnusson, Adam Maihofer, Dolores Malaspina, Eirini Maratou, Lina Martinsson, Nathaniel W. McGregor, James D. McKay, Helena Medeiros, Vincent Millischer, Jennifer L. Moran, Derek W. Morris, Thomas W. Mühleisen, Niamh O’Brien, Claire O’Donovan, Loes M. Olde Loohuis, Lilijana Oruc, Sergi Papiol, Antonio F. Pardiñas, Amy Perry, Andrea Pfennig, Evgenia Porichi, Towfique Raj, Mark H. Rapaport, J. Raymond DePaulo, Eline J. Regeer, Fabio Rivas, Julian Roth, Panos Roussos, Fanny Senner, Sally Sharp, Paul D. Shilling, Claire Slaney, Janet L. Sobell, Maria Soler Artigas, Anne T. Spijker, Dan J. Stein, Chikashi Terao, Claudio Toma, Paul Tooney, Evangelia-Eirini Tsermpini, Marquis P. Vawter, Helmut Vedder, Simon Xi, Wei Xu, Jessica Mei Kay Yang, Allan H. Young, Hannah Young, Peter P. Zandi, Hang Zhou, null HUNT All-In Psychiatry, Gulja Babadjanova, Lena Backlund, Susanne Bengesser, Douglas H.R. Blackwood, Vaughan J. Carr, Stanley Catts, Dimitris Dikeos, Bruno Etain, Panagiotis Ferentinos, Micha Gawlik, Elliot S. Gershon, Frans Henskens, Jan Hillert, Kyung Sue Hong, Christina M. Hultman, Kristian Hveem, Nakao Iwata, Assen V. Jablensky, George Kirov, Christine Lochner, Carmel Loughland, Carol A. Mathews, Francis J. McMahon, Patricia Michie, Bryan Mowry, Benjamin M. Neale, Caroline M. Nievergelt, Ketil J. Oedegaard, Tomas Olsson, Chris Pantelis, George P. Patrinos, Eva Z. Reininghaus, Takeo Saito, Ulrich Schall, Martin Schalling, Rodney J. Scott, Eystein Stordal, Arne E. Vaaler, Eduard Vieta, Irwin D. Waldman, John-Anker Zwart, John I. Nurnberger, Arianna Di Florio, Roger A.H. Adan, Tetsuya Ando, Harald Aschauer, Jessica H. Baker, Vladimir Bencko, Andreas Birgegård, Joseph M. Boden, Ilka Boehm, Claudette Boni, Vesna Boraska Perica, Katharina Buehren, Roland Burghardt, Laura Carlberg, Matteo Cassina, Maurizio Clementi, Roger D. Cone, Philippe Courtet, James J. Crowley, Unna N. Danner, Oliver S.P. Davis, Martina de Zwaan, George Dedoussis, Daniela Degortes, Janiece E. DeSocio, Danielle M. Dick, Christian Dina, Monika Dmitrzak-Weglarz, Elisa Docampo Martinez, Laramie E. Duncan, Karin Egberts, Morten Mattingsdal, Sara McDevitt, Ingrid Meulenbelt, Nadia Micali, James Mitchell, Karen Mitchell, Palmiero Monteleone, Alessio Maria Monteleone, Melissa A. Munn-Chernoff, Benedetta Nacmias, Marie Navratilova, Ioanna Ntalla, Julie K. O’Toole, Leonid Padyukov, Aarno Palotie, Jacques Pantel, Hana Papezova, Richard Parker, John F. Pearson, Stefan Ehrlich, Geòrgia Escaramís, Thomas Espeseth, Xavier Estivill, Anne Farmer, Angela Favaro, Krista Fischer, James A.B. Floyd, Manuel Föcker, Lenka Foretova, Monica Forzan, Christopher S. Franklin, Giovanni Gambaro, Johanna Giuranna, Paola Giusti-Rodríquez, Fragiskos Gonidakis, Scott Gordon, Monica Gratacos Mayora, Sébastien Guillaume, Ken B. Hanscombe, Konstantinos Hatzikotoulas, Johannes Hebebrand, Sietske G. Helder, Anjali K. Henders, Beate Herpertz-Dahlmann, Wolfgang Herzog, Anke Hinney, L. John Horwood, Christopher Hübel, Liselotte V. Petersen, Kirstin L. Purves, Anu Raevuori, Ted Reichborn-Kjennerud, Valdo Ricca, Samuli Ripatti, Franziska Ritschel, Marion Roberts, Filip Rybakowski, Paolo Santonastaso, André Scherag, Ulrike Schmidt, Nicholas J. Schork, Alexandra Schosser, Jochen Seitz, Lenka Slachtova, P. Eline Slagboom, Margarita C.T. Slof-Op ‘t Landt, Agnieszka Slopien, Nicole Soranzo, Sandro Sorbi, Lorraine Southam, Vidar W. Steen, Laura M. Huckins, James I. Hudson, Hartmut Imgart, Hidetoshi Inoko, Vladimir Janout, Jennifer Jordan, Antonio Julià, Gursharan Kalsi, Deborah Kaminská, Jaakko Kaprio, Leila Karhunen, Andreas Karwautz, Martien J.H. Kas, Martin A. Kennedy, Anna Keski-Rahkonen, Kirsty Kiezebrink, Youl-Ri Kim, Katherine M. Kirk, Lars Klareskog, Gun Peggy S. Knudsen, Janne T. Larsen, Stephanie Le Hellard, Virpi M. Leppä, Paul Lichtenstein, Bochao Danae Lin, Astri Lundervold, Jurjen Luykx, Mario Maj, Katrin Mannik, Sara Marsal, Garret D. Stuber, Jin P. Szatkiewicz, Ioanna Tachmazidou, Elena Tenconi, Alfonso Tortorella, Federica Tozzi, Artemis Tsitsika, Marta Tyszkiewicz-Nwafor, Konstantinos Tziouvas, Annemarie A. van Elburg, Eric F. van Furth, Tracey D. Wade, Gudrun Wagner, Esther Walton, H. Erich Wichmann, Elisabeth Widen, Shuyang Yao, Eleftheria Zeggini, Stephanie Zerwas, Stephan Zipfel, Martin Jungkunz, Lydie Dietl, Cornelia E. Schwarze, Norbert Dahmen, Björn H. Schott, Arian Mobascher, Silvia Crivelli, Michelle F. Dennis, Phillip D. Harvey, Bruce W. Carter, Jennifer E. Huffman, Daniel Jacobson, Ravi Madduri, Maren K. Olsen, John Pestian, J. Michael Gaziano, Sumitra Muralidhar, Rachel Ramoni, Jean Beckham, Kyong-Mi Chang, Christopher J. O’Donnell, Philip S. Tsao, James Breeling, Grant Huang, J.P. Casas Romero, Jennifer Moser, Stacey B. Whitbourne, Jessica V. Brewer, Mihaela Aslan, Todd Connor, Dean P. Argyres, Brady Stephens, Mary T. Brophy, Donald E. Humphries, Luis E. Selva, Nhan Do, Shahpoor Shayan, Kelly Cho, Saiju Pyarajan, Elizabeth Hauser, Yan Sun, Hongyu Zhao, Peter Wilson, Rachel McArdle, Louis Dellitalia, Kristin Mattocks, John Harley, Clement J. Zablocki, Jeffrey Whittle, Frank Jacono, Salvador Gutierrez, Gretchen Gibson, Kimberly Hammer, Laurence Kaminsky, Gerardo Villareal, Scott Kinlay, Junzhe Xu, Mark Hamner, Roy Mathew, Sujata Bhushan, Pran Iruvanti, Michael Godschalk, Zuhair Ballas, Douglas Ivins, Stephen Mastorides, Jonathan Moorman, Saib Gappy, Jon Klein, Nora Ratcliffe, Hermes Florez, Olaoluwa Okusaga, Maureen Murdoch, Peruvemba Sriram, Shing Shing Yeh, Neeraj Tandon, Darshana Jhala, Samuel Aguayo, David Cohen, Satish Sharma, Suthat Liangpunsakul, Kris Ann Oursler, Mary Whooley, Sunil Ahuja, Joseph Constans, Paul Meyer, Jennifer Greco, Michael Rauchman, Richard Servatius, Melinda Gaddy, Agnes Wallbom, Timothy Morgan, Todd Stapley, Scott Sherman, George Ross, Philip Tsao, Patrick Strollo, Edward Boyko, Laurence Meyer, Samir Gupta, Mostaqul Huq, Joseph Fayad, Adriana Hung, Jack Lichy, Robin Hurley, Brooks Robey, Robert Striker, Dietl, Lydie, Schwarze, Cornelia E., Dahmen, Norbert, Schott, Björn H., Nöthen, Markus M., Ripke, Stephan, Mobascher, Arian, Rujescu, Dan, Lieb, Klaus, Roepke, Stefan, Schmahl, Christian, Bohus, Martin, Rietschel, Marcella, Crivelli, Silvia, Dennis, Michelle F., Harvey, Phillip D., Carter, Bruce W., Huffman, Jennifer E., Jacobson, Daniel, Madduri, Ravi, Olsen, Maren K., Pestian, John, Gaziano, J. Michael, Muralidhar, Sumitra, Ramoni, Rachel, Beckham, Jean, Chang, Kyong-Mi, O'Donnell, Christopher J., Tsao, Philip S., Breeling, James, Huang, Grant, Romero, J. P. Casas, Moser, Jennifer, Whitbourne, Stacey B., Brewer, Jessica V., Aslan, Mihaela, Connor, Todd, Argyres, Dean P., Stephens, Brady, Brophy, Mary T., Humphries, Donald E., Selva, Luis E., Do, Nhan, Shayan, Shahpoor, Cho, Kelly, Pyarajan, Saiju, Hauser, Elizabeth, Sun, Yan, Zhao, Hongyu, Wilson, Peter, McArdle, Rachel, Dellitalia, Louis, Mattocks, Kristin, Harley, John, Zablocki, Clement J., Whittle, Jeffrey, Jacono, Frank, Gutierrez, Salvador, Gibson, Gretchen, Hammer, Kimberly, Kaminsky, Laurence, Villareal, Gerardo, Kinlay, Scott, Xu, Junzhe, Hamner, Mark, Mathew, Roy, Bhushan, Sujata, Iruvanti, Pran, Godschalk, Michael, Ballas, Zuhair, Ivins, Douglas, Mastorides, Stephen, Moorman, Jonathan, Gappy, Saib, Klein, Jon, Ratcliffe, Nora, Florez, Hermes, Okusaga, Olaoluwa, Murdoch, Maureen, Sriram, Peruvemba, Yeh, Shing Shing, Tandon, Neeraj, Jhala, Darshana, Aguayo, Samuel, Cohen, David, Sharma, Satish, Liangpunsakul, Suthat, Oursler, Kris Ann, Whooley, Mary, Ahuja, Sunil, Constans, Joseph, Meyer, Paul, Greco, Jennifer, Rauchman, Michael, Servatius, Richard, Gaddy, Melinda, Wallbom, Agnes, Morgan, Timothy, Stapley, Todd, Sherman, Scott, Ross, George, Tsao, Philip, Strollo, Patrick, Boyko, Edward, Meyer, Laurence, Gupta, Samir, Huq, Mostaqul, Fayad, Joseph, Hung, Adriana, Lichy, Jack, Hurley, Robin, Robey, Brooks, Striker, Robert, Wray, Naomi R., Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Adams, Mark J., Agerbo, Esben, Air, Tracy M., Andlauer, Till F. M., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan T. F., Bigdeli, Tim B., Binder, Elisabeth B., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane Hvarregaard, Clarke, Toni-Kim, Coleman, Jonathan R. I., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Davies, Gail, Degenhardt, Franziska, Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Escott-Price, Valentina, Hassan Kiadeh, Farnush Farhadi, Finucane, Hilary K., Foo, Jerome C., Forstner, Andreas J., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Goes, Fernando S., Gordon, Scott D., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Yang, Jian, Zhang, Futao, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Cichon, Sven, Dannlowski, Udo, de Geus, E. J. C., DePaulo, J. Raymond, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Grove, Jakob, Hall, Lynsey S., Hansen, Christine Søholm, Hansen, Thomas F., Herms, Stefan, Hickie, Ian B., Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Howard, David M., Ising, Marcus, Jansen, Rick, Jones, Ian, Jones, Lisa A., Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Kutalik, Zoltán, Li, Yihan, Lind, Penelope A., MacIntyre, Donald J., MacKinnon, Dean F., Maier, Robert M., Maier, Wolfgang, Marchini, Jonathan, Mbarek, Hamdi, McGrath, Patrick, McGuffin, Peter, Medland, Sarah E., Mehta, Divya, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mondimore, Francis M., Montgomery, Grant W., Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nivard, Michel G., Nyholt, Dale R., O'Reilly, Paul F., Oskarsson, Hogni, Hayward, Caroline, Heath, Andrew C., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela A. F., Magnusson, Patrik K., Martin, Nicholas G., McIntosh, Andrew M., Metspalu, Andres, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Nordentoft, Merete, O'Donovan, Michael C., Paciga, Sara A., Pedersen, Nancy L., Owen, Michael J., Painter, Jodie N., Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Peterson, Roseann E., Peyrot, Wouter J., Pistis, Giorgio, Posthuma, Danielle, Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Mirza, Saira Saeed, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant C. B., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Trubetskoy, Vassily, Uitterlinden, André G., Umbricht, Daniel, Van der Auwera, Sandra, van Hemert, Albert M., Viktorin, Alexander, Visscher, Peter M., Wang, Yunpeng, Webb, Bradley T., Penninx, Brenda W. J. H., Perlis, Roy H., Porteous, David J., Potash, James B., Preisig, Martin, Schaefer, Catherine, Schulze, Thomas G., Smoller, Jordan W., Stefansson, Kari, Tiemeier, Henning, Uher, Rudolf, Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Lewis, Cathryn M., Levinson, Douglas F., Breen, Gerome, Børglum, Anders D., Sullivan, Patrick F., O'Connell, Kevin S., Coombes, Brandon, Qiao, Zhen, Als, Thomas D., Børte, Sigrid, Charney, Alexander W., Drange, Ole Kristian, Gandal, Michael J., Hagenaars, Saskia P., Ikeda, Masashi, Kamitaki, Nolan, Kim, Minsoo, Krebs, Kristi, Panagiotaropoulou, Georgia, Schilder, Brian M., Sloofman, Laura G., Winsvold, Bendik S., Won, Hong-Hee, Abramova, Liliya, Adorjan, Kristina, Al Eissa, Mariam, Albani, Diego, Alliey-Rodriguez, Ney, Anjorin, Adebayo, Antilla, Verneri, Antoniou, Anastasia, Awasthi, Swapnil, Baek, Ji Hyun, Bass, Nicholas, Bauer, Michael, Beins, Eva C., Bergen, Sarah E., Birner, Armin, Bøen, Erlend, Boks, Marco P., Bosch, Rosa, Brum, Murielle, Brumpton, Ben M., Brunkhorst-Kanaan, Nathalie, Budde, Monika, Byerley, William, Cairns, Murray, Casas, Miquel, Cervantes, Pablo, Cruceanu, Cristiana, Cuellar-Barboza, Alfredo, Cunningham, Julie, Curtis, David, Czerski, Piotr M., Dale, Anders M., Dalkner, Nina, David, Friederike S., Djurovic, Srdjan, Dobbyn, Amanda L., Douzenis, Athanassios, Elvsåshagen, Torbjørn, Ferrier, I. Nicol, Fiorentino, Alessia, Foroud, Tatiana M., Forty, Liz, Frei, Oleksandr, Freimer, Nelson B., Frisén, Louise, Gade, Katrin, Garnham, Julie, Gelernter, Joel, Gizer, Ian R., Gordon-Smith, Katherine, Greenwood, Tiffany A., Guzman-Parra, José, Ha, Kyooseob, Haraldsson, Magnus, Hautzinger, Martin, Heilbronner, Urs, Hellgren, Dennis, Holmans, Peter A., Huckins, Laura, Jamain, Stéphane, Johnson, Jessica S., Kalman, Janos L., Kamatani, Yoichiro, Kennedy, James L., Kittel-Schneider, Sarah, Kogevinas, Manolis, Koromina, Maria, Kranz, Thorsten M., Kranzler, Henry R., Kubo, Michiaki, Kupka, Ralph, Kushner, Steven A., Lavebratt, Catharina, Lawrence, Jacob, Leber, Markus, Lee, Heon-Jeong, Lee, Phil H., Levy, Shawn E., Lewis, Catrin, Liao, Calwing, Lundberg, Martin, Magnusson, Sigurdur H., Maihofer, Adam, Malaspina, Dolores, Maratou, Eirini, Martinsson, Lina, McGregor, Nathaniel W., McKay, James D., Medeiros, Helena, Millischer, Vincent, Moran, Jennifer L., Morris, Derek W., Mühleisen, Thomas W., O'Brien, Niamh, O'Donovan, Claire, Olde Loohuis, Loes M., Oruc, Lilijana, Papiol, Sergi, Pardiñas, Antonio F., Perry, Amy, Pfennig, Andrea, Porichi, Evgenia, Quested, Digby, Raj, Towfique, Rapaport, Mark H., Regeer, Eline J., Rivas, Fabio, Roth, Julian, Roussos, Panos, Ruderfer, Douglas M., Sánchez-Mora, Cristina, Senner, Fanny, Sharp, Sally, Shilling, Paul D., Sirignano, Lea, Slaney, Claire, Smeland, Olav B., Sobell, Janet L., Artigas, Maria Soler, Spijker, Anne T., Stein, Dan J., Strauss, John S., Świątkowska, Beata, Terao, Chikashi, Toma, Claudio, Tooney, Paul, Tsermpini, Evangelia-Eirini, Vawter, Marquis P., Vedder, Helmut, Walters, James T. R., Xi, Simon, Xu, Wei, Kay Yang, Jessica Mei, Young, Allan H., Young, Hannah, Zandi, Peter P., Zhou, Hang, Zillich, Lea, Adolfsson, Rolf, Agartz, Ingrid, Alda, Martin, Alfredsson, Lars, Babadjanova, Gulja, Backlund, Lena, Bellivier, Frank, Bengesser, Susanne, Berrettini, Wade H., Blackwood, Douglas H. R., Boehnke, Michael, Carr, Vaughan J., Catts, Stanley, Corvin, Aiden, Craddock, Nicholas, Dikeos, Dimitris, Etain, Bruno, Ferentinos, Panagiotis, Frye, Mark, Fullerton, Janice M., Gawlik, Micha, Gershon, Elliot S., Green, Melissa J., Grigoroiu-Serbanescu, Maria, Hauser, Joanna, Henskens, Frans, Hillert, Jan, Hong, Kyung Sue, Hultman, Christina M., Hveem, Kristian, Iwata, Nakao, Jablensky, Assen V., Kahn, René S., Kelsoe, John R., Kirov, George, Landén, Mikael, Leboyer, Marion, Lissowska, Jolanta, Lochner, Christine, Loughland, Carmel, Mathews, Carol A., Mayoral, Fermin, McElroy, Susan L., McMahon, Francis J., Melle, Ingrid, Michie, Patricia, Mitchell, Philip B., Morken, Gunnar, Mowry, Bryan, Myers, Richard M., Neale, Benjamin M., Nievergelt, Caroline M., Oedegaard, Ketil J., Olsson, Tomas, Pantelis, Chris, Pato, Carlos, Pato, Michele T., Patrinos, George P., Ramos-Quiroga, Josep Antoni, Reif, Andreas, Reininghaus, Eva Z., Ribasés, Marta, Rouleau, Guy A., Saito, Takeo, Schall, Ulrich, Schalling, Martin, Schofield, Peter R., Scott, Laura J., Scott, Rodney J., Serretti, Alessandro, Weickert, Cynthia Shannon, Stordal, Eystein, Turecki, Gustavo, Vaaler, Arne E., Vieta, Eduard, Vincent, John B., Waldman, Irwin D., Weickert, Thomas W., Zwart, John-Anker, Biernacka, Joanna M., Nurnberger, John I., Edenberg, Howard J., Stahl, Eli A., McQuillin, Andrew, Di Florio, Arianna, Ophoff, Roel A., Andreassen, Ole A., Adan, Roger A. H., Ando, Tetsuya, Aschauer, Harald, Baker, Jessica H., Bencko, Vladimir, Bergen, Andrew W., Birgegård, Andreas, Boden, Joseph M., Boehm, Ilka, Boni, Claudette, Perica, Vesna Boraska, Brandt, Harry, Buehren, Katharina, Bulik, Cynthia M., Burghardt, Roland, Carlberg, Laura, Cassina, Matteo, Clementi, Maurizio, Cone, Roger D., Courtet, Philippe, Crawford, Steven, Crow, Scott, Crowley, James J., Danner, Unna N., Davis, Oliver S. P., de Zwaan, Martina, Dedoussis, George, Degortes, Daniela, DeSocio, Janiece E., Dick, Danielle M., Dina, Christian, Dmitrzak-Weglarz, Monika, Martinez, Elisa Docampo, Duncan, Laramie E., Egberts, Karin, Marshall, Christian R., Mattingsdal, Morten, McDevitt, Sara, Meulenbelt, Ingrid, Micali, Nadia, Mitchell, James, Mitchell, Karen, Monteleone, Palmiero, Monteleone, Alessio Maria, Munn-Chernoff, Melissa A., Nacmias, Benedetta, Navratilova, Marie, Ntalla, Ioanna, Olsen, Catherine M., O'Toole, Julie K., Padyukov, Leonid, Palotie, Aarno, Pantel, Jacques, Papezova, Hana, Parker, Richard, Pearson, John F., Ehrlich, Stefan, Escaramís, Geòrgia, Espeseth, Thomas, Estivill, Xavier, Farmer, Anne, Favaro, Angela, Fernández-Aranda, Fernando, Fichter, Manfred M., Fischer, Krista, Floyd, James A. B., Föcker, Manuel, Foretova, Lenka, Forzan, Monica, Franklin, Christopher S., Gallinger, Steven, Gambaro, Giovanni, Giegling, Ina, Giuranna, Johanna, Giusti-Rodríquez, Paola, Gonidakis, Fragiskos, Gordon, Scott, Gorwood, Philip, Mayora, Monica Gratacos, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Halmi, Katherine A., Hanscombe, Ken B., Hatzikotoulas, Konstantinos, Hebebrand, Johannes, Helder, Sietske G., Henders, Anjali K., Herpertz-Dahlmann, Beate, Herzog, Wolfgang, Hinney, Anke, Horwood, L. John, Hübel, Christopher, Petersen, Liselotte V., Pinto, Dalila, Purves, Kirstin L., Raevuori, Anu, Ramoz, Nicolas, Reichborn-Kjennerud, Ted, Ricca, Valdo, Ripatti, Samuli, Ritschel, Franziska, Roberts, Marion, Rybakowski, Filip, Santonastaso, Paolo, Scherag, André, Scherer, Stephen W., Schmidt, Ulrike, Schork, Nicholas J., Schosser, Alexandra, Seitz, Jochen, Slachtova, Lenka, Slagboom, P. Eline, Slof-Op 't Landt, Margarita C. T., Slopien, Agnieszka, Soranzo, Nicole, Sorbi, Sandro, Southam, Lorraine, Steen, Vidar W., Strober, Michael, Huckins, Laura M., Hudson, James I., Imgart, Hartmut, Inoko, Hidetoshi, Janout, Vladimir, Jiménez-Murcia, Susana, Johnson, Craig, Jordan, Jennifer, Julià, Antonio, Kalsi, Gursharan, Kaminská, Deborah, Kaplan, Allan S., Kaprio, Jaakko, Karhunen, Leila, Karwautz, Andreas, Kas, Martien J. H., Kaye, Walter H., Kennedy, Martin A., Keski-Rahkonen, Anna, Kiezebrink, Kirsty, Kim, Youl-Ri, Kirk, Katherine M., Klareskog, Lars, Klump, Kelly L., Knudsen, Gun Peggy S., Larsen, Janne T., Le Hellard, Stephanie, Leppä, Virpi M., Li, Dong, Lichtenstein, Paul, Lilenfeld, Lisa, Lin, Bochao Danae, Lundervold, Astri, Luykx, Jurjen, Magistretti, Pierre J., Maj, Mario, Mannik, Katrin, Marsal, Sara, Stuber, Garret D., Szatkiewicz, Jin P., Tachmazidou, Ioanna, Tenconi, Elena, Thornton, Laura M., Tortorella, Alfonso, Tozzi, Federica, Treasure, Janet, Tsitsika, Artemis, Tyszkiewicz-Nwafor, Marta, Tziouvas, Konstantinos, van Elburg, Annemarie A., van Furth, Eric F., Wade, Tracey D., Wagner, Gudrun, Walton, Esther, Watson, Hunna J., Whiteman, David C., Wichmann, H. Erich, Widen, Elisabeth, Woodside, D. Blake, Yao, Shuyang, Yilmaz, Zeynep, Zeggini, Eleftheria, Zerwas, Stephanie, Zipfel, Stephan, Jungkunz, Martin, Mullins, N., Kang, J., Campos, A. I., Coleman, J. R. I., Edwards, A. C., Galfalvy, H., Levey, D. F., Lori, A., Shabalin, A., Starnawska, A., Su, M. -H., Watson, H. J., Adams, M., Awasthi, S., Gandal, M., Hafferty, J. D., Hishimoto, A., Kim, M., Okazaki, S., Otsuka, I., Ripke, S., Ware, E. B., Bergen, A. W., Berrettini, W. H., Bohus, M., Brandt, H., Chang, X., Chen, W. J., Chen, H. -C., Crawford, S., Crow, S., Diblasi, E., Duriez, P., Fernandez-Aranda, F., Fichter, M. M., Gallinger, S., Glatt, S. J., Gorwood, P., Guo, Y., Hakonarson, H., Halmi, K. A., Hwu, H. -G., Jain, S., Jamain, S., Jimenez-Murcia, S., Johnson, C., Kaplan, A. S., Kaye, W. H., Keel, P. K., Kennedy, J. L., Klump, K. L., Li, D., Liao, S. -C., Lieb, K., Lilenfeld, L., Liu, C. -M., Magistretti, P. J., Marshall, C. R., Mitchell, J. E., Monson, E. T., Myers, R. M., Pinto, D., Powers, A., Ramoz, N., Roepke, S., Rozanov, V., Scherer, S. W., Schmahl, C., Sokolowski, M., Strober, M., Thornton, L. M., Treasure, J., Tsuang, M. T., Witt, S. H., Woodside, D. B., Yilmaz, Z., Zillich, L., Adolfsson, R., Agartz, I., Air, T. M., Alda, M., Alfredsson, L., Andreassen, O. A., Anjorin, A., Appadurai, V., Soler Artigas, M., Van der Auwera, S., Azevedo, M. H., Bass, N., Bau, C. H. D., Baune, B. T., Bellivier, F., Berger, K., Biernacka, J. M., Bigdeli, T. B., Binder, E. B., Boehnke, M., Boks, M. P., Bosch, R., Braff, D. L., Bryant, R., Budde, M., Byrne, E. M., Cahn, W., Casas, M., Castelao, E., Cervilla, J. A., Chaumette, B., Cichon, S., Corvin, A., Craddock, N., Craig, D., Degenhardt, F., Djurovic, S., Edenberg, H. J., Fanous, A. H., Foo, J. C., Forstner, A. J., Frye, M., Fullerton, J. M., Gatt, J. M., Gejman, P. V., Giegling, I., Grabe, H. J., Green, M. J., Grevet, E. H., Grigoroiu-Serbanescu, M., Gutierrez, B., Guzman-Parra, J., Hamilton, S. P., Hamshere, M. L., Hartmann, A., Hauser, J., Heilmann-Heimbach, S., Hoffmann, P., Ising, M., Jones, I., Jones, L. A., Jonsson, L., Kahn, R. S., Kelsoe, J. R., Kendler, K. S., Kloiber, S., Koenen, K. C., Kogevinas, M., Konte, B., Krebs, M. -O., Landen, M., Lawrence, J., Leboyer, M., Lee, P. H., Levinson, D. F., Liao, C., Lissowska, J., Lucae, S., Mayoral, F., Mcelroy, S. L., Mcgrath, P., Mcguffin, P., Mcquillin, A., Medland, S. E., Mehta, D., Melle, I., Milaneschi, Y., Mitchell, P. B., Molina, E., Morken, G., Mortensen, P. B., Muller-Myhsok, B., Nievergelt, C., Nimgaonkar, V., Nothen, M. M., O'Donovan, M. C., Ophoff, R. A., Owen, M. J., Pato, C., Pato, M. T., Penninx, B. W. J. H., Pimm, J., Pistis, G., Potash, J. B., Power, R. A., Preisig, M., Quested, D., Ramos-Quiroga, J. A., Reif, A., Ribases, M., Richarte, V., Rietschel, M., Rivera, M., Roberts, A., Roberts, G., Rouleau, G. A., Rovaris, D. L., Rujescu, D., Sanchez-Mora, C., Sanders, A. R., Schofield, P. R., Schulze, T. G., Scott, L. J., Serretti, A., Shi, J., Shyn, S. I., Sirignano, L., Sklar, P., Smeland, O. B., Smoller, J. W., Sonuga-Barke, E. J. S., Spalletta, G., Strauss, J. S., Swiatkowska, B., Trzaskowski, M., Turecki, G., Vilar-Ribo, L., Vincent, J. B., Volzke, H., Walters, J. T. R., Shannon