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1. FixItFelix: improving genomic analysis by fixing reference errors

Author

Sairam Behera, Jonathon LeFaive, Peter Orchard, Medhat Mahmoud, Luis F. Paulin, Jesse Farek, Daniela C. Soto, Stephen C. J. Parker, Albert V. Smith, Megan Y. Dennis, Justin M. Zook, and Fritz J. Sedlazeck

Subjects
Reference, GRCh38, T2T-CHM13, Variant, SNV, INDEL, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract The current version of the human reference genome, GRCh38, contains a number of errors including 1.2 Mbp of falsely duplicated and 8.04 Mbp of collapsed regions. These errors impact the variant calling of 33 protein-coding genes, including 12 with medical relevance. Here, we present FixItFelix, an efficient remapping approach, together with a modified version of the GRCh38 reference genome that improves the subsequent analysis across these genes within minutes for an existing alignment file while maintaining the same coordinates. We showcase these improvements over multi-ethnic control samples, demonstrating improvements for population variant calling as well as eQTL studies.

Published
2023
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2. Epigenome-wide DNA methylation association study of circulating IgE levels identifies novel targets for asthmaResearch in context

Author

Kathryn Recto, Priyadarshini Kachroo, Tianxiao Huan, David Van Den Berg, Gha Young Lee, Helena Bui, Dong Heon Lee, Jessica Gereige, Chen Yao, Shih-Jen Hwang, Roby Joehanes, Scott T. Weiss, George T. O’Connor, Daniel Levy, Dawn L. DeMeo, Namiko Abe, Gonçalo Abecasis, Francois Aguet, Christine Albert, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Kristin Ardlie, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, Najib Ayas, Adithya Balasubramanian, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Lucas Barwick, Terri Beaty, Gerald Beck, Diane Becker, Lewis Becker, Rebecca Beer, Amber Beitelshees, Emelia Benjamin, Takis Benos, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Nathan Blue, Eric Boerwinkle, Donald W. Bowden, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Deborah Brown, Karen Bunting, Esteban Burchard, Carlos Bustamante, Erin Buth, Brian Cade, Jonathan Cardwell, Vincent Carey, Julie Carrier, April P. Carson, Cara Carty, Richard Casaburi, Juan P. Casas Romero, James Casella, Peter Castaldi, Mark Chaffin, Christy Chang, Yi-Cheng Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Yii-Der Ida Chen, Michael Cho, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Ren-Hua Chung, Clary Clish, Suzy Comhair, Matthew Conomos, Elaine Cornell, Adolfo Correa, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sean David, Colleen Davis, Michelle Daya, Mariza de Andrade, Lisa de las Fuentes, Paul de Vries, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Huyen Dinh, Harsha Doddapaneni, Qing Duan, Shannon Dugan-Perez, Ravi Duggirala, Jon Peter Durda, Susan K. Dutcher, Charles Eaton, Lynette Ekunwe, Adel El Boueiz, Patrick Ellinor, Leslie Emery, Serpil Erzurum, Charles Farber, Jesse Farek, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Chris Frazar, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Shanshan Gao, Yan Gao, Margery Gass, Heather Geiger, Bruce Gelb, Mark Geraci, Soren Germer, Robert Gerszten, Auyon Ghosh, Richard Gibbs, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, Sharon Graw, Kathryn J. Gray, Daniel Grine, Colin Gross, C. Charles Gu, Yue Guan, Xiuqing Guo, Namrata Gupta, Jeff Haessler, Michael Hall, Yi Han, Patrick Hanly, Daniel Harris, Nicola L. Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, Brian Hobbs, John Hokanson, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Jianhong Hu, Yi-Jen Hung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Deepti Jain, Cashell Jaquish, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Ziad Khan, Wonji Kim, John Kimoff, Greg Kinney, Barbara Konkle, Charles Kooperberg, Holly Kramer, Christoph Lange, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Jiwon Lee, Sandra Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Joshua Lewis, Xiaohui Li, Yun Li, Henry Lin, Honghuang Lin, Xihong Lin, Simin Liu, Yongmei Liu, Yu Liu, Ruth J.F. Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Ulysses Magalang, Michael Mahaney, Barry Make, Ani Manichaikul, Alisa Manning, JoAnn Manson, Lisa Martin, Melissa Marton, Susan Mathai, Rasika Mathias, Susanne May, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Daniel McGoldrick, Caitlin McHugh, Becky McNeil, Hao Mei, James Meigs, Vipin Menon, Luisa Mestroni, Ginger Metcalf, Deborah A. Meyers, Emmanuel Mignot, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton D. Mitchell, Matt Moll, Zeineen Momin, May E. Montasser, Courtney Montgomery, Donna Muzny, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Take Naseri, Pradeep Natarajan, Sergei Nekhai, Sarah C. Nelson, Bonnie Neltner, Caitlin Nessner, Deborah Nickerson, Osuji Nkechinyere, Kari North, Jeff O'Connell, Tim O'Connor, Heather Ochs-Balcom, Geoffrey Okwuonu, Allan Pack, David T. Paik, Nicholette Palmer, James Pankow, George Papanicolaou, Cora Parker, Gina Peloso, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Jacob Pleiness, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Bruce Psaty, Pankaj Qasba, Dandi Qiao, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Mahitha Rajendran, Vasan S. Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Catherine Reeves, Elizabeth Regan, Alex Reiner, Muagututi‘a Sefuiva Reupena, Ken Rice, Stephen Rich, Rebecca Robillard, Nicolas Robine, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Alexi Runnels, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Ester Cerdeira Sabino, Danish Saleheen, Shabnam Salimi, Sejal Salvi, Steven Salzberg, Kevin Sandow, Vijay G. Sankaran, Jireh Santibanez, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Frédéric Sériès, Vivien Sheehan, Stephanie L. Sherman, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Robert Skomro, Albert Vernon Smith, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Michael Snyder, Tamar Sofer, Nona Sotoodehnia, Adrienne M. Stilp, Garrett Storm, Elizabeth Streeten, Jessica Lasky Su, Yun Ju Sung, Jody Sylvia, Adam Szpiro, Daniel Taliun, Hua Tang, Margaret Taub, Kent Taylor, Matthew Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Machiko Threlkeld, Lesley Tinker, David Tirschwell, Sarah Tishkoff, Hemant Tiwari, Catherine Tong, Russell Tracy, Michael Tsai, Dhananjay Vaidya, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Fei Fei Wang, Heming Wang, Jiongming Wang, Karol Watson, Jennifer Watt, Daniel E. Weeks, Joshua Weinstock, Bruce Weir, Lu-Chen Weng, Jennifer Wessel, Cristen Willer, Kayleen Williams, L. Keoki Williams, Scott Williams, Carla Wilson, James Wilson, Lara Winterkorn, Quenna Wong, Baojun Wu, Joseph Wu, Huichun Xu, Lisa Yanek, Ivana Yang, Ketian Yu, Seyedeh Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiaofeng Zhu, Elad Ziv, Michael Zody, and Sebastian Zoellner

Subjects
EWAS, DNA methylation, IgE, Asthma, RNA-Sequencing, Mendelian randomization, Medicine, Medicine (General), R5-920
Abstract

Summary: Background: Identifying novel epigenetic signatures associated with serum immunoglobulin E (IgE) may improve our understanding of molecular mechanisms underlying asthma and IgE-mediated diseases. Methods: We performed an epigenome-wide association study using whole blood from Framingham Heart Study (FHS; n = 3,471, 46% females) participants and validated results using the Childhood Asthma Management Program (CAMP; n = 674, 39% females) and the Genetic Epidemiology of Asthma in Costa Rica Study (CRA; n = 787, 41% females). Using the closest gene to each IgE-associated CpG, we highlighted biologically plausible pathways underlying IgE regulation and analyzed the transcription patterns linked to IgE-associated CpGs (expression quantitative trait methylation loci; eQTMs). Using prior UK Biobank summary data from genome-wide association studies of asthma and allergy, we performed Mendelian randomization (MR) for causal inference testing using the IgE-associated CpGs from FHS with methylation quantitative trait loci (mQTLs) as instrumental variables. Findings: We identified 490 statistically significant differentially methylated CpGs associated with IgE in FHS, of which 193 (39.3%) replicated in CAMP and CRA (FDR < 0.05). Gene ontology analysis revealed enrichment in pathways related to transcription factor binding, asthma, and other immunological processes. eQTM analysis identified 124 cis-eQTMs for 106 expressed genes (FDR < 0.05). MR in combination with drug-target analysis revealed CTSB and USP20 as putatively causal regulators of IgE levels (Bonferroni adjusted P

Published
2023
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3. Telomere length is not a main factor for the development of islet autoimmunity and type 1 diabetes in the TEDDY study

Author

Carina Törn, Xiang Liu, Suna Onengut-Gumuscu, Kevin M. Counts, Jose Leonardo Moreno, Cassandra L. Remedios, Wei-Min Chen, Jonathon LeFaive, Martha D. Butterworth, Beena Akolkar, Jeffrey P. Krischer, Åke Lernmark, Marian Rewers, Jin-Xiong She, Jorma Toppari, Anette-Gabriele Ziegler, Aakrosh Ratan, Albert V. Smith, William A. Hagopian, Stephen S. Rich, Hemang M. Parikh, and The TEDDY Study Group

Subjects
Medicine, Science
Abstract

Abstract The Environmental Determinants of Diabetes in the Young (TEDDY) study enrolled 8676 children, 3–4 months of age, born with HLA-susceptibility genotypes for islet autoimmunity (IA) and type 1 diabetes (T1D). Whole-genome sequencing (WGS) was performed in 1119 children in a nested case–control study design. Telomere length was estimated from WGS data using five tools: Computel, Telseq, Telomerecat, qMotif and Motif_counter. The estimated median telomere length was 5.10 kb (IQR 4.52–5.68 kb) using Computel. The age when the blood sample was drawn had a significant negative correlation with telomere length (P = 0.003). European children, particularly those from Finland (P = 0.041) and from Sweden (P = 0.001), had shorter telomeres than children from the U.S.A. Paternal age (P = 0.019) was positively associated with telomere length. First-degree relative status, presence of gestational diabetes in the mother, and maternal age did not have a significant impact on estimated telomere length. HLA-DR4/4 or HLA-DR4/X children had significantly longer telomeres compared to children with HLA-DR3/3 or HLA-DR3/9 haplogenotypes (P = 0.008). Estimated telomere length was not significantly different with respect to any IA (P = 0.377), IAA-first (P = 0.248), GADA-first (P = 0.248) or T1D (P = 0.861). These results suggest that telomere length has no major impact on the risk for IA, the first step to develop T1D. Nevertheless, telomere length was shorter in the T1D high prevalence populations, Finland and Sweden.

Published
2022
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4. Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease

Author

Jonas B. Nielsen, Oren Rom, Ida Surakka, Sarah E. Graham, Wei Zhou, Tanmoy Roychowdhury, Lars G. Fritsche, Sarah A. Gagliano Taliun, Carlo Sidore, Yuhao Liu, Maiken E. Gabrielsen, Anne Heidi Skogholt, Brooke Wolford, William Overton, Ying Zhao, Jin Chen, He Zhang, Whitney E. Hornsby, Akua Acheampong, Austen Grooms, Amanda Schaefer, Gregory J. M. Zajac, Luis Villacorta, Jifeng Zhang, Ben Brumpton, Mari Løset, Vivek Rai, Pia R. Lundegaard, Morten S. Olesen, Kent D. Taylor, Nicholette D. Palmer, Yii-Der Chen, Seung H. Choi, Steven A. Lubitz, Patrick T. Ellinor, Kathleen C. Barnes, Michelle Daya, Nicholas Rafaels, Scott T. Weiss, Jessica Lasky-Su, Russell P. Tracy, Ramachandran S. Vasan, L. Adrienne Cupples, Rasika A. Mathias, Lisa R. Yanek, Lewis C. Becker, Patricia A. Peyser, Lawrence F. Bielak, Jennifer A. Smith, Stella Aslibekyan, Bertha A. Hidalgo, Donna K. Arnett, Marguerite R. Irvin, James G. Wilson, Solomon K. Musani, Adolfo Correa, Stephen S. Rich, Xiuqing Guo, Jerome I. Rotter, Barbara A. Konkle, Jill M. Johnsen, Allison E. Ashley-Koch, Marilyn J. Telen, Vivien A. Sheehan, John Blangero, Joanne E. Curran, Juan M. Peralta, Courtney Montgomery, Wayne H-H Sheu, Ren-Hua Chung, Karen Schwander, Seyed M. Nouraie, Victor R. Gordeuk, Yingze Zhang, Charles Kooperberg, Alexander P. Reiner, Rebecca D. Jackson, Eugene R. Bleecker, Deborah A. Meyers, Xingnan Li, Sayantan Das, Ketian Yu, Jonathon LeFaive, Albert Smith, Tom Blackwell, Daniel Taliun, Sebastian Zollner, Lukas Forer, Sebastian Schoenherr, Christian Fuchsberger, Anita Pandit, Matthew Zawistowski, Sachin Kheterpal, Chad M. Brummett, Pradeep Natarajan, David Schlessinger, Seunggeun Lee, Hyun Min Kang, Francesco Cucca, Oddgeir L. Holmen, Bjørn O. Åsvold, Michael Boehnke, Sekar Kathiresan, Goncalo R. Abecasis, Y. Eugene Chen, Cristen J. Willer, and Kristian Hveem

Subjects
Science
Abstract

Drugs targeting cardiovascular disease (CVD) can have negative consequences for liver function. Here, the authors combine genome wide analyses on 69,479 individuals to identify loss-of-function variants with beneficial effects on CVD-related traits without negative impacts on liver function.

