Genetic Susceptibility to Hidradenitis Suppurativa and Predisposition to Cardiometabolic Disease.

Abstract

Importance: Hidradenitis suppurativa (HS) is associated with an increased prevalence of cardiovascular diseases compared with the general population. Any association between polygenic risk for HS, risk of incident cardiometabolic outcomes, and the plasma proteome is unclear.

Objective: To investigate the genetic correlation between HS and cardiometabolic disease.

Design, setting, and participants: This cohort study used a polygenic risk score (PRS) for HS to examine the risks of coronary artery disease (CAD) and diabetes and identify changes in the plasma proteome in individuals of European ancestry from the UK Biobank. Participants were enrolled from January 1, 2006, to December 31, 2010. End of follow-up was January 1, 2023. Correlations were assessed between HS susceptibility and cardiometabolic traits using linkage disequilibrium score regression. Odds ratios were assessed in logistic regressions. The risk of incident CAD and diabetes was estimated in cause-specific survival models designed as time-to-event analyses.

Exposure: The PRS for HS.

Main outcomes and measures: Main outcomes were CAD and diabetes diagnosis measured by logistic regressions and incident disease measured by Cox proportional hazards regression models adjusted for sex, age, body mass index, and smoking status.

Results: The study included 391 481 individuals (median [IQR] age, 58 [51-64] years; 209 235 [53%] female). Genetic variants for HS correlated significantly with variants associated with CAD, diabetes, and plasma levels of high-density lipoprotein cholesterol, triglycerides, and C-reactive protein. Compared with the low-risk group, a high PRS for HS (≥75th percentile) conferred odds ratios of 1.09 (95% CI, 1.06-1.12; P < .001) for CAD and 1.13 (95% CI, 1.10-1.17; P < .001) for diabetes. Estimates remained consistent when examining only incident CAD and diabetes. The PRS for HS was significantly associated with altered expression of 58 plasma proteins. Integrating this proteomic profile and the PRS for HS in a machine learning model improved prediction of CAD and diabetes compared with a reference model based on sex, age, and body mass index.

Conclusions and relevance: These findings suggest that a high genetic risk of HS is associated with increased risk of subsequent CAD and diabetes and altered composition of the plasma proteome. Additional investigation into the identified proteins and their potential roles as drug targets is warranted.