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1. Association of Race and Major Adverse Cardiac Events (MACE): The Atherosclerosis Risk in Communities (ARIC) Cohort

Author

Ericha G Franey, Donna Kritz-Silverstein, Erin L Richard, John E Alcaraz, Caroline M Nievergelt, Richard A Shaffer, and Vibha Bhatnagar

Subjects
Geriatrics, RC952-954.6
Abstract

Background and Aims. To evaluate the association of self-reported race with major adverse cardiac events (MACE) and modification of this association by paraoxonase gene (PON1, PON2, and PON3) single nucleotide polymorphisms (SNPs). Methods. Included in this longitudinal study were 12,770 black or white participants from the Atherosclerosis Risk in Communities (ARIC) cohort who completed a baseline visit (1987–1989) with PON genotyping. Demographic, behavioral, and health information was obtained at baseline. MACE was defined as first occurrence of myocardial infarction, stroke, or CHD-related death through 2004. Cox proportional hazards regression was used to evaluate the association between race and MACE after adjustment for age, gender, and other demographic and cardiovascular risk factors such as diabetes and hypertension. Modification of the association between PON SNPs and MACE was also assessed. Results. Blacks comprised 24.6% of the ARIC cohort; overall, 14.0% of participants developed MACE. Compared with whites, blacks had 1.24 times greater hazard of MACE (OR = 1.24,95%CI = 1.10,1.39) than whites after adjusting for age, gender, BMI, cigarette and alcohol use, educational and marital status, and aspirin use. This association became nonsignificant after further adjustment for high cholesterol, diabetes, and hypertension. None of the evaluated SNPs met the significance level (p

Published
2020
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2. Genetic Overlap Between Alzheimer’s Disease and Bipolar Disorder Implicates the MARK2 and VAC14 Genes

Author

Ole Kristian Drange, Olav Bjerkehagen Smeland, Alexey A. Shadrin, Per Ivar Finseth, Aree Witoelar, Oleksandr Frei, Psychiatric Genomics Consortium Bipolar Disorder Working Group, Yunpeng Wang, Sahar Hassani, Srdjan Djurovic, Anders M. Dale, Ole A. Andreassen, Eli A Stahl, Gerome Breen, Andreas J Forstner, Andrew McQuillin, Stephan Ripke, Vassily Trubetskoy, Manuel Mattheisen, Jonathan R I Coleman, Heìleìna A Gaspar, Christiaan A de Leeuw, Stacy Steinberg, Jennifer M Whitehead Pavlides, Maciej Trzaskowski, Tune H Pers, Peter A Holmans, Liam Abbott, Esben Agerbo, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Thomas D Als, Adebayo Anjorin, Verneri Antilla, Swapnil Awasthi, Judith A Badner, Marie Bækvad-Hansen, Jack D Barchas, Nicholas Bass, Michael Bauer, Richard Belliveau, Sarah E Bergen, Carsten Bøcker Pedersen, Erlend Bøen, Marco Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Jonas Bybjerg-Grauholm, William Byerley, Miquel Casas, Felecia Cerrato, Pablo Cervantes, Kimberly Chambert, Alexander W Charney, Danfeng Chen, Claire Churchhouse, Toni-Kim Clarke, William Coryell, David W Craig, Cristiana Cruceanu, David Curtis, Piotr M Czerski, Anders M Dale, Simone de Jong, Franziska Degenhardt, Jurgen Del-Favero, J Raymond DePaulo, Amanda L Dobbyn, Ashley Dumont, Torbjørn Elvsåshagen, Valentina Escott-Price, Chun Chieh Fan, Sascha B Fischer, Matthew Flickinger, Tatiana M Foroud, Liz Forty, Josef Frank, Christine Fraser, Nelson B Freimer, Louise Friseìn, Katrin Gade, Diane Gage, Julie Garnham, Claudia Giambartolomei, Marianne Giørtz Pedersen, Jaqueline Goldstein, Scott D Gordon, Katherine Gordon-Smith, Elaine K Green, Melissa J Green, Tiffany A Greenwood, Jakob Grove, Weihua Guan, Joseì Guzman Parra, Marian L Hamshere, Martin Hautzinger, Urs Heilbronner, Stefan Herms, Maria Hipolito, Per Hoffmann, Dominic Holland, Laura Huckins, Steìphane Jamain, Jessica S Johnson, Anders Jureìus, Radhika Kandaswamy, Robert Karlsson, James L Kennedy, Sarah Kittel-Schneider, Sarah V Knott, James A Knowles, Manolis Kogevinas, Anna C Koller, Ralph Kupka, Catharina Lavebratt, Jacob Lawrence, William B Lawson, Markus Leber, Phil H Lee, Shawn E Levy, Jun Z Li, Chunyu Liu, Susanne Lucae, Anna Maaser, Donald J MacIntyre, Pamela B Mahon, Wolfgang Maier, Lina Martinsson, Steve McCarroll, Peter McGuffin, Melvin G McInnis, James D McKay, Helena Medeiros, Sarah E Medland, Fan Meng, Lili Milani, Grant W Montgomery, Derek W Morris, Thomas W Mühleisen, Niamh Mullins, Hoang Nguyen, Caroline M Nievergelt, Annelie Nordin Adolfsson, Evaristus A Nwulia, Claire O’Donovan, Loes M Olde Loohuis, Anil P S Ori, Lilijana Oruc, Urban Ösby, Roy H Perlis, Amy Perry, Andrea Pfennig, James B Potash, Shaun M Purcell, Eline J Regeer, Andreas Reif, Ceìline S Reinbold, John P Rice, Fabio Rivas, Margarita Rivera, Panos Roussos, Douglas M Ruderfer, Euijung Ryu, Cristina Saìnchez-Mora, Alan F Schatzberg, William A Scheftner, Nicholas J Schork, Cynthia Shannon Weickert, Tatyana Shehktman, Paul D Shilling, Engilbert Sigurdsson, Claire Slaney, Olav B Smeland, Janet L Sobell, Christine Søholm Hansen, Anne T Spijker, David St Clair, Michael Steffens, John S Strauss, Fabian Streit, Jana Strohmaier, Szabolcs Szelinger, Robert C Thompson, Thorgeir E Thorgeirsson, Jens Treutlein, Helmut Vedder, Weiqing Wang, Stanley J Watson, Thomas W Weickert, Stephanie H Witt, Simon Xi, Wei Xu, Allan H Young, Peter Zandi, Peng Zhang, Sebastian Zollner, Rolf Adolfsson, Ingrid Agartz, Martin Alda, Lena Backlund, Bernhard T Baune, Frank Bellivier, Wade H Berrettini, Joanna M Biernacka, Douglas H R Blackwood, Michael Boehnke, Anders D Børglum, Aiden Corvin, Nicholas Craddock, Mark J Daly, Udo Dannlowski, ToÞnu Esko, Bruno Etain, Mark Frye, Janice M Fullerton, Elliot S Gershon, Michael Gill, Fernando Goes, Maria Grigoroiu-Serbanescu, Joanna Hauser, David M Hougaard, Christina M Hultman, Ian Jones, Lisa A Jones, Reneì S Kahn, George Kirov, Mikael Landeìn, Marion Leboyer, Cathryn M Lewis, Qingqin S Li, Jolanta Lissowska, 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, Danielle Posthuma, Josep Antoni Ramos-Quiroga, Marta Ribaseìs, Marcella Rietschel, Guy A Rouleau, Martin Schalling, Peter R Schofield, Thomas G Schulze, Alessandro Serretti, Jordan W Smoller, Hreinn Stefansson, Kari Stefansson, Eystein Stordal, Patrick F Sullivan, Gustavo Turecki, Arne E Vaaler, Eduard Vieta, John B Vincent, Thomas Werge, John I Nurnberger, Naomi R Wray, Arianna Di Florio, Howard J Edenberg, Sven Cichon, Roel A Ophoff, Laura J Scott, Ole A Andreassen, John Kelsoe, and Pamela Sklar

Subjects
Alzheimer’s disease, bipolar disorder, GWAS, pleiotropy, cognitive symptoms, affective symptoms, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Background: Alzheimer’s disease (AD) and bipolar disorder (BIP) are complex traits influenced by numerous common genetic variants, most of which remain to be detected. Clinical and epidemiological evidence suggest that AD and BIP are related. However, it is not established if this relation is of genetic origin. Here, we applied statistical methods based on the conditional false discovery rate (FDR) framework to detect genetic overlap between AD and BIP and utilized this overlap to increase the power to identify common genetic variants associated with either or both traits.Methods: We obtained genome wide association studies data from the International Genomics of Alzheimer’s Project part 1 (17,008 AD cases and 37,154 controls) and the Psychiatric Genetic Consortium Bipolar Disorder Working Group (20,352 BIP cases and 31,358 controls). We used conditional QQ-plots to assess overlap in common genetic variants between AD and BIP. We exploited the genetic overlap to re-rank test-statistics for AD and BIP and improve detection of genetic variants using the conditional FDR framework.Results: Conditional QQ-plots demonstrated a polygenic overlap between AD and BIP. Using conditional FDR, we identified one novel genomic locus associated with AD, and nine novel loci associated with BIP. Further, we identified two novel loci jointly associated with AD and BIP implicating the MARK2 gene (lead SNP rs10792421, conjunctional FDR = 0.030, same direction of effect) and the VAC14 gene (lead SNP rs11649476, conjunctional FDR = 0.022, opposite direction of effect).Conclusion: We found polygenic overlap between AD and BIP and identified novel loci for each trait and two jointly associated loci. Further studies should examine if the shared loci implicating the MARK2 and VAC14 genes could explain parts of the shared and distinct features of AD and BIP.

Published
2019
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3. APOEε4 and slow wave sleep in older adults.

Author

Gregory J Tranah, Kristine Yaffe, Caroline M Nievergelt, Neeta Parimi, M Maria Glymour, Kristine E Ensrud, Jane A Cauley, Sonia Ancoli-Israel, Sara Mariani, Susan Redline, Katie L Stone, and Osteoporotic Fractures in Men Study (MrOS) Research Group

Subjects
Medicine, Science
Abstract

Slow wave (or stage N3) sleep has been linked to a variety of cognitive processes. However, the role of stage N3 in the elderly is debated. The link between stage N3 and episodic memory may be weakened or changed in the older adult population, possibly due to several altered mechanisms impacting the cellular structure of the brain. The bases for the age-related dissociation between stage N3 and cognition are not understood. Since APOEε4 status is the strongest genetic risk factor for cognitive decline, we assessed whether the ε4 allele is associated with stage N3 sleep. Participants were from the population-based Osteoporotic Fractures in Men (MrOS) cohort with polysomnography and APOEε4 genotype data (n = 2,302, 100% male, mean age 76.6 years). Sleep stages were objectively measured using overnight in-home polysomnography and central electroencephalogram data were used to score stage N3 sleep. Cognitive function was assessed using the Modified Mini Mental State Exam (3MS). The APOE rs429358 single nucleotide polymorphism, which defines the APOEε4 allele, was genotyped using a custom genotyping array. Total time in stage N3 sleep was significantly higher (p

Published
2018
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4. FMR1, circadian genes and depression: suggestive associations or false discovery?

Author

Daniel F Kripke, Caroline M Nievergelt, Gregory J Tranah, Sarah S Murray, Katharine M Rex, Alexandra P Grizas, Elizabeth K Hahn, Heon-Jeong Lee, John R Kelsoe, and Lawrence E Kline

Subjects
Circadian, Depression, DSPS, FMR1, PPARGC1B, GSK3B, NR1D1, rs25702, rs28900, rs7732671, Biology (General), QH301-705.5
Abstract

Background: There are several indications that malfunctions of the circadian clock contribute to depression. To search for particular circadian gene polymorphisms associated with depression, diverse polymorphisms were genotyped in two samples covering a range of depressed volunteers and participants with normal mood. Methods: Depression mood self-ratings and DNA were collected independently from a sample of patients presenting to a sleep disorders center (1086 of European origin) and from a separate sample consisting of 399 participants claiming delayed sleep phase symptoms and 406 partly-matched controls. A custom Illumina Golden Gate array of 768 selected single nucleotide polymorphisms (SNPs) was assayed in both samples, supplemented by additional SNPlex and Taqman assays, including assay of 41 ancestry-associated markers (AIMs) to control stratification. Results: In the Sleep Clinic sample, these assays yielded Bonferroni-significant association with depressed mood in three linked SNPs of the gene FMR1: rs25702 (nominal P=1.77E-05), rs25714 (P=1.83E-05), and rs28900 (P=5.24E-05). This FMR1 association was supported by 8 SNPs with nominal significance and a nominally-significant gene-wise set test. There was no association of depressed mood with FMR1 in the delayed sleep phase case–control sample or in downloaded GWAS data from the GenRED 2 sample contrasting an early-onset recurrent depression sample with controls. No replication was located in other GWAS studies of depression. Our data did weakly replicate a previouslyreported association of depression with PPARGC1B rs7732671 (P=0.0235). Suggestive associations not meeting strict criteria for multiple testing and replication were found with GSK3B, NPAS2, RORA, PER3, CRY1, MTNR1A and NR1D1. Notably, 16 SNPs nominally associated with depressed mood (14 in GSK3B) were also nominally associated with delayed sleep phase syndrome (P=3E10-6). Conclusions: Considering the inconsistencies between samples and the likelihood that the significant three FMR1 SNPs might be linked to complex polymorphisms more functionally related to depression, large gene resequencing studies may be needed to clarify the import for depression of these circadian genes.

Published
2013
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5. Heritable influence of DBH on adrenergic and renal function: twin and disease studies.

Author

Dalal N Pasha, Jason T Davis, Fangwen Rao, Yuqing Chen, Gen Wen, Maple M Fung, Manjula Mahata, Kuixing Zhang, Danuta Trzebinska, Maja Mustapic, C Makena Hightower, Michael S Lipkowitz, Ming Ji, Michael G Ziegler, Caroline M Nievergelt, and Daniel T O'Connor

Subjects
Medicine, Science
Abstract

Elevated sympathetic activity is associated with kidney dysfunction. Here we used twin pairs to probe heritability of GFR and its genetic covariance with other traits.We evaluated renal and adrenergic phenotypes in twins. GFR was estimated by CKD-EPI algorithm. Heritability and genetic covariance of eGFR and associated risk traits were estimated by variance-components. Meta-analysis probed reproducibility of DBH genetic effects. Effect of DBH genetic variation on renal disease was tested in the NIDDK-AASK cohort.Norepinephrine secretion rose across eGFR tertiles while eGFR fell (p

Published
2013
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6. A survey of genomic studies supports association of circadian clock genes with bipolar disorder spectrum illnesses and lithium response.

