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73 results on '"Suganthi Balasubramanian"'

1. Relative contribution of biomedical, demographic, and socioeconomic factors to COVID-19 vaccine receipt in rural India

Author: Bethany F. Ferris, Suganthi Balasubramanian, Anuradha Rajamanickam, Saravanan Munisankar, Bindu Dasan, Pradeep A. Menon, P'ng Loke, Subash Babu, and Goylette F. Chami
Subjects: Medicine, Science
Published: 2024

2. PMS2CL interference leading to erroneous identification of a pathogenic PMS2 variant in Black patients

Author: Jacqueline Cappadocia, Lisa B. Aiello, Michael J. Kelley, Bryson W. Katona, Kara N. Maxwell, Anurag Verma, Ph.D., Shefali S. Verma, Ph.D., Yuki Bradford, M.S., Ashlei Brock, Stephanie DerOhannessian, Scott Dudek, M.S., Joseph Dunn, Theodore Drivas, M.D., Ph.D., Ned Haubein, Khadijah Hu-Sain, Renae Judy, Ashley Kloter, Yi-An Ko, Meghan Livingstone, Linda Morrel, Colleen Morse, M.S., Afiya Poindexter, Marjorie Risman, M.S., Teo Tran, Fred Vadivieso, JoEllen Weaver, Daniel J. Rader, M.D., Marylyn D. Ritchie, Ph.D., Michael D. Feldman, M.D., Ph.D., Christina Beechert, Caitlin Forsythe, M.S., Erin D. Fuller, Zhenhua Gu, M.S., Michael Lattari, Alexander Lopez, M.S., John D. Overton, Ph.D., Maria Sotiropoulos Padilla, M.S., Manasi Pradhan, M.S., Kia Manoochehri, B.S., Thomas D. Schleicher, M.S., Louis Widom, Sarah E. Wolf, M.S., Ricardo H. Ulloa, B.S., Amelia Averitt, Ph.D., Nilanjana Banerjee, Ph.D., Michael Cantor, M.D., Dadong Li, Ph.D., Sameer Malhotra, M.D., Deepika Sharma, MHI, Jeffrey Staples, Ph.D., Xiaodong Bai, Ph.D., Suganthi Balasubramanian, Ph.D., Suying Bao, Ph.D., Boris Boutkov, Ph.D., Siying Chen, Ph.D., Gisu Eom, B.S., Lukas Habegger, Ph.D., Alicia Hawes, B.S., Shareef Khalid, Olga Krasheninina, M.S., Rouel Lanche, B.S., Adam J. Mansfield, B.A., Evan K. Maxwell, Ph.D., George Mitra, B.A., Mona Nafde, M.S., Sean O’Keeffe, Ph.D., Max Orelus, B.B.A., Razvan Panea, Ph.D., Tommy Polanco, B.A., Ayesha Rasool, M.S., Jeffrey G. Reid, Ph.D., William Salerno, Ph.D., Jeffrey C. Staples, Ph.D., Kathie Sun, Ph.D., Goncalo Abecasis, D.Phil., Joshua Backman, Ph.D., Amy Damask, Ph.D., Lee Dobbyn, Ph.D., Manuel Allen Revez Ferreira, Ph.D., Arkopravo Ghosh, M.S., Christopher Gillies, Ph.D., Lauren Gurski, B.S., Eric Jorgenson, Ph.D., Hyun Min Kang, Ph.D., Michael Kessler, Ph.D., Jack Kosmicki, Ph.D., Alexander Li, Ph.D., Nan Lin, Ph.D., Daren Liu, M.S., Adam Locke, Ph.D., Jonathan Marchini, Ph.D., Anthony Marcketta, M.S., Joelle Mbatchou, Ph.D., Arden Moscati, Ph.D., Charles Paulding, Ph.D., Carlo Sidore, Ph.D., Eli Stahl, Ph.D., Kyoko Watanabe, Ph.D., Bin Ye, Ph.D., Blair Zhang, Ph.D., Andrey Ziyatdinov, Ph.D., Ariane Ayer, B.S., Aysegul Guvenek, Ph.D., George Hindy, Ph.D., Giovanni Coppola, M.D., Jan Freudenberg, M.D., Jonas Bovijn, M.D., Katherine Siminovitch, M.D., Kavita Praveen, Ph.D., Luca A. Lotta, M.D., Manav Kapoor, Ph.D., Mary Haas, Ph.D., Moeen Riaz, Ph.D., Niek Verweij, Ph.D., Olukayode Sosina, Ph.D., Parsa Akbari, Ph.D., Priyanka Nakka, Ph.D., Sahar Gelfman, Ph.D., Sujit Gokhale, B.E., Tanima De, Ph.D., Veera Rajagopal, Ph.D., Alan Shuldiner, M.D., Gannie Tzoneva, Ph.D., Juan Rodriguez-Flores, Ph.D., Esteban Chen, M.S., Marcus B. Jones, Ph.D., Michelle G. LeBlanc, Ph.D., Jason Mighty, Ph.D., Lyndon J. Mitnaul, Ph.D., Nirupama Nishtala, Ph.D., Nadia Rana, Ph.D., Jaimee Hernandez, Goncalo Abecasis, PhD, Aris Baras, M.D., Andrew Deubler, Aris Economides, Ph.D., and Luca A. Lotta, M.D., Ph.D.
Subjects: PMS2, germline genetic testing, Lynch syndrome, PMS2CL, pseudogene interference, Genetics, QH426-470, Medicine
Abstract: This study investigates the frequency of a clinically reported variant in PMS2, NM_000535.7:c.2523G>A p.(W841∗), from next-generation sequencing studies in 2 racially diverse cohorts. We identified clinical reports of the PMS2 c.2523G>A p.(W841∗) variant in the National Precision Oncology Program’s somatic testing database (n = 25,168). We determined frequency of the variant in germline exome sequencing from the Penn Medicine BioBank (n = 44,256) and in gnomAD. The PMS2 c.2523G>A p.(W841∗) was identified as a homozygous variant on tumor testing in an adult patient of self-identified Black race/ethnicity with no evidence of constitutional mismatch repair deficiency. The variant was clinically reported on 35 total tumor and liquid biopsy tests (0.1%), and all individuals with the variant were of self-identified Black race/ethnicity (0.6% of n = 5787). In individuals of African genetic ancestry (AFR), the variant's germline frequency was reported to be 0.2% and 1.3% in the Penn Medicine BioBank (PMBB) and gnomAD, respectively. The variant cannot be found in any individuals of European genetic ancestry (EUR) from either of the databases. The variant is found in a region of PMS2 with 100% homology to the PMS2CL pseudogene. PMS2 c.2523G>A p.(W841∗), when identified, is typically an African-ancestry-specific PMS2CL pseudogene variant, which should be recognized to prevent misdiagnosis of Lynch syndrome in Blacks.
Published: 2024
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3. Multiancestry exome sequencing reveals INHBE mutations associated with favorable fat distribution and protection from diabetes

Author: Parsa Akbari, Olukayode A. Sosina, Jonas Bovijn, Karl Landheer, Jonas B. Nielsen, Minhee Kim, Senem Aykul, Tanima De, Mary E. Haas, George Hindy, Nan Lin, Ian R. Dinsmore, Jonathan Z. Luo, Stefanie Hectors, Benjamin Geraghty, Mary Germino, Lampros Panagis, Prodromos Parasoglou, Johnathon R. Walls, Gabor Halasz, Gurinder S. Atwal, Regeneron Genetics Center, DiscovEHR Collaboration, Marcus Jones, Michelle G. LeBlanc, Christopher D. Still, David J. Carey, Alice Giontella, Marju Orho-Melander, Jaime Berumen, Pablo Kuri-Morales, Jesus Alegre-Díaz, Jason M. Torres, Jonathan R. Emberson, Rory Collins, Daniel J. Rader, Brian Zambrowicz, Andrew J. Murphy, Suganthi Balasubramanian, John D. Overton, Jeffrey G. Reid, Alan R. Shuldiner, Michael Cantor, Goncalo R. Abecasis, Manuel A. R. Ferreira, Mark W. Sleeman, Viktoria Gusarova, Judith Altarejos, Charles Harris, Aris N. Economides, Vincent Idone, Katia Karalis, Giusy Della Gatta, Tooraj Mirshahi, George D. Yancopoulos, Olle Melander, Jonathan Marchini, Roberto Tapia-Conyer, Adam E. Locke, Aris Baras, Niek Verweij, and Luca A. Lotta
Subjects: Science
Abstract: Fat distribution is associated with cardiometabolic disease, although it has been less well studied than overall obesity. In a multiancestry exome-sequencing study, the authors identified predicted loss-of-function mutations in INHBE associated with favorable fat distribution and protection from type 2 diabetes.
Published: 2022
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4. Population-scale analysis of common and rare genetic variation associated with hearing loss in adults

Author: Kavita Praveen, Lee Dobbyn, Lauren Gurski, Ariane H. Ayer, Jeffrey Staples, Shawn Mishra, Yu Bai, Alexandra Kaufman, Arden Moscati, Christian Benner, Esteban Chen, Siying Chen, Alexander Popov, Janell Smith, GHS-REGN DiscovEHR collaboration, Regeneron Genetics Center, Decibel-REGN collaboration, Olle Melander, Marcus B. Jones, Jonathan Marchini, Suganthi Balasubramanian, Brian Zambrowicz, Meghan C. Drummond, Aris Baras, Goncalo R. Abecasis, Manuel A. Ferreira, Eli A. Stahl, and Giovanni Coppola
Subjects: Biology (General), QH301-705.5
Abstract: A GWAS and exome-wide association study meta-analysis identifies 53 loci affecting hearing loss risk from over half a million individuals across five cohorts. Rare variants in Mendelian hearing loss genes contribute to hearing loss risk in adults.
Published: 2022
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5. Prevalence of proximate risk factors of active tuberculosis in latent tuberculosis infection: A cross-sectional study from South India

Author: Saravanan Munisankar, Anuradha Rajamanickam, Suganthi Balasubramanian, Satishwaran Muthusamy, Pradeep Aravindan Menon, Shaik Fayaz Ahamed, Christopher Whalen, Paschaline Gumne, Inderdeep Kaur, Varma Nadimpalli, Akshay Deverakonda, Zhenhao Chen, John David Otto, Tesfalidet Habitegiyorgis, Harish Kandaswamy, and Subash Babu
Subjects: latent tuberculosis, diabetes mellitus, hypertension, undernutrition, obesity, co-morbidity, Public aspects of medicine, RA1-1270
Abstract: The prevalence of proximate risk factors for active tuberculosis (TB) in areas of high prevalence of latent tuberculosis infection (LTBI) is not clearly understood. We aimed at assessing the prevalence of non-communicable multi-morbidity focusing on diabetes mellitus (DM), malnutrition, and hypertension (HTN) as common risk factors of LTBI progressing to active TB. In a cross-sectional study, 2,351 adults (45% male and 55% female) from villages in the Kancheepuram district of South India were enrolled between 2013 and 2020. DM was defined as HbA1c >6.4%, undernutrition was defined as low body mass index (LBMI) 130 mmHg, and LTBI was defined as positive (≥ 0.35 international units/ml) by QuantiFERON Gold In-Tube assay. A total of 1,226 individuals (52%) were positive for LTBI out of 2351 tested individuals. The prevalence of DM and pre-diabetes mellitus (PDM) was 21 and 35%, respectively, HTN was 15% in latent tuberculosis (LTB)-infected individuals. The association of DM [odds ratio (OR)]; adjusted odds ratio (aOR) (OR = 1.26, 95% CI: 1.13–1.65; aOR = 1.19, 95% CI: 1.10–1.58), PDM (OR = 1.11, 95% CI: 1.0–1.35), and HTN (OR = 1.28, 95% CI: 1.11–1.62; aOR = 1.18, 95% CI: 1.0–1.56) poses as risk factors of LTBI progression to active TB. The prevalence of LBMI 9% (OR = 1.07, 95% CI: 0.78–1.48) and obesity 42% (OR = 0.85, 95% CI: 0.70–1.03) did not show any statistically significant association with LTB-infected individuals. The present evidence of a high burden of multi-morbidity suggests that proximate risk factors of active TB in LTBI can be managed by nutrition and lifestyle modification.
Published: 2022
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6. Seroprevalence of Strongyloides stercoralis infection in a South Indian adult population.

Author: Saravanan Munisankar, Anuradha Rajamanickam, Suganthi Balasubramanian, Satishwaran Muthusamy, Chandra Kumar Dolla, Pradeep Aravindan Menon, Ponnuraja Chinnayan, Christopher Whalen, Paschaline Gumne, Inderdeep Kaur, Varma Nadimpalli, Akshay Deverakonda, Zhenhao Chen, John David Otto, Tesfalidet Habitegiyorgis, Harish Kandaswamy, Thomas B Nutman, and Subash Babu
Subjects: Arctic medicine. Tropical medicine, RC955-962, Public aspects of medicine, RA1-1270
Abstract: BackgroundThe prevalence of Strongyloides stercoralis infection is estimated to be 30-100 million worldwide, although this an underestimate. Most cases remain undiagnosed due to the asymptomatic nature of the infection. We wanted to estimate the seroprevalence of S. stercoralis infection in a South Indian adult population.MethodsTo this end, we performed community-based screening of 2351 individuals (aged 18-65) in Kanchipuram District of Tamil Nadu between 2013 and 2020. Serological testing for S. stercoralis was performed using the NIE ELISA.ResultsOur data shows a seroprevalence of 33% (768/2351) for S. stercoralis infection which had a higher prevalence among males 36% (386/1069) than among females 29.8% (382/1282). Adults aged ≥55 (aOR = 1.65, 95% CI: 1.25-2.18) showed higher adjusted odds of association compared with other age groups. Eosinophil levels (39%) (aOR = 1.43, 95% CI: 1.19-1.74) and hemoglobin levels (24%) (aOR = 1.25, 95% CI: 1.11-1.53) were significantly associated with S. stercoralis infection. In contrast, low BMI (aOR = 1.15, 95% CI: 0.82-1.61) or the presence of diabetes mellitus (OR = 1.18, 95% CI: 0.83-1.69) was not associated with S. stercoralis seropositivity.ConclusionsOur study provides evidence for a very high baseline prevalence of S. stercoralis infection in South Indian communities and this information could provide realistic and concrete planning of control measures.
Published: 2022
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7. Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes

Author: Suganthi Balasubramanian, Yao Fu, Mayur Pawashe, Patrick McGillivray, Mike Jin, Jeremy Liu, Konrad J. Karczewski, Daniel G. MacArthur, and Mark Gerstein
Subjects: Science
Abstract: Variants causing loss of function (LoF) of human genes have clinical implications. Here, the authors present a method to predict disease-causing potential of LoF variants, ALoFT (annotation of Loss-of-Function Transcripts) and show its application to interpreting LoF variants in different contexts.
Published: 2017
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8. Genetic Susceptibility to Mood Disorders and Risk of Stroke: A Polygenic Risk Score and Mendelian Randomization Study

Author: Jiangming Sun, Yan Borné, Andreas Edsfeldt, Yunpeng Wang, Mengyu Pan, Olle Melander, Gunnar Engström, Isabel Gonçalves, Goncalo Abecasis, Aris Baras, Michael Cantor, Giovanni Coppola, Aris Economides, Luca A. Lotta, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Karina Toledo, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H. Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Leland Barnard, Andrew Blumenfeld, Gisu Eom, Lukas Habegger, Young Hahn, Alicia Hawes, Shareef Khalid, Evan K. Maxwell, William Salerno, Jeffrey C. Staples, Ashish Yadav, Marcus B. Jones, and Lyndon J. Mitnaul
Subjects: Advanced and Specialized Nursing, Neurology (clinical), Cardiology and Cardiovascular Medicine
Abstract: Background: Mood disorders and strokes are often comorbid, and their health toll worldwide is huge. This study characterizes prognostic and causal roles of mood disorders in stroke. Methods: We tested if genetic susceptibilities for mood disorders were associated with all strokes, ischemic strokes in the Malmö Diet and Cancer cohort (24 631 individuals with a median follow-up of 21.3 (interquartile range: 16.6–23.2) years. We further examined the causal effects for mood disorders on all strokes and ischemic strokes using summary statistics from large genome-wide association studies of mood disorders (up to 609 424 individuals, Psychiatric Genomics Consortium), all strokes and ischemic strokes (up to 446 696 individuals, MEGASTROKE Consortium). Results: Among 24 366 stroke-free participants at baseline, 2632 individuals developed strokes, 2172 of them ischemic, during follow-up. After properly adjusting for well-known risk factors, participants in the highest quintile of polygenic risk scores for mood disorders had 1.45× (95% CI, 1.21–1.74) higher risk of strokes and 1.44× (95% CI, 1.18–1.76) higher risk of ischemic strokes compared with the lowest quintile in women. Mendelian randomization analyses suggested that mood disorders had a causal effect on strokes (odds ratio, 1.07 [95% CI, 1.03–1.11]) and ischemic strokes (odds ratio, 1.09 [95% CI, 1.04–1.13]). Conclusions: Our results suggest a causal role of mood disorders in the risk of stroke. High-risk women could be identified early in life using polygenic risk scores to ultimately prevent mood disorders and strokes.
Published: 2023
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9. Germline Mutations in CIDEB and Protection against Liver Disease

Author: Niek Verweij, Mary E. Haas, Jonas B. Nielsen, Olukayode A. Sosina, Minhee Kim, Parsa Akbari, Tanima De, George Hindy, Jonas Bovijn, Trikaldarshi Persaud, Lawrence Miloscio, Mary Germino, Lampros Panagis, Kyoko Watanabe, Joelle Mbatchou, Marcus Jones, Michelle LeBlanc, Suganthi Balasubramanian, Craig Lammert, Sofia Enhörning, Olle Melander, David J. Carey, Christopher D. Still, Tooraj Mirshahi, Daniel J. Rader, Prodromos Parasoglou, Johnathon R. Walls, John D. Overton, Jeffrey G. Reid, Aris Economides, Michael N. Cantor, Brian Zambrowicz, Andrew J. Murphy, Goncalo R. Abecasis, Manuel A.R. Ferreira, Eriks Smagris, Viktoria Gusarova, Mark Sleeman, George D. Yancopoulos, Jonathan Marchini, Hyun M. Kang, Katia Karalis, Alan R. Shuldiner, Giusy Della Gatta, Adam E. Locke, Aris Baras, and Luca A. Lotta
Subjects: General Medicine
Published: 2022
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10. Thrombotic risk determined by rare and common SERPINA1 variants in a population‐based cohort study

Author: Eric Manderstedt, Christer Halldén, Christina Lind‐Halldén, Johan Elf, Peter J. Svensson, Gunnar Engström, Olle Melander, Aris Baras, Luca A. Lotta, Bengt Zöller, Goncalo Abecasis, Michael Cantor, Giovanni Coppola, Aris Economides, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Kia Manoochehri, Maria Sotiropoulos Padilla, Manasi Pradhan, Thomas D. Schleicher, Ricardo H. Ulloa, Louis Widom, Sarah E. Wolf, Xiaodong Bai, Suganthi Balasubramanian, Andrew Blumenfeld, Boris Boutkov, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Olga Krasheninina, Rouel Lanche, Adam J. Mansfield, Evan K. Maxwell, Mrunali Nafde, Sean O’Keeffe, Max Orelus, Razvan Panea, Tommy Polanco, Ayesha Rasool, William Salerno, Jeffrey C. Staples, Marcus B. Jones, Jason Mighty, and Lyndon J. Mitnaul
Subjects: Aged, 80 and over, Cohort Studies, Male, Genotype, Case-Control Studies, alpha 1-Antitrypsin, alpha 1-Antitrypsin Deficiency, Humans, Female, Thrombosis, Venous Thromboembolism, Hematology, Aged
Abstract: Severe alpha-1-antitrypsin deficiency (AATD), phenotype PiZZ, was associated with venous thromboembolism (VTE) in a case-control study.This study aimed to determine the genetic variation in the SERPINA1 gene and a possible thrombotic risk of these variants in a population-based cohort study.The coding sequence of SERPINA1 was analyzed for the Z (rs28929474), S (rs17580), and other qualifying variants in 28,794 subjects without previous VTE (born 1923-1950, 60% women), who participated in the Malmö Diet and Cancer study (1991-1996). Individuals were followed from baseline until the first event of VTE, death, or 2018.Resequencing the coding sequence of SERPINA1 identified 84 variants in the total study population, 21 synonymous, 62 missense, and 1 loss-of-function variant. Kaplan-Meier analysis showed that homozygosity for the Z allele increased the risk of VTE whereas heterozygosity showed no effect. The S (rs17580) variant was not associated with VTE. Thirty-one rare variants were qualifying and included in collapsing analysis using the following selection criteria, loss of function, in frame deletion or non-benign (PolyPhen-2) missense variants with minor allele frequency (MAF)0.1%. Combining the rare qualifying variants with the Z variant showed that carrying two alleles (ZZ or compound heterozygotes) showed increased risk. Cox regression analysis revealed an adjusted hazard ratio of 4.5 (95% confidence interval 2.0-10.0) for combinations of the Z variant and rare qualifying variants. One other variant (rs141620200; MAF = 0.002) showed an increased risk of VTE.The SERPINA1 ZZ genotype and compound heterozygotes for severe AATD are rare but associated with VTE in a population-based Swedish study.
Published: 2022
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11. Centers for Mendelian Genomics: A decade of facilitating gene discovery

