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Latent Genetic Factors in Pleiotropy

Definition
AI-generated

In pleiotropy research, a latent genetic variable is an unobserved factor that captures shared genetic influence across multiple measured traits—estimated, for example, via factor analysis, Genomic SEM, or related multivariate models on GWAS summary data.

Topics
Post-GWAS
Related
Genetic Correlation Genomic Structural Equation Modeling (Genomic SEM) Matrix Factorization for Pleiotropy

Why it matters in GWAS

Latent factors summarize high-dimensional cross-trait architecture, can improve interpretability over many pairwise r_g estimates, and connect observed phenotypes to simpler genetic dimensions.

Example usage

"A replication step checks whether Latent Genetic Factors in Pleiotropy assumptions remain stable across cohorts."

Genetic Correlation Genomic Structural Equation Modeling (Genomic SEM) Matrix Factorization for Pleiotropy Multi-Trait GWAS Pleiotropy Principal Component Analysis (PCA)
Related-term network

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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

  • Grotzinger AD, et al. (2019). Genomic structural equation modelling provides insights into multivariate genetic architecture of complex traits. Nat Hum Behav.
  • Jee J, et al. (2026). The pleiotropic landscape of the human genome. Nat Rev Genet. https://doi.org/10.1038/s41576-025-00908-0
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