A groundbreaking genetic analysis of UK Biobank data has uncovered significant associations between hidradenitis suppurativa (HS) genetic susceptibility and increased risks of major cardiometabolic diseases, potentially reshaping our understanding of these conditions' interconnected pathways.
The extensive study, published in JAMA Dermatology, analyzed data from 391,418 adults of European ancestry with a median age of 58 years. Researchers employed polygenic risk scores (PRS) to evaluate genetic correlations between HS and various metabolic conditions.
Genetic Correlations and Risk Patterns
The analysis revealed strong positive genetic correlations between HS and several conditions:
- Coronary artery disease (CAD): genetic correlation of 0.25
- Type 2 diabetes: genetic correlation of 0.30
- Elevated triglyceride levels: genetic correlation of 0.20
- Increased C-reactive protein levels: genetic correlation of 0.31
During the median follow-up period of 13.7 years, 26,994 participants developed CAD and 13,153 were diagnosed with diabetes. Notably, individuals in the highest genetic risk category (≥75th PRS percentile) demonstrated a 9% higher risk of CAD and a 13% greater risk of diabetes compared to those in the lowest risk group.
Metabolic Impact and Protein Expression
The study identified significant alterations in plasma proteome profiles associated with HS genetic risk. Each standard deviation increase in the HS polygenic risk score corresponded to a 0.14-unit increase in body mass index (BMI), highlighting the metabolic implications of the condition.
The cumulative incidence rates over 15 years further emphasized the clinical significance of these findings. High-risk individuals showed an 8.22% incidence of CAD compared to 7.81% in the low-risk group. Similarly, diabetes incidence was 4.17% in the high-risk group versus 3.66% in the low-risk cohort.
Clinical Implications and Future Directions
These findings reinforce previous observations linking HS with increased cardiovascular and metabolic risks. The shared pathophysiologic pathways, particularly involving obesity as a common risk factor, suggest potential opportunities for integrated treatment approaches.
The study's robust methodology and large sample size provide compelling evidence for the genetic basis of these associations. However, the researchers acknowledge limitations, including potential healthy volunteer bias in the UK Biobank cohort and the need for further validation of the polygenic risk scores.
The research team recommends future investigations focus on identifying specific altered plasma proteins as potential therapeutic targets, which could lead to more effective treatments for patients affected by these interconnected conditions.
