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

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.