{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T08:53:20Z","timestamp":1791017600555,"version":"4.1.0"},"reference-count":51,"publisher":"SAGE Publications","issue":"10","license":[{"start":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:00:00Z","timestamp":1783555200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Sichuan Science and Technology Program","award":["2025ZNSFSC1021"],"award-info":[{"award-number":["2025ZNSFSC1021"]}]},{"name":"National Science Foundation for Distinguished Young Scholars of China","award":["82501656"],"award-info":[{"award-number":["82501656"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Cereb Blood Flow Metab"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:p>\n                    Cardiovascular\u2013kidney\u2013metabolic (CKM) syndrome has increasingly affected the middle-aged and elderly population. The relationship between CKM risk factors and stroke at metabolomic level and underlying genetic alterations remains unknown. Elastic net regression was utilized to establish a metabolic signature indicative of CKM risk factors in 108,305 participants in UK Biobank. Multivariable COX proportional hazard models were utilized to determine the association between CKM plasma metabolic signature and incident stroke. Causal relationships between metabolites and stroke were explored through Mendelian randomization (MR) analysis and colocalization analysis. During a follow up of 13.94\u2009years (interquartile range (IQR), 13.00\u201314.43), 3881 incident stroke events were documented. Forty-eight metabolites were identified to represent the metabolic process of CKM risk factors. After adjustment of demographic factors and CKM risk factors, the elevated metabolic signature was correlated with higher stroke incidence risks with hazard ratio of 1.075 (95% confidential intervals (CI), 1.001\u20131.154). MR analysis identified 38 potential causal metabolites. In addition, colocalization analysis revealed\n                    <jats:italic toggle=\"yes\">LDLR<\/jats:italic>\n                    and\n                    <jats:italic toggle=\"yes\">CELSR2<\/jats:italic>\n                    as two genetic targets. In general, this study identified a metabolic signature reflecting CKM risk factors is positively associated with stroke, while\n                    <jats:italic toggle=\"yes\">LDLR<\/jats:italic>\n                    and\n                    <jats:italic toggle=\"yes\">CELSR2<\/jats:italic>\n                    might impact the metabolic process in CKM population at genetic level.\n                  <\/jats:p>","DOI":"10.1177\/0271678x261462718","type":"journal-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T10:01:11Z","timestamp":1781517671000},"page":"2757-2769","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Plasma metabolic signature of cardiovascular\u2013kidney\u2013metabolic syndrome and incident stroke: A nationwide prospective cohort study"],"prefix":"10.1177","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-5670-4154","authenticated-orcid":false,"given":"Kaixin","family":"Lei","sequence":"first","affiliation":[{"name":"The Center of Gerontology and Geriatrics, Sichuan University West China Hospital, Guo Xue Xiang, Chengdu, Sichuan Province, China"},{"name":"West China School of Medicine, Sichuan University West China Hospital, Chengdu, Sichuan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bojun","family":"Ma","sequence":"additional","affiliation":[{"name":"West China School of Medicine, Sichuan University West China Hospital, Chengdu, Sichuan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenxi","family":"Lu","sequence":"additional","affiliation":[{"name":"National Center for Chronic Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lifan","family":"Xu","sequence":"additional","affiliation":[{"name":"West China School of Medicine, Sichuan University West China Hospital, Chengdu, Sichuan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunxia","family":"Qiao","sequence":"additional","affiliation":[{"name":"Mental Health Center and Psychiatric Laboratory, Sichuan University West China Hospital, Guo Xue Xiang, Chengdu, Sichuan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Teng","sequence":"additional","affiliation":[{"name":"West China School of Medicine, Sichuan University West China Hospital, Chengdu, Sichuan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6034-7240","authenticated-orcid":false,"given":"Wen","family":"Guo","sequence":"additional","affiliation":[{"name":"The Center of Gerontology and Geriatrics, Sichuan University West China Hospital, Guo Xue Xiang, Chengdu, Sichuan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,7,9]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000001186"},{"key":"e_1_3_5_3_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000001191"},{"key":"e_1_3_5_4_2","doi-asserted-by":"publisher","DOI":"10.1681\/ASN.0000000658"},{"key":"e_1_3_5_5_2","doi-asserted-by":"publisher","DOI":"10.4093\/dmj.2024.0544"},{"key":"e_1_3_5_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(24)00757-8"},{"key":"e_1_3_5_7_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000001209"},{"key":"e_1_3_5_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11910-022-01236-0"},{"key":"e_1_3_5_9_2","doi-asserted-by":"publisher","DOI":"10.1161\/STROKEAHA.124.047070"},{"key":"e_1_3_5_10_2","doi-asserted-by":"publisher","DOI":"10.1002\/brb3.70550"},{"key":"e_1_3_5_11_2","doi-asserted-by":"publisher","DOI":"10.5853\/jos.2025.00409"},{"key":"e_1_3_5_12_2","doi-asserted-by":"publisher","DOI":"10.5853\/jos.2024.04623"},{"key":"e_1_3_5_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2025.02.035"},{"key":"e_1_3_5_14_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12933-025-02819-0"},{"key":"e_1_3_5_15_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2024.6892"},{"key":"e_1_3_5_16_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1001779"},{"key":"e_1_3_5_17_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurjpc\/zwaf050"},{"key":"e_1_3_5_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.redox.2025.103588"},{"key":"e_1_3_5_19_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurjpc\/zwaf248"},{"key":"e_1_3_5_20_2","article-title":"KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease","volume":"105","author":"Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group","year":"2024","unstructured":"Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int 2024; 105(4S): S117\u2013S314.","journal-title":"Kidney Int"},{"key":"e_1_3_5_21_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehz897"},{"key":"e_1_3_5_22_2","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12973"},{"key":"e_1_3_5_23_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-20885-8"},{"key":"e_1_3_5_24_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11427-023-2507-9"},{"key":"e_1_3_5_25_2","doi-asserted-by":"publisher","DOI":"10.1053\/j.ajkd.2024.03.028"},{"key":"e_1_3_5_26_2","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.202407-1345OC"},{"key":"e_1_3_5_27_2","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.123.032643"},{"key":"e_1_3_5_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2025.105807"},{"key":"e_1_3_5_29_2","article-title":"Metabolomics data improve 10-year cardiovascular risk prediction with the SCORE2 algorithm for the general population without cardiovascular disease or diabetes","volume":"2025","author":"Xie R","year":"2025","unstructured":"Xie R, Sha S, Peng L, et al. 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