An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility.

dc.contributor.author

Wang, Liuyang

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Balmat, Thomas J

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Antonia, Alejandro L

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Constantine, Florica J

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Henao, Ricardo

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Burke, Thomas W

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Ingham, Andy

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McClain, Micah T

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Tsalik, Ephraim L

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Ko, Emily R

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Ginsburg, Geoffrey S

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DeLong, Mark R

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Shen, Xiling

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Woods, Christopher W

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Hauser, Elizabeth R

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Ko, Dennis C

dc.date.accessioned

2023-04-01T16:23:50Z

dc.date.available

2023-04-01T16:23:50Z

dc.date.issued

2021-05

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2023-04-01T16:23:48Z

dc.description.abstract

Background

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.

Results

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)) 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 associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.

Conclusions

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. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .
dc.identifier

10.1186/s13073-021-00904-z

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1756-994X

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1756-994X

dc.identifier.uri

https://hdl.handle.net/10161/26955

dc.language

eng

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Springer Science and Business Media LLC

dc.relation.ispartof

Genome medicine

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10.1186/s13073-021-00904-z

dc.subject

Humans

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Genetic Predisposition to Disease

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Multifactorial Inheritance

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Linkage Disequilibrium

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Polymorphism, Single Nucleotide

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Databases, Nucleic Acid

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Genome-Wide Association Study

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COVID-19

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SARS-CoV-2

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An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility.

dc.type

Journal article

duke.contributor.orcid

Wang, Liuyang|0000-0001-9556-2361

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Henao, Ricardo|0000-0003-4980-845X

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Burke, Thomas W|0000-0003-0592-5822

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Tsalik, Ephraim L|0000-0002-6417-2042

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Ginsburg, Geoffrey S|0000-0003-4739-9808

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Shen, Xiling|0000-0002-4978-3531

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Woods, Christopher W|0000-0001-7240-2453

duke.contributor.orcid

Hauser, Elizabeth R|0000-0003-0367-9189

duke.contributor.orcid

Ko, Dennis C|0000-0002-0113-5981

pubs.begin-page

83

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1

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Duke

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Pratt School of Engineering

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School of Medicine

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School of Nursing

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Faculty

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Staff

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Nursing

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Basic Science Departments

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Clinical Science Departments

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Institutes and Centers

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Biostatistics & Bioinformatics

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Cell Biology

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Molecular Genetics and Microbiology

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Electrical and Computer Engineering

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Medicine

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Pathology

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Medicine, Cardiology

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Medicine, General Internal Medicine

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Medicine, Infectious Diseases

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Duke Cancer Institute

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Duke Human Vaccine Institute

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Institutes and Provost's Academic Units

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University Institutes and Centers

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Duke Global Health Institute

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Duke Molecular Physiology Institute

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Initiatives

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Duke Science & Society

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Duke Center for Applied Genomics and Precision Medicine

pubs.publication-status

Published

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13

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