Weickert, C., Weickert, T. W., Weissman, M. M., Williams, L. M., Wray, N. R., Zai, C. C., Ashley-Koch, A. E., Beckham, J. C., Hauser, E. R., Hauser, M. A., Kimbrel, N. A., Lindquist, J. H., Mcmahon, B., Oslin, D. W., Qin, X., Mattheisen, M., Abdellaoui, A., Adams, M. J., Agerbo, E., Andlauer, T. F. M., Bacanu, S. -A., Baekvad-Hansen, M., Beekman, A. T. F., Bryois, J., Buttenschon, H. N., Bybjerg-Grauholm, J., Cai, N., Christensen, J. H., Clarke, T. -K., Colodro-Conde, L., Couvy-Duchesne, B., Crawford, G. E., Davies, G., Derks, E. M., Direk, N., Dolan, C. V., Dunn, E. C., Eley, T. C., Escott-Price, V., Hassan Kiadeh, F. F., Finucane, H. K., Frank, J., Gaspar, H. A., Gill, M., Goes, F. S., Gordon, S. D., Weinsheimer, S. M., Wellmann, J., Willemsen, G., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Boomsma, D. I., Dannlowski, U., Depaulo, J. R., Domenici, E., Domschke, K., Esko, T., Grove, J., Hall, L. S., Hansen, C. S., Hansen, T. F., Herms, S., Hickie, I. B., Homuth, G., Horn, C., Hottenga, J. -J., Hougaard, D. M., Howard, D. M., Jansen, R., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Kutalik, Z., Li, Y., Lind, P. A., Macintyre, D. J., Mackinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., Middeldorp, C. M., Mihailov, E., Milani, L., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O'Reilly, P. F., Oskarsson, H., Hayward, C., Heath, A. C., Lewis, G., Li, Q. S., Madden, P. A. F., Magnusson, P. K., Martin, N. G., Mcintosh, A. M., Metspalu, A., Mors, O., Nordentoft, M., Paciga, S. A., Pedersen, N. L., Painter, J. N., Pedersen, C. B., Pedersen, M. G., Peterson, R. E., Peyrot, W. J., Posthuma, D., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Mirza, S. S., Schoevers, R., Schulte, E. C., Shen, L., Sigurdsson, E., Sinnamon, G. C. B., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., der Auwera, S. V., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Perlis, R. H., Porteous, D. J., Schaefer, C., Stefansson, K., Tiemeier, H., Uher, R., Werge, T., Lewis, C. M., Breen, G., Borglum, A. D., Sullivan, P. F., O'Connell, K. S., Coombes, B., Qiao, Z., Als, T. D., Borte, S., Charney, A. W., Drange, O. K., Gandal, M. J., Hagenaars, S. P., Ikeda, M., Kamitaki, N., Krebs, K., Panagiotaropoulou, G., Schilder, B. M., Sloofman, L. G., Winsvold, B. S., Won, H. -H., Abramova, L., Adorjan, K., Al Eissa, M., Albani, D., Alliey-Rodriguez, N., Antilla, V., Antoniou, A., Baek, J. H., Bauer, M., Beins, E. C., Bergen, S. E., Birner, A., Boen, E., Brum, M., Brumpton, B. M., Brunkhorst-Kanaan, N., Byerley, W., Cairns, M., Cervantes, P., Cruceanu, C., Cuellar-Barboza, A., Cunningham, J., Curtis, D., Czerski, P. M., Dale, A. M., Dalkner, N., David, F. S., Dobbyn, A. L., Douzenis, A., Elvsashagen, T., Ferrier, I. N., Fiorentino, A., Foroud, T. M., Forty, L., Frei, O., Freimer, N. B., Frisen, L., Gade, K., Garnham, J., Gelernter, J., Gizer, I. R., Gordon-Smith, K., Greenwood, T. A., Ha, K., Haraldsson, M., Hautzinger, M., Heilbronner, U., Hellgren, D., Holmans, P. A., Huckins, L., Johnson, J. S., Kalman, J. L., Kamatani, Y., Kittel-Schneider, S., Koromina, M., Kranz, T. M., Kranzler, H. R., Kubo, M., Kupka, R., Kushner, S. A., Lavebratt, C., Leber, M., Lee, H. -J., Levy, S. E., Lewis, C., Lundberg, M., Magnusson, S. H., Maihofer, A., Malaspina, D., Maratou, E., Martinsson, L., Mcgregor, N. W., Mckay, J. D., Medeiros, H., Millischer, V., Moran, J. L., Morris, D. W., Muhleisen, T. W., O'Brien, N., O'Donovan, C., Olde Loohuis, L. M., Oruc, L., Papiol, S., Pardinas, A. F., Perry, A., Pfennig, A., Porichi, E., Raj, T., Rapaport, M. H., Regeer, E. J., Rivas, F., Roth, J., Roussos, P., Ruderfer, D. M., Senner, F., Sharp, S., Shilling, P. D., Slaney, C., Sobell, J. L., Artigas, M. S., Spijker, A. T., Stein, D. J., Terao, C., Toma, C., Tooney, P., Tsermpini, E. -E., Vawter, M. P., Vedder, H., Xi, S., Xu, W., Kay Yang, J. M., Young, A. H., Young, H., Zandi, P. P., Zhou, H., HUNT All-In, Psychiatry, Babadjanova, G., Backlund, L., Bengesser, S., Blackwood, D. H. R., Carr, V. J., Catts, S., Dikeos, D., Etain, B., Ferentinos, P., Gawlik, M., Gershon, E. S., Henskens, F., Hillert, J., Hong, K. S., Hultman, C. M., Hveem, K., Iwata, N., Jablensky, A. V., Kirov, G., Lochner, C., Loughland, C., Mathews, C. A., Mcmahon, F. J., Michie, P., Mowry, B., Neale, B. M., Nievergelt, C. M., Oedegaard, K. J., Olsson, T., Pantelis, C., Patrinos, G. P., Reininghaus, E. Z., Saito, T., Schall, U., Schalling, M., Scott, R. J., Weickert, C. S., Stordal, E., Vaaler, A. E., Vieta, E., Waldman, I. D., Zwart, J. -A., Nurnberger, J. I., Stahl, E. A., Di Florio, A., Adan, R. A. H., Ando, T., Aschauer, H., Baker, J. H., Bencko, V., Birgegard, A., Boden, J. M., Boehm, I., Boni, C., Perica, V. B., Buehren, K., Bulik, C. M., Burghardt, R., Carlberg, L., Cassina, M., Clementi, M., Cone, R. D., Courtet, P., Crowley, J. J., Danner, U. N., Davis, O. S. P., de Zwaan, M., Dedoussis, G., Degortes, D., Desocio, J. E., Dick, D. M., Dina, C., Dmitrzak-Weglarz, M., Martinez, E. D., Duncan, L. E., Egberts, K., Mattingsdal, M., Mcdevitt, S., Meulenbelt, I., Micali, N., Mitchell, J., Mitchell, K., Monteleone, P., Monteleone, A. M., Munn-Chernoff, M. A., Nacmias, B., Navratilova, M., Ntalla, I., Olsen, C. M., O'Toole, J. K., Padyukov, L., Palotie, A., Pantel, J., Papezova, H., Parker, R., Pearson, J. F., Ehrlich, S., Escaramis, G., Espeseth, T., Estivill, X., Farmer, A., Favaro, A., Fischer, K., Floyd, J. A. B., Focker, M., Foretova, L., Forzan, M., Franklin, C. S., Gambaro, G., Giuranna, J., Giusti-Rodriquez, P., Gonidakis, F., Gordon, S., Mayora, M. G., Guillaume, S., Hanscombe, K. B., Hatzikotoulas, K., Hebebrand, J., Helder, S. G., Henders, A. K., Herpertz-Dahlmann, B., Herzog, W., Hinney, A., Horwood, L. J., Hubel, C., Petersen, L. V., Purves, K. L., Raevuori, A., Reichborn-Kjennerud, T., Ricca, V., Ripatti, S., Ritschel, F., Roberts, M., Rybakowski, F., Santonastaso, P., Scherag, A., Schmidt, U., Schork, N. J., Schosser, A., Seitz, J., Slachtova, L., Slagboom, P. E., Slof-Op 't Landt, M. C. T., Slopien, A., Soranzo, N., Sorbi, S., Southam, L., Steen, V. W., Huckins, L. M., Hudson, J. I., Imgart, H., Inoko, H., Janout, V., Jordan, J., Julia, A., Kalsi, G., Kaminska, D., Kaprio, J., Karhunen, L., Karwautz, A., Kas, M. J. H., Kennedy, M. A., Keski-Rahkonen, A., Kiezebrink, K., Kim, Y. -R., Kirk, K. M., Klareskog, L., Knudsen, G. P. S., Larsen, J. T., Le Hellard, S., Leppa, V. M., Lichtenstein, P., Lin, B. D., Lundervold, A., Luykx, J., Maj, M., Mannik, K., Marsal, S., Stuber, G. D., Szatkiewicz, J. P., Tachmazidou, I., Tenconi, E., Tortorella, A., Tozzi, F., Tsitsika, A., Tyszkiewicz-Nwafor, M., Tziouvas, K., van Elburg, A. A., van Furth, E. F., Wade, T. D., Wagner, G., Walton, E., Whiteman, D. C., Wichmann, H. E., Widen, E., Yao, S., Zeggini, E., Zerwas, S., Zipfel, S., Jungkunz, M., Dietl, L., Schwarze, C. E., Dahmen, N., Schott, B. H., Mobascher, A., Crivelli, S., Dennis, M. F., Harvey, P. D., Carter, B. W., Huffman, J. E., Jacobson, D., Madduri, R., Olsen, M. K., Pestian, J., Gaziano, J. M., Muralidhar, S., Ramoni, R., Beckham, J., Chang, K. -M., O'Donnell, C. J., Tsao, P. S., Breeling, J., Huang, G., Romero, J. P. C., Moser, J., Whitbourne, S. B., Brewer, J. V., Aslan, M., Connor, T., Argyres, D. P., Stephens, B., Brophy, M. T., Humphries, D. E., Selva, L. E., Do, N., Shayan, S., Cho, K., Pyarajan, S., Hauser, E., Sun, Y., Zhao, H., Wilson, P., Mcardle, R., Dellitalia, L., Mattocks, K., Harley, J., Zablocki, C. J., Whittle, J., Jacono, F., Gutierrez, S., Gibson, G., Hammer, K., Kaminsky, L., Villareal, G., Kinlay, S., Xu, J., Hamner, M., Mathew, R., Bhushan, S., Iruvanti, P., Godschalk, M., Ballas, Z., Ivins, D., Mastorides, S., Moorman, J., Gappy, S., Klein, J., Ratcliffe, N., Florez, H., Okusaga, O., Murdoch, M., Sriram, P., Yeh, S. S., Tandon, N., Jhala, D., Aguayo, S., Cohen, D., Sharma, S., Liangpunsakul, S., Oursler, K. A., Whooley, M., Ahuja, S., Constans, J., Meyer, P., Greco, J., Rauchman, M., Servatius, R., Gaddy, M., Wallbom, A., Morgan, T., Stapley, T., Sherman, S., Ross, G., Tsao, P., Strollo, P., Boyko, E., Meyer, L., Gupta, S., Huq, M., Fayad, J., Hung, A., Lichy, J., Hurley, R., Robey, B., Striker, R., Erlangsen, A., Kessler, R. C., Porteous, D., Ursano, R. J., Wasserman, D., Coon, H., Demontis, D., Docherty, A. R., Kuo, P. -H., Mann, J. J., Renteria, M. E., Stein, M. B., Willour, V., Psychiatry, Biological Psychology, APH - Methodology, APH - Mental Health, APH - Health Behaviors & Chronic Diseases, AMS - Sports, AMS - Ageing & Vitality, APH - Personalized Medicine, Amsterdam Neuroscience - Complex Trait Genetics, Complex Trait Genetics, Institute for Molecular Medicine Finland, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, Genomics of Neurological and Neuropsychiatric Disorders, HUS Psychiatry, Department of Public Health, Clinicum, Nuorisopsykiatria, Faculty Common Matters (Faculty of Social Sciences), Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, Biostatistics Helsinki, Anna Keski-Rahkonen / Principal Investigator, Elisabeth Ingrid Maria Widen / Principal Investigator, Genomic Discoveries and Clinical Translation, Internal medicine, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, Mullins N., Kang J., Campos A.I., Coleman J.R.I., Edwards A.C., Galfalvy H., Levey D.F., Lori A., Shabalin A., Starnawska A., Su M.-H., Watson H.J., Adams M., Awasthi S., Gandal M., Hafferty J.D., Hishimoto A., Kim M., Okazaki S., Otsuka I., Ripke S., Ware E.B., Bergen A.W., Berrettini W.H., Bohus M., Brandt H., Chang X., Chen W.J., Chen H.-C., Crawford S., Crow S., DiBlasi E., Duriez P., Fernandez-Aranda F., Fichter M.M., Gallinger S., Glatt S.J., Gorwood P., Guo Y., Hakonarson H., Halmi K.A., Hwu H.-G., Jain S., Jamain S., Jimenez-Murcia S., Johnson C., Kaplan A.S., Kaye W.H., Keel P.K., Kennedy J.L., Klump K.L., Li D., Liao S.-C., Lieb K., Lilenfeld L., Liu C.-M., Magistretti P.J., Marshall C.R., Mitchell J.E., Monson E.T., Myers R.M., Pinto D., Powers A., Ramoz N., Roepke S., Rozanov V., Scherer S.W., Schmahl C., Sokolowski M., Strober M., Thornton L.M., Treasure J., Tsuang M.T., Witt S.H., Woodside D.B., Yilmaz Z., Zillich L., Adolfsson R., Agartz I., Air T.M., Alda M., Alfredsson L., Andreassen O.A., Anjorin A., Appadurai V., Soler Artigas M., Van der Auwera S., Azevedo M.H., Bass N., Bau C.H.D., Baune B.T., Bellivier F., Berger K., Biernacka J.M., Bigdeli T.B., Binder E.B., Boehnke M., Boks M.P., Bosch R., Braff D.L., Bryant R., Budde M., Byrne E.M., Cahn W., Casas M., Castelao E., Cervilla J.A., Chaumette B., Cichon S., Corvin A., Craddock N., Craig D., Degenhardt F., Djurovic S., Edenberg H.J., Fanous A.H., Foo J.C., Forstner A.J., Frye M., Fullerton J.M., Gatt J.M., Gejman P.V., Giegling I., Grabe H.J., Green M.J., Grevet E.H., Grigoroiu-Serbanescu M., Gutierrez B., Guzman-Parra J., Hamilton S.P., Hamshere M.L., Hartmann A., Hauser J., Heilmann-Heimbach S., Hoffmann P., Ising M., Jones I., Jones L.A., Jonsson L., Kahn R.S., Kelsoe J.R., Kendler K.S., Kloiber S., Koenen K.C., Kogevinas M., Konte B., Krebs M.-O., Landen M., Lawrence J., Leboyer M., Lee P.H., Levinson D.F., Liao C., Lissowska J., Lucae S., Mayoral F., McElroy S.L., McGrath P., McGuffin P., McQuillin A., Medland S.E., Mehta D., Melle I., Milaneschi Y., Mitchell P.B., Molina E., Morken G., Mortensen P.B., Muller-Myhsok B., Nievergelt C., Nimgaonkar V., Nothen M.M., O'Donovan M.C., Ophoff R.A., Owen M.J., Pato C., Pato M.T., Penninx B.W.J.H., Pimm J., Pistis G., Potash J.B., Power R.A., Preisig M., Quested D., Ramos-Quiroga J.A., Reif A., Ribases M., Richarte V., Rietschel M., Rivera M., Roberts A., Roberts G., Rouleau G.A., Rovaris D.L., Rujescu D., Sanchez-Mora C., Sanders A.R., Schofield P.R., Schulze T.G., Scott L.J., Serretti A., Shi J., Shyn S.I., Sirignano L., Sklar P., Smeland O.B., Smoller J.W., Sonuga-Barke E.J.S., Spalletta G., Strauss J.S., Swiatkowska B., Trzaskowski M., Turecki G., Vilar-Ribo L., Vincent J.B., Volzke H., Walters J.T.R., Shannon Weickert C., Weickert T.W., Weissman M.M., Williams L.M., Wray N.R., Zai C.C., Ashley-Koch A.E., Beckham J.C., Hauser E.R., Hauser M.A., Kimbrel N.A., Lindquist J.H., McMahon B., Oslin D.W., Qin X., Mattheisen M., Abdellaoui A., Adams M.J., Agerbo E., Andlauer T.F.M., Bacanu S.-A., Baekvad-Hansen M., Beekman A.T.F., Bryois J., Buttenschon H.N., Bybjerg-Grauholm J., Cai N., Christensen J.H., Clarke T.-K., Colodro-Conde L., Couvy-Duchesne B., Crawford G.E., Davies G., Derks E.M., Direk N., Dolan C.V., Dunn E.C., Eley T.C., Escott-Price V., Hassan Kiadeh F.F., Finucane H.K., Frank J., Gaspar H.A., Gill M., Goes F.S., Gordon S.D., Weinsheimer S.M., Wellmann J., Willemsen G., Wu Y., Xi H.S., Yang J., Zhang F., Arolt V., Boomsma D.I., Dannlowski U., de Geus E.J.C., Depaulo J.R., Domenici E., Domschke K., Esko T., Grove J., Hall L.S., Hansen C.S., Hansen T.F., Herms S., Hickie I.B., Homuth G., Horn C., Hottenga J.-J., Hougaard D.M., Howard D.M., Jansen R., Jorgenson E., Knowles J.A., Kohane I.S., Kraft J., Kretzschmar W.W., Kutalik Z., Li Y., Lind P.A., MacIntyre D.J., MacKinnon D.F., Maier R.M., Maier W., Marchini J., Mbarek H., Middeldorp C.M., Mihailov E., Milani L., Mondimore F.M., Montgomery G.W., Mostafavi S., Nauck M., Ng B., Nivard M.G., Nyholt D.R., O'Reilly P.F., Oskarsson H., Hayward C., Heath A.C., Lewis G., Li Q.S., Madden P.A.F., Magnusson P.K., Martin N.G., McIntosh A.M., Metspalu A., Mors O., Nordentoft M., Paciga S.A., Pedersen N.L., Painter J.N., Pedersen C.B., Pedersen M.G., Peterson R.E., Peyrot W.J., Posthuma D., Quiroz J.A., Qvist P., Rice J.P., Riley B.P., Mirza S.S., Schoevers R., Schulte E.C., Shen L., Sigurdsson E., Sinnamon G.C.B., Smit J.H., Smith D.J., Stefansson H., Steinberg S., Streit F., Strohmaier J., Tansey K.E., Teismann H., Teumer A., Thompson W., Thomson P.A., Thorgeirsson T.E., Traylor M., Treutlein J., Trubetskoy V., Uitterlinden A.G., Umbricht D., der Auwera S.V., van Hemert A.M., Viktorin A., Visscher P.M., Wang Y., Webb B.T., Perlis R.H., Porteous D.J., Schaefer C., Stefansson K., Tiemeier H., Uher R., Werge T., Lewis C.M., Breen G., Borglum A.D., Sullivan P.F., O'Connell K.S., Coombes B., Qiao Z., Als T.D., Borte S., Charney A.W., Drange O.K., Gandal M.J., Hagenaars S.P., Ikeda M., Kamitaki N., Krebs K., Panagiotaropoulou G., Schilder B.M., Sloofman L.G., Winsvold B.S., Won H.-H., Abramova L., Adorjan K., Al Eissa M., Albani D., Alliey-Rodriguez N., Antilla V., Antoniou A., Baek J.H., Bauer M., Beins E.C., Bergen S.E., Birner A., Boen E., Brum M., Brumpton B.M., Brunkhorst-Kanaan N., Byerley W., Cairns M., Cervantes P., Cruceanu C., Cuellar-Barboza A., Cunningham J., Curtis D., Czerski P.M., Dale A.M., Dalkner N., David F.S., Dobbyn A.L., Douzenis A., Elvsashagen T., Ferrier I.N., Fiorentino A., Foroud T.M., Forty L., Frei O., Freimer N.B., Frisen L., Gade K., Garnham J., Gelernter J., Gizer I.R., Gordon-Smith K., Greenwood T.A., Ha K., Haraldsson M., Hautzinger M., Heilbronner U., Hellgren D., Holmans P.A., Huckins L., Johnson J.S., Kalman J.L., Kamatani Y., Kittel-Schneider S., Koromina M., Kranz T.M., Kranzler H.R., Kubo M., Kupka R., Kushner S.A., Lavebratt C., Leber M., Lee H.-J., Levy S.E., Lewis C., Lundberg M., Magnusson S.H., Maihofer A., Malaspina D., Maratou E., Martinsson L., McGregor N.W., McKay J.D., Medeiros H., Millischer V., Moran J.L., Morris D.W., Muhleisen T.W., O'Brien N., O'Donovan C., Olde Loohuis L.M., Oruc L., Papiol S., Pardinas A.F., Perry A., Pfennig A., Porichi E., Raj T., Rapaport M.H., Regeer E.J., Rivas F., Roth J., Roussos P., Ruderfer D.M., Senner F., Sharp S., Shilling P.D., Slaney C., Sobell J.L., Artigas M.S., Spijker A.T., Stein D.J., Terao C., Toma C., Tooney P., Tsermpini E.-E., Vawter M.P., Vedder H., Xi S., Xu W., Kay Yang J.M., Young A.H., Young H., Zandi P.P., Zhou H., HUNT All-In Psychiatry, Babadjanova G., Backlund L., Bengesser S., Blackwood D.H.R., Carr V.J., Catts S., Dikeos D., Etain B., Ferentinos P., Gawlik M., Gershon E.S., Henskens F., Hillert J., Hong K.S., Hultman C.M., Hveem K., Iwata N., Jablensky A.V., Kirov G., Lochner C., Loughland C., Mathews C.A., McMahon F.J., Michie P., Mowry B., Neale B.M., Nievergelt C.M., Oedegaard K.J., Olsson T., Pantelis C., Patrinos G.P., Reininghaus E.Z., Saito T., Schall U., Schalling M., Scott R.J., Weickert C.S., Stordal E., Vaaler A.E., Vieta E., Waldman I.D., Zwart J.-A., Nurnberger J.I., Stahl E.A., Di Florio A., Adan R.A.H., Ando T., Aschauer H., Baker J.H., Bencko V., Birgegard A., Boden J.M., Boehm I., Boni C., Perica V.B., Buehren K., Bulik C.M., Burghardt R., Carlberg L., Cassina M., Clementi M., Cone R.D., Courtet P., Crowley J.J., Danner U.N., Davis O.S.P., de Zwaan M., Dedoussis G., Degortes D., DeSocio J.E., Dick D.M., Dina C., Dmitrzak-Weglarz M., Martinez E.D., Duncan L.E., Egberts K., Mattingsdal M., McDevitt S., Meulenbelt I., Micali N., Mitchell J., Mitchell K., Monteleone P., Monteleone A.M., Munn-Chernoff M.A., Nacmias B., Navratilova M., Ntalla I., Olsen C.M., O'Toole J.K., Padyukov L., Palotie A., Pantel J., Papezova H., Parker R., Pearson J.F., Ehrlich S., Escaramis G., Espeseth T., Estivill X., Farmer A., Favaro A., Fischer K., Floyd J.A.B., Focker M., Foretova L., Forzan M., Franklin C.S., Gambaro G., Giuranna J., Giusti-Rodriquez P., Gonidakis F., Gordon S., Mayora M.G., Guillaume S., Hanscombe K.B., Hatzikotoulas K., Hebebrand J., Helder S.G., Henders A.K., Herpertz-Dahlmann B., Herzog W., Hinney A., Horwood L.J., Hubel C., Petersen L.V., Purves K.L., Raevuori A., Reichborn-Kjennerud T., Ricca V., Ripatti S., Ritschel F., Roberts M., Rybakowski F., Santonastaso P., Scherag A., Schmidt U., Schork N.J., Schosser A., Seitz J., Slachtova L., Slagboom P.E., Slof-Op 't Landt M.C.T., Slopien A., Soranzo N., Sorbi S., Southam L., Steen V.W., Huckins L.M., Hudson J.I., Imgart H., Inoko H., Janout V., Jordan J., Julia A., Kalsi G., Kaminska D., Kaprio J., Karhunen L., Karwautz A., Kas M.J.H., Kennedy M.A., Keski-Rahkonen A., Kiezebrink K., Kim Y.-R., Kirk K.M., Klareskog L., Knudsen G.P.S., Larsen J.T., Le Hellard S., Leppa V.M., Lichtenstein P., Lin B.D., Lundervold A., Luykx J., Maj M., Mannik K., Marsal S., Stuber G.D., Szatkiewicz J.P., Tachmazidou I., Tenconi E., Tortorella A., Tozzi F., Tsitsika A., Tyszkiewicz-Nwafor M., Tziouvas K., van Elburg A.A., van Furth E.F., Wade T.D., Wagner G., Walton E., Whiteman D.C., Wichmann H.E., Widen E., Yao S., Zeggini E., Zerwas S., Zipfel S., Jungkunz M., Dietl L., Schwarze C.E., Dahmen N., Schott B.H., Mobascher A., Crivelli S., Dennis M.F., Harvey P.D., Carter B.W., Huffman J.E., Jacobson D., Madduri R., Olsen M.K., Pestian J., Gaziano J.M., Muralidhar S., Ramoni R., Beckham J., Chang K.-M., O'Donnell C.J., Tsao P.S., Breeling J., Huang G., Romero J.P.C., Moser J., Whitbourne S.B., Brewer J.V., Aslan M., Connor T., Argyres D.P., Stephens B., Brophy M.T., Humphries D.E., Selva L.E., Do N., Shayan S., Cho K., Pyarajan S., Hauser E., Sun Y., Zhao H., Wilson P., McArdle R., Dellitalia L., Mattocks K., Harley J., Zablocki C.J., Whittle J., Jacono F., Gutierrez S., Gibson G., Hammer K., Kaminsky L., Villareal G., Kinlay S., Xu J., Hamner M., Mathew R., Bhushan S., Iruvanti P., Godschalk M., Ballas Z., Ivins D., Mastorides S., Moorman J., Gappy S., Klein J., Ratcliffe N., Florez H., Okusaga O., Murdoch M., Sriram P., Yeh S.S., Tandon N., Jhala D., Aguayo S., Cohen D., Sharma S., Liangpunsakul S., Oursler K.A., Whooley M., Ahuja S., Constans J., Meyer P., Greco J., Rauchman M., Servatius R., Gaddy M., Wallbom A., Morgan T., Stapley T., Sherman S., Ross G., Tsao P., Strollo P., Boyko E., Meyer L., Gupta S., Huq M., Fayad J., Hung A., Lichy J., Hurley R., Robey B., Striker R., Erlangsen A., Kessler R.C., Porteous D., Ursano R.J., Wasserman D., Coon H., Demontis D., Docherty A.R., Kuo P.-H., Mann J.J., Renteria M.E., Stein M.B., and Willour V.
Subjects: LD SCORE REGRESSION, Genome-wide association study, Suicide, Attempted, 3124 Neurology and psychiatry, 0302 clinical medicine, Risk Factors, Insomnia, Suicide attempt, GWAS, Suïcidi, Depression (differential diagnoses), Cause of death, Psychiatry, 0303 health sciences, Factors de risc en les malalties, Mental Disorders, Genetic Correlation, Genome-wide Association Study, Pleiotropy, Polygenicity, Suicide, Suicide Attempt, DEPRESSION, 3. Good health, Genetic correlation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Depressive Disorder, Major, Mental illness, Cohort, SEX, medicine.symptom, Human, medicine.medical_specialty, Risk factors in diseases, BF, Locus (genetics), BEHAVIORS, Psykiatri, EVENTS, 03 medical and health sciences, SDG 3 - Good Health and Well-being, medicine, ddc:610, GENOME-WIDE ASSOCIATION, IDEATION, Socioeconomic status, METAANALYSIS, Biological Psychiatry, 030304 developmental biology, business.industry, Risk Factor, Genetic architecture, THOUGHTS, RC0321, business, Malalties mentals, 030217 neurology & neurosurgery
Abstract: Statistical analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org) hosted by SURFsara and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu), which is supported by the Office of Research Infrastructure of the National Institutes of Health (Grant Nos. S10OD018522 and S10OD026880). This work was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN. This work was funded by the National Institutes of Health (Grant Nos. R01MH116269 and R01MH121455 [to DMR]), NIGMS of the National Institutes of Health (Grant No. T32GM007347 [to JK]), and the Brain & Behavior Research Foundation (NARSAD Young Investigator Award No. 29551 [to NM])., BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders., Office of Research Infrastructure of the National Institutes of Health S10OD018522 S10OD026880, United States Department of Health & Human Services, National Institutes of Health (NIH) - USA R01MH116269 R01MH121455, NIH National Institute of General Medical Sciences (NIGMS) T32GM007347 NARSAD 29551
Published: 2022