Published
2020
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5. Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb.

Author

Lars G Fritsche, Lauren J Beesley, Peter VandeHaar, Robert B Peng, Maxwell Salvatore, Matthew Zawistowski, Sarah A Gagliano Taliun, Sayantan Das, Jonathon LeFaive, Erin O Kaleba, Thomas T Klumpner, Stephanie E Moser, Victoria M Blanc, Chad M Brummett, Sachin Kheterpal, Gonçalo R Abecasis, Stephen B Gruber, and Bhramar Mukherjee

Subjects
Genetics, QH426-470
Abstract

Polygenic risk scores (PRS) are designed to serve as single summary measures that are easy to construct, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The primary focus of this paper is to demonstrate how we can combine PRS and electronic health records data to better understand the shared and unique genetic architecture and etiology of disease subtypes that may be both related and heterogeneous. PRS construction strategies often depend on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. We consider several choices for constructing a PRS using data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict not just the primary phenotype but also secondary phenotypes derived from electronic health records (EHR). This study was conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. We examine the three most common skin cancer subtypes in the USA: basal cell carcinoma, cutaneous squamous cell carcinoma, and melanoma. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate PRS associations with secondary traits. PheWAS results are then replicated using population-based UK Biobank data and compared across various PRS construction methods. We develop an accompanying visual catalog called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods.

Published
2019
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7. Extent to which array genotyping and imputation with large reference panels approximate deep whole-genome sequencing

Author

Sarah C. Hanks, Lukas Forer, Sebastian Schönherr, Jonathon LeFaive, Taylor Martins, Ryan Welch, Sarah A. Gagliano Taliun, David Braff, Jill M. Johnsen, Eimear E. Kenny, Barbara A. Konkle, Markku Laakso, Ruth F.J. Loos, Steven McCarroll, Carlos Pato, Michele T. Pato, Albert V. Smith, Michael Boehnke, Laura J. Scott, and Christian Fuchsberger

Subjects
Gene Frequency, Genotype, Whole Genome Sequencing, Genetics, High-Throughput Nucleotide Sequencing, Humans, Polymorphism, Single Nucleotide, Article, Genetics (clinical), Genome-Wide Association Study
Abstract

Understanding the genetic basis of human diseases and traits is dependent on the identification and accurate genotyping of genetic variants. Deep whole-genome sequencing (WGS), the gold standard technology for SNP and indel identification and genotyping, remains very expensive for most large studies. Here, we quantify the extent to which array genotyping followed by genotype imputation can approximate WGS in studies of individuals of African, Hispanic/Latino, and European ancestry in the US and of Finnish ancestry in Finland (a population isolate). For each study, we performed genotype imputation by using the genetic variants present on the Illumina Core, OmniExpress, MEGA, and Omni 2.5M arrays with the 1000G, HRC, and TOPMed imputation reference panels. Using the Omni 2.5M array and the TOPMed panel, ≥90% of bi-allelic single-nucleotide variants (SNVs) are well imputed (r(2) > 0.8) down to minor-allele frequencies (MAFs) of 0.14% in African, 0.11% in Hispanic/Latino, 0.35% in European, and 0.85% in Finnish ancestries. There was little difference in TOPMed-based imputation quality among the arrays with >700k variants. Individual-level imputation quality varied widely between and within the three US studies. Imputation quality also varied across genomic regions, producing regions where even common (MAF > 5%) variants were consistently not well imputed across ancestries. The extent to which array genotyping and imputation can approximate WGS therefore depends on reference panel, genotype array, sample ancestry, and genomic location. Imputation quality by variant or genomic region can be queried with our new tool, RsqBrowser, now deployed on the Michigan Imputation Server.

Published
2022
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8. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension

Author

Tanika N, Kelly, Xiao, Sun, Karen Y, He, Michael R, Brown, Sarah A Gagliano, Taliun, Jacklyn N, Hellwege, Marguerite R, Irvin, Xuenan, Mi, Jennifer A, Brody, Nora, Franceschini, Xiuqing, Guo, Shih-Jen, Hwang, Paul S, de Vries, Yan, Gao, Arden, Moscati, Girish N, Nadkarni, Lisa R, Yanek, Tali, Elfassy, Jennifer A, Smith, Ren-Hua, Chung, Amber L, Beitelshees, Amit, Patki, Stella, Aslibekyan, Brandon M, Blobner, Juan M, Peralta, Themistocles L, Assimes, Walter R, Palmas, Chunyu, Liu, Adam P, Bress, Zhijie, Huang, Lewis C, Becker, Chii-Min, Hwa, Jeffrey R, O'Connell, Jenna C, Carlson, Helen R, Warren, Sayantan, Das, Ayush, Giri, Lisa W, Martin, W, Craig Johnson, Ervin R, Fox, Erwin P, Bottinger, Alexander C, Razavi, Dhananjay, Vaidya, Lee-Ming, Chuang, Yen-Pei C, Chang, Take, Naseri, Deepti, Jain, Hyun Min, Kang, Adriana M, Hung, Vinodh, Srinivasasainagendra, Beverly M, Snively, Dongfeng, Gu, May E, Montasser, Muagututi'a Sefuiva, Reupena, Benjamin D, Heavner, Jonathon, LeFaive, James E, Hixson, Kenneth M, Rice, Fei Fei, Wang, Jonas B, Nielsen, Jianfeng, Huang, Alyna T, Khan, Wei, Zhou, Jovia L, Nierenberg, Cathy C, Laurie, Nicole D, Armstrong, Mengyao, Shi, Yang, Pan, Adrienne M, Stilp, Leslie, Emery, Quenna, Wong, Nicola L, Hawley, Ryan L, Minster, Joanne E, Curran, Patricia B, Munroe, Daniel E, Weeks, Kari E, North, Russell P, Tracy, Eimear E, Kenny, Daichi, Shimbo, Aravinda, Chakravarti, Stephen S, Rich, Alex P, Reiner, John, Blangero, Susan, Redline, Braxton D, Mitchell, Dabeeru C, Rao, Yii-Der, Ida Chen, Sharon L R, Kardia, Robert C, Kaplan, Rasika A, Mathias, Jiang, He, Bruce M, Psaty, Myriam, Fornage, Ruth J F, Loos, Adolfo, Correa, Eric, Boerwinkle, Jerome I, Rotter, Charles, Kooperberg, Todd L, Edwards, Gonçalo R, Abecasis, Xiaofeng, Zhu, Daniel, Levy, Donna K, Arnett, and Alanna C, Morrison

Subjects
Hypertension, Internal Medicine, Humans, Blood Pressure, Genomics, Precision Medicine, Polymorphism, Single Nucleotide, Genome-Wide Association Study
Abstract

Background: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. Methods: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. Results: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings ( P -8 ). Among them, a rare intergenic variant at novel locus, LOC100506274 , was associated with lower systolic blood pressure in stage-1 (beta [SE]=−32.6 [6.0]; P =4.99×10 -8 ) but not stage-2 analysis ( P =0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=−0.36 [0.07]; P =4.18×10 -7 ) and attained genome-wide significance in stage-2 (beta [SE]=−0.29 [0.03]; P =7.28×10 -23 ). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings ( P -6 and P -4 , respectively). Discussion: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.

Published
2023

9. Meta-imputation: An efficient method to combine genotype data after imputation with multiple reference panels

Author

Ketian, Yu, Sayantan, Das, Jonathon, LeFaive, Alan, Kwong, Jacob, Pleiness, Lukas, Forer, Sebastian, Schönherr, Christian, Fuchsberger, Albert Vernon, Smith, and Gonçalo Rocha, Abecasis

Subjects
Genome, Genotype, Research Design, Genetics, Humans, Polymorphism, Single Nucleotide, Article, Genetics (clinical), Genome-Wide Association Study
Abstract

Genotype imputation is an integral tool in genome-wide association studies, in which it facilitates meta-analysis, increases power, and enables fine-mapping. With the increasing availability of whole-genome-sequence datasets, investigators have access to a multitude of reference-panel choices for genotype imputation. In principle, combining all sequenced whole genomes into a single large panel would provide the best imputation performance, but this is often cumbersome or impossible due to privacy restrictions. Here, we describe meta-imputation, a method that allows imputation results generated using different reference panels to be combined into a consensus imputed dataset. Our meta-imputation method requires small changes to the output of existing imputation tools to produce necessary inputs, which are then combined using dynamically estimated weights that are tailored to each individual and genome segment. In the scenarios we examined, the method consistently outperforms imputation using a single reference panel and achieves accuracy comparable to imputation using a combined reference panel.

Published
2022
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10. Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease

Author

Daniel H. Katz, Usman A. Tahir, Alexander G. Bick, Akhil Pampana, Debby Ngo, Mark D. Benson, Zhi Yu, Jeremy M. Robbins, Zsu-Zsu Chen, Daniel E. Cruz, Shuliang Deng, Laurie Farrell, Sumita Sinha, Alec A. Schmaier, Dongxiao Shen, Yan Gao, Michael E. Hall, Adolfo Correa, Russell P. Tracy, Peter Durda, Kent D. Taylor, Yongmei Liu, W. Craig Johnson, Xiuqing Guo, Jie Yao, Yii-Der Ida Chen, Ani W. Manichaikul, Deepti Jain, Claude Bouchard, Mark A. Sarzynski, Stephen S. Rich, Jerome I. Rotter, Thomas J. Wang, James G. Wilson, Pradeep Natarajan, Robert E. Gerszten, Namiko Abe, Gonçalo Abecasis, Francois Aguet, Christine Albert, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Kristin Ardlie, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, Najib Ayas, Adithya Balasubramanian, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Lucas Barwick, Terri Beaty, Gerald Beck, Diane Becker, Lewis Becker, Rebecca Beer, Amber Beitelshees, Emelia Benjamin, Takis Benos, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Eric Boerwinkle, Donald W. Bowden, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Deborah Brown, Karen Bunting, Esteban Burchard, Carlos Bustamante, Erin Buth, Brian Cade, Jonathan Cardwell, Vincent Carey, Julie Carrier, April Carson, Cara Carty, Richard Casaburi, Juan P. Casas Romero, James Casella, Peter Castaldi, Mark Chaffin, Christy Chang, Yi-Cheng Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Michael Cho, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Ren-Hua Chung, Clary Clish, Suzy Comhair, Matthew Conomos, Elaine Cornell, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sean David, Colleen Davis, Michelle Daya, Mariza de Andrade, Lisa de las Fuentes, Paul de Vries, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Huyen Dinh, Harsha Doddapaneni, Qing Duan, Shannon Dugan-Perez, Ravi Duggirala, Jon Peter Durda, Susan K. Dutcher, Charles Eaton, Lynette Ekunwe, Adel El Boueiz, Patrick Ellinor, Leslie Emery, Serpil Erzurum, Charles Farber, Jesse Farek, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Chris Frazar, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Shanshan Gao, Margery Gass, Heather Geiger, Bruce Gelb, Mark Geraci, Soren Germer, Robert Gerszten, Auyon Ghosh, Richard Gibbs, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, Sharon Graw, Kathryn J. Gray, Daniel Grine, Colin Gross, C. Charles Gu, Yue Guan, Namrata Gupta, David M. Haas, Jeff Haessler, Michael Hall, Yi Han, Patrick Hanly, Daniel Harris, Nicola L. Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, Brian Hobbs, John Hokanson, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Jianhong Hu, Yi-Jen Hung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Cashell Jaquish, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Ziad Khan, Wonji Kim, John Kimoff, Greg Kinney, Barbara Konkle, Charles Kooperberg, Holly Kramer, Christoph Lange, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Jiwon Lee, Sandra Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Dan Levy, Joshua Lewis, Xiaohui Li, Yun Li, Henry Lin, Honghuang Lin, Xihong Lin, Simin Liu, Yu Liu, Ruth J.F. Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Ulysses Magalang, Michael Mahaney, Barry Make, Ani Manichaikul, Alisa Manning, JoAnn Manson, Lisa Martin, Melissa Marton, Susan Mathai, Rasika Mathias, Susanne May, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Daniel McGoldrick, Caitlin McHugh, Becky McNeil, Hao Mei, James Meigs, Vipin Menon, Luisa Mestroni, Ginger Metcalf, Deborah A. Meyers, Emmanuel Mignot, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton D. Mitchell, Matt Moll, Zeineen Momin, May E. Montasser, Courtney Montgomery, Donna Muzny, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Take Naseri, Sergei Nekhai, Sarah C. Nelson, Bonnie Neltner, Caitlin Nessner, Deborah Nickerson, Osuji Nkechinyere, Kari North, Jeff O’Connell, Tim O’Connor, Heather Ochs-Balcom, Geoffrey Okwuonu, Allan Pack, David T. Paik, Nicholette Palmer, James Pankow, George Papanicolaou, Cora Parker, Gina Peloso, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Jacob Pleiness, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Bruce Psaty, Pankaj Qasba, Dandi Qiao, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Mahitha Rajendran, Vasan S. Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Catherine Reeves, Elizabeth Regan, Alex Reiner, Muagututi’a Sefuiva Reupena, Ken Rice, Stephen Rich, Rebecca Robillard, Nicolas Robine, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Alexi Runnels, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Ester Cerdeira Sabino, Danish Saleheen, Shabnam Salimi, Sejal Salvi, Steven Salzberg, Kevin Sandow, Vijay G. Sankaran, Jireh Santibanez, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Frédéric Sériès, Vivien Sheehan, Stephanie L. Sherman, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Robert Skomro, Albert Vernon Smith, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Michael Snyder, Tamar Sofer, Nona Sotoodehnia, Adrienne M. Stilp, Garrett Storm, Elizabeth Streeten, Jessica Lasky Su, Yun Ju Sung, Jody Sylvia, Adam Szpiro, Daniel Taliun, Hua Tang, Margaret Taub, Matthew Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Machiko Threlkeld, Lesley Tinker, David Tirschwell, Sarah Tishkoff, Hemant Tiwari, Catherine Tong, Russell Tracy, Michael Tsai, Dhananjay Vaidya, David Van Den Berg, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Fei Fei Wang, Heming Wang, Jiongming Wang, Karol Watson, Jennifer Watt, Daniel E. Weeks, Joshua Weinstock, Bruce Weir, Scott T. Weiss, Lu-Chen Weng, Jennifer Wessel, Cristen Willer, Kayleen Williams, L. Keoki Williams, Carla Wilson, James Wilson, Lara Winterkorn, Quenna Wong, Joseph Wu, Huichun Xu, Lisa Yanek, Ivana Yang, Ketian Yu, Seyedeh Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiaofeng Zhu, Michael Zody, and Sebastian Zoellner

