Lagou · Nature genetics 2023 · Genome-wide association study meta-analysis · n=476,326

GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification.

Cited 108 times in the scientific literature.

Level 3 - non-randomized controlled study

Meta-analysis of observational cohort and cross-sectional genetic association data (graded by design strength analogy).

PubMed 37679419 · doi:10.1038/s41588-023-01462-3 · record verified 2026-08-29

What was done

Authors conducted a genome-wide association study (GWAS) meta-analysis of non-standardized random glucose (RG) measurements in 476,326 individuals without diabetes across diverse ancestries. Discovered loci were mapped using regulatory, glycosylation, and metagenomic annotations. Lower-frequency coding variants in *GLP1R* were evaluated using molecular dynamics simulations, and Mendelian randomization was performed to evaluate causal associations between blood glucose and lung function.

What was found

The meta-analysis identified 120 RG loci represented by 150 distinct signals, of which 44 loci are new for glycemic traits. These included 13 sex-dimorphic, 2 cross-ancestry, and 7 rare frequency signals. Tissue annotations highlighted the ileum and colon. Molecular dynamics simulations of *GLP1R* coding variants indicated potential benefits of genetic stratification for GLP-1R agonist therapy. Mendelian randomization showed that blood glucose modulates lung function and that pulmonary dysfunction is a complication of diabetes. The abstract reports no effect sizes, p-values, or confidence intervals.

Why it matters

This study shows that unstandardized random glucose captures unique glucoregulatory biology that conventional fasting and postprandial tests miss, revealing gastrointestinal contributions to glucose homeostasis and suggesting pharmacogenetic tailoring for GLP-1R agonists.

Limits

The abstract provides no numeric effect estimates, odds ratios, or test statistics. Therapeutic stratification claims for GLP-1R agonists rely on computational molecular dynamics simulations rather than clinical trial data. Causality regarding lung function depends on standard Mendelian randomization assumptions.

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