12. Genome‐wide association study of shared liability to anxiety disorders in Army STARRS

Author: Murray B. Stein, Silviu-Alin Bacanu, Feng He, Sonia Jain, Robert J. Ursano, Chia-Yen Chen, Brad Verhulst, Ronald C. Kessler, Jordan W. Smoller, Joel Gelernter, John M. Hettema, and Chris Chatzinakos
Subjects: Adult, Male, Risk, Databases, Factual, Genotype, Genome-wide association study, Single-nucleotide polymorphism, Anxiety, Polymorphism, Single Nucleotide, Article, Young Adult, Cellular and Molecular Neuroscience, Surveys and Questionnaires, medicine, Humans, SNP, Genetic Predisposition to Disease, Genetics (clinical), Genetic association, business.industry, Panic disorder, Resilience, Psychological, medicine.disease, Anxiety Disorders, Comorbidity, United States, Psychiatry and Mental health, Military Personnel, Phenotype, Female, medicine.symptom, business, Anxiety disorder, Genome-Wide Association Study, Clinical psychology
Abstract: Anxiety disorders (ANX), namely generalized anxiety, panic disorder, and phobias, are common, etiologically complex syndromes that show increasing prevalence and comorbidity throughout adolescence and beyond. Few genome-wide association studies (GWAS) examining ANX risk have been published and almost exclusively in individuals of European ancestry. In this study, we phenotyped participants from the Army Study To Assess Risk and Resilience in Servicemembers (STARRS) to approximate DSM-based ANX diagnoses. We factor-analyzed those to create a single dimensional anxiety score for each subject. GWAS were conducted using that score within each of three ancestral groups (EUR, AFR, LAT) and then meta-analyzed across ancestries (N(Total)=16,510). We sought to (i) replicate prior ANX GWAS findings in ANGST; (ii) determine whether results extended to other ancestry groups; and (iii) meta-analyze with ANGST for increased power to identify novel susceptibility loci. No reliable genome-wide significant SNP associations were detected in STARRS. However, SNPs within the CAMKMT gene located in region 2p21 associated with shared ANX risk in ANGST were replicated in EUR soldiers but not other ancestry groups. Combining EUR STARRS and ANGST (N=28,950) yielded a more robust 2p21 association signal (p=9.08×10(−11)). Gene-based analyses supported three genes within 2p21 and LBX1 on chromosome 10. More powerful ANX genetic studies will be required to identify further loci.
Published: 2019

13. Transcriptome-based polygenic score links depression-related corticolimbic gene expression changes to sex-specific brain morphology and depression risk

Author: Amy Miles, Martin Preisig, Yuliya S. Nikolova, Jianxin Shi, Mark Adams, Fernanda Caroline dos Santos, Glyn Lewis, Rudolf Uher, Lisa Jones, Brenda W.J.H. Penninx, Etienne Sibille, Roy H. Perlis, Cathryn M. Lewis, Andrew M. McIntosh, James B. Potash, Myrna M. Weissman, Ahmad R. Hariri, Bernhard T. Baune, Jordan W. Smoller, Miguel E. Rentería, Dorret I. Boomsma, Giorgio Pistis, Enda M. Byrne, Steven P. Hamilton, Douglas F. Levinson, Enrique Castelao, Ian Jones, K Oliver Schubert, Biological Psychology, APH - Mental Health, APH - Methodology, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, and APH - Digital Health
Subjects: Oncology, Male, medicine.medical_specialty, Multifactorial Inheritance, DISORDERS, Neurogenetics, Genome-wide association study, Article, Young Adult, SDG 3 - Good Health and Well-being, DSM-IV, Internal medicine, Medicine, Humans, Genetic Predisposition to Disease, Young adult, Gyrification, Depression (differential diagnoses), Pharmacology, Depressive Disorder, Major, Depression, business.industry, Brain morphometry, Brain, Depression/genetics, Human brain, ASSOCIATION, medicine.disease, Brain/diagnostic imaging, AMYGDALA, Psychiatry and Mental health, medicine.anatomical_structure, ONSET, Major depressive disorder, Female, business, Transcriptome, Depressive Disorder, Major/genetics
Abstract: Studies in post-mortem human brain tissue have associated major depressive disorder (MDD) with cortical transcriptomic changes, whose potential in vivo impact remains unexplored. To address this translational gap, we recently developed a transcriptome-based polygenic risk score (T-PRS) based on common functional variants capturing ‘depression-like’ shifts in cortical gene expression. Here, we used a non-clinical sample of young adults (n = 482, Duke Neurogenetics Study: 53% women; aged 19.8 ± 1.2 years) to map T-PRS onto brain morphology measures, including Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index, as well as broad MDD risk, indexed by self-reported family history of depression. We conducted side-by-side comparisons with a PRS independently derived from a Psychiatric Genomics Consortium (PGC) MDD GWAS (PGC-PRS), and sought to link T-PRS with diagnosis and symptom severity directly in PGC-MDD participants (n = 29,340, 59% women; 12,923 MDD cases, 16,417 controls). T-PRS was associated with smaller amygdala volume in women (t = −3.478, p = 0.001) and lower prefrontal gyrification across sexes. In men, T-PRS was associated with hypergyrification in temporal and occipital regions. Prefrontal hypogyrification mediated a male-specific indirect link between T-PRS and familial depression (b = 0.005, p = 0.029). PGC-PRS was similarly associated with lower amygdala volume and cortical gyrification; however, both effects were male-specific and hypogyrification emerged in distinct parietal and temporo-occipital regions, unassociated with familial depression. In PGC-MDD, T-PRS did not predict diagnosis (OR = 1.007, 95% CI = [0.997–1.018]) but correlated with symptom severity in men (rho = 0.175, p = 7.957 × 10−4) in one cohort (N = 762, 48% men). Depression-like shifts in cortical gene expression have sex-specific effects on brain morphology and may contribute to broad depression vulnerability in men.
Published: 2021

14. Identifying high-risk comorbidities of short and long-term opioid prescription use

Author: Jordan W. Smoller, Travis T. Mallard, Peter Straub, Lea K. Davis, Daniel B. Rocha, Annika Faucon, PsycheMERGE Substance Use Disorder Workgroup, Melissa N Poulsen, Hyunjoon Lee, Maria Niarchou, Richard D. Urman, Mariela V Jennings, Sandra Sanchez-Roige, Vanessa Troiani, Yirui Hu, Richard C. Crist, Colin G. Walsh, Sevim B Bianchi, Brandon J. Coombes, and Rachel L. Kember
Subjects: medicine.medical_specialty, biology, business.industry, biology.organism_classification, medicine.disease, Comorbidity, Schizophrenia, Internal medicine, medicine, Anxiety, Cannabis, Bipolar disorder, Diagnosis code, medicine.symptom, Medical prescription, business, Depression (differential diagnoses)
Abstract: BackgroundElectronic health records (EHR) are useful tools for understanding complex medical phenotypes, but they have been underutilized for opioid use disorders (OUD). Patterns of prescription opioid use might provide an objective measure of OUD risk.MethodsWe extracted data for over 2.6 million patients across three health registries (Vanderbilt University Medical Center, Mass General Brigham, Geisinger) between 2005 and 2018. We defined three groups based on levels of opioid exposure: No Prescription, Minimal Exposure (2 prescriptions within 90 days at least once, but never 3 prescriptions ResultsThe prevalence of substance (alcohol, tobacco, cannabis) use disorders was higher in patients with OUD and Chronic Exposure than those with No Prescription or Minimal Exposure. Patients in the OUD and Chronic Exposure groups had more psychiatric (anxiety, depression, schizophrenia, bipolar disorder) and medical comorbidities (pain, hepatitis C, HIV) than those in the Minimal Exposure group. Notably, patients in the Minimal Exposure group had different comorbidity profiles (higher rates of substance use and psychiatric disorders, more pain conditions) than those in the Unscreened or No Prescription groups, highlighting the value of including opioid exposure in studies of OUD.ConclusionsLong-term opioid prescription use may serve as an additional tool to characterize OUD risk.
Published: 2021

15. Cortical and subcortical brain structure in generalized anxiety disorder

Author: Paolo Brambilla, Tali M. Ball, Dan J. Stein, Courtney A. Filippi, Kathryn E. Werwath, Pedro Mario Pan, Heidi K. Schroeder, Hannah Zwiebel, Andrea Parolin Jackowski, Jared A. Nielsen, Savannah N. Gosnell, Hans J. Grabe, Christian Grillon, Paul M. Thompson, Gabrielle F. Freitag, Murray B. Stein, Karina S. Blair, Narcís Cardoner, Neda Jahanshad, Ana Munjiza Jovanovic, Cristina Ottaviani, Massimo Filippi, André Zugman, Katharina Wittfeld, Antonia N. Kaczkurkin, Camilla Cividini, Hugo D. Critchley, Nynke A. Groenewold, Elise M. Cardinale, Moji Aghajani, Bianca A.V. Alberton, Michael T. Perino, Anderson M. Winkler, Ellen Leibenluft, Sophia I. Thomopoulos, Mohammed R. Milad, Kevin Hilbert, Matteo Mancini, Randy L. Buckner, Henry Völzke, Robin Bülow, Carmen Andreescu, Milutin Kostić, Raquel E. Gur, Benson Mwangi, Daniel Porta-Casteràs, Michael J. Myers, Federica Agosta, Thomas Straube, Giovana Zunta-Soares, Gretchen J. Diefenbach, Martin P. Paulus, Erica Tamburo, Brenda E. Benson, Elena Makovac, Grace V. Ringlein, Andrea L. Gold, David Hofmann, Mon-Ju Wu, Jeffrey R. Strawn, Janna Marie Bas-Hoogendam, Dick J. Veltman, Eleonora Maggioni, Sandra Van der Auwera, Gregory A. Fonzo, Ramiro Salas, Giovanni Abrahão Salum, Daniel S. Pine, Gisele Gus Manfro, Bart Larsen, Monique Ernst, Nic J.A. van der Wee, Helena van Nieuwenhuizen, Mira Z. Hammoud, Ruben C. Gur, Katie L. Burkhouse, Chad M. Sylvester, Rachel Berta, Elisa Canu, Jair C. Soares, Theodore D. Satterthwaite, Qiongru Yu, Frances Meeten, Ulrike Lueken, Jordan W. Smoller, Michal Assaf, Lilianne R. Mujica-Parodi, K. Luan Phan, Jennifer Harper, Nicholas L. Balderston, James R. Blair, Anita Harrewijn, Rebecca B. Price, Katja Beesdo-Baum, Psychiatry, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Anatomy and neurosciences, Amsterdam Neuroscience - Brain Imaging, Harrewijn, A., Cardinale, E. M., Groenewold, N. A., Bas-Hoogendam, J. M., Aghajani, M., Hilbert, K., Cardoner, N., Porta-Casteras, D., Gosnell, S., Salas, R., Jackowski, A. P., Pan, P. M., Salum, G. A., Blair, K. S., Blair, J. R., Hammoud, M. Z., Milad, M. R., Burkhouse, K. L., Phan, K. L., Schroeder, H. K., Strawn, J. R., Beesdo-Baum, K., Jahanshad, N., Thomopoulos, S. I., Buckner, R., Nielsen, J. A., Smoller, J. W., Soares, J. C., Mwangi, B., Wu, M. -J., Zunta-Soares, G. B., Assaf, M., Diefenbach, G. J., Brambilla, P., Maggioni, E., Hofmann, D., Straube, T., Andreescu, C., Berta, R., Tamburo, E., Price, R. B., Manfro, G. G., Agosta, F., Canu, E., Cividini, C., Filippi, M., Kostic, M., Munjiza Jovanovic, A., Alberton, B. A. V., Benson, B., Freitag, G. F., Filippi, C. A., Gold, A. L., Leibenluft, E., Ringlein, G. V., Werwath, K. E., Zwiebel, H., Zugman, A., Grabe, H. J., Van der Auwera, S., Wittfeld, K., Volzke, H., Bulow, R., Balderston, N. L., Ernst, M., Grillon, C., Mujica-Parodi, L. R., van Nieuwenhuizen, H., Critchley, H. D., Makovac, E., Mancini, M., Meeten, F., Ottaviani, C., Ball, T. M., Fonzo, G. A., Paulus, M. P., Stein, M. B., Gur, R. E., Gur, R. C., Kaczkurkin, A. N., Larsen, B., Satterthwaite, T. D., Harper, J., Myers, M., Perino, M. T., Sylvester, C. M., Yu, Q., Lueken, U., Veltman, D. J., Thompson, P. M., Stein, D. J., Van der Wee, N. J. A., Winkler, A. M., and Pine, D. S.
Subjects: Adult, Male, medicine.medical_specialty, endocrine system, Generalized anxiety disorder, Neurosciences. Biological psychiatry. Neuropsychiatry, Anxiety, Audiology, Article, Structural magnetic resonance imaging, Cellular and Molecular Neuroscience, Secondary analysis, medicine, Psychology, Humans, ddc:610, Cortical surface, generalized anxiety disorder, structural brain imaging, cortical thickness, Child, diagnostic imaging [Brain], Biological Psychiatry, Medication use, diagnostic imaging [Anxiety Disorders], medicine.diagnostic_test, business.industry, Brain, Small sample, Magnetic resonance imaging, medicine.disease, Magnetic Resonance Imaging, Anxiety Disorders, Psychiatry and Mental health, multicentric network, Female, medicine.symptom, business, RC321-571, Neuroscience
Abstract: The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5–90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.
Published: 2021