Author: Samantha M. Baxter, Jennifer E. Posey, Nicole J. Lake, Nara Sobreira, Jessica X. Chong, Steven Buyske, Elizabeth E. Blue, Lisa H. Chadwick, Zeynep H. Coban-Akdemir, Kimberly F. Doheny, Colleen P. Davis, Monkol Lek, Christopher Wellington, Shalini N. Jhangiani, Mark Gerstein, Richard A. Gibbs, Richard P. Lifton, Daniel G. MacArthur, Tara C. Matise, James R. Lupski, David Valle, Michael J. Bamshad, Ada Hamosh, Shrikant Mane, Deborah A. Nickerson, Heidi L. Rehm, Anne O’Donnell-Luria, Marcia Adams, François Aguet, Gulsen Akay, Peter Anderson, Corina Antonescu, Harindra M. Arachchi, Mehmed M. Atik, Christina A. Austin-Tse, Larry Babb, Tamara J. Bacus, Vahid Bahrambeigi, Suganthi Balasubramanian, Yavuz Bayram, Arthur L. Beaudet, Christine R. Beck, John W. Belmont, Jennifer E. Below, Kaya Bilguvar, Corinne D. Boehm, Eric Boerwinkle, Philip M. Boone, Sara J. Bowne, Harrison Brand, Kati J. Buckingham, Alicia B. Byrne, Daniel Calame, Ian M. Campbell, Xiaolong Cao, Claudia Carvalho, Varuna Chander, Jaime Chang, Katherine R. Chao, Ivan K. Chinn, Declan Clarke, Ryan L. Collins, Beryl Cummings, Zain Dardas, Moez Dawood, Kayla Delano, Stephanie P. DiTroia, Harshavardhan Doddapaneni, Haowei Du, Renqian Du, Ruizhi Duan, Mohammad Eldomery, Christine M. Eng, Eleina England, Emily Evangelista, Selin Everett, Jawid Fatih, Adam Felsenfeld, Laurent C. Francioli, Christian D. Frazar, Jack Fu, Emmanuel Gamarra, Tomasz Gambin, Weiniu Gan, Mira Gandhi, Vijay S. Ganesh, Kiran V. Garimella, Laura D. Gauthier, Danielle Giroux, Claudia Gonzaga-Jauregui, Julia K. Goodrich, William W. Gordon, Sean Griffith, Christopher M. Grochowski, Shen Gu, Sanna Gudmundsson, Stacey J. Hall, Adam Hansen, Tamar Harel, Arif O. Harmanci, Isabella Herman, Kurt Hetrick, Hadia Hijazi, Martha Horike-Pyne, Elvin Hsu, Jianhong Hu, Yongqing Huang, Jameson R. Hurless, Steve Jahl, Gail P. Jarvik, Yunyun Jiang, Eric Johanson, Angad Jolly, Ender Karaca, Michael Khayat, James Knight, J. Thomas Kolar, Sushant Kumar, Seema Lalani, Kristen M. Laricchia, Kathryn E. Larkin, Suzanne M. Leal, Gabrielle Lemire, Richard A. Lewis, He Li, Hua Ling, Rachel B. Lipson, Pengfei Liu, Alysia Kern Lovgren, Francesc López-Giráldez, Melissa P. MacMillan, Brian E. Mangilog, Stacy Mano, Dana Marafi, Beth Marosy, Jamie L. Marshall, Renan Martin, Colby T. Marvin, Michelle Mawhinney, Sean McGee, Daniel J. McGoldrick, Michelle Mehaffey, Betselote Mekonnen, Xiaolu Meng, Tadahiro Mitani, Christina Y. Miyake, David Mohr, Shaine Morris, Thomas E. Mullen, David R. Murdock, Mullai Murugan, Donna M. Muzny, Ben Myers, Juanita Neira, Kevin K. Nguyen, Patrick M. Nielsen, Natalie Nudelman, Emily O’Heir, Melanie C. O’Leary, Chrissie Ongaco, Jordan Orange, Ikeoluwa A. Osei-Owusu, Ingrid S. Paine, Lynn S. Pais, Justin Paschall, Karynne Patterson, Davut Pehlivan, Benjamin Pelle, Samantha Penney, Jorge Perez de Acha Chavez, Emma Pierce-Hoffman, Cecilia M. Poli, Jaya Punetha, Aparna Radhakrishnan, Matthew A. Richardson, Eliete Rodrigues, Gwendolin T. Roote, Jill A. Rosenfeld, Erica L. Ryke, Aniko Sabo, Alice Sanchez, Isabelle Schrauwen, Daryl A. Scott, Fritz Sedlazeck, Jillian Serrano, Chad A. Shaw, Tameka Shelford, Kathryn M. Shively, Moriel Singer-Berk, Joshua D. Smith, Hana Snow, Grace Snyder, Matthew Solomonson, Rachel G. Son, Xiaofei Song, Pawel Stankiewicz, Taylorlyn Stephan, V. Reid Sutton, Abigail Sveden, Diana Cornejo Sánchez, Monica Tackett, Michael Talkowski, Machiko S. Threlkeld, Grace Tiao, Miriam S. Udler, Laura Vail, Zaheer Valivullah, Elise Valkanas, Grace E. VanNoy, Qingbo S. Wang, Gao Wang, Lu Wang, Michael F. Wangler, Nicholas A. Watts, Ben Weisburd, Jeffrey M. Weiss, Marsha M. Wheeler, Janson J. White, Clara E. Williamson, Michael W. Wilson, Wojciech Wiszniewski, Marjorie A. Withers, Dane Witmer, Lauren Witzgall, Elizabeth Wohler, Monica H. Wojcik, Isaac Wong, Jordan C. Wood, Nan Wu, Jinchuan Xing, Yaping Yang, Qian Yi, Bo Yuan, Jordan E. Zeiger, Chaofan Zhang, Peng Zhang, Yan Zhang, Xiaohong Zhang, Yeting Zhang, Shifa Zhang, Huda Zoghbi, and Igna van den Veyver
Subjects: Phenotype, Exome Sequencing, Humans, Exome, Genomics, Article, Genetic Association Studies, Genetics (clinical)
Abstract: PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS: Over the past 10 years, the National Institutes of Health–supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION: The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.
Published: 2022
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12. Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions

Author: Brenda Xiao, Digna R. Velez Edwards, Anastasia Lucas, Theodore Drivas, Kathryn Gray, Brendan Keating, Chunhua Weng, Gail P. Jarvik, Hakon Hakonarson, Leah Kottyan, Noemie Elhadad, Wei‐Qi Wei, Yuan Luo, Dokyoon Kim, Marylyn Ritchie, Shefali Setia Verma, Goncalo Abecasis, Aris Baras, Michael Cantor, Giovanni Coppola, Andrew Deubler, Aris Economides, Katia Karalis, Luca A. Lotta, John D. Overton, Jeffrey G. Reid, Katherine Siminovitch, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Maria Sotiropoulos Padilla, Manasi Pradhan, Kia Manoochehri, Thomas D. Schleicher, Louis Widom, Sarah E. Wolf, Ricardo H. Ulloa, Amelia Averitt, Nilanjana Banerjee, Dadong Li, Sameer Malhotra, Deepika Sharma, Jeffrey Staples, Xiaodong Bai, Suganthi Balasubramanian, Suying Bao, Boris Boutkov, Siying Chen, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Olga Krasheninina, Rouel Lanche, Adam J. Mansfield, Evan K. Maxwell, George Mitra, Mona Nafde, Sean O’Keeffe, Max Orelus, Razvan Panea, Tommy Polanco, Ayesha Rasool, William Salerno, Jeffrey C. Staples, Kathie Sun, Joshua Backman, Amy Damask, Lee Dobbyn, Manuel Allen Revez Ferreira, Arkopravo Ghosh, Christopher Gillies, Lauren Gurski, Eric Jorgenson, Hyun Min Kang, Michael Kessler, Jack Kosmicki, Alexander Li, Nan Lin, Daren Liu, Adam Locke, Jonathan Marchini, Anthony Marcketta, Joelle Mbatchou, Arden Moscati, Charles Paulding, Carlo Sidore, Eli Stahl, Kyoko Watanabe, Bin Ye, Blair Zhang, Andrey Ziyatdinov, Ariane Ayer, Aysegul Guvenek, George Hindy, Jan Freudenberg, Jonas Bovijn, Kavita Praveen, Manav Kapoor, Mary Haas, Moeen Riaz, Niek Verweij, Olukayode Sosina, Parsa Akbari, Priyanka Nakka, Sahar Gelfman, Sujit Gokhale, Tanima De, Veera Rajagopal, Gannie Tzoneva, Juan Rodriguez‐Flores, Shek Man Chim, Valerio Donato, Daniel Fernandez, Giusy Della Gatta, Alessandro Di Gioia, Kristen Howell, Lori Khrimian, Minhee Kim, Hector Martinez, Lawrence Miloscio, Sheilyn Nunez, Elias Pavlopoulos, Trikaldarshi Persaud, Esteban Chen, Marcus B. Jones, Michelle G. LeBlanc, Jason Mighty, Lyndon J. Mitnaul, Nirupama Nishtala, and Nadia Rana
Subjects: Cardiology and Cardiovascular Medicine
Abstract: Background Cardiometabolic diseases are highly comorbid, but their relationship with female‐specific or overwhelmingly female‐predominant health conditions (breast cancer, endometriosis, pregnancy complications) is understudied. This study aimed to estimate the cross‐trait genetic overlap and influence of genetic burden of cardiometabolic traits on health conditions unique to women. Methods and Results Using electronic health record data from 71 008 ancestrally diverse women, we examined relationships between 23 obstetrical/gynecological conditions and 4 cardiometabolic phenotypes (body mass index, coronary artery disease, type 2 diabetes, and hypertension) by performing 4 analyses: (1) cross‐trait genetic correlation analyses to compare genetic architecture, (2) polygenic risk score–based association tests to characterize shared genetic effects on disease risk, (3) Mendelian randomization for significant associations to assess cross‐trait causal relationships, and (4) chronology analyses to visualize the timeline of events unique to groups of women with high and low genetic burden for cardiometabolic traits and highlight the disease prevalence in risk groups by age. We observed 27 significant associations between cardiometabolic polygenic scores and obstetrical/gynecological conditions (body mass index and endometrial cancer, body mass index and polycystic ovarian syndrome, type 2 diabetes and gestational diabetes, type 2 diabetes and polycystic ovarian syndrome). Mendelian randomization analysis provided additional evidence of independent causal effects. We also identified an inverse association between coronary artery disease and breast cancer. High cardiometabolic polygenic scores were associated with early development of polycystic ovarian syndrome and gestational hypertension. Conclusions We conclude that polygenic susceptibility to cardiometabolic traits is associated with elevated risk of certain female‐specific health conditions.
Published: 2023
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13. Germline Mutations in

Author: Niek, Verweij, Mary E, Haas, Jonas B, Nielsen, Olukayode A, Sosina, Minhee, Kim, Parsa, Akbari, Tanima, De, George, Hindy, Jonas, Bovijn, Trikaldarshi, Persaud, Lawrence, Miloscio, Mary, Germino, Lampros, Panagis, Kyoko, Watanabe, Joelle, Mbatchou, Marcus, Jones, Michelle, LeBlanc, Suganthi, Balasubramanian, Craig, Lammert, Sofia, Enhörning, Olle, Melander, David J, Carey, Christopher D, Still, Tooraj, Mirshahi, Daniel J, Rader, Prodromos, Parasoglou, Johnathon R, Walls, John D, Overton, Jeffrey G, Reid, Aris, Economides, Michael N, Cantor, Brian, Zambrowicz, Andrew J, Murphy, Goncalo R, Abecasis, Manuel A R, Ferreira, Eriks, Smagris, Viktoria, Gusarova, Mark, Sleeman, George D, Yancopoulos, Jonathan, Marchini, Hyun M, Kang, Katia, Karalis, Alan R, Shuldiner, Giusy, Della Gatta, Adam E, Locke, Aris, Baras, and Luca A, Lotta
Subjects: Liver, Liver Diseases, Exome Sequencing, Humans, Genetic Predisposition to Disease, Apoptosis Regulatory Proteins, Germ-Line Mutation, Transaminases
Abstract: Exome sequencing in hundreds of thousands of persons may enable the identification of rare protein-coding genetic variants associated with protection from human diseases like liver cirrhosis, providing a strategy for the discovery of new therapeutic targets.We performed a multistage exome sequencing and genetic association analysis to identify genes in which rare protein-coding variants were associated with liver phenotypes. We conducted in vitro experiments to further characterize associations.The multistage analysis involved 542,904 persons with available data on liver aminotransferase levels, 24,944 patients with various types of liver disease, and 490,636 controls without liver disease. We found that rare coding variants inRare germline mutations in
Published: 2022

14. Exome sequencing and characterization of 49,960 individuals in the UK Biobank

Author: David J. Carey, Cristen J. Willer, Anthony Marcketta, Claudia Schurmann, Leland Barnard, John Penn, Suganthi Balasubramanian, Daren Liu, Joseph B. Leader, Gonçalo R. Abecasis, Marcus B. Jones, John C. Whittaker, Ashutosh K. Pandey, Ida Surakka, David H. Ledbetter, Evan Maxwell, John D. Overton, Andrew Blumenfeld, Michael N. Cantor, Robert A. Scott, Wendy K. Chung, Alexander H. Li, Alexander Lopez, Joshua D. Backman, Matthew R. Nelson, Jeffrey Staples, Giovanni Coppola, Jonathan Marchini, Xiaodong Bai, Kavita Praveen, Alan R. Shuldiner, Claudia Gonzaga-Jauregui, Aris N. Economides, Shareef Khalid, William J Salerno, Bin Ye, Cristopher V. Van Hout, Kristian Hveem, Jeffrey G. Reid, Colm O'Dushlaine, Joshua D. Hoffman, Laura M. Yerges-Armstrong, Nilanjana Banerjee, Sean O'Keeffe, Ioanna Tachmazidou, Lon R. Cardon, Alicia Hawes, Aris Baras, Ashish Yadav, George D. Yancopoulos, and Lukas Habegger
Subjects: Male, 0301 basic medicine, Genes, BRCA2, Genes, BRCA1, Hasso-Plattner-Institut für Digital Engineering GmbH, Penetrance, 030204 cardiovascular system & hematology, Ion Channels, 0302 clinical medicine, Bone Density, Loss of Function Mutation, Neoplasms, Databases, Genetic, Genetics research, Genotype, Exome, Exome sequencing, Biological Specimen Banks, education.field_of_study, Multidisciplinary, Genomics, Middle Aged, Biobank, Pedigree, Phenotype, ras GTPase-Activating Proteins, Female, Kidney Diseases, Population, Collagen Type VI, Computational biology, Biology, Article, DNA sequencing, Varicose Veins, 03 medical and health sciences, Exome Sequencing, Humans, education, Alleles, Aged, Demography, Rare variants, Peptide Fragments, United Kingdom, 030104 developmental biology, ddc:000, Next-generation sequencing
Abstract: The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community., Exome sequences from the first 49,960 participants in the UK Biobank highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.
Published: 2020
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15. Sequencing of 640,000 exomes identifies GPR75 variants associated with protection from obesity

Author: Jack A. Kosmicki, Charles Paulding, Nan Lin, Andrew J. Murphy, Jerome I. Rotter, Brian Zambrowicz, Niek Verweij, Luca A. Lotta, Michal L. Schwartzman, Giusy Della Gatta, Yii-Der Ida Chen, Alexander H. Li, Suganthi Balasubramanian, Jason M. Torres, Hyun Min Kang, Rory Collins, Parsa Akbari, Michael E. Dunn, Gonçalo R. Abecasis, Christian Benner, David J. Carey, Svati H. Shah, Jonathan Marchini, Giovanni Coppola, Marcus B. Jones, Olle Melander, Christopher D. Still, Yi-Ya Fang, Olukayode A. Sosina, Manuel A. R. Ferreira, Roberto Tapia-Conyer, Michael Cantor, Aris N. Economides, Dylan Sun, Adam E. Locke, Jonathan V. Pascale, Daniel J. Rader, Ankit Gilani, Joelle Mbatchou, Jesus Alegre-Díaz, Mark W. Sleeman, Trikaldarshi Persaud, Jeffrey G. Reid, Pablo Kuri-Morales, Jaime Berumen-Campos, John D. Overton, Aris Baras, Ercument Dirice, Sakib Hossain, Alicia Hawes, George D. Yancopoulos, Jonathan Emberson, Victor Garcia, Judith Altarejos, Lori Khrimian, Katia Karalis, William E. Kraus, Tooraj Mirshahi, Kevin Agostinucci, Alan R. Shuldiner, Center, Regeneron Genetics, and Collaboration, DiscovEHR
Subjects: 0301 basic medicine, Genetics, medicine.medical_specialty, Multidisciplinary, Body Weight, Genomics, Organ Size, Biology, medicine.disease, Obesity, Article, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Genetic variation, medicine, Medical genetics, Humans, medicine.symptom, Body mass index, Weight gain, 030217 neurology & neurosurgery, Exome sequencing, Glycemic
Abstract: Introduction Obesity accounts for a substantial and growing burden of disease globally. Body adiposity is highly heritable, and human genetic studies can lead to biological and therapeutic insights. Rationale Whole-exome sequencing of hundreds of thousands of individuals is complementary to approaches used to date in obesity genetics and has the potential to identify rare protein-coding variants with large phenotypic impact. We sequenced the exomes of 645,626 individuals from the UK, the US, and Mexico and estimated associations of rare coding variants with body mass index (BMI), a measure of overall adiposity used to define obesity in clinical practice. We complemented exome sequencing with fine-mapping of common alleles, polygenic score analysis, and in vitro and in vivo modeling work. Results We identified 16 genes for which the burden of rare nonsynonymous variants was associated with BMI at exome-wide statistical significance (inverse-variance weighted meta-analysis P < 3.6 × 10−7), including associations at five brain-expressed G protein–coupled receptors (CALCR, MC4R, GIPR, GPR151, and GPR75). We observed an overrepresentation of genes highly expressed in the hypothalamus, a key center for the neuroendocrine regulation of energy balance. Protein-truncating variants in GPR75 were found in ~4/10,000 sequenced people and were associated with 1.8 kg/m2 lower BMI, 5.3 kg lower bodyweight, and 54% lower odds of obesity in heterozygous carriers. Knock out of Gpr75 in mice resulted in resistance to weight gain in a high-fat diet model, which was allele-dose dependent (25% and 44% lower weight gain, respectively, for heterozygous Gpr75−/+ mice and knockout Gpr75−/− mice compared with wild type) and accompanied by improved glycemic control and insulin sensitivity. Protein-truncating variants in CALCR were associated with higher BMI and obesity risk, whereas protein-truncating variants in GIPR and two missense alleles [Arg190→Gln (Arg190Gln), Glu288Gly], which we show result in loss of function in vitro, were associated with lower adiposity. Among monogenic obesity genes in the leptin-melanocortin pathway, heterozygous predicted loss-of-function variants in LEP, POMC, PCSK1, and MC4R (but not LEPR) were associated with higher BMI. Rare protein-truncating variants in UBR2, ANO4, and PCSK1 were associated with more than twofold higher odds of obesity in heterozygous carriers, similar to predicted-deleterious nonsynonymous variants in MC4R, which are considered the most common cause of monogenic obesity. Polygenic predisposition due to >2 million common genetic variants influenced the penetrance of obesity in rare variant carriers in an additive fashion. Conclusion These results suggest that inhibition of GPR75 may be a therapeutic strategy for obesity and illustrate the power of massive-scale exome sequencing for the identification of large-effect coding variant associations and drug targets for complex traits.
Published: 2022
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16. Classic Thrombophilias and Thrombotic Risk Among Middle-Aged and Older Adults: A Population-Based Cohort Study

Author: Eric Manderstedt, Christina Lind‐Halldén, Christer Halldén, Johan Elf, Peter J. Svensson, Björn Dahlbäck, Gunnar Engström, Olle Melander, Aris Baras, Luca A. Lotta, Bengt Zöller, Goncalo Abecasis, Michael Cantor, Giovanni Coppola, Aris Economides, Luca A Lotta, John D Overton, Jeffrey G Reid, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D Schleicher, Maria Sotiropoulos Padilla, Louis Widom, Sarah E Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Andrew Blumenfeld, Boris Boutkov, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Olga Krasheninina, Rouel Lanche, Adam J Mansfield, Evan K Maxwell, Mrunali Nafde, Sean O’Keeffe, Max Orelus, Razvan Panea, Tommy Polanco, Ayesha Rasool, William Salerno, Jeffrey C Staples, Marcus B Jones, Jason Mighty, and Lyndon J Mitnaul
Subjects: Male, Anticoagulants, Factor V, Thrombosis, Venous Thromboembolism, Middle Aged, Antithrombins, Protein S, Cohort Studies, Risk Factors, RC666-701, Mutation, natural anticoagulants, Diseases of the circulatory (Cardiovascular) system, Humans, Thrombophilia, epidemiology, genetics, Female, Prothrombin, Cardiology and Cardiovascular Medicine, Aged, Protein C
Abstract: Background Five classic thrombophilias have been recognized: factor V Leiden (rs6025), the prothrombin G20210A variant (rs1799963), and protein C, protein S, and antithrombin deficiencies. This study aimed to determine the thrombotic risk of classic thrombophilias in a cohort of middle‐aged and older adults. Methods and Results Factor V Leiden, prothrombin G20210A and protein‐coding variants in the PROC (protein C), PROS1 (protein S), and SERPINC1 (antithrombin) anticoagulant genes were determined in 29 387 subjects (born 1923–1950, 60% women) who participated in the Malmö Diet and Cancer study (1991–1996). The Human Gene Mutation Database was used to define 68 disease‐causing mutations. Patients were followed up from baseline until the first event of venous thromboembolism (VTE), death, or Dec 31, 2018. Carriership (n=908, 3.1%) for disease‐causing mutations in the PROC , PROS1 , and SERPINC1 genes was associated with incident VTE: Hazard ratio (HR) was 1.6 (95% CI, 1.3–1.9). Variants not in Human Gene Mutation Database were not linked to VTE (HR, 1.1; 95% CI, 0.8–1.5). Heterozygosity for rs6025 and rs1799963 was associated with incident VTE: HR, 1.8 (95% CI, 1.6–2.0) and HR, 1.6 (95% CI, 1.3–2.0), respectively. The HR for carrying 1 classical thrombophilia variant was 1.7 (95% CI, 1.6–1.9). HR was 3.9 (95% CI, 3.1–5.0) for carriers of ≥2 thrombophilia variants. Conclusions The 5 classic thrombophilias are associated with a dose‐graded risk of VTE in middle‐aged and older adults. Disease‐causing variants in the PROC , PROS1 , and SERPINC1 genes were more common than the rs1799963 variant but the conferred genetic risk was comparable with the rs6025 and rs1799963 variants.
Published: 2022

17. Corrigendum to ‘An international genome-wide meta-analysis of primary biliary cholangitis: Novel risk loci and candidate drugs’ [J Hepatol 2021;75(3):572–581]

