Analysis of whole genome sequencing and plasma metabolomics unveil genetic determinants and clinical implications for human health

Blood metabolites are critical biomarkers linking genetic variation to diverse health outcomes, exhibiting significant variability across individuals. Here, we analyze and integrate whole-genome sequencing with plasma metabolomics to investigate the genetic architecture of 313 metabolic biomarkers in up to 199,138 UK Biobank participants. Through single-variant analyses, we identify 36,105 independent signals, with 22.20% being novel. Furthermore, we pinpoint 12,361 putative causal variant-trait associations, demonstrating enhanced causal signal discovery and improved fine-mapping resolution compared with imputed array-based approaches. Rare-variant aggregate testing reveals 1,527 conditionally independent protein-coding gene-trait pairs, with 32.9% being unique to non-coding regions. We estimate the heritability at a median of h2 = 0.31, nearly tripling the heritability estimates obtained from array-based approaches. Integrating our findings with disease genetics reveals 245 potential causal associations, such as that between omega-3 fatty acids and cholelithiasis risk. Prioritizing proteins with concordant effects on metabolites and clinical outcomes revealed 410 potential targets, offering opportunities for therapeutic strategies and drug repurposing. Our open-access resource (https://metabolome-whole-genome-landscape.com/) provides a foundation for future research into metabolic pathways, disease mechanisms, and therapeutic development. Whole-genome sequencing and plasma metabolomics in ~200,000 individuals uncover the genetic basis of the metabolome and identify clinically relevant links between metabolic changes and complex diseases.