16. Cross-Disorder Genomics Data Analysis Elucidates a Shared Genetic Basis Between Major Depression and Osteoarthritis Pain

Author: Sophie Barowsky, Jae-Yoon Jung, Nicholas Nesbit, Micah Silberstein, Maurizio Fava, Marco L. Loggia, Jordan W. Smoller, and Phil H. Lee
Subjects: business.industry, Genomics, cross-disorder GWAS, Osteoarthritis, QH426-470, mechanosensory behavior, Affect (psychology), Bioinformatics, medicine.disease, Comorbidity, osteoarthritis, comorbidity, Pleiotropy, pleiotropy, Sensation, Mendelian randomization, Genetics, Molecular Medicine, Medicine, pain, major depression, business, Genetics (clinical), Depression (differential diagnoses), Original Research
Abstract: Osteoarthritis (OA) and major depression (MD) are two debilitating disorders that frequently co-occur and affect millions of the elderly each year. Despite the greater symptom severity, poorer clinical outcomes, and increased mortality of the comorbid conditions, we have a limited understanding of their etiologic relationships. In this study, we conducted the first cross-disorder investigations of OA and MD, using genome-wide association data representing over 247K cases and 475K controls. Along with significant positive genome-wide genetic correlations (rg = 0.299 ± 0.026, p = 9.10 × 10–31), Mendelian randomization (MR) analysis identified a bidirectional causal effect between OA and MD (βOA→MD = 0.09, SE = 0.02, z-score p-value < 1.02 × 10–5; βMD→OA = 0.19, SE = 0.026, p < 2.67 × 10–13), indicating genetic variants affecting OA risk are, in part, shared with those influencing MD risk. Cross-disorder meta-analysis of OA and MD identified 56 genomic risk loci (Pmeta ≤ 5 × 10–8), which show heightened expression of the associated genes in the brain and pituitary. Gene-set enrichment analysis highlighted “mechanosensory behavior” genes (GO:0007638; Pgene_set = 2.45 × 10–8) as potential biological mechanisms that simultaneously increase susceptibility to these mental and physical health conditions. Taken together, these findings show that OA and MD share common genetic risk mechanisms, one of which centers on the neural response to the sensation of mechanical stimulus. Further investigation is warranted to elaborate the etiologic mechanisms of the pleiotropic risk genes, as well as to develop early intervention and integrative clinical care of these serious conditions that disproportionally affect the aging population.
Published: 2021

17. Validation of a Trans-Ancestry Polygenic Risk Score for Type 2 Diabetes in Diverse Populations

Author: Atlas Khan, Emma Perez, Nita A. Limdi, Miriam S. Udler, Krzysztof Kiryluk, Barbara Benoit, James J. Cimino, James B. Meigs, Matthew S. Lebo, Vinodh Srinivasasainagendra, Chia-Yen Chen, Scott T. Weiss, Renuka Narayan, Christoph Lange, Bethany Etheridge, Elizabeth W. Karlson, Tian Ge, Maggie C.Y. Ng, Mark J. O’Connor, Shawn N. Murphy, Nicole D. Armstrong, Yen-Feng Lin, Yen-Chen Anne Feng, Brittney H. Davis, Aaron Leong, Hailiang Huang, Hemant K. Tiwari, Karmel W. Choi, Maria I. Stamou, Vivian S. Gainer, Marguerite R. Irvin, Jordan W. Smoller, Amit Patki, and Ayme D. Miles
Subjects: African american, endocrine system diseases, business.industry, nutritional and metabolic diseases, Genome-wide association study, Type 2 diabetes, medicine.disease, Biobank, Health care, Medicine, Polygenic risk score, business, Clinical risk factor, Demography, Genetic association
Abstract: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for an equitable deployment of PRS to clinical practice that benefits global populations. Here we integrate T2D GWAS in European, African American and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and evaluate the PRS in the multi-ethnic eMERGE study, four African American cohorts, and the Taiwan Biobank. The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined, and the top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5 fold of increase in T2D risk, suggesting the potential of using the trans-ancestry PRS as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.
Published: 2021

18. Predictive Structured-Unstructured Interactions in EHR Models: A Case Study of Suicide Prediction

Author: Yuval Barak-Corren, Ben Y. Reis, Emily M. Madsen, Matthew K. Nock, Jordan W. Smoller, I. Bayramli, and Victor Castro
Subjects: Computer science, business.industry, Unstructured data, Machine learning, computer.software_genre, Data type, Random forest, Naive Bayes classifier, Feature (machine learning), Artificial intelligence, Suicide Risk, business, computer, Clinical risk factor, Predictive modelling
Abstract: Clinical risk prediction models powered by electronic health records (EHRs) are becoming increasingly widespread in clinical practice. With suicide-related mortality rates rising in recent years, it is becoming increasingly urgent to understand, predict, and prevent suicidal behavior. Here, we compare the predictive value of structured and unstructured EHR data for predicting suicide risk. We find that Naive Bayes Classifier (NBC) and Random Forest (RF) models trained on structured EHR data perform better than those based on unstructured EHR data. An NBC model trained on both structured and unstructured data yields similar performance (AUC = 0.743) to an NBC model trained on structured data alone (0.742, p = 0.668), while an RF model trained on both data types yields significantly better results (AUC = 0.903) than an RF model trained on structured data alone (0.887, p
Published: 2021

19. Generalizability of Polygenic Risk Scores for Breast Cancer Among Women With European, African, and Latinx Ancestry

Author: Eric B. Larson, Stephanie M. Fullerton, Ozan Dikilitas, Nur Zeinomar, Alexander G. Bick, Paul K. Crane, George Hripcsak, Robb Rowley, Krzysztof Kiryluk, Teri A. Manolio, Chunhua Weng, Gail P. Jarvik, Atlas Khan, Georgia L. Wiesner, Mary Beth Terry, Jordan W. Smoller, Ali G. Gharavi, Katherine D. Crew, Ning Shang, Ann E. Justice, Cong Liu, Alanna Kulchak Rahm, Wendy K. Chung, and David Fasel
Subjects: Linkage disequilibrium, Black People, Information Storage and Retrieval, Breast Neoplasms, Logistic regression, Linkage Disequilibrium, White People, Breast cancer, Gene Frequency, Risk Factors, Genotype, Odds Ratio, Medicine, Electronic Health Records, Humans, Generalizability theory, Genetic Predisposition to Disease, business.industry, Medical record, General Medicine, Odds ratio, Genomics, Hispanic or Latino, Middle Aged, medicine.disease, Logistic Models, Phenotype, Female, business, Algorithms, Cohort study, Demography
Abstract: Importance Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown. Objective To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry. Design, Setting, and Participants This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39 591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm. Main Outcomes and Measures Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components. Results This study included 39 591 women: 33 594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations. Conclusions and Relevance This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.
Published: 2021

20. Initial Antidepressant Choice by Non-Psychiatrists: Learning from Large-scale Electronic Health Records

Author: Jordan W. Smoller, Yi-Han Sheu, Deborah Blacker, Colin Magdamo, and Matthew J. Miller
Subjects: Bupropion, medicine.medical_specialty, business.industry, Mirtazapine, Odds ratio, Confidence interval, Internal medicine, Medicine, Antidepressant, Medical prescription, business, Reuptake inhibitor, medicine.drug, Multinomial logistic regression
Abstract: IntroductionPharmacological treatment of depression mostly occurs in non-psychiatric settings, but factors that determine the initial choice of antidepressant treatment in these settings are not well-understood. This study models how non-psychiatrists choose among four antidepressant classes at first prescription (selective serotonin reuptake inhibitors [SSRI], bupropion, mirtazapine, or serotonin-norepinephrine reuptake inhibitors [SNRI]), by analyzing electronic health record (EHR) data.MethodsEHR data were from the Mass General Brigham Healthcare System (Boston, Massachusetts, USA) for the period from 1990 to 2018. From a literature search and expert consultation, we selected 64 variables that may be associated with antidepressant choice. Patients who participated in the study were aged 18 to 65 at the time of first antidepressant prescription with a co-occurring International Classification of Diseases (ICD) code for a depressive disorder. Multinomial logistic regression with main effect terms for all 64 variables was used to model the choice of antidepressant. Using SSRI as the reference class, odds ratios, 95% confidence intervals (CI), and likelihood ratio-based p-values for each variable were reported. We used a false discovery rate (FDR) with the Benjamini–Hochberg procedure to correct for multiple comparisons.FindingsA total of 47,107 patients were included after application of inclusion/exclusion criteria. We observed significant associations for 36 of 64 variables after multiple comparison corrections. Many of these associations suggested that antidepressants’ known pharmacological properties/actions guided choice. For example, there was a decreased likelihood of bupropion prescription among patients with epilepsy (adjusted OR 0.41, 95% CI: 0.33–0.51, p < 0.001), an increased likelihood of mirtazapine prescription among patients with insomnia (adjusted OR 1.58, 95% CI: 1.39–1.80, p < 0.001), and an increased likelihood of SNRI prescription among patients with pain (adjusted OR 1.22, 95% CI: 1.11–1.34, p = 0.001).InterpretationNon-psychiatrists’ selection of antidepressant class appears to be guided by clinically relevant pharmacological properties, indications, and contraindications, suggesting that broadly speaking they choose antidepressants based on meaningful differences among medication classes.
Published: 2021

21. Hypertension prevalence in the All of Us Research Program among groups traditionally underrepresented in medical research

Author: Paulette D, Chandler, Cheryl R, Clark, Guohai, Zhou, Nyia L, Noel, Confidence, Achilike, Lizette, Mendez, Andrea H, Ramirez, Roxana, Loperena-Cortes, Kelsey, Mayo, Elizabeth, Cohn, Lucila, Ohno-Machado, Eric, Boerwinkle, Mine, Cicek, Jun, Qian, Sheri, Schully, Francis, Ratsimbazafy, Stephen, Mockrin, Kelly, Gebo, Julien J, Dedier, Shawn N, Murphy, Jordan W, Smoller, Elizabeth W, Karlson, and Brian, Ahmedani
Subjects: Male, Biomedical Research, 030204 cardiovascular system & hematology, Cardiovascular, All of Us Research Program Investigators, 0302 clinical medicine, Prevalence, 030212 general & internal medicine, Aetiology, Minority Groups, education.field_of_study, Multidisciplinary, Middle Aged, Hypertension, Cohort, Medicine, Female, Adult, medicine.medical_specialty, Adolescent, National Health and Nutrition Examination Survey, Science, Population, Cardiology, MEDLINE, Article, Young Adult, 03 medical and health sciences, Clinical Research, medicine, Humans, cardiovascular diseases, education, SNOMED CT, business.industry, Prevention, Public health, Health care, Precision medicine, United States, Computational biology and bioinformatics, Good Health and Well Being, Blood pressure, Risk factors, Family medicine, business, 2.4 Surveillance and distribution
Abstract: The All of Us Research Program was designed to enable broad-based precision medicine research in a cohort of unprecedented scale and diversity. Hypertension (HTN) is a major public health concern. The validity of HTN data and definition of hypertension cases in the All of Us (AoU) Research Program for use in rule-based algorithms is unknown. In this cross-sectional, population-based study, we compare HTN prevalence in the AoU Research Program to HTN prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES). We used AoU baseline data from patient (age ≥ 18) measurements (PM), surveys, and electronic health record (EHR) blood pressure measurements. We retrospectively examined the prevalence of HTN in the EHR cohort using Systemized Nomenclature of Medicine (SNOMED) codes and blood pressure medications recorded in the EHR. We defined HTN as the participant having at least 2 HTN diagnosis/billing codes on separate dates in the EHR data AND at least one HTN medication. We calculated an age-standardized HTN prevalence according to the age distribution of the U.S. Census, using 3 groups (18–39, 40–59, and ≥ 60). Among the 185,770 participants enrolled in the AoU Cohort (mean age at enrollment = 51.2 years) available in a Researcher Workbench as of October 2019, EHR data was available for at least one SNOMED code from 112,805 participants, medications for 104,230 participants, and 103,490 participants had both medication and SNOMED data. The total number of persons with SNOMED codes on at least two distinct dates and at least one antihypertensive medication was 33,310 for a crude prevalence of HTN of 32.2%. AoU age-adjusted HTN prevalence was 27.9% using 3 groups compared to 29.6% in NHANES. The AoU cohort is a growing source of diverse longitudinal data to study hypertension nationwide and develop precision rule-based algorithms for use in hypertension treatment and prevention research. The prevalence of hypertension in this cohort is similar to that in prior population-based surveys.
Published: 2021

22. Temporally-Informed Random Forests for Suicide Risk Prediction

Author: E. Masden, Y. Barak-Corrren, Matthew K. Nock, I. Bayramli, Jordan W. Smoller, Victor Castro, and Ben Y. Reis
Subjects: business.industry, Computer science, Patient data, Machine learning, computer.software_genre, Random forest, Naive Bayes classifier, Tree (data structure), Artificial intelligence, Sensitivity (control systems), business, Baseline (configuration management), Suicide Risk, computer, Temporal information
Abstract: BackgroundSuicide is one of the leading causes of death worldwide, yet clinicians find it difficult to reliably identify individuals at high risk for suicide. Algorithmic approaches for suicide risk detection have been developed in recent years, mostly based on data from electronics health records (EHRs). These models typically do not optimally exploit the valuable temporal information inherent in these longitudinal data.MethodsWe propose a temporally enhanced variant of the Random Forest model - Omni-Temporal Balanced Random Forests (OTBRFs) - that incorporates temporal information in every tree within the forest. We develop and validate this model using longitudinal EHRs and clinician notes from the Mass General Brigham Health System recorded between 1998 and 2018, and compare its performance to a baseline Naive Bayes Classifier and two standard versions of Balanced Random Forests.ResultsTemporal variables were found to be associated with suicide risk. RF models were more accurate than Naive Bayesian classifiers at predicting suicide risk in advance (AUC=0.824 vs. 0.754 respectively). The OT-BRF model performed best among all RF approaches (0.339 sensitivity at 95% specificity), compared to 0.290 and 0.286 for the other two RF models. Temporal variables were assigned high importance by the models that incorporated them.DiscussionWe demonstrate that temporal variables have an important role to play in suicide risk detection, and that requiring their inclusion in all random forest trees leads to increased predictive performance. Integrating temporal information into risk prediction models helps the models interpret patient data in temporal context, improving predictive performance.
Published: 2021

23. Implementing machine learning algorithms for suicide risk prediction in clinical practice: A focus group study

Author: Kate H. Bentley, Kelly L. Zuromski, Emily M. Madsen, Matthew K. Nock, Jordan W. Smoller, Ben Y. Reis, Lee H, Kessler D, Castro, and Rebecca G. Fortgang
Subjects: Clinical Practice, Text mining, business.industry, Computer science, Artificial intelligence, Suicide Risk, Machine learning, computer.software_genre, business, Focus group, computer
Abstract: Background: Interest in developing machine learning algorithms that use electronic health record data to predict patients’ risk of suicidal behavior has recently proliferated. Whether and how such models might be implemented and useful in clinical practice, however, remains unknown. In order to ultimately make automated suicide risk prediction algorithms useful in practice, and thus better prevent patient suicides, it is critical to partner with key stakeholders (including the frontline providers who will be using such tools) at each stage of the implementation process.Objective: The aim of this focus group study was to inform ongoing and future efforts to deploy suicide risk prediction models in clinical practice. The specific goals were to better understand hospital providers’ current practices for assessing and managing suicide risk; determine providers’ perspectives on using automated suicide risk prediction algorithms; and identify barriers, facilitators, recommendations, and factors to consider for initiatives in this area. Methods: We conducted 10 two-hour focus groups with a total of 40 providers from psychiatry, internal medicine and primary care, emergency medicine, and obstetrics and gynecology departments within an urban academic medical center. Audio recordings of open-ended group discussions were transcribed and coded for relevant and recurrent themes by two independent study staff members. All coded text was reviewed and discrepancies resolved in consensus meetings with doctoral-level staff. Results: Though most providers reported using standardized suicide risk assessment tools in their clinical practices, existing tools were commonly described as unhelpful and providers indicated dissatisfaction with current suicide risk assessment methods. Overall, providers’ general attitudes toward the practical use of automated suicide risk prediction models and corresponding clinical decision support tools were positive. Providers were especially interested in the potential to identify high-risk patients who might be missed by traditional screening methods. Some expressed skepticism about the potential usefulness of these models in routine care; specific barriers included concerns about liability, alert fatigue, and increased demand on the healthcare system. Key facilitators included presenting specific patient-level features contributing to risk scores, emphasizing changes in risk over time, and developing systematic clinical workflows and provider trainings. Participants also recommended considering risk-prediction windows, timing of alerts, who will have access to model predictions, and variability across treatment settings.Conclusions: Providers were dissatisfied with current suicide risk assessment methods and open to the use of a machine learning-based risk prediction system to inform clinical decision-making. They also raised multiple concerns about potential barriers to the usefulness of this approach and suggested several possible facilitators. Future efforts in this area will benefit from incorporating systematic qualitative feedback from providers, patients, administrators, and payers on the use of new methods in routine care, especially given the complex, sensitive, and unfortunately still stigmatized nature of suicide risk.
Published: 2021

24. Physical activity offsets genetic risk for incident depression assessed via electronic health records in a biobank cohort study

Author: Murray B. Stein, Erin C. Dunn, Karmel W. Choi, Min-Jung Wang, Elizabeth W. Karlson, Amanda B Zheutlin, Rebecca A. Karlson, and Jordan W. Smoller
Subjects: Male, Multifactorial Inheritance, Poison control, Context (language use), Suicide prevention, Article, Occupational safety and health, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Databases, Genetic, Injury prevention, Electronic Health Records, Humans, Medicine, Exercise, Depression (differential diagnoses), Depressive Disorder, Major, Depression, business.industry, Middle Aged, 030227 psychiatry, Psychiatry and Mental health, Clinical Psychology, Cohort, Female, business, 030217 neurology & neurosurgery, Genome-Wide Association Study, Demography, Cohort study
Abstract: Background Physical activity is increasingly recognized as an important modifiable factor for depression. However, the extent to which individuals with stable risk factors for depression, such as high genetic vulnerability, can benefit from the protective effects of physical activity, remains unknown. Using a longitudinal biobank cohort integrating genomic data from 7,968 individuals of European ancestry with high-dimensional electronic health records and lifestyle survey responses, we examined whether physical activity was prospectively associated with reduced risk for incident depression in the context of genetic vulnerability. Methods We identified individuals with incident episodes of depression, based on two or more diagnostic billing codes for a depressive disorder within 2 years following their lifestyle survey, and no such codes in the year prior. Polygenic risk scores were derived based on large-scale genome-wide association results for major depression. We tested main effects of physical activity and polygenic risk scores on incident depression, and effects of physical activity within stratified groups of polygenic risk. Results Polygenic risk was associated with increased odds of incident depression, and physical activity showed a protective effect of similar but opposite magnitude, even after adjusting for BMI, employment status, educational attainment, and prior depression. Higher levels of physical activity were associated with reduced odds of incident depression across all levels of genetic vulnerability, even among individuals at highest polygenic risk. Conclusions Real-world data from a large healthcare system suggest that individuals with high genetic vulnerability are more likely to avoid incident episodes of depression if they are physically active.
Published: 2019

25. Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network

Author: Ian B. Stanaway, Dan M. Roden, Divya Kalra, Dustin Key, Debra J. Abrams, David Fasel, Victor Castro, Brad Malin, Berta Almoguera, Beenish Riza, Meckenzie A. Behr, Eric Venner, Christine M. Eng, Joy Jayaseelan, Scott J. Hebbring, Michelle L. McGowan, Steven E. Scherer, Theresa L. Walunas, Mark Bowser, James D. Ralston, Wei-Qi Wei, Liwen Wang, David R. Murdock, Wayne H. Liang, Julia Wynn, Nancy D. Leslie, Laura J. Rasmussen-Torvik, Ming Ta (Michael) Lee, Frank D. Mentch, Lan Zhang, Alanna Kulchak Rahm, Josh F. Peterson, Jodell E. Linder, Joshua C. Smith, Soumitra Sengupta, Brendan J. Keating, Gina Vicente, Andrew Carroll, Nora B. Henrikson, Anne E. Justice, Heather S. Hain, Wen Liu, Andrea H. Ramirez, Matthew S. Lebo, Hana Zouk, Georgia L. Wiesner, Andrea L. Hartzler, Cassandra J. Pisieczko, Catherine M. Rives, Jessica Goehringer, Maegan V. Harden, John Lynch, Chiao-Feng Lin, Peter White, Phil Dunlea, Shawn N. Murphy, Mullai Murugan, Harshad Mahadeshwar, Mark Fleharty, Andrea Foster, Arvind Ramaprasan, Christopher A. Friedrich, Justin H. Gundelach, Hayley Lyon, Niall J. Lennon, Eric W. Klee, David R. Crosslin, Ge Zhang, Rongling Li, Ozan Dikilitas, Xiuping Liu, Christin Hoell, Aniwaa Owusu Obeng, Katherine D. Crew, Lisa M. Castillo, Justin Starren, Jonathan D. Mosley, Carrie L. Blout, Himanshu Sharma, Elizabeth M. McNally, Sarah T. Bland, Megan J. Puckelwartz, Matthew Varugheese, Keith Marsolo, Betty Woolf, Sharon Aufox, Janet L. Williams, Kimberly Walker, Murray H. Brilliant, Birgit Funke, Laura Allison Woods, Marylyn D. Ritchie, Brittany City, Todd Lingren, Hila Milo Rasouly, Lawrence J. Babb, Alex Fedotov, Robert C. Onofrio, Margaret Harr, Suzette J. Bielinski, Michael W. Wilson, Shubhabrata Mukherjee, Robert R. Freimuth, Chet Graham, Todd L. Edwards, Quinn S. Wells, Marc S. Williams, Jordan W. Smoller, Wendy K. Chung, Avni Santani, Paul K. Crane, George Hripcsak, QiPing Feng, Ali G. Gharavi, Yizhao Ni, Iftikhar J. Kullo, Michael Wagner, Philip E. Lammers, Michael J. Dinsmore, Thomas N. Person, Victoria Yi, Samuel E. Adunyah, Tim DeSmet, Eric B. Larson, Elizabeth Hynes, David C. Kochan, Eimear E. Kenny, Magalie S. Leduc, Lisa Mahanta, David Carrell, Paul S. Appelbaum, Viktoriya Korchina, Beth L. Cobb, Lynn Petukhova, Jessica De la Cruz, Patrick M. A. Sleiman, Stuart A. Scott, Tsung-Jung Wu, Gail P. Jarvik, Erwin P. Bottinger, Ken Wiley, Josh C. Denny, Melissa A. Basford, Samuel J. Aronson, David L. Veenstra, Yaping Yang, Kayla Marie Howell, John J. Connolly, Jessica Su, Yoonjung Yoonie Joo, Miguel Verbitsky, Sean M. Vargas, Cong Liu, Barbara Benoit, Andrew Hershey, Richard A. Gibbs, Cynthia A. Prows, Hana Bangash, Wendy Brodeur, Gauthami Chandanavelli, Sara L. Van Driest, Kurt D. Christensen, Elizabeth J. Bhoj, Vivian S. Gainer, Adam S. Gordon, Robert C. Green, Hakon Hakonarson, Krzysztof Kiryluk, Elisabeth A. Rosenthal, Rajbir Singh, James G. Linneman, Harrison Brand, Theodore Chiang, Sheila Dodge, Ingrid A. Holm, M. Geoffrey Hayes, Yunyun Jiang, Ning Shang, Samantha Baxter, Noralane M. Lindor, Kathleen A. Leppig, Teri A. Manolio, Sara E. Kalla, Pedro J. Caraballo, Ritika Raj, Aaron Scrol, Jyoti G. Dayal, Richard R. Sharp, Christie Kovar, Soumya Raychaudhuri, Sunghwan Sohn, Emily Kudalkar, Maddalena Marasa, Stacey Gabriel, Dan Schaid, Ladia Albertson-Junkans, Rex L. Chisholm, Maureen E. Smith, Donna M. Muzny, Casey Overby Taylor, Jianhong Hu, Elizabeth W. Karlson, Lisa Bastarache, Darren C. Ames, Joseph T. Glessner, Leora Witkowski, Siddharth Pratap, Qiaoyan Wang, Melissa A. Kelly, Adithya Balasubramanian, Kara Slowik, Terrie Kitchner, Barbara J. Klanderman, Shawn Denson, Mary Stroud, Alyssa Macbeth, Melanie F. Myers, Jesse Muniz, Kasia Tolwinski, Scott T. Weiss, Chunhua Weng, Stephanie M. Fullerton, John B. Harley, Christopher G. Chute, Heidi L. Rehm, Sheethal Jose, Andrew M. Glazer, Navya Shilpa Josyula, Kenneth M. Borthwick, Thomas E. Mullen, Mariza de Andrade, Leah C. Kottyan, Luke V. Rasmussen, James Meldrim, and Bahram Namjou
Subjects: 0301 basic medicine, Standardization, Test data generation, business.industry, Computer science, Sequence Analysis, DNA, 030105 genetics & heredity, Precision medicine, Data science, Clinical decision support system, Biobank, Article, 3. Good health, Data sharing, 03 medical and health sciences, 030104 developmental biology, Genetics, Humans, Genetic Testing, Prospective Studies, Sample collection, Personalized medicine, Precision Medicine, business, Genetics (clinical)
Abstract: The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.
Published: 2019

26. Prospective study of polygenic risk, protective factors, and incident depression following combat deployment in US Army soldiers

Author: Karmel W. Choi, Karestan C. Koenen, Robert J. Ursano, Xiaoying Sun, Murray B. Stein, Chia-Yen Chen, Ronald C. Kessler, Laura Campbell-Sills, Gary H. Wynn, Jordan W. Smoller, Min-Jung Wang, and Sonia Jain
Subjects: Male, Multifactorial Inheritance, SYMPTOMS, POSTDEPLOYMENT SOCIAL SUPPORT, POSTTRAUMATIC-STRESS-DISORDER, 0302 clinical medicine, Risk Factors, genetics, Prospective Studies, Prospective cohort study, Applied Psychology, Depression (differential diagnoses), media_common, Afghan Campaign 2001, Depression, Resilience, Psychological, Psychiatry and Mental health, Mental Health, Military Personnel, Trait, Major depressive disorder, Female, Psychological resilience, MENTAL-HEALTH, Adult, medicine.medical_specialty, polygenic risk, LIFE EVENTS, longitudinal, media_common.quotation_subject, Protective factor, behavioral disciplines and activities, Article, ACTIVE-DUTY, Young Adult, 03 medical and health sciences, Social support, parasitic diseases, mental disorders, Genetic predisposition, medicine, UNIT COHESION, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Psychiatry, Depressive Disorder, Major, business.industry, MAJOR DEPRESSION, social support, RESILIENCE, Protective Factors, medicine.disease, Mental health, United States, 030227 psychiatry, Military Deployment, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: BackgroundWhereas genetic susceptibility increases the risk for major depressive disorder (MDD), non-genetic protective factors may mitigate this risk. In a large-scale prospective study of US Army soldiers, we examined whether trait resilience and/or unit cohesion could protect against the onset of MDD following combat deployment, even in soldiers at high polygenic risk.MethodsData were analyzed from 3079 soldiers of European ancestry assessed before and after their deployment to Afghanistan. Incident MDD was defined as no MDD episode at pre-deployment, followed by a MDD episode following deployment. Polygenic risk scores were constructed from a large-scale genome-wide association study of major depression. We first examined the main effects of the MDD PRS and each protective factor on incident MDD. We then tested the effects of each protective factor on incident MDD across strata of polygenic risk.ResultsPolygenic risk showed a dose–response relationship to depression, such that soldiers at high polygenic risk had greatest odds for incident MDD. Both unit cohesion and trait resilience were prospectively associated with reduced risk for incident MDD. Notably, the protective effect of unit cohesion persisted even in soldiers at highest polygenic risk.ConclusionsPolygenic risk was associated with new-onset MDD in deployed soldiers. However, unit cohesion – an index of perceived support and morale – was protective against incident MDD even among those at highest genetic risk, and may represent a potent target for promoting resilience in vulnerable soldiers. Findings illustrate the value of combining genomic and environmental data in a prospective design to identify robust protective factors for mental health.
Published: 2019

27. An independently validated, portable algorithm for the rapid identification of COPD patients using electronic health records

Author: James G. Linneman, Erica J. Scotty, Jessica Lasky-Su, Jordan W. Smoller, Scott J. Hebbring, Emily S. Wan, Sergey Goryachev, Shawn N. Murphy, Su H. Chu, Vivian S. Gainer, Elizabeth W. Karlson, Michael H. Cho, and Scott T. Weiss
Subjects: Spirometry, Databases, Factual, Epidemiology, Science, Population, Vital Capacity, Predictive medicine, Article, FEV1/FVC ratio, Pulmonary Disease, Chronic Obstructive, Population screening, Medical research, Forced Expiratory Volume, Machine learning, Feature (machine learning), Medicine, Electronic Health Records, Humans, education, education.field_of_study, COPD, Multidisciplinary, medicine.diagnostic_test, business.industry, Medical record, High-throughput screening, medicine.disease, Biobank, Identification (information), business, Algorithm, Algorithms
Abstract: Electronic health records (EHR) provide an unprecedented opportunity to conduct large, cost-efficient, population-based studies. However, the studies of heterogeneous diseases, such as chronic obstructive pulmonary disease (COPD), often require labor-intensive clinical review and testing, limiting widespread use of these important resources. To develop a generalizable and efficient method for accurate identification of large COPD cohorts in EHRs, a COPD datamart was developed from 3420 participants meeting inclusion criteria in the Mass General Brigham Biobank. Training and test sets were selected and labeled with gold-standard COPD classifications obtained from chart review by pulmonologists. Multiple classes of algorithms were built utilizing both structured (e.g. ICD codes) and unstructured (e.g. medical notes) data via elastic net regression. Models explicitly including and excluding spirometry features were compared. External validation of the final algorithm was conducted in an independent biobank with a different EHR system. The final COPD classification model demonstrated excellent positive predictive value (PPV; 91.7%), sensitivity (71.7%), and specificity (94.4%). This algorithm performed well not only within the MGBB, but also demonstrated similar or improved classification performance in an independent biobank (PPV 93.5%, sensitivity 61.4%, specificity 90%). Ancillary comparisons showed that the classification model built including a binary feature for FEV1/FVC produced substantially higher sensitivity than those excluding. This study fills a gap in COPD research involving population-based EHRs, providing an important resource for the rapid, automated classification of COPD cases that is both cost-efficient and requires minimal information from unstructured medical records.
Published: 2021

28. Hippocampal Threat Reactivity Interacts with Physiological Arousal to Predict PTSD Symptoms

Author: Büsra Tanriverdi, David F. Gregory, Thomas M Olino, Timothy D Ely, Nathaniel G Harnett, Sanne J H van Rooij, Lauren Lebois, Antonia V. Seligowski, Tanja Jovanovic, Kerry J. Ressler, Stacey L. House, Francesca Beaudoin, Xinming An, Thomas C. Neylan, Gari D. Clifford, Sarah D. Linnstaedt, Laura T. Germine, Kenneth Bollen, Scott L. Rauch, John P. Haran, Alan B. Storrow, Christopher Lewandowski, Paul I. Musey, Phyllis L. Hendry, Sophia Sheikh, Christopher W. Jones, Brittany E. Punches, Michael C. Kurz, Meghan E. McGrath, Lauren A. Hudak, Jose L. Pascual, Mark S. Seamon, Elizabeth M. Datner, Claire Pearson, Robert M. Domeier, Niels K. Rathlev, Brian J. O'Neil, León D. Sánchez, Steven E. Bruce, Mark W. Miller, Robert H Pietrzak, Jutta Joormann, Deanna Barch, Diego A. Pizzagalli, John F. Sheridan, Jordan W. Smoller, Steven E. Harte, James M Elliott, Samuel A. McLean, Ronald C Kessler, Karestan C. Koenen, Jennifer S. Stevens, and Vishnu P. Murty
Subjects: Text mining, business.industry, General Neuroscience, Hippocampal formation, business, Reactivity (psychology), Psychology, Neuroscience, Research Articles, Arousal
Abstract: Hippo campal impairments are reliably associated with post-traumatic stress disorder (PTSD); however, little research has characterized how increased threat sensitivity may interact with arousal responses to alter hippocampal reactivity, and further how these interactions relate to the sequelae of trauma-related symptoms. In a sample of individuals recently exposed to trauma (N = 116, 76 female), we found that PTSD symptoms at 2 weeks were associated with decreased hippocampal responses to threat as assessed with fMRI. Further, the relationship between hippocampal threat sensitivity and PTSD symptomology only emerged in individuals who showed transient, high threat-related arousal, as assayed by an independently collected measure of fear potentiated startle. Collectively, our finding suggests that development of PTSD is associated with threat-related decreases in hippocampal function because of increases in fear-potentiated arousal. SIGNIFICANCE STATEMENT Alterations in hippocampal function linked to threat-related arousal are reliably associated with post-traumatic stress disorder (PTSD); however, how these alterations relate to the sequelae of trauma-related symptoms is unknown. Prior models based on nontrauma samples suggest that arousal may impact hippocampal neurophysiology leading to maladaptive behavior. Here we show that decreased hippocampal threat sensitivity interacts with fear-potentiated startle to predict PTSD symptoms. Specifically, individuals with high fear-potentiated startle and low, transient hippocampal threat sensitivity showed the greatest PTSD symptomology. These findings bridge literatures of threat-related arousal and hippocampal function to better understand PTSD risk.
Published: 2021

29. Characterization of Age and Polarity at Onset in Bipolar Disorder

Author: Aiden Corvin, Maria Grigoroiu-Serbanescu, Mark Hyman Rapaport, Frederike T. Fellendorf, Urs Heilbronner, Mariam M. Al Eissa, John J Nurnberger, Claire O'Donovan, Claire Slaney, Mark A. Frye, Niamh L. O'Brien, Roland Hasler, Michael John Owen, Michael Conlon O'Donovan, Farah Klöhn-Saghatolislam, Markus M. Nöthen, Scott R. Clark, Mikael Landén, Lina Jonsson, Peter Falkai, Qingqin S. Li, Alessio Squassina, Simon Schmitt, Gustavo Turecki, Heike Anderson-Schmidt, Jonathan Repple, Sofie R. Aminoff, Eduard Vieta, Katherine Gordon-Smith, Stéphane Jamain, William Byerley, Hélène Richard-Lepouriel, Fermín Mayoral, Francis J. McMahon, Marin Veldic, Ingrid Melle, Andrew McQuillin, Nicholas Bass, Gloria Roberts, Douglas M. Ruderfer, John B. Vincent, Nelson B. Freimer, Kirov George, Wei Xu, Susan L. McElroy, Ceylan Balaban, Marco P. Boks, Franziska Degenhardt, Paul E. Croarkin, Wade H. Berrettini, Piotr M. Czerski, Fernando S. Goes, Peter P. Zandi, Sabrina K. Schaupp, Barbara W. Schweizer, Andrew M. McIntosh, Marcella Rietschel, Helena Pelin, Evelyn J. Bromet, Marion Leboyer, Ole A. Andreassen, Georgia Panagiotaropoulou, Alessia Fiorentino, Sally I. Sharp, Torbjørn Elvsåshagen, Kristina Adorjan, Monika Budde, Lisa Jones, Thomas G. Schulze, Vihra Milanova, Janos Kalman, Tim B. Bigdeli, Esther Jiménez, Abigail Ortiz, Dolores Malaspina, Kevin S. O’Connell, Sergi Papiol, Mario Maj, Tim Hahn, Frederike Stein, Jordan W. Smoller, Tomas Novak, Katrin Gade, J. Raymond DePaulo, Sarah Kittel-Schneider, Julia-Katharina Pfarr, Martin Alda, James A. Knowles, Sven Cichon, David Craig, Eli A. Stahl, William A. Scheftner, Bruno Etain, Annabel Vreeker, Guy A. Rouleau, Stephan Ripke, Clement C. Zai, Frank Bellivier, Giovanni Severino, Palmiero Monteleone, Ian Jones, Bertram Müller-Myhsok, Mark Adams, John Strauss, Philip B. Mitchell, Andreas Reif, Fabian Streit, Roel A. Ophoff, James L. Kennedy, Nils Opel, Raffaella Ardau, Paul Grof, Peter R. Schofield, Susanne Bengesser, Maria Hake, Loes M. Olde Loohuis, Joanna Pawlak, Daniela Reich-Erkelenz, Ingrid Agartz, Maria Del Zompo, Antonio Benabarre, Bernhard T. Baune, Arianna Di Florio, Ashley L. Comes, Michael Gill, Cristiana Cruceanu, Susanne Meinert, William Coryell, Alessio Maria Monteleone, Fanny Senner, Trine Vik Lagerberg, Jose Guzman-Parra, Erik Pålsson, Elliot S. Gershon, Melvin G. McInnis, Pavla Stopkova, Nikolaos Koutsouleris, René S. Kahn, Janice M. Fullerton, Howard J. Edenberg, Tilo Kircher, Nina Dalkner, Udo Dannlowski, Rolf Adolfsson, Alfonso Tortorella, Jean-Michel Aubry, James B. Potash, Catina Chillotti, Eva Z. Reininghaus, Janet L. Sobell, Thorsten M. Kranz, Tina Meller, Ayman H. Fanous, Kai Ringwald, K Oliver Schubert, Andreas J. Forstner, Till F. M. Andlauer, Helena Medeiros, Mirko Manchia, Joanna M. Biernacka, Katharina Brosch, Julie Garnham, Olav B. Smeland, Eva C. Schulte, Carlos N. Pato, Nicholas John Craddock, Srdjan Djurovic, Pablo Cervantes, Michele T. Pato, John R. Kelsoe, Claudia Pisanu, Joanna Twarowska-Hauser, and William Lawson
Subjects: 0303 health sciences, medicine.medical_specialty, business.industry, Genome-wide association study, Disease, Heritability, medicine.disease, Genetic architecture, 03 medical and health sciences, 0302 clinical medicine, Autism spectrum disorder, Schizophrenia, Internal medicine, medicine, Bipolar disorder, business, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract: BackgroundStudying the phenotypic and genetic characteristics of age and polarity at onset (AAO, PAO) in bipolar disorder (BD) can provide new insights into disease pathology and facilitate the development of screening tools.AimsTo examine the genetic architecture of AAO and PAO and their association with BD disease characteristics.MethodsGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (N=12977) and PAO (N=6773) were conducted in BD patients of 34 cohorts and a replication sample (N=2237). The association of onset with disease characteristics was investigated in two of these cohorts.ResultsEarlier AAO was associated with an increased risk of psychotic symptoms, suicidality, and fewer episodes. A depressive onset correlated with lifetime suicidality and a manic onset with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in SNV-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased polygenic scores for autism spectrum disorder (β=-0.34 years, SE=0.08), major depression (β=-0.34 years, SE=0.08), schizophrenia (β=-0.39 years, SE=0.08), and educational attainment (β=-0.31 years, SE=0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.ConclusionsAAO and PAO are associated with indicators of BD severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents, and phenotype definitions introduce significant heterogeneity, affecting analyses.RELEVANCE STATEMENTIn the largest study to systematically characterize age at onset (N=12977) and polarity at onset (N=6773) in bipolar disorder, we describe an association between illness onset characteristics and indicators of severity, confirming their clinical relevance. Our study shows that that early illness onset is associated with genetic liability for a broad range of psychiatric disorders. However, we also highlight systematic differences in age at onset across cohorts, continents, and phenotype definitions. This heterogeneity results in reduced heritability and affects genetic analyses, underscoring the need for the development of standardized phenotype definitions.
Published: 2021

30. Exome sequencing in bipolar disorder reveals shared risk geneAKAP11with schizophrenia

Author: Matthew Solomonson, Michael Conlon O'Donovan, Nancy L. Pedersen, Faith Dickerson, Eli A. Stahl, Neil Risch, Catherine Schaefer, Laura J. Scott, René S. Kahn, Duncan S. Palmer, Derek W. Morris, Claire Churchhouse, Xiaoming Jia, James T.R. Walters, Andrew M. McIntosh, Chia-Yen Chen, Michael John Owen, Arianna Di Florio, Lina Jonsson, Benjamin M. Neale, Roel A. Ophoff, Annabel Vreeker, Tarjinder Singh, Douglas Blackwood, Nicholas John Craddock, Jordan W. Smoller, Ian Jones, Weiqing Wang, Peter P. Zandi, Marco P. Boks, Fernando S. Goes, Lisa Jones, Robert H. Yolken, Mikael Landén, David Curtis, Danielle Posthuma, Andreas Reif, David St Clair, Sinéad B. Chapman, Nicholas A. Watts, Rolf Adolfsson, Adam E. Locke, Aiden Corvin, Nick Bass, Daniel P. Howrigan, and Andrew McQuillin
Subjects: Genetics, business.industry, Schizophrenia, Medicine, Risk gene, Genome-wide association study, Bipolar disorder, business, medicine.disease, Exome, Gene, GSK3B, Exome sequencing
Abstract: Here we report results from the Bipolar Exome (BipEx) collaboration analysis of whole exome sequencing of 13,933 individuals diagnosed with bipolar disorder (BD), matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in BD patients among genes under strong evolutionary constraint, a signal evident in both major BD subtypes, bipolar 1 disorder (BD1) and bipolar 2 disorder (BD2). We also find an excess of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 SCZ cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from GWAS of BD, however, are not significantly enriched for ultra-rare PTVs. Combining BD gene-level results with SCHEMA,AKAP11emerges as a definitive risk gene (ultra-rare PTVs seen in 33 cases and 13 controls, OR = 7.06,P= 2.83 × 10−9). At the protein level, AKAP-11 is known to interact with GSK3B, the hypothesized mechanism of action for lithium, one of the few treatments for BD. Overall, our results lend further support to the polygenic basis of BD and demonstrate a role for rare coding variation as a significant risk factor in BD onset.
Published: 2021

31. Novel polygenic risk score links depression-related cortical transcriptomic changes to brain morphology and symptom severity

Author: Amy Miles, Jianxin Shi, James B. Potash, Giorgio Pistis, Enrique Castelao, Mark Adams, Jordan W. Smoller, Yuliya S. Nikolova, Glyn Lewis, Brenda W.J.H. Penninx, Martin Preisig, Dos Santos Fc, Etienne Sibille, Schubert Ko, Roy H. Perlis, Ian Jones, Miguel E. Rentería, Ahmad R. Hariri, Douglas F. Levinson, Cathryn M. Lewis, S. P. Hamilton, Lisa Jones, Myrna M. Weissman, Rudolf Uher, Enda M. Byrne, Andrew M. McIntosh, Dorret I. Boomsma, and Bernhardt T. Baune
Subjects: Oncology, medicine.medical_specialty, business.industry, Brain morphometry, Neurogenetics, medicine.disease, Internal medicine, Cohort, medicine, Major depressive disorder, Young adult, Family history, business, Gyrification, Depression (differential diagnoses)
Abstract: Our group developed a transcriptome-based polygenic risk score (T-PRS) that uses common genetic variants to capture ‘depression-like’ shifts in cortical gene expression. Here, we mapped T-PRS onto diagnosis and symptom severity in major depressive disorder (MDD) cases and controls from the Psychiatric Genomics Consortium (PGC). To evaluate potential mechanisms, we further mapped T-PRS onto discrete measures of brain morphology and broad depression risk in healthy young adults. Genetic, self-report, and/or neuroimaging data were available in 29,340 PGC participants (59% women; 12,923 MDD cases, 16,417 controls) and 482 participants in the Duke Neurogenetics Study (DNS: 53% women; aged 19.8±1.2 years). T-PRS was computed from SNP data using PrediXcan to impute cortical expression levels of MDD-related genes from a previous post-mortem transcriptome meta-analysis. Sex-specific regressions were used to test effects of T-PRS on depression diagnosis, symptom severity, and Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index in the PGC and DNS samples, respectively. T-PRS did not predict depression diagnosis (OR=1.007, 95%CI=[0.997-1.018]); however, it correlated with symptom severity in men (rho=0.175, p=7.957×10−4) in one large PGC cohort (N=762, 48% men). In DNS, T-PRS was associated with smaller amygdala volume in women (β=-0.186, t=-3.478, p=.001) and less prefrontal gyrification (max≤-2.970, p≤.006) in both sexes. In men, prefrontal gyrification mediated an indirect effect of T-PRS on broad depression risk (b=.005, p=.029), indexed using self-reported family history of depression. Depression-like shifts in cortical gene expression predict symptom severity in men and may contribute to disease vulnerability through their effect on cortical gyrification.
Published: 2021

