Abstract 052: Clinical and Genetic Determinants of Varicose Veins: a Prospective, Community-Based Study of ~500,000 Individuals

Abstract

Background: Varicose veins are a common problem with no approved medical therapies. While it is believed that varicose vein pathogenesis is multifactorial, there is a limited understanding of the genetic and environmental factors that contribute to their formation. Large-scale studies of risk factors for varicose veins may highlight important aspects of pathophysiology and identify groups at increased risk for disease. Methods: We applied machine learning to agnostically search for risk factors of varicose veins in 493,519 individuals in the UK Biobank. Predictors were further studied using univariable and multivariable Cox regression analysis. A genome-wide association study (GWAS) of varicose veins was also performed among 337,536 individuals (9,577 cases) of white British descent, followed by eQTL and pathway analyses. Because height emerged as a new candidate predictor, we used LD score regression to estimate the genetic correlation between height and varicose veins. Finally, we performed Mendelian randomization analyses to assess for a causal role for height in varicose vein disease. Results: Machine learning confirmed several known (age, gender, obesity, pregnancy, history of deep vein thrombosis) and identified several new risk factors for varicose vein disease. The most important novel predictors were leg bioimpedance (HR: 0.44, 95% CI: 0.39-0.50, P < 0.0001) and height (HR: 1.74; 95% CI: 1.51-2.01, P < 0.0001), which both remained independently associated with varicose veins after adjusting for traditional risk factors in Cox regression. A GWAS identified 30 new genome-wide significant loci, identifying pathways involved in vascular development and skeletal/limb biology. Mendelian randomization analysis provided evidence that increased height is causally related to varicose veins (IVW: beta = 0.266, P = 1.28 x 10 -16 ). Conclusions: Using data from nearly half a million individuals, we identified novel clinical and genetic risk factors which provide pathophysiological insights and could help future improvements of treatment of varicose vein disease.