Shared genomic architecture between COVID-19 severity and numerous clinical and physiologic parameters revealed by LD score regression analysis.

Journal Article (Journal Article)

The COVID-19 pandemic has produced broad clinical manifestations, from asymptomatic infection to hospitalization and death. Despite progress from genomic and clinical epidemiology research, risk factors for developing severe COVID-19 are incompletely understood and identification of modifiable risk factors is desperately needed. We conducted linkage disequilibrium score regression (LDSR) analysis to estimate cross-trait genetic correlation between COVID-19 severity and various polygenic phenotypes. To attenuate the genetic contribution of smoking and BMI, we further conducted sensitivity analyses by pruning genomic regions associated with smoking/BMI and repeating LDSR analyses. We identified robust positive associations between the genetic architecture of severe COVID-19 and both BMI and smoking. We observed strong positive genetic correlation (rg) with diabetes (rg = 0.25) and shortness of breath walking on level ground (rg = 0.28) and novel protective associations with vitamin E (rg = - 0.53), calcium (rg = - 0.33), retinol (rg = - 0.59), Apolipoprotein A (rg = - 0.13), and HDL (rg = - 0.17), but no association with vitamin D (rg = - 0.02). Removing genomic regions associated with smoking and BMI generally attenuated the associations, but the associations with nutrient biomarkers persisted. This study provides a comprehensive assessment of the shared genetic architecture of COVID-19 severity and numerous clinical/physiologic parameters. Associations with blood and plasma-derived traits identified biomarkers for Mendelian randomization studies to explore causality and nominates therapeutic targets for clinical evaluation.

Full Text

Duke Authors

Cited Authors

  • Byun, J; Han, Y; Walsh, KM; Park, AS; Bondy, ML; Amos, CI

Published Date

  • February 3, 2022

Published In

Volume / Issue

  • 12 / 1

Start / End Page

  • 1891 -

PubMed ID

  • 35115602

Pubmed Central ID

  • PMC8814062

Electronic International Standard Serial Number (EISSN)

  • 2045-2322

Digital Object Identifier (DOI)

  • 10.1038/s41598-022-05832-5

Language

  • eng

Conference Location

  • England