Integrative Omics Defines Metabolic Biomarkers and Genetic Regulatory Mechanisms of Mortality Risk.

ABSTRACT: The genetic and metabolic architecture of mortality risk represents a fundamental, yet poorly understood, challenge in human medicine and livestock breeding. Here serum metabolomics and multi-omics data is integrated in a designed 3-generation chicken model (n = 1,277) with divergent mortality. The analysis reveals a trade-off between heightened inflammatory responses and impaired growth in susceptible animals. To uncover the genetic underpinnings, 45,585 metabolite quantitative trait loci are identified, which are predominantly enriched among liver-specific regulatory variants. Using a machine learning approach, a robust 16-metabolite signature is established, including hexyl glucoside and pyrraline, that accurately predicts mortality risk. Importantly, these metabolites and their genetic

SUBMITTER: Liu P 

PROVIDER: S-EPMC12806298 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature