Causal Effects Between Retinal Characteristics and Cardiovascular Diseases: Insights from Genetic Correlation,...

Area of Science:

• Ophthalmology
• Cardiology
• Genetics
• Biomarkers

Background:

• Cardiovascular diseases (CVDs) are a leading cause of death globally, with increasing prevalence.
• The retina's microvasculature offers insights into systemic vascular health and disease.
• Retinal microvascular dysfunction is linked to CVDs and other systemic vascular conditions.

Purpose of the Study:

• To investigate the genetic correlation and causal relationship between retinal characteristics and CVDs.
• To explore shared etiological pathways between retinal microstructure and cardiovascular health.
• To assess the potential of retinal traits as non-invasive markers for CVD risk.

Main Methods:

• Genome-wide association study (GWAS) data from UK Biobank and FinnGen were analyzed using Linkage Disequilibrium Score Regression (LDSC) and Mendelian Randomization (MR).
• Cross-sectional study utilizing optical coherence tomography (OCT) to measure retinal layer thickness.
• Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed for CVD risk prediction.

Main Results:

• Genetically proxied thinner retinal nerve fiber layer (RNFL) correlated with increased risk of hypertension and myocardial infarction (MI).
• Genetically proxied thicker photoreceptor inner segment/outer segment (PR-IS/OS) associated with coronary heart disease and MI.
• Thinner retinal pigment epithelium (RPE) showed an inverse association with stroke risk.
• Circulating biomarkers like lipoprotein(a) (Lp(a)), LDL-C, and ApoB showed MR evidence of association with CVDs.
• Retinal layer differences and lipid relationships were directionally consistent with genetic findings in the cross-sectional cohort.

Conclusions:

• Retinal structural traits (RNFL, PR-IS/OS, RPE thickness) serve as non-invasive markers reflecting systemic vascular biology.
• MR analyses support shared etiological pathways between retinal microstructure and CVDs.
• Findings require validation in larger, diverse populations and do not confirm direct clinical causality.