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We aimed to explore this MASLD\u2010T2D relationship, addressing organ\u2010specific IR for personalized management and risk prevention.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This cross\u2010sectional study included 41 T2D participants enrolled in a clinical trial (NCT02248311) undergoing biochemical analyses, anthropometric measurements and [\n                      <jats:sup>18<\/jats:sup>\n                      F]FDG\u2010PET\/CT imaging before and after hyperinsulinemic euglycemic clamp (HEC).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>\n                      Two MASLD\u2010T2D phenotypes were identified according to their IGLU patterns, that is, with low (HepGluc[+],\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200921) and with high (HepGluc[\u2212],\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200920) hepatic response to insulin. HepGluc[+] participants exhibited increased systemic IR (HOMA\u2010IR,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.012), inflammation (interleukin 6,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.005); alanine and aspartate aminotransferase ALT, AST (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.015 and\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.007); gamma\u2010glutamyl transferase GGT (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.019) and steatosis markers (liver volume,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.006); NAFLD liver fat score,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.0017; hepatic steatosis index,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.02; fatty liver index,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.008; liver stiffness measurements (LSM) (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009.049). No statistical differences in serum\u2010based liver fibrosis scores were shown. To identify MASLD\u2010T2D phenotypes in a friendly manner, the MASLD\u2010T2D score based on support vector machines was developed using AST, ALT and GGT (AUC\u2009=\u2009.83), as well as with MASLD indices including LSM and NAFLD liver fat score (AUC\u2009=\u2009.90).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Implications<\/jats:title>\n                    <jats:p>Two new MASLD\u2010T2D phenotypes have been identified, HepGluc[+] and HepGluc[\u2212], according to IGLU patterns, with HepGluc[+] being more deleterious due to higher systemic IR, steatosis and inflammation. Phenotypes can be identified using a new function, the MASLD\u2010T2D score.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/eci.70050","type":"journal-article","created":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T06:08:25Z","timestamp":1747807705000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Phenotypic patterns of metabolic dysfunction\u2010associated steatotic liver disease in type 2 diabetes: The impact of insulin"],"prefix":"10.1111","volume":"55","author":[{"given":"Queralt","family":"Mart\u00edn\u2010Saladich","sequence":"first","affiliation":[{"name":"Medical Molecular Imaging Research Group, Vall d'Hebron Research Institute (VHIR), Nuclear Medicine, Radiology and Cardiology Departments Vall d'Hebron University Hospital (VHUH), Autonomous University Barcelona (UAB)  Barcelona Spain"},{"name":"BCN MedTech, Information and Communication Technologies Department Pompeu Fabra University  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