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妊娠期糖尿病的代谢组学和蛋白质组学联合分析

A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus.

作者信息

Hajduk Joanna, Klupczynska Agnieszka, Dereziński Paweł, Matysiak Jan, Kokot Piotr, Nowak Dorota M, Gajęcka Marzena, Nowak-Markwitz Ewa, Kokot Zenon J

机构信息

Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, Poznań 60-780, Poland.

Obstetrics and Gynecology Ward, District Hospital in Mielec, 22a Żeromskiego Street, Mielec 39-300, Poland.

出版信息

Int J Mol Sci. 2015 Dec 16;16(12):30034-45. doi: 10.3390/ijms161226133.

Abstract

The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, L-citrulline, L-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44%) and specificity (84.62%), as well as the total group membership classification value (90.32%) calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases.

摘要

这项初步研究的目的是应用一种新型的代谢组学和蛋白质组学联合方法来分析妊娠期糖尿病。研究使用了来自确诊妊娠期糖尿病孕妇(n = 18)和匹配对照组(n = 13)的血浆样本。基于质谱的分析能够确定42种游离氨基酸和低分子量肽谱。在分析组中观察到几种肽的不同表达和氨基酸谱的改变。蛋白质组学和代谢组学数据的结合使得能够获得具有高鉴别力的模型,其中乙醇胺、L-瓜氨酸、L-天冬酰胺等氨基酸以及质荷比为1488.59、4111.89和2913.15的肽离子对模型的贡献最大。与单独分析氨基酸水平或肽离子强度相比,根据联合模型的事后分类矩阵计算得出的灵敏度(94.44%)、特异性(84.62%)以及总组成员分类值(90.32%)是最高的。所获得的结果表明,无论样本量大小,蛋白质组学和代谢组学分析整合具有很大潜力。这种有前景的方法连同对受试者的临床评估也可用于其他疾病的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f5b/4691080/b7403c6a9fd9/ijms-16-26133-g001.jpg

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