Author: Heather J. Cordell, James J. Fryett, Kazuko Ueno, Rebecca Darlay, Yoshihiro Aiba, Yuki Hitomi, Minae Kawashima, Nao Nishida, Seik-Soon Khor, Olivier Gervais, Yosuke Kawai, Masao Nagasaki, Katsushi Tokunaga, Ruqi Tang, Yongyong Shi, Zhiqiang Li, Brian D. Juran, Elizabeth J. Atkinson, Alessio Gerussi, Marco Carbone, Rosanna Asselta, Angela Cheung, Mariza de Andrade, Aris Baras, Julie Horowitz, Manuel A.R. Ferreira, Dylan Sun, David E. Jones, Steven Flack, Ann Spicer, Victoria L. Mulcahy, Jinyoung Byun, Younghun Han, Richard N. Sandford, Konstantinos N. Lazaridis, Christopher I. Amos, Gideon M. Hirschfield, Michael F. Seldin, Pietro Invernizzi, Katherine A. Siminovitch, Xiong Ma, Minoru Nakamura, George F. Mells, Andrew Mason, Catherine Vincent, Gang Xie, Jinyi Zhang, Andrea Affronti, Piero L. Almasio, Domenico Alvaro, Pietro Andreone, Angelo Andriulli, Francesco Azzaroli, Pier Maria Battezzati, Antonio Benedetti, Maria Consiglia Bragazzi, Maurizia Brunetto, Savino Bruno, Vincenza Calvaruso, Vincenzo Cardinale, Giovanni Casella, Nora Cazzagon, Antonio Ciaccio, Barbara Coco, Agostino Colli, Guido Colloredo, Massimo Colombo, Silvia Colombo, Laura Cristoferi, Carmela Cursaro, Lory Saveria Crocè, Andrea Crosignani, Daphne D’Amato, Francesca Donato, Gianfranco Elia, Luca Fabris, Stefano Fagiuoli, Carlo Ferrari, Annarosa Floreani, Andrea Galli, Edoardo Giannini, Ignazio Grattagliano, Pietro Lampertico, Ana Lleo, Federica Malinverno, Clara Mancuso, Fabio Marra, Marco Marzioni, Sara Massironi, Alberto Mattalia, Luca Miele, Chiara Milani, Lorenzo Morini, Filomena Morisco, Luigi Muratori, Paolo Muratori, Grazia A. Niro, Sarah O’Donnell, Antonio Picciotto, Piero Portincasa, Cristina Rigamonti, Vincenzo Ronca, Floriano Rosina, Giancarlo Spinzi, Mario Strazzabosco, Mirko Tarocchi, Claudio Tiribelli, Pierluigi Toniutto, Luca Valenti, Maria Vinci, Massimo Zuin, Hitomi Nakamura, Seigo Abiru, Shinya Nagaoka, Atsumasa Komori, Hiroshi Yatsuhashi, Hiromi Ishibashi, Masahiro Ito, Kiyoshi Migita, Hiromasa Ohira, Shinji Katsushima, Atsushi Naganuma, Kazuhiro Sugi, Tatsuji Komatsu, Tomohiko Mannami, Kouki Matsushita, Kaname Yoshizawa, Fujio Makita, Toshiki Nikami, Hideo Nishimura, Hiroshi Kouno, Hirotaka Kouno, Hajime Ota, Takuya Komura, Yoko Nakamura, Masaaki Shimada, Noboru Hirashima, Toshiki Komeda, Keisuke Ario, Makoto Nakamuta, Tsutomu Yamashita, Kiyoshi Furuta, Masahiro Kikuchi, Noriaki Naeshiro, Hironao Takahashi, Yutaka Mano, Seiji Tsunematsu, Iwao Yabuuchi, Yusuke Shimada, Kazuhiko Yamauchi, Rie Sugimoto, Hironori Sakai, Eiji Mita, Masaharu Koda, Satoru Tsuruta, Hiroshi Kamitsukasa, Takeaki Sato, Naohiko Masaki, Tatsuro Kobata, Nobuyoshi Fukushima, Yukio Ohara, Toyokichi Muro, Eiichi Takesaki, Hitoshi Takaki, Tetsuo Yamamoto, Michio Kato, Yuko Nagaoki, Shigeki Hayashi, Jinya Ishida, Yukio Watanabe, Masakazu Kobayashi, Michiaki Koga, Takeo Saoshiro, Michiyasu Yagura, Keisuke Hirata, Atsushu Tanaka, Hajime Takikawa, Mikio Zeniya, Masanori Abe, Morikazu Onji, Shuichi Kaneko, Masao Honda, Kuniaki Arai, Teruko Arinaga-Hino, Etsuko Hashimoto, Makiko Taniai, Takeji Umemura, Satoru Joshita, Kazuhiko Nakao, Tatsuki Ichikawa, Hidetaka Shibata, Satoshi Yamagiwa, Masataka Seike, Koichi Honda, Shotaro Sakisaka, Yasuaki Takeyama, Masaru Harada, Michio Senju, Osamu Yokosuka, Tatsuo Kanda, Yoshiyuki Ueno, Kentaro Kikuchi, Hirotoshi Ebinuma, Takashi Himoto, Michio Yasunami, Kazumoto Murata, Masashi Mizokami, Kazuhito Kawata, Shinji Shimoda, Yasuhiro Miyake, Akinobu Takaki, Kazuhide Yamamoto, Katsuji Hirano, Takafumi Ichida, Akio Ido, Hirohito Tsubouchi, Kazuaki Chayama, Kenichi Harada, Yasuni Nakanuma, Yoshihiko Maehara, Akinobu Taketomi, Ken Shirabe, Yuji Soejima, Akira Mori, Shintaro Yagi, Shinji Uemoto, Egawa H, Tomohiro Tanaka, Noriyo Yamashiki, Sumito Tamura, Yasuhiro Sugawara, Norihiro Kokudo, Naga Chalasani, Vel Luketic, Joseph Odin, Kapil Chopra, Goncalo Abecasis, Michael Cantor, Giovanni Coppola, Aris Economides, Luca A. Lotta, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Karina Toledo, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H. Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Leland Barnard, Andrew Blumenfeld, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Evan K. Maxwell, William Salerno, Jeffrey C. Staples, Marcus B. Jones, Lyndon J. Mitnaul, Richard Sturgess, Christopher Healey, Andrew Yeoman, Anton V.J. Gunasekera, Paul Kooner, Kapil Kapur, V. Sathyanarayana, Yiannis Kallis, Javaid Subhani, Rory Harvey, Roger McCorry, Paul Rooney, David Ramanaden, Richard Evans, Thiriloganathan Mathialahan, Jaber Gasem, Christopher Shorrock, Mahesh Bhalme, Paul Southern, Jeremy A. Tibble, David A. Gorard, Susan Jones, George Mells, Victoria Mulcahy, Brijesh Srivastava, Matthew R. Foxton, Carole E. Collins, David Elphick, Mazn Karmo, Francisco Porras-Perez, Michael Mendall, Tom Yapp, Minesh Patel, Roland Ede, Joanne Sayer, James Jupp, Neil Fisher, Martyn J. Carter, Konrad Koss, Jayshri Shah, Andrzej Piotrowicz, Glyn Scott, Charles Grimley, Ian R. Gooding, Simon Williams, Judith Tidbury, Guan Lim, Kuldeep Cheent, Sass Levi, Dina Mansour, Matilda Beckley, Coral Hollywood, Terry Wong, Richard Marley, John Ramage, Harriet M. Gordon, Jo Ridpath, Theodore Ngatchu, Vijay Paul Bob Grover, Ray G. Shidrawi, George Abouda, L. Corless, Mark Narain, Ian Rees, Ashley Brown, Simon Taylor-Robinson, Joy Wilkins, Leonie Grellier, Paul Banim, Debasish Das, Michael A. Heneghan, Howard Curtis, Helen C. Matthews, Faiyaz Mohammed, Mark Aldersley, Raj Srirajaskanthan, Giles Walker, Alistair McNair, Amar Sharif, Sambit Sen, George Bird, Martin I. Prince, Geeta Prasad, Paul Kitchen, Adrian Barnardo, Chirag Oza, Nurani N. Sivaramakrishnan, Prakash Gupta, Amir Shah, Chris D.J. Evans, Subrata Saha, Katharine Pollock, Peter Bramley, Ashis Mukhopadhya, Stephen T. Barclay, Natasha McDonald, Andrew J. Bathgate, Kelvin Palmer, John F. Dillon, Simon M. Rushbrook, Robert Przemioslo, Chris McDonald, Andrew Millar, Cheh Tai, Stephen Mitchell, Jane Metcalf, Syed Shaukat, Mary Ninkovic, Udi Shmueli, Andrew Davis, Asifabbas Naqvi, Tom J.W. Lee, Stephen Ryder, Jane Collier, Howard Klass, Matthew E. Cramp, Nichols Sharer, Richard Aspinall, Deb Ghosh, Andrew C. Douds, Jonathan Booth, Earl Williams, Hyder Hussaini, John Christie, Steven Mann, Douglas Thorburn, Aileen Marshall, Imran Patanwala, Aftab Ala, Julia Maltby, Ray Matthew, Chris Corbett, Sam Vyas, Saket Singhal, Dermot Gleeson, Sharat Misra, Jeff Butterworth, Keith George, Tim Harding, Andrew Douglass, Harriet Mitchison, Simon Panter, Jeremy Shearman, Gary Bray, Michael Roberts, Graham Butcher, Daniel Forton, Zahid Mahmood, Matthew Cowan, Debashis Das, Chin Lye Ch'ng, Mesbah Rahman, Gregory C.A. Whatley, Emma Wesley, Aditya Mandal, Sanjiv Jain, Stephen P. Pereira, Mark Wright, Palak Trivedi, Fiona H. Gordon, Esther Unitt, Altaf Palejwala, Andrew Austin, Vishwaraj Vemala, Allister Grant, Andrew D. Higham, Alison Brind, Ray Mathew, Mark Cox, Subramaniam Ramakrishnan, Alistair King, Simon Whalley, Jocelyn Fraser, S.J. Thomson, Andrew Bell, Voi Shim Wong, Richard Kia, Ian Gee, Richard Keld, Rupert Ransford, James Gotto, and Charles Millson
Subjects: Science & Technology, Hepatology, Gastroenterology & Hepatology, Italian PBC Study Group, Japan-PBC-GWAS Consortium, UK-PBC Consortium, Chinese PBC Consortium, 1103 Clinical Sciences, US PBC Consortium, Canadian PBC Consortium, Life Sciences & Biomedicine, PBC Consortia, 1117 Public Health and Health Services
Published: 2021

18. VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment.

Author: Lukas Habegger, Suganthi Balasubramanian, David Z. Chen, Ekta Khurana, Andrea Sboner, Arif Ozgun Harmanci, Joel S. Rozowsky, Declan Clarke, Michael Snyder 0001, and Mark Gerstein
Published: 2012
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19. Thrombotic Risk Determined by STAB 2 Variants in a Population-Based Cohort Study

Author: Eric Manderstedt, Christer Halldén, Christina Lind-Halldén, Johan Elf, Peter J. Svensson, Gunnar Engström, Olle Melander, Aris Baras, Luca A Lotta, Bengt Zöller, Goncalo Abecasis, Michael Cantor, Giovanni Coppola, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Katia Karalis, Katherine Siminovitch, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H. Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Andrew Blumenfeld, Boris Boutkov, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Olga Krasheninina, Rouel Lanche, Adam J. Mansfield, Evan K. Maxwell, Mrunali Nafde, Sean O’Keeffe, Max Orelus, Razvan Panea, Tommy Polanco, Ayesha Rasool, William Salerno, Jeffrey C. Staples, Niek Verweij, Jonas Nielsen, Tanima De, Marcus B. Jones, Jason Mighty, Michelle G. LeBlanc, and Lyndon J. Mitnaul
Subjects: Thrombotic risk, medicine.medical_specialty, education.field_of_study, business.industry, Population, General Medicine, medicine.disease, Thrombosis, Population based cohort, Internal medicine, Medicine, business, education, Venous thromboembolism
Published: 2021
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20. Population-scale analysis of common and rare genetic variation associated with hearing loss in adults

Author: Shawn Mishra, Siying Chen, Manuel A. R. Ferreira, Brian Zambrowicz, Jeffrey Staples, Alexander Popov, Yu Bai, Arden Moscati, Alexandra Kaufman, Ariane H. Ayer, Meghan Drummond, Jonathan Marchini, Aris Baras, Janell Smith, Lauren Gurski, Kavita Praveen, Lee Dobbyn, Esteban Chen, Christian Benner, Olle Melander, Gonçalo R. Abecasis, Suganthi Balasubramanian, Marcus Herbert Jones, Giovanni Coppola, and Eli A. Stahl
Subjects: Genetics, education.field_of_study, Hearing loss, Serine Endopeptidases, Population, Genetic Variation, Membrane Proteins, Odds ratio, Biology, Genetic architecture, Neoplasm Proteins, symbols.namesake, Exome Sequencing, Genetic variation, Mendelian inheritance, symbols, Etiology, medicine, Humans, Exome, medicine.symptom, Hearing Loss, education, Exome sequencing, Genome-Wide Association Study
Abstract: Understanding the genetic underpinnings of disabling hearing loss, which affects ∼466 million people worldwide, can provide avenues for new therapeutic target development. We performed a genome-wide association meta-analysis of hearing loss with 125,749 cases and 469,497 controls across five cohorts, including UK Biobank, Geisinger DiscovEHR, the Malmö Diet and Cancer Study, Mount Sinai’s BioMe Personalized Medicine Cohort, and FinnGen. We identified 53 loci affecting hearing loss risk, 15 of which are novel, including common coding variants in COL9A3 and TMPRSS3. Through exome-sequencing of 108,415 cases and 329,581 controls from the same cohorts, we identified hearing loss associations with burden of rare coding variants in FSCN2 (odds ratio [OR] = 1.14, P = 1.9 × 10−15) and burden of predicted loss-of-function variants in KLHDC7B (OR = 2.14, P = 5.2 × 10−30). We also observed single-variant and gene-burden associations with 11 genes known to cause Mendelian forms of hearing loss, including an increased risk in heterozygous carriers of mutations in the autosomal recessive hearing loss genes GJB2 (Gly12fs; OR = 1.21, P = 4.2 × 10−11) and SLC26A5 (gene burden; OR = 1.96, P = 2.8 × 10−17). Our results suggest that loss of KLHDC7B function increases risk for hearing loss, and show that Mendelian hearing loss genes contribute to the burden of hearing loss in the adult population, suggesting a shared etiology between common and rare forms of hearing loss. This work illustrates the potential of large-scale exome sequencing to elucidate the genetic architecture of common traits in which risk is modulated by both common and rare variation.
Published: 2021
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21. Genetic variation of the blood coagulation regulator tissue factor pathway inhibitor and venous thromboembolism among middle‐aged and older adults: A population‐based cohort study

Author: Eric Manderstedt, Christina Lind‐Halldén, Christer Halldén, Johan Elf, Peter J. Svensson, Gunnar Engström, Olle Melander, Aris Baras, Luca A. Lotta, Bengt Zöller, Goncalo Abecasis, Michael Cantor, Giovanni Coppola, Aris Economides, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H. Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Andrew Blumenfeld, Boris Boutkov, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Olga Krasheninina, Rouel Lanche, Adam J. Mansfield, Evan K. Maxwell, Mrunali Nafde, Sean O’Keeffe, Max Orelus, Razvan Panea, Tommy Polanco, Ayesha Rasool, William Salerno, Jeffrey C. Staples, Marcus B. Jones, Jason Mighty, and Lyndon J. Mitnaul
Subjects: Hematology
Abstract: Tissue factor is the main initiator of blood coagulation, and tissue factor pathway inhibitor (TFPI) is the primary inhibitor of the initiation of blood coagulation.The genetic variation ofThe exomes ofNo common variant was associated with VTE. Nine rare variants (two loss-of-function and seven nonbenign missense) were classified as qualifying and included in collapsing analysis. Prevalence of qualifying variants was 0.09%. Five individuals with VTE compared to 17 individuals without VTE carried one qualifying variant. Cox multivariate regression analysis adjusted for age, sex, body mass index, systolic blood pressure, smoking and alcohol consumption, rs6025, rs1799963, and ancestry showed a hazard ratio of 2.9 (95% CI, 1.2-7.1) for rare qualifying variants.Rare qualifying
Published: 2022
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22. Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals

Author: Martin I. Jones, Joseph D. Szustakowski, Giorgio Sirugo, Lukas Habegger, Adam J. Mansfield, Will Salerno, Joshua D. Backman, Athanasios Kousathanas, David J. Carey, Yi-Pin Lai, James F. Wilson, Alison M. Meynert, Anne E. Justice, Alexander H. Li, Jack A. Kosmicki, Anthony Marcketta, Sándor Szalma, Shane McCarthy, A. R. Shuldiner, A. Baras, Daniel J. Rader, Michael N. Cantor, Ashish Yadav, Manuel A. R. Ferreira, F. S. P. Kury, Konrad Rawlik, Loukas Moutsianas, Gonçalo R. Abecasis, Susan P. Walker, Xing Chen, Albert Tenesa, Paul Nioi, Adam E. Locke, Guillaume Butler-Laporte, E. N. Smith, Richard H Scott, Gundula Povysil, Joseph B. Leader, Lauren Gurski, Dorota Pasko, Marylyn D. Ritchie, A. Cordova-Palomera, Kyoko Watanabe, Colm O'Dushlaine, A. O'Neill, Tomoko Nakanishi, Erola Pairo-Castineira, Xiuwen Zheng, Emily Wong, Jeffrey G. Reid, Slavé Petrovski, Julie E. Horowitz, Anurag Verma, Justin W. Davis, Dylan Sun, Sahar Esmaeeli, Heiko Runz, Quanli Wang, John D. Overton, Shareef Khalid, Tooraj Mirshahi, Evan Maxwell, Mark J. Caulfield, Mark Lathrop, Olympe Chazara, Deepika Sharma, David Goldstein, Jonathan Marchini, Xiaodong Bai, Suganthi Balasubramanian, Krzysztof Kiryluk, Nilanjana Banerjee, Rouel Lanche, J. B. Richards, Hyun Min Kang, J. K. Baillie, Yunfeng Huang, Sean O'Keeffe, Erika Kvikstad, Margaret M. Parker, and Joelle Mbatchou
Subjects: Male, 0301 basic medicine, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Biology, 03 medical and health sciences, Current sample, 0302 clinical medicine, Data sequences, Report, Exome Sequencing, Genetics, Humans, Exome, Genetic Predisposition to Disease, 030212 general & internal medicine, Gene, Genetics (clinical), SARS-CoV-2, COVID-19, Prognosis, Hospitalization, 030104 developmental biology, Sample Size, Multiple comparisons problem, Susceptibility locus, Female, Interferons
Abstract: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.
Published: 2021
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23. Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank

Author: Lukas Habegger, Max Orelus, Marcus B. Jones, Anurag Verma, Aris Economides, Shareef Khalid, William J Salerno, Adam J. Mansfield, Luca A. Lotta, Maria Sotiropoulos Padilla, Louis Widom, Michael Cantor, Giovanni Coppola, Katherine L. Nathanson, Suganthi Balasubramanian, Razvan Panea, John D. Overton, Alicia Hawes, Anh D. Le, Jeffrey C. Staples, Danielle L. Mowery, Jason Mighty, Kara N. Maxwell, Renae Judy, Andrew Blumenfeld, Manasi Pradhan, Peter Gabriel, Heena Desai, Caitlin Forsythe, Jeffrey G. Reid, Lyndon J. Mitnaul, Christina Beechert, Xiaodong Bai, Olga Krasheninina, Zhenhua Gu, Abigail Doucette, Mrunali Nafde, Boris Boutkov, Kia Manoochehri, Marylyn D. Ritchie, Tommy Polanco, Rouel Lanche, Alexander E. Lopez, Ryan Hausler, Alan R. Shuldiner, Sarah E. Wolf, Thomas D. Schleicher, Gisu Eom, Shefali S. Verma, Sean O’Keeffe, Ayesha Rasool, Rachel L. Kember, Evan Maxwell, Michael Lattari, Erin D. Fuller, Scott M. Damrauer, Ricardo H. Ulloa, Gonçalo R. Abecasis, Louise Wang, and Aris Baras
Subjects: Gerontology, business.industry, Medicine, Cancer, Polygenic risk score, business, medicine.disease, Biobank
Abstract: PurposeGenome-wide association studies (GWAS) have identified hundreds of single nucleotide polymorphisms (SNPs) significantly associated with several cancers, but the predictive ability of polygenic risk scores (PRS) is unclear, especially among non-Whites.MethodsGenome-wide genotype data was available for 20,079 individuals enrolled in an academic biobank. PRS were derived from significant DNA variants for 15 cancers. We determined the discriminatory accuracy of each cancer-specific PRS in patients of genetically-determined African and European ancestry separately.ResultsAmong individuals of European genetic ancestry, PRS for breast, colon, melanoma, and prostate were significantly associated with their respective cancers (OR 1.25-1.47). Among individuals of African genetic ancestry, PRS for breast, colon, and prostate were significantly associated with their respective cancers. The AUC of a model comprised of age, sex, and principal components was 0.617–0.709 and increased by 1-4% with the PRS in individuals of European genetic ancestry. In individuals of African genetic ancestry, AUC was overall higher in the model without PRS (0.740-0.811) but increased < 1% with the PRS in the majority of cancers.ConclusionPRS constructed from SNPs moderately increased discriminatory ability for cancer status in individuals of European but not African ancestry. Further large-scale studies are needed to identify ancestry-specific genetic factors in non-White populations to incorporate PRS into cancer risk assessment.
Published: 2021
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24. Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank

Author: Louise Wang, Heena Desai, Shefali S. Verma, Anh Le, Ryan Hausler, Anurag Verma, Renae Judy, Abigail Doucette, Peter E. Gabriel, Katherine L. Nathanson, Scott M. Damrauer, Danielle L. Mowery, Marylyn D. Ritchie, Rachel L. Kember, Kara N. Maxwell, Goncalo Abecasis, Xiaodong Bai, Suganthi Balasubramanian, Aris Baras, Andrew Blumenfeld, Boris Boutkov, Michael Cantor, Giovanni Coppola, Aris Economides, Gisu Eom, Lukas Habegger, Alicia Hawes, Marcus B. Jones, Shareef Khalid, Olga Krasheninina, Rouel Lanche, Luca A. Lotta, Adam J. Mansfield, Evan K. Maxwell, Jason Mighty, Lyndon J. Mitnaul, Mrunali Nafde, Sean O’Keeffe, Max Orelus, John D. Overton, Razvan Panea, Tommy Polanco, Ayesha Rasool, Jeffrey G. Reid, William Salerno, Jeffrey C. Staples, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Kia Manoochehri, Manasi Pradhan, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Ricardo H. Ulloa, Louis Widom, and Sarah E. Wolf
Subjects: Male, Multifactorial Inheritance, Risk Factors, Neoplasms, Black People, Humans, Female, Genetic Predisposition to Disease, Genetics (clinical), White People, Biological Specimen Banks, Genome-Wide Association Study
Abstract: Genome-wide association studies have identified hundreds of single nucleotide variations (formerly single nucleotide polymorphisms) associated with several cancers, but the predictive ability of polygenic risk scores (PRSs) is unclear, especially among non-Whites.PRSs were derived from genome-wide significant single-nucleotide variations for 15 cancers in 20,079 individuals in an academic biobank. We evaluated the improvement in discriminatory accuracy by including cancer-specific PRS in patients of genetically-determined African and European ancestry.Among the individuals of European genetic ancestry, PRSs for breast, colon, melanoma, and prostate were significantly associated with their respective cancers. Among the individuals of African genetic ancestry, PRSs for breast, colon, prostate, and thyroid were significantly associated with their respective cancers. The area under the curve of the model consisting of age, sex, and principal components was 0.621 to 0.710, and it increased by 1% to 4% with the inclusion of PRS in individuals of European genetic ancestry. In individuals of African genetic ancestry, area under the curve was overall higher in the model without the PRS (0.723-0.810) but increased by1% with the inclusion of PRS for most cancers.PRS moderately increased the ability to discriminate the cancer status in individuals of European but not African ancestry. Further large-scale studies are needed to identify ancestry-specific genetic factors in non-White populations to incorporate PRS into cancer risk assessment.
Published: 2021

25. Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline

Author: Lukas Habegger, Charumathi Sabanayagam, Michael Preuss, Laura M. Raffield, Mary F. Feitosa, Bamidele O. Tayo, Kevin Ho, Leo-Pekka Lyytikäinen, Florian Kronenberg, Valencia Hui Xian Foo, Adrienne Tin, Michael Cantor, Nisha Bansal, Tarunveer S. Ahluwalia, Melanie Waldenberger, Sarah A. Pendergrass, Behrooz Z. Alizadeh, Wolfgang Koenig, Qiong Yang, Xiaodong Bai, Christoph Wanner, Ben Schöttker, Giovanni Coppola, A. R. Shuldiner, Leslie A. Lange, Piyush Gampawar, Markus Scholz, Tien Yin Wong, Mary L. Biggs, Morris Swertz, Alicia Hawes, Girish N. Nadkarni, Christina-Alexandra Schulz, Chiea Chuen Khor, Ricardo H. Ulloa, Jeffrey C. Staples, Miao-Li Chee, Laura M. Yerges-Armstrong, Andrew Blumenfeld, Karlhans Endlich, Bernhard Banas, Bruce H.R. Wolffenbuttel, Kai-Uwe Eckardt, Pavel Hamet, Carsten A. Böger, Harold Snieder, Marcus B. Jones, Judy Wang, Shih-Jen Hwang, Mathias Gorski, Anselm Hoppmann, Josyf C. Mychaleckyj, Bernd Holleczek, Pamela R. Matias-Garcia, Rainer Rettig, Karsten B. Sieber, Manasi Pradhan, Pashupati P. Mishra, Peter Rossing, Matthias Wuttke, Miao-Ling Chee, H. Marike Boezen, Yong Li, M. Arfan Ikram, Jeffrey G. Reid, Teresa Nutile, Maria Sotiropoulos Padilla, Lude Franke, Robert J. Carroll, Luca A. Lotta, Bernhard K. Krämer, Kjell Nikus, Jerome I. Rotter, Thomas Meitinger, Lars Wallentin, Cisca Wijmenga, Kent D. Taylor, Holly Kramer, Louis Widom, Olli T. Raitakari, Marcus E. Kleber, Man Li, Nina Hutri-Kähönen, Massimiliano Cocca, Reinhold Schmidt, John D. Overton, Cristian Pattaro, Michael Lattari, Sarah E. Wolf, Jin-Fang Chai, Karina Toledo, Brigitte Kühnel, Zhenhua Gu, Peter Almgren, Caitlin Forsythe, Yuri Milaneschi, Stephan J. L. Bakker, Layal Chaker, Dawn M. Waterworth, Silke Szymczak, James G. Wilson, Peter J. van der Most, Michelle L. O'Donoghue, William Salerno, Masayuki Yasuda, Sahar Ghasemi, Eric Boerwinkle, Josef Coresh, Ilja M. Nolte, Kia Manoochehri, Konstantin Strauch, Thomas D. Schleicher, Myriam Rheinberger, Audrey Y. Chu, Sanaz Sedaghat, Sandra Freitag-Wolf, Boting Ning, Matthias Nauck, Christina Beechert, Helena Schmidt, Harvey D. White, Nina Mononen, Johanne Tremblay, Navya Shilpa Josyula, Mika Kähönen, Katrin Horn, Andre Franke, Marianne Rots, Bettina Jung, Alexander R. Rosenkranz, Christian M. Shaffer, Mary Ann Lukas, Gerjan Navis, Christian Gieger, John Chalmers, Shareef Khalid, Uwe Völker, Marju Orho-Melander, Iris M. Heid, Brenda W.J.H. Penninx, A. Baras, Alexander Lopez, Evan Maxwell, Ruth J. F. Loos, Erin D. Fuller, Christa Meisinger, Gonçalo R. Abecasis, Suganthi Balasubramanian, Chris H. L. Thio, Martin H. de Borst, Stefan Coassin, Ching-Yu Cheng, Wolfgang Lieb, Kenneth Rice, Alexander Teumer, Mark Woodward, Gisu Eom, Hermann Brenner, Thomas W. Winkler, Anna Köttgen, Edith Hofer, Aris Economides, Ron T. Gansevoort, Pim van der Harst, Lyndon J. Mitnaul, Bruce M. Psaty, Erwin P. Bottinger, Olle Melander, Niek Verweij, Frauke Degenhardt, Yan Zhang, Mohsen Ghanbari, Veronika Wanner, Terho Lehtimäki, Leland Barnard, Tampere University, Primary Health Care, Department of Paediatrics, Clinical Medicine, Department of Clinical Physiology and Nuclear Medicine, Department of Clinical Chemistry, TAYS Heart Centre, Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Cardiovascular Centre (CVC), Life Course Epidemiology (LCE), Department of Marketing Management, Epidemiology, Internal Medicine, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, and APH - Digital Health
Subjects: 0301 basic medicine, medicine.medical_specialty, Genome-wide association study, 030232 urology & nephrology, Protein Disulfide-Isomerases, Hasso-Plattner-Institut für Digital Engineering GmbH, Renal function, Locus (genetics), Biology, AMP-Activated Protein Kinases, Kidney, 3121 Internal medicine, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, end-stage kidney disease, rapid eGFRcrea decline, Urologi och njurmedicin, medicine, Humans, Urology and Nephrology, ddc:610, Allele, Genetic association, Genetics, Creatinine, genome-wide association study, Acute kidney injury, acute kidney injury, medicine.disease, United Kingdom, ddc, 030104 developmental biology, chemistry, Nephrology, Medical genetics, 3111 Biomedicine, 610 Medizin und Gesundheit, Glomerular Filtration Rate
Abstract: Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m(2)/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m(2) at follow-up among those with eGFRcrea 60 mL/min/1.73m(2) or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or (LARP4B). Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function., Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät; 19
Published: 2021
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26. An international genome-wide meta-analysis of primary biliary cholangitis: Novel risk loci and candidate drugs