Author

Michael J McCarthy, Caroline M Nievergelt, John R Kelsoe, and David K Welsh

Subjects
Medicine, Science
Abstract

Circadian rhythm abnormalities in bipolar disorder (BD) have led to a search for genetic abnormalities in circadian "clock genes" associated with BD. However, no significant clock gene findings have emerged from genome-wide association studies (GWAS). At least three factors could account for this discrepancy: complex traits are polygenic, the organization of the clock is more complex than previously recognized, and/or genetic risk for BD may be shared across multiple illnesses. To investigate these issues, we considered the clock gene network at three levels: essential "core" clock genes, upstream circadian clock modulators, and downstream clock controlled genes. Using relaxed thresholds for GWAS statistical significance, we determined the rates of clock vs. control genetic associations with BD, and four additional illnesses that share clinical features and/or genetic risk with BD (major depression, schizophrenia, attention deficit/hyperactivity). Then we compared the results to a set of lithium-responsive genes. Associations with BD-spectrum illnesses and lithium-responsiveness were both enriched among core clock genes but not among upstream clock modulators. Associations with BD-spectrum illnesses and lithium-responsiveness were also enriched among pervasively rhythmic clock-controlled genes but not among genes that were less pervasively rhythmic or non-rhythmic. Our analysis reveals previously unrecognized associations between clock genes and BD-spectrum illnesses, partly reconciling previously discordant results from past GWAS and candidate gene studies.

Published
2012
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7. Genome-wide association of bipolar disorder suggests an enrichment of replicable associations in regions near genes.

Author

Erin N Smith, Daniel L Koller, Corrie Panganiban, Szabolcs Szelinger, Peng Zhang, Judith A Badner, Thomas B Barrett, Wade H Berrettini, Cinnamon S Bloss, William Byerley, William Coryell, Howard J Edenberg, Tatiana Foroud, Elliot S Gershon, Tiffany A Greenwood, Yiran Guo, Maria Hipolito, Brendan J Keating, William B Lawson, Chunyu Liu, Pamela B Mahon, Melvin G McInnis, Francis J McMahon, Rebecca McKinney, Sarah S Murray, Caroline M Nievergelt, John I Nurnberger, Evaristus A Nwulia, James B Potash, John Rice, Thomas G Schulze, William A Scheftner, Paul D Shilling, Peter P Zandi, Sebastian Zöllner, David W Craig, Nicholas J Schork, and John R Kelsoe

Subjects
Genetics, QH426-470
Abstract

Although a highly heritable and disabling disease, bipolar disorder's (BD) genetic variants have been challenging to identify. We present new genotype data for 1,190 cases and 401 controls and perform a genome-wide association study including additional samples for a total of 2,191 cases and 1,434 controls. We do not detect genome-wide significant associations for individual loci; however, across all SNPs, we show an association between the power to detect effects calculated from a previous genome-wide association study and evidence for replication (P = 1.5×10(-7)). To demonstrate that this result is not likely to be a false positive, we analyze replication rates in a large meta-analysis of height and show that, in a large enough study, associations replicate as a function of power, approaching a linear relationship. Within BD, SNPs near exons exhibit a greater probability of replication, supporting an enrichment of reproducible associations near functional regions of genes. These results indicate that there is likely common genetic variation associated with BD near exons (±10 kb) that could be identified in larger studies and, further, provide a framework for assessing the potential for replication when combining results from multiple studies.

Published
2011
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8. Tracing sub-structure in the European American population with PCA-informative markers.

Author

Peristera Paschou, Petros Drineas, Jamey Lewis, Caroline M Nievergelt, Deborah A Nickerson, Joshua D Smith, Paul M Ridker, Daniel I Chasman, Ronald M Krauss, and Elad Ziv

Subjects
Genetics, QH426-470
Abstract

Genetic structure in the European American population reflects waves of migration and recent gene flow among different populations. This complex structure can introduce bias in genetic association studies. Using Principal Components Analysis (PCA), we analyze the structure of two independent European American datasets (1,521 individuals-307,315 autosomal SNPs). Individual variation lies across a continuum with some individuals showing high degrees of admixture with non-European populations, as demonstrated through joint analysis with HapMap data. The CEPH Europeans only represent a small fraction of the variation encountered in the larger European American datasets we studied. We interpret the first eigenvector of this data as correlated with ancestry, and we apply an algorithm that we have previously described to select PCA-informative markers (PCAIMs) that can reproduce this structure. Importantly, we develop a novel method that can remove redundancy from the selected SNP panels and show that we can effectively remove correlated markers, thus increasing genotyping savings. Only 150-200 PCAIMs suffice to accurately predict fine structure in European American datasets, as identified by PCA. Simulating association studies, we couple our method with a PCA-based stratification correction tool and demonstrate that a small number of PCAIMs can efficiently remove false correlations with almost no loss in power. The structure informative SNPs that we propose are an important resource for genetic association studies of European Americans. Furthermore, our redundancy removal algorithm can be applied on sets of ancestry informative markers selected with any method in order to select the most uncorrelated SNPs, and significantly decreases genotyping costs.

Published
2008
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9. Generalized analysis of molecular variance.

Author

Caroline M Nievergelt, Ondrej Libiger, and Nicholas J Schork

Subjects
Genetics, QH426-470
Abstract

Many studies in the fields of genetic epidemiology and applied population genetics are predicated on, or require, an assessment of the genetic background diversity of the individuals chosen for study. A number of strategies have been developed for assessing genetic background diversity. These strategies typically focus on genotype data collected on the individuals in the study, based on a panel of DNA markers. However, many of these strategies are either rooted in cluster analysis techniques, and hence suffer from problems inherent to the assignment of the biological and statistical meaning to resulting clusters, or have formulations that do not permit easy and intuitive extensions. We describe a very general approach to the problem of assessing genetic background diversity that extends the analysis of molecular variance (AMOVA) strategy introduced by Excoffier and colleagues some time ago. As in the original AMOVA strategy, the proposed approach, termed generalized AMOVA (GAMOVA), requires a genetic similarity matrix constructed from the allelic profiles of individuals under study and/or allele frequency summaries of the populations from which the individuals have been sampled. The proposed strategy can be used to either estimate the fraction of genetic variation explained by grouping factors such as country of origin, race, or ethnicity, or to quantify the strength of the relationship of the observed genetic background variation to quantitative measures collected on the subjects, such as blood pressure levels or anthropometric measures. Since the formulation of our test statistic is rooted in multivariate linear models, sets of variables can be related to genetic background in multiple regression-like contexts. GAMOVA can also be used to complement graphical representations of genetic diversity such as tree diagrams (dendrograms) or heatmaps. We examine features, advantages, and power of the proposed procedure and showcase its flexibility by using it to analyze a wide variety of published data sets, including data from the Human Genome Diversity Project, classical anthropometry data collected by Howells, and the International HapMap Project.

Published
2007
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10. Correction: Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Author

Klaus Oliver Schubert, Anbupalam Thalamuthu, Azmeraw T. Amare, Joseph Frank, Fabian Streit, Mazda Adl, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, Jean-Michel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Cynthia Marie-Claire, Micah Cearns, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Sven Cichon, Scott R. Clark, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Ewa Ferensztajn-Rochowiak, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O’Donovan, Norio Ozaki, Urban Ösby, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil Tekola-Ayele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, and Bernhard T. Baune

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Published
2022
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11. The Relationship of Attention-Deficit/Hyperactivity Disorder With Posttraumatic Stress Disorder

Author

Frank R. Wendt, Miguel Garcia-Argibay, Brenda Cabrera-Mendoza, Unnur A. Valdimarsdóttir, Joel Gelernter, Murray B. Stein, Michel G. Nivard, Adam X. Maihofer, Caroline M. Nievergelt, Henrik Larsson, Manuel Mattheisen, Renato Polimanti, Sandra M. Meier, Karmel W. Choi, Jonathan R.I. Coleman, Nikolaos P. Daskalakis, Christy A. Denckla, Elizabeth Ketema, Rajendra A. Morey, Andrew Ratanatharathorn, Katy Torres, Aliza P. Wingo, Clement C. Zai, Allison E. Aiello, Lynn M. Almli, Ananda B. Amstadter, Soren B. Andersen, Ole A. Andreassen, Paul A. Arbisi, Allison E. Ashley-Koch, S. Bryn Austin, Esmina Avdibegovic, Anders D. Borglum, Dragan Babic, Marie Bækvad-Hansen, Dewleen G. Baker, Jean C. Beckham, Laura J. Bierut, Jonathan I. Bisson, Marco P. Boks, Elizabeth A. Bolger, Bekh Bradley, Meghan Brashear, Gerome Breen, Richard A. Bryant, Angela C. Bustamante, Jonas Bybjerg-Grauholm, Joseph R. Calabrese, Jose Miguel Caldas-de-Almeida, Chia-Yen Chen, Anders M. Dale, Shareefa Dalvie, Jürgen Deckert, Douglas L. Delahanty, Michelle F. Dennis, Seth G. Disner, Katharina Domschke, Laramie E. Duncan, Alma Dzubur Kulenovic, Christopher R. Erbes, Alexandra Evans, Lindsay A. Farrer, Norah C. Feeny, Janine D. Flory, David Forbes, Carol E. Franz, Sandro Galea, Melanie E. Garrett, Aarti Gautam, Bizu Gelaye, Elbert Geuze, Charles F. Gillespie, Aferdita Goci Uka, Scott D. Gordon, Guia Guffanti, Rasha Hammamieh, Michael A. Hauser, Andrew C. Heath, Sian M.J. Hemmings, David Michael Hougaard, Miro Jakovljevic, Marti Jett, Eric Otto Johnson, Ian Jones, Tanja Jovanovic, Xue-Jun Qin, Karen-Inge Karstoft, Milissa L. Kaufman, Ronald C. Kessler, Alaptagin Khan, Nathan A. Kimbrel, Anthony P. King, Nastassja Koen, Henry R. Kranzler, William S. Kremen, Bruce R. Lawford, Lauren A.M. Lebois, Catrin Lewis, Israel Liberzon, Sarah D. Linnstaedt, Mark W. Logue, Adriana Lori, Bozo Lugonja, Jurjen J. Luykx, Michael J. Lyons, Jessica L. Maples-Keller, Charles Marmar, Nicholas G. Martin, Douglas Maurer, Matig R. Mavissakalian, Alexander McFarlane, Regina E. McGlinchey, Katie A. McLaughlin, Samuel A. McLean, Divya Mehta, Rebecca Mellor, Vasiliki Michopoulos, William Milberg, Mark W. Miller, Charles Phillip Morris, Ole Mors, Preben Bo Mortensen, Elliot C. Nelson, Merete Nordentoft, Sonya B. Norman, Meaghan O’Donnell, Holly K. Orcutt, Matthew S. Panizzon, Edward S. Peters, Alan L. Peterson, Matthew Peverill, Robert H. Pietrzak, Melissa A. Polusny, John P. Rice, Victoria B. Risbrough, Andrea L. Roberts, Alex O. Rothbaum, Barbara O. Rothbaum, Peter Roy-Byrne, Kenneth J. Ruggiero, Ariane Rung, Bart P.F. Rutten, Nancy L. Saccone, Sixto E. Sanchez, Dick Schijven, Soraya Seedat, Antonia V. Seligowski, Julia S. Seng, Christina M. Sheerin, Derrick Silove, Alicia K. Smith, Jordan W. Smoller, Scott R. Sponheim, Dan J. Stein, Jennifer S. Stevens, Martin H. Teicher, Wesley K. Thompson, Edward Trapido, Monica Uddin, Robert J. Ursano, Leigh Luella van den Heuvel, Miranda Van Hooff, Eric Vermetten, Christiaan Vinkers, Joanne Voisey, Yunpeng Wang, Zhewu Wang, Thomas Werge, Michelle A. Williams, Douglas E. Williamson, Sherry Winternitz, Christiane Wolf, Erika J. Wolf, Rachel Yehuda, Keith A. Young, Ross McD. Young, Hongyu Zhao, Lori A. Zoellner, Magali Haas, Heather Lasseter, Allison C. Provost, Rany M. Salem, Jonathan Sebat, Richard Shaffer, Tianying Wu, Stephan Ripke, Mark J. Daly, Kerry J. Ressler, Karestan C. Koenen, Biological Psychology, APH - Mental Health, APH - Methodology, Anatomy and neurosciences, Psychiatry, and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
Genome-wide association study, Epidemiology, Siblings, PTSD, Mendelian Randomization Analysis, Comorbidities, SDG 3 - Good Health and Well-being, Humans, ADHD, Attention Deficit Disorder with Hyperactivity/epidemiology, Stress Disorders, Post-Traumatic/genetics, Biological Psychiatry, Causal inference
Abstract

Background: Attention-deficit/hyperactivity disorder (ADHD) and posttraumatic stress disorder (PTSD) are associated, but it is unclear if this is a causal relationship or confounding. We used genetic analyses and sibling comparisons to clarify the direction of this relationship. Methods: Linkage disequilibrium score regression and 2-sample Mendelian randomization were used to test for genetic correlation (r g) and bidirectional causal effects using European ancestry genome-wide association studies of ADHD (20,183 cases and 35,191 controls) and 6 PTSD definitions (up to 320,369 individuals). Several additional variables were included in the analysis to verify the independence of the ADHD-PTSD relationship. In a population-based sibling comparison (N = 2,082,118 individuals), Cox regression models were fitted to account for time at risk, a range of sociodemographic factors, and unmeasured familial confounders (via sibling comparisons). Results: ADHD and PTSD had consistent r g (r g range, 0.43–0.52; p < .001). ADHD genetic liability was causally linked with increased risk for PTSD (β = 0.367; 95% CI, 0.186–0.552; p = 7.68 × 10 −5). This result was not affected by heterogeneity, horizontal pleiotropy (Mendelian randomization Egger intercept = 4.34 × 10 −4, p = .961), or other phenotypes and was consistent across PTSD datasets. However, we found no consistent associations between PTSD genetic liability and ADHD risk. Individuals diagnosed with ADHD were at a higher risk for developing PTSD than their undiagnosed sibling (hazard ratio = 2.37; 95% CI, 1.98–3.53). Conclusions: Our findings add novel evidence supporting the need for early and effective treatment of ADHD, as patients with this diagnosis are at significantly higher risk to develop PTSD later in life.

