Predictive Model for Peyronie’s Disease: Genetics, Risk Factors, and Ultrasound Insights

Peyronie’s Disease (PD) is a complex condition with unclear pathophysiology, though genetic predisposition is strongly suspected. This study utilized the UK Biobank (UKB), a cohort of approximately 500,000 participants aged 40–69, to investigate genetic and clinical risk factors for PD. Over a median follow-up of 12.5 years, 1,227 PD cases and 228,420 controls were identified using ICD codes. Logistic regression, adjusted for age and genetic background, was employed to analyze clinical risk factors such as age, obesity, Dupuytren’s contracture (DC), type 2 diabetes mellitus (T2D), hypertension, coronary artery disease (CAD), and low testosterone. Polygenic scores (PGS) of associated traits—calculated from genome-wide association studies—revealed significant correlations with PD, particularly for DC, T2D, and CAD. These findings indicate shared genetic etiologies, reducing the influence of external biases. Importantly, PD risk increased significantly with higher PGS for these factors (p<0.0001), confirming a genetic predisposition. The study also highlights the potential role of ultrasound in assessing PD-associated fibrotic changes, offering a non-invasive method to support genetic and clinical risk profiling. The results emphasize that genetic probabilities (Gen-ProbPD) can predict PD risk, aiding in early identification and counseling of at-risk individuals. The robust dataset and bias controls strengthen the validity of these findings, contributing to a better understanding of PD’s genetic and clinical underpinnings.