32. 58. IDENTIFYING POTENTIAL ENVIRONMENTAL INFLUENCES ON CLINICAL COMORBIDITIES OF SCHIZOPHRENIA THROUGH INTEGRATION OF ELECTRONIC HEALTH DATA AND GENETICS

Author: Karmel W. Choi, Nicholas Strayer, Tess Vessels, Yaomin Xu, Hyunjoon Lee, Douglas M. Ruderfer, Jordan W. Smoller, and Theodore Morley
Subjects: Pharmacology, Psychiatry and Mental health, medicine.medical_specialty, Neurology, business.industry, Schizophrenia (object-oriented programming), medicine, Pharmacology (medical), Neurology (clinical), Psychiatry, business, Biological Psychiatry, Health data
Published: 2021

33. 76. IMPACT OF ASCERTAINMENT BIAS ON POLYGENIC RISK SCORE ESTIMATES IN HEALTHCARE SETTINGS

Author: Peter Kraft, Tian Ge, Yen-Chen Anne Feng, Yi-Han Sheu, Jordan W. Smoller, Younga H Lee, and Tanayott Thaweethai
Subjects: Pharmacology, Psychiatry and Mental health, Neurology, business.industry, Healthcare settings, Medicine, Pharmacology (medical), Polygenic risk score, Neurology (clinical), business, Biological Psychiatry, Sampling bias, Demography
Published: 2021

34. A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts

Author: Guiyan Ni, Jian Zeng, Joana A. Revez, Ying Wang, Zhili Zheng, Tian Ge, Restuadi Restuadi, Jacqueline Kiewa, Dale R. Nyholt, Jonathan R.I. Coleman, Jordan W. Smoller, Jian Yang, Peter M. Visscher, Naomi R. Wray, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberley D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Ina Giegling, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Julià, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Patrik K.E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Müller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Psychosis Endophenotypes International Consortium, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Hon-Cheong So, Chris C.A. Spencer, Eli A. Stahl, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Kari Stefansson, Wellcome Trust Case-Control Consortium, Rolf Adolfsson, Ole A. Andreassen, Douglas H.R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tõnu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jönsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarroll, Andrew McQuillin, Jennifer L. Moran, Preben B. Mortensen, Bryan J. Mowry, Markus M. Nöthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietschel, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O’Donovan, Maciej Trzaskowski, Enda M. Byrne, Abdel Abdellaoui, Mark J. Adams, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Toni-Kim Clarke, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Gregory E. Crawford, Gail Davies, Ian J. Deary, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Andreas J. Forstner, Héléna A. Gaspar, Fernando S. Goes, Scott D. Gordon, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Ian B. Hickie, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Peter McGuffin, Sarah E. Medland, Divya Mehta, Christel M. Middeldorp, Evelin Mihailov, Yuri Milaneschi, Francis M. Mondimore, Grant W. Montgomery, Sara Mostafavi, Niamh Mullins, Matthias Nauck, Bernard Ng, Michel G. Nivard, Paul F. O’Reilly, Hogni Oskarsson, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Jorge A. Quiroz, Per Qvist, John P. Rice, Margarita Rivera, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Stanley I. Shyn, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Fabian Streit, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, Vassily Trubetskoy, André G. Uitterlinden, Daniel Umbricht, Sandra Van der Auwera, Albert M. van Hemert, Alexander Viktorin, Yunpeng Wang, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Yang Wu, Hualin S. Xi, Futao Zhang, Volker Arolt, Bernhard T. Baune, Klaus Berger, Dorret I. Boomsma, Udo Dannlowski, E.J.C. de Geus, J. Raymond DePaulo, Katharina Domschke, Hans J. Grabe, Steven P. Hamilton, Caroline Hayward, Andrew C. Heath, Stefan Kloiber, Glyn Lewis, Susanne Lucae, Pamela A.F. Madden, Patrik K. Magnusson, Nicholas G. Martin, Preben Bo Mortensen, Merete Nordentoft, Sara A. Paciga, Nancy L. Pedersen, Adult Psychiatry, APH - Mental Health, ANS - Complex Trait Genetics, ANS - Mood, Anxiety, Psychosis, Stress & Sleep, Ni, Guiyan, Zeng, Jian, Revez, Joana A., Wang, Ying, Zhili, Zheng, Ge, Tian, Restuadi, Restuadi, Kiewa, Jacqueline, Nyholt, Dale R, Coleman, Jonathan RI, Smoller, Jordan W, Lee, S Hong, APH - Methodology, Biological Psychology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Econometrics, Psychiatry, Department of Technology and Operations Management, Child and Adolescent Psychiatry / Psychology, Epidemiology, Erasmus MC other, Urology, Internal Medicine, Medical Informatics, Immunology, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep
Subjects: 0301 basic medicine, Multifactorial Inheritance, medicine.medical_specialty, LDpred2, BF, Genomics, Disease, Major depressive disorder, risk prediction, 03 medical and health sciences, 0302 clinical medicine, MegaPRS, SDG 3 - Good Health and Well-being, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Genetic risk, Psychiatry, Biological Psychiatry, Genetic association, Depressive Disorder, Major, business.industry, Mental Disorders, medicine.disease, Genetic architecture, Polygenic scores, Risk prediction, polygenic scores, PRS-CS, psychiatric disorders, 030104 developmental biology, SBayesR, Schizophrenia, Cohort, Lassosum, RC0321, business, Psychiatric disorders, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: BACKGROUND: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors.METHODS: The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressive disorder bring together many independently collected case-control cohorts. We used these resources (31,328 schizophrenia cases, 41,191 controls; 248,750 major depressive disorder cases, 563,184 controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and 9 methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) were compared.RESULTS: Compared with PC+T, the other 9 methods gave higher prediction statistics, MegaPRS, LDPred2, and SBayesR significantly so, explaining up to 9.2% variance in liability for schizophrenia across 30 target cohorts, an increase of 44%. For major depressive disorder across 26 target cohorts, these statistics were 3.5% and 59%, respectively.CONCLUSIONS: Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparisons and are recommended in applications to psychiatric disorders.
Published: 2021

35. Clinical laboratory test-wide association scan of polygenic scores identifies biomarkers of complex disease

Author: Jonathan D. Mosley, Tian Ge, Theodore Morley, Douglas M. Ruderfer, Ky’Era Actkins, Jessica Dennis, Slavina B. Goleva, Jordan W. Smoller, Kritika Singh, Yen-Chen Anne Feng, Guanhua Chen, Peter Straub, Younga H Lee, Annika Faucon, Maria Niarchou, Julia M. Sealock, Lea K. Davis, and Donald Hucks
Subjects: Male, medicine.medical_specialty, Multifactorial Inheritance, lcsh:QH426-470, Heart disease, Population genetics, Population, lcsh:Medicine, Disease, Coronary Artery Disease, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Internal medicine, Genetics, medicine, Electronic health records, Humans, Genetic epidemiology, education, Molecular Biology, Genetics (clinical), 030304 developmental biology, Biological Specimen Banks, 0303 health sciences, education.field_of_study, business.industry, Clinical Laboratory Techniques, Research, lcsh:R, Reproducibility of Results, Heritability, Middle Aged, medicine.disease, Biobank, Lipids, 3. Good health, lcsh:Genetics, chemistry, Molecular Medicine, Biomarker (medicine), Female, Glycated hemoglobin, business, 030217 neurology & neurosurgery, Biomarkers, Genome-Wide Association Study
Abstract: Background Clinical laboratory (lab) tests are used in clinical practice to diagnose, treat, and monitor disease conditions. Test results are stored in electronic health records (EHRs), and a growing number of EHRs are linked to patient DNA, offering unprecedented opportunities to query relationships between genetic risk for complex disease and quantitative physiological measurements collected on large populations. Methods A total of 3075 quantitative lab tests were extracted from Vanderbilt University Medical Center’s (VUMC) EHR system and cleaned for population-level analysis according to our QualityLab protocol. Lab values extracted from BioVU were compared with previous population studies using heritability and genetic correlation analyses. We then tested the hypothesis that polygenic risk scores for biomarkers and complex disease are associated with biomarkers of disease extracted from the EHR. In a proof of concept analyses, we focused on lipids and coronary artery disease (CAD). We cleaned lab traits extracted from the EHR performed lab-wide association scans (LabWAS) of the lipids and CAD polygenic risk scores across 315 heritable lab tests then replicated the pipeline and analyses in the Massachusetts General Brigham Biobank. Results Heritability estimates of lipid values (after cleaning with QualityLab) were comparable to previous reports and polygenic scores for lipids were strongly associated with their referent lipid in a LabWAS. LabWAS of the polygenic score for CAD recapitulated canonical heart disease biomarker profiles including decreased HDL, increased pre-medication LDL, triglycerides, blood glucose, and glycated hemoglobin (HgbA1C) in European and African descent populations. Notably, many of these associations remained even after adjusting for the presence of cardiovascular disease and were replicated in the MGBB. Conclusions Polygenic risk scores can be used to identify biomarkers of complex disease in large-scale EHR-based genomic analyses, providing new avenues for discovery of novel biomarkers and deeper understanding of disease trajectories in pre-symptomatic individuals. We present two methods and associated software, QualityLab and LabWAS, to clean and analyze EHR labs at scale and perform a Lab-Wide Association Scan.
Published: 2021

36. Increased depression genetic liability associates with inflammatory markers in multiple electronic health record systems

Author: Yen-Chen Anne Feng, Georgios Voloudakis, Arden Moscati, Peter Straub, Ge T, Sanan Venkatesh, Jordan W. Smoller, Guanhua Chen, Lea K. Davis, Julia M. Sealock, Younga H Lee, Kritika Singh, and Panagiotis Roussos
Subjects: medicine.medical_specialty, business.industry, Electronic health record, Liability, Medicine, business, Psychiatry, Depression (differential diagnoses)
Abstract: Although depression is a common disorder, its underlying biological basis remains poorly understood. The results of clinical lab tests available for research in electronic health records can be used to identify biomarkers that may reveal biological processes involved in the development of depression or may be markers of physiological changes due to depression. Here, we leveraged clinical laboratory tests and integrated biobank data to evaluate the relationship between genetic risk for depression and 315 routinely collected quantitative lab measures. Analyses across four health care systems (N = 382,452) robustly implicate increased white blood cell count as both a risk factor and consequence of depression diagnosis and revealed neutrophils, lymphocytes, and monocytes as the primary cell types responsible for this association. Our results highlight the importance of the immune system in the etiology of depression and motivate future development of clinical biomarkers and targeted treatment options for depression and its systemic effects.
Published: 2020

37. Hematopoietic mosaic chromosomal alterations and risk for infection among 767,891 individuals without blood cancer

Author: Steven A. McCarroll, Matthew S. Lebo, Seyedeh M. Zekavat, Zhaolong Yu, Aoxing Liu, Puja Kohli, Benjamin L. Ebert, Mesbah Uddin, Xiaoxi Liu, Po-Ru Loh, Eric A. Engels, James P. Pirruccello, Pradeep Natarajan, Alexander G. Bick, Akhil Pampana, Kaavya Paruchuri, Mark J. Daly, Derek Brown, Jordan W. Smoller, Scott T. Weiss, Benjamin M. Neale, Shu-Hong Lin, Yixuan Ye, Mitchell J. Machiela, Hongyu Zhao, Elizabeth W. Karlson, Robert C. Green, Chikashi Terao, Yoichiro Kamatani, Patrick T. Ellinor, Andrea Ganna, and Giulio Genovese
Subjects: 0303 health sciences, Somatic cell, business.industry, Cancer, medicine.disease, Germline, Article, 3. Good health, Sepsis, 03 medical and health sciences, 0302 clinical medicine, Immune system, Immunity, 030220 oncology & carcinogenesis, Immunology, medicine, Risk factor, business, Genotyping, 030304 developmental biology
Abstract: Summary ParagraphAge is the dominant risk factor for infectious diseases, but the mechanisms linking the two are incompletely understood1,2. Age-related mosaic chromosomal alterations (mCAs) detected from blood-derived DNA genotyping, are structural somatic variants associated with aberrant leukocyte cell counts, hematological malignancy, and mortality3-11. Whether mCAs represent independent risk factors for infection is unknown. Here we use genome-wide genotyping of blood DNA to show that mCAs predispose to diverse infectious diseases. We analyzed mCAs from 767,891 individuals without hematological cancer at DNA acquisition across four countries. Expanded mCA (cell fraction >10%) prevalence approached 4% by 60 years of age and was associated with diverse incident infections, including sepsis, pneumonia, and coronavirus disease 2019 (COVID-19) hospitalization. A genome-wide association study of expanded mCAs identified 63 significant loci. Germline genetic alleles associated with expanded mCAs were enriched at transcriptional regulatory sites for immune cells. Our results link mCAs with impaired immunity and predisposition to infections. Furthermore, these findings may also have important implications for the ongoing COVID-19 pandemic, particularly in prioritizing individual preventive strategies and evaluating immunization responses.
Published: 2020

38. Abstract 16270: Genetic Susceptibility to Stress Associates With Higher Amygdalar Activity and Greater Myocardial Infarction Risk

Author: Michael T. Osborne, Ahmed Ghoneem, Shady Abohashem, Taimur Abbasi, Ahmed Tawakol, Tawseef Dar, Nicki Naddaf, Hadil Zureigat, Karmel W. Choi, Jordan W. Smoller, and Zhaowen Liu
Subjects: medicine.medical_specialty, business.industry, Disease, 030204 cardiovascular system & hematology, medicine.disease_cause, medicine.disease, Amygdala, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, Physiology (medical), Internal medicine, medicine, Cardiology, Genetic predisposition, Psychological stress, 030212 general & internal medicine, Myocardial infarction, Cardiology and Cardiovascular Medicine, business, Metabolic activity
Abstract: Introduction and Hypothesis: Chronic psychological stress is strongly linked to cardiovascular disease (CVD) risk. Metabolic activity of the amygdala, a stress-associated brain center, robustly associates with high inflammation and CVD risk. We hypothesized that a validated polygenic risk score for neuroticism (nPRS), a broad trait measure of vulnerability to stress, independently associates with 1) heightened amygdalar activity (AmygA) and 2) increased myocardial infarction (MI) risk Methods: Individuals (N=14349; median age (IQR): 64 (52, 74) yrs, 46%male) were identified from the Partners Biobank where genome wide nPRS and principle components of ancestry (PCI) were calculated. Using validated 18 FDG PET/CT imaging methods, AmygA was measured (N=995) as a target-to-background-ratio in individuals with clinical PET/CT imaging. MI was adjudicated using International Classification of Diseases (ICD) diagnoses. Traditional CVD risk factors * and psychiatric history were obtained using ICD codes and questionnaires. Independent t-tests and linear and logistic regression were employed Results: A total of 1708 (12%) individuals experienced MI. nPRS associated with AmygA (standardized β [95% CI]: 0.07 [0.01, 0.13], p=0.02 Fig A ) after adjustment for age, sex, and 10 PCI. It remained significant after additional adjustment for psychiatric history (p=0.02). AmygA also predicted MI in an adjusted model (OR: 1.50, p=0.006 * ). Importantly, after adjustment for age, sex, and 10 PCI, nPRS significantly associated with MI incidence (standardized OR [95% CI]: 1.12 [1.05, 1.17], pFig B ) and remained significant after additional adjustment for CVD factors (p=0.006*) and psychiatric history (p=0.007) Conclusions: These findings show for the first time that a genetic susceptibility to stress (high nPRS) associates with greater stress-related neurobiological activity, and MI risk. Further, these findings suggest nPRS may serve as a novel risk marker for MI
Published: 2020

39. Hematopoietic mosaic chromosomal alterations and risk for infection among 767,891 individuals without blood cancer

Author: Zhaolong Yu, Mark J. Daly, Patrick T. Ellinor, Puja Kohli, Pradeep Natarajan, Yixuan Ye, Xiaoxi Liu, Eric A. Engels, Chikashi Terao, Aoxing Liu, Mesbah Uddin, Mitchell J. Machiela, Po-Ru Loh, Benjamin M. Neale, Derek Brown, Giulio Genovese, Jordan W. Smoller, Akhil Pampana, Elizabeth W. Karlson, Yoichiro Kamatani, Seyedeh M. Zekavat, Robert C. Green, Shu-Hong Lin, James P. Pirruccello, Alexander G. Bick, Matthew S. Lebo, Benjamin L. Ebert, Hongyu Zhao, Steven A. McCarroll, Kaavya Paruchuri, and Scott T. Weiss
Subjects: Somatic cell, business.industry, Cancer, medicine.disease, Article, Germline, Sepsis, Immune system, Immunity, Immunology, Medicine, Risk factor, business, Genotyping
Abstract: Age is the dominant risk factor for infectious diseases, but the mechanisms linking the two are incompletely understood1,2. Age-related mosaic chromosomal alterations (mCAs) detected from blood-derived DNA genotyping, are structural somatic variants associated with aberrant leukocyte cell counts, hematological malignancy, and mortality3-11. Whether mCAs represent independent risk factors for infection is unknown. Here we use genome-wide genotyping of blood DNA to show that mCAs predispose to diverse infectious diseases. We analyzed mCAs from 767,891 individuals without hematological cancer at DNA acquisition across four countries. Expanded mCA (cell fraction >10%) prevalence approached 4% by 60 years of age and was associated with diverse incident infections, including sepsis, pneumonia, and coronavirus disease 2019 (COVID-19) hospitalization. A genome-wide association study of expanded mCAs identified 63 significant loci. Germline genetic alleles associated with expanded mCAs were enriched at transcriptional regulatory sites for immune cells. Our results link mCAs with impaired immunity and predisposition to infections. Furthermore, these findings may also have important implications for the ongoing COVID-19 pandemic, particularly in prioritizing individual preventive strategies and evaluating immunization responses.
Published: 2020

40. Generalizability of Polygenic Risk Scores for Breast Cancer in the Multiethnic eMERGE Study

Author: Katherine D. Crew, Ozan Dikilitas, Jordan W. Smoller, Paul K. Crane, George Hripcsak, Ali G. Ghravi, Nur Zeinomar, Eric B. Larson, Wendy K. Chung, David Fasel, Atlas Khan, Krzysztof Kiryluk, Ning Shang, Alanna Kulchak Rahm, Robb Rowley, Mary Beth Terry, Chunhua Weng, Teri A. Manolio, Stephanie M. Fullerton, Ann E. Justice, Gail P. Jarvik, and Cong Liu
Subjects: Breast cancer, business.industry, Medical record, Cohort, Breast cancer family history, medicine, Polygenic risk score, Generalizability theory, Odds ratio, medicine.disease, business, Confidence interval, Demography
Abstract: BackgroundThe majority of polygenic risk scores (PRS) for breast cancer have been developed and validated using cohorts of European ancestry (EA). Less is known about the generalizability of these PRS in other ancestral groups.MethodsThe Electronic Medical Records and Genomics (eMERGE) network cohort dataset was used to evaluate the performance of seven previously developed PRS (three EA-based PRSs, and four non-EA based PRSs) in three major ancestral groups. Each PRS was separately evaluated in EA (cases: 3939; controls: 28840), African ancestry (AA) (cases: 121; controls: 1173) and self-reported LatinX ancestry (LA) (cases: 92; controls: 1363) women. We assessed the association between breast cancer risk and each PRS, adjusting forage, study site, breast cancer family history, and first three ancestry informative principal components.ResultsEA-based PRSs were significantly associated with breast cancer risk in EA women per one SD increase (odds ratio [OR] = 1.45, 95% confidence interval [CI] = 1.40–1.51), and LA women (OR = 1.41, 95% CI = 1.13–1.77), but not AA women (OR = 1.13, 95% CI = 0.92–1.40). There was no statistically significant association for the non-EA PRSs in all ancestry groups, LA including an LA-based PRS and an AA-based PRS.ConclusionWe evaluated EA-derived PRS for estimating breast cancer risk using the eMERGE dataset and found they generalized well in LA women but not in AA women. For non-EA based PRSs, we did not replicate previously reported associations for the respective ancestries in the eMERGE cohort. Our results highlight the need to improve representation of diverse population groups, particularly AA women, in research cohorts.
Published: 2020

41. An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression

Author: Murray B. Stein, Karmel W. Choi, Kristen Nishimi, Jonathan R. I. Coleman, Tian Ge, Gerome Breen, Karestan C. Koenen, Amanda B Zheutlin, Jordan W. Smoller, Chia-Yen Chen, Andrew Ratanatharathorn, and Erin C. Dunn
Subjects: Adult, Male, Exposome, Multifactorial Inheritance, Depression/etiology, Genomic data, Preventive Psychiatry, Bioinformatics, Article, Screen Time, 03 medical and health sciences, Exercise/psychology, 0302 clinical medicine, Risk Factors, Mendelian randomization, Medicine, Humans, Sleep Hygiene, Multifactorial Inheritance/genetics, Exercise, Depression (differential diagnoses), business.industry, Depression, Mendelian Randomization Analysis, 030227 psychiatry, Diet, Psychiatry and Mental health, Databases as Topic, Polygenic risk score, Female, Epidemiologic Methods, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: OBJECTIVE: Efforts to prevent depression, the leading cause of disability worldwide, have focused on a limited number of candidate factors. Using phenotypic and genomic data from over 100,000 UK Biobank participants, the authors sought to systematically screen and validate a wide range of potential modifiable factors for depression.METHODS: Baseline data were extracted for 106 modifiable factors, including lifestyle (e.g., exercise, sleep, media, diet), social (e.g., support, engagement), and environmental (e.g., green space, pollution) variables. Incident depression was defined as minimal depressive symptoms at baseline and clinically significant depression at follow-up. At-risk individuals for incident depression were identified by polygenic risk scores or by reported traumatic life events. An exposure-wide association scan was conducted to identify factors associated with incident depression in the full sample and among at-risk individuals. Two-sample Mendelian randomization was then used to validate potentially causal relationships between identified factors and depression.RESULTS: Numerous factors across social, sleep, media, dietary, and exercise-related domains were prospectively associated with depression, even among at-risk individuals. However, only a subset of factors was supported by Mendelian randomization evidence, including confiding in others (odds ratio=0.76, 95% CI=0.67, 0.86), television watching time (odds ratio=1.09, 95% CI=1.05, 1.13), and daytime napping (odds ratio=1.34, 95% CI=1.17, 1.53).CONCLUSIONS: Using a two-stage approach, this study validates several actionable targets for preventing depression. It also demonstrates that not all factors associated with depression in observational research may translate into robust targets for prevention. A large-scale exposure-wide approach combined with genetically informed methods for causal inference may help prioritize strategies for multimodal prevention in psychiatry.
Published: 2020