Subjects
Adult, Male, Proteomics, Aging, Whole genome sequence analysis, Proteome, Clinical Sciences, Black People, Disease, Computational biology, race and ethnicity, Cardiorespiratory Medicine and Haematology, Cardiovascular, Article, proteomics, cardiovascular disease, Physiology (medical), Genetics, 2.1 Biological and endogenous factors, Humans, Medicine, Aetiology, Lung, Heart Disease - Coronary Heart Disease, and Blood Institute TOPMed (Trans-Omics for Precision Medicine) Consortium†, business.industry, Prevention, Human Genome, National Heart, Genomics, Blood proteins, Genetic architecture, Heart Disease, Good Health and Well Being, Cardiovascular System & Hematology, Cardiovascular Diseases, Public Health and Health Services, Female, Cardiology and Cardiovascular Medicine, business, Biotechnology, Genome-Wide Association Study
Abstract

Background: Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants. Methods: Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics). Results: We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10 -11 . These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P =3.27×10 -30 ) and MMP-3 (β=-0.60±0.05, P =1.67×10 -32 ), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P =1.34×10 -17 ) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure. Conclusions: Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.

Published
2022
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11. The Phenotype-Genotype Reference Map: Improving biobank data science through replication

Author

Lisa Bastarache, Sarah Delozier, Anita Pandit, Jing He, Adam Lewis, Aubrey C Annis, Jonathon LeFaive, Joshua C. Denny, Robert J. Carroll, Jacob J. Hughey, Matthew Zawistowski, and Josh F. Peterson

Abstract

Population-scale biobanks linked to electronic health record data provide vast opportunity to extend our knowledge of human genetics. While biobanks have already proven their value to research, data quality remains an important concern. Here we introduce the phenotype-genotype reference map (PGRM), a set of 5,879 genetic associations from 523 GWAS publications that can be used for high-throughput replication experiments in biobank data. We tested the PGRM on five ancestry-specific cohorts drawn from four established, independent biobanks and found evidence of robust replications across a wide array of phenotypes. We defined simple replication measures and show how these can be applied to any EHR-linked biobank to detect data corruption and to empirically assess parameters for phenome-wide studies. Finally, we used the PGRM to determine factors associated with reproducibility of GWAS results.

Published
2022
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12. A statistical genetics guide to identifying HLA alleles driving complex disease

Author

Saori Sakaue, Saisriram Gurajala, Michelle Curtis, Yang Luo, Wanson Choi, Kazuyoshi Ishigaki, Joyce B. Kang, Laurie Rumker, Aaron J. Deutsch, Sebastian Schönherr, Lukas Forer, Jonathon LeFaive, Christian Fuchsberger, Buhm Han, Tobias L. Lenz, Paul I. W. de Bakker, Albert V. Smith, and Soumya Raychaudhuri

Abstract

The human leukocyte antigen (HLA) locus is associated with more human complex diseases than any other locus. In many diseases it explains more heritability than all other known loci combined. Investigators have now demonstrated the accuracy of in silico HLA imputation methods. These approaches enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and infectious diseases, such as HIV infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine-mapping. Here, we present comprehensive statistical genetics guide to impute HLA alleles from genotype data. We provide detailed protocols, including standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids including a web-based Michigan Imputation Server. We updated the HLA imputation reference panel representing global populations (African, East Asian, European and Latino) available at the Michigan Imputation Server (n = 20,349) and achived high imputation accuracy (mean dosage correlation r = 0.981). We finally offer best practice recommendations to conduct association tests in order to define the alleles, amino acids, and haplotypes affecting human traits. This protocol will be broadly applicable to the large-scale genotyping data and contribute to defining the role of HLA in human diseases across global populations.

Published
2022
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13. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Author

Nancy L. Heard-Costa, Lucas Barwick, Clary B. Clish, Celeste Eng, Joanne M. Murabito, Esteban G. Burchard, Yii-Der Ida Chen, Daniel I. Chasman, Robert C. Kaplan, James B. Meigs, Deborah A. Nickerson, Cashell E. Jaquish, Eric Boerwinkle, Jennifer A. Brody, Charles Kooperberg, Mark T. Gladwin, Sebastian Schoenherr, Keng-Han Lin, John Barnard, Ryan D. Hernandez, Andrew D. Johnson, Edwin K. Silverman, Mollie A. Minear, Michelle Daya, Barbara A. Konkle, Sharon R. Browning, Daniel E. Weeks, Wendy S. Post, Alexander P. Reiner, Kathryn L. Lunetta, Gina M. Peloso, David Van Den Berg, Dan E. Arking, Seung-been Lee, Leslie A. Lange, Cristen J. Willer, Zachary A. Szpiech, Tasha E. Fingerlin, Wayne E. Clarke, Xutong Zhao, Stephen S. Rich, Nora Franceschini, Sudha Seshadri, Chloé Sarnowski, Hyun Min Kang, Sayantan Das, Michael C. Zody, Stephanie M. Fullerton, Dean Bobo, Alanna C. Morrison, Brian Custer, Nona Sotoodehnia, Shannon Kelly, Thomas W. Blackwell, Bruce M. Psaty, Yingze Zhang, Susan R. Heckbert, Robert E. Gerszten, M. Benjamin Shoemaker, Daniel Taliun, Leslie S. Emery, André Corvelo, Michael H. Cho, Braxton D. Mitchell, Xiaoming Liu, Stella Aslibekyan, Paul L. Auer, Brandon Chalazan, Sarah C. Nelson, Seung Hoan Choi, Jeong-Sun Seo, Matthew P. Conomos, Anne-Katrin Emde, Lawrence F. Bielak, Alisa K. Manning, Allison E. Ashley-Koch, Diane Fatkin, Xiaowen Tian, Emelia J. Benjamin, D. C. Rao, Mina K. Chung, Myriam Fornage, Daniel Levy, Michael D. Kessler, Weihong Tang, Daniel J. Gottlieb, Pradeep Natarajan, Jessica Lasky-Su, Amol C. Shetty, Cathy C. Laurie, Dan M. Roden, Timothy D. O’Connor, Jedidiah Carlson, Lewis C. Becker, Achilleas N. Pitsillides, Karine A. Viaud-Martinez, Raul Torres, Adolfo Correa, Christian Fuchsberger, Deborah A. Meyers, Alvaro Alonso, Sanghamitra Mohanty, Jonathon LeFaive, Soren Germer, Julie L. Mikulla, François Aguet, Susan K. Dutcher, Sarah A Gagliano Taliun, Ani Manichaikul, Lori Garman, Xiuqing Guo, Timothy A. Thornton, David D. McManus, Albert V. Smith, Kristin G. Ardlie, Anna Köttgen, Sharon L.R. Kardia, Quenna Wong, Jill M. Johnsen, Andrea Natale, Richard A. Gibbs, Douglas P. Kiel, Ingo Ruczinski, Susan Redline, Lukas Forer, Scott I. Vrieze, May E. Montasser, Rasika A. Mathias, Jerome I. Rotter, Jacob Pleiness, Chunyu Liu, Brian L. Browning, James G. Wilson, Weiniu Gan, Christine M. Albert, Marilyn J. Telen, Courtney G. Montgomery, Steven A. Lubitz, Robert Klemmer, Ramachandran S. Vasan, Nathan Pankratz, Mariza de Andrade, Vivien A. Sheehan, Kenneth Rice, Xihong Lin, Eimear E. Kenny, Stephanie M. Gogarten, John Blangero, Donna K. Arnett, Jiang He, Pankaj Qasba, James F. Casella, Patrick T. Ellinor, Nicholette D. Palmer, R. Graham Barr, Scott T. Weiss, Joanne E. Curran, Bruce S. Weir, Kari E. North, L. Adrienne Cupples, Dawn L. DeMeo, Tanika N. Kelly, Angel C.Y. Mak, Russell P. Tracy, David A. Schwartz, Kent D. Taylor, Rebecca L. Beer, Daniel N. Harris, George J. Papanicolaou, Marguerite R. Irvin, Stephen T. McGarvey, Sebastian Zöllner, Patricia A. Peyser, Brian E. Cade, Ruth J. F. Loos, Douglas Loesch, Nicholas L. Smith, Gonçalo R. Abecasis, Jennifer A. Smith, Michael E. Hall, Lu-Chen Weng, Jeffrey R. O'Connell, Adrienne M. Stilp, Donald W. Bowden, Kathleen C. Barnes, Stacey Gabriel, Michael Boehnke, Wayne Huey-Herng Sheu, and Dawood Darbar

Subjects
Quality Control, Heterozygote, Genomics, Computational biology, Biology, Polymorphism, Single Nucleotide, Genome, Article, DNA sequencing, INDEL Mutation, Loss of Function Mutation, Genetics research, Genetic variation, Humans, Precision Medicine, Genetic association, Population Density, Multidisciplinary, Whole Genome Sequencing, Genome, Human, Genetic Variation, Rare variants, United States, Genetic architecture, Phenotype, Cytochrome P-450 CYP2D6, Haplotypes, Mutagenesis, Sample Size, Next-generation sequencing, National Heart, Lung, and Blood Institute (U.S.), Imputation (genetics), Reference genome
Abstract

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%., The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

Published
2021
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14. Scalable generalized linear mixed model for region-based association tests in large biobanks and cohorts

Author

Zhangchen Zhao, Lars G. Fritsche, Jonas B. Nielsen, Seunggeun Lee, Kristian Hveem, Wei Zhou, Wenjian Bi, Gonçalo R. Abecasis, Benjamin M. Neale, Cristen J. Willer, Sarah A Gagliano Taliun, Jonathon LeFaive, Maiken Elvestad Gabrielsen, and Mark J. Daly

Subjects
Genetic Markers, Multifactorial Inheritance, Sample (statistics), Biology, Population stratification, Article, Generalized linear mixed model, 03 medical and health sciences, 0302 clinical medicine, Statistics, Genetics, Humans, Exome, Biological Specimen Banks, 030304 developmental biology, Genetic association, 0303 health sciences, Models, Genetic, Norway, Waist-Hip Ratio, Linear model, Biobank, United Kingdom, Case-Control Studies, Scalability, Linear Models, Lipoproteins, HDL, 030217 neurology & neurosurgery, Type I and type II errors
Abstract

With very large sample sizes, biobanks provide an exciting opportunity to identify genetic components of complex traits. To analyze rare variants, region-based multiple-variant aggregate tests are commonly used to increase power for association tests. However, because of the substantial computational cost, existing region-based tests cannot analyze hundreds of thousands of samples while accounting for confounders such as population stratification and sample relatedness. Here we propose a scalable generalized mixed-model region-based association test, SAIGE-GENE, that is applicable to exome-wide and genome-wide region-based analysis for hundreds of thousands of samples and can account for unbalanced case–control ratios for binary traits. Through extensive simulation studies and analysis of the HUNT study with 69,716 Norwegian samples and the UK Biobank data with 408,910 White British samples, we show that SAIGE-GENE can efficiently analyze large-sample data (N > 400,000) with type I error rates well controlled. SAIGE-GENE is a scalable generalized mixed-model region-based association test that can analyze large datasets while accounting for sample relatedness and unbalanced case–control ratios for binary traits.

