Targeted plasma metabolomics reveals potential biomarkers of the elderly with mild cognitive impairment in Qingdao rural area

IntroductionPrevious research has suggested a link between the onset of Alzheimer’s disease (AD) and metabolic disorder; however, the findings have been inconsistent. To date, the majority of metabolomics studies have focused on AD, resulting in a relative paucity of research on early-stage conditio...

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Main Authors: Yuchi Meng, Murong Cheng, Hongyan Qu, Zhenxue Song, Ling Zhang, Yuanjun Zeng, Dongfeng Zhang, Suyun Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Aging Neuroscience
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Online Access:https://www.frontiersin.org/articles/10.3389/fnagi.2024.1511437/full
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author Yuchi Meng
Murong Cheng
Hongyan Qu
Zhenxue Song
Ling Zhang
Yuanjun Zeng
Dongfeng Zhang
Suyun Li
author_facet Yuchi Meng
Murong Cheng
Hongyan Qu
Zhenxue Song
Ling Zhang
Yuanjun Zeng
Dongfeng Zhang
Suyun Li
author_sort Yuchi Meng
collection DOAJ
description IntroductionPrevious research has suggested a link between the onset of Alzheimer’s disease (AD) and metabolic disorder; however, the findings have been inconsistent. To date, the majority of metabolomics studies have focused on AD, resulting in a relative paucity of research on early-stage conditions such as mild cognitive impairment (MCI) underexplored. In this study, we employed a comprehensive platform for the early screening of individuals with MCI using high-throughput targeted metabolomics.MethodWe included 171 participants including 124 individuals with MCI and 47 healthy subjects. Univariate statistical analysis was conducted using t-tests or Wilcoxon rank-sum tests, with p-values corrected by the Benjamini-Hochberg method. The screening criteria were set at FDR < 0.05 and fold change (FC) > 1.5 or < 0.67. Multivariate analysis was performed using orthogonal partial least squares discriminant analysis (OPLS-DA), where differential metabolites were identified based on variable influence on projection (VIP) scores (VIP > 1 and FDR < 0.05). Random forest analysis was used to further evaluate the ability of the metabolic data to distinguish effectively between the two groups.ResultsA total of 14 differential metabolites were identified, leading to the discovery of a biomarker panel consisting of three plasma metabolites including uric acid, pyruvic acid and isolithocholic acid that effectively distinguished MCI patients from healthy subjects.DiscussionThese findings have provided a comprehensive metabolic profile, offering valuable insights into the early prediction and understanding of the pathogenic processes underlying MCI. This study holds the potential for advancing early detection and intervention strategies for MCI.
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series Frontiers in Aging Neuroscience
spelling doaj-art-34d31b7fad8f4ef3a9fc8a00fe5863f82024-12-18T06:44:05ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652024-12-011610.3389/fnagi.2024.15114371511437Targeted plasma metabolomics reveals potential biomarkers of the elderly with mild cognitive impairment in Qingdao rural areaYuchi MengMurong ChengHongyan QuZhenxue SongLing ZhangYuanjun ZengDongfeng ZhangSuyun LiIntroductionPrevious research has suggested a link between the onset of Alzheimer’s disease (AD) and metabolic disorder; however, the findings have been inconsistent. To date, the majority of metabolomics studies have focused on AD, resulting in a relative paucity of research on early-stage conditions such as mild cognitive impairment (MCI) underexplored. In this study, we employed a comprehensive platform for the early screening of individuals with MCI using high-throughput targeted metabolomics.MethodWe included 171 participants including 124 individuals with MCI and 47 healthy subjects. Univariate statistical analysis was conducted using t-tests or Wilcoxon rank-sum tests, with p-values corrected by the Benjamini-Hochberg method. The screening criteria were set at FDR < 0.05 and fold change (FC) > 1.5 or < 0.67. Multivariate analysis was performed using orthogonal partial least squares discriminant analysis (OPLS-DA), where differential metabolites were identified based on variable influence on projection (VIP) scores (VIP > 1 and FDR < 0.05). Random forest analysis was used to further evaluate the ability of the metabolic data to distinguish effectively between the two groups.ResultsA total of 14 differential metabolites were identified, leading to the discovery of a biomarker panel consisting of three plasma metabolites including uric acid, pyruvic acid and isolithocholic acid that effectively distinguished MCI patients from healthy subjects.DiscussionThese findings have provided a comprehensive metabolic profile, offering valuable insights into the early prediction and understanding of the pathogenic processes underlying MCI. This study holds the potential for advancing early detection and intervention strategies for MCI.https://www.frontiersin.org/articles/10.3389/fnagi.2024.1511437/fullcognitive functionthe elderlymetabolomicsmild cognitive impairmentMCI
spellingShingle Yuchi Meng
Murong Cheng
Hongyan Qu
Zhenxue Song
Ling Zhang
Yuanjun Zeng
Dongfeng Zhang
Suyun Li
Targeted plasma metabolomics reveals potential biomarkers of the elderly with mild cognitive impairment in Qingdao rural area
Frontiers in Aging Neuroscience
cognitive function
the elderly
metabolomics
mild cognitive impairment
MCI
title Targeted plasma metabolomics reveals potential biomarkers of the elderly with mild cognitive impairment in Qingdao rural area
title_full Targeted plasma metabolomics reveals potential biomarkers of the elderly with mild cognitive impairment in Qingdao rural area
title_fullStr Targeted plasma metabolomics reveals potential biomarkers of the elderly with mild cognitive impairment in Qingdao rural area
title_full_unstemmed Targeted plasma metabolomics reveals potential biomarkers of the elderly with mild cognitive impairment in Qingdao rural area
title_short Targeted plasma metabolomics reveals potential biomarkers of the elderly with mild cognitive impairment in Qingdao rural area
title_sort targeted plasma metabolomics reveals potential biomarkers of the elderly with mild cognitive impairment in qingdao rural area
topic cognitive function
the elderly
metabolomics
mild cognitive impairment
MCI
url https://www.frontiersin.org/articles/10.3389/fnagi.2024.1511437/full
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