Skip to content

Multi-Trait GWAS

Definition
AI-generated

Multi-trait GWAS jointly models association with two or more traits—using summary-statistic correlation structure, multivariate mixed models, or related frameworks—to boost power, estimate shared genetic architecture, and characterize cross-trait effects at loci.

Topics
GWAS
Related
Genetic Correlation Genomic Structural Equation Modeling (Genomic SEM) GWAS Summary Statistics

Why it matters in GWAS

Correlated traits share genetic signal; joint analysis can detect loci missed in single-trait scans and supports pleiotropy dissection and interpretation of genetic correlation.

Example usage

"We ran a multi-trait GWAS of related glycemic endpoints to increase power and summarize cross-trait effects at each locus."

Genetic Correlation Genomic Structural Equation Modeling (Genomic SEM) GWAS Summary Statistics Joint Fine-Mapping LD Score Regression Matrix Factorization for Pleiotropy Pleiotropy Pleiotropy Dissection Trait
Related-term network

Click any node to open that term page.

Node order. The current term is first. Next come every page linked from Related terms, in the same top-to-bottom order as that list. Then new terms appear in two-hop layers: for each of those direct neighbors (in that same order), their related terms are appended if not already listed. A third pass does the same for two-hop nodes. The walk stops when a fixed maximum number of nodes is reached.

References

  • Jee J, et al. (2026). The pleiotropic landscape of the human genome. Nat Rev Genet. https://doi.org/10.1038/s41576-025-00908-0
  • Turley P, et al. (2018). Multi-trait analysis of GWAS. Nat Genet.
← Multi-Omics Multiallelic Variant →

Last updated (UTC · Git history)