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Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program

Genome-wide association studies (GWAS) have underrepresented individuals from non-European populations, impeding progress in characterizing the genetic architecture and consequences of health and disease traits. To address this, we present a population-stratified phenome-wide GWAS followed by a mult...

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Autores principales: Verma, Anurag, Huffman, Jennifer E, Rodriguez, Alex, Conery, Mitchell, Liu, Molei, Ho, Yuk-Lam, Kim, Youngdae, Heise, David A, Guare, Lindsay, Panickan, Vidul Ayakulangara, Garcon, Helene, Linares, Franciel, Costa, Lauren, Goethert, Ian, Tipton, Ryan, Honerlaw, Jacqueline, Davies, Laura, Whitbourne, Stacey, Cohen, Jeremy, Posner, Daniel C, Sangar, Rahul, Murray, Michael, Wang, Xuan, Dochtermann, Daniel R, Devineni, Poornima, Shi, Yunling, Nandi, Tarak Nath, Assimes, Themistocles L, Brunette, Charles A, Carroll, Robert J, Clifford, Royce, Duvall, Scott, Gelernter, Joel, Hung, Adriana, Iyengar, Sudha K, Joseph, Jacob, Kember, Rachel, Kranzler, Henry, Levey, Daniel, Luoh, Shiuh-Wen, Merritt, Victoria C, Overstreet, Cassie, Deak, Joseph D, Grant, Struan F A, Polimanti, Renato, Roussos, Panos, Sun, Yan V, Venkatesh, Sanan, Voloudakis, Georgios, Justice, Amy, Begoli, Edmon, Ramoni, Rachel, Tourassi, Georgia, Pyarajan, Saiju, Tsao, Philip S, O’Donnell, Christopher J, Muralidhar, Sumitra, Moser, Jennifer, Casas, Juan P, Bick, Alexander G, Zhou, Wei, Cai, Tianxi, Voight, Benjamin F, Cho, Kelly, Gaziano, Michael J, Madduri, Ravi K, Damrauer, Scott M, Liao, Katherine P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327290/
https://www.ncbi.nlm.nih.gov/pubmed/37425708
http://dx.doi.org/10.1101/2023.06.28.23291975
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author Verma, Anurag
Huffman, Jennifer E
Rodriguez, Alex
Conery, Mitchell
Liu, Molei
Ho, Yuk-Lam
Kim, Youngdae
Heise, David A
Guare, Lindsay
Panickan, Vidul Ayakulangara
Garcon, Helene
Linares, Franciel
Costa, Lauren
Goethert, Ian
Tipton, Ryan
Honerlaw, Jacqueline
Davies, Laura
Whitbourne, Stacey
Cohen, Jeremy
Posner, Daniel C
Sangar, Rahul
Murray, Michael
Wang, Xuan
Dochtermann, Daniel R
Devineni, Poornima
Shi, Yunling
Nandi, Tarak Nath
Assimes, Themistocles L
Brunette, Charles A
Carroll, Robert J
Clifford, Royce
Duvall, Scott
Gelernter, Joel
Hung, Adriana
Iyengar, Sudha K
Joseph, Jacob
Kember, Rachel
Kranzler, Henry
Levey, Daniel
Luoh, Shiuh-Wen
Merritt, Victoria C
Overstreet, Cassie
Deak, Joseph D
Grant, Struan F A
Polimanti, Renato
Roussos, Panos
Sun, Yan V
Venkatesh, Sanan
Voloudakis, Georgios
Justice, Amy
Begoli, Edmon
Ramoni, Rachel
