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妊娠期糖尿病:对胎儿神经发育、肠道菌群失调的影响以及精准医学的前景

Gestational diabetes mellitus: Impacts on fetal neurodevelopment, gut dysbiosis, and the promise of precision medicine.

作者信息

Biete Michelle, Vasudevan Sona

机构信息

Department of Biochemistry, Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC, United States.

出版信息

Front Mol Biosci. 2024 Jul 11;11:1420664. doi: 10.3389/fmolb.2024.1420664. eCollection 2024.

Abstract

Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting approximately 16.5% of pregnancies worldwide and causing significant health concerns. GDM is a serious pregnancy complication caused by chronic insulin resistance in the mother and has been associated with the development of neurodevelopmental disorders in offspring. Emerging data support the notion that GDM affects both the maternal and fetal microbiome, altering the composition and function of the gut microbiota, resulting in dysbiosis. The observed dysregulation of microbial presence in GDM pregnancies has been connected to fetal neurodevelopmental problems. Several reviews have focused on the intricate development of maternal dysbiosis affecting the fetal microbiome. Omics data have been instrumental in deciphering the underlying relationship among GDM, gut dysbiosis, and fetal neurodevelopment, paving the way for precision medicine. Microbiome-associated omics analyses help elucidate how dysbiosis contributes to metabolic disturbances and inflammation, linking microbial changes to adverse pregnancy outcomes such as those seen in GDM. Integrating omics data across these different layers-genomics, transcriptomics, proteomics, metabolomics, and microbiomics-offers a comprehensive view of the molecular landscape underlying GDM. This review outlines the affected pathways and proposes future developments and possible personalized therapeutic interventions by integrating omics data on the maternal microbiome, genetics, lifestyle factors, and other relevant biomarkers aimed at identifying women at high risk of developing GDM. For example, machine learning tools have emerged with powerful capabilities to extract meaningful insights from large datasets.

摘要

妊娠期糖尿病(GDM)是一种常见的代谢紊乱疾病,影响着全球约16.5%的孕妇,并引发了重大的健康问题。GDM是由母亲慢性胰岛素抵抗引起的严重妊娠并发症,与后代神经发育障碍的发生有关。新出现的数据支持这样一种观点,即GDM会影响母体和胎儿的微生物群,改变肠道微生物群的组成和功能,导致生态失调。在GDM妊娠中观察到的微生物存在失调与胎儿神经发育问题有关。几项综述集中探讨了影响胎儿微生物群的母体生态失调的复杂发展。组学数据有助于解读GDM、肠道生态失调和胎儿神经发育之间的潜在关系,为精准医学铺平了道路。与微生物群相关的组学分析有助于阐明生态失调如何导致代谢紊乱和炎症,将微生物变化与不良妊娠结局(如GDM中所见的结局)联系起来。整合跨这些不同层面(基因组学、转录组学、蛋白质组学、代谢组学和微生物组学)的组学数据,提供了GDM潜在分子格局的全面视图。本综述概述了受影响的途径,并通过整合关于母体微生物群、遗传学、生活方式因素和其他相关生物标志物的组学数据,提出了未来的发展方向和可能的个性化治疗干预措施,旨在识别有患GDM高风险的女性。例如,机器学习工具已经出现,具有从大型数据集中提取有意义见解的强大能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d20/11269231/1971859b99fe/fmolb-11-1420664-g001.jpg

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