{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T05:38:58Z","timestamp":1792647538983,"version":"4.5.0"},"reference-count":102,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"20","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2026,10,20]]},"abstract":"<jats:sec xml:lang=\"en\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p xml:lang=\"en\">Cardiometabolic risk associated with obesity is increasingly recognized to be strongly influenced by the anatomical distribution and ectopic deposition of adipose tissue, yet the genetic mechanisms linking adipose depots to cardiometabolic diseases remain incompletely understood.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p xml:lang=\"en\">Using large\u2010scale genome\u2010wide association summary statistics, we systematically characterized shared genetic architecture between 7 magnetic resonance imaging\u2010derived regional and ectopic adipose traits and 20 cardiometabolic diseases, including major cardiovascular outcomes and type 2 diabetes. Genetic overlap was assessed at genome\u2010wide, regional, and variant levels, followed by functional annotation, cell\u2010type enrichment, and phenotype enrichment analyses. Protein\u2013protein interaction networks and molecular docking analyses were further applied to prioritize disease\u2010relevant genes and potential therapeutic compounds.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p xml:lang=\"en\">\n                      We identified widespread yet heterogeneous genetic overlap, including 109 adipose\u2010cardiometabolic diseases pairs with genome\u2010wide overlap, 92 pairs showing regional concordance across 423 genomic regions, and 146 pleiotropic loci supported by colocalization. Shared variants were enriched in regulatory elements and connected to pleiotropic genes involved in metabolic and inflammatory pathways, including insulin signaling, ion homeostasis, and cellular stress responses. Cell type enrichment analyses highlighted immune, endothelial, and metabolically active parenchymal cells as key contributing cell types. Network and docking analyses further prioritized cardiometabolic disease\u2010related genes such as\n                      <jats:italic toggle=\"no\">MMP9<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"no\">PPARG<\/jats:italic>\n                      , and\n                      <jats:italic toggle=\"no\">TM6SF2<\/jats:italic>\n                      , along with candidate compounds exhibiting favorable binding properties.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p xml:lang=\"en\">This study delineates differential genetic risk patterns linking adipose distribution to multiple cardiometabolic diseases and reveals interconnected metabolic, immune, and vascular mechanisms, providing a genetic framework for cardiometabolic and cardiovascular risk assessment and the prioritization of potential therapeutic targets.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/jaha.126.049987","type":"journal-article","created":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T11:50:46Z","timestamp":1791633046000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Regional Adipose Distribution Reveals Differential Genetic Risk Patterns for Cardiometabolic Diseases"],"prefix":"10.1161","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-9764-0650","authenticated-orcid":false,"given":"Qian","family":"Wu","sequence":"first","affiliation":[{"name":"Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fan","family":"Yang","sequence":"additional","affiliation":[{"name":"Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of 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