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 38 465 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 n = 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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1429-1441 |
| Number of pages | 13 |
| Journal | Human molecular genetics |
| Volume | 33 |
| Issue number | 16 |
| DOIs | |
| State | Published - Aug 15 2024 |
Funding
The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 03/31/2020. In the past three years, Edwin K. Silverman received grant support from Bayer and Northpond Laboratories. Molecular data for the TOPMed program was supported by the National Heart, Lung and Blood Institute (NHLBI). Study-specific omics support information can be found in the supplement. Core support including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering, were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonization, data management, sample-identity QC, and general program coordination, were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. TOPMed specific acknowledgments for studies are included in Table S2. Additional study specific acknowledgments are included under cohort descriptions in Table S1. Support for this work was provided by the National Institutes of Health, National Heart, Lung, and Blood Institute, through the BioData Catalyst program (awards 1OT3HL142479-01, 1OT3HL142478-01, 1OT3HL142481-01, 1OT3HL142480-01, and 1OT3HL147154). The authors wish to acknowledge the contributions of the consortium working on the development of the NHLBI BioData Catalyst (BDC) ecosystem. L.M.R., S.G., and Z.L. were supported by NHLBI BioData Catalyst Fellowship program. X.Li was supported by NHLBI TOPMed Fellowship program. L.M.R. was also supported by R01HG010297. X.Lin was supported by NHLBI R01HL163560 and NHGRI U01 HG009088 and U01HG012064. E.J.B. was supported by 75N92019D00031, 1RO1 HL64753, R01 HL076784, 1R01 AG028321, and R01HL092577. H.L. was supported by U01AG068221. B.M.P. was supported by R01HL105756. J.C.B. was supported by R01HL105756. The project described was also supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant KL2TR002490 (L.M.R.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 03/31/2020. The authors wish to acknowledge the contributions of the consortium working on the development of the NHLBI BioData Catalyst\u00AE (BDC) ecosystem. L.M.R., S.G., and Z.L. were supported by NHLBI BioData Catalyst Fellowship program. X.Li was supported by NHLBI TOPMed Fellowship program. L.M.R. was also supported by R01HG010297. X.Lin was supported by NHLBI R01HL163560 and NHGRI U01 HG009088 and U01HG012064. E.J.B. was supported by 75N92019D00031, 1RO1 HL64753, R01 HL076784, 1R01 AG028321, and R01HL092577. H.L. was supported by U01AG068221. B.M.P. was supported by R01HL105756. J.C.B. was supported by R01HL105756. The project described was also supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant KL2TR002490 (L.M.R.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Molecular data for the TOPMed program was supported by the National Heart, Lung and Blood Institute (NHLBI). Study-specific omics support information can be found in the supplement. Core support including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering, were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonization, data management, sample-identity QC, and general program coordination, were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. TOPMed specific acknowledgments for studies are included in . Additional study specific acknowledgments are included under cohort descriptions in . Support for this work was provided by the National Institutes of Health, National Heart, Lung, and Blood Institute, through the BioData Catalyst program (awards 1OT3HL142479-01, 1OT3HL142478-01, 1OT3HL142481-01, 1OT3HL142480-01, and 1OT3HL147154).
Keywords
- Trans-Omics for Precision Medicine (TOPMed) consortium
- genome-wide association studies
- inflammation biomarkers
- rare variant aggregate test
- whole genome sequencing data
ASJC Scopus subject areas
- Molecular Biology
- Genetics
- Genetics(clinical)