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A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n=35) or hospitalization (n=4...

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Autores principales: Verma, Anurag, Tsao, Noah, Thomann, Lauren, Ho, Yuk-Lam, Iyengar, Sudha, Luoh, Shiuh-Wen, Carr, Rotonya, Crawford, Dana, Efird, Jimmy T., Huffman, Jennifer, Hung, Adriana, Ivey, Kerry, Levin, Michael, Lynch, Julie, Natarajan, Pradeep, Pyarajan, Saiju, Bick, Alexander, Costa, Lauren, Genovese, Giulio, Hauger, Richard, Madduri, Ravi, Pathak, Gita, Polimanti, Renato, Voight, Benjamin, Vujkovic, Marijana, Zekavat, Maryam, Zhao, Hongyu, Ritchie, Marylyn D, Chang, Kyong-Mi, Cho, Kelly, Casas, Juan P., Tsao, Philip S., Gaziano, J. Michael, O’Donnell, Christopher, Damrauer, Scott, Liao, Katherine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8509103/
https://www.ncbi.nlm.nih.gov/pubmed/34642702
http://dx.doi.org/10.1101/2021.05.18.21257396
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author Verma, Anurag
Tsao, Noah
Thomann, Lauren
Ho, Yuk-Lam
Iyengar, Sudha
Luoh, Shiuh-Wen
Carr, Rotonya
Crawford, Dana
Efird, Jimmy T.
Huffman, Jennifer
Hung, Adriana
Ivey, Kerry
Levin, Michael
Lynch, Julie
Natarajan, Pradeep
Pyarajan, Saiju
Bick, Alexander
Costa, Lauren
Genovese, Giulio
Hauger, Richard
Madduri, Ravi
Pathak, Gita
Polimanti, Renato
Voight, Benjamin
Vujkovic, Marijana
Zekavat, Maryam
Zhao, Hongyu
Ritchie, Marylyn D
Chang, Kyong-Mi
Cho, Kelly
Casas, Juan P.
Tsao, Philip S.
Gaziano, J. Michael
O’Donnell, Christopher
Damrauer, Scott
Liao, Katherine
author_facet Verma, Anurag
Tsao, Noah
Thomann, Lauren
Ho, Yuk-Lam
Iyengar, Sudha
Luoh, Shiuh-Wen
Carr, Rotonya
Crawford, Dana
Efird, Jimmy T.
Huffman, Jennifer
Hung, Adriana
Ivey, Kerry
Levin, Michael
Lynch, Julie
Natarajan, Pradeep
Pyarajan, Saiju
Bick, Alexander
Costa, Lauren
Genovese, Giulio
Hauger, Richard
Madduri, Ravi
Pathak, Gita
Polimanti, Renato
Voight, Benjamin
Vujkovic, Marijana
Zekavat, Maryam
Zhao, Hongyu
Ritchie, Marylyn D
Chang, Kyong-Mi
Cho, Kelly
Casas, Juan P.
Tsao, Philip S.
Gaziano, J. Michael
O’Donnell, Christopher
Damrauer, Scott
Liao, Katherine
author_sort Verma, Anurag
collection PubMed
description The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n=35) or hospitalization (n=42) due to severe COVID-19 using genome-wide association summary from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n(rs495828)=53 and n(rs505922)=59); strongest association with venous embolism, odds ratio (ORrs495828 1.33 (p=1.32 × 10(−199)), and thrombosis OR(rs505922) 1.33, p=2.2 × 10(−265). Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p=4.12 × 10(−191); CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p=2.26 × 10(−12). The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p=6.48 × 10(−23), lupus OR 0.84, p=3.97 × 10(−06). PheWAS stratified by genetic ancestry demonstrated differences in genotype-phenotype associations across ancestry. LMNA (rs581342) associated with neutropenia OR 1.29 p=4.1 × 10(−13) among Veterans of African ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.
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spelling pubmed-85091032021-10-13 A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program Verma, Anurag Tsao, Noah Thomann, Lauren Ho, Yuk-Lam Iyengar, Sudha Luoh, Shiuh-Wen Carr, Rotonya Crawford, Dana Efird, Jimmy T. Huffman, Jennifer Hung, Adriana Ivey, Kerry Levin, Michael Lynch, Julie Natarajan, Pradeep Pyarajan, Saiju Bick, Alexander Costa, Lauren Genovese, Giulio Hauger, Richard Madduri, Ravi Pathak, Gita Polimanti, Renato Voight, Benjamin Vujkovic, Marijana Zekavat, Maryam Zhao, Hongyu Ritchie, Marylyn D Chang, Kyong-Mi Cho, Kelly Casas, Juan P. Tsao, Philip S. Gaziano, J. Michael O’Donnell, Christopher Damrauer, Scott Liao, Katherine medRxiv Article The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n=35) or hospitalization (n=42) due to severe COVID-19 using genome-wide association summary from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n(rs495828)=53 and n(rs505922)=59); strongest association with venous embolism, odds ratio (ORrs495828 1.33 (p=1.32 × 10(−199)), and thrombosis OR(rs505922) 1.33, p=2.2 × 10(−265). Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p=4.12 × 10(−191); CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p=2.26 × 10(−12). The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p=6.48 × 10(−23), lupus OR 0.84, p=3.97 × 10(−06). PheWAS stratified by genetic ancestry demonstrated differences in genotype-phenotype associations across ancestry. LMNA (rs581342) associated with neutropenia OR 1.29 p=4.1 × 10(−13) among Veterans of African ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets. Cold Spring Harbor Laboratory 2021-10-15 /pmc/articles/PMC8509103/ /pubmed/34642702 http://dx.doi.org/10.1101/2021.05.18.21257396 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
Tsao, Noah
Thomann, Lauren
Ho, Yuk-Lam
Iyengar, Sudha
Luoh, Shiuh-Wen
Carr, Rotonya
Crawford, Dana
Efird, Jimmy T.
Huffman, Jennifer
Hung, Adriana
Ivey, Kerry
Levin, Michael
Lynch, Julie
Natarajan, Pradeep
Pyarajan, Saiju
Bick, Alexander
Costa, Lauren
Genovese, Giulio
Hauger, Richard
Madduri, Ravi
Pathak, Gita
Polimanti, Renato
Voight, Benjamin
Vujkovic, Marijana
Zekavat, Maryam
Zhao, Hongyu
Ritchie, Marylyn D
Chang, Kyong-Mi
Cho, Kelly
Casas, Juan P.
Tsao, Philip S.
Gaziano, J. Michael
O’Donnell, Christopher
Damrauer, Scott
Liao, Katherine
A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program
title A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program
title_full A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program
title_fullStr A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program
title_full_unstemmed A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program
title_short A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program
title_sort phenome-wide association study of genes associated with covid-19 severity reveals shared genetics with complex diseases in the million veteran program
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8509103/
https://www.ncbi.nlm.nih.gov/pubmed/34642702
http://dx.doi.org/10.1101/2021.05.18.21257396
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