Discovering new peripheral plasma biomarkers to identify cognitive decline in type 2 diabetes - Yu, Haitao; Gao, Yang; He, Ting; Li, Mengzhu; Zhang, Yao; Zheng, Jie; Jiang, Bijun; Chen, Chongyang; Ke, Dan; Liu, Yanchao; Wang, Jian-Zhi (Frontiers in Cell and Developmental Biology, 2022)
Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer's disease (AD), thus, identifying who among the increasing T2DM populations may develop into AD is important for early intervention. By using TMT-labeling coupled high-throughput mass spectrometry, we conducted a comprehensive plasma proteomic analysis in none-T2DM people (Ctrl, n=30), and the age-/sex-matched T2DM patients with mild cognitive impairment (T2DM-MCI, n=30) or T2DM without MCI (T2DM-nMCI, n=25). The candidate biomarkers identified by proteomics and bioinformatics analyses were verified by ELISA, and their diagnostic capabilities were evaluated with machine learning. A total of 53 differentially expressed proteins (DEPs) were identified in T2DM-MCI compared with T2DM-nMCI patients. These DEPs were significantly enriched in multiple biological processes, such as amyloid neuropathies, CNS disorders, and metabolic acidosis. Among the DEPs, alpha-1-antitrypsin (SERPINA1), major viral protein (PRNP), valosin-containing protein (VCP) showed strong collection with AD high-risk genes APP, MAPT, APOE, PSEN1, and PSEN2. And the levels of PP2A cancer inhibitor (CIP2A), PRNP, corticotropin releasing factor binding protein (CRHBP) were significantly increased, while the level of VCP was decreased in T2DM-MCI patients compared with the T2DM-nMCI, and these changes were correlated with the mini-mental state examination (MMSE) score. Further machine learning data showed that increases of PRNP, CRHBP, VCP, and rGSK-3β(T/S9) (ratio of total to serine-9-phosphorylated glycogen synthase kinase-3β) had the greatest power to identify mild cognitive decline in T2DM patients.