Published
2020
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15. Genome-wide association study of cardiac troponin i in the general population

Author

Ida Surakka, Magnus Nakrem Lyngbakken, Nay Aung, Jonathon LeFaive, Caroline Hayward, Ailin Falkmo Hansen, Wei Zhou, Paul Welsh, Sarah E. Graham, Jonas B. Nielsen, Sarah A Gagliano Taliun, Archie Campbell, Brooke N. Wolford, Patricia B. Munroe, David J. Porteous, Bjørn Olav Åsvold, Marta R Moksnes, Lars G. Fritsche, George Davey Smith, Cristen J. Willer, Torbjørn Omland, Humaira Rasheed, Nicholas J. Douville, Ben Michael Brumpton, Helge Røsjø, Kristian Hveem, Laurent F. Thomas, Anne Richmond, Naveed Sattar, and Steffen E. Petersen

Subjects
AcademicSubjects/SCI01140, medicine.medical_specialty, Heart disease, Population, Quantitative Trait Loci, Gene Expression, Genome-wide association study, macromolecular substances, 030204 cardiovascular system & hematology, Biology, 03 medical and health sciences, 0302 clinical medicine, Troponin T, Internal medicine, Mendelian randomization, Troponin I, Genetics, medicine, genetics, Myocardial infarction, cardiovascular diseases, education, Association Studies Article, genes, Molecular Biology, Genetics (clinical), Alleles, 030304 developmental biology, 0303 health sciences, education.field_of_study, genome-wide association study, cardiac troponin i, Chromosome Mapping, Genetic Variation, General Medicine, Mendelian Randomization Analysis, medicine.disease, musculoskeletal system, Genetics, Population, Organ Specificity, Heart failure, Cardiology, cardiovascular system, Biomarker (medicine), Biomarkers, Genome-Wide Association Study
Abstract

Circulating cardiac troponin proteins are associated with structural heart disease and predict incident cardiovascular disease in the general population. However, the genetic contribution to cardiac troponin I (cTnI) concentrations and its causal effect on cardiovascular phenotypes are unclear. We combine data from two large population-based studies, the Trøndelag Health Study and the Generation Scotland Scottish Family Health Study, and perform a genome-wide association study of high-sensitivity cTnI concentrations with 48 115 individuals. We further use two-sample Mendelian randomization to investigate the causal effects of circulating cTnI on acute myocardial infarction (AMI) and heart failure (HF). We identified 12 genetic loci (8 novel) associated with cTnI concentrations. Associated protein-altering variants highlighted putative functional genes: CAND2, HABP2, ANO5, APOH, FHOD3, TNFAIP2, KLKB1 and LMAN1. Phenome-wide association tests in 1688 phecodes and 83 continuous traits in UK Biobank showed associations between a genetic risk score for cTnI and cardiac arrhythmias, metabolic and anthropometric measures. Using two-sample Mendelian randomization, we confirmed the non-causal role of cTnI in AMI (5948 cases, 355 246 controls). We found indications for a causal role of cTnI in HF (47 309 cases and 930 014 controls), but this was not supported by secondary analyses using left ventricular mass as outcome (18 257 individuals). Our findings clarify the biology underlying the heritable contribution to circulating cTnI and support cTnI as a non-causal biomarker for AMI in the general population. Using genetically informed methods for causal inference helps inform the role and value of measuring cTnI in the general population.

Published
2021
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16. False discovery rates for genome-wide association tests in biobanks with thousands of phenotypes

Author

Sebastian Zöllner, Gonçalo R. Abecasis, Michael Boehnke, Matthew Zawistowski, Anita Pandit, Lars G. Fritsche, Peter VandeHaar, Jonathon LeFaive, Aubrey C. Annis, and Sarah A Gagliano Taliun

Subjects
Genome-wide association study, Computational biology, Biology, Phenotype, Biobank
Abstract

Biobanks housing genetic and phenotypic data for thousands of individuals introduce new opportunities and challenges for genetic association studies. Association testing across many phenotypes increases the multiple-testing burden and correlation between phenotypes makes appropriate multiple-testing correction uncertain. Moreover, analysis including low-frequency variants results in inflated type I error due to the much larger number of tests and the elevated importance of each individual minor allele carrier in those tests. Here we demonstrate that standard Bonferroni and permutation-based methods for multiple testing correction are inadequate for a holistic analysis of biobank data because ideal significance thresholds vary across datasets and minor allele frequencies. We propose a single-iteration permutation method that is computationally feasible and provides false discovery rate (FDR) estimates tailored to individual datasets and variant frequencies. Each dataset’s unique FDR estimates provide customized levels of confidence for association results and enable informed interpretation of genetic association studies across the phenome.

Published
2021
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17. Whole Genome Sequencing Identifies CRISPLD2 as a Lung Function Gene in Children With Asthma

Author

Priyadarshini Kachroo, Julian Hecker, Bo L. Chawes, Tarunveer S. Ahluwalia, Michael H. Cho, Dandi Qiao, Rachel S. Kelly, Su H. Chu, Yamini V. Virkud, Mengna Huang, Kathleen C. Barnes, Esteban G. Burchard, Celeste Eng, Donglei Hu, Juan C. Celedón, Michelle Daya, Albert M. Levin, Hongsheng Gui, L. Keoki Williams, Erick Forno, Angel C.Y. Mak, Lydiana Avila, Manuel E. Soto-Quiros, Michelle M. Cloutier, Edna Acosta-Pérez, Glorisa Canino, Klaus Bønnelykke, Hans Bisgaard, Benjamin A. Raby, Christoph Lange, Scott T. Weiss, Jessica A. Lasky-Su, Namiko Abe, Goncalo Abecasis, Christine Albert, Nicholette (Nichole) Palmer Allred, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Terri Beaty, Diane Becker, Lewis Becker, Rebecca Beer, Ferdouse Begum, Amber Beitelshees, Emelia Benjamin, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Eric Boerwinkle, Ingrid Borecki, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Karen Bunting, Esteban Burchard, Jonathan Cardwell, Cara Carty, Richard Casaburi, James Casella, Mark Chaffin, Christy Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Yii-Der Ida Chen, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Elaine Cornell, Adolfo Correa, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sayantan Das, Sean David, Colleen Davis, Mariza de Andrade, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Ron Do, Qing Duan, Ravi Duggirala, Peter Durda, Susan Dutcher, Charles Eaton, Lynette Ekunwe, Patrick Ellinor, Leslie Emery, Charles Farber, Leanna Farnam, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Yan Gao, Margery Gass, Bruce Gelb, Xiaoqi (Priscilla) Geng, Soren Germer, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, C. Charles Gu, Yue Guan, Xiuqing Guo, Jeff Haessler, Michael Hall, Daniel Harris, Nicola Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, John Hokanson, Kramer Holly, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Deepti Jain, Cashell Jaquish, Min A. Jhun, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Sekar Kathiresan, Laura Kaufman, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Greg Kinney, Barbara Konkle, Charles Kooperberg, Stephanie Krauter, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Seunggeun Shawn Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Dan Levy, Joshua Lewis, Yun Li, Honghuang Lin, Keng Han Lin, Simin Liu, Yongmei Liu, Ruth Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Michael Mahaney, Barry Make, Ani Manichaikul, JoAnn Manson, Lauren Margolin, Lisa Martin, Susan Mathai, Rasika Mathias, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Hao Mei, Deborah A. Meyers, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton Mitchell, May E. Montasser, Solomon Musani, Stanford Mwasongwe, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Pradeep Natarajan, Sergei Nekhai, Deborah Nickerson, Kari North, Jeff O'Connell, Tim O'Connor, Heather Ochs-Balcom, James Pankow, George Papanicolaou, Margaret Parker, Afshin Parsa, Sara Penchev, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Sam Phillips, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Dmitry Prokopenko, Bruce Psaty, Pankaj Qasba, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Vasan Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Elizabeth Regan, Alex Reiner, Ken Rice, Stephen Rich, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Phuwanat Sakornsakolpat, Shabnam Salimi, Steven Salzberg, Kevin Sandow, Vijay Sankaran, Christopher Scheller, Ellen Schmidt, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Vivien Sheehan, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Tamar Sofer, Nona Sotoodehnia, Adrienne Stilp, Elizabeth Streeten, Yun Ju Sung, Jessica Su-Lasky, Jody Sylvia, Adam Szpiro, Carole Sztalryd, Daniel Taliun, Hua Tang, Margaret Taub, Kent Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Lesley Tinker, David Tirschwell, Hemant Tiwari, Russell Tracy, Michael Tsai, Dhananjay Vaidya, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Emily Wan, Fei Fei Wang, Karol Watson, Daniel E. Weeks, Bruce Weir, Scott Weiss, Lu-Chen Weng, Cristen Willer, Kayleen Williams, Carla Wilson, James Wilson, Quenna Wong, Huichun Xu, Lisa Yanek, Ivana Yang, Rongze Yang, Norann Zaghloul, Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiuwen Zheng, Degui Zhi, Xiang Zhou, Michael Zody, and Sebastian Zoellner

Subjects
Adult, Costa Rica, Male, Pulmonary and Respiratory Medicine, Adolescent, Vital Capacity, Single-nucleotide polymorphism, Pedigree chart, Critical Care and Intensive Care Medicine, Young Adult, 03 medical and health sciences, FEV1/FVC ratio, 0302 clinical medicine, Polymorphism (computer science), Forced Expiratory Volume, Humans, Medicine, SNP, 030212 general & internal medicine, Child, Asthma, Whole Genome Sequencing, business.industry, Middle Aged, respiratory system, medicine.disease, respiratory tract diseases, Minor allele frequency, 030228 respiratory system, Genetic epidemiology, Child, Preschool, Interferon Regulatory Factors, Immunology, Respiratory Physiological Phenomena, Female, Cardiology and Cardiovascular Medicine, business, Cell Adhesion Molecules
Abstract

BACKGROUND: Asthma is a common respiratory disorder with a highly heterogeneous nature that remains poorly understood. The objective was to use whole genome sequencing (WGS) data to identify regions of common genetic variation contributing to lung function in individuals with a diagnosis of asthma. METHODS: WGS data were generated for 1,053 individuals from trios and extended pedigrees participating in the family-based Genetic Epidemiology of Asthma in Costa Rica study. Asthma affection status was defined through a physician’s diagnosis of asthma, and most participants with asthma also had airway hyperresponsiveness (AHR) to methacholine. Family-based association tests for single variants were performed to assess the associations with lung function phenotypes. RESULTS: A genome-wide significant association was identified between baseline FEV(1)/FVC ratio and a single-nucleotide polymorphism in the top hit cysteine-rich secretory protein LCCL domain-containing 2 (CRISPLD2) (rs12051168; P = 3.6 × 10(−8) in the unadjusted model) that retained suggestive significance in the covariate-adjusted model (P = 5.6 × 10(−6)). Rs12051168 was also nominally associated with other related phenotypes: baseline FEV(1) (P = 3.3 × 10(−3)), postbronchodilator (PB) FEV(1) (7.3 × 10(−3)), and PB FEV(1)/FVC ratio (P = 2.7 × 10(−3)). The identified baseline FEV(1)/FVC ratio and rs12051168 association was meta-analyzed and replicated in three independent cohorts in which most participants with asthma also had confirmed AHR (combined weighted z-score P = .015) but not in cohorts without information about AHR. CONCLUSIONS: These findings suggest that using specific asthma characteristics, such as AHR, can help identify more genetically homogeneous asthma subgroups with genotype-phenotype associations that may not be observed in all children with asthma. CRISPLD2 also may be important for baseline lung function in individuals with asthma who also may have AHR.

Published
2019
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18. Sparse allele vectors and the savvy software suite

Author

Albert V. Smith, Jonathon LeFaive, Hyun Min Kang, and Gonçalo R. Abecasis

Subjects
Statistics and Probability, 0303 health sciences, Software suite, Command-line interface, Computer science, Serialization, 030302 biochemistry & molecular biology, File format, computer.software_genre, Biochemistry, Applications Notes, Computer Science Applications, 03 medical and health sciences, Computational Mathematics, Computational Theory and Mathematics, Operating system, Analysis software, Molecular Biology, Throughput (business), computer, Computer memory, 030304 developmental biology, Complement (set theory)
Abstract

Summary The sparse allele vectors file format is an efficient storage format for large-scale DNA variation data and is designed for high throughput association analysis by leveraging techniques for fast deserialization of data into computer memory. A command line interface has been developed to complement the storage format and supports basic features like importing, exporting and subsetting. Additionally, a C++ programming API is available allowing for easy integration into analysis software. Availability and implementation https://github.com/statgen/savvy. Supplementary information Supplementary data are available at Bioinformatics online.