Published
2023

13. A putative causal relationship between genetically determined female body shape and posttraumatic stress disorder

Author

Renato Polimanti, Ananda B. Amstadter, Murray B. Stein, Lynn M. Almli, Dewleen G. Baker, Laura J. Bierut, Bekh Bradley, Lindsay A. Farrer, Eric O. Johnson, Anthony King, Henry R. Kranzler, Adam X. Maihofer, John P. Rice, Andrea L. Roberts, Nancy L. Saccone, Hongyu Zhao, Israel Liberzon, Kerry J. Ressler, Caroline M. Nievergelt, Karestan C. Koenen, Joel Gelernter, and for The Psychiatric Genomics Consortium Posttraumatic Stress Disorder Workgroup

Subjects
Trauma, Genetics, Women, Anthropometric traits, Medicine, QH426-470
Abstract

Abstract Background The nature and underlying mechanisms of the observed increased vulnerability to posttraumatic stress disorder (PTSD) in women are unclear. Methods We investigated the genetic overlap of PTSD with anthropometric traits and reproductive behaviors and functions in women. The analysis was conducted using female-specific summary statistics from large genome-wide association studies (GWAS) and a cohort of 3577 European American women (966 PTSD cases and 2611 trauma-exposed controls). We applied a high-resolution polygenic score approach and Mendelian randomization analysis to investigate genetic correlations and causal relationships. Results We observed an inverse association of PTSD with genetically determined anthropometric traits related to body shape, independent of body mass index (BMI). The top association was related to BMI-adjusted waist circumference (WCadj; R = –0.079, P

Published
2017
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14. Assessing Neuronal and Astrocyte Derived Exosomes From Individuals With Mild Traumatic Brain Injury for Markers of Neurodegeneration and Cytotoxic Activity

Author

Charisse N. Winston, Haylie K. Romero, Maya Ellisman, Sophie Nauss, David A. Julovich, Tori Conger, James R. Hall, Wendy Campana, Sid E. O’Bryant, Caroline M. Nievergelt, Dewleen G. Baker, Victoria B. Risbrough, and Robert A. Rissman

Subjects
traumatic brain injury, neuronal exosomes, astrocytes, amyloid, tau, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Mild traumatic brain injury (mTBI) disproportionately affects military service members and is very difficult to diagnose. To-date, there is currently no blood-based, diagnostic biomarker for mTBI cases with persistent post concussive symptoms. To examine the potential of neuronally-derived (NDE) and astrocytic-derived (ADE) exosome cargo proteins as biomarkers of chronic mTBI in younger adults, we examined plasma exosomes from a prospective longitudinal study of combat-related risk and resilience, marine resiliency study II (MRSII). After return from a combat-deployment participants were interviewed to assess TBI exposure while on deployment. Plasma exosomes from military service members with mTBI (mean age, 21.7 years, n = 19, avg. days since injury 151), and age-matched, controls (deployed service members who did not endorse a deployment-related TBI or a pre-deployment history of TBI; mean age, 21.95 years, n = 20) were precipitated and enriched against a neuronal adhesion protein, L1-CAM, and an astrocyte marker, glutamine aspartate transporter (GLAST) using magnetic beads to immunocapture the proteins and subsequently selected by fluorescent activated cell sorting (FACS). Extracted protein cargo from NDE and ADE preparations were quantified for protein levels implicated in TBI neuropathology by standard ELISAs and on the ultra-sensitive single molecule assay (Simoa) platform. Plasma NDE and ADE levels of Aβ42 were significantly higher while plasma NDE and ADE levels of the postsynaptic protein, neurogranin (NRGN) were significantly lower in participants endorsing mTBI exposure compared to controls with no TBI history. Plasma NDE and ADE levels of Aβ40, total tau, and neurofilament light (NFL), P-T181-tau, P-S396-tau were either undetectable or not significantly different between the two groups. In an effort to understand the pathogenetic potential of NDE and ADE cargo proteins, neuron-like cultures were treated with NDE and ADE preparations from TBI and non-TBI groups. Lastly, we determined that plasma NDE but not ADE cargo proteins from mTBI samples were found to be toxic to neuron-like recipient cells in vitro. These data support the presence of markers of neurodegeneration in NDEs of mTBI and suggest that these NDEs can be used as tools to identify pathogenic mechanisms of TBI.

Published
2019
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15. Sex differences in the polygenic architecture of hearing problems in adults

Author

Flavio De Angelis, Oana A. Zeleznik, Frank R. Wendt, Gita A. Pathak, Daniel S. Tylee, Antonella De Lillo, Dora Koller, Brenda Cabrera-Mendoza, Royce E. Clifford, Adam X. Maihofer, Caroline M. Nievergelt, Gary C. Curhan, Sharon G. Curhan, and Renato Polimanti

Subjects
Adult, Male, Multifactorial Inheritance, Genome-wide association study, Aging, Clinical Sciences, Genome-wide gene-by-environment interaction, Hearing, Sex differences, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Aetiology, Molecular Biology, Genetics (clinical), Hearing problems, Ancestry, Pleiotropy, Sex Characteristics, Transcriptomic regulation, Prevention, Human Genome, Brain Disorders, Polygenic risk scores, Good Health and Well Being, Molecular Medicine, Female, Follow-Up Studies, Causal inference
Abstract

Background Hearing problems (HP) in adults are common and are associated with several comorbid conditions. Its prevalence increases with age, reflecting the cumulative effect of environmental factors and genetic predisposition. Although several risk loci have been already identified, HP biology and epidemiology are still insufficiently investigated by large-scale genetic studies. Methods Leveraging the UK Biobank, the Nurses’ Health Studies (I and II), the Health Professionals Follow-up Study, and the Million Veteran Program, we conducted a comprehensive genome-wide investigation of HP in 748,668 adult participants (discovery N = 501,825; replication N = 226,043; cross-ancestry replication N = 20,800). We leveraged the GWAS findings to characterize HP polygenic architecture, exploring sex differences, polygenic risk across ancestries, tissue-specific transcriptomic regulation, cause-effect relationships with genetically correlated traits, and gene interactions with HP environmental risk factors. Results We identified 54 risk loci and demonstrated that HP polygenic risk is shared across ancestry groups. Our transcriptomic regulation analysis highlighted the potential role of the central nervous system in HP pathogenesis. The sex-stratified analyses showed several additional associations related to peripheral hormonally regulated tissues reflecting a potential role of estrogen in hearing function. This evidence was supported by the multivariate interaction analysis that showed how genes involved in brain development interact with sex, noise pollution, and tobacco smoking in relation to their HP associations. Additionally, the genetically informed causal inference analysis showed that HP is linked to many physical and mental health outcomes. Conclusions The results provide many novel insights into the biology and epidemiology of HP in adults. Our sex-specific analyses and transcriptomic associations highlighted molecular pathways that may be targeted for drug development or repurposing. Additionally, the potential causal relationships identified may support novel preventive screening programs to identify individuals at risk.

Published
2023

16. Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder

Author

Thomas S. Wingo, Ekaterina S. Gerasimov, Yue Liu, Duc M. Duong, Selina M. Vattathil, Adriana Lori, Jake Gockley, Michael S. Breen, Adam X. Maihofer, Caroline M. Nievergelt, Karestan C. Koenen, Daniel F. Levey, Joel Gelernter, Murray B. Stein, Kerry J. Ressler, David A. Bennett, Allan I. Levey, Nicholas T. Seyfried, and Aliza P. Wingo

Subjects
Cellular and Molecular Neuroscience, Psychiatry and Mental health, Molecular Biology
Published
2022

18. Genome-wide Association Study of Traumatic Brain Injury in U.S. Military Veterans Enrolled in the VA Million Veteran Program

Author

Victoria C. Merritt, Adam X. Maihofer, Marianna Gasperi, Elizabeth Ketema, Catherine Chanfreau-Coffinier, Murray B. Stein, Matthew S. Panizzon, Richard L. Hauger, Mark W. Logue, Lisa Delano-Wood, and Caroline M. Nievergelt

Abstract

Large-scale genetic studies of traumatic brain injury (TBI) are lacking; thus, our understanding of the influence of genetic factors on TBI risk and recovery is incomplete. This study aimed to conduct a genome-wide association study (GWAS) of TBI in VA Million Veteran Program enrollees. Participants included a multi-ancestry cohort (European, African, and Hispanic ancestries; N=304,485; 111,494 TBI cases, 192,991 controls). TBI was assessed using MVP survey data and ICD codes from the Veterans Health Administration’s electronic health record. GWAS was performed using logistic regression in PLINK, and meta-analyzed in METAL. FUMA was used for post-GWAS analysis. Genomic structural equation modeling (gSEM) was conducted to investigate underlying genetic associations with TBI, and bivariate MiXeR was used to estimate phenotype specific and shared polygenicity. SNP-based heritability was 0.060 (SE=0.004,p=7.83×10−66). GWAS analysis identified 15 genome-wide significant (GWS) loci atp−8. Gene-based analyses revealed 14 gene-wide significant genes, includingNCAM1, APOE, FTO, andFOXP2. Gene tissue expression analysis identified the brain as significantly enriched, particularly in the frontal cortex, anterior cingulate cortex, and nucleus accumbens. Genetic correlations with TBI were significant for risk-taking behaviors and psychiatric disorders, but generally not significant for the neurocognitive variables investigated. gSEM analysis revealed stronger associations with risk-taking traits than with psychiatric traits. Finally, the genetic architecture of TBI was similar to polygenic psychiatric disorders. Neurodegenerative disorders including Alzheimer’s and Parkinson’s disease showed much less polygenicity, however, the proportion of shared variance with TBI was high. This first well-powered GWAS of TBI identified 15 loci including genes relevant to TBI biology, and showed that TBI is a heritable trait with comparable genetic architecture and high genetic correlation with psychiatric traits. Our findings set the stage for future TBI GWASs that focus on injury severity and diversity and chronicity of symptom sequelae.

Published
2023

19. Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis

Author

Vipavee Niemsiri, Sara Brin Rosenthal, Caroline M. Nievergelt, Adam X. Maihofer, Maria C. Marchetto, Renata Santos, Tatyana Shekhtman, Ney Alliey-Rodriguez, Amit Anand, Yokesh Balaraman, Wade H. Berrettini, Holli Bertram, Katherine E. Burdick, Joseph R. Calabrese, Cynthia V. Calkin, Carla Conroy, William H. Coryell, Anna DeModena, Lisa T. Eyler, Scott Feeder, Carrie Fisher, Nicole Frazier, Mark A. Frye, Keming Gao, Julie Garnham, Elliot S. Gershon, Fernando S. Goes, Toyomi Goto, Gloria J. Harrington, Petter Jakobsen, Masoud Kamali, Marisa Kelly, Susan G. Leckband, Falk W. Lohoff, Michael J. McCarthy, Melvin G. McInnis, David Craig, Caitlin E. Millett, Francis Mondimore, Gunnar Morken, John I. Nurnberger, Claire O’ Donovan, Ketil J. Øedegaard, Kelly Ryan, Martha Schinagle, Paul D. Shilling, Claire Slaney, Emma K. Stapp, Andrea Stautland, Bruce Tarwater, Peter P. Zandi, Martin Alda, Kathleen M. Fisch, Fred H. Gage, and John R. Kelsoe

Subjects
Psychiatry, Cellular and Molecular Neuroscience, Psychiatry and Mental health, Mental Health, Human Genome, Psychology and Cognitive Sciences, Genetics, Biological Sciences, Serious Mental Illness, Molecular Biology, Medical and Health Sciences, Brain Disorders
Abstract

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E–09 and 4.10E–18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Published
2023

20. Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume

Author

Yuanchao Zheng, Melanie E. Garrett, Delin Sun, Emily K. Clarke-Rubright, Courtney C. Haswell, Adam X. Maihofer, Jeremy A. Elman, Carol E. Franz, Michael J. Lyons, William S. Kremen, Matthew Peverill, Kelly Sambrook, Katie A. McLaughlin, Nicholas D. Davenport, Seth Disner, Scott R. Sponheim, Elpiniki Andrew, Mayuresh Korgaonkar, Richard Bryant, Tim Varkevisser, Elbert Geuze, Jonathan Coleman, Jean C. Beckham, Nathan A. Kimbrel, Danielle Sullivan, Mark Miller, Jasmeet Hayes, Mieke Verfaellie, Erika Wolf, David Salat, Jeffrey M. Spielberg, William Milberg, Regina McGlinchey, Emily L. Dennis, Paul M. Thompson, Sarah Medland, Neda Jahanshad, Caroline M. Nievergelt, Allison E. Ashley-Koch, Mark W. Logue, and Rajendra A. Morey

Subjects
Clinical Sciences, Neurosciences. Biological psychiatry. Neuropsychiatry, Predictive markers, Hippocampus, Article, Stress Disorders, Post-Traumatic, Cellular and Molecular Neuroscience, Behavioral and Social Science, mental disorders, Genetics, 2.1 Biological and endogenous factors, Psychology, Humans, Clinical genetics, Aetiology, Biological Psychiatry, Stress Disorders, Neurosciences, Brain, Post-Traumatic Stress Disorder (PTSD), Amygdala, Anxiety Disorders, Magnetic Resonance Imaging, Brain Disorders, Psychiatry and Mental health, Mental Health, Good Health and Well Being, Post-Traumatic, Public Health and Health Services, Psychiatric disorders, RC321-571
Abstract

The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10−20), thalamus (p = 7.46 × 10−10), caudate (p = 1.97 × 10−18), putamen (p = 1.7 × 10−12), and nucleus accumbens (p = 1.99 × 10−7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = −0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p −19) in four out of five threshold peaks (0.024, 0.133, 0.487, 0.730, and 0.889) used to calculate hippocampal volume PGSs. We detected similar GxE (G × ChildTrauma) relationships in the amygdala for exposure to childhood trauma (rs4702973; p = 2.16 × 10−7) or PTSD (rs10861272; p = 1.78 × 10−6) in the CHST11 gene. The hippocampus and amygdala are pivotal brain structures in mediating PTSD symptomatology. Trauma exposure and PTSD modulate the effect of polygenic markers on hippocampal volume (GxE) and the amygdala volume PGS is associated with PTSD risk, which supports the role of amygdala volume as a risk factor for PTSD.

Published
2021

21. Development and application of novel performance validity metrics for computerized neurocognitive batteries

Author

Dewleen G. Baker, David R. Roalf, Daniel H. Wolf, J. C. Scott, R.C. Gur, R.E. Gur, Ellyn R. Butler, Kosha Ruparel, Victoria B. Risbrough, Caroline M. Nievergelt, Theodore D. Satterthwaite, Allison M. Port, and Tyler M. Moore

Subjects
Psychiatry and Mental health, Clinical Psychology, Computer science, business.industry, General Neuroscience, Artificial intelligence, Neurology (clinical), Machine learning, computer.software_genre, business, computer, Neurocognitive
Abstract

Objectives: Data from neurocognitive assessments may not be accurate in the context of factors impacting validity, such as disengagement, unmotivated responding, or intentional underperformance. Performance validity tests (PVTs) were developed to address these phenomena and assess underperformance on neurocognitive tests. However, PVTs can be burdensome, rely on cutoff scores that reduce information, do not examine potential variations in task engagement across a battery, and are typically not well-suited to acquisition of large cognitive datasets. Here we describe the development of novel performance validity measures that could address some of these limitations by leveraging psychometric concepts using data embedded within the Penn Computerized Neurocognitive Battery (PennCNB). Methods: We first developed these validity measures using simulations of invalid response patterns with parameters drawn from real data. Next, we examined their application in two large, independent samples: 1) children and adolescents from the Philadelphia Neurodevelopmental Cohort (n = 9498); and 2) adult servicemembers from the Marine Resiliency Study-II (n = 1444). Results: Our performance validity metrics detected patterns of invalid responding in simulated data, even at subtle levels. Furthermore, a combination of these metrics significantly predicted previously established validity rules for these tests in both developmental and adult datasets. Moreover, most clinical diagnostic groups did not show reduced validity estimates. Conclusions: These results provide proof-of-concept evidence for multivariate, data-driven performance validity metrics. These metrics offer a novel method for determining the performance validity for individual neurocognitive tests that is scalable, applicable across different tests, less burdensome, and dimensional. However, more research is needed into their application.

