Multiomic Framework for Glaucoma

Primary open-angle glaucoma (POAG) produces chronic, progressive, and irreversible optic nerve degeneration, leading to visual disability and blindness. We propose to analyze preclinical proteomic and metabolomic markers and their interactions with glaucoma genetic predisposition to better understand POAG pathophysiology. We will use plasma samples from a matched case-control group (500 cases and 500 controls) nested within ongoing prospective cohorts (Nurses' Health Study (NHS), NHS2, and Health Professionals Follow-up Study) as well as genetic data and prospectively collected biennial questionnaire data and clinical data on incident glaucoma cases. For incident POAG cases, we have used an artificial intelligence algorithm to define POAG subtypes by visual field loss patterns; the POAG subtype with paracentral visual field is of particular interest, as this subtype is more strongly associated with considerable functional disability. This study will employ a cutting-edge platform that uses slow off-rate modified aptamer reagents, which bind proteins like antibodies to quantify 5,000 proteins (Aim 1). In addition to an untargeted approach, we will test a priori hypotheses in targeted approaches to investigate the relation to POAG for proteins related to nitric oxide signaling, lipid metabolism, and immune response. We will then test the hypothesis that dysregulation of lipid metabolism is important in POAG etiology by using a commercial NMR metabolomics platform assaying 168 metabolites that quantify metabolites in 3 categories: a) low molecular weight molecules like ketone bodies; b) lipoproteins like high-density lipoproteins of specified particle size; and c) plasma lipids (Aim 2). We will use preclinical plasma collected ~10 years before diagnosis in 600 cases and 600 controls who previously underwent high throughput genotyping and LC/MS metabolomics. For Aims 1 and 2, we will explore whether associations vary by visual field loss patterns in POAG. Lastly, in NHS, NHS2, and HPFS, participants with the top 10% of the POAG polygenic risk score (PRS) had a 10+ fold higher risk of POAG; yet ≥70% of those in the highest PRS did not develop POAG and are “resilient to high POAG polygenic risk”. We will evaluate the biomarker signature and ophthalmic features associated with this resilience in those with the highest POAG PRS scores (Aim 3). We will seek nominal replications for all aims in the UK Biobank. The aims will expand the repository of multiple `omics data available for preclinical glaucoma. The proposed aims are significant and innovative, as analyses of prospective proteomic and metabolomic markers, in combination with genetic and clinical phenotype data to subclassify POAG, will advance our understanding of POAG etiology.