Published
2021

19. Robust, flexible, and scalable tests for Hardy–Weinberg equilibrium across diverse ancestries

Author

Nicholas L. Smith, Alan M. Kwong, Gonçalo R. Abecasis, Jennifer A. Smith, Celeste Eng, Charles Kooperberg, John Barnard, L. Adrienne Cupples, Ani Manichaikul, Wonji Kim, Dan M. Roden, Nicholette D. Palmer, M. Benjamin Shoemaker, Eric Boerwinkle, Michael Boehnke, John Blangero, Marguerite R. Irvin, Hemant K. Tiwari, Albert V. Smith, Alexander P. Reiner, Daniel E. Weeks, Tanika N. Kelly, Mariza de Andrade, Steven A. Lubitz, Laura J. Scott, Kathleen C. Barnes, Esteban G. Burchard, Han Chen, Scott T. Weiss, May E. Montasser, Yan Gao, Angel C.Y. Mak, Brian E. Cade, Thomas W. Blackwell, Courtney G. Montgomery, Solomon K. Musani, Xiuqing Guo, Daniel I. Chasman, Gina M. Peloso, Jessica Su, Hyun Min Kang, Dandi Qiao, Matthew P. Conomos, Patrick T. Ellinor, Jonathon LeFaive, and Rasika A. Mathias

Subjects
Genotype, Population structure, Biology, Linkage Disequilibrium, Statistical power, 03 medical and health sciences, 0302 clinical medicine, Gene Frequency, Statistics, Genetics, False positive paradox, Humans, Alleles, 030304 developmental biology, Investigation, 0303 health sciences, Models, Statistical, Models, Genetic, Hardy–Weinberg principle, Exact test, Genetics, Population, Phenotype, Data quality, Metric (mathematics), Scalability, Software, 030217 neurology & neurosurgery
Abstract

Traditional Hardy–Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.

Published
2021
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20. SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Author

Matteo D’Antonio, Jennifer P. Nguyen, Timothy D. Arthur, Hiroko Matsui, Agnieszka D’Antonio-Chronowska, Kelly A. Frazer, Benjamin M. Neale, Mark Daly, Andrea Ganna, Christine Stevens, Gita A. Pathak, Shea J. Andrews, Masahiro Kanai, Mattia Cordioli, Juha Karjalainen, Renato Polimanti, Matti Pirinen, Nadia Harerimana, Kumar Veerapen, Brooke Wolford, Huy Nguyen, Matthew Solomonson, Rachel G. Liao, Karolina Chwialkowska, Amy Trankiem, Mary K. Balaconis, Caroline Hayward, Anne Richmond, Archie Campbell, Marcela Morris, Chloe Fawns-Ritchie, Joseph T. Glessner, Douglas M. Shaw, Xiao Chang, Hannah Polikowski, Petty E. Lauren, Hung-Hsin Chen, Zhu Wanying, Hakon Hakonarson, David J. Porteous, Jennifer Below, Kari North, Joseph B. McCormick, Paul R.H.J. Timmers, James F. Wilson, Albert Tenesa, Kenton D’Mellow, Shona M. Kerr, Mari E.K. Niemi, Lindokuhle Nkambul, Kathrin Aprile von Hohenstaufen, Ali Sobh, Madonna M. Eltoukhy, Amr M. Yassen, Mohamed A.F. Hegazy, Kamal Okasha, Mohammed A. Eid, Hanteera S. Moahmed, Doaa Shahin, Yasser M. El-Sherbiny, Tamer A. Elhadidy, Mohamed S. Abd Elghafar, Jehan J. El-Jawhari, Attia A.S. Mohamed, Marwa H. Elnagdy, Amr Samir, Mahmoud Abdel-Aziz, Walid T. Khafaga, Walaa M. El-Lawaty, Mohamed S. Torky, Mohamed R. El-shanshory, Chiara Batini, Paul H. Lee, Nick Shrine, Alexander T. Williams, Martin D. Tobin, Anna L. Guyatt, Catherine John, Richard J. Packer, Altaf Ali, Robert C. Free, Xueyang Wang, Louise V. Wain, Edward J. Hollox, Laura D. Venn, Catherine E. Bee, Emma L. Adams, Ahmadreza Niavarani, Bahareh Sharififard, Rasoul Aliannejad, Ali Amirsavadkouhi, Zeinab Naderpour, Hengameh Ansari Tadi, Afshar Etemadi Aleagha, Saeideh Ahmadi, Seyed Behrooz Mohseni Moghaddam, Alireza Adamsara, Morteza Saeedi, Hamed Abdollahi, Abdolmajid Hosseini, Pajaree Chariyavilaskul, Monpat Chamnanphon, Thitima B. Suttichet, Vorasuk Shotelersuk, Monnat Pongpanich, Chureerat Phokaew, Wanna Chetruengchai, Watsamon Jantarabenjakul, Opass Putchareon, Pattama Torvorapanit, Thanyawee Puthanakit, Pintip Suchartlikitwong, Nattiya Hirankarn, Voraphoj Nilaratanakul, Pimpayao Sodsai, Ben M. Brumpton, Kristian Hveem, Cristen Willer, Wei Zhou, Tormod Rogne, Erik Solligard, Bjørn Olav Åsvold, Malak Abedalthagafi, Manal Alaamery, Saleh Alqahtani, Dona Baraka, Fawz Al Harthi, Ebtehal Alsolm, Leen Abu Safieh, Albandary M. Alowayn, Fatimah Alqubaishi, Amal Al Mutairi, Serghei Mangul, Abdulraheem Alshareef, Mona Sawaji, Mansour Almutairi, Nora Aljawini, Nour Albesher, Yaseen M. Arabi, Ebrahim S. Mahmoud, Amin K. Khattab, Roaa T. Halawani, Ziab Z. Alahmadey, Jehad K. Albakri, Walaa A. Felemban, Bandar A. Suliman, Rana Hasanato, Laila Al-Awdah, Jahad Alghamdi, Deema AlZahrani, Sameera AlJohani, Hani Al-Afghani, May Alrashed, Nouf AlDhawi, Hadeel AlBardis, Sarah Alkwai, Moneera Alswailm, Faisal Almalki, Maha Albeladi, Iman Almohammed, Eman Barhoush, Anoud Albader, Salam Massadeh, Abdulaziz AlMalik, Sara Alotaibi, Bader Alghamdi, Junghyun Jung, Mohammad S. Fawzy, Yunsung Lee, Per Magnus, Lill-Iren S. Trogstad, Øyvind Helgeland, Jennifer R. Harris, Massimo Mangino, Tim D. Spector, Duncan Emma, Sandra P. Smieszek, Bartlomiej P. Przychodzen, Christos Polymeropoulos, Vasilios Polymeropoulos, Mihael H. Polymeropoulos, Israel Fernandez-Cadenas, Jordi Perez-Tur, Laia Llucià-Carol, Natalia Cullell, Elena Muiño, Jara Cárcel-Márquez, Marta L. DeDiego, Lara Lloret Iglesias, Anna M. Planas, Alex Soriano, Veronica Rico, Daiana Agüero, Josep L. Bedini, Francisco Lozano, Carlos Domingo, Veronica Robles, Francisca Ruiz-Jaén, Leonardo Márquez, Juan Gomez, Eliecer Coto, Guillermo M. Albaiceta, Marta García-Clemente, David Dalmau, Maria J. Arranz, Beatriz Dietl, Alex Serra-Llovich, Pere Soler, Roger Colobrán, Andrea Martín-Nalda, Alba Parra Martínez, David Bernardo, Silvia Rojo, Aida Fiz-López, Elisa Arribas, Paloma de la Cal-Sabater, Tomás Segura, Esther González-Villa, Gemma Serrano-Heras, Joan Martí-Fàbregas, Elena Jiménez-Xarrié, Alicia de Felipe Mimbrera, Jaime Masjuan, Sebastian García-Madrona, Anna Domínguez-Mayoral, Joan Montaner Villalonga, Paloma Menéndez-Valladares, Daniel I. Chasman, Julie E. Buring, Paul M. Ridker, Giulianini Franco, Howard D. Sesso, JoAnn E. Manson, Joseph R. Glessner, Carolina Medina-Gomez, Andre G. Uitterlinden, M. Arfan Ikram, Kati Kristiansson, Sami Koskelainen, Markus Perola, Kati Donner, Katja Kivinen, Aarno Palotie, Samuli Ripatti, Sanni Ruotsalainen, Mari Kaunisto, null FinnGen, Tomoko Nakanishi, Guillaume Butler-Laporte, Vincenzo Forgetta, David R. Morrison, Biswarup Ghosh, Laetitia Laurent, Alexandre Belisle, Danielle Henry, Tala Abdullah, Olumide Adeleye, Noor Mamlouk, Nofar Kimchi, Zaman Afrasiabi, Nardin Rezk Branka Vulesevic, Meriem Bouab, Charlotte Guzman, Louis Petitjean, Chris Tselios, Xiaoqing Xue, Erwin Schurr, Jonathan Afilalo, Marc Afilalo, Maureen Oliveira, Bluma Brenner, Pierre Lepage, Jiannis Ragoussis, Daniel Auld, Nathalie Brassard, Madeleine Durand, Michaël Chassé, Daniel E. Kaufmann, G. Mark Lathrop, Vincent Mooser, J. Brent Richards, Rui Li, Darin Adra, Souad Rahmouni, Michel Georges, Michel Moutschen, Benoit Misset, Gilles Darcis, Julien Guiot, Julien Guntz, Samira Azarzar, Stéphanie Gofflot, Yves Beguin, Sabine Claassen, Olivier Malaise, Pascale Huynen, Christelle Meuris, Marie Thys, Jessica Jacques, Philippe Léonard, Frederic Frippiat, Jean-Baptiste Giot, Anne-Sophie Sauvage, Christian Von Frenckell, Yasmine Belhaj, Bernard Lambermont, Sara Pigazzini, Lindokuhle Nkambule, Michelle Daya, Jonathan Shortt, Nicholas Rafaels, Stephen J. Wicks, Kristy Crooks, Kathleen C. Barnes, Christopher R. Gignoux, Sameer Chavan, Triin Laisk, Kristi Läll, Maarja Lepamets, Reedik Mägi, Tõnu Esko, Ene Reimann, Lili Milani, Helene Alavere, Kristjan Metsalu, Mairo Puusepp, Andres Metspalu, Paul Naaber, Edward Laane, Jaana Pesukova, Pärt Peterson, Kai Kisand, Jekaterina Tabri, Raili Allos, Kati Hensen, Joel Starkopf, Inge Ringmets, Anu Tamm, Anne Kallaste, Pierre-Yves Bochud, Carlo Rivolta, Stéphanie Bibert, Mathieu Quinodoz, Dhryata Kamdar, Noémie Boillat, Semira Gonseth Nussle, Werner Albrich, Noémie Suh, Dionysios Neofytos, Véronique Erard, Cathy Voide, null FHoGID, null RegCOVID, null P-PredictUs, null SeroCOVID, null CRiPSI, Rafael de Cid, Iván Galván-Femenía, Natalia Blay, Anna Carreras, Beatriz Cortés, Xavier Farré, Lauro Sumoy, Victor Moreno, Josep Maria Mercader, Marta Guindo-Martinez, David Torrents, Manolis Kogevinas, Judith Garcia-Aymerich, Gemma Castaño-Vinyals, Carlota Dobaño, Alessandra Renieri, Francesca Mari, Chiara Fallerini, Sergio Daga, Elisa Benetti, Margherita Baldassarri, Francesca Fava, Elisa Frullanti, Floriana Valentino, Gabriella Doddato, Annarita Giliberti, Rossella Tita, Sara Amitrano, Mirella Bruttini, Susanna Croci, Ilaria Meloni, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Giada Beligni, Andrea Tommasi, Laura Di Sarno, Maria Palmieri, Miriam Lucia Carriero, Diana Alaverdian, Stefano Busani, Raffaele Bruno, Marco Vecchia, Mary Ann Belli, Nicola Picchiotti, Maurizio Sanarico, Marco Gori, Simone Furini, Stefania Mantovani, Serena Ludovisi, Mario Umberto Mondelli, Francesco Castelli, Eugenia Quiros-Roldan, Melania Degli Antoni, Isabella Zanella, Massimo Vaghi, Stefano Rusconi, Matteo Siano, Francesca Montagnani, Arianna Emiliozzi, Massimiliano Fabbiani, Barbara Rossetti, Elena Bargagli, Laura Bergantini, Miriana D’Alessandro, Paolo Cameli, David Bennett, Federico Anedda, Simona Marcantonio, Sabino Scolletta, Federico Franchi, Maria Antonietta Mazzei, Susanna Guerrini, Edoardo Conticini, Luca Cantarini, Bruno Frediani, Danilo Tacconi, Chiara Spertilli, Marco Feri, Alice Donati, Raffaele Scala, Luca Guidelli, Genni Spargi, Marta Corridi, Cesira Nencioni, Leonardo Croci, Maria Bandini, Gian Piero Caldarelli, Paolo Piacentini, Elena Desanctis, Silvia Cappelli, Anna Canaccini, Agnese Verzuri, Valentina Anemoli, Agostino Ognibene, Alessandro Pancrazzi, Maria Lorubbio, Antonella D’Arminio Monforte, Federica Gaia Miraglia, Massimo Girardis, Sophie Venturelli, Andrea Cossarizza, Andrea Antinori, Alessandra Vergori, Arianna Gabrieli, Agostino Riva, Daniela Francisci, Elisabetta Schiaroli, Francesco Paciosi, Pier Giorgio Scotton, Francesca Andretta, Sandro Panese, Renzo Scaggiante, Francesca Gatti, Saverio Giuseppe Parisi, Stefano Baratti, Matteo Della Monica, Carmelo Piscopo, Mario Capasso, Roberta Russo, Immacolata Andolfo, Achille Iolascon, Giuseppe Fiorentino, Massimo Carella, Marco Castori, Giuseppe Merla, Gabriella Maria Squeo, Filippo Aucella, Pamela Raggi, Carmen Marciano, Rita Perna, Matteo Bassetti, Antonio Di Biagio, Maurizio Sanguinetti, Luca Masucci, Serafina Valente, Marco Mandalà, Alessia Giorli, Lorenzo Salerni, Patrizia Zucchi, Pierpaolo Parravicini, Elisabetta Menatti, Tullio Trotta, Ferdinando Giannattasio, Gabriella Coiro, Fabio Lena, Domenico A. Coviello, Cristina Mussini, Enrico Martinelli, Sandro Mancarella, Luisa Tavecchia, Lia Crotti, Chiara Gabbi, Marco Rizzi, Franco Maggiolo, Diego Ripamonti, Tiziana Bachetti, Maria Teresa La Rovere, Simona Sarzi-Braga, Maurizio Bussotti, Stefano Ceri, Pietro Pinoli, Francesco Raimondi, Filippo Biscarini, Alessandra Stella, Kristina Zguro, Katia Capitani, Claudia Suardi, Simona Dei, Gianfranco Parati, Sabrina Ravaglia, Rosangela Artuso, Giordano Bottà, Paolo Di Domenico, Ilaria Rancan, Antonio Perrella Francesco Bianchi, Davide Romani, Paola Bergomi, Emanuele Catena, Riccardo Colombo, Marco Tanfoni, Antonella Vincenti, Claudio Ferri, Davide Grassi, Gloria Pessina, Mario Tumbarello, Massimo Di Pietro, Ravaglia Sabrina, Sauro Luchi, Chiara Barbieri, Donatella Acquilini, Elena Andreucci, Francesco Vladimiro Segala, Giusy Tiseo, Marco Falcone, Mirjam Lista, Monica Poscente, Oreste De Vivo, Paola Petrocelli, Alessandra Guarnaccia, Silvia Baroni, Albert V. Smith, Andrew P. Boughton, Kevin W. Li, Jonathon LeFaive, Aubrey Annis, Anne E. Justice, Tooraj Mirshahi, Geetha Chittoor, Navya Shilpa Josyula, Jack A. Kosmicki, Manuel A.R. Ferreira, Joseph B. Leader, Dave J. Carey, Matthew C. Gass, Julie E. Horowitz, Michael N. Cantor, Ashish Yadav, Aris Baras, Goncalo R. Abecasis, David A. van Heel, Karen A. Hunt, Dan Mason, Qin Qin Huang, Sarah Finer, null Genes & Health Research Team, Bhavi Trivedi, Christopher J. Griffiths, Hilary C. Martin, John Wright, Richard C. Trembath, Nicole Soranzo, Jing Hua Zhao, Adam S. Butterworth, John Danesh, Emanuele Di Angelantonio, Lude Franke Marike Boezen, Patrick Deelen, Annique Claringbould, Esteban Lopera, Robert Warmerdam, Judith.M. Vonk, Irene van Blokland, Pauline Lanting, Anil P.S. Ori, Brooke Wolford Sebastian Zöllner, Jiongming Wang, Andrew Beck, Gina Peloso, Yuk-Lam Ho, Yan V. Sun, Jennifer E. Huffman, Christopher J. O’Donnell, Kelly Cho, Phil Tsao, J. Michael Gaziano, Michel (M.G.) Nivard, Eco (E.J.C.) de geus, Meike Bartels, Jouke Jan Hottenga, Scott T. Weiss, Elizabeth W. Karlson, Jordan W. Smoller, Robert C. Green, Yen-Chen Anne Feng, Josep Mercader, Shawn N. Murphy, James B. Meigs, Ann E. Woolley, Emma F. Perez, Daniel Rader, Anurag Verma, Marylyn D. Ritchie, Binglan Li, Shefali S. Verma, Anastasia Lucas, Yuki Bradford, Hugo Zeberg, Robert Frithiof, Michael Hultström, Miklos Lipcsey, Lindo Nkambul, Nicolas Tardif, Olav Rooyackers, Jonathan Grip, Tomislav Maricic, Konrad J. Karczewski, Elizabeth G. Atkinson, Kristin Tsuo, Nikolas Baya, Patrick Turley, Rahul Gupta, Shawneequa Callier, Raymond K. Walters, Duncan S. Palmer, Gopal Sarma, Nathan Cheng, Wenhan Lu, Sam Bryant, Claire Churchhouse, Caroline Cusick, Jacqueline I. Goldstein, Daniel King, Cotton Seed, Hilary Finucane, Alicia R. Martin, F. Kyle Satterstrom, Daniel J. Wilson, Jacob Armstrong, Justine K. Rudkin, Gavin Band, Sarah G. Earle, Shang-Kuan Lin, Nicolas Arning, Derrick W. Crook, David H. Wyllie, Anne Marie O’Connell, Chris C.A. Spencer, Nils Koelling, Mark J. Caulfield, Richard H. Scott, Tom Fowler, Loukas Moutsianas, Athanasios Kousathanas, Dorota Pasko, Susan Walker, Augusto Rendon, Alex Stuckey, Christopher A. Odhams, Daniel Rhodes, Georgia Chan, Prabhu Arumugam, Catherine A. Ball, Eurie L. Hong, Kristin Rand, Ahna Girshick, Harendra Guturu, Asher Haug Baltzell, Genevieve Roberts, Danny Park, Marie Coignet, Shannon McCurdy, Spencer Knight, Raghavendran Partha, Brooke Rhead, Miao Zhang, Nathan Berkowitz, Michael Gaddis, Keith Noto, Luong Ruiz, Milos Pavlovic, Laura G. Sloofman, Alexander W. Charney, Noam D. Beckmann, Eric E. Schadt, Daniel M. Jordan, Ryan C. Thompson, Kyle Gettler, Noura S. Abul-Husn, Steven Ascolillo, Joseph D. Buxbaum, Kumardeep Chaudhary, Judy H. Cho, Yuval Itan, Eimear E. Kenny, Gillian M. Belbin, Stuart C. Sealfon, Robert P. Sebra, Irene Salib, Brett L. Collins, Tess Levy, Bari Britvan, Katherine Keller, Lara Tang, Michael Peruggia, Liam L. Hiester, Kristi Niblo, Alexandra Aksentijevich, Alexander Labkowsky, Avromie Karp, Menachem Zlatopolsky, Michael Preuss, Ruth J.F. Loos, Girish N. Nadkarni, Ron Do, Clive Hoggart, Sam Choi, Slayton J. Underwood, Paul O’Reilly, Laura M. Huckins, Marissa Zyndorf, AII - Infectious diseases, Amsterdam Neuroscience - Neuroinfection & -inflammation, and Neurology

