Varicose veins are a common problem with no approved medical therapies. Although it is believed that varicose vein pathogenesis is multifactorial, there is 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.
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 with univariable and multivariable Cox regression analyses (2441 incident events). A genome-wide association study of varicose veins was also performed among 337,536 unrelated individuals (9,577 cases) of white British descent, followed by expression quantitative loci and pathway analyses. Because height emerged as a new candidate risk factor, we performed mendelian randomization analyses to assess a potential causal role for height in varicose vein development.
Machine learning confirmed several known (age, sex, obesity, pregnancy, history of deep vein thrombosis) and identified several new risk factors for varicose vein disease, including height. After adjustment for traditional risk factors in Cox regression, greater height remained independently associated with varicose veins (hazard ratio for upper versus lower quartile, 1.74; 95% CI, 1.51-2.01; P<0.0001). A genome-wide association study 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 (inverse-variance weighted: odds ratio, 1.26; P=2.07 10-16).
Using data from nearly a half-million individuals, we present a comprehensive genetic and epidemiological study of varicose veins. We identified novel clinical and genetic risk factors that provide pathophysiological insights and could help future improvements of treatment of varicose vein disease.
Causal associations of circulating biomarkers with cardiovascular disease
The overall goal of this project is to study the causal roles of the 36 biomarkers currently being assayed in UK Biobank for development of coronary heart disease, stroke and heart failure. Knowledge about causal relations of these 36 biomarkers with cardiovascular outcomes will give important insights regarding the etiological understanding of these diseases and accelerate development of new prevention strategies, including druggable targets. Hence, the proposed research does meet UK Biobank's stated purpose via improving the prevention and treatment of heart disease and stroke.
First, we will study associations of 36 circulating biomarkers representing different biological systems with incidence of coronary heart disease, stroke and heart failure.
Second, by combing data from the UK Biobank gene analyses with the biomarker data, we will perform genetic studies across the whole human genome for all 36 biomarkers to establish common genetic variation associated with respective biomarker.
Third, we will perform so called Mendelian randomization analyses to study whether the biomarkers are causally related to coronary heart disease, stroke and heart failure.
Full cohort (n=502,650).
|Lead investigator:||Prof. Themistocles Assimes|
|Lead institution:||Stanford University|