{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T14:59:16Z","timestamp":1791557956516,"version":"4.3.4"},"reference-count":38,"publisher":"American Medical Association (AMA)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"Importance<\/jats:title>The neural retina is considered a unique window to systemic health, but its biological link with systemic health remains unknown.<\/jats:p><\/jats:sec>Objective<\/jats:title>To investigate the independent associations of retinal ganglion cell\u2013inner plexiform layer thickness (GCIPLT) metabolic profiles with rates of mortality and morbidity of common diseases.<\/jats:p><\/jats:sec>Design, Setting, and Participants<\/jats:title>This cohort study evaluated UK Biobank participants enrolled between 2006 and 2010, and prospectively followed them up for multidisease diagnosis and mortality. Additional participants from the Guangzhou Diabetes Eye Study (GDES) underwent optical coherence tomography scanning and metabolomic profiling and were included for validation.<\/jats:p><\/jats:sec>Main Outcomes and Measures<\/jats:title>Systematic analysis of circulating plasma metabolites to identify GCIPLT metabolic profiles; prospective associations of these profiles with mortality and morbidity of 6 common diseases with their incremental discriminative value and clinical utility.<\/jats:p><\/jats:sec>Results<\/jats:title>Among 93\u202f838 community-based participants (51\u202f182 [54.5%] women), the mean (SD) age was 56.7 (8.1) years and mean (SD) follow-up was 12.3 (0.8) years. Of 249 metabolic metrics, 37 were independently associated with GCIPLT, including 8 positive and 29 negative associations, and most were associated with the rates of future mortality and common diseases. These metabolic profiles significantly improved the models for discriminating type 2 diabetes over clinical indicators (C statistic: 0.862; 95% CI, 0.852-0.872 vs clinical indicators only, 0.803; 95% CI, 0.792-0.814; P<\/jats:italic>\u2009&amp;lt;\u2009.001), myocardial infarction (0.792; 95% CI, 0.775-0.808 vs 0.768; 95% CI, 0.751-0.786; P<\/jats:italic>\u2009&amp;lt;\u2009.001), heart failure (0.803; 95% CI, 0.786-0.820 vs 0.790; 95% CI, 0.773-0.807; P<\/jats:italic>\u2009&amp;lt;\u2009.001), stroke (0.739; 95% CI, 0.714-0.764 vs 0.719; 95% CI, 0.693-0.745; P<\/jats:italic>\u2009&amp;lt;\u2009.001), all-cause mortality (0.747; 95% CI, 0.734-0.760 vs 0.724; 95% CI, 0.711-0.738; P<\/jats:italic>\u2009&amp;lt;\u2009.001), and cardiovascular disease mortality (0.790; 95% CI, 0.767-0.812 vs 0.763; 95% CI, 0.739-0.788; P<\/jats:italic>\u2009&amp;lt;\u2009.001). Additionally, the potential of GCIPLT metabolic profiles for risk stratification of cardiovascular diseases were further confirmed in the GDES cohort using a different metabolomic approach.<\/jats:p><\/jats:sec>Conclusions and Relevance<\/jats:title>In this prospective study of multinational participants, GCIPLT-associated metabolites demonstrated the potential to inform mortality and morbidity risks. Incorporating information on these profiles may facilitate individualized risk stratification for these health outcomes.<\/jats:p><\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2023.13220","type":"journal-article","created":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T15:01:28Z","timestamp":1684249288000},"page":"e2313220","source":"Crossref","is-referenced-by-count":15,"title":["Analysis of Plasma Metabolic Profile on Ganglion Cell\u2013Inner Plexiform Layer Thickness With Mortality and Common Diseases"],"prefix":"10.1001","volume":"6","author":[{"given":"Shaopeng","family":"Yang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, 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Diseases, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianwen","family":"Shang","sequence":"additional","affiliation":[{"name":"Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia"},{"name":"Department of Ophthalmology, Guangdong Academy of Medical Sciences, Guangdong Provincial People\u2019s Hospital, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabriella","family":"Bulloch","sequence":"additional","affiliation":[{"name":"Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingguang","family":"He","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research 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