Subjects
Medical Physiology, Gene Expression, Genome-wide association study, Genome, Severity of Illness Index, colocalization, Gene expression, Databases, Genetic, Ethnicity, 2.1 Biological and endogenous factors, GWAS, Aetiology, Biology (General), Lung, Genetics, Chromosome Mapping, Single Nucleotide, Organ Specificity, Biotechnology, Cell type, QH301-705.5, Quantitative Trait Loci, Single-nucleotide polymorphism, Biology, eQTL, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, Databases, Genetic, SNP, Humans, Genetic Predisposition to Disease, COVID-19 Host Genetics Initiative, Polymorphism, Gene, COVID-19, SARS-CoV-2, Gene Expression Profiling, Prevention, Human Genome, Computational Biology, Genetic Variation, Good Health and Well Being, Expression quantitative trait loci, Biochemistry and Cell Biology, Transcriptome, Genome-Wide Association Study
Abstract

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types., Graphical abstract, D’Antonio et al. characterize associations between GWAS signals for COVID-19 disease and eQTLs in 69 human tissues to identify causal variants and their underlying molecular mechanisms. They show that diverse symptoms and disease severity of COVID-19 are associated with variants affecting gene expression in a wide variety of tissues.

Published
2022
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21. Using human genetics to understand the causes and consequences of circulating cardiac troponin I in the general population

Author

Anne Richmond, David J. Porteous, Torbjørn Omland, Brooke N. Wolford, Humaira Rasheed, Wei Zhou, Ailin Falkmo Hansen, Sarah A Gagliano Taliun, Lars G. Fritsche, Archie Campbell, Ben Michael Brumpton, Laurent F. Thomas, Jonathon LeFaive, George Davey Smith, Marta R Moksnes, Magnus Nakrem Lyngbakken, Ida Surakka, Sarah E. Graham, Naveed Sattar, Helge Røsjø, Caroline Hayward, Paul Welsh, Bjørn Olav Åsvold, Cristen J. Willer, Jonas B. Nielsen, Nicholas J. Douville, and Kristian Hveem

Subjects
education.field_of_study, medicine.medical_specialty, Heart disease, business.industry, Population, macromolecular substances, Disease, musculoskeletal system, medicine.disease, Internal medicine, Heart failure, Troponin I, Mendelian randomization, cardiovascular system, Cardiology, Medicine, Biomarker (medicine), cardiovascular diseases, Myocardial infarction, business, education
Abstract

Circulating cardiac troponin proteins are associated with structural heart disease and predict incident cardiovascular disease in the general population. However, the genetic contribution to cardiac troponin I (cTnI) concentrations and its causal effect on cardiovascular phenotypes is unclear. We combine data from two large population-based studies, the Trondelag Health Study and the Generation Scotland Scottish Family Health Study and perform a genome-wide association study of high-sensitivity cTnI concentrations with 48 115 individuals. We further used two-sample Mendelian randomization to investigate the causal effects of circulating cTnI on acute myocardial infarction and heart failure. We identified 12 genetic loci (8 novel) associated with cTnI concentrations. Associated protein-altering variants highlighted putative functional genes: CAND2, HABP2, ANO5, APOH, FHOD3, TNFAIP2, KLKB1 and LMAN1. Phenome-wide association tests in 1283 phecodes and 274 continuous traits in UK Biobank showed associations between a polygenic risk score for cTnI and cardiac arrhythmias, aspartate aminotransferase 1 and anthropometric measures. Excluding individuals with a known history of comorbidities did not materially change associations with cTnI. Using two-sample Mendelian randomization we confirmed the non-causal role of cTnI in acute myocardial infarction (5 948 cases, 355 246 controls). We found some indications for a causal role of cTnI in heart failure (47 309 cases and 930 014 controls), but this was not supported by secondary analyses using left ventricular mass as outcome (18 257 individuals). Our findings clarify the biology underlying the heritable contribution to circulating cTnI and support cTnI as a non-causal biomarker for acute myocardial infarction and heart failure development in the general population. Using genetically informed methods for causal inference of cTnI helps inform the role and value of measuring cTnI in the general population.

Published
2020
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22. Robust, flexible, and scalable tests for Hardy-Weinberg Equilibrium across diverse ancestries

Author

Daniel E. Weeks, Matthew P. Conomos, Tanika N. Kelly, John Barnard, Celeste Eng, Daniel I. Chasman, Gina M. Peloso, L. Adrienne Cupples, Hyun Min Kang, Dan M. Roden, Angel C.Y. Mak, Yan Gao, Xiuqing Guo, Nicholette D. Palmer, Dandi Qiao, Eric Boerwinkle, Nicholas L. Smith, Marguerite R. Irvin, May E. Montasser, Patrick T. Ellinor, Alan Kwong, Gonçalo R. Abecasis, Kathleen C. Barnes, Courtney G. Montgomery, Jennifer A. Smith, Solomon K. Musani, Brian E. Cade, Michael Boehnke, John Blangero, Jessica Lasky-Su, Thomas W. Blackwell, Laura J. Scott, Wonji Kim, Esteban G. Burchard, Jonathon LeFaive, Hemant K. Tiwari, Rasika A. Mathias, Alexander P. Reiner, Charles Kooperberg, M. Benjamin Shoemaker, Albert V. Smith, Ani Manichaikul, Steven A. Lubitz, Mariza de Andrade, Han Chen, and Scott T. Weiss

Subjects
Exact test, Computer science, Metric (mathematics), Scalability, Statistics, False positive paradox, Hardy–Weinberg principle, Genotyping, Statistical power
Abstract

Traditional Hardy-Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in datasets comprised of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence datasets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently amongst the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.

