TY - JOUR
T1 - Genetic architecture and analysis practices of circulating metabolites in the NHLBI Trans-Omics for Precision Medicine Program
AU - Wang, Nannan
AU - Ockerman, Franklin P.
AU - Zhou, Laura Y.
AU - Grove, Megan L.
AU - Alkis, Taryn
AU - Barnard, John
AU - Bowler, Russell P.
AU - Clish, Clary B.
AU - Chung, Shinhye
AU - Drzymalla, Emily
AU - Evans, Anne M.
AU - Franceschini, Nora
AU - Gerszten, Robert E.
AU - Gillman, Madeline G.
AU - Hutton, Scott R.
AU - Kelly, Rachel S.
AU - Kooperberg, Charles
AU - Larson, Martin G.
AU - Lasky-Su, Jessica
AU - Meyers, Deborah A.
AU - Woodruff, Prescott G.
AU - Reiner, Alexander P.
AU - Rich, Stephen S.
AU - Rotter, Jerome I.
AU - Silverman, Edwin K.
AU - Vasan, Ramachandran S.
AU - Weiss, Scott T.
AU - Wong, Kari E.
AU - Wood, Alexis C.
AU - Wu, Lang
AU - Yarden, Ronit
AU - Blackwell, Thomas W.
AU - Smith, Albert V.
AU - Chen, Han
AU - Raffield, Laura M.
AU - Yu, Bing
N1 - Publisher Copyright:
© 2025 American Society of Human Genetics.
PY - 2025/11/6
Y1 - 2025/11/6
N2 - Circulating metabolite levels partly reflect the state of human health and diseases and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single-study analyses. Leveraging the rich metabolomics resources generated by the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally diverse samples. From our comparison of multiple methods, we provided a set of reasonable strategies for outlier and imputation handling to process metabolite data and show that inverse normalization by study and half-minimum imputation provide mostly similar results for pooled or meta-analysis. Following the practical analysis framework, we further performed a genome-wide association analysis on 1,135 selected metabolites using whole-genome sequencing data from 16,359 individuals passing the quality-control filters and discovered 1,775 independent loci associated with 667 metabolites. Among 160 unreported locus-metabolite pairs, we identified associations with loci locating within previously implicated metabolite-associated genes, as well as associations with loci locating in genes such as GAB3 and VSIG4 (located on the X chromosome) that may play a role in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, which were located in well-known metabolic genes such as FADS2, D2HGDH, SUGP1, and UGT2B17, strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.
AB - Circulating metabolite levels partly reflect the state of human health and diseases and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single-study analyses. Leveraging the rich metabolomics resources generated by the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally diverse samples. From our comparison of multiple methods, we provided a set of reasonable strategies for outlier and imputation handling to process metabolite data and show that inverse normalization by study and half-minimum imputation provide mostly similar results for pooled or meta-analysis. Following the practical analysis framework, we further performed a genome-wide association analysis on 1,135 selected metabolites using whole-genome sequencing data from 16,359 individuals passing the quality-control filters and discovered 1,775 independent loci associated with 667 metabolites. Among 160 unreported locus-metabolite pairs, we identified associations with loci locating within previously implicated metabolite-associated genes, as well as associations with loci locating in genes such as GAB3 and VSIG4 (located on the X chromosome) that may play a role in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, which were located in well-known metabolic genes such as FADS2, D2HGDH, SUGP1, and UGT2B17, strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.
KW - GWAS
KW - TOPMed
KW - circulating metabolites
KW - half-minimum imputation
KW - inverse normal transformation
KW - metQTLs
KW - metabolite catalog
KW - multiple studies analysis
KW - sex-stratified analysis
UR - https://www.scopus.com/pages/publications/105018211162
UR - https://www.scopus.com/pages/publications/105018211162#tab=citedBy
U2 - 10.1016/j.ajhg.2025.08.022
DO - 10.1016/j.ajhg.2025.08.022
M3 - Article
C2 - 40972578
AN - SCOPUS:105018211162
SN - 0002-9297
VL - 112
SP - 2720
EP - 2738
JO - American Journal of Human Genetics
JF - American Journal of Human Genetics
IS - 11
ER -