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1. 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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2. 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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3. 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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4. 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

5. 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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6. 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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7. 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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8. 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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9. 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

10. 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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11. 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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12. 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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