Lenan Liu, Qian Yang, Panyuan Shen, Junsong Wang, Qi Zheng, Guoying Zhang, Bai Jin
{"title":"代谢谱分析确定了与产后从妊娠糖尿病发展为糖尿病前期相关的潜在生物标志物。","authors":"Lenan Liu, Qian Yang, Panyuan Shen, Junsong Wang, Qi Zheng, Guoying Zhang, Bai Jin","doi":"10.7555/JBR.38.20240267","DOIUrl":null,"url":null,"abstract":"<p><p>The current study aims to identify potential metabolic biomarkers that predict the progression to prediabetes in women with a history of gestational diabetes mellitus (GDM). We constructed a prediabetes group ( <i>n</i> = 42) and a control group ( <i>n</i> = 40) based on a2-hour 75 g oral glucose tolerance test for women with a history of GDM from six weeks to six months postpartum, and collected their clinical data and biochemical test results. We performed the plasma metabolomics analysis of the subjects at the fasting and 2-hour post-load time points by using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS). We found that the prediabetes group was older and had higher 2-hour post-load glucose levels during pregnancy than the control group. The metabolomic analysis identified 164 differential metabolites between the groups. Compared with the control group, 15 metabolites in the prediabetes group exhibited consistent change trends at both time points, including three increased and 12 decreased metabolites. By building a prediction model of the progression from GDM to prediabetes, we found a combination of three clinical markers yielded an area under thecurve (AUC) of 0.71 (95% confidence interval [CI], 0.60-0.82). We also assessed the discriminative power of the panel of 15 metabolites for distinguishing between postpartum prediabetes and normal glucose tolerance of the subjects at the fasting (AUC, 0.98; 95% CI, 0.94-1.00) and 2-hour post-load (AUC, 0.99; 95% CI, 0.97-1.00) time points. The metabolic pathway analysis indicated that energy metabolism and branched-chain amino acids played a role in the development of prediabetes in women with a history of GDM during early postpartum. In conclusion, this study identified potential metabolic biomarkers and pathways associated with the progression from GDM to prediabetes in the early postpartum period. A panel of 15 metabolites showed promising discriminative power for distinguishing between postpartum prediabetes and normal glucose tolerance. These findings provide insights into the underlying pathophysiology of this transition and suggest the feasibility of developing a metabolic profiling test for the early identification of women at high risk of prediabetes following GDM.</p>","PeriodicalId":15061,"journal":{"name":"Journal of Biomedical Research","volume":" ","pages":"1-13"},"PeriodicalIF":2.2000,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Metabolic profiling identifies potential biomarkers associated with progression from gestational diabetes mellitus to prediabetes postpartum.\",\"authors\":\"Lenan Liu, Qian Yang, Panyuan Shen, Junsong Wang, Qi Zheng, Guoying Zhang, Bai Jin\",\"doi\":\"10.7555/JBR.38.20240267\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The current study aims to identify potential metabolic biomarkers that predict the progression to prediabetes in women with a history of gestational diabetes mellitus (GDM). We constructed a prediabetes group ( <i>n</i> = 42) and a control group ( <i>n</i> = 40) based on a2-hour 75 g oral glucose tolerance test for women with a history of GDM from six weeks to six months postpartum, and collected their clinical data and biochemical test results. We performed the plasma metabolomics analysis of the subjects at the fasting and 2-hour post-load time points by using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS). We found that the prediabetes group was older and had higher 2-hour post-load glucose levels during pregnancy than the control group. The metabolomic analysis identified 164 differential metabolites between the groups. Compared with the control group, 15 metabolites in the prediabetes group exhibited consistent change trends at both time points, including three increased and 12 decreased metabolites. By building a prediction model of the progression from GDM to prediabetes, we found a combination of three clinical markers yielded an area under thecurve (AUC) of 0.71 (95% confidence interval [CI], 0.60-0.82). We also assessed the discriminative power of the panel of 15 metabolites for distinguishing between postpartum prediabetes and normal glucose tolerance of the subjects at the fasting (AUC, 0.98; 95% CI, 0.94-1.00) and 2-hour post-load (AUC, 0.99; 95% CI, 0.97-1.00) time points. The metabolic pathway analysis indicated that energy metabolism and branched-chain amino acids played a role in the development of prediabetes in women with a history of GDM during early postpartum. In conclusion, this study identified potential metabolic biomarkers and pathways associated with the progression from GDM to prediabetes in the early postpartum period. A panel of 15 metabolites showed promising discriminative power for distinguishing between postpartum prediabetes and normal glucose tolerance. These findings provide insights into the underlying pathophysiology of this transition and suggest the feasibility of developing a metabolic profiling test for the early identification of women at high risk of prediabetes following GDM.</p>\",\"PeriodicalId\":15061,\"journal\":{\"name\":\"Journal of Biomedical Research\",\"volume\":\" \",\"pages\":\"1-13\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biomedical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.7555/JBR.38.20240267\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomedical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.7555/JBR.38.20240267","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Metabolic profiling identifies potential biomarkers associated with progression from gestational diabetes mellitus to prediabetes postpartum.
The current study aims to identify potential metabolic biomarkers that predict the progression to prediabetes in women with a history of gestational diabetes mellitus (GDM). We constructed a prediabetes group ( n = 42) and a control group ( n = 40) based on a2-hour 75 g oral glucose tolerance test for women with a history of GDM from six weeks to six months postpartum, and collected their clinical data and biochemical test results. We performed the plasma metabolomics analysis of the subjects at the fasting and 2-hour post-load time points by using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS). We found that the prediabetes group was older and had higher 2-hour post-load glucose levels during pregnancy than the control group. The metabolomic analysis identified 164 differential metabolites between the groups. Compared with the control group, 15 metabolites in the prediabetes group exhibited consistent change trends at both time points, including three increased and 12 decreased metabolites. By building a prediction model of the progression from GDM to prediabetes, we found a combination of three clinical markers yielded an area under thecurve (AUC) of 0.71 (95% confidence interval [CI], 0.60-0.82). We also assessed the discriminative power of the panel of 15 metabolites for distinguishing between postpartum prediabetes and normal glucose tolerance of the subjects at the fasting (AUC, 0.98; 95% CI, 0.94-1.00) and 2-hour post-load (AUC, 0.99; 95% CI, 0.97-1.00) time points. The metabolic pathway analysis indicated that energy metabolism and branched-chain amino acids played a role in the development of prediabetes in women with a history of GDM during early postpartum. In conclusion, this study identified potential metabolic biomarkers and pathways associated with the progression from GDM to prediabetes in the early postpartum period. A panel of 15 metabolites showed promising discriminative power for distinguishing between postpartum prediabetes and normal glucose tolerance. These findings provide insights into the underlying pathophysiology of this transition and suggest the feasibility of developing a metabolic profiling test for the early identification of women at high risk of prediabetes following GDM.