{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T11:57:49Z","timestamp":1784807869818,"version":"3.55.0"},"reference-count":32,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T00:00:00Z","timestamp":1750636800000},"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":"<jats:sec><jats:title>Objective<\/jats:title><jats:p>To examine the expression levels of miR-144-3p in the plasma of patients with gestational diabetes mellitus (GDM) and to construct a nomogram for predicting and evaluating factors influencing adverse pregnancy outcomes (APO) in GDM based on plasma miR-144-3p levels.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This study included 442 pregnant women, comprising 216 diagnosed with GDM (GDM group) and 226 with normal glucose tolerance (NGT group). Plasma miR-144-3p levels in both groups were measured using reverse transcription real-time polymerase chain reaction (RT-qPCR). The diagnostic performance of plasma miR-144-3p for GDM was assessed by receiver operating characteristic (ROC) curve analysis. During pregnancy, the GDM group was followed, and outcomes were categorized into two groups: 132 with favorable pregnancy outcomes (FPO) and 84 with APO. A random number table method was applied to divide the GDM group into a training set (n=151) and a validation set (n=65) using a 7:3 ratio. Differences in variables across pregnancy outcome subgroups in the training set were examined. Univariate and multivariate logistic regression analyses were performed to identify risk factors for APO in GDM. Based on these factors, a nomogram prediction model was developed to estimate the risk of APO in GDM. The model\u2019s performance was evaluated using area under the curve (AUC) analysis, calibration curve analysis, and decision curve analysis (DCA).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The expression of miR-144-3p was significantly higher in the GDM group than in the NGT group (<jats:italic>p<\/jats:italic> &amp;lt; 0.05). miR-144-3p showed an AUC of 0.877, with a sensitivity of 81.09% and a specificity of 91.20% for diagnosing GDM. No statistically significant differences were observed in general clinical characteristics between the training and validation sets. In the training set, gestational weight gain (GWG), the number of OGTT abnormalities, glycaemic control (GC), and miR-144-3p expression varied significantly between the APO and FPO subgroups (<jats:italic>p<\/jats:italic> &amp;lt; 0.05). Multivariate logistic regression analysis identified increased GWG, the number of OGTT abnormalities, poor GC, and higher miR-144-3p levels as independent risk factors for APO in GDM. The AUC of the nomogram based on these variables was 0.881 in the training set and 0.855 in the validation set. Calibration curves indicated good agreement between predicted and actual outcomes in both sets. The DCA showed a clear net clinical benefit and stable predictive utility.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Elevated plasma miR-144-3p levels in pregnant women with GDM may contribute to the occurrence of APO. The number of OGTT abnormalities and glycaemic control were also identified as independent risk factors. A nomogram incorporating miR-144-3p and these clinical indicators displays strong predictive accuracy and provides a practical tool for assessing APO risk in GDM.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fendo.2025.1548780","type":"journal-article","created":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T04:10:34Z","timestamp":1750651834000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Construct a nomogram prediction and evaluation of influencing factors of adverse pregnancy outcomes in GDM patients based on plasma miR-144-3p levels"],"prefix":"10.3389","volume":"16","author":[{"given":"Sanqiang","family":"Niu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengwen","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huaili","family":"Xin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kangjun","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ningning","family":"Du","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,6,23]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1097\/CM9.0000000000002160","article-title":"Molecular biomarkers for gestational diabetes mellitus and postpartum diabetes","volume":"16","author":"Lu","year":"2022","journal-title":"Chin Med J (Engl)"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17249517","article-title":"Prevalence, prevention, and lifestyle intervention of gestational diabetes mellitus in China","volume":"24","author":"Juan","year":"2020","journal-title":"Int J Environ Res Public Health"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2023.1191184","article-title":"Lifestyle interventions to prevent adverse pregnancy outcomes in women at high risk for gestational diabetes mellitus: a randomized controlled trial","volume":"14","author":"Xu","year":"2023","journal-title":"Front Immunol"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.5603\/GP.a2021.0121","article-title":"Influence of MiRNAs in gestational diabetes mellitus development","volume":"8","author":"Juchnicka","year":"2021","journal-title":"Ginekol Pol"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.3390\/ijms24076186","article-title":"Circulating microRNA as biomarkers for gestational diabetes mellitus-A systematic review and meta-analysis","volume":"7","author":"Dinesen","year":"2023","journal-title":"Int J Mol Sci"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.3390\/ijms23137167","article-title":"MicroRNA-based diagnosis and therapy","volume":"13","author":"Ho","year":"2022","journal-title":"Int J Mol Sci"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkw116","article-title":"Distribution of miRNA expression across human tissues","volume":"8","author":"Ludwig","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1080\/14737159.2018.1480939","article-title":"miRNAs in pregnancy-related complications: an update","volume":"7","author":"Mavreli","year":"2018","journal-title":"Expert Rev Mol Diagn"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1080\/14737159.2023.2284780","article-title":"MicroRnas in preeclampsia","volume":"12","author":"Fasoulakis","year":"2023","journal-title":"Expert Rev Mol Diagn"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0290720","article-title":"Maternal circulating miRNAs contribute to negative pregnancy outcomes by altering placental transcriptome and fetal vascular dynamics","volume":"11","author":"Pinson","year":"2023","journal-title":"PloS One"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1186\/1756-0500-6-491","article-title":"Identifying common and specific microRNAs expressed in peripheral blood mononuclear cell of type 1, type 2, and gestational diabetes mellitus patients","volume":"6","author":"Collares","year":"2013","journal-title":"BMC