Published
2022

23. Association of polygenic risk scores, traumatic life events and coping strategies with war-related PTSD diagnosis and symptom severity in the South Eastern Europe (SEE)-PTSD cohort

Author

Katharina Domschke, Mirnesa Muminovic Umihanic, Alma Bravo Mehmedbasic, N. Kravić, Caroline M. Nievergelt, Miro Jakovljević, Elma Feric Bojic, Osman Sinanović, Sabina Kucukalic, Shpend Haxhibeqiri, Angelika Erhardt, Bodo Warrings, Blerina Hoxha, Aferdita Goci Uka, Emina Sabic Dzananovic, Valdete Haxhibeqiri, Jürgen Deckert, Ferid Agani, Nenad Jakšić, Alma Dzubur-Kulenovic, Branka Aukst-Margetić, Romana Babić, Damir Marjanović, Nada Bozina, Esmina Avdibegović, Ana Cima Franc, Heike Weber, Abdulah Kucukalic, Marko Pavlović, Dragan Babić, and Adam X. Maihofer

Subjects
Coping (psychology), medicine.medical_specialty, Neurology, Emotions, Genome-wide association study, Logistic regression, behavioral disciplines and activities, Stress Disorders, Post-Traumatic, Risk Factors, Adaptation, Psychological, mental disorders, Humans, Medicine, ddc:610, Europe, Eastern, Association (psychology), Biological Psychiatry, business.industry, Hypervigilance, CAPS, Coping style, Life events, PTSD, Polygenic risk score, Psychiatry and Mental health, Cohort, Neurology (clinical), medicine.symptom, business, Psychopathology, Clinical psychology
Abstract

Objectives Posttraumatic stress disorder (PTSD) is triggered by extremely stressful environmental events and characterized by high emotional distress, re-experiencing of trauma, avoidance and hypervigilance. The present study uses polygenic risk scores (PRS) derived from the UK Biobank (UKBB) mega-cohort analysis as part of the PGC PTSD GWAS effort to determine the heritable basis of PTSD in the South Eastern Europe (SEE)-PTSD cohort. We further analyzed the relation between PRS and additional disease-related variables, such as number and intensity of life events, coping, sex and age at war on PTSD and CAPS as outcome variables. Methods Association of PRS, number and intensity of life events, coping, sex and age on PTSD were calculated using logistic regression in a total of 321 subjects with current and remitted PTSD and 337 controls previously subjected to traumatic events but not having PTSD. In addition, PRS and other disease-related variables were tested for association with PTSD symptom severity, measured by the Clinician Administrated PTSD Scale (CAPS) by liner regression. To assess the relationship between the main outcomes PTSD diagnosis and symptom severity, each of the examined variables was adjusted for all other PTSD related variables. Results The categorical analysis showed significant polygenic risk in patients with remitted PTSD and the total sample, whereas no effects were found on symptom severity. Intensity of life events as well as the individual coping style were significantly associated with PTSD diagnosis in both current and remitted cases. The dimensional analyses showed as association of war-related frequency of trauma with symptom severity, whereas the intensity of trauma yielded significant results independently of trauma timing in current PTSD. Conclusions The present PRS application in the SEE-PTSD cohort confirms modest but significant polygenic risk for PTSD diagnosis. Environmental factors, mainly the intensity of traumatic life events and negative coping strategies, yielded associations with PTSD both categorically and dimensionally with more significant p-values. This suggests that, at least in the present cohort of war-related trauma, the association of environmental factors and current individual coping strategies with PTSD psychopathology was stronger than the polygenic risk.

Published
2021

24. Exposure to unpredictability and mental health: Validation of the brief version of the Questionnaire of Unpredictability in Childhood (QUIC-5) in English and Spanish

Author

Natasha G, Lindert, Megan Y, Maxwell, Sabrina R, Liu, Hal S, Stern, Tallie Z, Baram, Elysia, Poggi Davis, Victoria B, Risbrough, Dewleen G, Baker, Caroline M, Nievergelt, and Laura M, Glynn

Subjects
General Psychology
Abstract

Unpredictability is increasingly recognized as a primary dimension of early life adversity affecting lifespan mental health trajectories; screening for these experiences is therefore vital. The Questionnaire of Unpredictability in Childhood (QUIC) is a 38-item tool that measures unpredictability in childhood in social, emotional and physical domains. The available evidence indicates that exposure to unpredictable experiences measured with the QUIC predicts internalizing symptoms including depression and anxiety. The purpose of the present study was to validate English and Spanish brief versions (QUIC-5) suitable for administration in time-limited settings (e.g., clinical care settings, large-scale epidemiological studies). Five representative items were identified from the QUIC and their psychometric properties examined. The predictive validity of the QUIC-5 was then compared to the QUIC by examining mental health in four cohorts: (1) English-speaking adult women assessed at 6-months postpartum (N = 116), (2) English-speaking male veterans (N = 95), (3) English-speaking male and female adolescents (N = 155), and (4) Spanish-speaking male and female adults (N = 285). The QUIC-5 demonstrated substantial variance in distributions in each of the cohorts and is correlated on average 0.84 (r’s = 0.81–0.87) with the full 38-item version. Furthermore, the QUIC-5 predicted internalizing symptoms (anxiety and depression) in all cohorts with similar effect sizes (r’s = 0.16–0.39; all p’s < 0.05) to the full versions (r’s = 0.19–0.42; all p’s < 0.05). In sum, the QUIC-5 exhibits good psychometric properties and is a valid alternative to the full QUIC. These findings support the future use of the QUIC-5 in clinical and research settings as a concise way to measure unpredictability, identify risk of psychopathology, and intervene accordingly.

Published
2022

25. Genomic Structural Equation Modeling Reveals Latent Phenotypes in the Human Cortex with Distinct Genetic Architecture

Author

Rajendra A. Morey, Yuanchao Zheng, Delin Sun, Melanie E. Garrett, Marianna Gasperi, Adam X. Maihofer, Lexi Baird, Katrina L. Grasby, Ashley Huggins, Courtney C. Haswell, C. Paul M. Thompson, Sarah Medland, Daniel E. Gustavson, Matthew S. Panizzon, William S. Kremen, Caroline M. Nievergelt, Allison E. Ashley-Koch, and Mark W. Logue

Abstract

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from anatomical, functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to model the genetic architecture of cortical surface area (SA) and cortical thickness (CT) of 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance. Genomic SEM can fit a multivariate GWAS from summary statistics, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA was explained by 6 latent factors and CT was explained by 4 latent factors. The multivariate GWAS of these latent factors identified 74 genome-wide significant (GWS) loci (p−8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of latent factor GWAS results found that SA-derived factors had a positive genetic correlation with bipolar disorder (BPD), and major depressive disorder (MDD), and a negative genetic correlation with attention deficit hyperactivity disorder (ADHD), MDD, and insomnia, while CT factors displayed a negative genetic correlation with alcohol dependence. Jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across phenotypes offers a new vantage point for mapping genetically informed cortical networks.HIGHLIGHTSGenomic SEM can examine genetic correlation across cortical regions.We inferred regional genetic networks of cortical thickness and surface area.Network-associated variants have been implicated in multiple traits.These networks are genetically correlated with several psychiatric disorders including MDD, bipolar, ADHD, and alcohol dependence.

Published
2022

26. A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex

Author

Danny Antaki, James Guevara, Adam X. Maihofer, Marieke Klein, Madhusudan Gujral, Jakob Grove, Caitlin E. Carey, Oanh Hong, Maria J. Arranz, Amaia Hervas, Christina Corsello, Keith K. Vaux, Alysson R. Muotri, Lilia M. Iakoucheva, Eric Courchesne, Karen Pierce, Joseph G. Gleeson, Elise B. Robinson, Caroline M. Nievergelt, and Jonathan Sebat

Subjects
Male, Pediatric, Multifactorial Inheritance, Autism Spectrum Disorder, Prevention, Intellectual and Developmental Disabilities (IDD), Autism, Neurosciences, Biological Sciences, Medical and Health Sciences, Brain Disorders, Mental Health, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Family, Female, Genetic Testing, Autistic Disorder, Aetiology, Child, Developmental Biology
Abstract

The genetic etiology of autism spectrum disorder (ASD) is multifactorial, but how combinations of genetic factors determine risk is unclear. In a large family sample, we show that genetic loads of rare and polygenic risk are inversely correlated in cases and greater in females than in males, consistent with a liability threshold that differs by sex. De novo mutations (DNMs), rare inherited variants and polygenic scores were associated with various dimensions of symptom severity in children and parents. Parental age effects on risk for ASD in offspring were attributable to a combination of genetic mechanisms, including DNMs that accumulate in the paternal germline and inherited risk that influences behavior in parents. Genes implicated by rare variants were enriched in excitatory and inhibitory neurons compared with genes implicated by common variants. Our results suggest that a phenotypic spectrum of ASD is attributable to a spectrum of genetic factors that impact different neurodevelopmental processes.

Published
2022

27. Pre-deployment threat learning predicts increased risk for post-deployment insomnia: Evidence from the Marine Resiliency Study

Author

Christopher Hunt, Daniel M. Stout, Ziyun Tie, Dean Acheson, Peter J. Colvonen, Caroline M. Nievergelt, Kate A. Yurgil, Dewleen G. Baker, and Victoria B. Risbrough

Subjects
Male, Stress Disorders, Post-Traumatic, Psychiatry and Mental health, Clinical Psychology, Military Personnel, Sleep Initiation and Maintenance Disorders, Humans, Learning, Experimental and Cognitive Psychology, Dreams
Abstract

Insomnia is a common and impairing consequence of military deployment, but little is known about pre-deployment risk factors for post-deployment insomnia. Abnormal threat learning tendencies are commonly observed in individuals with insomnia and maladaptive responses to stress have been implicated in the development of insomnia, suggesting that threat learning could be an important risk factor for post-deployment insomnia. Here, we examined pre-deployment threat learning as a predictor of post-deployment insomnia and the potential mechanisms underlying this effect. Male servicemembers (N = 814) completed measures of insomnia, psychiatric symptoms, and a threat learning task before and after military deployment. Threat learning indices that differentiated participants with versus withoutinsomnia at post-deployment were tested as pre-deployment predictors of post-deployment insomnia. Post-deployment insomnia was linked to elevations on several threat learning indices at post-deployment, but only higher threat conditioning, as indexed by higher threat expectancy ratings to the danger cue, emerged as a pre-deployment predictor of post-deployment insomnia. This effect was independent of combat exposure levels and partially mediated by greater post-deployment nightmares. The tendency to acquire stronger expectations of aversive events following encounters with danger cues may increase risk for post-deployment insomnia, in part due to the development of more severe nightmares.

Published
2022

28. Circadian rhythms in bipolar disorder patient-derived neurons predict lithium response: Preliminary studies

Author

Melvin G. McInnis, David K. Welsh, Michael McCarthy, Heather Wei, Himanshu K. Mishra, Sara Vandenburgh, William Coryell, Joseph R. Calabrese, Noelle M. Ying, Elliot S. Gershon, Paul D. Shilling, Fred H. Gage, Timothy Nakhla, Angelica Luis, John R. Kelsoe, Wade H. Berrettini, Peter P. Zandi, Martin Alda, John I. Nurnberger, Kristen J. Brennand, Caroline M. Nievergelt, Metta Nguyen, Mark A. Frye, and Ketil J. Oedegaard

Subjects
0301 basic medicine, circadian rhythm, medicine.medical_specialty, Bipolar Disorder, Lithium (medication), Period (gene), Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Internal medicine, medicine, Humans, Circadian rhythm, Bipolar disorder, Molecular Biology, Neurons, business.industry, medicine.disease, neuron, PER2, CLOCK, stem cell, Psychiatry and Mental health, 030104 developmental biology, medicine.anatomical_structure, Endocrinology, lithium, Lithium Compounds, Neuron, medicine.symptom, business, Mania, 030217 neurology & neurosurgery, medicine.drug
Abstract

Bipolar disorder (BD) is a neuropsychiatric illness defined by recurrent episodes of mania/hypomania, depression and circadian rhythm abnormalities. Lithium is an effective drug for BD, but 30-40% of patients fail to respond adequately to treatment. Previous work has demonstrated that lithium affects the expression of "clock genes" and that lithium responders (Li-R) can be distinguished from non-responders (Li-NR) by differences in circadian rhythms. However, circadian rhythms have not been evaluated in BD patient neurons from Li-R and Li-NR. We used induced pluripotent stem cells (iPSCs) to culture neuronal precursor cells (NPC) and glutamatergic neurons from BD patients characterized for lithium responsiveness and matched controls. We identified strong circadian rhythms in Per2-luc expression in NPCs and neurons from controls and Li-R, but NPC rhythms in Li-R had a shorter circadian period. Li-NR rhythms were low amplitude and profoundly weakened. In NPCs and neurons, expression of PER2 was higher in both BD groups compared to controls. In neurons, PER2 protein levels were higher in BD than controls, especially in Li-NR samples. In single cells, NPC and neuron rhythms in both BD groups were desynchronized compared to controls. Lithium lengthened period in Li-R and control neurons but failed to alter rhythms in Li-NR. In contrast, temperature entrainment increased amplitude across all groups, and partly restored rhythms in Li-NR neurons. We conclude that neuronal circadian rhythm abnormalities are present in BD and most pronounced in Li-NR. Rhythm deficits in BD may be partly reversible through stimulation of entrainment pathways.

Published
2021

29. Neural progenitor cells derived from lithium responsive and non-responsive bipolar disorder patients exhibit distinct sensitivity to cell death following methamphetamine

Author

Himanshu K. Mishra, Atulya D. Mandyam, Wulfran Trenet, Heather Wei, Caroline M. Nievergelt, Adam X. Maihofer, Paul D. Shilling, Martin Alda, Elliot Gershon, Melvin G. McInnis, John R. Kelsoe, and Michael J. McCarthy

Subjects
Pharmacology, Cellular and Molecular Neuroscience
Abstract

Bipolar disorder (BD) is characterized by manic and depressive mood episodes and loss of brain gray matter. Lithium has antimanic and neuroprotective properties, but only 30% BD patients respond to lithium pharmacotherapy. Dopamine signaling has been implicated in BD and may contribute to lithium response. Methamphetamine (METH) stimulates dopamine release and models the clinical features of mania but has never been used to study cell death in BD patient neurons. We used BD patient derived neuronal progenitor cells (NPCs) to determine whether the vulnerability to cell death differed in samples from lithium responder (Li-R) and non-responder (Li-NR) BD patients and healthy controls following METH exposure in vitro. We hypothesized that NPCs from Li-R and Li-NR would differ in vulnerability to METH, dopamine signaling and neuroprotection from lithium. Following METH, NPCs from controls and Li-NR showed significantly greater cell loss compared to Li-R. Pre-treatment of NPCs with the D1 dopamine receptor antagonist SCH 23390 reversed the neurotoxic effects of METH. In Li-R NPCs, expression of phosho-ERK1/2 was significantly increased. In Li-NR NPCs, phospho-AKT, D1 and D2 dopamine receptor proteins were significantly increased. Pre-treatment of NPCs with lithium before METH reversed the neurotoxic effects of METH in control NPCs, whereas Li-NR showed less protective benefit. Li-R cells showed decreased levels of cell death after METH and comparatively high viability, and lithium treatment did not increase viability any further. This novel NPC model of mania reveals differences in cell death that could help identify mechanisms of lithium response in BD.