Tourassi, Georgia
Pyarajan, Saiju
Tsao, Philip S
O’Donnell, Christopher J
Muralidhar, Sumitra
Moser, Jennifer
Casas, Juan P
Bick, Alexander G
Zhou, Wei
Cai, Tianxi
Voight, Benjamin F
Cho, Kelly
Gaziano, Michael J
Madduri, Ravi K
Damrauer, Scott M
Liao, Katherine P
author_facet Verma, Anurag
Huffman, Jennifer E
Rodriguez, Alex
Conery, Mitchell
Liu, Molei
Ho, Yuk-Lam
Kim, Youngdae
Heise, David A
Guare, Lindsay
Panickan, Vidul Ayakulangara
Garcon, Helene
Linares, Franciel
Costa, Lauren
Goethert, Ian
Tipton, Ryan
Honerlaw, Jacqueline
Davies, Laura
Whitbourne, Stacey
Cohen, Jeremy
Posner, Daniel C
Sangar, Rahul
Murray, Michael
Wang, Xuan
Dochtermann, Daniel R
Devineni, Poornima
Shi, Yunling
Nandi, Tarak Nath
Assimes, Themistocles L
Brunette, Charles A
Carroll, Robert J
Clifford, Royce
Duvall, Scott
Gelernter, Joel
Hung, Adriana
Iyengar, Sudha K
Joseph, Jacob
Kember, Rachel
Kranzler, Henry
Levey, Daniel
Luoh, Shiuh-Wen
Merritt, Victoria C
Overstreet, Cassie
Deak, Joseph D
Grant, Struan F A
Polimanti, Renato
Roussos, Panos
Sun, Yan V
Venkatesh, Sanan
Voloudakis, Georgios
Justice, Amy
Begoli, Edmon
Ramoni, Rachel
Tourassi, Georgia
Pyarajan, Saiju
Tsao, Philip S
O’Donnell, Christopher J
Muralidhar, Sumitra
Moser, Jennifer
Casas, Juan P
Bick, Alexander G
Zhou, Wei
Cai, Tianxi
Voight, Benjamin F
Cho, Kelly
Gaziano, Michael J
Madduri, Ravi K
Damrauer, Scott M
Liao, Katherine P
author_sort Verma, Anurag
collection PubMed
description Genome-wide association studies (GWAS) have underrepresented individuals from non-European populations, impeding progress in characterizing the genetic architecture and consequences of health and disease traits. To address this, we present a population-stratified phenome-wide GWAS followed by a multi-population meta-analysis for 2,068 traits derived from electronic health records of 635,969 participants in the Million Veteran Program (MVP), a longitudinal cohort study of diverse U.S. Veterans genetically similar to the respective African (121,177), Admixed American (59,048), East Asian (6,702), and European (449,042) superpopulations defined by the 1000 Genomes Project. We identified 38,270 independent variants associating with one or more traits at experiment-wide [Formula: see text] significance; fine-mapping 6,318 signals identified from 613 traits to single-variant resolution. Among these, a third (2,069) of the associations were found only among participants genetically similar to non-European reference populations, demonstrating the importance of expanding diversity in genetic studies. Our work provides a comprehensive atlas of phenome-wide genetic associations for future studies dissecting the architecture of complex traits in diverse populations.
