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Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium.
Tuesday,2023-10-10 11:32 America/Los_Angeles — ecterry
| Title | Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Authors | Jiang, 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, K, 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/Institutional Authors | NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Inflammation Working Group |
| Journal | bioRxiv |
| Date Published | 2023 Sep 12 |
| Abstract | <p>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 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. 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.</p> |
| DOI | 10.1101/2023.09.10.555215 |
| Alternate Journal | bioRxiv |
| PubMed ID | 37745480 |
| PubMed Central ID | PMC10515765 |
| Grant List | OT3 HL142478 / HL / NHLBI NIH HHS / United States R01 HL120393 / HL / NHLBI NIH HHS / United States U01 HG012064 / HG / NHGRI NIH HHS / United States U01 HL120393 / HL / NHLBI NIH HHS / United States OT3 HL147154 / HL / NHLBI NIH HHS / United States HHSN268201800001C / HL / NHLBI NIH HHS / United States OT3 HL142480 / HL / NHLBI NIH HHS / United States KL2 TR002490 / TR / NCATS NIH HHS / United States OT3 HL142479 / HL / NHLBI NIH HHS / United States U01 HG009088 / HG / NHGRI NIH HHS / United States R01 HL117626 / HL / NHLBI NIH HHS / United States R01 HG010297 / HG / NHGRI NIH HHS / United States OT3 HL142481 / HL / NHLBI NIH HHS / United States R01 HL163560 / HL / NHLBI NIH HHS / United States |
ePub date:
23/09