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An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility
While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this cruc...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7781346/ https://www.ncbi.nlm.nih.gov/pubmed/33398303 http://dx.doi.org/10.1101/2020.12.20.20248572 |
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author | Wang, Liuyang Balmat, Thomas J. Antonia, Alejandro L. Constantine, Florica J. Henao, Ricardo Burke, Thomas W. Ingham, Andy McClain, Micah T. Tsalik, Ephraim L. Ko, Emily R. Ginsburg, Geoffrey S. DeLong, Mark R. Shen, Xiling Woods, Christopher W. Hauser, Elizabeth R. Ko, Dennis C. |
author_facet | Wang, Liuyang Balmat, Thomas J. Antonia, Alejandro L. Constantine, Florica J. Henao, Ricardo Burke, Thomas W. Ingham, Andy McClain, Micah T. Tsalik, Ephraim L. Ko, Emily R. Ginsburg, Geoffrey S. DeLong, Mark R. Shen, Xiling Woods, Christopher W. Hauser, Elizabeth R. Ko, Dennis C. |
author_sort | Wang, Liuyang |
collection | PubMed |
description | While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. |
format | Online Article Text |
id | pubmed-7781346 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-77813462021-01-05 An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility Wang, Liuyang Balmat, Thomas J. Antonia, Alejandro L. Constantine, Florica J. Henao, Ricardo Burke, Thomas W. Ingham, Andy McClain, Micah T. Tsalik, Ephraim L. Ko, Emily R. Ginsburg, Geoffrey S. DeLong, Mark R. Shen, Xiling Woods, Christopher W. Hauser, Elizabeth R. Ko, Dennis C. medRxiv Article While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. Cold Spring Harbor Laboratory 2020-12-22 /pmc/articles/PMC7781346/ /pubmed/33398303 http://dx.doi.org/10.1101/2020.12.20.20248572 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Wang, Liuyang Balmat, Thomas J. Antonia, Alejandro L. Constantine, Florica J. Henao, Ricardo Burke, Thomas W. Ingham, Andy McClain, Micah T. Tsalik, Ephraim L. Ko, Emily R. Ginsburg, Geoffrey S. DeLong, Mark R. Shen, Xiling Woods, Christopher W. Hauser, Elizabeth R. Ko, Dennis C. An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility |
title | An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility |
title_full | An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility |
title_fullStr | An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility |
title_full_unstemmed | An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility |
title_short | An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility |
title_sort | atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into covid-19 susceptibility |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7781346/ https://www.ncbi.nlm.nih.gov/pubmed/33398303 http://dx.doi.org/10.1101/2020.12.20.20248572 |
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