Discovery of metabolic biomarkers for gestational diabetes mellitus in a Chinese population.
Discovery of metabolic biomarkers for gestational diabetes mellitus in a Chinese population.
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中国人群妊娠期糖尿病代谢生物标志物的发现
DOI：
10.1186/s12986-021-00606-8
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发表时间：
2021-08-21
影响因子：
4.5
通讯作者：
Hu C
中科院分区：
文献类型：
--
作者：
Lu W;Luo M;Fang X;Zhang R;Li S;Tang M;Yu X;Hu C
妊娠期糖尿病(GDM)是最常见的妊娠并发症之一，可导致母亲和婴儿的发病率和死亡率。代谢组学为GDM的发病机制提供了新的见解，需要对GDM的代谢产物进行系统分析，为GDM的诊断和机制研究提供更多线索。本研究旨在揭示正常孕妇和妊娠期糖尿病患者的代谢差异，并确认这些新发现的临床意义。方法对200名健康孕妇和200名妊娠期糖尿病患者、199名正常对照和199名妊娠晚期妊娠期糖尿病患者的血清进行代谢定量。功能和途径分析都被用来探索这两组代谢物所涉及的生物学作用。然后结合机器学习方法识别GDM代谢物生物标志物，并构建Logistic回归模型以评估预测效率。结果发现中期妊娠组有57个差异表达代谢物(DEM)，其中3-甲基-2-氧戊酸是最显著的代谢物。同样，在妊娠晚期组中发现72个DEM，最显著的代谢物是酮亮氨酸和α-酮异戊酸。这些DEM主要参与氨基酸、脂肪酸和胆汁酸的代谢途径。对于选定的代谢物生物标志物，Logistic回归模型得出中期和晚期妊娠组的曲线下面积分别为0.807和0.81%。此外，DEM/生物标志物与GDM相关指标存在显著相关性。结论健康孕妇与GDM患者存在代谢差异。生物标记物与临床指标之间的关系也被研究，这可能为GDM的病理提供洞察力。
BackgroundGestational diabetes mellitus (GDM), one of the most common pregnancy complications, can lead to morbidity and mortality in both the mother and the infant. Metabolomics has provided new insights into the pathology of GDM and systemic analysis of GDM with metabolites is required for providing more clues for GDM diagnosis and mechanism research. This study aims to reveal metabolic differences between normal pregnant women and GDM patients in the second- and third-trimester stages and to confirm the clinical relevance of these new findings.MethodsMetabolites were quantitated with the serum samples of 200 healthy pregnant women and 200 GDM women in the second trimester, 199 normal controls, and 199 GDM patients in the third trimester. Both function and pathway analyses were applied to explore biological roles involved in the two sets of metabolites. Then the trimester stage-specific GDM metabolite biomarkers were identified by combining machine learning approaches, and the logistic regression models were constructed to evaluate predictive efficiency. Finally, the weighted gene co-expression network analysis method was used to further capture the associations between metabolite modules with biomarkers and clinical indices.ResultsThis study revealed that 57 differentially expressed metabolites (DEMs) were discovered in the second-trimester group, among which the most significant one was 3-methyl-2-oxovaleric acid. Similarly, 72 DEMs were found in the third-trimester group, and the most significant metabolites were ketoleucine and alpha-ketoisovaleric acid. These DEMs were mainly involved in the metabolism pathway of amino acids, fatty acids and bile acids. The logistic regression models for selected metabolite biomarkers achieved the area under the curve values of 0.807 and 0.81 for the second- and third-trimester groups. Furthermore, significant associations were found between DEMs/biomarkers and GDM-related indices.ConclusionsMetabolic differences between healthy pregnant women and GDM patients were found. Associations between biomarkers and clinical indices were also investigated, which may provide insights into pathology of GDM.
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影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
影响因子：
8.1
作者：
Lerin C;Goldfine AB;Boes T;Liu M;Kasif S;Dreyfuss JM;De Sousa-Coelho AL;Daher G;Manoli I;Sysol JR;Isganaitis E;Jessen N;Goodyear LJ;Beebe K;Gall W;Venditti CP;Patti ME
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影响因子：
37.8
作者：
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通讯作者：
Muller, Dominik N.
影响因子：
4.3
作者：
Liu, Tianhu;Li, Jiaxun;Dong, Fang
通讯作者：
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与中国妊娠期糖尿病相关的代谢组生物标志物和新型饮食因素
影响因子：
3.6
作者：
Chen, Xuyang;de Seymour, Jamie V.;Baker, Philip N.
通讯作者：
Baker, Philip N.