Plasma Proteomic Analysis for Alzheimer's Disease Biomarkers, Pathways, and Subgroup Identification

The proteomic profile in plasma samples from patients with complex diseases such as Alzheimer's disease (AD) is a useful tool for identifying potential biomarkers in minimally invasive samples and describing impaired pathways and early disease subgroups. Untargeted proteomics by mass spectrometry was performed on plasma samples from patients of a cognitive disorders unit (data available in BioStudies (S-BSST1631)). Participants were classified as mild cognitive impairment due to AD (MCI-AD, n = 30) or subjective cognitive impairment (SCI, n = 30) based on cerebrospinal fluid (CSF) biomarkers, neuropsychological assessment, and neuroimaging. Discriminant analysis, using partial least-squares (PLS) regression and volcano plot, was performed using the STRING database, and cluster analysis identified AD subtypes. From 1094 detected proteins, 71 differed significantly between groups. PLS and volcano plot analyses identified 45 and 22 variables, respectively (e.g., CRIP1, CRTAC1, LTBP2, MMP14, PLIN3, REG3A, SHH). Most of them were elevated in MCI-AD and correlated to CSF biomarkers and cognition. Altered pathways included the immune system, cell adhesion, and proteolysis, and two MCI-AD subgroups were found based on protein profiles. This study identified 10 proteins as potential plasma biomarkers for early AD detection and highlighted the affected biological pathways, contributing to the understanding of AD physiopathology.