Published
2020
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23. Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies

Author

Cristen J. Willer, Rounak Dey, Joshua C. Denny, Maoxuan Lin, Aliya Gifford, Seunggeun Lee, Hyun Min Kang, Gonçalo R. Abecasis, Wei Zhou, Jonas B. Nielsen, Lisa Bastarache, Brooke N. Wolford, Lars G. Fritsche, Kristian Hveem, Jonathon LeFaive, Sarah A. Gagliano, Peter VandeHaar, Wei-Qi Wei, and Maiken Elvestad Gabrielsen

Subjects
0301 basic medicine, Mixed model, Score test, Scale (ratio), Computer science, Sample (statistics), Genome-wide association study, Biology, Bioinformatics, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, 0302 clinical medicine, Statistics, Genetics, Humans, Computer Simulation, 030304 developmental biology, 0303 health sciences, Models, Genetic, Linear model, Biobank, 030104 developmental biology, Logistic Models, Phenotype, Sample size determination, Case-Control Studies, Linear Models, 030217 neurology & neurosurgery, Type I and type II errors, Genome-Wide Association Study
Abstract

In genome-wide association studies (GWAS) for thousands of phenotypes in large biobanks, most binary traits have substantially fewer cases than controls. Both of the widely used approaches, linear mixed model and the recently proposed logistic mixed model, perform poorly – producing large type I error rates – in the analysis of phenotypes with unbalanced case-control ratios. Here we propose a scalable and accurate generalized mixed model association test that uses the saddlepoint approximation (SPA) to calibrate the distribution of score test statistics. This method, SAIGE, provides accurate p-values even when case-control ratios are extremely unbalanced. It utilizes state-of-art optimization strategies to reduce computational time and memory cost of generalized mixed model. The computation cost linearly depends on sample size, and hence can be applicable to GWAS for thousands of phenotypes by large biobanks. Through the analysis of UK Biobank data of 408,961 white British European-ancestry samples for >1400 binary phenotypes, we show that SAIGE can efficiently analyze large sample data, controlling for unbalanced case-control ratios and sample relatedness.

Published
2018

24. Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

Author

Cashell E. Jaquish, Craig P. Hersh, Emily Barron-Casella, Larry Phillips, James S. Pankow, JoAnn E. Manson, Mariza de Andrade, Vivien A. Sheehan, Norann A. Zaghloul, Yongmei Liu, Sergei Nekhai, Russell P. Tracy, Bruce S. Weir, Pankaj Qasba, Adrienne M. Stilp, Tasha E. Fingerlin, Heather M. Ochs-Balcom, L. Adrienne Cupples, Rongze Yang, David A. Schwartz, Shannon Kelly, Scott E. Devine, Tanja Smith, G.L. Kinney, Beverly Snively, Kent D. Taylor, Manolis Kellis, Ruth J. F. Loos, Seth A. Ament, Kathleen C. Barnes, Robert C. Kaplan, Ulrich Broeckel, Hemant K. Tiwari, Karin F. Hoth, Peter Durda, Julie L. Mikulla, Charles B. Eaton, Cotton Seed, Merry Lynn McDonald, Eric Boerwinkle, Josh Smith, Honghuang Lin, Ingrid B. Borecki, Jeffrey L. Curtis, Emelia J. Benjamin, Kenneth Rice, Sharon L.R. Kardia, Nicholas L. Smith, Coleen M. Damcott, Jeffrey Haessler, Kimberly L. Jones, Elaine Cornell, Nona Sotoodehnia, Adolfo Correa, Rich Johnston, C. Charles Gu, Chii Min Hwu, Peter C. Anderson, Lesley F. Tinker, Colleen Davis, R. Graham Barr, Scott T. Weiss, Leanna Farnam, Chao Hsiung, Brian Silver, Patrick F. McArdle, Lisa W. Martin, Yii-Der Ida Chen, John Barnard, Holly Kramer, Sekar Kathiresan, Gonçalo R. Abecasis, Barry Make, Michael C. Mahaney, Marco V Perez, Donna K. Arnett, Mark Chaffin, Xiuqing Guo, Joshua C. Bis, Pamela Russell, Paul L. Auer, James G. Wilson, Marilyn J. Telen, David K. Levine, Jennifer A. Smith, Christopher Scheller, Meher Preethi Boorgula, Aakrosh Ratan, Kari E. North, Dan E. Arking, Elizabeth A. Regan, Margaret G. Parker, Andres Metspalu, Jai G. Broome, Daniel Taliun, Lynette Ekunwe, Alyna T. Khan, Hao Mei, Dhananjay Vaidya, Ellen M. Schmidt, Stanford Mwasongwe, Joshua P. Lewis, Stacey Gabriel, Christine E. Seidman, Margery Gass, Deborah A. Nickerson, Nicola L. Hawley, Rebecca L. Beer, Afshin Parsa, Steven L. Salzberg, Terri H. Beaty, Stella Aslibekyan, Girish N. Nadkarni, Wei Zhao, David L. Tirschwell, Karen Bunting, Dawn L. DeMeo, Laura J. Rasmussen-Torvik, Julia Powers Becker, Dmitry Prokopenko, Karen Schwander, Bruce D. Gelb, Stephanie Krauter, Laura M. Raffield, Michael E. Hall, Frank C. Sciurba, Lauren Margolin, Nora Franceschini, Daniel N. Harris, Seyedeh M. Zekavat, Dawood Darbar, Keng-Han Lin, Haley Huston, Steven A. Lubitz, Andrea Ganna, Carole Sztalryd, Cathy C. Laurie, Christy Chang, James E. Hixson, Steven A. McCarroll, Barbara A. Konkle, Michael D. Kessler, Scott I. Vrieze, Yingze Zhang, Sarah Ruuska, George J. Papanicolaou, Weiniu Gan, Maris Alver, Elizabeth A. Streeten, Fei Fei Wang, Lu-Chen Weng, Braxton D. Mitchell, Lee-Ming Chuang, Sean P. David, Wei-Min Chen, Susan R. Heckbert, Ryan D. Hernandez, Andrew D. Johnson, Cristen J. Willer, Ani Manichaikul, Jonathan M. Bloom, Timothy D. O’Connor, Sylvia Smoller, Marguerite R. Irvin, Seung Hoan Choi, Ida Surakka, Veikko Salomaa, Diane M. Becker, Ron Do, W. Craig Johnson, Cecelia A. Laurie, Meryl S. LeBoff, Aniket Shetty, Tõnu Esko, Michael C. Zody, Xiaoqi Geng, Da Wei Gong, Snow Xueyan Zhao, Esteban G. Burchard, Xiuwen Zheng, Cara L. Carty, Alexander P. Reiner, Tim Assimes, Deborah A. Meyers, Mina K. Chung, Harald H H Göring, Benjamin M. Neale, Pradeep Natarajan, Yan Gao, Stephen S. Rich, Yun Ju Sung, Susan K. Dutcher, Ferdouse Begum, Stephanie M. Gogarten, John Blangero, Jonathan Cardwell, Kayleen Williams, Rakhi P. Naik, Amol C. Shetty, Sayantan Das, Myriam Fornage, May E. Montasser, Michelle Daya, Edwin K. Silverman, Daniel E. Weeks, Laura J. Kaufman, Dimitrios Avramopoulos, Michael Y. Tsai, Christine M. Albert, Vijay G. Sankaran, Jeffrey R. O'Connell, Thomas W. Blackwell, Stephen T. McGarvey, Robert M. Reed, Leslie A. Lange, Qing Duan, Bruce M. Psaty, Leslie S. Emery, Bertha Hidalgo, Jennifer A. Brody, L. Keoki Williams, Soren Germer, Zhaohui S. Qin, Deepti Jain, Deborah Applebaum-Bowden, Carla Wilson, Degui Zhi, Christoph Lange, Elliott Hong, L.F. Bielak, Wen Jane Lee, Yue Guan, Tarik Walker, Rebecca D. Jackson, Charles R. Farber, Mark J. Daly, Stephanie M. Fullerton, John E. Hokanson, Karol E. Watson, James Luo, Richard Casaburi, Seunggeun Lee, Jill M. Johnsen, Margaret A. Taub, Ryan L. Minster, Ravi Duggirala, Susan K. Mathai, Yun Li, Quenna Wong, Matthew Flickinger, Huichun Xu, Susan Redline, Ulrike Peters, Ivana V. Yang, Jesse M. Engreitz, Sanni Ruotsalainen, Sean K. McFarland, Avram D Walts, Patricia A. Peyser, Allison E. Ashley-Koch, Lewis C. Becker, Nicholette Palmer Allred, James A. Perry, Jody S. Sylvia, Tamar Sofer, Vasan S. Ramachandran, Laura Almasy, Matthew J. Budoff, Ranjan Deka, David M. Herrington, Simeon I. Taylor, Daniel Levy, Chaojie Yang, Sameer Chavan, Kathleen A. Ryan, Josyf C. Mychaleckyj, Ingo Ruczinski, Sebastian Zoellner, Michael Preuss, Tim Poterba, Wendy S. Post, Amber L. Beitelshees, Ben Heavner, Carolina Roselli, Namiko Abe, Jonathon LeFaive, Mark T. Gladwin, Brian Custer, Robert B. Wallace, Simin Liu, Michael H. Cho, Robert E. Handsaker, Dabeeru C. Rao, Bo Juen Chen, Wayne Hui Heng Sheu, Xiang Zhou, Marcos Bezerra, Solomon K. Musani, Eimear E. Kenny, James F. Casella, Kathryn L. Lunetta, Nancy Min, Nicholas Rafaels, Lisa R. Yanek, Min A. Jhun, David C. Glahn, Rasika A. Mathias, Mollie A. Minear, Russell P. Bowler, Jason Ernst, Carolyn J. Crandall, Sara Penchev, Alvaro Alonso, Timothy A. Thornton, Toni I. Pollin, Charles Kooperberg, Ethan M. Lange, Juan M. Peralta, Pramod Anugu, Lucinda Fulton, Adam A. Szpiro, Michael R. DeBaun, M. Benjamin Shoemaker, Sam Phillips, Dan M. Roden, Mao Fu, Daniel I. Chasman, James D. Crapo, Hua Tang, Gina M. Peloso, Hyun Min Kang, Samuli Ripatti, Phuwanat Sakornsakolpat, Christopher R. Gignoux, Peter VandeHaar, Jerome I. Rotter, Dandi Qiao, Emily S. Wan, Shabnam Salimi, Kevin Sandow, Jiang He, Patrick T. Ellinor, Joanne E. Curran, Institute for Molecular Medicine Finland, Samuli Olli Ripatti / Principal Investigator, University of Helsinki, Centre of Excellence in Complex Disease Genetics, Clinicum, Doctoral Programme in Population Health, Department of Public Health, and Complex Disease Genetics

Subjects
0301 basic medicine, Apolipoprotein B, General Physics and Astronomy, Gene Expression, Genome-wide association study, 030204 cardiovascular system & hematology, Cardiovascular, Lipoprotein particle, chemistry.chemical_compound, 0302 clinical medicine, Risk Factors, GENETIC-VARIANTS, 2.1 Biological and endogenous factors, WIDE ASSOCIATION, Aetiology, lcsh:Science, African Continental Ancestry Group, Genetics, Multidisciplinary, Genome, biology, CHOLESTEROL, Adaptor Proteins, Lipoprotein(a), Single Nucleotide, NHLBI TOPMed Lipids Working Group, 3142 Public health care science, environmental and occupational health, 3. Good health, Cholesterol, Heart Disease, Cardiovascular Diseases, CARDIOVASCULAR-DISEASE, RARE VARIANTS, lipids (amino acids, peptides, and proteins), LOW-FREQUENCY, Human, DNA Copy Number Variations, Science, Quantitative Trait Loci, European Continental Ancestry Group, Black People, POPULATION-SCALE, Quantitative trait locus, Article, White People, General Biochemistry, Genetics and Molecular Biology, LDL, Structural variation, 03 medical and health sciences, COMPONENTS-ANALYSIS, RISK-FACTOR, Humans, CORONARY-HEART-DISEASE, Polymorphism, Whole Genome Sequencing, Prevention, Human Genome, General Chemistry, Atherosclerosis, Vesicular Transport, Good Health and Well Being, 030104 developmental biology, chemistry, biology.protein, lcsh:Q, 3111 Biomedicine, Lipoprotein, Genome-Wide Association Study
Abstract

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans., Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels.

