The contribution of genetic determinants of blood gene expression and splicing to molecular phenotypes and health outcomes

genetics
multi-omics
eQTL
sQTL
causal inference
disease mechanisms
  • Topic: Investigating the gene-regulatory mechanisms (eQTLs and sQTLs) of nonprotein-coding genetic variants in blood and their causal contribution to 3,430 molecular phenotypes (proteins, metabolites, lipids) and health outcomes.
  • Method: Mapped eQTLs and sQTLs in 4,732 individuals and used colocalization and mediation analyses to link these regulatory variants to downstream molecular and disease traits.
  • Impact: Identified 222 molecular phenotypes significantly mediated by gene expression or splicing, providing mechanistic insights into diseases (e.g., \(WARS1\) in hypertension) and offering a valuable public resource for human genetic etiology.
Published

23 January 2026

PubMed: 40038547 DOI: 10.1038/s41588-025-02096-3 Overview generated by: Gemini 2.5 Flash, 27/11/2025

Background and Objective

The biological mechanisms through which the majority of nonprotein-coding genetic variants influence disease risk remain largely unknown. These variants often function by regulating gene activity. The objective of this study was to comprehensively investigate these gene-regulatory mechanisms by mapping genetic determinants of gene expression and splicing in blood and integrating them with various molecular and health outcomes.

Methods: Multi-Omics QTL Mapping and Integration

The researchers conducted a comprehensive multi-omics study using data from 4,732 participants to identify quantitative trait loci (QTLs):

  1. QTL Mapping: They mapped gene expression QTLs (eQTLs) and splicing QTLs (sQTLs) in blood using bulk RNA sequencing, identifying cis-QTLs for 17,233 genes and 29,514 splicing events.
  2. Multi-omics Integration: They integrated the identified genetic associations with data on protein, metabolite, and lipid levels from the same individuals.
  3. Causal Inference: They employed colocalization analyses to pinpoint instances where the same causal genetic variant affects both a transcriptional/splicing phenotype and a molecular/health outcome.
  4. Mediation Analysis: They quantified the relative contribution of genetic effects at loci with shared etiology to determine which molecular phenotypes are significantly mediated by gene expression or splicing.

Key Results and Significance

The study successfully bridged the gap between genetic variation and downstream molecular and clinical phenotypes:

  • Extensive Shared Genetic Etiology: Colocalization analyses revealed a shared genetic association signal with gene expression or splicing for 3,430 proteomic and metabolomic traits.
  • Mediated Molecular Phenotypes: They found that 222 molecular phenotypes were significantly mediated by gene expression or splicing, providing strong evidence for gene-regulatory causality.
  • Mechanistic Insights: The approach uncovered specific gene-regulatory mechanisms at disease loci with potential therapeutic relevance, such as \(WARS1\) in hypertension, \(IL7R\) in dermatitis, and \(IFNAR2\) in COVID-19$.
  • Public Resource: The findings provide a comprehensive, open-access resource on the shared genetic etiology across transcriptional phenotypes, molecular traits, and health outcomes (https://IntervalRNA.org.uk).