Published
2023

30. Tractor uses local ancestry to enable inclusion of admixed individuals into GWAS and boost power

Author

Marcos L. Santoro, Elizabeth G. Atkinson, Konrad J. Karczewski, Adam X. Maihofer, Karestan C. Koenen, Jacob C. Ulirsch, Masahiro Kanai, Alicia R. Martin, Caroline M. Nievergelt, Hilary K. Finucane, Yoichiro Kamatani, Mark J. Daly, Yukinori Okada, and Benjamin M. Neale

Subjects
Tractor, business.product_category, Genome-wide association study, Computational biology, Biology, Polymorphism, Single Nucleotide, White People, Article, 03 medical and health sciences, 0302 clinical medicine, Genetics, Guanine Nucleotide Exchange Factors, Humans, Genetic risk, 030304 developmental biology, Genetic association, Homeodomain Proteins, 0303 health sciences, Models, Genetic, Regression analysis, Replicate, Software package, Lipids, Pedigree, Cholesterol blood, Black or African American, Cholesterol, Haplotypes, business, Software, 030217 neurology & neurosurgery, Genome-Wide Association Study, Transcription Factors
Abstract

Admixed populations are routinely excluded from genomic studies due to concerns over population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with simulated and empirical two-way admixed African–European cohorts. Tractor generates accurate ancestry-specific effect-size estimates and P values, can boost genome-wide association study (GWAS) power and improves the resolution of association signals. Using a local ancestry-aware regression model, we replicate known hits for blood lipids, discover novel hits missed by standard GWAS and localize signals closer to putative causal variants. Tractor is a statistical framework that facilitates the inclusion of admixed individuals in association studies by leveraging local ancestry. Tractor generates accurate ancestry-specific effect-size estimates and improves the resolution of association signals.

Published
2021

31. Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach - CORRIGENDUM

Author

Micah, Cearns, Azmeraw T, Amare, Klaus Oliver, Schubert, Anbupalam, Thalamuthu, Joseph, Frank, Fabian, Streit, Mazda, Adli, Nirmala, Akula, Kazufumi, Akiyama, Raffaella, Ardau, Bárbara, Arias, JeanMichel, Aubry, Lena, Backlund, Abesh Kumar, Bhattacharjee, Frank, Bellivier, Antonio, Benabarre, Susanne, Bengesser, Joanna M, Biernacka, Armin, Birner, Clara, Brichant-Petitjean, Pablo, Cervantes, HsiChung, Chen, Caterina, Chillotti, Sven, Cichon, Cristiana, Cruceanu, Piotr M, Czerski, Nina, Dalkner, Alexandre, Dayer, Franziska, Degenhardt, Maria Del, Zompo, J Raymond, DePaulo, Bruno, Étain, Peter, Falkai, Andreas J, Forstner, Louise, Frisen, Mark A, Frye, Janice M, Fullerton, Sébastien, Gard, Julie S, Garnham, Fernando S, Goes, Maria, Grigoroiu-Serbanescu, Paul, Grof, Ryota, Hashimoto, Joanna, Hauser, Urs, Heilbronner, Stefan, Herms, Per, Hoffmann, Andrea, Hofmann, Liping, Hou, Yi-Hsiang, Hsu, Stephane, Jamain, Esther, Jiménez, Jean-Pierre, Kahn, Layla, Kassem, Po-Hsiu, Kuo, Tadafumi, Kato, John, Kelsoe, Sarah, Kittel-Schneider, Sebastian, Kliwicki, Barbara, König, Ichiro, Kusumi, Gonzalo, Laje, Mikael, Landén, Catharina, Lavebratt, Marion, Leboyer, Susan G, Leckband, Mario, Maj, Mirko, Manchia, Lina, Martinsson, Michael J, McCarthy, Susan, McElroy, Francesc, Colom, Marina, Mitjans, Francis M, Mondimore, Palmiero, Monteleone, Caroline M, Nievergelt, Markus M, Nöthen, Tomas, Novák, Claire, O'Donovan, Norio, Ozaki, Vincent, Millischer, Sergi, Papiol, Andrea, Pfennig, Claudia, Pisanu, James B, Potash, Andreas, Reif, Eva, Reininghaus, Guy A, Rouleau, Janusz K, Rybakowski, Martin, Schalling, Peter R, Schofield, Barbara W, Schweizer, Giovanni, Severino, Tatyana, Shekhtman, Paul D, Shilling, Katzutaka, Shimoda, Christian, Simhandl, Claire M, Slaney, Alessio, Squassina, Thomas, Stamm, Pavla, Stopkova, Fasil, TekolaAyele, Alfonso, Tortorella, Gustavo, Turecki, Julia, Veeh, Eduard, Vieta, Stephanie H, Witt, Gloria, Roberts, Peter P, Zandi, Martin, Alda, Michael, Bauer, Francis J, McMahon, Philip B, Mitchell, Thomas G, Schulze, Marcella, Rietschel, Scott R, Clark, and Bernhard T, Baune

Subjects
Machine Learning, Psychiatry and Mental health, Depressive Disorder, Major, Depressive Disorder, Treatment-Resistant, Bipolar Disorder, Humans, Lithium
Published
2022

32. Contribution of early-life unpredictability to neuropsychiatric symptom patterns in adulthood

Author

Andrea D. Spadoni, Meghan Vinograd, Bruna Cuccurazzu, Katy Torres, Laura M. Glynn, Elysia P. Davis, Tallie Z. Baram, Dewleen G. Baker, Caroline M. Nievergelt, and Victoria B. Risbrough

Subjects
Adult, Stress Disorders, Post-Traumatic, Psychiatry and Mental health, Clinical Psychology, Anhedonia, Emotions, Animals, Humans, Anxiety, Anxiety Disorders
Abstract

Recent studies in both human and experimental animals have identified fragmented and unpredictable parental and environmental signals as a novel source of early-life adversity. Early-life unpredictability may be a fundamental developmental factor that impacts brain development, including reward and emotional memory circuits, affecting the risk for psychopathology later in life. Here, we tested the hypothesis that self-reported early-life unpredictability is associated with psychiatric symptoms in adult clinical populations.Using the newly validated Questionnaire of Unpredictability in Childhood, we assessed early-life unpredictability in 156 trauma-exposed adults, of which 65% sought treatment for mood, anxiety, and/or posttraumatic stress disorder (PTSD) symptoms. All participants completed symptom measures of PTSD, depression and anhedonia, anxiety, alcohol use, and chronic pain. Relative contributions of early-life unpredictability versus childhood trauma and associations with longitudinal outcomes over a 6-month period were determined.Early-life unpredictability, independent of childhood trauma, was significantly associated with higher depression, anxiety symptoms, and anhedonia, and was related to higher overall symptom ratings across time. Early-life unpredictability was also associated with suicidal ideation, but not alcohol use or pain symptoms.Early-life unpredictability is an independent and consistent predictor of specific adult psychiatric symptoms, providing impetus for studying mechanisms of its effects on the developing brain that promote risk for psychopathology.

Published
2022

33. 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

34. Rare copy number variation in posttraumatic stress disorder

Author

Adam X, Maihofer, Worrawat, Engchuan, Guillaume, Huguet, Marieke, Klein, Jeffrey R, MacDonald, Omar, Shanta, Bhooma, Thiruvahindrapuram, Martineau, Jean-Louis, Zohra, Saci, Sebastien, Jacquemont, Stephen W, Scherer, Elizabeth, Ketema, Allison E, Aiello, Ananda B, Amstadter, Esmina, Avdibegović, Dragan, Babic, Dewleen G, Baker, Jonathan I, Bisson, Marco P, Boks, Elizabeth A, Bolger, Richard A, Bryant, Angela C, Bustamante, Jose Miguel, Caldas-de-Almeida, Graça, Cardoso, Jurgen, Deckert, Douglas L, Delahanty, Katharina, Domschke, Boadie W, Dunlop, Alma, Dzubur-Kulenovic, Alexandra, Evans, Norah C, Feeny, Carol E, Franz, Aarti, Gautam, Elbert, Geuze, Aferdita, Goci, Rasha, Hammamieh, Miro, Jakovljevic, Marti, Jett, Ian, Jones, Milissa L, Kaufman, Ronald C, Kessler, Anthony P, King, William S, Kremen, Bruce R, Lawford, Lauren A M, Lebois, Catrin, Lewis, Israel, Liberzon, Sarah D, Linnstaedt, Bozo, Lugonja, Jurjen J, Luykx, Michael J, Lyons, Matig R, Mavissakalian, Katie A, McLaughlin, Samuel A, McLean, Divya, Mehta, Rebecca, Mellor, Charles Phillip, Morris, Seid, Muhie, Holly K, Orcutt, Matthew, Peverill, Andrew, Ratanatharathorn, Victoria B, Risbrough, Albert, Rizzo, Andrea L, Roberts, Alex O, Rothbaum, Barbara O, Rothbaum, Peter, Roy-Byrne, Kenneth J, Ruggiero, Bart P F, Rutten, Dick, Schijven, Julia S, Seng, Christina M, Sheerin, Michael A, Sorenson, Martin H, Teicher, Monica, Uddin, Robert J, Ursano, Christiaan H, Vinkers, Joanne, Voisey, Heike, Weber, Sherry, Winternitz, Miguel, Xavier, Ruoting, Yang, Ross, McD Young, Lori A, Zoellner, Rany M, Salem, Richard A, Shaffer, Tianying, Wu, Kerry J, Ressler, Murray B, Stein, Karestan C, Koenen, Jonathan, Sebat, Caroline M, Nievergelt, MUMC+: MA Psychiatrie (3), Psychiatrie & Neuropsychologie, RS: MHeNs - R3 - Neuroscience, Anatomy and neurosciences, Psychiatry, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, Centro de Estudos de Doenças Crónicas (CEDOC), and NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)

Subjects
Stress Disorders, Post-Traumatic, Cellular and Molecular Neuroscience, Psychiatry and Mental health, Genome, SDG 3 - Good Health and Well-being, DNA Copy Number Variations, Humans, Brain, Genetic Predisposition to Disease, Molecular Biology, Polymorphism, Single Nucleotide, 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, MBS, KJRe, and KCK]), and National Institutes of Health (Grant No. 5U01MH109539 [to the Psychiatric Genomics Consortium] and Grant No. U19 MH069056 [to BWD])). Financial support for the PTSD PGC was provided by the Cohen Veterans Bioscience, Stanley Center for Psychiatric Research at the Broad Institute, and One Mind. 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). Posttraumatic stress disorder (PTSD) is a heritable (h2 = 24–71%) psychiatric illness. Copy number variation (CNV) is a form of rare genetic variation that has been implicated in the etiology of psychiatric disorders, but no large-scale investigation of CNV in PTSD has been performed. We present an association study of CNV burden and PTSD symptoms in a sample of 114,383 participants (13,036 cases and 101,347 controls) of European ancestry. CNVs were called using two calling algorithms and intersected to a consensus set. Quality control was performed to remove strong outlier samples. CNVs were examined for association with PTSD within each cohort using linear or logistic regression analysis adjusted for population structure and CNV quality metrics, then inverse variance weighted meta-analyzed across cohorts. We examined the genome-wide total span of CNVs, enrichment of CNVs within specified gene-sets, and CNVs overlapping individual genes and implicated neurodevelopmental regions. The total distance covered by deletions crossing over known neurodevelopmental CNV regions was significant (beta = 0.029, SE = 0.005, P = 6.3 × 10−8). The genome-wide neurodevelopmental CNV burden identified explains 0.034% of the variation in PTSD symptoms. The 15q11.2 BP1-BP2 microdeletion region was significantly associated with PTSD (beta = 0.0206, SE = 0.0056, P = 0.0002). No individual significant genes interrupted by CNV were identified. 22 gene pathways related to the function of the nervous system and brain were significant in pathway analysis (FDR q < 0.05), but these associations were not significant once NDD regions were removed. A larger sample size, better detection methods, and annotated resources of CNV are needed to explore this relationship further. publishersversion published

Published
2022

35. Dissecting the genetic association of C-reactive protein with PTSD, traumatic events, and social support

Author

Dan J. Stein, Renato Polimanti, Murray B. Stein, Sintia Iole Belangero, Jennifer A. Sumner, Caroline M. Nievergelt, Frank R. Wendt, Karestan C. Koenen, Joel Gelernter, Adam X. Maihofer, Carolina Muniz Carvalho, and Sian M. J. Hemmings

Subjects
Linkage disequilibrium, medicine.medical_specialty, Negative association, Polymorphism, Single Nucleotide, Article, Stress Disorders, Post-Traumatic, 03 medical and health sciences, Social support, 0302 clinical medicine, Mendelian randomization, Epidemiology, Humans, Medicine, Child, Socioeconomic status, Genetic association, Pharmacology, biology, business.industry, C-reactive protein, Social Support, 030227 psychiatry, Psychiatry and Mental health, C-Reactive Protein, biology.protein, business, 030217 neurology & neurosurgery, Genome-Wide Association Study, Clinical psychology
Abstract

Inflammatory markers like C-reactive protein (CRP) have been associated with post-traumatic stress disorder (PTSD) and traumatic experiences, but the underlying mechanisms are unclear. We investigated the relationship among serum CRP, PTSD, and traits related to traumatic events and social support using genetic association data from the Psychiatric Genomics Consortium (23,185 PTSD cases and 151,309 controls), the UK Biobank (UKB; up to 117,900 individuals), and the CHARGE study (Cohorts for Heart and Aging Research in Genomic Epidemiology, 148,164 individual). Linkage disequilibrium score regression, polygenic risk scoring, and two-sample Mendelian randomization (MR) analyses were used to investigate genetic overlap and causal relationships. Genetic correlations of CRP were observed with PTSD (rg = 0.16, p = 0.026) and traits related to traumatic events, and the presence of social support (−0.28

Published
2020

36. Network-based integrative analysis of lithium response in bipolar disorder using transcriptomic and GWAS data

Author

Vipavee Niemsiri, Sarah Brin Rosenthal, Caroline M. Nievergelt, Adam X. Maihofer, Maria C. Marchetto, Renata Santos, Tatyana Shekhtman, Ney Alliey-Rodriguez, Amit Anand, Yokesh Balaraman, Wade H. Berrettini, Holli Bertram, Katherine E. Burdick, Joseph R. Calabrese, Cynthia V. Calkin, Carla Conroy, William H. Coryell, Anna DeModena, Scott Feeder, Carrie Fisher, Nicole Frazier, Mark A. Frye, Keming Gao, Julie Garnham, Elliot S. Gershon, Fernando Goes, Toyomi Goto, Gloria J. Harrington, Petter Jakobsen, Masoud Kamali, Marisa Kelly, Susan G. Leckband, Falk Lohoff, Michael J. McCarthy, Melvin G. McInnis, David Craig, Caitlin E. Millett, Francis Mondimore, Gunnar Morken, John I. Nurnberger, Claire O’ Donovan, Ketil J. Øedegaard, Kelly Ryan, Martha Schinagle, Paul D. Shilling, Claire Slaney, Emma K. Stapp, Andrea Stautland, Bruce Tarwater, Peter P. Zandi, Martin Alda, Kathleen M. Fisch, Fred H. Gage, and John R. Kelsoe

Abstract

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA- boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric=1.28E- 09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Published
2022

37. Epigenome-wide meta-analysis of PTSD symptom severity in three military cohorts implicates DNA methylation changes in genes involved in immune system and oxidative stress

Author

Seyma Katrinli, Adam X. Maihofer, Agaz H. Wani, John R. Pfeiffer, Elizabeth Ketema, Andrew Ratanatharathorn, Dewleen G. Baker, Marco P. Boks, Elbert Geuze, Ronald C. Kessler, Victoria B. Risbrough, Bart P. F. Rutten, Murray B. Stein, Robert J. Ursano, Eric Vermetten, Mark W. Logue, Caroline M. Nievergelt, Alicia K. Smith, Monica Uddin, RS: MHeNs - R3 - Neuroscience, Psychiatrie & Neuropsychologie, and MUMC+: MA Psychiatrie (3)

Subjects
Male, EXPRESSION, DISORDER, TRANSMISSION, PROTEIN, Medical and Health Sciences, THROMBOXANE RECEPTOR, ACTIVATION, PATHWAY, Cellular and Molecular Neuroscience, Epigenome, Genetic, Genetics, Humans, 2.1 Biological and endogenous factors, Aetiology, Molecular Biology, Stress Disorders, PROSTANOID RECEPTORS, Psychiatry, Human Genome, Psychology and Cognitive Sciences, Signal Transducing, Adaptor Proteins, DNA Methylation, Biological Sciences, Post-Traumatic Stress Disorder (PTSD), Psychiatry and Mental health, Oxidative Stress, Military Personnel, Mental Health, Good Health and Well Being, Immune System, Post-Traumatic, Epigenesis, PACKAGE
Abstract

Epigenetic factors modify the effects of environmental factors on biological outcomes. Identification of epigenetic changes that associate with PTSD is therefore a crucial step in deciphering mechanisms of risk and resilience. In this study, our goal is to identify epigenetic signatures associated with PTSD symptom severity (PTSS) and changes in PTSS over time, using whole blood DNA methylation (DNAm) data (MethylationEPIC BeadChip) of military personnel prior to and following combat deployment. A total of 429 subjects (858 samples across 2 time points) from three male military cohorts were included in the analyses. We conducted two different meta-analyses to answer two different scientific questions: one to identify a DNAm profile of PTSS using a random effects model including both time points for each subject, and the other to identify a DNAm profile of change in PTSS conditioned on pre-deployment DNAm. Four CpGs near four genes (F2R, CNPY2, BAIAP2L1, and TBXAS1) and 88 differentially methylated regions (DMRs) were associated with PTSS. Change in PTSS after deployment was associated with 15 DMRs, of those 2 DMRs near OTUD5 and ELF4 were also associated with PTSS. Notably, three PTSS-associated CpGs near F2R, BAIAP2L1 and TBXAS1 also showed nominal evidence of association with change in PTSS. This study, which identifies PTSD-associated changes in genes involved in oxidative stress and immune system, provides novel evidence that epigenetic differences are associated with PTSS.

Published
2022

38. Contributors

Author

Charlotte Bainomugisa, Dewleen G. Baker, Marco P. Boks, Dušan Braný, Belinda U. Busogi, Ramón Cacabelos, Shiloh Cleveland, Sonia Dela Cruz, Daniel van den Hove, Dana Dvorská, Alana I.H. Escoto, Gabriel R. Fries, Fred H. Gage, Thorhildur Halldorsdottir, Guang Hao, Richard L. Hauger, Aileen Hsu, Annie Jeong, Jayesh Kamath, Gunter Kenis, Richard S. Lee, Laura Lockwood, Olaia Martínez-Iglesias, Divya Mehta, Janitza L. Montalvo-Ortiz, Vinogran Naidoo, Jessica Nguyen, Caroline M. Nievergelt, Laurence de Nijs, Shota Nishitani, Jeffrey O’Neill, Safiye Bahar Ölmez, Aarti Patel, Bhargav Patel, Parit Patel, Demietrice Pittman, Kristina Reed, Bart P.F. Rutten, Erika M. Salarda, Clara Snijders, Ján Strnádel, Arthur Su, Shaoyong Su, Jennifer A. Sumner, Jordan Thomas, Heiddis B. Valdimarsdottir, Unnur A. Valdimarsdottir, Eric Vermetten, Sophia Walker, Onur Yılmaz, Nagy A. Youssef, and Sheila Zhang

Published
2022

39. Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders

Author

Gabriëlla A.M. Blokland, Jakob Grove, Chia-Yen Chen, Chris Cotsapas, Stuart Tobet, Robert Handa, David St Clair, Todd Lencz, Bryan J. Mowry, Sathish Periyasamy, Murray J. Cairns, Paul A. Tooney, Jing Qin Wu, Brian Kelly, George Kirov, Patrick F. Sullivan, Aiden Corvin, Brien P. Riley, Tõnu Esko, Lili Milani, Erik G. Jönsson, Aarno Palotie, Hannelore Ehrenreich, Martin Begemann, Agnes Steixner-Kumar, Pak C. Sham, Nakao Iwata, Daniel R. Weinberger, Pablo V. Gejman, Alan R. Sanders, Joseph D. Buxbaum, Dan Rujescu, Ina Giegling, Bettina Konte, Annette M. Hartmann, Elvira Bramon, Robin M. Murray, Michele T. Pato, Jimmy Lee, Ingrid Melle, Espen Molden, Roel A. Ophoff, Andrew McQuillin, Nicholas J. Bass, Rolf Adolfsson, Anil K. Malhotra, Nicholas G. Martin, Janice M. Fullerton, Philip B. Mitchell, Peter R. Schofield, Andreas J. Forstner, Franziska Degenhardt, Sabrina Schaupp, Ashley L. Comes, Manolis Kogevinas, José Guzman-Parra, Andreas Reif, Fabian Streit, Lea Sirignano, Sven Cichon, Maria Grigoroiu-Serbanescu, Joanna Hauser, Jolanta Lissowska, Fermin Mayoral, Bertram Müller-Myhsok, Beata Świątkowska, Thomas G. Schulze, Markus M. Nöthen, Marcella Rietschel, John Kelsoe, Marion Leboyer, Stéphane Jamain, Bruno Etain, Frank Bellivier, John B. Vincent, Martin Alda, Claire O’Donovan, Pablo Cervantes, Joanna M. Biernacka, Mark Frye, Susan L. McElroy, Laura J. Scott, Eli A. Stahl, Mikael Landén, Marian L. Hamshere, Olav B. Smeland, Srdjan Djurovic, Arne E. Vaaler, Ole A. Andreassen, Bernhard T. Baune, Tracy Air, Martin Preisig, Rudolf Uher, Douglas F. Levinson, Myrna M. Weissman, James B. Potash, Jianxin Shi, James A. Knowles, Roy H. Perlis, Susanne Lucae, Dorret I. Boomsma, Brenda W.J.H. Penninx, Jouke-Jan Hottenga, Eco J.C. de Geus, Gonneke Willemsen, Yuri Milaneschi, Henning Tiemeier, Hans J. Grabe, Alexander Teumer, Sandra Van der Auwera, Uwe Völker, Steven P. Hamilton, Patrik K.E. Magnusson, Alexander Viktorin, Divya Mehta, Niamh Mullins, Mark J. Adams, Gerome Breen, Andrew M. McIntosh, Cathryn M. Lewis, David M. Hougaard, Merete Nordentoft, Ole Mors, Preben B. Mortensen, Thomas Werge, Thomas D. Als, Anders D. Børglum, Tracey L. Petryshen, Jordan W. Smoller, Jill M. Goldstein, Stephan Ripke, Benjamin M. Neale, 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, 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, Kimberly 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, David Curtis, Michael Davidson, Kenneth L. Davis, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, 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, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, 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, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee Chee Keong, 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, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Sandra Meier, Carin J. Meijer, Bela Melegh, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Vihra Milanova, Younes Mokrab, Derek W. Morris, Kieran C. Murphy, Inez Myin-Germeys, 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, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, 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, Ulrich Schall, Christian R. Schubert, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Hon-Cheong So, Chris C.A. Spencer, 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, Naomi R. Wray, Kari Stefansson, Peter M. Visscher, Douglas H.R. Blackwood, Ariel Darvasi, Enrico Domenici, Michael Gill, Hugh Gurling, Christina M. Hultman, Assen V. Jablensky, Kenneth S. Kendler, Jo Knight, Qingqin S. Li, Jianjun Liu, Steven A. McCarroll, Jennifer L. Moran, Michael J. Owen, Carlos N. Pato, Danielle Posthuma, Pamela Sklar, Jens R. Wendland, Mark J. Daly, Michael C. O’Donovan, Peter Donnelly, Ines Barroso, Jenefer M. Blackwell, Matthew A. Brown, Juan P. Casas, Panos Deloukas, Audrey Duncanson, Janusz Jankowski, Hugh S. Markus, Christopher G. Mathew, Colin N.A. Palmer, Robert Plomin, Anna Rautanen, Stephen J. Sawcer, Richard C. Trembath, Ananth C. Viswanathan, Nicholas W. Wood, Gavin Band, Céline Bellenguez, Colin Freeman, Eleni Giannoulatou, Garrett Hellenthal, Richard Pearson, Matti Pirinen, Amy Strange, Zhan Su, Damjan Vukcevic, Cordelia Langford, Hannah Blackburn, Suzannah J. Bumpstead, Serge Dronov, Sarah Edkins, Matthew Gillman, Emma Gray, Rhian Gwilliam, Naomi Hammond, Sarah E. Hunt, Alagurevathi Jayakumar, Jennifer Liddle, Owen T. McCann, Simon C. Potter, Radhi Ravindrarajah, Michelle Ricketts, Avazeh Tashakkori-Ghanbaria, Matthew Waller, Paul Weston, Pamela Whittaker, Sara Widaa, Mark I. McCarthy, Maria J. Arranz, Steven Bakker, Stephan Bender, Benedicto Crespo-Facorro, Jeremy Hall, Conrad Iyegbe, Stephen Lawrie, Kuang Lin, Don H. Linszen, Ignacio Mata, Muriel Walshe, Matthias Weisbrod, Durk Wiersma, Vassily Trubetskoy, Yunpeng Wang, Jonathan R.I. Coleman, Héléna A. Gaspar, Christiaan A. de Leeuw, Jennifer M. Whitehead Pavlides, Maciej Trzaskowski, Enda M. Byrne, Liam Abbott, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Adebayo Anjorin, Verneri Antilla, Swapnil Awasthi, Judith A. Badner, Marie Bækvad-Hansen, Jack D. Barchas, Nicholas Bass, Michael Bauer, Richard Belliveau, Carsten Bøcker Pedersen, Erlend Bøen, Marco P. Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Jonas Bybjerg-Grauholm, Miquel Casas, Felecia Cerrato, Kimberly Chambert, Alexander W. Charney, Danfeng Chen, Claire Churchhouse, Toni-Kim Clarke, William Coryell, David W. Craig, Cristiana Cruceanu, Piotr M. Czerski, Anders M. Dale, Simone de Jong, Jurgen Del-Favero, J. Raymond DePaulo, Amanda L. Dobbyn, Ashley Dumont, Torbjørn Elvsåshagen, Chun Chieh Fan, Sascha B. Fischer, Matthew Flickinger, Tatiana M. Foroud, Liz Forty, Christine Fraser, Katrin Gade, Diane Gage, Julie Garnham, Claudia Giambartolomei, Marianne Giørtz Pedersen, Jaqueline Goldstein, Scott D. Gordon, Katherine Gordon-Smith, Elaine K. Green, Melissa J. Green, Tiffany A. Greenwood, Weihua Guan, Martin Hautzinger, Urs Heilbronner, Maria Hipolito, Dominic Holland, Laura Huckins, Jessica S. Johnson, Radhika Kandaswamy, Robert Karlsson, Sarah Kittel-Schneider, Anna C. Koller, Ralph Kupka, Catharina Lavebratt, Jacob Lawrence, William B. Lawson, Markus Leber, Phil H. Lee, Shawn E. Levy, Jun Z. Li, Chunyu Liu, Anna Maaser, Donald J. MacIntyre, Pamela B. Mahon, Lina Martinsson, Steve McCarroll, Peter McGuffin, Melvin G. McInnis, James D. McKay, Helena Medeiros, Sarah E. Medland, Fan Meng, Grant W. Montgomery, Thomas W. Mühleisen, Hoang Nguyen, Caroline M. Nievergelt, Annelie Nordin Adolfsson, Evaristus A. Nwulia, Claire O'Donovan, Loes M. Olde Loohuis, Anil P.S. Ori, Lilijana Oruc, Urban Ösby, Amy Perry, Andrea Pfennig, Eline J. Regeer, Céline S. Reinbold, John P. Rice, Fabio Rivas, Margarita Rivera, Euijung Ryu, Cristina Sánchez-Mora, Alan F. Schatzberg, William A. Scheftner, Nicholas J. Schork, Cynthia Shannon Weickert, Tatyana Shehktman, Paul D. Shilling, Claire Slaney, Janet L. Sobell, Christine Søholm Hansen, Anne T. Spijker, Michael Steffens, John S. Strauss, Szabolcs Szelinger, Robert C. Thompson, Thorgeir E. Thorgeirsson, Jens Treutlein, Helmut Vedder, Weiqing Wang, Stanley J. Watson, Thomas W. Weickert, Simon Xi, Wei Xu, Allan H. Young, Peter Zandi, Peng Zhang, Sebastian Zöllner, Abdel Abdellaoui, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Aartjan T.F. Beekman, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, 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, Fernando S. Goes, Lynsey S. Hall, Thomas F. Hansen, Ian B. Hickie, Georg Homuth, Carsten Horn, 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, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Christel M. Middeldorp, Evelin Mihailov, Francis M. Mondimore, Sara Mostafavi, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O'Reilly, Hogni Oskarsson, Jodie N. Painter, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Jorge A. Quiroz, Per Qvist, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Stanley I. Shyn, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Katherine E. Tansey, Henning Teismann, Wesley Thompson, Pippa A. Thomson, Matthew Traylor, André G. Uitterlinden, Daniel Umbricht, Albert M. van Hemert, Shantel Marie Weinsheimer, Jürgen Wellmann, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Volker Arolt, Klaus Berger, Udo Dannlowski, Katharina Domschke, Caroline Hayward, Andrew C. Heath, Stefan Kloiber, Glyn Lewis, Pamela AF. Madden, Patrik K. Magnusson, Preben Bo Mortensen, Michael C. O'Donovan, Sara A. Paciga, Nancy L. Pedersen, David J. Porteous, Catherine Schaefer, Henry Völzke, Marco Bortolato, Janita Bralten, Cynthia M. Bulik, Christie L. Burton, Caitlin E. Carey, Lea K. Davis, Laramie E. Duncan, Howard J. Edenberg, Lauren Erdman, Stephen V. Faraone, Slavina B. Goleva, Wei Guo, Christopher Hübel, Laura M. Huckins, Ekaterina A. Khramtsova, Joanna Martin, Carol A. Mathews, Elise Robinson, Eli Stahl, Barbara E. Stranger, Michela Traglia, Raymond K. Walters, Lauren A. Weiss, Stacey J. Winham, Yin Yao, Kristjar Skajaa, Markus Nöthen, Michael Owen, Robert H. Yolken, Niels Plath, Jonathan Mill, Daniel Geschwind, Psychiatry 1, RS: MHeNs - R2 - Mental Health, Psychiatrie & Neuropsychologie, Centre of Excellence in Complex Disease Genetics, Research Programme of Molecular Medicine, Research Programs Unit, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, Functional Genomics, Biological Psychology, APH - Mental Health, APH - Methodology, Sociology and Social Gerontology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Blokland, Gabriella AM, Grove, Jakob, Chen, Chia Yen, Cotsapas, Chris, Tobet, Stuart, Handa, Robert, Lee, Sang Hong, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Sex Differences Cross-Disorder Analysis Group of the Psychiatric Genomics Consortium, iPSYCH, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Human genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), Child and Adolescent Psychiatry / Psychology, Adult Psychiatry, ANS - Complex Trait Genetics, and ANS - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
0301 basic medicine, Male, Bipolar Disorder, Schizophrenia/genetics, LD SCORE REGRESSION, Genome-wide association study, 0302 clinical medicine, Receptors, SCHIZOPHRENIA, Psychotic Disorders/genetics, KYNURENINE PATHWAY METABOLISM, Genetics, RISK, Sex Characteristics, Vascular Endothelial Growth Factor, Bipolar Disorder/genetics, Major/genetics, Single Nucleotide, AFFECTIVE STIMULI IMPACT, Schizophrenia, Sulfurtransferases, Major depressive disorder, Female, Depressive Disorder, Major/genetics, Bipolar disorder, Locus (genetics), Genomics, Biology, Polymorphism, Single Nucleotide, Article, DYSPHORIC MOOD, 03 medical and health sciences, Sex differences, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Polymorphism, GENOME-WIDE ASSOCIATION, Genotype-by-sex interaction, Biological Psychiatry, Depressive Disorder, Major, Depressive Disorder, GENDER-DIFFERENCES, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], PARAVENTRICULAR NUCLEUS, 3112 Neurosciences, Endothelial Cells, MAJOR DEPRESSION, medicine.disease, Genetic architecture, 030104 developmental biology, Mood, Receptors, Vascular Endothelial Growth Factor, Psychotic Disorders, 3111 Biomedicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Contains fulltext : 248656.pdf (Publisher’s version ) (Closed access) BACKGROUND: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. METHODS: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. RESULTS: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10(-8)), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10(-6)) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10(-7); rs73033497, p = 8.8 × 10(-7); rs7914279, p = 6.4 × 10(-7)), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10(-7)) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10(-7)), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10(-7)) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). CONCLUSIONS: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