Author: Heather J. Cordell, James J. Fryett, Kazuko Ueno, Rebecca Darlay, Yoshihiro Aiba, Yuki Hitomi, Minae Kawashima, Nao Nishida, Seik-Soon Khor, Olivier Gervais, Yosuke Kawai, Masao Nagasaki, Katsushi Tokunaga, Ruqi Tang, Yongyong Shi, Zhiqiang Li, Brian D. Juran, Elizabeth J. Atkinson, Alessio Gerussi, Marco Carbone, Rosanna Asselta, Angela Cheung, Mariza de Andrade, Aris Baras, Julie Horowitz, Manuel A.R. Ferreira, Dylan Sun, David E. Jones, Steven Flack, Ann Spicer, Victoria L. Mulcahy, Jinyoung Byan, Younghun Han, Richard N. Sandford, Konstantinos N. Lazaridis, Christopher I. Amos, Gideon M. Hirschfield, Michael F. Seldin, Pietro Invernizzi, Katherine A. Siminovitch, Xiong Ma, Minoru Nakamura, George F. Mells, Andrew Mason, Catherine Vincent, Gang Xie, Jinyi Zhang, Andrea Affronti, Piero L. Almasio, Domenico Alvaro, Pietro Andreone, Angelo Andriulli, Francesco Azzaroli, Pier Maria Battezzati, Antonio Benedetti, MariaConsiglia Bragazzi, Maurizia Brunetto, Savino Bruno, Vincenza Calvaruso, Vincenzo Cardinale, Giovanni Casella, Nora Cazzagon, Antonio Ciaccio, Barbara Coco, Agostino Colli, Guido Colloredo, Massimo Colombo, Silvia Colombo, Laura Cristoferi, Carmela Cursaro, Lory Saveria Crocè, Andrea Crosignani, Daphne D’Amato, Francesca Donato, Gianfranco Elia, Luca Fabris, Stefano Fagiuoli, Carlo Ferrari, Annarosa Floreani, Andrea Galli, Edoardo Giannini, Ignazio Grattagliano, Pietro Lampertico, Ana Lleo, Federica Malinverno, Clara Mancuso, Fabio Marra, Marco Marzioni, Sara Massironi, Alberto Mattalia, Luca Miele, Chiara Milani, Lorenzo Morini, Filomena Morisco, Luigi Muratori, Paolo Muratori, Grazia A. Niro, Sarah O’Donnell, Antonio Picciotto, Piero Portincasa, Cristina Rigamonti, Vincenzo Ronca, Floriano Rosina, Giancarlo Spinzi, Mario Strazzabosco, Mirko Tarocchi, Claudio Tiribelli, Pierluigi Toniutto, Luca Valenti, Maria Vinci, Massimo Zuin, Hitomi Nakamura, Seigo Abiru, Shinya Nagaoka, Atsumasa Komori, Hiroshi Yatsuhashi, Hiromi Ishibashi, Masahiro Ito, Kiyoshi Migita, Hiromasa Ohira, Shinji Katsushima, Atsushi Naganuma, Kazuhiro Sugi, Tatsuji Komatsu, Tomohiko Mannami, Kouki Matsushita, Kaname Yoshizawa, Fujio Makita, Toshiki Nikami, Hideo Nishimura, Hiroshi Kouno, Hirotaka Kouno, Hajime Ota, Takuya Komura, Yoko Nakamura, Masaaki Shimada, Noboru Hirashima, Toshiki Komeda, Keisuke Ario, Makoto Nakamuta, Tsutomu Yamashita, Kiyoshi Furuta, Masahiro Kikuchi, Noriaki Naeshiro, Hironao Takahashi, Yutaka Mano, Seiji Tsunematsu, Iwao Yabuuchi, Yusuke Shimada, Kazuhiko Yamauchi, Rie Sugimoto, Hironori Sakai, Eiji Mita, Masaharu Koda, Satoru Tsuruta, Hiroshi Kamitsukasa, Takeaki Sato, Naohiko Masaki, Tatsuro Kobata, Nobuyoshi Fukushima, Yukio Ohara, Toyokichi Muro, Eiichi Takesaki, Hitoshi Takaki, Tetsuo Yamamoto, Michio Kato, Yuko Nagaoki, Shigeki Hayashi, Jinya Ishida, Yukio Watanabe, Masakazu Kobayashi, Michiaki Koga, Takeo Saoshiro, Michiyasu Yagura, Keisuke Hirata, Atsushu Tanaka, Hajime Takikawa, Mikio Zeniya, Masanori Abe, Morikazu Onji, Shuichi Kaneko, Masao Honda, Kuniaki Arai, Teruko Arinaga-Hino, Etsuko Hashimoto, Makiko Taniai, Takeji Umemura, Satoru Joshita, Kazuhiko Nakao, Tatsuki Ichikawa, Hidetaka Shibata, Satoshi Yamagiwa, Masataka Seike, Koichi Honda, Shotaro Sakisaka, Yasuaki Takeyama, Masaru Harada, Michio Senju, Osamu Yokosuka, Tatsuo Kanda, Yoshiyuki Ueno, Kentaro Kikuchi, Hirotoshi Ebinuma, Takashi Himoto, Michio Yasunami, Kazumoto Murata, Masashi Mizokami, Kazuhito Kawata, Shinji Shimoda, Yasuhiro Miyake, Akinobu Takaki, Kazuhide Yamamoto, Katsuji Hirano, Takafumi Ichida, Akio Ido, Hirohito Tsubouchi, Kazuaki Chayama, Kenichi Harada, Yasuni Nakanuma, Yoshihiko Maehara, Akinobu Taketomi, Ken Shirabe, Yuji Soejima, Akira Mori, Shintaro Yagi, Shinji Uemoto, Egawa H, Tomohiro Tanaka, Noriyo Yamashiki, Sumito Tamura, Yasuhiro Sugawara, Norihiro Kokudo, Naga Chalasani, Vel Luketic, Joseph Odin, Kapil Chopra, Goncalo Abecasis, Michael Cantor, Giovanni Coppola, Aris Economides, Luca A. Lotta, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Karina Toledo, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H. Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Leland Barnard, Andrew Blumenfeld, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Evan K. Maxwell, William Salerno, Jeffrey C. Staples, Marcus B. Jones, Lyndon J. Mitnaul, Richard Sturgess, Christopher Healey, Andrew Yeoman, Anton VJ. Gunasekera, Paul Kooner, Kapil Kapur, V. Sathyanarayana, Yiannis Kallis, Javaid Subhani, Rory Harvey, Roger McCorry, Paul Rooney, David Ramanaden, Richard Evans, Thiriloganathan Mathialahan, Jaber Gasem, Christopher Shorrock, Mahesh Bhalme, Paul Southern, Jeremy A. Tibble, David A. Gorard, Susan Jones, George Mells, Victoria Mulcahy, Brijesh Srivastava, Matthew R. Foxton, Carole E. Collins, David Elphick, Mazn Karmo, Francisco Porras-Perez, Michael Mendall, Tom Yapp, Minesh Patel, Roland Ede, Joanne Sayer, James Jupp, Neil Fisher, Martyn J. Carter, Konrad Koss, Jayshri Shah, Andrzej Piotrowicz, Glyn Scott, Charles Grimley, Ian R. Gooding, Simon Williams, Judith Tidbury, Guan Lim, Kuldeep Cheent, Sass Levi, Dina Mansour, Matilda Beckley, Coral Hollywood, Terry Wong, Richard Marley, John Ramage, Harriet M. Gordon, Jo Ridpath, Theodore Ngatchu, Vijay Paul Bob Grover, Ray G. Shidrawi, George Abouda, L. Corless, Mark Narain, Ian Rees, Ashley Brown, Simon Taylor-Robinson, Joy Wilkins, Leonie Grellier, Paul Banim, Debasish Das, Michael A. Heneghan, Howard Curtis, Helen C. Matthews, Faiyaz Mohammed, Mark Aldersley, Raj Srirajaskanthan, Giles Walker, Alistair McNair, Amar Sharif, Sambit Sen, George Bird, Martin I. Prince, Geeta Prasad, Paul Kitchen, Adrian Barnardo, Chirag Oza, Nurani N. Sivaramakrishnan, Prakash Gupta, Amir Shah, Chris DJ. Evans, Subrata Saha, Katharine Pollock, Peter Bramley, Ashis Mukhopadhya, Stephen T. Barclay, Natasha McDonald, Andrew J. Bathgate, Kelvin Palmer, John F. Dillon, Simon M. Rushbrook, Robert Przemioslo, Chris McDonald, Andrew Millar, Cheh Tai, Stephen Mitchell, Jane Metcalf, Syed Shaukat, Mary Ninkovic, Udi Shmueli, Andrew Davis, Asifabbas Naqvi, Tom JW. Lee, Stephen Ryder, Jane Collier, Howard Klass, Matthew E. Cramp, Nichols Sharer, Richard Aspinall, Deb Ghosh, Andrew C. Douds, Jonathan Booth, Earl Williams, Hyder Hussaini, John Christie, Steven Mann, Douglas Thorburn, Aileen Marshall, Imran Patanwala, Aftab Ala, Julia Maltby, Ray Matthew, Chris Corbett, Sam Vyas, Saket Singhal, Dermot Gleeson, Sharat Misra, Jeff Butterworth, Keith George, Tim Harding, Andrew Douglass, Harriet Mitchison, Simon Panter, Jeremy Shearman, Gary Bray, Michael Roberts, Graham Butcher, Daniel Forton, Zahid Mahmood, Matthew Cowan, Debashis Das, Chin Lye Ch’ng, Mesbah Rahman, Gregory C.A. Whatley, Emma Wesley, Aditya Mandal, Sanjiv Jain, Stephen P. Pereira, Mark Wright, Palak Trivedi, Fiona H. Gordon, Esther Unitt, Altaf Palejwala, Andrew Austin, Vishwaraj Vemala, Allister Grant, Andrew D. Higham, Alison Brind, Ray Mathew, Mark Cox, Subramaniam Ramakrishnan, Alistair King, Simon Whalley, Jocelyn Fraser, S.J. Thomson, Andrew Bell, Voi Shim Wong, Richard Kia, Ian Gee, Richard Keld, Rupert Ransford, James Gotto, Charles Millson, Cordell, H. J., Fryett, J. J., Ueno, K., Darlay, R., Aiba, Y., Hitomi, Y., Kawashima, M., Nishida, N., Khor, S. -S., Gervais, O., Kawai, Y., Nagasaki, M., Tokunaga, K., Tang, R., Shi, Y., Li, Z., Juran, B. D., Atkinson, E. J., Gerussi, A., Carbone, M., Asselta, R., Cheung, A., de Andrade, M., Baras, A., Horowitz, J., Ferreira, M. A. R., Sun, D., Jones, D. E., Flack, S., Spicer, A., Mulcahy, V. L., Byan, J., Han, Y., Sandford, R. N., Lazaridis, K. N., Amos, C. I., Hirschfield, G. M., Seldin, M. F., Invernizzi, P., Siminovitch, K. A., Ma, X., Nakamura, M., Mells, G. F., Mason, A., Vincent, C., Xie, G., Zhang, J., Affronti, A., Almasio, P. L., Alvaro, D., Andreone, P., Andriulli, A., Azzaroli, F., Battezzati, P. M., Benedetti, A., Bragazzi, M., Brunetto, M., Bruno, S., Calvaruso, V., Cardinale, V., Casella, G., Cazzagon, N., Ciaccio, A., Coco, B., Colli, A., Colloredo, G., Colombo, M., Colombo, S., Cristoferi, L., Cursaro, C., Croce, L. S., Crosignani, A., D'Amato, D., Donato, F., Elia, G., Fabris, L., Fagiuoli, S., Ferrari, C., Floreani, A., Galli, A., Giannini, E., Grattagliano, I., Lampertico, P., Lleo, A., Malinverno, F., Mancuso, C., Marra, F., Marzioni, M., Massironi, S., Mattalia, A., Miele, L., Milani, C., Morini, L., Morisco, F., Muratori, L., Muratori, P., Niro, G. A., O'Donnell, S., Picciotto, A., Portincasa, P., Rigamonti, C., Ronca, V., Rosina, F., Spinzi, G., Strazzabosco, M., Tarocchi, M., Tiribelli, C., Toniutto, P., Valenti, L., Vinci, M., Zuin, M., Nakamura, H., Abiru, S., Nagaoka, S., Komori, A., Yatsuhashi, H., Ishibashi, H., Ito, M., Migita, K., Ohira, H., Katsushima, S., Naganuma, A., Sugi, K., Komatsu, T., Mannami, T., Matsushita, K., Yoshizawa, K., Makita, F., Nikami, T., Nishimura, H., Kouno, H., Ota, H., Komura, T., Nakamura, Y., Shimada, M., Hirashima, N., Komeda, T., Ario, K., Nakamuta, M., Yamashita, T., Furuta, K., Kikuchi, M., Naeshiro, N., Takahashi, H., Mano, Y., Tsunematsu, S., Yabuuchi, I., Shimada, Y., Yamauchi, K., Sugimoto, R., Sakai, H., Mita, E., Koda, M., Tsuruta, S., Kamitsukasa, H., Sato, T., Masaki, N., Kobata, T., Fukushima, N., Ohara, Y., Muro, T., Takesaki, E., Takaki, H., Yamamoto, T., Kato, M., Nagaoki, Y., Hayashi, S., Ishida, J., Watanabe, Y., Kobayashi, M., Koga, M., Saoshiro, T., Yagura, M., Hirata, K., Tanaka, A., Takikawa, H., Zeniya, M., Abe, M., Onji, M., Kaneko, S., Honda, M., Arai, K., Arinaga-Hino, T., Hashimoto, E., Taniai, M., Umemura, T., Joshita, S., Nakao, K., Ichikawa, T., Shibata, H., Yamagiwa, S., Seike, M., Honda, K., Sakisaka, S., Takeyama, Y., Harada, M., Senju, M., Yokosuka, O., Kanda, T., Ueno, Y., Kikuchi, K., Ebinuma, H., Himoto, T., Yasunami, M., Murata, K., Mizokami, M., Kawata, K., Shimoda, S., Miyake, Y., Takaki, A., Yamamoto, K., Hirano, K., Ichida, T., Ido, A., Tsubouchi, H., Chayama, K., Harada, K., Nakanuma, Y., Maehara, Y., Taketomi, A., Shirabe, K., Soejima, Y., Mori, A., Yagi, S., Uemoto, S., H, E., Tanaka, T., Yamashiki, N., Tamura, S., Sugawara, Y., Kokudo, N., Chalasani, N., Luketic, V., Odin, J., Chopra, K., Abecasis, G., Cantor, M., Coppola, G., Economides, A., Lotta, L. A., Overton, J. D., Reid, J. G., Shuldiner, A., Beechert, C., Forsythe, C., Fuller, E. D., Gu, Z., Lattari, M., Lopez, A., Schleicher, T. D., Padilla, M. S., Toledo, K., Widom, L., Wolf, S. E., Pradhan, M., Manoochehri, K., Ulloa, R. H., Bai, X., Balasubramanian, S., Barnard, L., Blumenfeld, A., Eom, G., Habegger, L., Hawes, A., Khalid, S., Maxwell, E. K., Salerno, W., Staples, J. C., Jones, M. B., Mitnaul, L. J., Sturgess, R., Healey, C., Yeoman, A., Gunasekera, A. V., Kooner, P., Kapur, K., Sathyanarayana, V., Kallis, Y., Subhani, J., Harvey, R., Mccorry, R., Rooney, P., Ramanaden, D., Evans, R., Mathialahan, T., Gasem, J., Shorrock, C., Bhalme, M., Southern, P., Tibble, J. A., Gorard, D. A., Jones, S., Mells, G., Mulcahy, V., Srivastava, B., Foxton, M. R., Collins, C. E., Elphick, D., Karmo, M., Porras-Perez, F., Mendall, M., Yapp, T., Patel, M., Ede, R., Sayer, J., Jupp, J., Fisher, N., Carter, M. J., Koss, K., Shah, J., Piotrowicz, A., Scott, G., Grimley, C., Gooding, I. R., Williams, S., Tidbury, J., Lim, G., Cheent, K., Levi, S., Mansour, D., Beckley, M., Hollywood, C., Wong, T., Marley, R., Ramage, J., Gordon, H. M., Ridpath, J., Ngatchu, T., Bob Grover, V. P., Shidrawi, R. G., Abouda, G., Corless, L., Narain, M., Rees, I., Brown, A., Taylor-Robinson, S., Wilkins, J., Grellier, L., Banim, P., Das, D., Heneghan, M. A., Curtis, H., Matthews, H. C., Mohammed, F., Aldersley, M., Srirajaskanthan, R., Walker, G., Mcnair, A., Sharif, A., Sen, S., Bird, G., Prince, M. I., Prasad, G., Kitchen, P., Barnardo, A., Oza, C., Sivaramakrishnan, N. N., Gupta, P., Shah, A., Evans, C. D., Saha, S., Pollock, K., Bramley, P., Mukhopadhya, A., Barclay, S. T., Mcdonald, N., Bathgate, A. J., Palmer, K., Dillon, J. F., Rushbrook, S. M., Przemioslo, R., Mcdonald, C., Millar, A., Tai, C., Mitchell, S., Metcalf, J., Shaukat, S., Ninkovic, M., Shmueli, U., Davis, A., Naqvi, A., Lee, T. J., Ryder, S., Collier, J., Klass, H., Cramp, M. E., Sharer, N., Aspinall, R., Ghosh, D., Douds, A. C., Booth, J., Williams, E., Hussaini, H., Christie, J., Mann, S., Thorburn, D., Marshall, A., Patanwala, I., Ala, A., Maltby, J., Matthew, R., Corbett, C., Vyas, S., Singhal, S., Gleeson, D., Misra, S., Butterworth, J., George, K., Harding, T., Douglass, A., Mitchison, H., Panter, S., Shearman, J., Bray, G., Roberts, M., Butcher, G., Forton, D., Mahmood, Z., Cowan, M., Ch'Ng, C. L., Rahman, M., Whatley, G. C. A., Wesley, E., Mandal, A., Jain, S., Pereira, S. P., Wright, M., Trivedi, P., Gordon, F. H., Unitt, E., Palejwala, A., Austin, A., Vemala, V., Grant, A., Higham, A. D., Brind, A., Mathew, R., Cox, M., Ramakrishnan, S., King, A., Whalley, S., Fraser, J., Thomson, S. J., Bell, A., Wong, V. S., Kia, R., Gee, I., Keld, R., Ransford, R., Gotto, J., Millson, C., Cordell H.J., Fryett J.J., Ueno K., Darlay R., Aiba Y., Hitomi Y., Kawashima M., Nishida N., Khor S.-S., Gervais O., Kawai Y., Nagasaki M., Tokunaga K., Tang R., Shi Y., Li Z., Juran B.D., Atkinson E.J., Gerussi A., Carbone M., Asselta R., Cheung A., de Andrade M., Baras A., Horowitz J., Ferreira M.A.R., Sun D., Jones D.E., Flack S., Spicer A., Mulcahy V.L., Byan J., Han Y., Sandford R.N., Lazaridis K.N., Amos C.I., Hirschfield G.M., Seldin M.F., Invernizzi P., Siminovitch K.A., Ma X., Nakamura M., Mells G.F., Mason A., Vincent C., Xie G., Zhang J., Affronti A., Almasio P.L., Alvaro D., Andreone P., Andriulli A., Azzaroli F., Battezzati P.M., Benedetti A., Bragazzi M., Brunetto M., Bruno S., Calvaruso V., Cardinale V., Casella G., Cazzagon N., Ciaccio A., Coco B., Colli A., Colloredo G., Colombo M., Colombo S., Cristoferi L., Cursaro C., Croce L.S., Crosignani A., D'Amato D., Donato F., Elia G., Fabris L., Fagiuoli S., Ferrari C., Floreani A., Galli A., Giannini E., Grattagliano I., Lampertico P., Lleo A., Malinverno F., Mancuso C., Marra F., Marzioni M., Massironi S., Mattalia A., Miele L., Milani C., Morini L., Morisco F., Muratori L., Muratori P., Niro G.A., O'Donnell S., Picciotto A., Portincasa P., Rigamonti C., Ronca V., Rosina F., Spinzi G., Strazzabosco M., Tarocchi M., Tiribelli C., Toniutto P., Valenti L., Vinci M., Zuin M., Nakamura H., Abiru S., Nagaoka S., Komori A., Yatsuhashi H., Ishibashi H., Ito M., Migita K., Ohira H., Katsushima S., Naganuma A., Sugi K., Komatsu T., Mannami T., Matsushita K., Yoshizawa K., Makita F., Nikami T., Nishimura H., Kouno H., Ota H., Komura T., Nakamura Y., Shimada M., Hirashima N., Komeda T., Ario K., Nakamuta M., Yamashita T., Furuta K., Kikuchi M., Naeshiro N., Takahashi H., Mano Y., Tsunematsu S., Yabuuchi I., Shimada Y., Yamauchi K., Sugimoto R., Sakai H., Mita E., Koda M., Tsuruta S., Kamitsukasa H., Sato T., Masaki N., Kobata T., Fukushima N., Ohara Y., Muro T., Takesaki E., Takaki H., Yamamoto T., Kato M., Nagaoki Y., Hayashi S., Ishida J., Watanabe Y., Kobayashi M., Koga M., Saoshiro T., Yagura M., Hirata K., Tanaka A., Takikawa H., Zeniya M., Abe M., Onji M., Kaneko S., Honda M., Arai K., Arinaga-Hino T., Hashimoto E., Taniai M., Umemura T., Joshita S., Nakao K., Ichikawa T., Shibata H., Yamagiwa S., Seike M., Honda K., Sakisaka S., Takeyama Y., Harada M., Senju M., Yokosuka O., Kanda T., Ueno Y., Kikuchi K., Ebinuma H., Himoto T., Yasunami M., Murata K., Mizokami M., Kawata K., Shimoda S., Miyake Y., Takaki A., Yamamoto K., Hirano K., Ichida T., Ido A., Tsubouchi H., Chayama K., Harada K., Nakanuma Y., Maehara Y., Taketomi A., Shirabe K., Soejima Y., Mori A., Yagi S., Uemoto S., H E., Tanaka T., Yamashiki N., Tamura S., Sugawara Y., Kokudo N., Chalasani N., Luketic V., Odin J., Chopra K., Abecasis G., Cantor M., Coppola G., Economides A., Lotta L.A., Overton J.D., Reid J.G., Shuldiner A., Beechert C., Forsythe C., Fuller E.D., Gu Z., Lattari M., Lopez A., Schleicher T.D., Padilla M.S., Toledo K., Widom L., Wolf S.E., Pradhan M., Manoochehri K., Ulloa R.H., Bai X., Balasubramanian S., Barnard L., Blumenfeld A., Eom G., Habegger L., Hawes A., Khalid S., Maxwell E.K., Salerno W., Staples J.C., Jones M.B., Mitnaul L.J., Sturgess R., Healey C., Yeoman A., Gunasekera A.V., Kooner P., Kapur K., Sathyanarayana V., Kallis Y., Subhani J., Harvey R., McCorry R., Rooney P., Ramanaden D., Evans R., Mathialahan T., Gasem J., Shorrock C., Bhalme M., Southern P., Tibble J.A., Gorard D.A., Jones S., Mells G., Mulcahy V., Srivastava B., Foxton M.R., Collins C.E., Elphick D., Karmo M., Porras-Perez F., Mendall M., Yapp T., Patel M., Ede R., Sayer J., Jupp J., Fisher N., Carter M.J., Koss K., Shah J., Piotrowicz A., Scott G., Grimley C., Gooding I.R., Williams S., Tidbury J., Lim G., Cheent K., Levi S., Mansour D., Beckley M., Hollywood C., Wong T., Marley R., Ramage J., Gordon H.M., Ridpath J., Ngatchu T., Bob Grover V.P., Shidrawi R.G., Abouda G., Corless L., Narain M., Rees I., Brown A., Taylor-Robinson S., Wilkins J., Grellier L., Banim P., Das D., Heneghan M.A., Curtis H., Matthews H.C., Mohammed F., Aldersley M., Srirajaskanthan R., Walker G., McNair A., Sharif A., Sen S., Bird G., Prince M.I., Prasad G., Kitchen P., Barnardo A., Oza C., Sivaramakrishnan N.N., Gupta P., Shah A., Evans C.D., Saha S., Pollock K., Bramley P., Mukhopadhya A., Barclay S.T., McDonald N., Bathgate A.J., Palmer K., Dillon J.F., Rushbrook S.M., Przemioslo R., McDonald C., Millar A., Tai C., Mitchell S., Metcalf J., Shaukat S., Ninkovic M., Shmueli U., Davis A., Naqvi A., Lee T.J., Ryder S., Collier J., Klass H., Cramp M.E., Sharer N., Aspinall R., Ghosh D., Douds A.C., Booth J., Williams E., Hussaini H., Christie J., Mann S., Thorburn D., Marshall A., Patanwala I., Ala A., Maltby J., Matthew R., Corbett C., Vyas S., Singhal S., Gleeson D., Misra S., Butterworth J., George K., Harding T., Douglass A., Mitchison H., Panter S., Shearman J., Bray G., Roberts M., Butcher G., Forton D., Mahmood Z., Cowan M., Ch'ng C.L., Rahman M., Whatley G.C.A., Wesley E., Mandal A., Jain S., Pereira S.P., Wright M., Trivedi P., Gordon F.H., Unitt E., Palejwala A., Austin A., Vemala V., Grant A., Higham A.D., Brind A., Mathew R., Cox M., Ramakrishnan S., King A., Whalley S., Fraser J., Thomson S.J., Bell A., Wong V.S., Kia R., Gee I., Keld R., Ransford R., Gotto J., Millson C., Medical Research Council (MRC), LiveR North, Cordell, H, Fryett, J, Ueno, K, Darlay, R, Aiba, Y, Hitomi, Y, Kawashima, M, Nishida, N, Khor, S, Gervais, O, Kawai, Y, Nagasaki, M, Tokunaga, K, Tang, R, Shi, Y, Li, Z, Juran, B, Atkinson, E, Gerussi, A, Carbone, M, Asselta, R, Cheung, A, de Andrade, M, Baras, A, Horowitz, J, Ferreira, M, Sun, D, Jones, D, Flack, S, Spicer, A, Mulcahy, V, Byan, J, Han, Y, Sandford, R, Lazaridis, K, Amos, C, Hirschfield, G, Seldin, M, Invernizzi, P, Siminovitch, K, Ma, X, Nakamura, M, Mells, G, Mason, A, Vincent, C, Xie, G, Zhang, J, Affronti, A, Almasio, P, Alvaro, D, Andreone, P, Andriulli, A, Azzaroli, F, Battezzati, P, Benedetti, A, Bragazzi, M, Brunetto, M, Bruno, S, Calvaruso, V, Cardinale, V, Casella, G, Cazzagon, N, Ciaccio, A, Coco, B, Colli, A, Colloredo, G, Colombo, M, Colombo, S, Cristoferi, L, Cursaro, C, Croce, L, Crosignani, A, D'Amato, D, Donato, F, Elia, G, Fabris, L, Fagiuoli, S, Ferrari, C, Floreani, A, Galli, A, Giannini, E, Grattagliano, I, Lampertico, P, Lleo, A, Malinverno, F, Mancuso, C, Marra, F, Marzioni, M, Massironi, S, Mattalia, A, Miele, L, Milani, C, Morini, L, Morisco, F, Muratori, L, Muratori, P, Niro, G, O'Donnell, S, Picciotto, A, Portincasa, P, Rigamonti, C, Ronca, V, Rosina, F, Spinzi, G, Strazzabosco, M, Tarocchi, M, Tiribelli, C, Toniutto, P, Valenti, L, Vinci, M, Zuin, M, Nakamura, H, Abiru, S, Nagaoka, S, Komori, A, Yatsuhashi, H, Ishibashi, H, Ito, M, Migita, K, Ohira, H, Katsushima, S, Naganuma, A, Sugi, K, Komatsu, T, Mannami, T, Matsushita, K, Yoshizawa, K, Makita, F, Nikami, T, Nishimura, H, Kouno, H, Ota, H, Komura, T, Nakamura, Y, Shimada, M, Hirashima, N, Komeda, T, Ario, K, Nakamuta, M, Yamashita, T, Furuta, K, Kikuchi, M, Naeshiro, N, Takahashi, H, Mano, Y, Tsunematsu, S, Yabuuchi, I, Shimada, Y, Yamauchi, K, Sugimoto, R, Sakai, H, Mita, E, Koda, M, Tsuruta, S, Kamitsukasa, H, Sato, T, Masaki, N, Kobata, T, Fukushima, N, Ohara, Y, Muro, T, Takesaki, E, Takaki, H, Yamamoto, T, Kato, M, Nagaoki, Y, Hayashi, S, Ishida, J, Watanabe, Y, Kobayashi, M, Koga, M, Saoshiro, T, Yagura, M, Hirata, K, Tanaka, A, Takikawa, H, Zeniya, M, Abe, M, Onji, M, Kaneko, S, Honda, M, Arai, K, Arinaga-Hino, T, Hashimoto, E, Taniai, M, Umemura, T, Joshita, S, Nakao, K, Ichikawa, T, Shibata, H, Yamagiwa, S, Seike, M, Honda, K, Sakisaka, S, Takeyama, Y, Harada, M, Senju, M, Yokosuka, O, Kanda, T, Ueno, Y, Kikuchi, K, Ebinuma, H, Himoto, T, Yasunami, M, Murata, K, Mizokami, M, Kawata, K, Shimoda, S, Miyake, Y, Takaki, A, Yamamoto, K, Hirano, K, Ichida, T, Ido, A, Tsubouchi, H, Chayama, K, Harada, K, Nakanuma, Y, Maehara, Y, Taketomi, A, Shirabe, K, Soejima, Y, Mori, A, Yagi, S, Uemoto, S, H, E, Tanaka, T, Yamashiki, N, Tamura, S, Sugawara, Y, Kokudo, N, Chalasani, N, Luketic, V, Odin, J, Chopra, K, Abecasis, G, Cantor, M, Coppola, G, Economides, A, Lotta, L, Overton, J, Reid, J, Shuldiner, A, Beechert, C, Forsythe, C, Fuller, E, Gu, Z, Lattari, M, Lopez, A, Schleicher, T, Padilla, M, Toledo, K, Widom, L, Wolf, S, Pradhan, M, Manoochehri, K, Ulloa, R, Bai, X, Balasubramanian, S, Barnard, L, Blumenfeld, A, Eom, G, Habegger, L, Hawes, A, Khalid, S, Maxwell, E, Salerno, W, Staples, J, Jones, M, Mitnaul, L, Sturgess, R, Healey, C, Yeoman, A, Gunasekera, A, Kooner, P, Kapur, K, Sathyanarayana, V, Kallis, Y, Subhani, J, Harvey, R, Mccorry, R, Rooney, P, Ramanaden, D, Evans, R, Mathialahan, T, Gasem, J, Shorrock, C, Bhalme, M, Southern, P, Tibble, J, Gorard, D, Jones, S, Srivastava, B, Foxton, M, Collins, C, Elphick, D, Karmo, M, Porras-Perez, F, Mendall, M, Yapp, T, Patel, M, Ede, R, Sayer, J, Jupp, J, Fisher, N, Carter, M, Koss, K, Shah, J, Piotrowicz, A, Scott, G, Grimley, C, Gooding, I, Williams, S, Tidbury, J, Lim, G, Cheent, K, Levi, S, Mansour, D, Beckley, M, Hollywood, C, Wong, T, Marley, R, Ramage, J, Gordon, H, Ridpath, J, Ngatchu, T, Bob Grover, V, Shidrawi, R, Abouda, G, Corless, L, Narain, M, Rees, I, Brown, A, Taylor-Robinson, S, Wilkins, J, Grellier, L, Banim, P, Das, D, Heneghan, M, Curtis, H, Matthews, H, Mohammed, F, Aldersley, M, Srirajaskanthan, R, Walker, G, Mcnair, A, Sharif, A, Sen, S, Bird, G, Prince, M, Prasad, G, Kitchen, P, Barnardo, A, Oza, C, Sivaramakrishnan, N, Gupta, P, Shah, A, Evans, C, Saha, S, Pollock, K, Bramley, P, Mukhopadhya, A, Barclay, S, Mcdonald, N, Bathgate, A, Palmer, K, Dillon, J, Rushbrook, S, Przemioslo, R, Mcdonald, C, Millar, A, Tai, C, Mitchell, S, Metcalf, J, Shaukat, S, Ninkovic, M, Shmueli, U, Davis, A, Naqvi, A, Lee, T, Ryder, S, Collier, J, Klass, H, Cramp, M, Sharer, N, Aspinall, R, Ghosh, D, Douds, A, Booth, J, Williams, E, Hussaini, H, Christie, J, Mann, S, Thorburn, D, Marshall, A, Patanwala, I, Ala, A, Maltby, J, Matthew, R, Corbett, C, Vyas, S, Singhal, S, Gleeson, D, Misra, S, Butterworth, J, George, K, Harding, T, Douglass, A, Mitchison, H, Panter, S, Shearman, J, Bray, G, Roberts, M, Butcher, G, Forton, D, Mahmood, Z, Cowan, M, Ch'Ng, C, Rahman, M, Whatley, G, Wesley, E, Mandal, A, Jain, S, Pereira, S, Wright, M, Trivedi, P, Gordon, F, Unitt, E, Palejwala, A, Austin, A, Vemala, V, Grant, A, Higham, A, Brind, A, Mathew, R, Cox, M, Ramakrishnan, S, King, A, Whalley, S, Fraser, J, Thomson, S, Bell, A, Wong, V, Kia, R, Gee, I, Keld, R, Ransford, R, Gotto, J, Millson, C, Cordell HJ, Fryett JJ, Ueno K, Darlay R, Aiba Y, Hitomi Y, Kawashima M, Nishida N, Khor SS, Gervais O, Kawai Y, Nagasaki M, Tokunaga K, Tang R, Shi Y, Li Z, Juran BD, Atkinson EJ, Gerussi A, Carbone M, Asselta R, Cheung A, de Andrade M, Baras A, Horowitz J, Ferreira MAR, Sun D, Jones DE, Flack S, Spicer A, Mulcahy VL, Byan J, Han Y, Sandford RN, Lazaridis KN, Amos CI, Hirschfield GM, Seldin MF, Invernizzi P, Siminovitch KA, Ma X, Nakamura M, Mells GF, PBC Consortia, Canadian PBC Consortium, Chinese PBC Consortium, Italian PBC Study Group, Japan-PBC-GWAS Consortium, US PBC Consortium, UK-PBC Consortium, and Calvaruso V. .
Subjects: Liver Cirrhosis, ALSPAC, ERN RARE-LIVER, Genomic co-localization, Network-based in silico drug efficacy screening, UK-PBC, 0301 basic medicine, Candidate gene, Genome-Wide Association Study, Humans, Liver Cirrhosis, Biliary, Italian PBC Study Group, LD SCORE REGRESSION, Japan-PBC-GWAS Consortium, Genome-wide association study, Locus (genetics), Disease, SUSCEPTIBILITY, PBC, Chronic liver disease, Bioinformatics, GENETIC ASSOCIATION, 1117 Public Health and Health Services, 03 medical and health sciences, 0302 clinical medicine, UK-PBC Consortium, Genotype, Medicine, Genetic association, Science & Technology, Gastroenterology & Hepatology, Hepatology, business.industry, Biliary, Chinese PBC Consortium, 1103 Clinical Sciences, medicine.disease, PBC Consortia, 030104 developmental biology, Meta-analysis, ERN RARE LIVER, 030211 gastroenterology & hepatology, US PBC Consortium, Canadian PBC Consortium, business, Life Sciences & Biomedicine, Human
Abstract: [BACKGROUND & AIMS] Primary biliary cholangitis (PBC) is a chronic liver disease in which autoimmune destruction of the small intra-hepatic bile ducts eventually leads to cirrhosis. Many patients have inadequate response to licensed medications, motivating the search for novel therapies. Previous genome-wide association studies (GWAS) and meta-analyses (GWMA) of PBC have identified numerous risk loci for this condition, providing insight into its aetiology. We undertook the largest GWMA of PBC to date, aiming to identify additional risk loci and prioritise candidate genes for in silico drug efficacy screening. [METHODS] We combined new and existing genotype data for 10, 516 cases and 20, 772 controls from five European and two East Asian cohorts. [RESULTS] We identified 56 genome-wide significant loci (20 novel) including 46 in European, 13 in Asian, and 41 in combined cohorts; and a 57th genome-wide significant locus (also novel) in conditional analysis of the European cohorts. Candidate genes at newly identified loci include FCRL3, INAVA, PRDM1, IRF7, CCR6, CD226, and IL12RB1, each having key roles in immunity. Pathway analysis reiterated the likely importance of pattern recognition receptor and TNF signalling, Jak-STAT signalling, and differentiation of TH1 and TH17 cells in the pathogenesis of this disease. Drug efficacy screening identified several medications predicted to be therapeutic in PBC, some well-established in the treatment of other autoimmune disorders. [CONCLUSIONS] This study has identified additional risk loci for PBC, provided a hierarchy of agents that could be trialled in this condition, and emphasised the value of genetic and genomic approaches to drug discovery in complex disorders. [Lay summary] Primary biliary cholangitis (PBC) is a chronic liver disease that eventually leads to cirrhosis. In this study, we analysed genetic information from 10, 516 people with PBC and 20, 772 healthy individuals recruited in Canada, China, Italy, Japan, UK, or USA. We identified several genetic regions associated with PBC. Each of these regions contains several genes. For each region, we used diverse sources of evidence to help us choose the gene most likely to be involved in causing PBC. We used these ‘candidate genes’ to help us identify medications that are currently used for treatment of other conditions, which might also be useful for treatment of PBC., 原発性胆汁性胆管炎のゲノムワイド関連解析 --国際メタ解析による新規疾患感受性遺伝子と治療薬候補の同定--. 京都大学プレスリリース. 2021-06-28.
Published: 2021

27. Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Author: Cindy G. Boer, Konstantinos Hatzikotoulas, Lorraine Southam, Lilja Stefánsdóttir, Yanfei Zhang, Rodrigo Coutinho de Almeida, Tian T. Wu, Jie Zheng, April Hartley, Maris Teder-Laving, Anne Heidi Skogholt, Chikashi Terao, Eleni Zengini, George Alexiadis, Andrei Barysenka, Gyda Bjornsdottir, Maiken E. Gabrielsen, Arthur Gilly, Thorvaldur Ingvarsson, Marianne B. Johnsen, Helgi Jonsson, Margreet Kloppenburg, Almut Luetge, Sigrun H. Lund, Reedik Mägi, Massimo Mangino, Rob R.G.H.H. Nelissen, Manu Shivakumar, Julia Steinberg, Hiroshi Takuwa, Laurent F. Thomas, Margo Tuerlings, George C. Babis, Jason Pui Yin Cheung, Jae Hee Kang, Peter Kraft, Steven A. Lietman, Dino Samartzis, P. Eline Slagboom, Kari Stefansson, Unnur Thorsteinsdottir, Jonathan H. Tobias, André G. Uitterlinden, Bendik Winsvold, John-Anker Zwart, George Davey Smith, Pak Chung Sham, Gudmar Thorleifsson, Tom R. Gaunt, Andrew P. Morris, Ana M. Valdes, Aspasia Tsezou, Kathryn S.E. Cheah, Shiro Ikegawa, Kristian Hveem, Tõnu Esko, J. Mark Wilkinson, Ingrid Meulenbelt, Ming Ta Michael Lee, Joyce B.J. van Meurs, Unnur Styrkársdóttir, Eleftheria Zeggini, John Loughlin, Nigel Arden, Fraser Birrell, Andrew Carr, Panos Deloukas, Michael Doherty, Andrew W. McCaskie, William E.R. Ollier, Ashok Rai, Stuart H. Ralston, Tim D. Spector, Gillian A. Wallis, Amy E. Martinsen, Cristen Willer, Egil Andreas Fors, Ingunn Mundal, Knut Hagen, Kristian Bernhard Nilsen, Marie Udnesseter Lie, Sigrid Børte, Ben Brumpton, Jonas Bille Nielsen, Lars G. Fritsche, Wei Zhou, Ingrid Heuch, Kjersti Storheim, Evangelos Tyrpenou, Athanasios Koukakis, Dimitrios Chytas, Dimitrios Stergios Evangelopoulos, Chronopoulos Efstathios, Spiros Pneumaticos, Vasileios S. Nikolaou, Konstantinos Malizos, Lydia Anastasopoulou, Goncalo Abecasis, Aris Baras, Michael Cantor, Giovanni Coppola, Andrew Deubler, Aris Economides, Luca A. Lotta, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Katia Karalis, Katherine Siminovitch, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Xiaodong Bai, Suganthi Balasubramanian, Boris Boutkov, Gisu Eom, Lukas Habegger, Alicia Hawes, Olga Krasheninina, Rouel Lanche, Adam J. Mansfield, Evan K. Maxwell, Mona Nafde, Sean O’Keeffe, Max Orelus, Razvan Panea, Tommy Polanco, Ayesha Rasool, William Salerno, Jeffrey C. Staples, Dadong Li, Deepika Sharma, Ilanjana Banerjee, Jonas Bovijn, Adam Locke, Niek Verweij, Mary Haas, George Hindy, Tanima De, Parsa Akbari, Olukayode Sosina, Manuel A.R. Ferreira, Marcus B. Jones, Jason Mighty, Michelle G. LeBlanc, Lyndon J. Mitnaul, and Internal Medicine
Subjects: Resource, genome-wide association meta-analysis, Disease, Osteoarthritis, effector genes, Biology, Bioinformatics, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Drug Targets, Effector Genes, Functional Genomics, Genetic Architecture, Genome-wide Association Meta-analysis, Spine osteoarthritis, Risk Factors, drug targets, medicine, Humans, Genetic Predisposition to Disease, Sex Characteristics, Cartilage, Correction, medicine.disease, Phenotype, genetic architecture, Genetic architecture, ddc, osteoarthritis, Genetics, Population, medicine.anatomical_structure, Subchondral bone, Female, Functional genomics, functional genomics, Genome-Wide Association Study, Signal Transduction
Abstract: Summary Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation., Graphical abstract, Highlights • A multicohort study identifies 52 previously unknown osteoarthritis genetic risk variants • Similarities and differences in osteoarthritis genetic risk depend on joint sites • Osteoarthritis genetic components are associated with pain-related phenotypes • High-confidence effector genes highlight potential targets for drug intervention, A multicohort genome-wide association meta-analysis of osteoarthritis highlights the impact of joint site types on the features of genetic risk variants and the link between osteoarthritis genetics and pain-related phenotypes, pointing toward potential targets for therapeutic intervention.
Published: 2021
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28. Genome-wide analysis in 756,646 individuals provides first genetic evidence that ACE2 expression influences COVID-19 risk and yields genetic risk scores predictive of severe disease