Published
2018
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25. Loss-of-function genomic variants with impact on liver-related blood traits highlight potential therapeutic targets for cardiovascular disease

Author

Gregory J.M. Zajac, Jerome I. Rotter, Rasika A. Mathias, Vivek Rai, David Schlessinger, Tanmoy Roychowdhury, Yuhao Liu, Kathleen C. Barnes, Maiken Elvestad Gabrielsen, John Blangero, Russell P. Tracy, Xiuqing Guo, Albert V. Smith, Mari Løset, Luis Villacorta, Anita Pandit, Xingnan Li, Kent D. Taylor, Anne Heidi Skogholt, Seunggeun Lee, Brooke N. Wolford, Allison E. Ashley-Koch, Scott T. Weiss, Yingze Zhang, Akua Acheampong, Seung Hoan Choi, Steven A. Lubitz, Ketian Yu, Ren-Hua Chung, Jill M. Johnsen, Seyed Mehdi Nouraie, Lars G. Fritsche, Lisa R. Yanek, Yii Der Chen, Austen Grooms, Jessica Lasky-Su, Ida Surakka, Pradeep Natarajan, Michael Boehnke, Lukas Forer, Victor R. Gordeuk, Hyun Min Kang, Whitney E. Hornsby, Stella Aslibekyan, Wayne Huey-Herng Sheu, Ben Michael Brumpton, Sarah A Gagliano Taliun, Patrick T. Ellinor, Francesco Cucca, Karen Schwander, Patricia A. Peyser, Lewis C. Becker, Rebecca D. Jackson, Joanne E. Curran, Jonathon LeFaive, Sebastian Schoenherr, Marguerite R. Irvin, Sarah E. Graham, Eugene R. Bleecker, Solomon K. Musani, Michelle Daya, Alexander P. Reiner, Adolfo Correa, William Overton, Vivien A. Sheehan, Oddgeir L. Holmen, Cristen J. Willer, Bertha A. Hildalgo, Christian Fuchsberger, Chad M. Brummett, Sachin Kheterpal, Matthew Zawistowski, Kristian Hveem, Sekar Kathiresan, James G. Wilson, Marilyn J. Telen, Ramachandran S. Vasan, Bjørn Olav Åsvold, Donna K. Arnett, Sebastian Zöllner, Wei Zhou, Nicholette D. Palmer, Gonçalo R. Abecasis, Jennifer A. Smith, L. Adrienne Cupples, Nicholas M. Rafaels, Lawrence F. Bielak, Barbara A. Konkle, Charles Kooperberg, C Sidore, Juan M. Peralta, Jifeng Zhang, Daniel Taliun, Deborah A. Meyers, Stephen S. Rich, Sayantan Das, Jonas B. Nielsen, Thomas W. Blackwell, Oren Rom, Amanda Schaefer, Y. Eugene Chen, and Courtney G. Montgomery

Subjects
2. Zero hunger, 0303 health sciences, education.field_of_study, business.industry, Population, Fatty liver, Blood lipids, Genome-wide association study, Disease, 030204 cardiovascular system & hematology, Bioinformatics, medicine.disease, 3. Good health, 03 medical and health sciences, Liver disease, 0302 clinical medicine, Diabetes mellitus, Medicine, Liver function, business, education, 030304 developmental biology
Abstract

SUMMARYCardiovascular diseases (CVD), and in particular cerebrovascular and ischemic heart diseases, are leading causes of death globally.1Lowering circulating lipids is an important treatment strategy to reduce risk.2,3However, some pharmaceutical mechanisms of reducing CVD may increase risk of fatty liver disease or other metabolic disorders.4,5,6To identify potential novel therapeutic targets, which may reduce risk of CVD without increasing risk of metabolic disease, we focused on the simultaneous evaluation of quantitative traits related to liver function and CVD. Using a combination of low-coverage (5×) whole-genome sequencing and targeted genotyping, deep genotype imputation based on the TOPMed reference panel7, and genome-wide association study (GWAS) meta-analysis, we analyzed 12 liver-related blood traits (including liver enzymes, blood lipids, and markers of iron metabolism) in up to 203,476 people from three population-based cohorts of different ancestries. We identified 88 likely causal protein-altering variants that were associated with one or more liver-related blood traits. We identified several loss-of-function (LoF) variants reducing low-density lipoprotein cholesterol (LDL-C) or risk of CVD without increased risk of liver disease or diabetes, including variants in known lipid genes (e.g.APOB,LPL). A novel LoF variant,ZNF529:p.K405X, was associated with decreased levels of LDL-C (P=1.3×10−8) but demonstrated no association with liver enzymes or non-fasting blood glucose levels. Silencing ofZNF529in human hepatocytes resulted in upregulation of LDL receptor (LDLR) and increased LDL-C uptake in the cells, suggesting that inhibition ofZNF529or its gene product could be used for treating hypercholesterolemia and hence reduce the risk of CVD. Taken together, we demonstrate that simultaneous consideration of multiple phenotypes and a focus on rare protein-altering variants may identify promising therapeutic targets.

Published
2019
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26. Scalable generalized linear mixed model for region-based association tests in large biobanks and cohorts

Author

Wenjian Bi, Mark J. Daly, Jonas B. Nielsen, Kristian Hveem, Wei Zhou, Benjamin M. Neale, Gonçalo R. Abecasis, Lars G. Fritsche, Seunggeun Lee, Maiken Elvestad Gabrielsen, Jonathon LeFaive, Cristen J. Willer, and Sarah A Gagliano Taliun

Subjects
Mixed model, 0303 health sciences, education.field_of_study, Computer science, Aggregate (data warehouse), Population, Sample (statistics), Population stratification, Biobank, Generalized linear mixed model, 03 medical and health sciences, 0302 clinical medicine, Statistics, education, 030217 neurology & neurosurgery, 030304 developmental biology, Type I and type II errors
Abstract

With very large sample sizes, population-based cohorts and biobanks provide an exciting opportunity to identify genetic components of complex traits. To analyze rare variants, gene or region-based multiple variant aggregate tests are commonly used to increase association test power. However, due to the substantial computation cost, existing region-based rare variant tests cannot analyze hundreds of thousands of samples while accounting for confounders, such as population stratification and sample relatedness. Here we propose a scalable generalized mixed model region-based association test that can handle large sample sizes and accounts for unbalanced case-control ratios for binary traits. This method, SAIGE-GENE, utilizes state-of-the-art optimization strategies to reduce computational and memory cost, and hence is applicable to exome-wide and genome-wide region-based analysis for hundreds of thousands of samples. Through the analysis of the HUNT study of 69,716 Norwegian samples and the UK Biobank data of 408,910 White British samples, we show that SAIGE-GENE can efficiently analyze large sample data (N > 400,000) with type I error rates well controlled.

Published
2019
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27. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Author

Russell P. Tracy, Mollie A. Minear, James B. Meigs, Amol C. Shetty, David Van Den Berg, Yii-Der Ida Chen, Nona Sotoodehnia, Kent D. Taylor, Soren Germer, Adolfo Correa, John Barnard, Emelia J. Benjamin, Weihong Tang, Zachary A. Szpiech, Sebastian Schoenherr, Kristin G. Ardlie, Anna Köttgen, Tanika N. Kelly, Leslie A. Lange, Michelle Daya, Dan M. Roden, Lori Garman, Xutong Zhao, Lawrence F. Bielak, Edwin K. Silverman, Daniel E. Weeks, Gina M. Peloso, Jill M. Johnsen, Hyun Min Kang, Lukas Forer, Jerome I. Rotter, Stephen T. McGarvey, Wendy S. Post, Weiniu Gan, Stephanie M. Fullerton, Jedidiah Carlson, Brian Custer, Nora Franceschini, Alvaro Alonso, Brian L. Browning, Michael H. Cho, André Corvelo, Stacey Gabriel, Xiuqing Guo, Angel C.Y. Mak, Michael Boehnke, Yingze Zhang, Timothy A. Thornton, Douglas P. Kiel, Ingo Ruczinski, Sudha Seshadri, Seung-been Lee, Scott I. Vrieze, Charles Kooperberg, Stephanie M. Gogarten, John Blangero, Brandon Chalazan, Seung Hoan Choi, Dawood Darbar, Braxton D. Mitchell, Alisa K. Manning, Anne-Katrin Emde, Xihong Lin, D. C. Rao, Eimear E. Kenny, Christine M. Albert, Xiaowen Tian, Allison E. Ashley-Koch, Mina K. Chung, Pradeep Natarajan, Rebecca L. Beer, Stella Aslibekyan, Jiang He, Patrick T. Ellinor, James F. Casella, Richard A. Gibbs, Alanna C. Morrison, Clary B. Clish, Nancy L. Heard-Costa, Susan R. Heckbert, Daniel N. Harris, Myriam Fornage, M. Benjamin Shoemaker, Kari E. North, Courtney G. Montgomery, Sanghamitra Mohanty, Lewis C. Becker, George J. Papanicolaou, Chunyu Liu, Michael D. Kessler, Susan K. Dutcher, Marguerite R. Irvin, Daniel Levy, Karine A. Viaud-Martinez, Joanne E. Curran, Jonathon LeFaive, Dawn L. DeMeo, Mark T. Gladwin, Quenna Wong, Andrea Natale, Adrienne M. Stilp, Patricia A. Peyser, Robert Klemmer, Jessica Lasky-Su, Donald W. Bowden, Kathryn L. Lunetta, Rasika A. Mathias, Brian E. Cade, Kathleen C. Barnes, Daniel Taliun, Douglas Loesch, Sharon R. Browning, Joanne M. Murabito, Esteban G. Burchard, Sarah A Gagliano Taliun, Daniel J. Gottlieb, Timothy D. O’Connor, Deborah A. Meyers, Jennifer A. Brody, Ryan D. Hernandez, Andrew D. Johnson, Eric Boerwinkle, Sebastian Zöllner, Ruth J. F. Loos, Nicholas L. Smith, Gonçalo R. Abecasis, Jennifer A. Smith, Michael E. Hall, Lu-Chen Weng, Jeffrey R. O'Connell, Kenneth Rice, Donna K. Arnett, Nicholette D. Palmer, Bruce S. Weir, L. Adrienne Cupples, Barbara A. Konkle, Paul L. Auer, Cathy C. Laurie, Julie L. Mikulla, Deborah A. Nickerson, Alexander P. Reiner, Chloé Sarnowski, Raul Torres, Susan Redline, Mariza de Andrade, Vivien A. Sheehan, Cashell E. Jaquish, Pankaj Qasba, R. Graham Barr, Scott T. Weiss, Ani Manichaikul, Robert E. Gerszten, Albert V. Smith, Steven A. Lubitz, Cristen J. Willer, Michael C. Zody, Jeong-Sun Seo, Diane Fatkin, Christian Fuchsberger, François Aguet, Sharon L.R. Kardia, James G. Wilson, Marilyn J. Telen, Ramachandran S. Vasan, Nathan Pankratz, Keng-Han Lin, Shannon Kelly, Wayne E. Clarke, Sarah C. Nelson, May E. Montasser, Stephen S. Rich, Sayantan Das, Thomas W. Blackwell, Bruce M. Psaty, Leslie S. Emery, Achilleas N. Pitsillides, and David D. McManus

Subjects
Whole genome sequencing, 0303 health sciences, Genotype imputation, Disease, Computational biology, Biology, Precision medicine, Phenotype, Genome, Genetic architecture, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, 030217 neurology & neurosurgery, 030304 developmental biology, Reference genome
Abstract

Summary paragraphThe Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency

Published
2019
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28. Exploring Various Polygenic Risk Scores for Skin Cancer in the Phenomes of the Michigan Genomics Initiative and the UK Biobank with a Visual Catalog:PRSWeb

Author

Peter VandeHaar, Lauren J. Beesley, Robert B. Peng, Bhramar Mukherjee, Chad M. Brummett, Jonathon LeFaive, Sayantan Das, Maxwell Salvatore, Matthew Zawistowski, Sachin Kheterpal, Sarah A. Gagliano, Gonçalo R. Abecasis, Stephen B. Gruber, Thomas T. Klumpner, Stephanie E. Moser, Erin O. Kaleba, Victoria M. Blanc, and Lars G. Fritsche

Subjects
Gerontology, 0303 health sciences, education.field_of_study, Framingham Risk Score, business.industry, Population, Disease, Phenome, medicine.disease, Biobank, Genetic architecture, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Biorepository, 030220 oncology & carcinogenesis, medicine, Skin cancer, education, business, 030304 developmental biology
Abstract

Polygenic risk scores (PRS) are designed to serve as a single summary measure, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The construction of a PRS often depends on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. In this paper, we consider several choices for constructing a PRS using summary data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict outcomes derived from electronic health records (EHR). Weexamine the three most common skin cancer subtypes in the USA: basal cellcarcinoma, cutaneous squamous cell carcinoma, and melanoma. The genetic risk profiles of subtypes may consist of both shared and unique elements and we construct PRS to understand the common versus distinct etiology. This study is conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate their association with secondary traits. PheWAS results are then replicated using population-based UK Biobank data. We develop an accompanying visual catalog calledPRSwebthat provides detailed PheWAS results and allows users to directly compare different PRS construction methods. The results of this study can provide guidance regarding PRS construction in future PRS-PheWAS studies using EHR data involving disease subtypes.Author summaryIn the study of genetically complex diseases, polygenic risk scores synthesize information from multiple genetic risk factors to provide insight into a patient’s risk of developing a disease based on his/her genetic profile. These risk scores can be explored in conjunction with health and disease information available in the electronic medical records. They may be associated with diseases that may be related to or precursors of the underlying disease of interest. Limited work is available guiding risk score construction when the goal is to identify associations across the medical phenome. In this paper, we compare different polygenic risk score construction methods in terms of their relationships with the medical phenome. We further propose methods for using these risk scores to decouple the shared and unique genetic profiles of related diseases and to explore related diseases’ shared and unique secondary associations. Leveraging and harnessing the rich data resources of the Michigan Genomics Initiative, a biorepository effort at Michigan Medicine, and the larger population-based UK Biobank study, we investigated the performance of genetic risk profiling methods for the three most common types of skin cancer: melanoma, basal cell carcinoma and squamous cell carcinoma.

Published
2018
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