LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Phenome-wide Mendelian randomisation analysis identifies causal factors for age-related macular degeneration

Photo from wikipedia

Introduction: Age-related macular degeneration (AMD) is the leading cause of blindness in the industrialised world and is projected to affect 288 million people worldwide by 2040. Aiming to identify causal… Click to show full abstract

Introduction: Age-related macular degeneration (AMD) is the leading cause of blindness in the industrialised world and is projected to affect 288 million people worldwide by 2040. Aiming to identify causal factors for this common disorder, we designed and applied a phenome-wide Mendelian randomisation (MR) approach to identify therapeutic targets and avenues for future research. Methods: We evaluated the effect of 4,591 exposure traits on early AMD using univariable MR. Statistically significant results were explored further using validation in an advanced AMD cohort, MR Bayesian model averaging (MR BMA) and multivariable MR. Results: 44 traits were found to be putatively causal for early AMD in univariable analysis. MR BMA of lipid traits suggested a causal role for serum sphingomyelin (marginal inclusion probability=0.76, model averaged causal effect=0.29). Univariable MR analysis supported roles for complement and immune cell traits. Serum proteins were found to have significant relationships with AMD including S100-A5 (Odds ratio (OR)= 1.07, p = 6.80E-06), cathepsin F (OR=1.10, p = 7.16E-05) and serine palmitoyltransferase 2 (OR= 0.86, p value=1.00E-03). Conclusions: The results of this study support several putative causal factors in AMD and highlight avenues for future clinical research.

Keywords: related macular; causal factors; age related; macular degeneration; phenome wide; analysis

Journal Title: eLife
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.