42. Greater Neurobiological Resilience to Chronic Socioeconomic or Environmental Stressors Associates With Lower Risk for Cardiovascular Disease Events

Author: Michael T. Osborne, Ahmed Ghoneem, Gregory L. Fricchione, Karmel W. Choi, Lisa M. Shin, Jordan W. Smoller, Shady Abohashem, Ahmed Tawakol, Taimur Abbasi, Nicki Naddaf, John W. Denninger, Tawseef Dar, and Roger K. Pitman
Subjects: Chronic exposure, Adult, Male, Vasculitis, Time Factors, Social Determinants of Health, Disease, 030204 cardiovascular system & hematology, Environment, Lower risk, Risk Assessment, Article, 03 medical and health sciences, 0302 clinical medicine, Environmental health, Positron Emission Tomography Computed Tomography, Medicine, Humans, Radiology, Nuclear Medicine and imaging, Whole Body Imaging, Longitudinal Studies, Resilience (network), Socioeconomic status, Aged, Retrospective Studies, business.industry, Stressor, Environmental Exposure, Middle Aged, Protective Factors, Amygdala, Socioeconomic Factors, Cardiovascular Diseases, Heart Disease Risk Factors, Chronic Disease, Income, Female, Leukopoiesis, Crime, Cardiology and Cardiovascular Medicine, business, Noise, 030217 neurology & neurosurgery, Stress, Psychological
Abstract: Background: Chronic exposure to socioeconomic or environmental stressors associates with greater stress-related neurobiological activity (ie, higher amygdalar activity [AmygA]) and higher risk of major adverse cardiovascular events (MACE). However, among individuals exposed to such stressors, it is unknown whether neurobiological resilience (NBResilience, defined as lower AmygA despite stress exposure) lowers MACE risk. We tested the hypotheses that NBResilience protects against MACE, and that it does so through decreased bone marrow activity and arterial inflammation. Methods: Individuals underwent 18 F-fluorodeoxyglucose positron emission tomography/computed tomography; AmygA, bone marrow activity, and arterial inflammation were quantified. Chronic socioeconomic and environmental stressors known to associate with AmygA and MACE (ie, transportation noise exposure, neighborhood median household income, and crime rate) were quantified. Heightened stress exposure was defined as exposure to at least one chronic stressor (ie, the highest tertile of noise exposure or crime or lowest tertile of income). MACE within 5 years of imaging was adjudicated. Relationships were evaluated using linear and Cox regression, Kaplan-Meier survival, and mediation analyses. Results: Of 254 individuals studied (median age [interquartile range]: 57 years [46–67], 36.7% male), 166 were exposed to at least one chronic stressor. Among stress-exposed individuals, 12 experienced MACE over a median follow-up of 3.75 years. Among this group, higher AmygA (ie, lower resilience) associated with higher bone marrow activity (standardized β [95% CI]: 0.192 [0.030–0.353], P =0.020), arterial inflammation (0.203 [0.055–0.351], P =0.007), and MACE risk (standardized hazard ratio [95% CI]: 1.927 [1.370–2.711], P =0.001). The effect of NBResilience on MACE risk was significantly mediated by lower arterial inflammation ( P Conclusions: Among individuals who are chronically exposed to socioeconomic or environmental stressors, NBResilience (AmygA 50% reduction in MACE risk, potentially via reduced arterial inflammation. These data raise the possibility that enhancing NBResilience may decrease the burden of cardiovascular disease.
Published: 2020

43. Translating discoveries in Attention-Deficit/Hyperactivity Disorder genomics to an outpatient child and adolescent psychiatric cohort

Author: Pieter J. Vuijk, Ellen B. Braaten, Alysa E. Doyle, B Andi Lee, Jordan W. Smoller, Roy H. Perlis, Hannah S. Lind, Giulio Genovese, Joanna Martin, Sheila M. O'Keefe, Stephen V. Faraone, and Michael R. Capawana
Subjects: Adult, Multifactorial Inheritance, Longitudinal study, medicine.medical_specialty, polygenic risk, Adolescent, behavioral disciplines and activities, Article, clinical translation, Outpatients, mental disorders, Developmental and Educational Psychology, medicine, ADHD, Humans, Attention deficit hyperactivity disorder, 0501 psychology and cognitive sciences, Longitudinal Studies, Child, Psychiatry, business.industry, Aggression, Working memory, 05 social sciences, Discriminant validity, Cognition, Genomics, Odds ratio, medicine.disease, Psychiatry and Mental health, genomic medicine, Attention Deficit Disorder with Hyperactivity, Cohort, medicine.symptom, business, Biomarkers, Genome-Wide Association Study, 050104 developmental & child psychology
Abstract: Objective Genomic discoveries should be investigated in generalizable child psychiatric samples in order to justify and inform studies that will evaluate their use for specific clinical purposes. In youth consecutively referred for neuropsychiatric evaluation, we examined 1) the convergent and discriminant validity of attention-deficit/hyperactivity disorder (ADHD) polygenic risk scores (PRSs) in relation to DSM-based ADHD phenotypes; 2) the association of ADHD PRSs with phenotypes beyond ADHD that share its liability and have implications for outcome; and 3) the extent to which youth with high ADHD PRSs manifest a distinctive clinical profile. Method Participants were 433 youth, ages 7–18 years, from the Longitudinal Study of Genetic Influences on Cognition. We used logistic/linear regression and mixed effects models to examine associations with ADHD-related polygenic variation from the largest ADHD genome-wide association study to date. We replicated key findings in 5,140 adult patients from a local health system biobank. Results Among referred youth, ADHD PRSs were associated with ADHD diagnoses, cross-diagnostic ADHD symptoms and academic impairment (odds ratios ∼1.4; R2 values ∼2%–3%), as well as cross-diagnostic variation in aggression and working memory. In adults, ADHD PRSs were associated with ADHD and phenotypes beyond the condition that have public health implications. Finally, youth with a high ADHD polygenic burden showed a more severe clinical profile than youth with a low burden (β coefficients ∼.2). Conclusion Among child and adolescent outpatients, ADHD polygenic risk was associated with ADHD and related phenotypes as well as clinical severity. These results extend the scientific foundation for studies of ADHD polygenic risk in the clinical setting and highlight directions for further research.
Published: 2020

44. The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

Author: Jonathan R.I. Coleman, Héléna A. Gaspar, Julien Bryois, Gerome Breen, Enda M. Byrne, Andreas J. Forstner, Peter A. Holmans, Christiaan A. de Leeuw, Manuel Mattheisen, Andrew McQuillin, Jennifer M. Whitehead Pavlides, Tune H. Pers, Stephan Ripke, Eli A. Stahl, Stacy Steinberg, Vassily Trubetskoy, Maciej Trzaskowski, Yunpeng Wang, Liam Abbott, Abdel Abdellaoui, Mark J. Adams, Annelie Nordin Adolfsson, Esben Agerbo, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Thomas D. Als, Till F.M. Andlauer, Adebayo Anjorin, Verneri Antilla, Sandra Van der Auwera, Swapnil Awasthi, Silviu-Alin Bacanu, Judith A. Badner, Marie Bækvad-Hansen, Jack D. Barchas, Nicholas Bass, Michael Bauer, Aartjan T.F. Beekman, Richard Belliveau, Sarah E. Bergen, Tim B. Bigdeli, Elisabeth B. Binder, Erlend Bøen, Marco Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, William Byerley, Na Cai, Miquel Casas, Enrique Castelao, Felecia Cerrato, Pablo Cervantes, Kimberly Chambert, Alexander W. Charney, Danfeng Chen, Jane Hvarregaard Christensen, Claire Churchhouse, David St Clair, Toni-Kim Clarke, Lucía Colodro-Conde, William Coryell, Baptiste Couvy-Duchesne, David W. Craig, Gregory E. Crawford, Cristiana Cruceanu, Piotr M. Czerski, Anders M. Dale, Gail Davies, Ian J. Deary, Franziska Degenhardt, Jurgen Del-Favero, J Raymond DePaulo, Eske M. Derks, Nese Direk, Srdjan Djurovic, Amanda L. Dobbyn, Conor V. Dolan, Ashley Dumont, Erin C. Dunn, Thalia C. Eley, Torbjørn Elvsåshagen, Valentina Escott-Price, Chun Chieh Fan, Hilary K. Finucane, Sascha B. Fischer, Matthew Flickinger, Jerome C. Foo, Tatiana M. Foroud, Liz Forty, Josef Frank, Christine Fraser, Nelson B. Freimer, Louise Frisén, Katrin Gade, Diane Gage, Julie Garnham, Claudia Giambartolomei, Fernando S. Goes, Jaqueline Goldstein, Scott D. Gordon, Katherine Gordon-Smith, Elaine K. Green, Melissa J. Green, Tiffany A. Greenwood, Jakob Grove, Weihua Guan, Lynsey S. Hall, Marian L. Hamshere, Christine Søholm Hansen, Thomas F. Hansen, Martin Hautzinger, Urs Heilbronner, Albert M. van Hemert, Stefan Herms, Ian B. Hickie, Maria Hipolito, Per Hoffmann, Dominic Holland, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, Laura Huckins, Marcus Ising, Stéphane Jamain, Rick Jansen, Jessica S. Johnson, Simone de Jong, Eric Jorgenson, Anders Juréus, Radhika Kandaswamy, Robert Karlsson, James L. Kennedy, Farnush Farhadi Hassan Kiadeh, Sarah Kittel-Schneider, James A. Knowles, Manolis Kogevinas, Isaac S. Kohane, Anna C. Koller, Julia Kraft, Warren W. Kretzschmar, Jesper Krogh, Ralph Kupka, Zoltán Kutalik, Catharina Lavebratt, Jacob Lawrence, William B. Lawson, Markus Leber, Phil H. Lee, Shawn E. Levy, Jun Z. Li, Yihan Li, Penelope A. Lind, Chunyu Liu, Loes M. Olde Loohuis, Anna Maaser, Donald J. MacIntyre, Dean F. MacKinnon, Pamela B. Mahon, Wolfgang Maier, Robert M. Maier, Jonathan Marchini, Lina Martinsson, Hamdi Mbarek, Steve McCarroll, Patrick McGrath, Peter McGuffin, Melvin G. McInnis, James D. McKay, Helena Medeiros, Sarah E. Medland, Divya Mehta, Fan Meng, Christel M. Middeldorp, Evelin Mihailov, Yuri Milaneschi, Lili Milani, Saira Saeed Mirza, Francis M. Mondimore, Grant W. Montgomery, Derek W. Morris, Sara Mostafavi, Thomas W. Mühleisen, Niamh Mullins, Matthias Nauck, Bernard Ng, Hoang Nguyen, Caroline M. Nievergelt, Michel G. Nivard, Evaristus A. Nwulia, Dale R. Nyholt, Claire O'Donovan, Paul F. O'Reilly, Anil P.S. Ori, Lilijana Oruc, Urban Ösby, Hogni Oskarsson, Jodie N. Painter, José Guzman Parra, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Amy Perry, Roseann E. Peterson, Erik Pettersson, Wouter J. Peyrot, Andrea Pfennig, Giorgio Pistis, Shaun M. Purcell, Jorge A. Quiroz, Per Qvist, Eline J. Regeer, Andreas Reif, Céline S. Reinbold, John P. Rice, Brien P. Riley, Fabio Rivas, Margarita Rivera, Panos Roussos, Douglas M. Ruderfer, Euijung Ryu, Cristina Sánchez-Mora, Alan F. Schatzberg, William A. Scheftner, Robert Schoevers, Nicholas J. Schork, Eva C. Schulte, Tatyana Shehktman, Ling Shen, Jianxin Shi, Paul D. Shilling, Stanley I. Shyn, Engilbert Sigurdsson, Claire Slaney, Olav B. Smeland, Johannes H. Smit, Daniel J. Smith, Janet L. Sobell, Anne T. Spijker, Michael Steffens, John S. Strauss, Fabian Streit, Jana Strohmaier, Szabolcs Szelinger, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Robert C. Thompson, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, André G. Uitterlinden, Daniel Umbricht, Helmut Vedder, Alexander Viktorin, Peter M. Visscher, Weiqing Wang, Stanley J. Watson, Bradley T. Webb, Cynthia Shannon Weickert, Thomas W. Weickert, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Stephanie H. Witt, Yang Wu, Hualin S. Xi, Wei Xu, Jian Yang, Allan H. Young, Peter Zandi, Peng Zhang, Futao Zhang, Sebastian Zollner, Rolf Adolfsson, Ingrid Agartz, Martin Alda, Volker Arolt, Lena Backlund, Bernhard T. Baune, Frank Bellivier, Klaus Berger, Wade H. Berrettini, Joanna M. Biernacka, Douglas H.R. Blackwood, Michael Boehnke, Dorret I. Boomsma, Aiden Corvin, Nicholas Craddock, Mark J. Daly, Udo Dannlowski, Enrico Domenici, Katharina Domschke, Tõnu Esko, Bruno Etain, Mark Frye, Janice M. Fullerton, Elliot S. Gershon, E.J.C. de Geus, Michael Gill, Fernando Goes, Hans J. Grabe, Maria Grigoroiu-Serbanescu, Steven P. Hamilton, Joanna Hauser, Caroline Hayward, Andrew C. Heath, David M. Hougaard, Christina M. Hultman, Ian Jones, Lisa A. Jones, René S. Kahn, Kenneth S. Kendler, George Kirov, Stefan Kloiber, Mikael Landén, Marion Leboyer, Glyn Lewis, Qingqin S. Li, Jolanta Lissowska, Susanne Lucae, Pamela A.F. Madden, Patrik K. Magnusson, Nicholas G. Martin, Fermin Mayoral, Susan L. McElroy, Andrew M. McIntosh, Francis J. McMahon, Ingrid Melle, Andres Metspalu, Philip B. Mitchell, Gunnar Morken, Ole Mors, Preben Bo Mortensen, Bertram Müller-Myhsok, Richard M. Myers, Benjamin M. Neale, Vishwajit Nimgaonkar, Merete Nordentoft, Markus M. Nöthen, Michael C. O'Donovan, Ketil J. Oedegaard, Michael J. Owen, Sara A. Paciga, Carlos Pato, Michele T. Pato, Nancy L. Pedersen, Brenda W.J. H. Penninx, Roy H. Perlis, David J. Porteous, Danielle Posthuma, James B. Potash, Martin Preisig, Josep Antoni Ramos-Quiroga, Marta Ribasés, Marcella Rietschel, Guy A. Rouleau, Catherine Schaefer, Martin Schalling, Peter R. Schofield, Thomas G. Schulze, Alessandro Serretti, Jordan W. Smoller, Hreinn Stefansson, Kari Stefansson, Eystein Stordal, Henning Tiemeier, Gustavo Turecki, Rudolf Uher, Arne E. Vaaler, Eduard Vieta, John B. Vincent, Henry Völzke, Myrna M. Weissman, Thomas Werge, Ole A. Andreassen, Anders D. Børglum, Sven Cichon, Howard J. Edenberg, Arianna Di Florio, John Kelsoe, Douglas F. Levinson, Cathryn M. Lewis, John I. Nurnberger, Roel A. Ophoff, Laura J. Scott, Pamela Sklar, Patrick F. Sullivan, Naomi R. Wray, APH - Methodology, Biological Psychology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, APH - Mental Health, Amsterdam Neuroscience - Complex Trait Genetics, Complex Trait Genetics, Epidemiology, Erasmus MC other, Urology, Psychiatry, Internal Medicine, Medical Informatics, Immunology, Child and Adolescent Psychiatry / Psychology, Adult Psychiatry, Coleman J.R.I., Gaspar H.A., Bryois J., Byrne E.M., Forstner A.J., Holmans P.A., de Leeuw C.A., Mattheisen M., McQuillin A., Whitehead Pavlides J.M., Pers T.H., Ripke S., Stahl E.A., Steinberg S., Trubetskoy V., Trzaskowski M., Wang Y., Abbott L., Abdellaoui A., Adams M.J., Adolfsson A.N., Agerbo E., Akil H., Albani D., Alliey-Rodriguez N., Als T.D., Andlauer T.F.M., Anjorin A., Antilla V., Van der Auwera S., Awasthi S., Bacanu S.-A., Badner J.A., Baekvad-Hansen M., Barchas J.D., Bass N., Bauer M., Beekman A.T.F., Belliveau R., Bergen S.E., Bigdeli T.B., Binder E.B., Boen E., Boks M., Boocock J., Budde M., Bunney W., Burmeister M., Buttenschon H.N., Bybjerg-Grauholm J., Byerley W., Cai N., Casas M., Castelao E., Cerrato F., Cervantes P., Chambert K., Charney A.W., Chen D., Christensen J.H., Churchhouse C., St Clair D., Clarke T.-K., Colodro-Conde L., Coryell W., Couvy-Duchesne B., Craig D.W., Crawford G.E., Cruceanu C., Czerski P.M., Dale A.M., Davies G., Deary I.J., Degenhardt F., Del-Favero J., DePaulo J.R., Derks E.M., Direk N., Djurovic S., Dobbyn A.L., Dolan C.V., Dumont A., Dunn E.C., Eley T.C., Elvsashagen T., Escott-Price V., Fan C.C., Finucane H.K., Fischer S.B., Flickinger M., Foo J.C., Foroud T.M., Forty L., Frank J., Fraser C., Freimer N.B., Frisen L., Gade K., Gage D., Garnham J., Giambartolomei C., Goes F.S., Goldstein J., Gordon S.D., Gordon-Smith K., Green E.K., Green M.J., Greenwood T.A., Grove J., Guan W., Hall L.S., Hamshere M.L., Hansen C.S., Hansen T.F., Hautzinger M., Heilbronner U., van Hemert A.M., Herms S., Hickie I.B., Hipolito M., Hoffmann P., Holland D., Homuth G., Horn C., Hottenga J.-J., Huckins L., Ising M., Jamain S., Jansen R., Johnson J.S., de Jong S., Jorgenson E., Jureus A., Kandaswamy R., Karlsson R., Kennedy J.L., Hassan Kiadeh F.F., Kittel-Schneider S., Knowles J.A., Kogevinas M., Kohane I.S., Koller A.C., Kraft J., Kretzschmar W.W., Krogh J., Kupka R., Kutalik Z., Lavebratt C., Lawrence J., Lawson W.B., Leber M., Lee P.H., Levy S.E., Li J.Z., Li Y., Lind P.A., Liu C., Olde Loohuis L.M., Maaser A., MacIntyre D.J., MacKinnon D.F., Mahon P.B., Maier W., Maier R.M., Marchini J., Martinsson L., Mbarek H., McCarroll S., McGrath P., McGuffin P., McInnis M.G., McKay J.D., Medeiros H., Medland S.E., Mehta D., Meng F., Middeldorp C.M., Mihailov E., Milaneschi Y., Milani L., Mirza S.S., Mondimore F.M., Montgomery G.W., Morris D.W., Mostafavi S., Muhleisen T.W., Mullins N., Nauck M., Ng B., Nguyen H., Nievergelt C.M., Nivard M.G., Nwulia E.A., Nyholt D.R., O'Donovan C., O'Reilly P.F., Ori A.P.S., Oruc L., Osby U., Oskarsson H., Painter J.N., Parra J.G., Pedersen C.B., Pedersen M.G., Perry A., Peterson R.E., Pettersson E., Peyrot W.J., Pfennig A., Pistis G., Purcell S.M., Quiroz J.A., Qvist P., Regeer E.J., Reif A., Reinbold C.S., Rice J.P., Riley B.P., Rivas F., Rivera M., Roussos P., Ruderfer D.M., Ryu E., Sanchez-Mora C., Schatzberg A.F., Scheftner W.A., Schoevers R., Schork N.J., Schulte E.C., Shehktman T., Shen L., Shi J., Shilling P.D., Shyn S.I., Sigurdsson E., Slaney C., Smeland O.B., Smit J.H., Smith D.J., Sobell J.L., Spijker A.T., Steffens M., Strauss J.S., Streit F., Strohmaier J., Szelinger S., Tansey K.E., Teismann H., Teumer A., Thompson R.C., Thompson W., Thomson P.A., Thorgeirsson T.E., Traylor M., Treutlein J., Uitterlinden A.G., Umbricht D., Vedder H., Viktorin A., Visscher P.M., Wang W., Watson S.J., Webb B.T., Weickert C.S., Weickert T.W., Weinsheimer S.M., Wellmann J., Willemsen G., Witt S.H., Wu Y., Xi H.S., Xu W., Yang J., Young A.H., Zandi P., Zhang P., Zhang F., Zollner S., Adolfsson R., Agartz I., Alda M., Arolt V., Backlund L., Baune B.T., Bellivier F., Berger K., Berrettini W.H., Biernacka J.M., Blackwood D.H.R., Boehnke M., Boomsma D.I., Corvin A., Craddock N., Daly M.J., Dannlowski U., Domenici E., Domschke K., Esko T., Etain B., Frye M., Fullerton J.M., Gershon E.S., de Geus E.J.C., Gill M., Goes F., Grabe H.J., Grigoroiu-Serbanescu M., Hamilton S.P., Hauser J., Hayward C., Heath A.C., Hougaard D.M., Hultman C.M., Jones I., Jones L.A., Kahn R.S., Kendler K.S., Kirov G., Kloiber S., Landen M., Leboyer M., Lewis G., Li Q.S., Lissowska J., Lucae S., Madden P.A.F., Magnusson P.K., Martin N.G., Mayoral F., McElroy S.L., McIntosh A.M., McMahon F.J., Melle I., Metspalu A., Mitchell P.B., Morken G., Mors O., Mortensen P.B., Muller-Myhsok B., Myers R.M., Neale B.M., Nimgaonkar V., Nordentoft M., Nothen M.M., O'Donovan M.C., Oedegaard K.J., Owen M.J., Paciga S.A., Pato C., Pato M.T., Pedersen N.L., Penninx B.W.J.H., Perlis R.H., Porteous D.J., Posthuma D., Potash J.B., Preisig M., Ramos-Quiroga J.A., Ribases M., Rietschel M., Rouleau G.A., Schaefer C., Schalling M., Schofield P.R., Schulze T.G., Serretti A., Smoller J.W., Stefansson H., Stefansson K., Stordal E., Tiemeier H., Turecki G., Uher R., Vaaler A.E., Vieta E., Vincent J.B., Volzke H., Weissman M.M., Werge T., Andreassen O.A., Borglum A.D., Cichon S., Edenberg H.J., Di Florio A., Kelsoe J., Levinson D.F., Lewis C.M., Nurnberger J.I., Ophoff R.A., Scott L.J., Sklar P., Sullivan P.F., Wray N.R., and Breen G.
Subjects: 0301 basic medicine, Netherlands Twin Register (NTR), Genetic correlation, Genome-wide association study, Mood Disorder, Bipolar disorder, Population, BF, Genomics, Major depressive disorder, Affective disorder, Article, Mice, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, mental disorders, medicine, Animals, ddc:610, education, Depression (differential diagnoses), Biological Psychiatry, 030304 developmental biology, Genetic association, Genetics, Depressive Disorder, Major, 0303 health sciences, education.field_of_study, Animal, business.industry, Risk Factor, medicine.disease, 3. Good health, Affective disorders, 030104 developmental biology, Mood, Mood disorders, RC0321, Biological psychiatry, business, 030217 neurology & neurosurgery, Clinical psychology
Abstract: BackgroundMood disorders (including major depressive disorder and bipolar disorder) affect 10-20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Despite their diagnostic distinction, multiple approaches have shown considerable sharing of risk factors across the mood disorders.MethodsTo clarify their shared molecular genetic basis, and to highlight disorder-specific associations, we meta-analysed data from the latest Psychiatric Genomics Consortium (PGC) genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; non-overlapping N = 609,424).ResultsSeventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More genome-wide significant loci from the PGC analysis of major depression than bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment – positive in bipolar disorder but negative in major depressive disorder.ConclusionsThe mood disorders share several genetic associations, and can be combined effectively to increase variant discovery. However, we demonstrate several differences between these disorders. Analysing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.
Published: 2020