Published
2022

40. Prospective examination of pre-trauma anhedonia as a risk factor for post-traumatic stress symptoms

Author

Dean T. Acheson, Meghan Vinograd, Caroline M. Nievergelt, Kate A. Yurgil, Tyler M. Moore, Victoria B. Risbrough, and Dewleen G. Baker

Subjects
Male, Anhedonia, longitudinal, RC435-571, behavioral disciplines and activities, Stress Disorders, Post-Traumatic, reward: post-traumatic stress disorder, 纵向, Young Adult, 奖赏, Reward, Trastorno de Estrés Postraumático, Risk Factors, 前瞻性, Humans, Longitudinal Studies, Prospective Studies, Iraq War, 2003-2011, military, Psychiatry, Recompensa, 军队, Basic Research Article, Afghan Campaign 2001, Psychopathology, prospectivo, militar, prospective, Military Personnel, 创伤后应激障碍, behavior and behavior mechanisms, 快感缺失, psychological phenomena and processes, Research Article
Abstract

Background Anhedonia, the reduction of pleasure and reward-seeking behaviour, is a transdiagnostic symptom with well-described neural circuit mediators. Although typically observed during disease state, extant hypotheses suggest that anhedonia may also be an early risk factor for development of psychopathology. Understanding the contribution of anhedonia to the trauma-response trajectory may bolster inferences about biological mechanisms contributing to pre-trauma risk versus trauma-related symptom expression, knowledge of which could aid in targeted interventions. Objective Using a prospective, longitudinal design in a population at risk for trauma disorders, we tested the hypothesis that anhedonia may be a pre-trauma risk factor for post-traumatic stress disorder (PTSD) symptoms. Methods Adult male participants from the Marine Resilience Study (N = 2,593) were assessed across three time-points (pre-deployment, 3-month and 6-month post-deployment). An anhedonia factor was extracted from self-report instruments pre-trauma and tested for its relationship with development of PTSD re-experiencing symptoms after deployment. Results Higher pre-deployment anhedonia predicted increased PTSD intrusive re-experiencing symptoms at 3- and 6-months post-deployment when controlling for pre-trauma PTSD and depression symptoms. Depression symptoms were not significant predictors of subsequent PTSD intrusive re-experiencing symptoms. Anhedonia at 3 mo also robustly predicted maintenance of PTSD intrusive re-experiencing symptoms at the 6 mo time point. Conclusions Pre-deployment anhedonia may be a pre-trauma risk factor for PTSD, not simply a state-dependent effect of trauma exposure and PTSD symptom expression. Anhedonia may contribute to persistence and/or chronicity of re-experiencing symptoms after the emergence of PTSD symptoms., HIGHLIGHTS Anhedonia in US Marines significantly increased following combat deployment.Anhedonia was associated with re-experiencing symptoms cross-sectionally.Anhedonia was associated with re-experiencing symptoms prospectively.Anhedonia was associated more strongly with re-experiencing compared to depression.

Published
2022
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41. MicroRNAs in posttraumatic stress disorder

Author

Clara Snijders, Alana I.H. Escoto, Dewleen G. Baker, Richard L. Hauger, Daniel van den Hove, Gunter Kenis, Caroline M. Nievergelt, Marco P. Boks, Eric Vermetten, Fred H. Gage, Bart P.F. Rutten, and Laurence de Nijs

Published
2022

42. 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. 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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. 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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

43. Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Author

Michael McCarthy, Claire O'Donovan, Urs Heilbronner, Ichiro Kusumi, Eduard Vieta, Liping Hou, Hsi-Chung Chen, Claire Slaney, Maria Grigoroiu-Serbanescu, Kazufumi Akiyama, Michael Bauer, Janusz K. Rybakowski, Frank Bellivier, Marion Leboyer, Katzutaka Shimoda, Palmiero Monteleone, Cristiana Cruceanu, Alessio Squassina, Stephanie H. Witt, Tadafumi Kato, Giovanni Severino, Alfonso Tortorella, J. Raymond DePaulo, Martin Alda, Louise Frisén, Mazda Adl, Martin Schalling, Per Hoffmann, Susan G. Leckband, Jean-Pierre Kahn, Jean-Michel Aubry, Francis J. McMahon, Sven Cichon, Alexandre Dayer, Tatyana Shekhtman, Franziska Degenhardt, James B. Potash, Bruno Etain, Joseph Frank, Antonio Benabarre, Bernhard T. Baune, Gloria Roberts, Ryota Hashimoto, Tomas Novak, Paul D. Shilling, Julia Veeh, Joanna M. Biernacka, Barbara König, Peter Falkai, Philip B. Mitchell, Urban Ösby, Esther Jiménez, Sébastien Gard, Mark A. Frye, Sarah Kittel-Schneider, Layla Kassem, Fasil Tekola-Ayele, Armin Birner, Cynthia Marie-Claire, Raffaella Ardau, Abesh Kumar Bhattacharjee, Stéphane Jamain, Julie Garnham, Guy A. Rouleau, Caterina Chillotti, Piotr M. Czerski, Thomas G. Schulze, Gustavo Turecki, Anbupalam Thalamuthu, Claudia Pisanu, Azmeraw T. Amare, Marina Mitjans, Sergi Papiol, Mario Maj, Bárbara Arias, Janice M. Fullerton, Nina Dalkner, Peter R. Schofield, Susanne Bengesser, Stefan Herms, Klaus Oliver Schubert, Francis M. Mondimore, Eva Z. Reininghaus, Fernando S. Goes, Lena Backlund, Francesc Colom, Catharina Lavebratt, Christian Simhandl, Marcella Rietschel, Micah Cearns, Mikael Landén, Norio Ozaki, Gonzalo Laje, Barbara W. Schweizer, Nirmala Akula, Andrea Pfennig, Yi-Hsiang Hsu, John R. Kelsoe, Lina Martinsson, Markus M. Nöthen, Caroline M. Nievergelt, Pavla Stopkova, Mirko Manchia, Susan L. McElroy, Peter P. Zandi, Scott R. Clark, Joanna Hauser, Andreas J. Forstner, Po-Hsiu Kuo, Andreas Reif, Maria Del Zompo, Paul Grof, Fabian Streit, Ewa Ferensztajn-Rochowiak, Pablo Cervantes, Thomas Stamm, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Complex Trait Genetics, Psychiatry, APH - Digital Health, Schubert, K. O., Thalamuthu, A., Amare, A. T., Frank, J., Streit, F., Adl, M., Akula, N., Akiyama, K., Ardau, R., Arias, B., Aubry, J. -M., Backlund, L., Bhattacharjee, A. K., Bellivier, F., Benabarre, A., Bengesser, S., Biernacka, J. M., Birner, A., Marie-Claire, C., Cearns, M., Cervantes, P., Chen, H. -C., Chillotti, C., Cichon, S., Clark, S. R., Cruceanu, C., Czerski, P. M., Dalkner, N., Dayer, A., Degenhardt, F., Del Zompo, M., Depaulo, J. R., Etain, B., Falkai, P., Forstner, A. J., Frisen, L., Frye, M. A., Fullerton, J. M., Gard, S., Garnham, J. S., Goes, F. S., Grigoroiu-Serbanescu, M., Grof, P., Hashimoto, R., Hauser, J., Heilbronner, U., Herms, S., Hoffmann, P., Hou, L., Hsu, Y. -H., Jamain, S., Jimenez, E., Kahn, J. -P., Kassem, L., Kuo, P. -H., Kato, T., Kelsoe, J., Kittel-Schneider, S., Ferensztajn-Rochowiak, E., Konig, B., Kusumi, I., Laje, G., Landen, M., Lavebratt, C., Leboyer, M., Leckband, S. G., Maj, M., Manchia, M., Martinsson, L., Mccarthy, M. J., Mcelroy, S., Colom, F., Mitjans, M., Mondimore, F. M., Monteleone, P., Nievergelt, C. M., Nothen, M. M., Novak, T., O'Donovan, C., Ozaki, N., Osby, U., Papiol, S., Pfennig, A., Pisanu, C., Potash, J. B., Reif, A., Reininghaus, E., Rouleau, G. A., Rybakowski, J. K., Schalling, M., Schofield, P. R., Schweizer, B. W., Severino, G., Shekhtman, T., Shilling, P. D., Shimoda, K., Simhandl, C., Slaney, C. M., Squassina, A., Stamm, T., Stopkova, P., Tekola-Ayele, F., Tortorella, A., Turecki, G., Veeh, J., Vieta, E., Witt, S. H., Roberts, G., Zandi, P. P., Alda, M., Bauer, M., Mcmahon, F. J., Mitchell, P. B., Schulze, T. G., Rietschel, M., and Baune, B. T.

Subjects
Oncology, Multifactorial Inheritance, Treatment response, medicine.medical_specialty, Lithium (medication), Bipolar disorder, Poor responder, Neurosciences. Biological psychiatry. Neuropsychiatry, Lithium, DISEASE, Article, Cellular and Molecular Neuroscience, Risk Factors, Internal medicine, medicine, Humans, Manic-depressive illness, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Depressió psíquica, METAANALYSIS, Biological Psychiatry, Depression (differential diagnoses), MANIA, Depressive Disorder, Depressive Disorder, Major, Trastorn bipolar, Depression, business.industry, Major, medicine.disease, Pathway analysis, Liti, COMPARATIVE EFFICACY, Psychiatry and Mental health, Mental depression, Schizophrenia, Polygenic risk score, Esquizofrènia, Pharmacogenomics, business, RC321-571, medicine.drug
Abstract

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium’s therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

Published
2021

44. Epigenome-wide meta-analysis of PTSD symptom severity in three military cohorts implicates DNA methylation changes in genes involved in immune system and oxidative stress

Author

Seyma, Katrinli, Adam X, Maihofer, Agaz H, Wani, John R, Pfeiffer, Elizabeth, Ketema, Andrew, Ratanatharathorn, Dewleen G, Baker, Marco P, Boks, Elbert, Geuze, Ronald C, Kessler, Victoria B, Risbrough, Bart P F, Rutten, Murray B, Stein, Robert J, Ursano, Eric, Vermetten, Mark W, Logue, Caroline M, Nievergelt, Alicia K, Smith, and Monica, Uddin

Subjects
Male, Stress Disorders, Post-Traumatic, Epigenome, Oxidative Stress, Military Personnel, Immune System, Humans, DNA Methylation, Adaptor Proteins, Signal Transducing, Epigenesis, Genetic
Abstract

Epigenetic factors modify the effects of environmental factors on biological outcomes. Identification of epigenetic changes that associate with PTSD is therefore a crucial step in deciphering mechanisms of risk and resilience. In this study, our goal is to identify epigenetic signatures associated with PTSD symptom severity (PTSS) and changes in PTSS over time, using whole blood DNA methylation (DNAm) data (MethylationEPIC BeadChip) of military personnel prior to and following combat deployment. A total of 429 subjects (858 samples across 2 time points) from three male military cohorts were included in the analyses. We conducted two different meta-analyses to answer two different scientific questions: one to identify a DNAm profile of PTSS using a random effects model including both time points for each subject, and the other to identify a DNAm profile of change in PTSS conditioned on pre-deployment DNAm. Four CpGs near four genes (F2R, CNPY2, BAIAP2L1, and TBXAS1) and 88 differentially methylated regions (DMRs) were associated with PTSS. Change in PTSS after deployment was associated with 15 DMRs, of those 2 DMRs near OTUD5 and ELF4 were also associated with PTSS. Notably, three PTSS-associated CpGs near F2R, BAIAP2L1 and TBXAS1 also showed nominal evidence of association with change in PTSS. This study, which identifies PTSD-associated changes in genes involved in oxidative stress and immune system, provides novel evidence that epigenetic differences are associated with PTSS.

