Bioinformatic analysis of the SPs and NFTs proteomes unravel putative biomarker candidates for Alzheimer's disease.

Aging is the main risk factor for the appearance of age-related neurodegenerative diseases, including Alzheimer's disease (AD). AD is the most common form of dementia, characterized by the presence of senile plaques (SPs) and neurofibrillary tangles (NFTs), the main histopathological hallmarks in AD brains. The core of these deposits are predominantly amyloid fibrils in SPs and hyperphosphorylated Tau protein in NFTs, but other molecular components can be found associated with these pathological lesions. Herein, an extensive literature review was carried out to obtain the SPs and NFTs proteomes, followed by a bioinformatic analysis and further putative biomarker validation. For SPs, 857 proteins were recovered, and, for NFTs, 627 proteins of which 375 occur in both groups and represent the common proteome. Gene Ontology (GO) enrichment analysis permitted the identification of biological processes and the molecular functions most associated with these lesions. Analysis of the SPs and NFTs common proteins unraveled pathways and molecular targets linking both histopathological events. Further, validation of a putative phosphotarget arising from the in silico analysis was performed in serum-derived extracellular vesicles from AD patients. This bioinformatic approach contributed to the identification of putative molecular targets, valuable for AD diagnostic or therapeutic intervention.

BIN1 rs744373 SNP and APOE alleles specifically associate to common diseases.

APOE ε4 and BIN1 are the two main genetic risk factors for sporadic Alzheimer's Disease (AD). Among several BIN1 variants, the rs744373 is frequently associated with AD risk by contributing to tau pathology and poor cognitive performance. This study addressed the association of APOE and BIN1 rs744373 to specific characteristics in a Portuguese primary care-based study group, denoted pcb-Cohort. The study included 590 participants from five primary care health centers in the Aveiro district of Portugal. Individuals were evaluated and scored for cognitive and clinical characteristics, and blood samples were collected from the volunteers meeting the inclusion and exclusion criteria (N = 505). APOE and BIN1 genotypes were determined, and their association with cognitive characteristics and other diseases that might contribute to cognitive deficits, namely depression, hypertension, type 2 diabetes, dyslipidemia, osteoarticular diseases, gastrointestinal diseases, cardiovascular and respiratory diseases, was assessed. The diseases attributed to the study group were those previously diagnosed and confirmed by specialists. The results generated through multivariate analysis show that APOE ε4 carriers significantly associated with poorer cognitive performance (OR = 2.527; p = 0.031). Additionally, there was a significant risk of dyslipidemia for APOE ε4 carriers (OR = 1.804; p = 0.036), whereas BIN1 rs744373 risk-allele carriers were at a significantly lower risk of having dyslipidemia (OR = 0.558; p = 0.006). Correlations were evident for respiratory diseases in which APOE ε4 showed a protective tendency (OR = 0.515; p = 0.088), and BIN1 had a significative protective profile (OR = 0.556; p = 0.026). Not of statistical significance, APOE ε2 showed a trend to protect against type 2 diabetes (OR = 0.342; p = 0.093), in contrast BIN1 rs744373 risk-allele carriers were more likely to exhibit the disease (OR = 1.491; p = 0.099). The data here presented clearly show, for the first time, that the two top genetic risk factors for sporadic AD impact a similar group of common diseases, namely dyslipidemia, respiratory diseases, and type 2 diabetes.

Novel Exosome Biomarker Candidates for Alzheimer's Disease Unravelled Through Mass Spectrometry Analysis.

Exosomes are small extracellular vesicles (EVs) present in human biofluids that can transport specific disease-associated molecules. Consequently blood-derived exosomes have emerged as important peripheral biomarker sources for a wide range of diseases, among them Alzheimer's disease (AD). Although there is no effective cure for AD, an accurate diagnosis, relying on easily accessible peripheral biofluids, is still necessary to discriminate this disease from other dementias, test potential therapies and even monitor rate of disease progression. The ultimate goal is to produce a cost-effective and widely available alternative, which can also be employed as a first clinical screen. In this study, EVs with exosome-like characteristics were isolated from serum of Controls and AD cases through precipitation- and column-based methods, followed by mass spectrometry analysis. The resulting proteomes were characterized by Gene Ontology (GO) and multivariate analyses. Although GO terms were similar for exosomes' proteomes of Controls and ADs, using both methodologies, a clear segregation of disease cases was obtained when using the precipitation-based method. Nine significantly different abundant proteins were identified between Controls and AD cases, representing putative biomarker candidate targets. Among them are AACT and C4BPα, two Aß-binding proteins, whose exosome levels were further validated in individuals from independent cohorts using antibody-based approaches. The findings discussed represent an important contribution to the identification of novel exosomal biomarker candidates useful as potential blood-based tools for AD diagnosis.

Potential of FTIR Spectroscopy Applied to Exosomes for Alzheimer's Disease Discrimination: A Pilot Study.

Alzheimer's disease (AD) diagnosis is based on psychological and imaging tests but can also include monitoring cerebrospinal fluid (CSF) biomarkers. However, CSF based-neurochemical approaches are expensive and invasive, limiting their use to well-equipped settings. In contrast, blood-based biomarkers are minimally invasive, cost-effective, and a widely accessible alternative. Blood-derived exosomes have recently emerged as a reliable AD biomarker source, carrying disease-specific cargo. Fourier-transformed infrared (FTIR) spectroscopy meets the criteria for an ideal diagnostic methodology since it is rapid, easy to implement, and has high reproducibility. This metabolome-based technique is useful for diagnosing a broad range of diseases, although to our knowledge, no reports for FTIR spectroscopy applied to exosomes in AD exist. In this ground-breaking pilot study, FTIR spectra of serum and serum-derived exosomes from two independent cohorts were acquired and analyzed using multivariate analysis. The regional UA-cohort includes 9 individuals, clinically diagnosed with AD, mean age of 78.7 years old; and the UMG-cohort comprises 12 individuals, clinically diagnosed with AD (based on molecular and/or imaging data), mean age of 73.2 years old. Unsupervised principal component analysis of FTIR spectra of serum-derived exosomes revealed higher discriminatory value for AD cases when compared to serum as a whole. Consistently, the partial least-squares analysis revealed that serum-derived exosomes present higher correlations than serum. In addition, the second derivative peak area calculation also revealed significant differences among Controls and AD cases. The results obtained suggest that this methodology can discriminate cases from Controls and thus be potential useful to assist in AD clinical diagnosis.