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Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer’s disease (AD), and 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), and valosin-containing protein (VCP) showed strong correlation with AD high-risk genes APP, MAPT, APOE, PSEN1, and PSEN2. Also, 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 that of the T2DM-nMCI, and these changes were correlated with the Mini-Mental State Examination (MMSE) score. Further machine learning data showed that increases in 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.

BackgroundThe alternative usage of promoters provides a way to regulate gene expression, has a significant influence on the transcriptome, and contributes to the cellular transformation of cancer. However, the function of alternative promoters (APs) in hepatocellular carcinoma (HCC) has not been systematically studied yet. In addition, the potential mechanism of regulation to the usage of APs remains unclear. DNA methylation, one of the most aberrant epigenetic modifications in cancers, is known to regulate transcriptional activity. Whether DNA methylation regulates the usage of APs needs to be explored. Here, we aim to investigate the effects of DNA methylation on usage of APs in HCC.MethodsPromoter activities were calculated based on RNA-seq data. Functional enrichment analysis was implemented to conduct GO terms. Correlation tests were used to detect the correlation between promoter activity and methylation status. The LASSO regression model was used to generate a diagnostic model. Kaplan–Meier analysis was used to compare the overall survival between high and low methylation groups. RNA-seq and whole-genome bisulfite sequencing (WGBS) in HCC samples were performed to validate the correlation of promoter activity and methylation.ResultsWe identified 855 APs in total, which could be well used to distinguish cancer from normal samples. The correlation of promoter activity and DNA methylation in APs was observed, and the APs with negative correlation were defined as methylation-regulated APs (mrAPs). Six mrAPs were identified to generate a diagnostic model with good performance (AUC = 0.97). Notably, the majority of mrAPs had CpG sites that could be used to predict clinical outcomes by methylation status. Finally, we verified 85.6% of promoter activity variation and 92.3% of methylation changes in our paired RNA-seq and WGBS samples, respectively. The negative correlation between promoter activity and methylation status was further confirmed in our HCC samples.ConclusionThe aberrant methylation status plays a critical role in the precision usage of APs in HCC, which sheds light on the mechanism of cancer development and provides a new insight into cancer screening and treatment.