45. Risk of COVID-19 among frontline healthcare workers and the general community: a prospective cohort study

Author: Long H Nguyen, David A Drew, Mark S Graham, Amit D Joshi, Chuan-Guo Guo, Wenjie Ma, Raaj S Mehta, Erica T Warner, Daniel R Sikavi, Chun-Han Lo, Sohee Kwon, Mingyang Song, Lorelei A Mucci, Meir J Stampfer, Walter C Willett, A Heather Eliassen, Jaime E Hart, Jorge E Chavarro, Janet W Rich-Edwards, Richard Davies, Joan Capdevila, Karla A Lee, Mary Ni Lochlainn, Thomas Varsavsky, Carole H Sudre, M Jorge Cardoso, Jonathan Wolf, Tim D Spector, Sebastien Ourselin, Claire J Steves, Andrew T Chan, Christine M. Albert, Gabriella Andreotti, Bijal Bala, Bijal A. Balasubramanian, Laura E. Beane-Freeman, John S. Brownstein, Fiona J. Bruinsma, Joe Coresh, Rui Costa, Annie N. Cowan, Anusila Deka, Sandra L. Deming-Halverson, Maria Elena Martinez, Michael E. Ernst, Jane C. Figueiredo, Pedro Fortuna, Paul W. Franks, Laura Beane Freeman, Christopher D. Gardner, Irene M. Ghobrial, Christopher A. Haiman, Janet E. Hall, Jae H. Kang, Brenda Kirpach, Karestan C. Koenen, Laura D. Kubzansky, James V. Lacey, Jr, Loic Le Marchand, Xihong Lin, Pam Lutsey, Catherine R. Marinac, Roger L. Milne, Anne M. Murray, Denis Nash, Julie R. Palmer, Alpa V. Patel, Eric Pierce, McKaylee M. Robertson, Lynn Rosenberg, Dale P. Sandler, Shepherd H. Schurman, Kara Sewalk, Shreela V. Sharma, Christopher J. Sidey-Gibbons, Liz Slevin, Jordan W.. Smoller, Claire J. Steves, Maarit I. Tiirikainen, Scott T. Weiss, Lynne R. Wilkens, Feng Zhang, and Broad Institute of MIT and Harvard
Subjects: Male, 01 natural sciences, Occupational safety and health, 0302 clinical medicine, COVID-19 Testing, Health care, Medicine, 030212 general & internal medicine, Prospective Studies, Prospective cohort study, Hazard ratio, Articles, Middle Aged, Mobile Applications, 3. Good health, Female, Risk assessment, Coronavirus Infections, Incident report, Cohort study, Adult, medicine.medical_specialty, Infectious Disease Transmission, Patient-to-Professional, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), government.form_of_government, Health Personnel, Pneumonia, Viral, Risk Assessment, Article, 03 medical and health sciences, Young Adult, Environmental health, Humans, 0101 mathematics, Personal protective equipment, Pandemics, Personal Protective Equipment, Proportional hazards model, business.industry, Clinical Laboratory Techniques, 010102 general mathematics, Public Health, Environmental and Occupational Health, COVID-19, United Kingdom, United States, Emergency medicine, government, Observational study, Self Report, business, 030217 neurology & neurosurgery
Abstract: BackgroundData for frontline healthcare workers (HCWs) and risk of SARS-CoV-2 infection are limited and whether personal protective equipment (PPE) mitigates this risk is unknown. We evaluated risk for COVID-19 among frontline HCWs compared to the general community and the influence of PPE.MethodsWe performed a prospective cohort study of the general community, including frontline HCWs, who reported information through the COVID Symptom Study smartphone application beginning on March 24 (United Kingdom, U.K.) and March 29 (United States, U.S.) through April 23, 2020. We used Cox proportional hazards modeling to estimate multivariate-adjusted hazard ratios (aHRs) of a positive COVID-19 test.FindingsAmong 2,035,395 community individuals and 99,795 frontline HCWs, we documented 5,545 incident reports of a positive COVID-19 test over 34,435,272 person-days. Compared with the general community, frontline HCWs had an aHR of 11·6 (95% CI: 10·9 to 12·3) for reporting a positive test. The corresponding aHR was 3·40 (95% CI: 3·37 to 3·43) using an inverse probability weighted Cox model adjusting for the likelihood of receiving a test. A symptom-based classifier of predicted COVID-19 yielded similar risk estimates. Compared with HCWs reporting adequate PPE, the aHRs for reporting a positive test were 1·46 (95% CI: 1·21 to 1·76) for those reporting PPE reuse and 1·31 (95% CI: 1·10 to 1·56) for reporting inadequate PPE. Compared with HCWs reporting adequate PPE who did not care for COVID-19 patients, HCWs caring for patients with documented COVID-19 had aHRs for a positive test of 4·83 (95% CI: 3·99 to 5·85) if they had adequate PPE, 5·06 (95% CI: 3·90 to 6·57) for reused PPE, and 5·91 (95% CI: 4·53 to 7·71) for inadequate PPE.InterpretationFrontline HCWs had a significantly increased risk of COVID-19 infection, highest among HCWs who reused PPE or had inadequate access to PPE. However, adequate supplies of PPE did not completely mitigate high-risk exposures.FundingZoe Global Ltd., Wellcome Trust, EPSRC, NIHR, UK Research and Innovation, Alzheimer’s Society, NIH, NIOSH, Massachusetts Consortium on Pathogen ReadinessRESEARCH IN CONTEXTEvidence before this studyThe prolonged course of the coronavirus disease 2019 (COVID-19) pandemic, coupled with sustained challenges supplying adequate personal protective equipment (PPE) for frontline healthcare workers (HCW), have strained global healthcare systems in an unprecedented fashion. Despite growing awareness of this problem, there are few data to inform policy makers on the risk of COVID-19 among HCWs and the impact of PPE on their disease burden. Prior reports of HCW infections are based on cross sectional data with limited individual-level information on risk factors for infection. A PubMed search for articles published between January 1, 2020 and May 5, 2020 using the terms “covid-19”, “healthcare workers”, and “personal protective equipment,” yielded no population-scale investigations exploring this topic.Added value of this studyIn a prospective study of 2,135,190 individuals, frontline HCWs may have up to a 12-fold increased risk of reporting a positive COVID-19 test. Compared with those who reported adequate availability of PPE, frontline HCWs with inadequate PPE had a 31% increase in risk. However, adequate availability of PPE did not completely reduce risk among HCWs caring for COVID-19 patients.Implications of all the available evidenceBeyond ensuring adequate availability of PPE, additional efforts to protect HCWs from COVID-19 are needed, particularly as lockdown is lifted in many regions of the world.
Published: 2020

46. The All of Us Research Program: data quality, utility, and diversity

Author: Dan M. Roden, Cheryl R. Clark, Hoda Anton-Culver, Melissa A. Basford, Parinda Khatri, Mona N. Fouad, Stephen O. Sodeke, Paul A. Harris, Joshua C. Denny, Consuelo H. Wilkins, Robert M. Cronin, Mine S. Cicek, Scott J. Hebbring, Jun Qian, John Wilbanks, Karthik N. Muthuraman, David Goldstein, Lucila Ohno-Machado, Kelsey R. Mayo, Lina Sulieman, Roxana Loperena, Nicole A. Deflaux, Kelly Gebo, Abel N. Kho, Philip Greenland, Eric Boerwinkle, Anthony Philippakis, George Hripcsak, Brian K. Ahmedani, Stephanie A. Devaney, Elizabeth W. Karlson, David J. Schlueter, Maria Argos, Justin Hentges, Elizabeth Cohn, Karthik Natarajan, Alese E. Halvorson, Christopher J. O'Donnell, Bruce R. Korf, David Glazer, Jordan W. Smoller, Francis Ratsimbazafy, Hua Xu, Robert J. Carroll, Christopher Lunt, Sheri D. Schully, and Andrea H. Ramirez
Subjects: Gerontology, Research program, education.field_of_study, business.industry, Population, Cloud computing, Precision medicine, Data quality, Cohort, Survey data collection, Relevance (information retrieval), business, Psychology, education
Abstract: ImportanceThe All of Us Research Program hypothesizes that accruing one million or more diverse participants engaged in a longitudinal research cohort will advance precision medicine and ultimately improve human health. Launched nationally in 2018, to date All of Us has recruited more than 345,000 participants. All of Us plans to open beta access to researchers in May 2020.ObjectiveTo demonstrate the quality, utility, and diversity of the All of Us Research Program’s initial data release and beta launch of the cloud-based analysis platform, the cloud-based Researcher Workbench.EvidenceWe analyzed the initial All of Us data release, comprising surveys, physical measurements (PM), and electronic health record (EHR) data, to characterize All of Us participants including self-reported descriptors of diversity. Data depth, density, and quality were evaluated using medication sequencing analyses for depression and type 2 diabetes. Replication of known oncologic associations with smoking exposure ascertained by EHR and survey data and calculation of population-based atherosclerotic cardiovascular disease risk scores demonstrated the utility of data and platform capability.FindingsThe beta launch of the All of Us Researcher Workbench contains data on 224,143 participants. Seventy-seven percent of this cohort were identified as Underrepresented in Biomedical Research (UBR) including over forty-eight percent self-reporting non-White race. Medication usage patterns in common diseases depression and type 2 diabetes replicated prior findings previously reported in the literature and showed differences based on race. Oncologic associations with smoking were replicated and effect sizes compared for EHR and survey exposures finding general agreement. A cardiovascular disease score was calculated utilizing multiple data elements curated across sources. The cloud-based architecture built in the Researcher Workbench provided secure access and powerful computational resources at a low cost. All analyses have been made available for replication and reuse by registered researchers.Conclusions and RelevanceThe All of Us Research Program’s initial release of cohort data contains longitudinal and multidimensional data on diverse participants that replicate known associations. This dataset and the cloud-based Researcher Workbench advance the mission of All of Us to make data widely and securely available to researchers to improve human health and advance precision medicine.
Published: 2020

47. Making the right moves to prevent depression in young people

Author: Jordan W. Smoller and Karmel W. Choi
Subjects: medicine.medical_specialty, Depressive Disorder, Adolescent, business.industry, Depression, MEDLINE, Human factors and ergonomics, Poison control, Suicide prevention, Occupational safety and health, Article, Psychiatry and Mental health, Injury prevention, Medicine, Humans, Prospective Studies, Sedentary Behavior, Prospective cohort study, business, Psychiatry, Exercise, Biological Psychiatry, Depression (differential diagnoses)
Abstract: Summary Background Identifying modifiable risk factors is essential to reduce the prevalence adolescent depression. Self-report data suggest that physical activity and sedentary behaviour might be associated with depressive symptoms in adolescents. We examined associations between depressive symptoms and objectively measured physical activity and sedentary behaviour in adolescents. Methods From a population-based cohort of adolescents whose mothers were invited to participate in the Avon Longitudinal Study of Parents and Children (ALSPAC) study, we included participants with at least one accelerometer recording and a Clinical Interview Schedule-Revised (CIS-R) depression score at age 17·8 years (reported as age 18 years hereafter). Amounts of time spent in sedentary behaviour and physical activity (light or moderate-to-vigorous) were measured with accelerometers at around 12 years, 14 years, and 16 years of age. Total physical activity was also recorded as count per minute (CPM), with raw accelerometer counts averaged over 60 s epochs. Associations between the physical activity and sedentary behaviour variables and depression (CIS-R) scores at age 18 years were analysed with regression and group-based trajectory modelling. Findings 4257 adolescents from the 14 901 enrolled in the ALSPAC study had a CIS-R depression score at age 18 years. Longitudinal analyses included 2486 participants at age 12 years, 1938 at age 14 years, and 1220 at age 16 years. Total follow-up time was 6 years. Total physical activity decreased between 12 years and 16 years of age, driven by decreasing durations of light activity (mean 325·66 min/day [SD 58·09] at 12 years; 244·94 min/day [55·08] at 16 years) and increasing sedentary behaviour (430·99 min/day [65·80]; 523·02 min/day [65·25]). Higher depression scores at 18 years were associated with a 60 min/day increase in sedentary behaviour at 12 years (incidence rate ratio [IRR] 1·111 [95% CI 1·051–1·176]), 14 years (1·080 [1·012–1·152]), and 16 years of age (1·107 [1·015–1·208]). Depression scores at 18 years were lower for every additional 60 min/day of light activity at 12 years (0·904 [0·850–0·961]), 14 years (0·922 [0·857–0·992]), and 16 years of age (0·889 [0·809–0·974]). Group-based trajectory modelling across 12–16 years of age identified three latent subgroups of sedentary behaviour and activity levels. Depression scores were higher in those with persistently high (IRR 1·282 [95% CI 1·061–1·548]) and persistently average (1·249 [1·078–1·446]) sedentary behaviour compared with those with persistently low sedentary behaviour, and were lower in those with persistently high levels of light activity (0·804 [0·652–0·990]) compared with those with persistently low levels of light activity. Moderate-to-vigorous physical activity (per 15 min/day increase) at age 12 years (0·910 [0·857–0·966]) and total physical activity (per 100 CPM increase) at ages 12 years (0·941 [0·910–0·972]) and 14 years (0·965 [0·932–0·999]), were negatively associated with depressive symptoms. Interpretation Sedentary behaviour displaces light activity throughout adolescence, and is associated with a greater risk of depressive symptoms at 18 years of age. Increasing light activity and decreasing sedentary behaviour during adolescence could be an important target for public health interventions aimed at reducing the prevalence of depression. Funding Details of funding are provided in the Acknowledgments.
Published: 2020

48. N-glycome analysis detects dysglycosylation missed by conventional methods in SLC39A8 deficiency

Author: Thorsten Marquardt, Saskia Biskup, Corbin Schwanke, Janine Reunert, Jaclyn Haven, Richard D. Cummings, Julien H Park, Jonathan Schoof, Susanne Hoffmann, Abdallah F Elias, Marianne Grüneberg, Manfred Fobker, Robert G. Mealer, Stephan Rust, Jordan W. Smoller, and Ute Mangels
Subjects: Male, congenital, hereditary, and neonatal diseases and abnormalities, Glycosylation, Adolescent, glycosylation, Cell- och molekylärbiologi, macromolecular substances, Basal Ganglia, Mass Spectrometry, Article, chemistry.chemical_compound, symbols.namesake, Young Adult, Congenital Disorders of Glycosylation, Exome Sequencing, Genetics, Medicine, Humans, MALDI-TOF MS, Child, Exome, Cation Transport Proteins, Genetics (clinical), Exome sequencing, Chromatography, High Pressure Liquid, Whole blood, chemistry.chemical_classification, Sanger sequencing, Manganese, business.industry, Transferrin, Infant, Molecular biology, Glycome, Magnetic Resonance Imaging, Hyperintensity, Phenotype, chemistry, Child, Preschool, symbols, manganese, Female, business, Cell and Molecular Biology, congenital disorders of glycosylation
Abstract: PURPOSE: Congenital disorders of glycosylation (CDG) are a growing group of inborn metabolic disorders with multiorgan presentation. SLC39A8-CDG is a severe subtype caused by biallelic mutations in the manganese transporter SLC39A8, reducing levels of this essential cofactor for many enzymes including glycosyltransferases. The current diagnostic standard for disorders of N-glycosylation is the analysis of serum transferrin. PATIENTS AND METHODS: Exome and Sanger sequencing were performed in two patients with severe neurodevelopmental phenotypes suggestive of CDG. Transferrin glycosylation was analyzed by high performance liquid chromatography (HPLC) and isoelectric focusing (IEF), in addition to comprehensive N-glycome analysis using MALDI-TOF MS. Atomic absorption spectroscopy was used to quantify whole blood manganese levels. RESULTS: Both patients presented with a severe, multisystem disorder and a complex neurological phenotype. MRI revealed a Leigh-like syndrome with bilateral T2 hyperintensities of the basal ganglia. In patient 1, exome sequencing identified the previously undescribed homozygous variant c.608T>C [p.F203S] in SLC39A8. Patient 2 was found to be homozygous for c.112G>C [p.G38R]. Both individuals showed a reduction of whole blood manganese, though transferrin glycosylation was normal. N-glycome using MALDI-TOF MS identified an increase of the asialo-agalactosylated precursor N-glycan A2G1S1 and a decrease in bisected structures. In addition, analysis of heterozygous CDG-allele carriers identified similar but less severe glycosylation changes. CONCLUSIONS: Despite its reliance as a clinical gold standard, analysis of transferrin glycosylation cannot be categorically used to rule out SLC39A8-CDG. These results emphasize that SLC39A8-CDG presents as a spectrum of dysregulated glycosylation, and mass spectrometry is an important tool for identifying deficiencies not detected by conventional methods. SYNOPSIS: MALDI-TOF MS identifies subtle dysglycosylation not detected by conventional methods of glycosylation analysis in SLC39A8-CDG.
Published: 2020

49. Genetic overlap between vascular pathologies and Alzheimer's dementia and potential causal mechanisms

Author: Yen Feng Lin, Albert V. Smith, Rebecca A. Betensky, Deborah Blacker, Thor Aspelund, Lenore J. Launer, Vilmundur Gudnason, and Jordan W. Smoller
Subjects: Male, 0301 basic medicine, Apolipoprotein E, Mediation (statistics), Epidemiology, Single-nucleotide polymorphism, Disease, Neuropsychological Tests, Bioinformatics, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, Apolipoproteins E, 0302 clinical medicine, Developmental Neuroscience, Alzheimer Disease, Risk Factors, medicine, Humans, Dementia, Cognitive Dysfunction, Alzheimer s dementia, Aged, business.industry, Health Policy, Brain, Cognition, medicine.disease, White Matter, Peptide Fragments, Hyperintensity, Psychiatry and Mental health, 030104 developmental biology, Microvessels, Female, Neurology (clinical), Geriatrics and Gerontology, business, 030217 neurology & neurosurgery
Abstract: Introduction We sought to examine the genetic overlap between vascular pathologies and Alzheimer's disease (AD) dementia, and the potential mediating role of vascular pathologies between AD-related genetic variants and late-life cognition. Methods For 2907 stroke-free older individuals, we examined the association of polygenic risk scores for AD dementia (ADPRSs) with vascular pathologies and with cognition. Mediation analyses addressed whether association between ADPRSs and cognition was mediated by a vascular pathology. Results ADPRSs were associated with lobar cerebral microbleeds, white matter lesion load, and coronary artery calcification, mostly explained by single nucleotide polymorphisms in the 19q13 region. The effect of ADPRSs on cognition was partially but significantly mediated by cerebral microbleeds, white matter lesions, and coronary artery calcification. Discussion Our findings provide evidence for genetic overlap, mostly due to apolipoprotein E ( APOE ) gene, between vascular pathologies and AD dementia. The association between AD polygenic risk and late-life cognition is mediated in part via effects on vascular pathologies.
Published: 2018

50. Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System

Author: Ronald C. Kessler, Mark S. Bauer, Todd M. Bishop, Olga V. Demler, Steven K. Dobscha, Sarah M. Gildea, Joseph L. Goulet, Elizabeth Karras, Julie Kreyenbuhl, Sara J. Landes, Howard Liu, Alex R. Luedtke, Patrick Mair, William H. B. McAuliffe, Matthew Nock, Maria Petukhova, Wilfred R. Pigeon, Nancy A. Sampson, Jordan W. Smoller, Lauren M. Weinstock, and Robert M. Bossarte
Subjects: medicine.medical_specialty, lcsh:RC435-571, National Death Index, 03 medical and health sciences, 0302 clinical medicine, lcsh:Psychiatry, Hospital discharge, Medicine, Psychiatric hospital, Social determinants of health, super learner, suicide, Original Research, Psychiatry, business.industry, Case manager, Case management, Veterans health, intensive case management, 030227 psychiatry, predictive analytics, Psychiatry and Mental health, machine learning, Emergency medicine, business, 030217 neurology & neurosurgery, Psychopathology
Abstract: There is a very high suicide rate in the year after psychiatric hospital discharge. Intensive postdischarge case management programs can address this problem but are not cost-effective for all patients. This issue can be addressed by developing a risk model to predict which inpatients might need such a program. We developed such a model for the 391,018 short-term psychiatric hospital admissions of US veterans in Veterans Health Administration (VHA) hospitals 2010–2013. Records were linked with the National Death Index to determine suicide within 12 months of hospital discharge (n=771). The Super Learner ensemble machine learning method was used to predict these suicides for time horizon between 1 week and 12 months after discharge in a 70% training sample. Accuracy was validated in the remaining 30% holdout sample. Predictors included VHA administrative variables and small area geocode data linked to patient home addresses. The models had AUC=.79–.82 for time horizons between 1 week and 6 months and AUC=.74 for 12 months. An analysis of operating characteristics showed that 22.4%–32.2% of patients who died by suicide would have been reached if intensive case management was provided to the 5% of patients with highest predicted suicide risk. Positive predictive value (PPV) at this higher threshold ranged from 1.2% over 12 months to 3.8% per case manager year over 1 week. Focusing on the low end of the risk spectrum, the 40% of patients classified as having lowest risk account for 0%–9.7% of suicides across time horizons. Variable importance analysis shows that 51.1% of model performance is due to psychopathological risk factors accounted, 26.2% to social determinants of health, 14.8% to prior history of suicidal behaviors, and 6.6% to physical disorders. The paper closes with a discussion of next steps in refining the model and prospects for developing a parallel precision treatment model.
Published: 2019

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Journal

Database

Publisher

181 results on '"Jordan W. Smoller"'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources