Fine-mapping of retinal vascular complexity loci identifies Notch regulation as a shared mechanism with myocardial

Ana Villaplana-Velasco1,2, Marie Pigeyre3, Justin Engelmann2

  • 1The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, Scotland, UK.

Insights

Retinal fractal dimension (Df) complexity may predict coronary artery disease (CAD) risk earlier than traditional methods. Genetic analysis revealed shared pathways between Df and myocardial infarction (MI), improving risk prediction models.

Area of Science:

  • Ophthalmology
  • Cardiology
  • Genetics

Background:

  • Retinal vascular complexity, measured as fractal dimension (Df), shows potential for early coronary artery disease (CAD) detection.
  • The genetic underpinnings of Df and its relationship with CAD remain poorly understood.

Purpose of the Study:

  • To investigate the genetic basis of Df.
  • To analyze the genetic correlation between Df and CAD.
  • To develop an improved predictive model for myocardial infarction (MI) using Df.

Main Methods:

  • Genome-wide association study (GWAS) in 38,000 UK Biobank participants of white British ancestry.
  • Replication of Df loci and identification of novel loci associated with Df.
  • Genetic correlation analysis between Df and CAD/MI.
  • Development and validation of a predictive model for incident MI cases.

Main Results:

  • Identified and replicated several loci associated with Df variation.
  • Confirmed significant negative genetic correlations between Df and CAD/MI.
  • Fine-mapping implicated Notch signalling pathways.
  • The developed predictive model incorporating Df and CAD polygenic risk score showed improved area under the curve (AUC=0.770) compared to existing models (AUC=0.741, AUC=0.728).

Conclusions:

  • Df provides significant risk information for MI beyond traditional demographic, lifestyle, and genetic factors.
  • Shared genetic control exists between Df and MI.
  • Df is a valuable biomarker for enhanced individualised MI risk prediction.