{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T13:16:21Z","timestamp":1780665381609,"version":"3.54.1"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T00:00:00Z","timestamp":1751587200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012245","name":"Science and Technology Planning Project of Guangdong Province","doi-asserted-by":"publisher","award":["2023A0505030004"],"award-info":[{"award-number":["2023A0505030004"]}],"id":[{"id":"10.13039\/501100012245","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>The retina serves as a non-invasive window to visualize systemic health, with optical coherence tomography angiography (OCTA) enabling simultaneous assessment of retinal structural thickness and vascular density. Suboptimal cardiovascular-kidney-metabolic (CKM) health status, defined by the early stage of CKM syndrome, may impact retinal neurovascular integrity, yet comprehensive OCTA-based evaluations remain limited and controversial. This study aimed to investigate retinal structural and vascular alterations in the early-stage CKM using OCTA and explore its potential as a biomarker tool.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A cross-sectional study included 2,153 participants undergoing OCTA during health checks (2023\u20132024). Early-stage CKM (stages 1\u20132) is characterized by abnormal levels of glucose, lipid profile, uric acid, or blood pressure. Retinal thickness and vessel density in nine ETDRS grid regions were measured. Univariate and multivariate logistic regression analyses identified associations between early-stage CKM and OCTA parameters, adjusting for age and gender.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Early-stage CKM subjects (<jats:italic>n<\/jats:italic>\u202f=\u202f1,843, 94.5%) exhibited significantly reduced retinal thickness and vessel density across multiple regions compared to healthy controls (all <jats:italic>p<\/jats:italic>\u202f&amp;lt;\u202f0.05). Multivariate analysis revealed outer temporal thickness (OR\u202f=\u202f0.986, <jats:italic>p<\/jats:italic>\u202f&amp;lt;\u202f0.001), outer superficial vessel density (OR\u202f=\u202f1.04, <jats:italic>p<\/jats:italic>\u202f=\u202f0.020), and inner superior vessel density (OR\u202f=\u202f0.962, <jats:italic>p<\/jats:italic>\u202f=\u202f0.010) as independent predictors of early-stage CKM, alongside age and gender. Specific abnormalities, such as hypertension and diabetes, were associated with distinct regional decreases in thickness and density, suggesting a dose-dependent impact of glycemic dysregulation on retinal health.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Early-stage CKM syndrome is associated with subtle retinal structural and vascular alterations detectable by OCTA, particularly within the macular layers. OCTA-derived biomarkers, including outer temporal thickness and macular vessel density, may serve as non-invasive tools for evaluating systemic health status, offering promise for the early detection of metabolic and cardiovascular risks.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fmed.2025.1614321","type":"journal-article","created":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T05:21:49Z","timestamp":1751606509000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Investigation of early-stage cardiovascular-kidney-metabolic syndrome on retinal structure and function evaluated by optical coherence tomography angiography"],"prefix":"10.3389","volume":"12","author":[{"given":"Yunyi","family":"Liang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Congbi","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianping","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wanhua","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Runyi","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingfeng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peiqiong","family":"Lao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junhua","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaohao","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chubin","family":"Ou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,4]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/nrneurol.2012.227","article-title":"The retina as a window to the brain-from eye research to CNS disorders","volume":"9","author":"London","year":"2013","journal-title":"Nat Rev Neurol"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"152","DOI":"10.3390\/jcm12010152","article-title":"Application of deep learning to retinal-image-based Oculomics for evaluation of systemic health: a review","volume":"12","author":"Wu","year":"2022","journal-title":"J Clin Med"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1136\/jnnp-2020-325347","article-title":"Retinal imaging in Alzheimer's disease","volume":"92","author":"Cheung","year":"2021","journal-title":"J Neurol Neurosurg Psychiatry"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"109","DOI":"10.18240\/ijo.2017.01.18","article-title":"The association between retinal vasculature changes and stroke: a literature review and meta-analysis","volume":"10","author":"Wu","year":"2017","journal-title":"Int J Ophthalmol"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"56137","DOI":"10.3791\/56137","article-title":"Using retinal imaging to study dementia","volume":"6","author":"Chan","year":"2017","journal-title":"J Vis Exp"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"2285","DOI":"10.1007\/s00415-023-12171-6","article-title":"Retinal imaging for the assessment of stroke risk: a systematic review","volume":"271","author":"Girach","year":"2024","journal-title":"J Neurol"},{"key":"ref7","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-26269-3","volume-title":"OCT and imaging in central nervous system diseases","author":"Grzybowski","year":"2020"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1007\/s40123-022-00641-5","article-title":"Using artificial intelligence to analyse the retinal vascular network: the future of cardiovascular risk assessment based on Oculomics? 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