{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T05:40:42Z","timestamp":1788932442068,"version":"build-2803163510"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T00:00:00Z","timestamp":1769558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Chengdu Medical Research Project in Chengdu Municipal Health Commission","award":["2025238"],"award-info":[{"award-number":["2025238"]}]},{"name":"Key Research and Development Program in Sichuan Provincial Department of Science and Technology","award":["2024YFFK0085"],"award-info":[{"award-number":["2024YFFK0085"]}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Nutr."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Insulin resistance (IR) is central to type 2 diabetes mellitus (T2DM). Composite indices including the atherogenic index of plasma (AIP), metabolic score for insulin resistance (METS-IR), triglyceride\u2013glucose index (TyG), and TyG-BMI, are widely used to quantify IR severity. The gut microbiome (GM) has been implicated in metabolic dysregulation, but its associations with IR remain incompletely defined.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We collected blood test results and stool samples from participants with T2DM and healthy controls. Stool samples underwent 16S rRNA gene sequencing. We trained XGBoost models to distinguish individuals with higher IR from healthy controls based on GM profiles and performed correlation analyses between GM features, clinical measures, and IR indices.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Triglycerides (TG), fasting blood glucose (FBG), and high-density lipoprotein cholesterol (HDL-C) differed significantly between the T2DM and control groups. IR indices (AIP, METS-IR, TyG, and TyG-BMI) were markedly higher in the T2DM group. XGBoost models based on GM profiles showed high discriminatory performance for identifying T2DM individuals with higher IR, with Bacteroides and Faecalibacterium contributing most to model performance. Correlation analyses further indicated that Lachnospiraceae_UCG-010, Bacteroides, Faecalibacterium, Lachnospira, Parasutterella, and Escherichia\u2013Shigella were associated with clinical measures and IR indices.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Specific GM features are associated with IR-related clinical measures and composite indices in T2DM, supporting their potential as intervention targets to improve insulin resistance and restore carbohydrate and lipid metabolism.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnut.2026.1747767","type":"journal-article","created":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T06:46:06Z","timestamp":1769582766000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Exploring the gut microbiome in type 2 diabetes across different insulin resistance levels: a machine learning approach"],"prefix":"10.3389","volume":"13","author":[{"given":"Yuchi","family":"He","sequence":"first","affiliation":[{"name":"School of Clinical Medicine, Chengdu University of Traditional Chinese Medicine","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Traditional Chinese Medicine, Sichuan Academy of Chinese Medicine Sciences (Sichuan Second Traditional Chinese Medicine Hospital)","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Clinical Medicine, Chengdu University of Traditional Chinese Medicine","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialong","family":"Jia","sequence":"additional","affiliation":[{"name":"School of Clinical Medicine, Chengdu University of Traditional Chinese Medicine","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuqing","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Traditional Chinese Medicine Hospital of Meishan","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiyu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine","place":["Chengdu, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ya","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine","place":["Chengdu, Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,1,28]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"S27","DOI":"10.2337\/dc25-S002","article-title":"2. Diagnosis and classification of diabetes: standards of care in diabetes-2025","volume":"48","year":"2025","journal-title":"Diabetes Care"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"109119","DOI":"10.1016\/j.diabres.2021.109119","article-title":"IDF diabetes atlas: global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045","volume":"183","author":"Sun","year":"2022","journal-title":"Diabetes Res Clin Pract"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"2133","DOI":"10.1152\/physrev.00063.2017","article-title":"Mechanisms of insulin action and insulin resistance","volume":"98","author":"Petersen","year":"2018","journal-title":"Physiol Rev"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1186\/s12933-024-02314-y","article-title":"Association between atherogenic index of plasma and new-onset stroke in individuals with different glucose metabolism status: insights from 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