rs10799708 - USP48

Magnitude 2.0 · 1 study on file

Reported associations

• Improved genetic discovery and fine-mapping resolution through multivariate latent factor analysis of high-dimensional traits - Cell genomics (2025) · Zhou F, Astle WJ, Butterworth AS, Asimit JL · PubMed 40220762

  ABSTRACT: Summary Genome-wide association studies (GWASs) of high-dimensional traits, such as blood cell or metabolic traits, often use univariate approaches, ignoring trait relationships. Biological mechanisms generating variation in high-dimensional traits can be captured parsimoniously through a GWAS of latent factors. Here, we introduce flashfmZero, a zero-correlation latent-factor-based multi-trait fine-mapping approach. In an application to 25 latent factors derived from 99 blood cell traits in the INTERVAL cohort, we show that latent factor GWASs enable the detection of signals generating sub-threshold associations with several blood cell traits. The 99% credible sets (CS99) from flashfmZero were equal to or smaller in size than those from univariate fine-mapping of blood cell trait

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