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)