Author: Marie V. Coignet, Dylan Sun, Lukas Habegger, Evan Maxwell, Daniel J. Rader, David J. Carey, Katherine A. Siminovitch, Giorgio Sirugo, Anne E. Justice, Joelle Mbatchou, Eli A. Stahl, Gonçalo R. Abecasis, Alexander H. Li, David A. Turissini, Adam E. Locke, Kristin A. Rand, Aris Baras, Joseph B. Leader, Genevieve H.L. Roberts, Ahna R. Girshick, Deepika Sharma, Nilanjana Banerjee, Fabricio S. P. Kury, John D. Overton, Shane McCarthy, Jonathan Marchini, Xiaodong Bai, Eurie L. Hong, Rouel Lanche, Amy Damask, Ashish Yadav, Raghavendran Partha, Shannon R. McCurdy, Miao Zhang, Suganthi Balasubramanian, Hyun Min Kang, Anurag Verma, Marcus B. Jones, Marylyn D. Ritchie, Colm O'Dushlaine, Manuel A. R. Ferreira, Adam J. Mansfield, Anthony Marcketta, Joshua D. Backman, Alan R. Shuldiner, Michael N. Cantor, Tooraj Mirshahi, Lee Dobbyn, Spencer C. Knight, William J Salerno, Harenda Guturu, Jeffrey G. Reid, Julie E. Horowitz, Lauren Gurski, Danny S. Park, Kyoko Watanabe, Catherine A. Ball, Asher K. Haug Baltzell, and Jack A. Kosmicki
Subjects: 2019-20 coronavirus outbreak, Increased risk, Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Genetic variants, MEDLINE, Severe disease, Medicine, Bioinformatics, business
Abstract: SARS-CoV-2 enters host cells by binding angiotensin-converting enzyme 2 (ACE2). Through a genome-wide association study, we show that a rare variant (MAF = 0.3%, odds ratio 0.60, P=4.5x10-13) that down-regulates ACE2 expression reduces risk of COVID-19 disease, providing human genetics support for the hypothesis that ACE2 levels influence COVID-19 risk. Further, we show that common genetic variants define a risk score that predicts severe disease among COVID-19 cases.
Published: 2020
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29. Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank

Author: Joseph D, Szustakowski, Suganthi, Balasubramanian, Erika, Kvikstad, Shareef, Khalid, Paola G, Bronson, Ariella, Sasson, Emily, Wong, Daren, Liu, J, Wade Davis, Carolina, Haefliger, A, Katrina Loomis, Rajesh, Mikkilineni, Hyun Ji, Noh, Samir, Wadhawan, Xiaodong, Bai, Alicia, Hawes, Olga, Krasheninina, Ricardo, Ulloa, Alex E, Lopez, Erin N, Smith, Jeffrey F, Waring, Christopher D, Whelan, Ellen A, Tsai, John D, Overton, William J, Salerno, Howard, Jacob, Sandor, Szalma, Heiko, Runz, Gregory, Hinkle, Paul, Nioi, Slavé, Petrovski, Melissa R, Miller, Aris, Baras, Lyndon J, Mitnaul, Jeffrey G, Reid, and Zhan, Ye
Subjects: Research, Drug Discovery, Exome Sequencing, Humans, Human Genetics, Genomics, United Kingdom, Biological Specimen Banks
Abstract: The UK Biobank Exome Sequencing Consortium (UKB-ESC) is a private-public partnership between the UK Biobank (UKB) and eight biopharmaceutical companies that will complete the sequencing of exomes for all ~500,000 UKB participants. Here, we describe the early results from ~200,000 UKB participants and the features of this project that enabled its success. The biopharmaceutical industry has increasingly used human genetics to improve success in drug discovery. Recognizing the need for large-scale human genetics data, as well as the unique value of the data access and contribution terms of the UKB, the UKB-ESC was formed. As a result, exome data from 200,643 UKB enrollees are now available. These data include ~10 million exonic variants-a rich resource of rare coding variation that is particularly valuable for drug discovery. The UKB-ESC precompetitive collaboration has further strengthened academic and industry ties and has provided teams with an opportunity to interact with and learn from the wider research community.
Published: 2020

30. Advancing Human Genetics Research and Drug Discovery through Exome Sequencing of the UK Biobank

Author: Xiaodong Bai, Samir Wadhawan, Howard J. Jacob, Carolina Haefliger, Ariella Sasson, Rajesh Mikkilineni, Daren Liu, William J. Salerno, Jeffrey F. Waring, Joseph D. Szustakowski, Emily Wong, Paola G. Bronson, Ellen A. Tsai, Gregory Hinkle, Suganthi Balasubramanian, Alex Lopez, Olga Krasheninina, A. Katrina Loomis, E. N. Smith, Melissa R. Miller, Sándor Szalma, Hyun Ji Noh, Heiko Runz, Paul Nioi, Shareef Khalid, Christopher D. Whelan, Jeffrey G. Reid, Slavé Petrovski, Alicia Hawes, Lyndon J. Mitnaul, Ricardo Ulloa, John D. Overton, J. Wade Davis, Aris Baras, and Erika Kvikstad
Subjects: 0303 health sciences, business.industry, Drug discovery, Genomics, Computational biology, Biology, Data science, Biobank, Human genetics, 03 medical and health sciences, Open data, 0302 clinical medicine, Drug development, General partnership, Genetics, business, Indel, Exome, 030217 neurology & neurosurgery, Biomedicine, Exome sequencing, 030304 developmental biology
Abstract: The UK Biobank Exome Sequencing Consortium (UKB-ESC) is a unique private/public partnership between the UK Biobank and eight biopharma companies that will sequence the exomes of all ∼500,000 UK Biobank participants. Here we describe early results from the exome sequence data generated by this consortium for the first ∼200,000 UKB subjects and the key features of this project that enabled the UKB-ESC to come together and generate this data.Exome sequencing data from the first 200,643 UKB enrollees are now accessible to the research community. Approximately 10M variants were observed within the targeted regions, including: 8,086,176 SNPs, 370,958 indels and 1,596,984 multi-allelic variants. Of the ∼8M variants observed, 84.5% are coding variants and include 2,139,318 (25.3%) synonymous, 4,549,694 (53.8%) missense, 453,733 (5.4%) predicted loss-of-function (LOF) variants (initiation codon loss, premature stop codons, stop codon loss, splicing and frameshift variants) affecting at least one coding transcript. This open access data provides a rich resource of coding variants for rare variant genetic studies, and is particularly valuable for drug discovery efforts that utilize rare, functionally consequential variants.Over the past decade, the biopharma industry has increasingly leveraged human genetics as part of their drug discovery and development strategies. This shift was motivated by technical advances that enabled cost-effective human genetics research at scale, the emergence of electronic health records and biobanks, and a maturing understanding of how human genetics can increase the probability of successful drug development. Recognizing the need for large-scale human genetics data to drive drug discovery, and the unique value of the open data access policies and contribution terms of the UK Biobank, the UKB-ESC was formed. This precompetitive collaboration has further strengthened the ties between academia and industry and provided teams an unprecedented opportunity to interact with and learn from the wider research community.
Published: 2020
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31. A catalog of associations between rare coding variants and COVID-19 outcomes

Author: Anurag Verma, Anne E. Justice, Guillaume Butler-Laporte, E. N. Smith, Lukas Habegger, Joelle Mbatchou, Susan P. Walker, Albert Tenesa, Joseph D. Szustakowski, Konrad Rawlik, Dylan Sun, Loukas Moutsianas, Shane McCarthy, Richard H Scott, Aris Baras, Evan Maxwell, Aldo Cordova-Palomera, Tooraj Mirshahi, Dorota Pasko, David J. Carey, Sahar Esmaeli, Adam J. Mansfield, Quanli Wang, Jeffrey S. Reid, Nilanjana Banerjee, Joshua D. Backman, Athanasios Kousathanas, Ashish Yadav, Mark J. Caulfield, Alison M. Meynert, Rouel Lanche, Jack A. Kosmicki, James F. Wilson, J. Brent Richards, Heiko Runz, Gonçalo R. Abecasis, Adam E. Locke, Justin W. Davis, Mark Lathrop, Alan R. Shuldiner, Lauren Gurski, J Kenneth Baillie, Michael N. Cantor, David Goldstein, John D. Overton, Kyoko Watanabe, Amanda O'Neill, Yunfeng Huang, Jonathan Marchini, Xiaodong Bai, Krzysztof Kiryluk, Slavé Petrovski, Sean O'Keeffe, Erika Kvikstad, Anthony Marcketta, Margaret M. Parker, Giorgio Sirugo, Julie E. Horowitz, Emily Wong, Olympe Chazara, Paul Nioi, Manuel A. R. Ferreira, Sándor Szalma, Joseph B. Leader, Shareef Khalid, William J Salerno, Deepika Sharma, Tomoko Nakanishi, Marcus B. Jones, Gundula Povysil, Marylyn D. Ritchie, Colm O'Dushlaine, Xiuwen Zheng, Daniel J. Rader, Suganthi Balasubramanian, Hyun Min Kang, Yi-Pin Lai, Alexander H. Li, Xing Chen, and Erola Pairo-Castineira
Subjects: Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Genome-wide association study, medicine.disease_cause, Biobank, Article, Genetic association analysis, Immunology, Multiple comparisons problem, Medicine, business, Gene, Coronavirus
Abstract: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable athttps://rgc-covid19.regeneron.com.
Published: 2020
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32. Validating gene-phenotype associations using relationships in the UMLS

Author: Lukas Habegger, Suganthi Balasubramanian, Michael N. Cantor, Deepika Sharma, Jeffrey Staples, Ashish Yadav, Claudia Gonzaga-Jauregui, Jeffrey G. Reid, Shareef Khalid, and Andrew Blumenfeld
Subjects: Set (abstract data type), education.field_of_study, Computer science, Unified Medical Language System, Population, Cohort, Computational biology, Disease, Health records, education, Gene, Phenotype, Exome sequencing
Abstract: ObjectiveLarge scale next-generation sequencing of population cohorts paired with patients’ electronic health records (EHR) provides an excellent resource for the study of gene-disease associations. To validate those associations, researchers often consult databases that identify relationships between genes of interest and relevant disease phenotypes, which we refer to as simply “phenotypes”. However, most of these databases contain phenotypes that are not suited for automated analysis of EHR data, which often captured these phenotypes in the form of International Classification of Diseases (ICD) codes. There is a need for a resource that comprehensively provides gene-phenotype mappings in a format that can be used to evaluate phenotypes from EHR.MethodsWe built a directed graph database of genes, medical concepts and ICD codes based on a subset of the National Library of Medicine’s Unified Medical Language System (UMLS) and other resources. To obtain associations between genes and ICD codes, we traversed the defined relationships from gene, variant and disease concepts to ICD codes, resulting in a set of mappings that link specific genes and variants to these ICD codes.ResultsOur method created 249,764 mappings between genes and ICD codes, including 27,226 “disease” phenotypes and 222,538 “symptom” phenotypes, and provided mappings for 4,456 unique genes. Paths were validated by manual review of a diverse sample of paths. In a cohort of 92,455 samples, we used these mappings to validate gene-phenotype associations in 32,786 samples where a person had a potentially disease-causing genetic mutation and at least one corresponding diagnosis in their EHR.ConclusionThe concepts and relationships in the UMLS can be used to generate gene-ICD phenotype mappings that are not explicit in the source vocabularies. We were able use these mappings to validate gene-disease associations in a large cohort of sequenced exomes paired with EHR.
Published: 2020
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33. Profiling and Leveraging Relatedness in a Precision Medicine Cohort of 92,455 Exomes

Author: Shane McCarthy, David H. Ledbetter, Frederick E. Dewey, Lukas Habegger, John Penn, David J. Carey, George D. Yancoupolos, Cristopher V. Van Hout, H. Lester Kirchner, Suganthi Balasubramanian, Joseph B. Leader, Tanya M. Teslovich, Xiaodong Bai, Colm O'Dushlaine, Aris Baras, John D. Overton, Michael F. Murray, Nehal Gosalia, Jeffrey G. Reid, Evan Maxwell, Alan R. Shuldiner, Alexander Lopez, Claudia Gonzaga-Jauregui, Christopher Snyder, Jeffrey Staples, Ricardo Ulloa, and Alicia Hawes
Subjects: Male, 0301 basic medicine, Heterozygote, Population, Genomics, Pedigree chart, Biology, Compound heterozygosity, Article, Cohort Studies, 03 medical and health sciences, Genetics, Electronic Health Records, Humans, Computer Simulation, Exome, Family, Precision Medicine, education, Nuclear family, Genetics (clinical), Exome sequencing, education.field_of_study, Geography, Reproducibility of Results, Exons, Human genetics, Pedigree, Genetics, Population, Phenotype, 030104 developmental biology, Evolutionary biology, Mutation, Cohort, Female, Tandem exon duplication
Abstract: Large-scale human genetics studies are ascertaining increasing proportions of populations as they continue growing in both number and scale. As a result, the amount of cryptic relatedness within these study cohorts is growing rapidly and has significant implications on downstream analyses. We demonstrate this growth empirically among the first 92,455 exomes from the DiscovEHR cohort and, via a custom simulation framework we developed called SimProgeny, show that these measures are in-line with expectations given the underlying population and ascertainment approach. For example, we identified ∼66,000 close (first- and second-degree) relationships within DiscovEHR involving 55.6% of study participants. Our simulation results project that >70% of the cohort will be involved in these close relationships as DiscovEHR scales to 250,000 recruited individuals. We reconstructed 12,574 pedigrees using these relationships (including 2,192 nuclear families) and leveraged them for multiple applications. The pedigrees substantially improved the phasing accuracy of 20,947 rare, deleterious compound heterozygous mutations. Reconstructed nuclear families were critical for identifying 3,415 de novo mutations in ∼1,783 genes. Finally, we demonstrate the segregation of known and suspected disease-causing mutations through reconstructed pedigrees, including a tandem duplication in LDLR causing familial hypercholesterolemia. In summary, this work highlights the prevalence of cryptic relatedness expected among large healthcare population genomic studies and demonstrates several analyses that are uniquely enabled by large amounts of cryptic relatedness.
Published: 2018
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34. A comprehensive catalog of predicted functional upstream open reading frames in humans

Author: Robert R. Kitchen, Mark Gerstein, Patrick McGillivray, Russell Ault, Suganthi Balasubramanian, and Mayur Pawashe
Subjects: 0301 basic medicine, Computational Biology, Bayes Theorem, Translation (biology), Computational biology, Biology, Genome, 3. Good health, Open Reading Frames, 03 medical and health sciences, Open reading frame, 030104 developmental biology, 0302 clinical medicine, Protein Biosynthesis, Mutation, Genetics, Humans, Upstream (networking), RNA, Messenger, Ribosome profiling, Gene sequence, Ribosomes, Gene, 030217 neurology & neurosurgery
Abstract: Upstream open reading frames (uORFs) latent in mRNA transcripts are thought to modify translation of coding sequences by altering ribosome activity. Not all uORFs are thought to be active in such a process. To estimate the impact of uORFs on the regulation of translation in humans, we first circumscribed the universe of all possible uORFs based on coding gene sequence motifs and identified 1.3 million unique uORFs. To determine which of these are likely to be biologically relevant, we built a simple Bayesian classifier using 89 attributes of uORFs labeled as active in ribosome profiling experiments. This allowed us to extrapolate to a comprehensive catalog of likely functional uORFs. We validated our predictions using in vivo protein levels and ribosome occupancy from 46 individuals. This is a substantially larger catalog of functional uORFs than has previously been reported. Our ranked list of likely active uORFs allows researchers to test their hypotheses regarding the role of uORFs in health and disease. We demonstrate several examples of biological interest through the application of our catalog to somatic mutations in cancer and disease-associated germline variants in humans.
Published: 2018
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35. Polygenic Risk of Psychiatric Disorders Exhibits Cross-trait Associations in Electronic Health Record Data From European Ancestry Individuals

Author: Rachel L. Kember, Alison K. Merikangas, Shefali S. Verma, Anurag Verma, Renae Judy, Scott M. Damrauer, Marylyn D. Ritchie, Daniel J. Rader, Maja Bućan, Goncalo Abecasis, Aris Baras, Michael Cantor, Giovanni Coppola, Aris Economides, Luca Lotta, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Karina Toledo, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H. Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Leland Barnard, Andrew Blumenfeld, Gisu Eom, Lukas Habegger, Young Hahn, Alicia Hawes, Shareef Khalid, Evan K. Maxwell, William Salerno, Jeffrey C. Staples, Ashish Yadav, Marcus B. Jones, and Lyndon J. Mitnaul
Subjects: 0301 basic medicine, medicine.medical_specialty, Multifactorial Inheritance, Bipolar Disorder, Disease, Article, 03 medical and health sciences, 0302 clinical medicine, medicine, Electronic Health Records, Humans, Genetic Predisposition to Disease, Bipolar disorder, Psychiatry, Biological Psychiatry, Depressive Disorder, Major, business.industry, Odds ratio, medicine.disease, Biobank, Genetic architecture, 030104 developmental biology, Phenotype, Schizophrenia, Anorexia nervosa (differential diagnoses), Major depressive disorder, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Background Prediction of disease risk is a key component of precision medicine. Common traits such as psychiatric disorders have a complex polygenic architecture, making the identification of a single risk predictor difficult. Polygenic risk scores (PRSs) denoting the sum of an individual’s genetic liability for a disorder are a promising biomarker for psychiatric disorders, but they require evaluation in a clinical setting. Methods We developed PRSs for 6 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, and anorexia nervosa) and 17 nonpsychiatric traits in more than 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We performed phenome-wide association analyses to test their association across disease categories. Results Four of the 6 psychiatric PRSs were associated with their primary phenotypes (odds ratios from 1.2 to 1.6). Cross-trait associations were identified both within the psychiatric domain and across trait domains. PRSs for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder. Conclusions We demonstrated that the genetic architecture of electronic health record–derived psychiatric diagnoses is similar to ascertained research cohorts from large consortia. Psychiatric PRSs are moderately associated with psychiatric diagnoses but are not yet clinically predictive in naive patients. Cross-trait associations for these PRSs suggest a broader effect of genetic liability beyond traditional diagnostic boundaries. As identification of genetic markers increases, including PRSs alongside other clinical risk factors may enhance prediction of psychiatric disorders and associated conditions in clinical registries.
Published: 2020

36. Whole exome sequencing and characterization of coding variation in 49,960 individuals in the UK Biobank

Author: Ida Surakka, Alexander Lopez, Lukas Habegger, Shareef Khalid, William J Salerno, Andrew Blumenfeld, Bin Ye, Jeffrey G. Reid, Ashutosh K. Pandey, Alicia Hawes, John D. Overton, Giovanni Coppola, Jonathan Marchini, Wendy K. Chung, David J. Carey, David H. Ledbetter, Kristian Hveem, Aris N. Economides, Cristopher V. Van Hout, Kavita Praveen, Cristen J. Willer, Joshua D. Backman, Anthony Marcketta, Ioanna Tachmazidou, Marcus B. Jones, O’Dushlaine Colm, John Penn, Joseph B. Leader, Leland Barnard, Daren Liu, George D. Yancopoulos, Michael N. Cantor, Suganthi Balasubramanian, Laura M. Yerges-Armstrong, Alan R. Shuldiner, Claudia Gonzaga-Jauregui, John C. Whittaker, Nilanjana Banerjee, Aris Baras, Gonçalo R. Abecasis, Claudia Schurmann, Robert A. Scott, Evan Maxwell, Matthew R. Nelson, Jeffrey Staples, Ashish Yadav, Joshua D. Hoffman, Lon R. Cardon, and Alexander H. Li
Subjects: education.field_of_study, Genotype, Population, Disease, Computational biology, Biology, education, Exome, Gene, Biobank, Exome sequencing, Loss function
Abstract: SUMMARYThe UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world. Here we describe the first tranche of large-scale exome sequence data for 49,960 study participants, revealing approximately 4 million coding variants (of which ~98.4% have frequency < 1%). The data includes 231,631 predicted loss of function variants, a >10-fold increase compared to imputed sequence for the same participants. Nearly all genes (>97%) had ≥1 predicted loss of function carrier, and most genes (>69%) had ≥10 loss of function carriers. We illustrate the power of characterizing loss of function variation in this large population through association analyses across 1,741 phenotypes. In addition to replicating a range of established associations, we discover novel loss of function variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical significance in this population, finding that 2% of the population has a medically actionable variant. Additionally, we leverage the phenotypic data to characterize the relationship between rare BRCA1 and BRCA2 pathogenic variants and cancer risk. Exomes from the first 49,960 participants are now made accessible to the scientific community and highlight the promise offered by genomic sequencing in large-scale population-based studies.
Published: 2019
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37. A Protein-Truncating HSD17B13 Variant and Protection from Chronic Liver Disease

