Cross-Trait Genome-Wide Association Studies Identify Shared Genetic Risk Loci Between Psoriasis and Metabolic Syndrome and Their Associated Traits

Abstract

Background:

Psoriasis (PsO) demonstrates frequent co-occurrence with metabolic syndrome (MetS). Nevertheless, the shared genetic architecture underlying both pathological conditions remains incompletely characterized. This investigation sought to examine genetic correlations between PsO and multiple MetS-associated traits, and to identify shared genetic risk loci and genes contributing to their coexistence.

Methods:

Genome-wide association study data for PsO, MetS, and related traits in European populations were integrated to evaluate genetic associations between traits and to identify shared loci. Bayesian colocalization analysis was applied to determine whether association signals for different traits at the same locus were attributable to a common causal variant. Functional annotation and gene mapping were conducted for shared loci, followed by functional classification and pathway enrichment analyses of pleiotropic gene sets. In addition, summary data-based Mendelian randomization and transcriptome-wide association study analyses were applied to prioritize candidate genes with potential therapeutic relevance.

Results:

Significant genetic associations were observed between PsO and five metabolic traits, including body mass index, high-density lipoprotein cholesterol, triglycerides, waist circumference, and type 2 diabetes mellitus, while MetS, as a composite trait, also exhibited a genetic association with PsO. Pleiotropic Analysis under composite null hypothesis (PLACO) analysis revealed a total of 141 shared risk loci, with 22 loci substantiated by Bayesian colocalization analysis findings (PP.H4 ≥ 0.75). Multimarker analysis of genomic annotation analysis identified 195 distinct pleiotropic genes. The pathway enrichment analysis indicated that these genes were predominantly involved in immune and inflammatory pathways, transcriptional and epigenetic regulation, autophagy, and lipid–cholesterol metabolism, indicating that such biological processes may contribute to the shared genetic background of PsO and MetS-related traits. Through integrative evidence from multiple analytical approaches, three candidate therapeutic target genes, namely, KAT8, STX4, and VKORC1, were prioritized.

Conclusions:

Shared genetic loci, pleiotropic genes, and core biological pathways between PsO and multiple MetS-related traits were identified, and potential intervention targets were highlighted, providing genetic evidence to support subsequent functional investigations.