Deep-learning-derived glaucoma-related endophenotypes enable novel genome-wide genetic and functional discovery

Abstract The genetic architecture of primary open-angle glaucoma (POAG), a leading cause of irreversible blindness, remains largely unexplained due to the reliance of previous genome-wide association studies (GWAS) on imprecise phenotypes from electronic health records. Here, we overcome this with a disease-trained, task-transfer machine learning (ML) framework that learns glaucoma-related damage patterns from a large clinical repository of 8,323 glaucoma patients. We showed that ML optical coherence tomography (OCT)-derived endophenotypes trained on 18,985 OCT scans from these patients identified novel loci associated with POAG. By applying the derived endophenotypes to 47,908 UK Biobank participants, we performed GWAS in European, African, and Asian ancestral groups followed by cross-ancestry meta-analyses. In total, we identified 36 and 43 LD-independent GWAS loci that passed genome-wide significance in the EUR and cross-ancestry meta-analysis, respectively. About two thirds of the identified loci overlapped with previously reported POAG related associations, demonstrating the validity of our approach. Importantly, more than a third (21) of the loci were novel to glaucoma. Extensive functional analyses, including Bayesian colocalization analysis, gene-based association tests, Mendelian randomization, and single-cell enrichment analysis, converged on 11 high-confidence gene effectors, five of which are novel to glaucoma. These genes support Wnt-mediated outflow dysfunction and retinal ganglion cell vulnerability in POAG pathogenesis and are potential actionable drug targets. Our findings expanded POAG genetic associations, provided mechanistic insights at cell-type resolution, and proposed plausible putative causal genes. This study provides a powerful, generalizable ML-driven strategy for accelerating the discovery of disease mechanisms and therapeutic targets for complex diseases. One Sentence Summary A ML framework that bridged clinical eye scans with biobank genetics found 21 new genetic loci and 11 putative causal genes for glaucoma Competing Interest Statement N. Zebardast serves as a consultant for Sanofi/Genzyme. Funding Statement National Institutes of Health grants R01 EY036518 (NZ), R01 EY036222 (MW), R01 EY030575 (TE), NIH/NEI R01EY031424 (AVS) P30EY003790 (TE), P30EY014104 (AVS) Research to Prevent Blindness (NZ, TE) Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: UK Biobank data are available by request through the UK Biobank Access Management System https://www.ukbiobank.ac.uk/. The 1000 Genomes phase 3 data is available at https://www. internationalgenome.org/. The GTEx protected data are available through the database of Genotypes and Phenotypes (dbGaP) (accession no. phs000424.v8). The processed GTEx eQTL and sQTL summary statistics are available on the GTEx portal (https://gtexportal.org/home/datasets). The EyeGEx retina eQTL summary statistics is available at https://visiongenomics.org. The snRNA-seq data for the anterior segment and macula are available in Gene Expression Omnibus (GEO) accession number GSE199013, for the optic nerve head and posterior tissues in GSE236566, and for the retina in GSE226108. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability The GWAS summary statistics generated in this study are available in Figshare (10.6084/m9.figshare.30227764).