Author: Shane McCarthy, Jonathan C. Cohen, Frederick E. Dewey, Claudia Schurmann, Matthew D. Still, Panayiotis Stevis, Xin Chu, Daniel J. Rader, David J. Carey, Alan R. Shuldiner, Noura S. Abul-Husn, Semanti Mukherjee, Jonathan S. Packer, Xiping Cheng, Ann Stepanchick, Brian Zambrowicz, Helen H. Hobbs, John Penn, Uyenlinh L. Mirshahi, Scott M. Damrauer, Ingrid B. Borecki, Yurong Xin, G. Craig Wood, Jesper Gromada, Suganthi Balasubramanian, Tanya M. Teslovich, Andrew J. Murphy, Erin D. Fuller, Christopher D. Still, Tooraj Mirshahi, Jonathan Z. Luo, John D. Overton, George D. Yancopoulos, Yashu Liu, Alexander H. Li, Aeron Small, Omri Gottesman, Julia Kozlitina, Jeffrey G. Reid, Stefan Stender, David Esopi, William C. Olson, Michael Feldman, Colm O'Dushlaine, Alexander E. Lopez, Nehal Gosalia, Sun Y. Kim, and Aris Baras
Subjects: 0301 basic medicine, Male, medicine.medical_specialty, 17-Hydroxysteroid Dehydrogenases, Genotype, Chronic liver disease, Gastroenterology, Article, 03 medical and health sciences, Liver disease, 0302 clinical medicine, Non-alcoholic Fatty Liver Disease, Loss of Function Mutation, Internal medicine, Exome Sequencing, Medicine, Humans, Exome, Genetic Predisposition to Disease, Aspartate Aminotransferases, Exome sequencing, biology, business.industry, Sequence Analysis, RNA, Liver Diseases, Fatty liver, Genetic Variation, Alanine Transaminase, General Medicine, medicine.disease, Human genetics, Fatty Liver, 030104 developmental biology, Alanine transaminase, Liver, Chronic Disease, biology.protein, Disease Progression, Linear Models, 030211 gastroenterology & hepatology, Female, business, Biomarkers, TM6SF2
Abstract: BACKGROUND: Elucidation of the genetic factors underlying chronic liver disease may reveal new therapeutic targets. METHODS: We used exome sequence data and electronic health records from 46,544 participants in the DiscovEHR human genetics study to identify genetic variants associated with serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Variants that were replicated in three additional cohorts (12,527 persons) were evaluated for association with clinical diagnoses of chronic liver disease in DiscovEHR study participants and two independent cohorts (total of 37,173 persons) and with histopathological severity of liver disease in 2391 human liver samples. RESULTS: A splice variant (rs72613567:TA) in HSD17B13, encoding the hepatic lipid droplet protein hydroxysteroid 17-beta dehydrogenase 13, was found to be associated with reduced levels of ALT (P=4.20×10(−12)) and AST (P=6.2×10(−10)). Among DiscovEHR study participants, this variant was found to be associated with a reduced risk of alcoholic liver disease (by 42% [95% confidence interval {CI}, 20 to 58] among heterozygotes and by 53% [95% CI, 3 to 77] among homozygotes), nonalcoholic liver disease (by 17% [95% CI, 8 to 25] among heterozygotes and by 30% [95% CI, 13 to 43] among homozygotes), alcoholic cirrhosis (by 42% [95% CI, 14 to 61] among heterozygotes and by 73% [95% CI, 15 to 91] among homozygotes), and nonalcoholic cirrhosis (by 26% [95% CI, 7 to 40] among heterozygotes and by 49% [95% CI, 15 to 69] among homozygotes). Associations were confirmed in two independent cohorts. The rs72613567:TA variant was associated with a reduced risk of nonalcoholic steatohepatitis, but not steatosis, in human liver samples. The rs72613567:TA variant mitigated liver injury associated with the risk-increasing PNPLA3 p.I148M allele and resulted in an unstable and truncated protein with reduced enzymatic activity. CONCLUSIONS: A loss-of-function variant in HSD17B13 is associated with a reduced risk of chronic liver disease and of progression from steatosis to steatohepatitis. (Funded by Regeneron Pharmaceuticals and others.)
Published: 2018

38. MAPPIN: a method for annotating, predicting pathogenicity and mode of inheritance for nonsynonymous variants

Author: Frederick E. Dewey, Aris N. Economides, Suganthi Balasubramanian, and Nehal Gosalia
Subjects: 0301 basic medicine, Nonsynonymous substitution, Inheritance Patterns, Biology, Gene mutation, Bioinformatics, Polymorphism, Single Nucleotide, 03 medical and health sciences, symbols.namesake, Mice, Genetic variation, Databases, Genetic, Genetics, Animals, Humans, Disease, Genetic Predisposition to Disease, Gene, Inheritance (genetic algorithm), Chromosome Mapping, Computational Biology, Genetic Variation, Molecular Sequence Annotation, 030104 developmental biology, Mutation (genetic algorithm), Mutation, Mendelian inheritance, symbols, Algorithms, Forecasting
Abstract: Nonsynonymous single nucleotide variants (nsSNVs) constitute about 50% of known disease-causing mutations and understanding their functional impact is an area of active research. Existing algorithms predict pathogenicity of nsSNVs; however, they are unable to differentiate heterozygous, dominant disease-causing variants from heterozygous carrier variants that lead to disease only in the homozygous state. Here, we present MAPPIN (Method for Annotating, Predicting Pathogenicity, and mode of Inheritance for Nonsynonymous variants), a prediction method which utilizes a random forest algorithm to distinguish between nsSNVs with dominant, recessive, and benign effects. We apply MAPPIN to a set of Mendelian disease-causing mutations and accurately predict pathogenicity for all mutations. Furthermore, MAPPIN predicts mode of inheritance correctly for 70.3% of nsSNVs. MAPPIN also correctly predicts pathogenicity for 87.3% of mutations from the Deciphering Developmental Disorders Study with a 78.5% accuracy for mode of inheritance. When tested on a larger collection of mutations from the Human Gene Mutation Database, MAPPIN is able to significantly discriminate between mutations in known dominant and recessive genes. Finally, we demonstrate that MAPPIN outperforms CADD and Eigen in predicting disease inheritance modes for all validation datasets. To our knowledge, MAPPIN is the first nsSNV pathogenicity prediction algorithm that provides mode of inheritance predictions, adding another layer of information for variant prioritization.
Published: 2017

39. Determining the impact of putative loss-of-function variants in protein-coding genes

Author: Mike Jin, Suganthi Balasubramanian, Mark Gerstein, Konrad J. Karczewski, Yao Fu, Jeremy Liu, Daniel G. MacArthur, Patrick McGillivray, and Mayur Pawashe
Subjects: Genetics, 0303 health sciences, Genomics, Heterozygote advantage, Biology, 03 medical and health sciences, symbols.namesake, 0302 clinical medicine, Mendelian inheritance, symbols, Human genome, Allele, Gene, 030217 neurology & neurosurgery, Exome sequencing, Loss function, 030304 developmental biology
Abstract: Variants predicted to result in the loss of function (LoF) of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (Annotation of Loss-of-Function Transcripts), a method to annotate and predict the disease-causing potential of LoF variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between LoF variants deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo pLoF variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in > 6,500 cancer exomes shows that pLoF variants predicted to be deleterious by ALoFT are enriched in known driver genes.
Published: 2017
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40. Analysis of variable retroduplications in human populations suggests coupling of retrotransposition to cell division

Author: David W. Radke, Suganthi Balasubramanian, Charles Lee, Omer Gokcumen, Rebecca C. Iskow, Baikang Pei, Mark Gerstein, Alexej Abyzov, and Lukas Habegger
Subjects: Genotype, Retroelements, Pseudogene, Population, Biology, Genome, Evolution, Molecular, Gene Duplication, Genetics, Humans, 1000 Genomes Project, education, Gene, Phylogeny, Genetics (clinical), education.field_of_study, Phylogenetic tree, Genome, Human, Research, Computational Biology, Reproducibility of Results, Sequence Analysis, DNA, Evolutionary biology, Human genome, Cell Division, Pseudogenes, Reference genome
Abstract: In primates and other animals, reverse transcription of mRNA followed by genomic integration creates retroduplications. Expressed retroduplications are either “retrogenes” coding for functioning proteins, or expressed “processed pseudogenes,” which can function as noncoding RNAs. To date, little is known about the variation in retroduplications in terms of their presence or absence across individuals in the human population. We have developed new methodologies that allow us to identify “novel” retroduplications (i.e., those not present in the reference genome), to find their insertion points, and to genotype them. Using these methods, we catalogued and analyzed 174 retroduplication variants in almost one thousand humans, which were sequenced as part of Phase 1 of The 1000 Genomes Project Consortium. The accuracy of our data set was corroborated by (1) multiple lines of sequencing evidence for retroduplication (e.g., depth of coverage in exons vs. introns), (2) experimental validation, and (3) the fact that we can reconstruct a correct phylogenetic tree of human subpopulations based solely on retroduplications. We also show that parent genes of retroduplication variants tend to be expressed at the M-to-G1 transition in the cell cycle and that M-to-G1 expressed genes have more copies of fixed retroduplications than genes expressed at other times. These findings suggest that cell division is coupled to retrotransposition and, perhaps, is even a requirement for it.
Published: 2013
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41. Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study

Author: Christina Austin-Tse, Alan R. Shuldiner, Claudia Gonzaga-Jauregui, Noura S. Abul-Husn, Semanti Mukherjee, Samantha N. Fetterolf, Cristopher V. Van Hout, Monica A. Giovanni, Matthew S. Lebo, Omri Gottesman, Frederick E. Dewey, Thomas N. Person, Lukas Habegger, Korey A. Kost, Lance J. Adams, H. Lester Kirchner, James R. Elmore, Aris N. Economides, Christopher D. Still, Alexander H. Li, David J. Carey, Sarah A. Pendergrass, Anthony Marcketta, Jeffrey Staples, Marylyn D. Ritchie, Colm O'Dushlaine, Nehal Gosalia, Manoj Kanagaraj, William A. Faucett, John Penn, Raghu Metpally, Ingrid B. Borecki, Kavita Praveen, Jonathan S. Packer, Shannon Bruse, Andrew J. Murphy, Joseph B. Leader, Michael F. Murray, Suganthi Balasubramanian, Neil Stahl, Jeffrey G. Reid, David H. Ledbetter, Dustin N. Hartzel, Kimberly A. Skelding, F. Daniel Davis, Alexander Lopez, Aris Baras, George D. Yancopoulos, Scott Mellis, Robert H. Phillips, John D. Overton, Heather Mason-Suares, Lyndon J. Mitnaul, and Daniel R. Lavage
Subjects: Adult, 0301 basic medicine, Disease, Familial hypercholesterolemia, Bioinformatics, Polymorphism, Single Nucleotide, 03 medical and health sciences, 0302 clinical medicine, Gene Frequency, INDEL Mutation, Genetic variation, Electronic Health Records, Humans, Medicine, Exome, Molecular Targeted Therapy, Risk factor, Allele frequency, Exome sequencing, Hypolipidemic Agents, Multidisciplinary, Delivery of Health Care, Integrated, business.industry, High-Throughput Nucleotide Sequencing, Genomics, Sequence Analysis, DNA, Precision medicine, medicine.disease, Lipids, 030104 developmental biology, Drug Design, business, 030217 neurology & neurosurgery
Abstract: Unleashing the power of precision medicine Precision medicine promises the ability to identify risks and treat patients on the basis of pathogenic genetic variation. Two studies combined exome sequencing results for over 50,000 people with their electronic health records. Dewey et al. found that ∼3.5% of individuals in their cohort had clinically actionable genetic variants. Many of these variants affected blood lipid levels that could influence cardiovascular health. Abul-Husn et al. extended these findings to investigate the genetics and treatment of familial hypercholesterolemia, a risk factor for cardiovascular disease, within their patient pool. Genetic screening helped identify at-risk patients who could benefit from increased treatment. Science , this issue p. 10.1126/science.aaf6814 , p. 10.1126/science.aaf7000
Published: 2016
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42. Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes

Author: Hugo Y. K. Lam, Hua Tang, Suganthi Balasubramanian, Jennifer Li-Pook-Than, Elana Miriami, Alan P. Boyle, Lukas Habegger, Euan A. Ashley, Keith Bettinger, Michael Snyder, Atul J. Butte, Kari C. Nadeau, Phyllis Snyder, Lihua Jiang, Teri E. Klein, Sara Hillenmeyer, Michelle Whirl-Carrillo, Frederick E. Dewey, Maeve O'Huallachain, Joel T. Dudley, Hogune Im, Konrad J. Karczewski, Scott Seki, Fabian Grubert, Mercedes Gallardo, Donald Sharon, Marco Garcia, Mark Gerstein, Manoj Hariharan, Maria A. Blasco, Russ B. Altman, Ghia Euskirchen, Peter L. Greenberg, Yong Cheng, Rui Chen, Michael J. Clark, Phil Lacroute, Rong Chen, George I. Mias, Maya Kasowski, and Rajini R Haraksingh
Subjects: Male, Proteomics, Rhinovirus, Genomics, Computational biology, Biology, Genome, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, 0302 clinical medicine, Metabolomics, Humans, Precision Medicine, 030304 developmental biology, Genetics, 0303 health sciences, Biochemistry, Genetics and Molecular Biology(all), business.industry, Genome, Human, Gene Expression Profiling, Middle Aged, Precision medicine, Omics, 3. Good health, Respiratory Syncytial Viruses, Gene expression profiling, Diabetes Mellitus, Type 2, 030220 oncology & carcinogenesis, Mutation, Female, Personalized medicine, business
Abstract: SummaryPersonalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.
Published: 2012
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43. A systematic survey of loss-of-function variants in human protein-coding genes

Author: Klaudia Walter, Yali Xue, Jeffrey C. Barrett, Jennifer Harrow, Catherine E. Snow, Mark Gerstein, Ni Huang, Steven A. McCarroll, Jonathan K. Pritchard, Jeffrey A. Rosenfeld, Zhengdong D. Zhang, Hancheng Zheng, Menachem Fromer, Lukas Habegger, Yingrui Li, Mark A. DePristo, If H. A. Barnes, Bryndis Yngvadottir, James Morris, Alexandra Bignell, David Neil Cooper, Gerton Lunter, Ekta Khurana, Stephen B. Montgomery, Richard A. Gibbs, Donald F. Conrad, Emmanouil T. Dermitzakis, Daniel G. MacArthur, Suzannah Bumpstead, Gary Saunders, Kai Ye, Clara Amid, Marie-Marthe Suner, M. Kay, Joseph K. Pickrell, Adam Frankish, Robert E. Handsaker, Suganthi Balasubramanian, Eric Banks, Toby Hunt, Irene Gallego Romero, Cornelis A. Albers, Chris Tyler-Smith, Qasim Ayub, Denise Carvalho-Silva, Matthew E. Hurles, Min Hu, Luke Jostins, Jun Wang, Mike Jin, and Xinmeng Jasmine Mu
Subjects: Candidate gene, Gene Expression, Biology, Genome, Polymorphism, Single Nucleotide, Article, Genomic disorders and inherited multi-system disorders DCN MP - Plasticity and memory [IGMD 3], Gene Frequency, Genetic variation, Humans, ddc:576.5, Disease, Allele, Selection, Genetic, Gene, Loss function, Genetics, Multidisciplinary, Genome, Human, Genetic Variation, Proteins, Phenotype, Disease/genetics, Proteins/genetics, Human genome
Abstract: Defective Gene Detective Identifying genes that give rise to diseases is one of the major goals of sequencing human genomes. However, putative loss-of-function genes, which are often some of the first identified targets of genome and exome sequencing, have often turned out to be sequencing errors rather than true genetic variants. In order to identify the true scope of loss-of-function genes within the human genome, MacArthur et al. (p. 823 ; see the Perspective by Quintana-Murci ) extensively validated the genomes from the 1000 Genomes Project, as well as an additional European individual, and found that the average person has about 100 true loss-of-function alleles of which approximately 20 have two copies within an individual. Because many known disease-causing genes were identified in “normal” individuals, the process of clinical sequencing needs to reassess how to identify likely causative alleles.
Published: 2012
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44. Gene inactivation and its implications for annotation in the era of personal genomics

Author: Lukas Habegger, Suganthi Balasubramanian, Chris Tyler-Smith, Adam Frankish, Jennifer Harrow, Mark Gerstein, Rachel A. Harte, and Daniel G. MacArthur
Subjects: Genetics, Genome, Human, Pseudogene, Genetic Variation, Molecular Sequence Annotation, Computational biology, Biology, Polymorphism, Single Nucleotide, Genome, Human genetics, Perspective, Humans, Human genome, Gene Silencing, Genetic Privacy, Gene, Developmental Biology, Personal genomics, Reference genome
Abstract: The first wave of personal genomes documents how no single individual genome contains the full complement of functional genes. Here, we describe the extent of variation in gene and pseudogene numbers between individuals arising from inactivation events such as premature termination or aberrant splicing due to single-nucleotide polymorphisms. This highlights the inadequacy of the current reference sequence and gene set. We present a proposal to define a reference gene set that will remain stable as more individuals are sequenced. In particular, we recommend that the ancestral allele be used to define the reference sequence from which a core human reference gene annotation set can be derived. In addition, we call for the development of an expanded gene set to include human-specific genes that have arisen recently and are absent from the ancestral set.
Published: 2011
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45. Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies

Author: Monkol Lek, Samir H Al-Mueilo, Alhusain J. Alzahrani, Kelly A. Thomas, Dimitri S. Monos, Daniel G. MacArthur, Elena Carrigan, Ajay K. Israni, Eyas Mukhtar, Konrad J. Karczewski, Shefali S. Verma, Marylyn D. Ritchie, Brendan J. Keating, Hui Gao, Teresa Webster, Malek Kamoun, Ana Gonzalez, Jessica van Setten, Paul I.W. de Bakker, Laura Steel, Aubree Himes, Kim M. Olthoff, Pamala A. Jacobson, Maede Mohebnasab, Barbara Murphy, Kelsey M. Llyod, Hareesh R. Chandrupatla, Suganthi Balasubramanian, Takesha Lee, James Snyder, Abhinav Gangasani, Baolin Wu, B. Chang, Weihua Guan, Yun Li, Folkert W. Asselbergs, Kelly A. Birdwell, Matthew B. Lanktree, Abraham Shaked, Andrew Pasquier, Cisca Wijmenga, Cuiping Hou, Abigail Colasacco, Chanel Wong, Yontao Lu, Daniel E. McGinn, William S. Oetting, Fahad Al-Muhanna, Amein K. Al-Ali, Abdullah Akdere, Michael B. Miller, Jacob van Houten, David S. Schladt, Hongzhi Cao, Abdullah M. Al-Rubaish, Randy Phillips, Vinicius Tragante, Hakon Hakonarson, Nikhil Nair, Pablo García-Pavía, James Garifallou, Toumy Guettouche, Zach Michaud, Michael V. Holmes, Tiancheng Wang, Reina Yu, and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)
Subjects: SNP ARRAY, DNA Copy Number Variations, Genotype, KIDNEY-TRANSPLANTATION, Concordance, Population, MISMATCH, Genome-wide association study, 030230 surgery, Biology, Research Support, Polymorphism, Single Nucleotide, N.I.H, 03 medical and health sciences, 0302 clinical medicine, Receptors, KIR, Research Support, N.I.H., Extramural, HLA Antigens, MANAGEMENT, IMPUTATION, Genetics, Journal Article, Humans, Genetics(clinical), International HapMap Project, education, Non-U.S. Gov't, Genotyping, Molecular Biology, Genetics (clinical), POLYMORPHISMS, POPULATION, 030304 developmental biology, 0303 health sciences, education.field_of_study, Research, Research Support, Non-U.S. Gov't, Extramural, GENE, 3. Good health, SNP genotyping, Transplantation, RECIPIENTS, REJECTION, Molecular Medicine, Imputation (genetics), Genome-Wide Association Study
Abstract: Background In addition to HLA genetic incompatibility, non-HLA difference between donor and recipients of transplantation leading to allograft rejection are now becoming evident. We aimed to create a unique genome-wide platform to facilitate genomic research studies in transplant-related studies. We designed a genome-wide genotyping tool based on the most recent human genomic reference datasets, and included customization for known and potentially relevant metabolic and pharmacological loci relevant to transplantation. Methods We describe here the design and implementation of a customized genome-wide genotyping array, the ‘TxArray’, comprising approximately 782,000 markers with tailored content for deeper capture of variants across HLA, KIR, pharmacogenomic, and metabolic loci important in transplantation. To test concordance and genotyping quality, we genotyped 85 HapMap samples on the array, including eight trios. Results We show low Mendelian error rates and high concordance rates for HapMap samples (average parent-parent-child heritability of 0.997, and concordance of 0.996). We performed genotype imputation across autosomal regions, masking directly genotyped SNPs to assess imputation accuracy and report an accuracy of >0.962 for directly genotyped SNPs. We demonstrate much higher capture of the natural killer cell immunoglobulin-like receptor (KIR) region versus comparable platforms. Overall, we show that the genotyping quality and coverage of the TxArray is very high when compared to reference samples and to other genome-wide genotyping platforms. Conclusions We have designed a comprehensive genome-wide genotyping tool which enables accurate association testing and imputation of ungenotyped SNPs, facilitating powerful and cost-effective large-scale genotyping of transplant-related studies. Electronic supplementary material The online version of this article (doi:10.1186/s13073-015-0211-x) contains supplementary material, which is available to authorized users.
Published: 2015
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46. Sequence variation in G-protein-coupled receptors: analysis of single nucleotide polymorphisms

Author: Suganthi Balasubramanian, Elizaveta Freinkman, Mark Gerstein, and Yu Xia
Subjects: dbSNP, Sequence analysis, Entropy, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Article, Receptors, G-Protein-Coupled, Conserved sequence, 03 medical and health sciences, 0302 clinical medicine, Phylogenetics, Genetics, Humans, Genetic Predisposition to Disease, Genotyping, Phylogeny, 030304 developmental biology, Genetic association, 0303 health sciences, Phylogenetic tree, Sequence Analysis, DNA, Amino Acid Substitution, Regression Analysis, Hydrophobic and Hydrophilic Interactions, 030217 neurology & neurosurgery
Abstract: We assessed the disease-causing potential of single nucleotide polymorphisms (SNPs) based on a simple set of sequence-based features. We focused on SNPs from the dbSNP database in G-protein-coupled receptors (GPCRs), a large class of important transmembrane (TM) proteins. Apart from the location of the SNP in the protein, we evaluated the predictive power of three major classes of features to differentiate between disease-causing mutations and neutral changes: (i) properties derived from amino-acid scales, such as volume and hydrophobicity; (ii) position-specific phylogenetic features reflecting evolutionary conservation, such as normalized site entropy, residue frequency and SIFT score; and (iii) substitution-matrix scores, such as those derived from the BLOSUM62, GRANTHAM and PHAT matrices. We validated our approach using a control dataset consisting of known disease-causing mutations and neutral variations. Logistic regression analyses indicated that position-specific phylogenetic features that describe the conservation of an amino acid at a specific site are the best discriminators of disease mutations versus neutral variations, and integration of all our features improves discrimination power. Overall, we identify 115 SNPs in GPCRs from dbSNP that are likely to be associated with disease and thus are good candidates for genotyping in association studies.
Published: 2005
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47. Enhanced transcriptome maps from multiple mouse tissues reveal evolutionary constraint in gene expression