Res Notes"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2022.839344","article-title":"miRNAs as predictive factors in early diagnosis of gestational diabetes mellitus","volume":"13","author":"Juchnicka","year":"2022","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1210\/clinem\/dgaa899","article-title":"Early prediction of gestational diabetes mellitus in the chinese population via advanced machine learning","volume":"3","author":"Wu","year":"2021","journal-title":"J Clin Endocrinol Metab"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1080\/14767058.2024.2356031","article-title":"Gestational diabetes mellitus: relationship of adverse outcomes with severity of disease","volume":"1","author":"Karkia","year":"2024","journal-title":"J Matern Fetal Neonatal Med"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph191710846","article-title":"A systematic review to compare adverse pregnancy outcomes in women with pregestational diabetes and gestational diabetes","volume":"17","author":"Malaza","year":"2022","journal-title":"Int J Environ Res Public Health"},{"key":"B16","doi-asserted-by":"publisher","first-page":"3","DOI":"10.4093\/dmj.2021.0335","article-title":"Gestational diabetes mellitus: diagnostic approaches and maternal-offspring complications","volume":"1","author":"Moon","year":"2022","journal-title":"Diabetes Metab J"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1016\/j.lanwpc.2023.100823","article-title":"Continuous glucose monitoring-derived glycemic metrics and adverse pregnancy outcomes among women with gestational diabetes: a prospective cohort study","volume":"39","author":"Liang","year":"2023","journal-title":"Lancet Reg Health West Pac"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2021.790591","article-title":"hsa_circ_0111707 Is Associated With Risk of Stress-Related Type 2 Diabetes via Sponging miR-144-3p","volume":"12","author":"Yan","year":"2022","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.1080\/14767058.2021.1946779","article-title":"Do patients with a single abnormal OGTT value need a globally admitted definition such as \"borderline GDM\"? Pregnancy outcomes of these women and the evaluation of new inflammatory markers","volume":"22","author":"Simsek","year":"2021","journal-title":"J Matern Fetal Neonatal Med"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.1016\/j.carpath.2015.06.003","article-title":"Inhibiting microRNA-144 abates oxidative stress and reduces apoptosis in hearts of streptozotocin-induced diabetic mice","volume":"6","author":"Yu","year":"2015","journal-title":"Cardiovasc Pathol"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.65.1.1","article-title":"Inhibition of miR-144-3p\/FOXO1 attenuates diabetic keratopathy via modulating autophagy and apoptosis","volume":"1","author":"Wei","year":"2024","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"B22","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1186\/s13098-022-00852-7","article-title":"Targeting ferroptosis with miR-144-3p to attenuate pancreatic \u03b2 cells dysfunction via regulating USP22\/SIRT1 in type 2 diabetes","volume":"1","author":"Zhang","year":"2022","journal-title":"Diabetol Metab Syndr"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.4103\/0366-6999.204928","article-title":"Relationship between oral glucose tolerance test characteristics and adverse pregnancy outcomes among women with gestational diabetes mellitus","volume":"9","author":"Feng","year":"2017","journal-title":"Chin Med J (Engl)"},{"key":"B24","doi-asserted-by":"publisher","first-page":"108048","DOI":"10.1016\/j.diabres.2020.108048","article-title":"Abnormal fasting, post-load or combined glucose values on oral glucose tolerance test and pregnancy outcomes in women with gestational diabetes mellitus","volume":"161","author":"Papachatzopoulou","year":"2020","journal-title":"Diabetes Res Clin Pract"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2020.00135","article-title":"Size and shape of associations of OGTT as well as mediating effects on adverse pregnancy outcomes among women with gestational diabetes mellitus: population-based study from southern han chinese","volume":"11","author":"Zhou","year":"2020","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.3390\/nu14122383","article-title":"Prevention of gestational diabetes mellitus and gestational weight gain restriction in overweight\/obese pregnant women: A systematic review and network meta-analysis","volume":"12","author":"Wu","year":"2022","journal-title":"Nutrients"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1002926","article-title":"Preconception diabetes mellitus and adverse pregnancy outcomes in over 6.4 million women: A population-based cohort study in China","volume":"10","author":"Wei","year":"2019","journal-title":"PloS Med"},{"key":"B28","doi-asserted-by":"publisher","first-page":"908","DOI":"10.1038\/s41598-020-57838-6","article-title":"Circulating miR-330-3p in late pregnancy is associated with pregnancy outcomes among lean women with GDM","volume":"1","author":"Pfeiffer","year":"2020","journal-title":"Sci Rep"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1177\/0300060520954763","article-title":"Serum miR-29a\/b expression in gestational diabetes mellitus and its influence on prognosis evaluation","volume":"9","author":"Deng","year":"2020","journal-title":"J Int Med Res"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.2337\/dc18-1646","article-title":"Hyperglycemia and adverse pregnancy outcome follow-up study (HAPO FUS): maternal gestational diabetes mellitus and childhood glucose metabolism","volume":"3","author":"L Lowe","year":"2019","journal-title":"Diabetes Care"},{"key":"B31","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1186\/s12884-020-03071-y","article-title":"Effects of pre-pregnancy body mass index and gestational weight gain on maternal and infant complications","volume":"1","author":"Sun","year":"2020","journal-title":"BMC Pregnancy Childbirth"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2018.00677","article-title":"miR-144-3p promotes adipogenesis through releasing C\/EBP\u03b1 From klf3 and ctbp2","volume":"677","author":"Shen","year":"2018","journal-title":"Front Genet"}],"container-title":["Frontiers in Endocrinology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fendo.2025.1548780\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T04:10:34Z","timestamp":1750651834000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fendo.2025.1548780\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,23]]},"references-count":32,"alternative-id":["10.3389\/fendo.2025.1548780"],"URL":"https:\/\/doi.org\/10.3389\/fendo.2025.1548780","relation":{},"ISSN":["1664-2392"],"issn-type":[{"value":"1664-2392","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,23]]},"article-number":"1548780"}}