{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Wang J"],"funding":["Scientific Research and Innovation Platform for Intelligent and Precise Treatment of Bone and Joint Diseases in Shaanxi Province","Postdoctoral Fund of Shaanxi Province","Science and Technology Program of Xi'an, Shaanxi Province"],"pagination":["27"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12822255"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["18(1)"],"pubmed_abstract":["<h4>Background</h4>The relationship between metabolic syndrome (MetS) and osteoarthritis (OA) remains debated, necessitating further exploration to clarify potential causal links.<h4>Methods</h4>This study included 271,019 participants from the UK Biobank and NHANES, and conducted Mendelian randomization (MR) analyses to determine the relationship between BMI, MetS, and OA. We used generalized linear modeling and restricted cubic spline plots to identify non-linear associations, as well as a mediation analysis of the possible mediating effect of MetS between BMI and OA. MR analyses were used to assess genetic causality, with sensitivity and subgroup analyses ensuring robustness.<h4>Results</h4>MetS was present in 27.3% of UK Biobank and 32.4% of NHANES participants, with OA prevalence at 1"],"journal":["Diabetology & metabolic syndrome"],"pubmed_title":["Unraveling the connection between obesity, metabolic syndrome and osteoarthritis risk: a large-observational study."],"pmcid":["PMC12822255"],"funding_grant_id":["No. 2024PT-13","No. 24YXYJ0085","No. 2023BSHGZZHQYXMZZ02"],"pubmed_authors":["Xu K","Yang Z","Xu P","Guo J","Yang M","Guo F","Peng L","Xu X","Wang J","Yu H"],"additional_accession":[]},"is_claimable":false,"name":"Unraveling the connection between obesity, metabolic syndrome and osteoarthritis risk: a large-observational study.","description":"<h4>Background</h4>The relationship between metabolic syndrome (MetS) and osteoarthritis (OA) remains debated, necessitating further exploration to clarify potential causal links.<h4>Methods</h4>This study included 271,019 participants from the UK Biobank and NHANES, and conducted Mendelian randomization (MR) analyses to determine the relationship between BMI, MetS, and OA. We used generalized linear modeling and restricted cubic spline plots to identify non-linear associations, as well as a mediation analysis of the possible mediating effect of MetS between BMI and OA. MR analyses were used to assess genetic causality, with sensitivity and subgroup analyses ensuring robustness.<h4>Results</h4>MetS was present in 27.3% of UK Biobank and 32.4% of NHANES participants, with OA prevalence at 1","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Dec","modification":"2026-06-06T19:29:38.926Z","creation":"2026-06-04T03:10:47.569Z"},"accession":"S-EPMC12822255","cross_references":{"pubmed":["41408645"],"doi":["10.1186/s13098-025-02059-y"]}}