Author: Lei Hoon See, Jean Monlong, Huaien Wang, Dmitri D. Pervouchine, Alessandra Breschi, Alexander Dobin, Julien Lagarde, Cedric Notredame, Michael A. Beer, Suganthi Balasubramanian, Thomas R. Gingeras, Arif Harmanci, Meagan Fastuca, Chris Zaleski, Baikang Pei, Roderic Guigó, Pablo Prieto Barja, Mark Gerstein, Jorg Drenkow, Andrea Tanzer, Sarah Djebali, Giovanni Bussotti, and Carrie A. Davis
Subjects: Evolution, General Physics and Astronomy, Computational biology, Biology, Ratolins -- Genètica, Genome, Article, General Biochemistry, Genetics and Molecular Biology, Cell Line, Epigenesis, Genetic, Evolution, Molecular, Histones, Transcriptome, Mice, 03 medical and health sciences, 0302 clinical medicine, Regulació genètica, Gene expression, Genetics, Animals, Humans, Epigenetics, Gene, Gene Library, 030304 developmental biology, Regulation of gene expression, 0303 health sciences, Multidisciplinary, Models, Genetic, Sequence Analysis, RNA, Gene Expression Profiling, Alternative splicing, General Chemistry, Oligonucleotides, Antisense, Biological Evolution, Mice, Inbred C57BL, Gene expression profiling, Alternative Splicing, Biological sciences, Phenotype, Gene Expression Regulation, 030217 neurology & neurosurgery
Abstract: Mice have been a long-standing model for human biology and disease. Here we characterize, by RNA sequencing, the transcriptional profiles of a large and heterogeneous collection of mouse tissues, augmenting the mouse transcriptome with thousands of novel transcript candidates. Comparison with transcriptome profiles in human cell lines reveals substantial conservation of transcriptional programmes, and uncovers a distinct class of genes with levels of expression that have been constrained early in vertebrate evolution. This core set of genes captures a substantial fraction of the transcriptional output of mammalian cells, and participates in basic functional and structural housekeeping processes common to all cell types. Perturbation of these constrained genes is associated with significant phenotypes including embryonic lethality and cancer. Evolutionary constraint in gene expression levels is not reflected in the conservation of the genomic sequences, but is associated with conserved epigenetic marking, as well as with characteristic post-transcriptional regulatory programme, in which sub-cellular localization and alternative splicing play comparatively large roles., The analysis of mammalian transcriptomes could provide new insights into human biology. Here the authors carry out RNA sequencing in a large collection of mouse tissues and compare these data to human transcriptome profiles, identifying a set of constrained genes that carry out basic cellular functions with remarkably constant expression levels across tissues and species.
Published: 2015
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48. Additional file 2: Figure S1. of Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies

Author: Li, Yun, Setten, Jessica Van, Verma, Shefali, Yontao Lu, Holmes, Michael, Gao, Hui, Monkol Lek, Nair, Nikhil, Hareesh Chandrupatla, Baoli Chang, Karczewski, Konrad, Wong, Chanel, Maede Mohebnasab, Eyas Mukhtar, Phillips, Randy, Tragante, Vinicius, Cuiping Hou, Steel, Laura, Takesha Lee, Garifallou, James, Toumy Guettouche, Hongzhi Cao, Weihua Guan, Himes, Aubree, Houten, Jacob Van, Pasquier, Andrew, Yu, Reina, Carrigan, Elena, Miller, Michael, Schladt, David, Akdere, Abdullah, Gonzalez, Ana, Llyod, Kelsey, McGinn, Daniel, Abhinav Gangasani, Michaud, Zach, Colasacco, Abigail, Snyder, James, Thomas, Kelly, Tiancheng Wang, Baolin Wu, Alhusain Alzahrani, Amein Al-Ali, Al-Muhanna, Fahad, Al-Rubaish, Abdullah, Al-Mueilo, Samir, Monos, Dimitri, Murphy, Barbara, Olthoff, Kim, Wijmenga, Cisca, Webster, Teresa, Kamoun, Malek, Suganthi Balasubramanian, Lanktree, Matthew, Oetting, William, Garcia-Pavia, Pablo, MacArthur, Daniel, Bakker, Paul De, Hakon Hakonarson, Birdwell, Kelly, Jacobson, Pamala, Ritchie, Marylyn, Asselbergs, Folkert, Israni, Ajay, Shaked, Abraham, and Keating, Brendan
Abstract: TxArray transplant-specific modular contents. (PDF 140 kb)
Published: 2015
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49. Additional file 1: Table S1. of Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies

Author: Li, Yun, Setten, Jessica Van, Verma, Shefali, Yontao Lu, Holmes, Michael, Gao, Hui, Monkol Lek, Nair, Nikhil, Hareesh Chandrupatla, Baoli Chang, Karczewski, Konrad, Wong, Chanel, Maede Mohebnasab, Eyas Mukhtar, Phillips, Randy, Tragante, Vinicius, Cuiping Hou, Steel, Laura, Takesha Lee, Garifallou, James, Toumy Guettouche, Hongzhi Cao, Weihua Guan, Himes, Aubree, Houten, Jacob Van, Pasquier, Andrew, Yu, Reina, Carrigan, Elena, Miller, Michael, Schladt, David, Akdere, Abdullah, Gonzalez, Ana, Llyod, Kelsey, McGinn, Daniel, Abhinav Gangasani, Michaud, Zach, Colasacco, Abigail, Snyder, James, Thomas, Kelly, Tiancheng Wang, Baolin Wu, Alhusain Alzahrani, Amein Al-Ali, Al-Muhanna, Fahad, Al-Rubaish, Abdullah, Al-Mueilo, Samir, Monos, Dimitri, Murphy, Barbara, Olthoff, Kim, Wijmenga, Cisca, Webster, Teresa, Kamoun, Malek, Suganthi Balasubramanian, Lanktree, Matthew, Oetting, William, Garcia-Pavia, Pablo, MacArthur, Daniel, Bakker, Paul De, Hakon Hakonarson, Birdwell, Kelly, Jacobson, Pamala, Ritchie, Marylyn, Asselbergs, Folkert, Israni, Ajay, Shaked, Abraham, and Keating, Brendan
Abstract: Tagging and coverage of MHC region markers. Table S2: Tagging and coverage of Tx-specific genes. Table S3: Untranslated regions (UTRs) considered in the TxArray design. Table S4: Loss-of-function variants included in the TxArray. Table S5: Copy number polymorphisms (CNPs) and variations (CNVs) included in the TxArray. (DOCX 54 kb)
Published: 2015
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50. A global reference for human genetic variation

Author: Colonna V. (1000 Genomes Project Consortium) Adam Auton, Gonçalo R Abecasis, David M Altshuler, Richard M Durbin, David R Bentley, Aravinda Chakravarti, Andrew G Clark, Peter Donnelly, Evan E Eichler, Paul Flicek, Stacey B Gabriel, Richard A Gibbs, Eric D Green, Matthew E Hurles, Bartha M Knoppers, Jan O Korbel, Eric S Lander, Charles Lee, Hans Lehrach, Elaine R Mardis, Gabor T Marth, Gil A McVean, Deborah A Nickerson, Jeanette P Schmidt, Stephen T Sherry, Jun Wang, Richard K Wilson, Eric Boerwinkle, Harsha Doddapaneni, Yi Han, Viktoriya Korchina, Christie Kovar, Sandra Lee, Donna Muzny, Jeffrey G Reid, Yiming Zhu, Yuqi Chang, Qiang Feng, Xiaodong Fang, Xiaosen Guo, Min Jian, Hui Jiang, Xin Jin, Tianming Lan, Guoqing Li, Jingxiang Li, Yingrui Li, Shengmao Liu, Xiao Liu, Yao Lu, Xuedi Ma, Meifang Tang, Bo Wang, Guangbiao Wang, Honglong Wu, Renhua Wu, Xun Xu, Ye Yin, Dandan Zhang, Wenwei Zhang, Jiao Zhao, Meiru Zhao, Xiaole Zheng, Namrata Gupta, Neda Gharani, Lorraine H Toji, Norman P Gerry, Alissa M Resch, Jonathan Barker, Laura Clarke, Laurent Gil, Sarah E Hunt, Gavin Kelman, Eugene Kulesha, Rasko Leinonen, William M McLaren, Rajesh Radhakrishnan, Asier Roa, Dmitriy Smirnov, Richard E Smith, Ian Streeter, Anja Thormann, Iliana Toneva, Brendan Vaughan, Xiangqun Zheng-Bradley, Russell Grocock, Sean Humphray, Terena James, Zoya Kingsbury, Ralf Sudbrak, Marcus W Albrecht, Vyacheslav S Amstislavskiy, Tatiana A Borodina, Matthias Lienhard, Florian Mertes, Marc Sultan, Bernd Timmermann, Marie-Laure Yaspo, Lucinda Fulton, Robert Fulton, Victor Ananiev, Zinaida Belaia, Dimitriy Beloslyudtsev, Nathan Bouk, Chao Chen, Deanna Church, Robert Cohen, Charles Cook, John Garner, Timothy Hefferon, Mikhail Kimelman, Chunlei Liu, John Lopez, Peter Meric, Chris O'Sullivan, Yuri Ostapchuk, Lon Phan, Sergiy Ponomarov, Valerie Schneider, Eugene Shekhtman, Karl Sirotkin, Douglas Slotta, Hua Zhang, Senduran Balasubramaniam, John Burton, Petr Danecek, Thomas M Keane, Anja Kolb-Kokocinski, Shane McCarthy, James Stalker, Michael Quail, Christopher J Davies, Jeremy Gollub, Teresa Webster, Brant Wong, Yiping Zhan, Adam Auton, Christopher L Campbell, Yu Kong, Anthony Marcketta, Fuli Yu, Lilian Antunes, Matthew Bainbridge, Aniko Sabo, Zhuoyi Huang, Lachlan J M Coin, Lin Fang, Qibin Li, Zhenyu Li, Haoxiang Lin, Binghang Liu, Ruibang Luo, Haojing Shao, Yinlong Xie, Chen Ye, Chang Yu, Fan Zhang, Hancheng Zheng, Hongmei Zhu, Can Alkan, Elif Dal, Fatma Kahveci, Erik P Garrison, Deniz Kural, Wan-Ping Lee, Wen Fung Leong, Michael Stromberg, Alistair N Ward, Jiantao Wu, Mengyao Zhang, Mark J Daly, Mark A DePristo, Robert E Handsaker, Eric Banks, Gaurav Bhatia, Guillermo Del Angel, Giulio Genovese, Heng Li, Seva Kashin, Steven A McCarroll, James C Nemesh, Ryan E Poplin, Seungtai C Yoon, Jayon Lihm, Vladimir Makarov, Srikanth Gottipati, Alon Keinan, Juan L Rodriguez-Flores, Tobias Rausch, Markus H Fritz, Adrian M Stütz, Kathryn Beal, Avik Datta, Javier Herrero, Graham R S Ritchie, Daniel Zerbino, Pardis C Sabeti, Ilya Shlyakhter, Stephen F Schaffner, Joseph Vitti, David N Cooper, Edward V Ball, Peter D Stenson, Bret Barnes, Markus Bauer, R Keira Cheetham, Anthony Cox, Michael Eberle, Scott Kahn, Lisa Murray, John Peden, Richard Shaw, Eimear E Kenny, Mark A Batzer, Miriam K Konkel, Jerilyn A Walker, Daniel G MacArthur, Monkol Lek, Ralf Herwig, Li Ding, Daniel C Koboldt, David Larson, Kai Ye, Simon Gravel, Anand Swaroop, Emily Chew, Tuuli Lappalainen, Yaniv Erlich, Melissa Gymrek, Thomas Frederick Willems, Jared T Simpson, Mark D Shriver, Jeffrey A Rosenfeld, Carlos D Bustamante, Stephen B Montgomery, Francisco M De La Vega, Jake K Byrnes, Andrew W Carroll, Marianne K DeGorter, Phil Lacroute, Brian K Maples, Alicia R Martin, Andres Moreno-Estrada, Suyash S Shringarpure, Fouad Zakharia, Eran Halperin, Yael Baran, Eliza Cerveira, Jaeho Hwang, Ankit Malhotra, Dariusz Plewczynski, Kamen Radew, Mallory Romanovitch, Chengsheng Zhang, Fiona C L Hyland, David W Craig, Alexis Christoforides, Nils Homer, Tyler Izatt, Ahmet A Kurdoglu, Shripad A Sinari, Kevin Squire, Chunlin Xiao, Jonathan Sebat, Danny Antaki, Madhusudan Gujral, Amina Noor, Kenny Ye, Esteban G Burchard, Ryan D Hernandez, Christopher R Gignoux, David Haussler, Sol J Katzman, W James Kent, Bryan Howie, Andres Ruiz-Linares, Emmanouil T Dermitzakis, Scott E Devine, Hyun Min Kang, Jeffrey M Kidd, Tom Blackwell, Sean Caron, Wei Chen, Sarah Emery, Lars Fritsche, Christian Fuchsberger, Goo Jun, Bingshan Li, Robert Lyons, Chris Scheller, Carlo Sidore, Shiya Song, Elzbieta Sliwerska, Daniel Taliun, Adrian Tan, Ryan Welch, Mary Kate Wing, Xiaowei Zhan, Philip Awadalla, Alan Hodgkinson, Yun Li, Xinghua Shi, Andrew Quitadamo, Gerton Lunter, Jonathan L Marchini, Simon Myers, Claire Churchhouse, Olivier Delaneau, Anjali Gupta-Hinch, Warren Kretzschmar, Zamin Iqbal, Iain Mathieson, Androniki Menelaou, Andy Rimmer, Dionysia K Xifara, Taras K Oleksyk, Yunxin Fu, Xiaoming Liu, Momiao Xiong, Lynn Jorde, David Witherspoon, Jinchuan Xing, Brian L Browning, Sharon R Browning, Fereydoun Hormozdiari, Peter H Sudmant, Ekta Khurana, Chris Tyler-Smith, Cornelis A Albers, Qasim Ayub, Yuan Chen, Vincenza Colonna, Luke Jostins, Klaudia Walter, Yali Xue, Mark B Gerstein, Alexej Abyzov, Suganthi Balasubramanian, Jieming Chen, Declan Clarke, Yao Fu, Arif O Harmanci, Mike Jin, Donghoon Lee, Jeremy Liu, Xinmeng Jasmine Mu, Jing Zhang, Yan Zhang, Chris Hartl, Khalid Shakir, Jeremiah Degenhardt, Sascha Meiers, Benjamin Raeder, Francesco Paolo Casale, Oliver Stegle, Eric-Wubbo Lameijer, Ira Hall, Vineet Bafna, Jacob Michaelson, Eugene J Gardner, Ryan E Mills, Gargi Dayama, Ken Chen, Xian Fan, Zechen Chong, Tenghui Chen, Mark J Chaisson, John Huddleston, Maika Malig, Bradley J Nelson, Nicholas F Parrish, Ben Blackburne, Sarah J Lindsay, Zemin Ning, Yujun Zhang, Hugo Lam, Cristina Sisu, Danny Challis, Uday S Evani, James Lu, Uma Nagaswamy, Jin Yu, Wangshen Li, Lukas Habegger, Haiyuan Yu, Fiona Cunningham, Ian Dunham, Kasper Lage, Jakob Berg Jespersen, Heiko Horn, Donghoon Kim, Rob Desalle, Apurva Narechania, Melissa A Wilson Sayres, Fernando L Mendez, G David Poznik, Peter A Underhill, Lachlan Coin, David Mittelman, Ruby Banerjee, Maria Cerezo, Thomas W Fitzgerald, Sandra Louzada, Andrea Massaia, Graham R Ritchie, Fengtang Yang, Divya Kalra, Walker Hale, Xu Dan, Kathleen C Barnes, Christine Beiswanger, Hongyu Cai, Hongzhi Cao, Brenna Henn, Danielle Jones, Jane S Kaye, Alastair Kent, Angeliki Kerasidou, Rasika Mathias, Pilar N Ossorio, Michael Parker, Charles N Rotimi, Charmaine D Royal, Karla Sandoval, Yeyang Su, Zhongming Tian, Sarah Tishkoff, Marc Via, Yuhong Wang, Huanming Yang, Ling Yang, Jiayong Zhu, Walter Bodmer, Gabriel Bedoya, Zhiming Cai, Yang Gao, Jiayou Chu, Leena Peltonen, Andres Garcia-Montero, Alberto Orfao, Julie Dutil, Juan C Martinez-Cruzado, Rasika A Mathias, Anselm Hennis, Harold Watson, Colin McKenzie, Firdausi Qadri, Regina LaRocque, Xiaoyan Deng, Danny Asogun, Onikepe Folarin, Christian Happi, Omonwunmi Omoniwa, Matt Stremlau, Ridhi Tariyal, Muminatou Jallow, Fatoumatta Sisay Joof, Tumani Corrah, Kirk Rockett, Dominic Kwiatkowski, Jaspal Kooner, Trân T?nh Hiên, Sarah J Dunstan, Nguyen Thuy Hang, Richard Fonnie, Robert Garry, Lansana Kanneh, Lina Moses, John Schieffelin, Donald S Grant, Carla Gallo, Giovanni Poletti, Danish Saleheen, Asif Rasheed, Lisa D Brooks, Adam L Felsenfeld, Jean E McEwen, Yekaterina Vaydylevich, Audrey Duncanson, Michael Dunn, Jeffery A Schloss, 1000 Genomes Project Consortium, Institute for Medical Engineering and Science, Broad Institute of MIT and Harvard, Lincoln Laboratory, Massachusetts Institute of Technology. Department of Biology, Gabriel, Stacey, Lander, Eric Steven, Daly, Mark J, Banks, Eric, Bhatia, Gaurav, Kashin, Seva, McCarroll, Steven A, Nemesh, James, Poplin, Ryan E., Sabeti, Pardis, Shlyakhter, Ilya, Schaffner, Stephen F, Vitti, Joseph, Gymrek, Melissa A, Hartler, Christina M., and Tariyal, Ridhi
Subjects: demography, genetic association, genotype, Human genomics, Genome-wide association study, Review, SUSCEPTIBILITY, DISEASE, polymorphism, 0302 clinical medicine, quantitative trait locus, INDEL Mutation, genetics, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), MUTATION, Exome sequencing, 0303 health sciences, public health, Sequence analysis, High-Throughput Nucleotide Sequencing, standard, Genomics, Reference Standards, Physical Chromosome Mapping, 3. Good health, priority journal, Science & Technology - Other Topics, BAYES FACTORS, Molecular Developmental Biology, Genotype, Genetics, Medical, Quantitative Trait Loci, DNA sequence, rare disease, human genetics, information processing, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, POPULATION HISTORY, human genome, Humans, retroposon, Genetic variability, human, GENOME-WIDE ASSOCIATION, 1000 Genomes Project, Demography, Science & Technology, ancestry, disease predisposition, Genetic Variation, MACULAR DEGENERATION, major clinical study, gene linkage disequilibrium, purl.org/pe-repo/ocde/ford#3.01.02 [https], Genetics, Population, 030217 neurology & neurosurgery, haplotype, Internationality, VARIANT, Datasets as Topic, Human genetic variation, COMPLEMENT FACTOR-H, single nucleotide polymorphism, genetic variability, Exome, chromosome map, Genetics, Variant Call Format, Genome, Multidisciplinary, 1000 Genomes Project Consortium, international cooperation, Multidisciplinary Sciences, standards, Disease Susceptibility, medical genetics, General Science & Technology, Population, Computational biology, Biology, gene frequency, Polymorphism, Single Nucleotide, high throughput sequencing, Rare Diseases, promoter region, MD Multidisciplinary, Genetic variation, QH426, 030304 developmental biology, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Genome, Human, population genetics, population structure, Sequence Analysis, DNA, gene structure, INDIVIDUALS, Haplotypes, Genome-Wide Association Study, purl.org/pe-repo/ocde/ford#1.06.07 [https]
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies., Wellcome Trust (London, England) (Core Award 090532/Z/09/Z), Wellcome Trust (London, England) (Senior Investigator Award 095552/Z/11/Z ), Wellcome Trust (London, England) (WT095908), Wellcome Trust (London, England) (WT109497), Wellcome Trust (London, England) (WT098051), Wellcome Trust (London, England) (WT086084/Z/08/Z), Wellcome Trust (London, England) (WT100956/Z/13/Z ), Wellcome Trust (London, England) (WT097307), Wellcome Trust (London, England) (WT0855322/Z/08/Z ), Wellcome Trust (London, England) (WT090770/Z/09/Z ), Wellcome Trust (London, England) (Major Overseas program in Vietnam grant 089276/Z.09/Z), Medical Research Council (Great Britain) (grant G0801823), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I02593X/1), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I021213/1), Zhongguo ke xue ji shu qing bao yan jiu suo. Office of 863 Programme of China (2012AA02A201), National Basic Research Program of China (2011CB809201), National Basic Research Program of China (2011CB809202), National Basic Research Program of China (2011CB809203), National Natural Science Foundation of China (31161130357), Shenzhen Municipal Government of China (grant ZYC201105170397A), Canadian Institutes of Health Research (grant 136855), Quebec Ministry of Economic Development, Innovation, and Exports (PSR-SIIRI-195), Germany. Bundesministerium für Bildung und Forschung (0315428A), Germany. Bundesministerium für Bildung und Forschung (01GS08201), Germany. Bundesministerium für Bildung und Forschung (BMBF-EPITREAT grant 0316190A), Deutsche Forschungsgemeinschaft (Emmy Noether Grant KO4037/1-1), Beatriu de Pinos Program (2006 BP-A 10144), Beatriu de Pinos Program (2009 BP-B 00274), Spanish National Institute for Health (grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER), Japan Society for the Promotion of Science (fellowship number PE13075), Marie Curie Actions Career Integration (grant 303772), Fonds National Suisse del la Recherche, SNSF, Scientifique (31003A_130342), National Center for Biotechnology Information (U.S.) (U54HG3067), National Center for Biotechnology Information (U.S.) (U54HG3273), National Center for Biotechnology Information (U.S.) (U01HG5211), National Center for Biotechnology Information (U.S.) (U54HG3079), National Center for Biotechnology Information (U.S.) (R01HG2898), National Center for Biotechnology Information (U.S.) (R01HG2385), National Center for Biotechnology Information (U.S.) (RC2HG5552), National Center for Biotechnology Information (U.S.) (U01HG6513), National Center for Biotechnology Information (U.S.) (U01HG5214), National Center for Biotechnology Information (U.S.) (U01HG5715), National Center for Biotechnology Information (U.S.) (U01HG5718), National Center for Biotechnology Information (U.S.) (U01HG5728), National Center for Biotechnology Information (U.S.) (U41HG7635), National Center for Biotechnology Information (U.S.) (U41HG7497), National Center for Biotechnology Information (U.S.) (R01HG4960), National Center for Biotechnology Information (U.S.) (R01HG5701), National Center for Biotechnology Information (U.S.) (R01HG5214), National Center for Biotechnology Information (U.S.) (R01HG6855), National Center for Biotechnology Information (U.S.) (R01HG7068), National Center for Biotechnology Information (U.S.) (R01HG7644), National Center for Biotechnology Information (U.S.) (DP2OD6514), National Center for Biotechnology Information (U.S.) (DP5OD9154), National Center for Biotechnology Information (U.S.) (R01CA166661), National Center for Biotechnology Information (U.S.) (R01CA172652), National Center for Biotechnology Information (U.S.) (P01GM99568), National Center for Biotechnology Information (U.S.) (R01GM59290), National Center for Biotechnology Information (U.S.) (R01GM104390), National Center for Biotechnology Information (U.S.) (T32GM7790), National Center for Biotechnology Information (U.S.) (R01HL87699), National Center for Biotechnology Information (U.S.) (R01HL104608), National Center for Biotechnology Information (U.S.) (T32HL94284), National Center for Biotechnology Information (U.S.) (HHSN268201100040C), National Center for Biotechnology Information (U.S.) (HHSN272201000025C), Lundbeck Foundation (grant R170-2014-1039, Simons Foundation (SFARI award SF51), National Science Foundation (U.S.) (Research Fellowship DGE-1147470)
Published: 2015
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