Untargeted Metabolomic Profiling Reveals Differentially Expressed Serum Metabolites and Pathways in Type 2 Diabetes Patients with and without Cognitive Decline: A Cross-Sectional Study

代谢组学 代谢物 代谢途径 代谢组 生物化学 生物 精氨酸 2型糖尿病 小桶 新陈代谢 化学 生物信息学 糖尿病 内分泌学 氨基酸 转录组 基因表达 基因
作者
Neyla S. Al-Akl,Olfa Khalifa,Georgios Ponirakis,Aijaz Parray,Marwan Ramadan,Shafi Khan,Mani Chandran,Raheem Ayadathil,Ahmed Elsotouhy,Ahmed Own,Hanadi Al Hamad,Julie Decock,Nehad M. Alajez,Omar Albagha,Rayaz A. Malik,Omar M. A. El‐Agnaf,Abdelilah Arredouani
出处
期刊:International Journal of Molecular Sciences [Multidisciplinary Digital Publishing Institute]
卷期号:25 (4): 2247-2247
标识
DOI:10.3390/ijms25042247
摘要

Diabetes is recognized as a risk factor for cognitive decline, but the underlying mechanisms remain elusive. We aimed to identify the metabolic pathways altered in diabetes-associated cognitive decline (DACD) using untargeted metabolomics. We conducted liquid chromatography-mass spectrometry-based untargeted metabolomics to profile serum metabolite levels in 100 patients with type 2 diabetes (T2D) (54 without and 46 with DACD). Multivariate statistical tools were used to identify the differentially expressed metabolites (DEMs), and enrichment and pathways analyses were used to identify the signaling pathways associated with the DEMs. The receiver operating characteristic (ROC) analysis was employed to assess the diagnostic accuracy of a set of metabolites. We identified twenty DEMs, seven up- and thirteen downregulated in the DACD vs. DM group. Chemometric analysis revealed distinct clustering between the two groups. Metabolite set enrichment analysis found significant enrichment in various metabolite sets, including galactose metabolism, arginine and unsaturated fatty acid biosynthesis, citrate cycle, fructose and mannose, alanine, aspartate, and glutamate metabolism. Pathway analysis identified six significantly altered pathways, including arginine and unsaturated fatty acid biosynthesis, and the metabolism of the citrate cycle, alanine, aspartate, glutamate, a-linolenic acid, and glycerophospholipids. Classifier models with AUC-ROC > 90% were developed using individual metabolites or a combination of individual metabolites and metabolite ratios. Our study provides evidence of perturbations in multiple metabolic pathways in patients with DACD. The distinct DEMs identified in this study hold promise as diagnostic biomarkers for DACD patients.

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