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Clinical and Genetic Determinants of Varicose Veins Prospective, Community-Based Study of approximate to 500 000 Individuals

Fukaya, Eri (author)
Stanford Univ, Sch Med, Dept Surg, Div Vasc Surg, Stanford, CA 94305 USA
Flores, Alyssa M. (author)
Stanford Univ, Sch Med, Dept Surg, Div Vasc Surg, Stanford, CA 94305 USA
Lindholm, Daniel P, 1982- (author)
Uppsala universitet,Kardiologi,Uppsala kliniska forskningscentrum (UCR)
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Gustafsson, Stefan (author)
Uppsala universitet,Science for Life Laboratory, SciLifeLab,Molekylär epidemiologi
Zanetti, Daniela (author)
Stanford Univ, Sch Med, Dept Med, Div Cardiovasc Med, Stanford, CA 94305 USA
Ingelsson, Erik (author)
Stanford Univ, Sch Med, Dept Med, Div Cardiovasc Med, Stanford, CA 94305 USA;Stanford Cardiovasc Inst, Stanford, CA USA
Leeper, Nicholas J. (author)
Stanford Univ, Sch Med, Dept Surg, Div Vasc Surg, Stanford, CA 94305 USA;Stanford Univ, Sch Med, Dept Med, Div Cardiovasc Med, Stanford, CA 94305 USA;Stanford Cardiovasc Inst, Stanford, CA USA
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 (creator_code:org_t)
2018
2018
English.
In: Circulation. - 0009-7322 .- 1524-4539. ; 138:25, s. 2869-2880
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • BACKGROUND: 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. 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 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 (9577 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. RESULTS: 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% Cl, 1.51-2.01; P<0.0001). A genomewide 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=2.07x10(-16)). CONCLUSIONS: 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.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Kardiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)

Keyword

epidemiology
genetics
genome-wide association study
varicose veins

Publication and Content Type

ref (subject category)
art (subject category)

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