Artificial intelligence-driven metabolomics of retinal nerve fibre layer to profile risks of mortality and cardiometabolic diseases.

ABSTRACT: Retinal nerve fibre layer (RNFL) is a non-invasive structural biomarker of cardiometabolic health, yet its biological underpinnings remain unknown. Here, we integrate advanced retinal optical biopsy and artificial intelligence (AI) algorithms with two complementary metabolomic assays across ethnically diverse cohorts to elucidate the metabolic basis underlying RNFL degeneration and its link to cardiometabolic disease (CMD) in Western cohort and Eastern cohort (Guangzhou Diabetic Eye Study, GDES). We identify 26 metabolic biomarkers significantly associated with RNFL thickness, most of which (ranging from 19 to 26) are linked to HDL composition and lipid transport, mediating a substantial proportion of the RNFL-CMD association (e.g., 63.7% for type 2 diabetes and 44.7% for myocardial infarc

SUBMITTER: Yang S 

PROVIDER: S-EPMC12698701 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature