AUTHOR=Li Wanmeng , Sun Xuelian , Liu Yu , Ge Meiling , Lu Ying , Liu Xiaolei , Zhou Lixing , Liu Xiaohui , Dong Biao , Yue Jirong , Xue Qianli , Dai Lunzhi , Dong Birong 

TITLE=Plasma metabolomics and lipidomics signatures of motoric cognitive risk syndrome in community-dwelling older adults

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=Volume 14 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2022.977191

DOI=10.3389/fnagi.2022.977191

ISSN=1663-4365

ABSTRACT=Introduction: Motoric cognitive risk syndrome (MCR) is characterized subjective cognitive complaints (SCC) and slow gait (SG). Metabolomics characteristics potentiate disclosure of the underlying mechanism of MCR.
Methods: This was a cross-sectional study from West China Health and Aging Trend cohort study (WCHAT). The operational definition of MCR is the presence of SCC and SG but without dementia or mobility disability. Untargeted metabolomics and lipidomics, consensus clustering, and lasso regression and 10-fold cross-validation were carried out. 
Results: This study included 6,031 individuals for clinical analysis and 577 for omic 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. MCR-only 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 (OR=3.18 CI=1.02-9.91; OR=2.83 CI=1.33-6.04, respectively) had the highest above 1 ORs for MCR-II and MCR-III, but not for MCR-I. MCR-III was the closest metabolic subtype to the whole CI. Furthermore, the metabolic features of SG were close to MCR-II, while those of SCC were more similar to MCR-III. Notably, L-Proline, L-Cystine, ADMA, and N1-Acetylspermidine were remarkable metabolites of MCR-only, and PC(40:3), SM(32:1), TG(51:3), eicosanoic acid(20:1), methyl-D-galactoside and TG(50:3), were key metabolites in the most fitting prediction model for MCR-III. 
Interpretation: The pre-dementia MCR has distinct metabolic subtypes, and SCC and SG display discordant metabolic features to develop MCR.