Published
2021

45. Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder

Author

Thomas S, Wingo, Ekaterina S, Gerasimov, Yue, Liu, Duc M, Duong, Selina M, Vattathil, Adriana, Lori, Jake, Gockley, Michael S, Breen, Adam X, Maihofer, Caroline M, Nievergelt, Karestan C, Koenen, Daniel F, Levey, Joel, Gelernter, Murray B, Stein, Kerry J, Ressler, David A, Bennett, Allan I, Levey, Nicholas T, Seyfried, and Aliza P, Wingo

Subjects
Stress Disorders, Post-Traumatic, Proteome, Brain, Humans, Genetic Predisposition to Disease, Transcriptome, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Veterans
Abstract

Genome-wide association studies (GWAS) have identified several risk loci for post-traumatic stress disorder (PTSD); however, how they confer PTSD risk remains unclear. We aimed to identify genes that confer PTSD risk through their effects on brain protein abundance to provide new insights into PTSD pathogenesis. To that end, we integrated human brain proteomes with PTSD GWAS results to perform a proteome-wide association study (PWAS) of PTSD, followed by Mendelian randomization, using a discovery and confirmatory study design. Brain proteomes (N = 525) were profiled from the dorsolateral prefrontal cortex using mass spectrometry. The Million Veteran Program (MVP) PTSD GWAS (n = 186,689) was used for the discovery PWAS, and the Psychiatric Genomics Consortium PTSD GWAS (n = 174,659) was used for the confirmatory PWAS. To understand whether genes identified at the protein-level were also evident at the transcript-level, we performed a transcriptome-wide association study (TWAS) using human brain transcriptomes (N = 888) and the MVP PTSD GWAS results. We identified 11 genes that contribute to PTSD pathogenesis via their respective cis-regulated brain protein abundance. Seven of 11 genes (64%) replicated in the confirmatory PWAS and 4 of 11 also had their cis-regulated brain mRNA levels associated with PTSD. High confidence level was assigned to 9 of 11 genes after considering evidence from the confirmatory PWAS and TWAS. Most of the identified genes are expressed in other PTSD-relevant brain regions and several are preferentially expressed in excitatory neurons, astrocytes, and oligodendrocyte precursor cells. These genes are novel, promising targets for mechanistic and therapeutic studies to find new treatments for PTSD.

Published
2021

46. Critical evaluation of copy number variant calling methods using DNA methylation

Author

Adam X. Maihofer, Caroline M. Nievergelt, Karen N. Conneely, Alicia K. Smith, Adriana Lori, Dawayland O. Cobb, Varun Kilaru, Anna K. Knight, Seyma Katrinli, Charles F. Gillespie, and Anne L. Dunlop

Subjects
Adult, 0303 health sciences, DNA Copy Number Variations, Genotype, Epidemiology, 030305 genetics & heredity, Reproducibility of Results, Repeated measures design, Computational biology, Methylation, DNA Methylation, Biology, Article, Cohort Studies, 03 medical and health sciences, Consistency (statistics), DNA methylation, Humans, Female, Copy-number variation, Genetics (clinical), Reliability (statistics), 030304 developmental biology
Abstract

Recent technological and methodological developments have enabled the use of array-based DNA methylation data to call copy number variants (CNVs). ChAMP, Conumee, and cnAnalysis450k are popular methods currently used to call CNVs using methylation data. However, so far, no studies have analyzed the reliability of these methods using real samples. Data from a cohort of individuals with genotype and DNA methylation data generated using the HumanMethylation450 and MethylationEPIC BeadChips were used to assess the consistency between the CNV calls generated by methylation and genotype data. We also took advantage of repeated measures of methylation data collected from the same individuals to compare the reliability of CNVs called by ChAMP, Conumee, and cnAnalysis450k for both the methylation arrays. ChAMP identified more CNVs than Conumee and cnAnalysis450k for both the arrays and, as a consequence, had a higher overlap (~62%) with the calls from the genotype data. However, all methods had relatively low reliability. For the MethylationEPIC array, Conumee had the highest reliability (57.6%), whereas for the HumanMethylation450 array, cnAnalysis450k had the highest reliability (43.0%). Overall, the MethylationEPIC array provided significant gains in reliability for CNV calling over the HumanMethylation450 array but not for overlap with CNVs called using genotype data.

Published
2019

47. Epigenetic meta-analysis across three civilian cohorts identifies NRG1 and HGS as blood-based biomarkers for post-traumatic stress disorder

Author

Allison E. Aiello, Caroline M. Nievergelt, Derek E. Wildman, Karestan C. Koenen, Sandro Galea, Benjamin J. Luft, Don Armstrong, Evelyn J. Bromet, Monica Uddin, Andrew Ratanatharathorn, Alicia K. Smith, Pei Fen Kuan, and Kerry J. Ressler

Subjects
Adult, Epigenomics, Male, 0301 basic medicine, Cancer Research, Neuregulin-1, Biology, behavioral disciplines and activities, Cohort Studies, Stress Disorders, Post-Traumatic, 03 medical and health sciences, mental disorders, Genetics, Humans, Epigenetics, Aged, Demography, Genetic association, Endosomal Sorting Complexes Required for Transport, Blood based biomarkers, Traumatic stress, Genomics, DNA Methylation, Middle Aged, Phosphoproteins, 030104 developmental biology, Meta-analysis, DNA methylation, Female, Biomarkers, Research Article, Cohort study, Clinical psychology
Abstract

Aim: Trauma exposure is a necessary, but not deterministic, contributor to post-traumatic stress disorder (PTSD). Epigenetic factors may distinguish between trauma-exposed individuals with versus without PTSD. Materials & methods: We conducted a meta-analysis of PTSD epigenome-wide association studies in trauma-exposed cohorts drawn from civilian contexts. Whole blood-derived DNA methylation levels were analyzed in 545 study participants, drawn from the three civilian cohorts participating in the PTSD working group of the Psychiatric Genomics Consortium. Results: Two CpG sites significantly associated with current PTSD in NRG1 (cg23637605) and in HGS (cg19577098). Conclusion: PTSD is associated with differential methylation, measured in blood, within HGS and NRG1 across three civilian cohorts.

Published
2018

48. Gene–environment correlations and causal effects of childhood maltreatment on physical and mental health: a genetically informed approach

Author

Marinus H. van IJzendoorn, Alex S. F. Kwong, Andrew J. Grant, Caroline M. Nievergelt, Jazz Croft, Shareefa Dalvie, Marcus R. Munafò, Varun Warrier, Mannan Luo, Ran Barzilay, Charlotte A.M. Cecil, Stephen Burgess, Hannah M Sallis, Tyler M. Moore, Andrew M. McIntosh, Jessie R. Baldwin, Erasmus MC other, Department of Psychology, Education and Child Studies, Clinical Child and Family Studies, Child and Adolescent Psychiatry / Psychology, Epidemiology, Burgess, Stephen [0000-0001-5365-8760], and Apollo - University of Cambridge Repository

Subjects
Adult, Male, Longitudinal study, Adolescent, Databases, Factual, Population, Genome-wide association study, Young Adult, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, medicine, Humans, Longitudinal Studies, 030212 general & internal medicine, Gene–environment interaction, education, health care economics and organizations, Biological Psychiatry, Aged, Retrospective Studies, Aged, 80 and over, education.field_of_study, Adult Survivors of Child Abuse, Mental Disorders, Articles, Middle Aged, medicine.disease, Mental health, Biobank, United Kingdom, 3. Good health, 030227 psychiatry, Europe, Psychiatry and Mental health, Mental Health, Schizophrenia, Female, Gene-Environment Interaction, Generation R, Psychology, Genome-Wide Association Study, Clinical psychology
Abstract

Summary Background Childhood maltreatment is associated with poor mental and physical health. However, the mechanisms of gene–environment correlations and the potential causal effects of childhood maltreatment on health are unknown. Using genetics, we aimed to delineate the sources of gene–environment correlation for childhood maltreatment and the causal relationship between childhood maltreatment and health. Methods We did a genome-wide association study meta-analysis of childhood maltreatment using data from the UK Biobank (n=143 473), Psychiatric Genomics Consortium (n=26 290), Avon Longitudinal Study of Parents and Children (n=8346), Adolescent Brain Cognitive Development Study (n=5400), and Generation R (n=1905). We included individuals who had phenotypic and genetic data available. We investigated single nucleotide polymorphism heritability and genetic correlations among different subtypes, operationalisations, and reports of childhood maltreatment. Family-based and population-based polygenic score analyses were done to elucidate gene–environment correlation mechanisms. We used genetic correlation and Mendelian randomisation analyses to identify shared genetics and test causal relationships between childhood maltreatment and mental and physical health conditions. Findings Our meta-analysis of genome-wide association studies (N=185 414) identified 14 independent loci associated with childhood maltreatment (13 novel). We identified high genetic overlap (genetic correlations 0·24–1·00) among different maltreatment operationalisations, subtypes, and reporting methods. Within-family analyses provided some support for active and reactive gene–environment correlation but did not show the absence of passive gene–environment correlation. Robust Mendelian randomisation suggested a potential causal role of childhood maltreatment in depression (unidirectional), as well as both schizophrenia and ADHD (bidirectional), but not in physical health conditions (coronary artery disease, type 2 diabetes) or inflammation (C-reactive protein concentration). Interpretation Childhood maltreatment has a heritable component, with substantial genetic correlations among different operationalisations, subtypes, and retrospective and prospective reports of childhood maltreatment. Family-based analyses point to a role of active and reactive gene–environment correlation, with equivocal support for passive correlation. Mendelian randomisation supports a (primarily bidirectional) causal role of childhood maltreatment on mental health, but not on physical health conditions. Our study identifies research avenues to inform the prevention of childhood maltreatment and its long-term effects. Funding Wellcome Trust, UK Medical Research Council, Horizon 2020, National Institute of Mental Health, and National Institute for Health Research Biomedical Research Centre.

Published
2021

49. A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex

Author

Jakob Grove, Eric Courchesne, Caitlin E. Carey, Adam X. Maihofer, Maria Arranz, Danny Antaki, Caroline M. Nievergelt, Jonathan Sebat, Elise B. Robinson, A. Hervas, M. Klein, Oanh Hong, A. Muotria, J. Guevara, Karen Pierce, C. Corsello, Lilia M. Iakoucheva, and Joseph G. Gleeson

Subjects
Correlation, Genetics, Genetic etiology, Autism spectrum disorder, mental disorders, medicine, Autism, Polygenic risk score, Biology, Genetic risk, medicine.disease, Phenotype, De novo mutations
Abstract

The genetic etiology of autism spectrum disorder (ASD) is multifactorial with contributions from rare variants, polygenic risk, and sex. How combinations of factors determine risk for ASD is unclear. In 11,313 ASD families (N = 37,375 subjects), we investigated the effects rare and polygenic risk individually and in combination. We show that genetic liability for ASD differs by sex, with females having a greater polygenic load, and males having a lower liability threshold as evident by a negative correlation of rare and polygenic risk. Multiple genetic factors were associated with differing sets of behavioral traits with effects that differed by sex. Furthermore, the correlation of parental age with genetic risk for ASD was attributable tode novomutations and sex-biased effects of inherited risk in parents. Our results demonstrate that a phenotypic spectrum of ASD is attributable to the relative loadings and gene-by-sex effects of rare and common variation.

Published
2021

50. Clinical predictors of non-response to lithium treatment in the Pharmacogenomics of Bipolar Disorder (PGBD) study

Author

Paul D. Shilling, John I. Nurnberger, Michael McCarthy, Martin Alda, Megan Ritchey, Wade H. Berrettini, Vigdis Elin Giever Syrstad, Cynthia V. Calkin, Peter P. Zandi, Gloria Harrington, Fernando S. Goes, William Coryell, Elliot S. Gershon, Yokesh Balaraman, Toyomi Goto, Elizabeth Karberg, Abesh Kumar Bhattacharjee, Joseph R. Calabrese, Bruce Tarwater, Caroline M. Nievergelt, Helle K. Schoeyen, Kelly A. Ryan, John R. Kelsoe, Joanna M. Biernacka, Julie Garnham, Masoud Kamali, Kara Glazer, Falk W. Lohoff, Francis M. Mondimore, Gunnar Morken, Yian Lin, Ney Alliey-Rodriguez, Mark A. Frye, Nicole Frazier, Petter Jakobsen, Marth Shaw, Ole A. Andreassen, Melvin G. McInnis, Adam X. Maihofer, Martha Schinagle, Emma K. Stapp, Susan G. Leckband, Keming Gao, Amit Anand, Carrie Fisher, Marisa Kelly, Claire Slaney, Andrea Stautland, Carla Conroy, Ketil J. Oedegaard, Anna DeModena, Nicole D'Arcangelo, and Holli Bertram

Subjects
medicine.medical_specialty, Bipolar Disorder, Lithium (medication), business.industry, Lithium, medicine.disease, Treatment failure, First line treatment, Psychiatry and Mental health, Pharmacotherapy, Treatment Outcome, Prospective trial, Pharmacogenetics, Internal medicine, Partial response, Pharmacogenomics, medicine, Lithium Compounds, Humans, Bipolar disorder, Prospective Studies, business, Biological Psychiatry, medicine.drug
Abstract

Background Lithium is regarded as a first-line treatment for bipolar disorder (BD), but partial response and non-response commonly occurs. There exists a need to identify lithium non-responders prior to initiating treatment. The Pharmacogenomics of Bipolar Disorder (PGBD) Study was designed to identify predictors of lithium response. Methods The PGBD Study was an eleven site prospective trial of lithium treatment in bipolar I disorder. Subjects were stabilized on lithium monotherapy over 4 months and gradually discontinued from all other psychotropic medications. After ensuring a sustained clinical remission (defined by a score of ≤3 on the CGI for 4 weeks) had been achieved, subjects were followed for up to 2 years to monitor clinical response. Cox proportional hazard models were used to examine the relationship between clinical measures and time until failure to remit or relapse. Results A total of 345 individuals were enrolled into the study and included in the analysis. Of these, 101 subjects failed to remit or relapsed, 88 achieved remission and continued to study completion, and 156 were terminated from the study for other reasons. Significant clinical predictors of treatment failure (p < 0.05) included baseline anxiety symptoms, functional impairments, negative life events and lifetime clinical features such as a history of migraine, suicidal ideation/attempts, and mixed episodes, as well as a chronic course of illness. Conclusions In this PGBD Study of lithium response, several clinical features were found to be associated with failure to respond to lithium. Future validation is needed to confirm these clinical predictors of treatment failure and their use clinically to distinguish who will do well on lithium before starting pharmacotherapy. publishedVersion

Published
2021

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