Metabolic signatures and potential biomarkers in the progression of type 2 diabetes mellitus with cognitive impairment patients: a cross-sectional study

Author:

Zheng Jie1,Cheng Fangxiao2,Du Yage1,Song Ying1,Cao Zhaoming3,Li Mingzi1,Lu Yanhui1

Affiliation:

1. School of Nursing, Peking University Health Science Center, Beijing, China

2. Institute of Medical Technology, Peking University Health Science Center, Beijing, China

3. School of Nursing, Jinzhou Medical University, Liaoning, China

Abstract

Abstract Background: Type 2 diabetes mellitus (T2DM), a growing global chronic disease, can increase the risk of cognitive impairment. The microbiota-gut-brain axis has a crucial role in the development of neurological pathologies. Therefore, it is necessary to examine host-gut microbiota metabolites associated with diabetic cognitive impairment (DCI) progression. Objective: This study aimed to describe metabolic signatures, identify potential biomarkers in the progression from T2DM to DCI, and analyze the correlation between the potential biomarkers and clinical characteristics. Methods: A cross-sectional study involving 8 patients with T2DM and 8 with DCI was carried out between May 2018 and May 2020. The characteristic clinical data of the patients, such as demographics, hematological parameters, Mini-Mental State Examination, and Montreal Cognitive Assessment, were collected. Metabolomics profiling measured the host-gut microbiota metabolites in the serum. The potential biomarkers were found by getting intersection of the differential host-gut microbiota metabolites from multidimensional statistics (Orthogonal Partial Least Squares-Discriminant Analysis and permutation plot) and univariate statistics (independent-sample t test and Mann-Whitney U test). In addition, we examined the relationship between potential biomarkers and characteristic clinical data using the Spearman correlation coefficient test. Results: A total of 22 potential biomarkers were identified in the T2DM and DCI groups, including 15 upregulated potential biomarkers (such as gluconolactone, 4-hydroxybenzoic acid, and 3-hydroxyphenylacetic acid) and 7 downregulated potential biomarkers (such as benzoic acid, oxoglutaric acid, and rhamnose) in DCI group. Most of the potential biomarkers were associated with clinical characteristics, such as Mini-Mental State Examination, Montreal Cognitive Assessment, and glycated hemoglobin A1c. Conclusion: This study showed that metabolic signatures in the serum were associated with DCI development and clinical severity, providing new ideas for extensive screening and targeted treatment.

Publisher

Ovid Technologies (Wolters Kluwer Health)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3