TY - JOUR
T1 - Plasma metabolomics and lipidomics signatures of motoric cognitive risk syndrome in community-dwelling older adults
AU - Li, Wanmeng
AU - Sun, Xuelian
AU - Liu, Yu
AU - Ge, Meiling
AU - Lu, Ying
AU - Liu, Xiaolei
AU - Zhou, Lixing
AU - Liu, Xiaohui
AU - Dong, Biao
AU - Yue, Jirong
AU - Xue, Qianli
AU - Dai, Lunzhi
AU - Dong, Birong
N1 - Funding Information:
This work was supported by the National Key R&D Program of China (Nos. 2018YFC2000305 and 2018YFC2002400); the Project of Max Cynader Academy of Brain Workstation, WCHSCU (No. HXYS19005); the Department of Aging and Health, National Health Commission PRC (No. ZX2019023); and the Chengdu Science and Technology Bureau Major Science and Technology Application Demonstration Project (No. 2019YF0900083SN). The financial sponsors had no role in the design, implementation, analyses, or reporting of the results.
Publisher Copyright:
Copyright © 2022 Li, Sun, Liu, Ge, Lu, Liu, Zhou, Liu, Dong, Yue, Xue, Dai and Dong.
PY - 2022/9/7
Y1 - 2022/9/7
N2 - Introduction: Motoric cognitive risk syndrome (MCR) is characterized by subjective cognitive complaints (SCCs) and slow gait (SG). Metabolomics and lipidomics may potentiate disclosure of the underlying mechanisms of MCR. Methods: This was a cross-sectional study from the West China Health and Aging Trend cohort study (WCHAT). The operational definition of MCR is the presence of SCCs and SG without dementia or mobility disability. The test and analysis were based on untargeted metabolomics and lipidomics, consensus clustering, lasso regression and 10-fold cross-validation. Results: This study enrolled 6,031 individuals for clinical analysis and 577 plasma samples for omics analysis. The overall prevalence of MCR was 9.7%, and the prevalence of MCR-only, assessed cognitive impairment-only (CI-only) and MCR-CI were 7.5, 13.3, and 2.1%, respectively. By consensus clustering analysis, MCR-only was clustered into three metabolic subtypes, MCR-I, MCR-II and MCR-III. Clinically, body fat mass (OR = 0.89, CI = 0.82–0.96) was negatively correlated with MCR-I, and comorbidity (OR = 2.19, CI = 1.10–4.38) was positively correlated with MCR-III. Diabetes mellitus had the highest ORs above 1 in MCR-II and MCR-III (OR = 3.18, CI = 1.02–9.91; OR = 2.83, CI = 1.33–6.04, respectively). The risk metabolites of MCR-III showed relatively high similarity with those of cognitive impairment. Notably, L-proline, L-cystine, ADMA, and N1-acetylspermidine were significantly changed in MCR-only, and PC(40:3), SM(32:1), TG(51:3), eicosanoic acid(20:1), methyl-D-galactoside and TG(50:3) contributed most to the prediction model for MCR-III. Interpretation: Pre-dementia syndrome of MCR has distinct metabolic subtypes, and SCCs and SG may cause different metabolic changes to develop MCR.
AB - Introduction: Motoric cognitive risk syndrome (MCR) is characterized by subjective cognitive complaints (SCCs) and slow gait (SG). Metabolomics and lipidomics may potentiate disclosure of the underlying mechanisms of MCR. Methods: This was a cross-sectional study from the West China Health and Aging Trend cohort study (WCHAT). The operational definition of MCR is the presence of SCCs and SG without dementia or mobility disability. The test and analysis were based on untargeted metabolomics and lipidomics, consensus clustering, lasso regression and 10-fold cross-validation. Results: This study enrolled 6,031 individuals for clinical analysis and 577 plasma samples for omics analysis. The overall prevalence of MCR was 9.7%, and the prevalence of MCR-only, assessed cognitive impairment-only (CI-only) and MCR-CI were 7.5, 13.3, and 2.1%, respectively. By consensus clustering analysis, MCR-only was clustered into three metabolic subtypes, MCR-I, MCR-II and MCR-III. Clinically, body fat mass (OR = 0.89, CI = 0.82–0.96) was negatively correlated with MCR-I, and comorbidity (OR = 2.19, CI = 1.10–4.38) was positively correlated with MCR-III. Diabetes mellitus had the highest ORs above 1 in MCR-II and MCR-III (OR = 3.18, CI = 1.02–9.91; OR = 2.83, CI = 1.33–6.04, respectively). The risk metabolites of MCR-III showed relatively high similarity with those of cognitive impairment. Notably, L-proline, L-cystine, ADMA, and N1-acetylspermidine were significantly changed in MCR-only, and PC(40:3), SM(32:1), TG(51:3), eicosanoic acid(20:1), methyl-D-galactoside and TG(50:3) contributed most to the prediction model for MCR-III. Interpretation: Pre-dementia syndrome of MCR has distinct metabolic subtypes, and SCCs and SG may cause different metabolic changes to develop MCR.
KW - cross-sectional study
KW - metabolomics and lipidomics
KW - motoric cognitive risk syndrome
KW - pre-dementia
KW - slow gait speed
KW - subjective cognitive complaint
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U2 - 10.3389/fnagi.2022.977191
DO - 10.3389/fnagi.2022.977191
M3 - Article
C2 - 36158552
AN - SCOPUS:85138435038
SN - 1663-4365
VL - 14
JO - Frontiers in Aging Neuroscience
JF - Frontiers in Aging Neuroscience
M1 - 977191
ER -