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<p>Gestational diabetes mellitus (GDM) can elevate the likelihood of developing high blood pressure during pregnancy. It is one of the most common complications of pregnancy. The purpose of this study was to identify biomarkers related to mitochondria and glycometabolism in GDM and explore potential regulatory mechanisms. GDM transcriptome datasets were analyzed for differential expression to identify candidate genes and their functions. Machine learning and expression validation were used to find biomarkers. Enrichment analysis, drug prediction, immune infiltration analysis, and molecular docking were conducted to explore biomarker mechanisms. Reverse transcription-quantitative PCR analysis was done on clinical samples. Two biomarkers, <i>ALDH2</i> and <i>ENDOG</i>, were found to be involved in the “B cell receptor signaling pathway”. Nineteen immune cell types, including memory B cells, were identified as differentially expressed. <i>ALDH2</i> and <i>ENDOG</i> showed high correlations with effector memory CD4 T cells. Seven drugs were linked to both biomarkers. The binding affinities of <i>ALDH2</i> and <i>ENDOG</i> with 4-Hydroperoxycyclophosphamide were determined. Quantitative reverse transcription PCR analysis confirmed the upregulation of <i>ALDH2</i> and <i>ENDOG</i> in the disease group compared to the control group. The <i>ALDH2</i> and <i>ENDOG</i> dual-gene panel exhibits promising potential for early GDM diagnosis. Notably, further protein-level and functional validation is indispensable before the clinical translation of these biomarker findings.</p>

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Identification and validation of biomarkers associated with mitochondria and glycometabolism in gestational diabetes mellitus

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月29日

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  • Jingyun Gao,
  • Xianmei Lin,
  • Zhaozhao Hua,
  • Fang You,
  • Weidong Wu

摘要

Gestational diabetes mellitus (GDM) can elevate the likelihood of developing high blood pressure during pregnancy. It is one of the most common complications of pregnancy. The purpose of this study was to identify biomarkers related to mitochondria and glycometabolism in GDM and explore potential regulatory mechanisms. GDM transcriptome datasets were analyzed for differential expression to identify candidate genes and their functions. Machine learning and expression validation were used to find biomarkers. Enrichment analysis, drug prediction, immune infiltration analysis, and molecular docking were conducted to explore biomarker mechanisms. Reverse transcription-quantitative PCR analysis was done on clinical samples. Two biomarkers, ALDH2 and ENDOG, were found to be involved in the “B cell receptor signaling pathway”. Nineteen immune cell types, including memory B cells, were identified as differentially expressed. ALDH2 and ENDOG showed high correlations with effector memory CD4 T cells. Seven drugs were linked to both biomarkers. The binding affinities of ALDH2 and ENDOG with 4-Hydroperoxycyclophosphamide were determined. Quantitative reverse transcription PCR analysis confirmed the upregulation of ALDH2 and ENDOG in the disease group compared to the control group. The ALDH2 and ENDOG dual-gene panel exhibits promising potential for early GDM diagnosis. Notably, further protein-level and functional validation is indispensable before the clinical translation of these biomarker findings.