In-Depth Blood Proteome Profiling Analysis for Identification of Disease Biomarkers in Mild Cognitive Impairment Patients

Abstract

Mild cognitive impairment (MCI) is a syndrome characterized as an early stage of cognitive deterioration greater than that expected of normal aging. It is a complex condition with a varied etiology which leads to different neurological disorders. There is no specific diagnostic tool for MCI and its prognosis cannot be determined. Therefore, the identification of disease biomarkers that can specify the prognosis of the condition as well as elucidate the pathophysiology is required. The present study investigated the genetic and molecular markers present in whole blood and plasma samples of MCI subjects. The study investigated the proxy single nucleotide polymorphisms (SNPs) to assess their role in MCI disease progression and susceptibility. Six novel proxy SNPs (rs1760252C > A, rs199513T > C, rs990706G > A, rs1651010A > G, rs2274881A > C, rs10816832C > T) were validated via sequence specific PCR out of which rs1760252C > A, rs199513T > C and rs10816832C > T were found to be significantly associated with MCI. The affected genes affected by the SNPs were evaluated for their biological processes using ShinyGO v.0.76.2 while their protein-protein interactions were predicted via STRING v.11.5. The association of the proteins of affected genes elucidates the relationship of the significant SNPs with MCI pathology. The study also investigated the differential expression and differential glycosylation of plasma proteins via two-dimensional gel electrophoresis (2DE) and glycosylation staining as well as analysis of differentially expressed metabolites present in the plasma samples were identified through gas chromatography mass spectrometry (GC MS). Additionally, western blot analysis was also performed to evaluate the expression of activating transcription factor 6 (ATF6) in plasma to understand the endoplasmic reticulum stress (ER) in MCI. Although a slight increase was observed in the expression of ATF6 List of Abbreviations xix between MCI and control group but statistically insignificant, however the trend indicates the presence of ER stress in MCI. The 2DE analysis revealed a total of 8 significant protein spots to be differentially expressed in MCI as compared to normal subjects. The metabolomic analysis of plasma samples via GC-MS revealed a total of 72 metabolites. Further analysis of the screened metabolites through MetaboAnalyst v.5.0, revealed 36 metabolites as statistically different in MCI using Student’s t-test. These significantly differential metabolites are involved in fatty acid biosynthesis, linoleic acid metabolism, steroid biosynthesis, primary bile acid biosynthesis and steroid hormone biosynthesis assessed through Kyoto encyclopedia of genes and genomes (KEGG) Pathway database. The identified proteomic and metabolomic biomarkers could aid in elaborating our understanding of the pathophysiology as well as serve as potential diagnostic and prognostic markers of MCI