Whole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium.

TitleWhole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium.
Publication TypeJournal Article
Year of Publication2024
AuthorsJiang, M-Z, Gaynor, SM, Li, X, Van Buren, E, Stilp, A, Buth, E, Wang, FFei, Manansala, R, Gogarten, SM, Li, Z, Polfus, LM, Salimi, S, Bis, JC, Pankratz, N, Yanek, LR, Durda, P, Tracy, RP, Rich, SS, Rotter, JI, Mitchell, BD, Lewis, JP, Psaty, BM, Pratte, KA, Silverman, EK, Kaplan, RC, Avery, C, North, KE, Mathias, RA, Faraday, N, Lin, H, Wang, B, Carson, AP, Norwood, AF, Gibbs, RA, Kooperberg, C, Lundin, J, Peters, U, Dupuis, J, Hou, L, Fornage, M, Benjamin, EJ, Reiner, AP, Bowler, RP, Lin, X, Auer, PL, Raffield, LM
Corporate AuthorsNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Inflammation Working Group
JournalHum Mol Genet
Date Published2024 May 15
ISSN1460-2083
Abstract

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38ā€‰465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program (with varying sample size by trait, where the minimum sample size was nā€‰=ā€‰737 for MMP-1). We identified 22 distinct single-variant associations across 6 traits-E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin-that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

DOI10.1093/hmg/ddae050
Alternate JournalHum Mol Genet
PubMed ID38747556
Grant List / HL / NHLBI NIH HHS / United States
/ / NHGRI /
R01HL163560 / HB / NHLBI NIH HHS / United States
U01 HG009088 / HG / NHGRI NIH HHS / United States
/ / NIDA /
/ NH / NIH HHS / United States
/ / NIMH /
/ / NCI /
/ / NHLBI TOPMed Fellowship /
/ TR / NCATS NIH HHS / United States
/ / NHLBI BioData Catalyst Fellowship /
/ / NHLBI /
1OT3HL142479-01 / / BioData Catalyst /
/ / NINDS /
KL2TR002490 / NH / NIH HHS / United States