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spelling pubmed-103272902023-07-08 Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program Verma, Anurag Huffman, Jennifer E Rodriguez, Alex Conery, Mitchell Liu, Molei Ho, Yuk-Lam Kim, Youngdae Heise, David A Guare, Lindsay Panickan, Vidul Ayakulangara Garcon, Helene Linares, Franciel Costa, Lauren Goethert, Ian Tipton, Ryan Honerlaw, Jacqueline Davies, Laura Whitbourne, Stacey Cohen, Jeremy Posner, Daniel C Sangar, Rahul Murray, Michael Wang, Xuan Dochtermann, Daniel R Devineni, Poornima Shi, Yunling Nandi, Tarak Nath Assimes, Themistocles L Brunette, Charles A Carroll, Robert J Clifford, Royce Duvall, Scott Gelernter, Joel Hung, Adriana Iyengar, Sudha K Joseph, Jacob Kember, Rachel Kranzler, Henry Levey, Daniel Luoh, Shiuh-Wen Merritt, Victoria C Overstreet, Cassie Deak, Joseph D Grant, Struan F A Polimanti, Renato Roussos, Panos Sun, Yan V Venkatesh, Sanan Voloudakis, Georgios Justice, Amy Begoli, Edmon Ramoni, Rachel Tourassi, Georgia Pyarajan, Saiju Tsao, Philip S O’Donnell, Christopher J Muralidhar, Sumitra Moser, Jennifer Casas, Juan P Bick, Alexander G Zhou, Wei Cai, Tianxi Voight, Benjamin F Cho, Kelly Gaziano, Michael J Madduri, Ravi K Damrauer, Scott M Liao, Katherine P medRxiv Article Genome-wide association studies (GWAS) have underrepresented individuals from non-European populations, impeding progress in characterizing the genetic architecture and consequences of health and disease traits. To address this, we present a population-stratified phenome-wide GWAS followed by a multi-population meta-analysis for 2,068 traits derived from electronic health records of 635,969 participants in the Million Veteran Program (MVP), a longitudinal cohort study of diverse U.S. Veterans genetically similar to the respective African (121,177), Admixed American (59,048), East Asian (6,702), and European (449,042) superpopulations defined by the 1000 Genomes Project. We identified 38,270 independent variants associating with one or more traits at experiment-wide [Formula: see text] significance; fine-mapping 6,318 signals identified from 613 traits to single-variant resolution. Among these, a third (2,069) of the associations were found only among participants genetically similar to non-European reference populations, demonstrating the importance of expanding diversity in genetic studies. Our work provides a comprehensive atlas of phenome-wide genetic associations for future studies dissecting the architecture of complex traits in diverse populations. Cold Spring Harbor Laboratory 2023-06-29 /pmc/articles/PMC10327290/ /pubmed/37425708 http://dx.doi.org/10.1101/2023.06.28.23291975 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Verma, Anurag
Huffman, Jennifer E
Rodriguez, Alex
Conery, Mitchell
Liu, Molei
Ho, Yuk-Lam
Kim, Youngdae
Heise, David A
Guare, Lindsay
Panickan, Vidul Ayakulangara
Garcon, Helene
Linares, Franciel
Costa, Lauren
Goethert, Ian
Tipton, Ryan
Honerlaw, Jacqueline
Davies, Laura
Whitbourne, Stacey
Cohen, Jeremy
Posner, Daniel C
Sangar, Rahul
Murray, Michael
Wang, Xuan
Dochtermann, Daniel R
Devineni, Poornima
Shi, Yunling
Nandi, Tarak Nath
Assimes, Themistocles L
Brunette, Charles A
Carroll, Robert J
Clifford, Royce
Duvall, Scott
Gelernter, Joel
Hung, Adriana
Iyengar, Sudha K
Joseph, Jacob
Kember, Rachel
Kranzler, Henry
Levey, Daniel
Luoh, Shiuh-Wen
Merritt, Victoria C
Overstreet, Cassie
Deak, Joseph D
Grant, Struan F A
Polimanti, Renato
Roussos, Panos
Sun, Yan V
Venkatesh, Sanan
Voloudakis, Georgios
Justice, Amy
Begoli, Edmon
Ramoni, Rachel
Tourassi, Georgia
Pyarajan, Saiju
Tsao, Philip S
O’Donnell, Christopher J
Muralidhar, Sumitra
Moser, Jennifer
Casas, Juan P
Bick, Alexander G
Zhou, Wei
Cai, Tianxi
Voight, Benjamin F
Cho, Kelly
Gaziano, Michael J
Madduri, Ravi K
Damrauer, Scott M
Liao, Katherine P
Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program
title Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program
title_full Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program
title_fullStr Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program
title_full_unstemmed Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program
title_short Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program
title_sort diversity and scale: genetic architecture of 2,068 traits in the va million veteran program
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327290/
https://www.ncbi.nlm.nih.gov/pubmed/37425708
http://dx.doi.org/10.1101/2023.06.28.23291975
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