{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T20:22:54Z","timestamp":1792700574496,"version":"4.5.0"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T00:00:00Z","timestamp":1786060800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"\n Background<\/jats:title>\n Gestational diabetes mellitus (GDM) women often have abnormal lipid levels during pregnancy. Moreover, lipid metabolism and body mass index (BMI) may influence the occurrence of GDM, and the potential relationship between them remains unclear.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To explore the potential association between blood lipid levels, BMI and GDM in early pregnancy.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Multivariate logistic regression analysis was employed, and the odds ratio (OR) and its 95% confidence interval (CI) were used to evaluate the associations between early pregnancy lipid levels, such as triglyceride (TG), total cholesterol (TC) as well as BMI and the risk of GDM. Based on the identified significant associated factors, a clinical prediction model was attempted to be constructed. Further use bidirectional Mendelian randomization (MR) analysis to evaluate the potential relationship between screened risk associated blood lipids and GDM.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n In the case-control study, multivariate logistic regression analysis showed that BMI (OR\u00a0=\u00a01.12, 95% CI\u00a0=\u00a01.07-1.16,\n P<\/jats:italic>\n \u00a0&lt;\u00a00.05), TG (OR\u00a0=\u00a01.27, 95%CI=1.13-1.42,\n P<\/jats:italic>\n \u00a0&lt;\u00a00.05), TC (OR\u00a0=\u00a01.12, 95%CI=1.01-1.25,\n P<\/jats:italic>\n \u00a0&lt;\u00a00.05), LDL-c (OR\u00a0=\u00a01.13, 95%CI=1.01-1.27,\n P<\/jats:italic>\n \u00a0&lt;\u00a00.05) and HbA1c (OR\u00a0=\u00a05.94, 95%CI=4.28-8.25,\n P<\/jats:italic>\n \u00a0&lt;\u00a00.05) were significantly associated with the risk of GDM after adjusting for age. Based on TG, TC, LDL-c and BMI, the nomogram demonstrated AUCs of 0.772 in the training set, 0.754 in internal validation and 0.759 in external validation, indicating good and stable predictive performance. In the forward MR analysis, genetic evidence supported potential associations between TG (OR\u00a0=\u00a01.24, 95%CI=1.10-1.40,\n P<\/jats:italic>\n \u00a0&lt;\u00a00.05), BMI (OR\u00a0=\u00a01.75, 95%CI=1.51-2.03,\n P<\/jats:italic>\n \u00a0&lt;\u00a00.05) and GDM; while the reverse MR analysis indicated that GDM may have an association effect on TG (OR\u00a0=\u00a01.03, 95%CI=1.02-1.04,\n P<\/jats:italic>\n \u00a0&lt;\u00a00.05). Leave-one-out sensitivity analyses confirmed the robustness and reliability of the primary findings.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n This study provides suggestive evidence that TG and BMI may be associated with GDM risk, supported by clinical and genetic evidence. A nomogram demonstrated good and stable predictive performance. and MR analysis provided suggestive evidence of a potential bidirectional relationship between GDM and elevated TG. Further validation is needed.<\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fendo.2026.1870557","type":"journal-article","created":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T04:22:19Z","timestamp":1786076539000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Association between blood lipids, BMI and gestational diabetes mellitus in early pregnancy: a clinical study and Mendelian randomization"],"prefix":"10.3389","volume":"17","author":[{"given":"Yukun","family":"Wang","sequence":"first","affiliation":[{"name":"The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University","place":["Guilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"He","sequence":"additional","affiliation":[{"name":"The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University","place":["Guilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lijie","family":"Nie","sequence":"additional","affiliation":[{"name":"The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University","place":["Guilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunyi","family":"Yue","sequence":"additional","affiliation":[{"name":"The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University","place":["Guilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruiqi","family":"Li","sequence":"additional","affiliation":[{"name":"The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University","place":["Guilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Mo","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Guilin Medical University","place":["Guilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Cell and Genetics, School of Basic Medical Sciences, Guilin Medical University","place":["Guilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyuan","family":"Yu","sequence":"additional","affiliation":[{"name":"The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University","place":["Guilin, China"]},{"name":"Department of Epidemiology and Health Statistics, School of Public Health, Guilin Medical University","place":["Guilin, 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