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This study aimed to investigate whether urinary metabolites account for part of the association between cognition and cardiometabolic risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data from 606 participants (aged 48\u201360; 55% female; 45.5% Black\/African American) in the Year 30 follow-up of the Coronary Artery Risk Development in Young Adults Study were analyzed. Urinary metabolites were profiled using nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry; brain magnetic resonance imaging data were available for 281 participants. Structural equation models were used to assess pathways linking cardiometabolic factors to cognitive outcome, with urinary metabolites and brain MRI-derived parameters as mediators.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Fasting glucose showed a negative association with cognition. Valine, isoleucine, leucine, and phenylalanine were positively associated with fasting glucose. Valine and aminoadipic acid also showed positive associations between fasting glucose and cognition, while tryptophan was correlated with both fasting glucose and cognition. Indole-3-acetic acid showed negative associations with systolic blood pressure and fasting glucose. Brain MRI-derived parameters in memory-related medial temporal areas were associated with waist circumference.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Urinary metabolites and brain imaging markers were linked with hyperglycemia, obesity, and cognitive performance, highlighting multimodal biomarkers relevant to global cognitive function in individuals with cardiometabolic risk.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11306-026-02458-w","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T06:04:03Z","timestamp":1781676243000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Metabolic pathways associated with cardiometabolic risk effects on cognition in middle-aged adults: the CARDIA study"],"prefix":"10.1007","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6715-8027","authenticated-orcid":false,"given":"Sujin","family":"Kang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy","family":"Ebbels","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Queenie","family":"Chan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luke","family":"Whiley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elaine","family":"Holmes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristine","family":"Yaffe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katie","family":"Meyer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian","family":"Griffin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,17]]},"reference":[{"issue":"33","key":"2458_CR1","doi-asserted-by":"publisher","first-page":"3119","DOI":"10.1093\/eurheartj\/ehy288","volume":"39","author":"JG Abell","year":"2018","unstructured":"Abell, J. 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