ArticleOphthalmology science
Machine Learning on Prediagnostic Metabolite Data Identifies Etiologic Endotypes of Exfoliation Glaucoma in United States Health Professionals.
Article in Ophthalmology science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Transcending genome-wide association studies to create useful multi-omic views of glaucoma.Progress in retinal and eye research · 2026Review
- Metabolomic Signatures and Predictive Utility ofMetabolites · 2025Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Exfoliation glaucoma (XFG) etiology is poorly understood. Metabolomics-based etiologic endotypes of XFG may provide novel etiologic insights. We aimed to use unsupervised machine learning on prediagnostic plasma metabolites to characterize etiologic XFG endotypes. Design: Prospective case-only analysis. Participants: Among Nurses' Health Study and Health Professionals Follow-up Study participants, 205 (174 female and 31 male) incident XFG cases diagnosed with an average of 11.8 years following blood collection (1989-1995) were included. Methods: We identified and confirmed incident cases of XFG or XFG suspect (collectively called "XFG" henceforth) through 2016 with medical record review. Liquid chromatography-mass spectrometry was used to profile 341 plasma metabolites. After preprocessing prediagnostic metabolites with adjustment for season, time of blood draw, and fasting status, we computed a distance matrix using Pearson distance and computed gap statistics to identify distinct endotypes. Main Outcome Measures: Metabolomics-based XFG etiologic endotypes. Metabolomic profiles were compared across endotypes; false discovery rate (FDR) was used to account for multiple comparisons in Metabolite Set Enrichment Analyses. Exfoliation glaucoma environmental risk factors (e.g., lifetime ultraviolet (UV) exposure, folate consumption), a genetic risk score incorporating 8 major single nucleotide polymorphisms for exfoliation syndrome, and clinical presentations were compared across endotypes. Results: We identified 3 distinct XFG metabolomic endotypes. Compared with the most common endotype 2 (reference group [n = 90; 43.9%]), endotype 1 (n = 56; 27.3%) tended to include more male southern US residents with greater UV exposure and were the least likely to have cardiovascular disease; among women, a higher percentage were postmenopausal. Endotype 3 (n = 59; 28.8%) was associated with being a male northern US resident; a higher prevalence of cardiovascular disease and risk factors such as higher body mass index, diabetes, hypertension, and dyslipidemia; and the lowest genetic susceptibility score. There were no differences in ophthalmic characteristics (e.g., maximum intraocular pressure, bilaterality, age at diagnosis) across endotypes ( Conclusions: Integrated metabolomic profiling can identify distinct XFG etiologic endotypes, suggesting different pathobiological mechanisms. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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