Genome-wide association analysis and replication in 810,625 individuals with varicose veins

Waheed-Ul-Rahman Ahmed1, Sam Kleeman2, Michael Ng1

  • 1Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Windmill Road, Oxford, OX3 7LD, UK.

Insights

This large genetic study identified 49 signals for varicose veins, revealing insights into its heritability and potential therapeutic targets. Findings may improve risk prediction for this common vascular condition.

Area of Science:

  • Genetics
  • Vascular Biology
  • Epidemiology

Background:

  • Varicose veins affect one-third of Western populations, leading to costly venous ulceration.
  • A positive family history is common, with an estimated heritability of 17%.
  • Current treatments include compression stockings and surgical ablation.

Purpose of the Study:

  • To conduct the largest genome-wide association study (GWAS) for varicose veins.
  • To identify genetic susceptibility loci and associated genes for varicose veins.
  • To explore biological pathways and therapeutic targets implicated in varicose veins.

Main Methods:

  • A two-stage GWAS involving over 400,000 individuals from UK Biobank and 23andMe.
  • Analysis of 135,514 cases and 675,111 controls.
  • Gene mapping, pathway analysis, and polygenic risk score (PRS) development.

Main Results:

  • Discovery of 49 independent signals at 46 susceptibility loci for varicose veins.
  • Identification of 237 candidate genes, with several showing biological plausibility for therapeutic targeting.
  • Pathway enrichment in extracellular matrix, inflammation, angiogenesis, vascular smooth muscle cell migration, and apoptosis.
  • Demonstration of PRS utility in predicting varicose veins surgery risk.

Conclusions:

  • This study significantly expands the understanding of the genetic architecture of varicose veins.
  • Identified loci and genes offer novel avenues for therapeutic interventions.
  • Genetic risk scores show potential for clinical application in predicting disease progression and surgical need.

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