Multiomics integrative analysis identifies APOE allele-specific blood biomarkers associated to Alzheimer's disease etiopathogenesis.

Alzheimer's disease (AD) is the most common form of dementia, currently affecting 35 million people worldwide. Apolipoprotein E (APOE) ε4 allele is the major risk factor for sporadic, late-onset AD (LOAD), which comprises over 95% of AD cases, increasing the risk of AD 4-12 fold. Despite this, the role of APOE in AD pathogenesis is still a mystery. Aiming for a better understanding of APOE-specific effects, the ADAPTED consortium analysed and integrated publicly available data of multiple OMICS technologies from both plasma and brain stratified by APOE haplotype (APOE2, APOE3 and APOE4). Combining genome-wide association studies (GWAS) with differential mRNA and protein expression analyses and single-nuclei transcriptomics, we identified genes and pathways contributing to AD in both APOE dependent and independent fashion. Interestingly, we characterised a set of biomarkers showing plasma and brain consistent protein profiles and opposite trends in APOE2 and APOE4 AD cases that could constitute screening tools for a disease that lacks specific blood biomarkers. Beside the identification of APOE-specific signatures, our findings advocate that this novel approach, based on the concordance across OMIC layers and tissues, is an effective strategy for overcoming the limitations of often underpowered single-OMICS studies.

Decreased Blood Level of MFSD2a as a Potential Biomarker of Alzheimer's Disease.

The protein Major Facilitator Superfamily Domain containing 2A (MFSD2a) was recently described as the primary carrier for docosahexaenoic acid (DHA) into the brain. Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by lower DHA levels in blood lipids. The aim of this study was to investigate the expression of MFSD2a in the whole blood and brain as a potential biomarker of AD. Three groups were established: 38 healthy controls, 48 subjects with moderate AD (GDS4), and 47 with severe AD (GDS6). We analyzed postmortem brain samples from the hippocampus of 11 healthy controls and 11 severe AD patients. Fatty acid (FA) was determined in serum and brain by gas chromatography. Blood and brain MFSD2a protein expression was analyzed by Western blotting. We found a significant and progressive decline of MFSD2a levels in blood of AD patients (Control 0.83 ± 0.13, GDS4 0.72 ± 0.09, GDS6 0.48 ± 0.05*, p ˂ 0.01). We also corroborated a significant reduction of DHA and other n-3 long-chain polyunsaturated FA in serum of AD. No differences were found in MFSD2a expression or FA levels in brain of controls and AD subjects. MFSD2A carrier was analyzed in AD patients for the first time and the level of MFSD2a in the whole blood could be a potential biomarker of this disease.

Novel Mutation (Gly212Val) in the PS2 Gene Associated with Early-Onset Familial Alzheimer's Disease.

Mutations in the presenilin 2 gene (PS2) are an extremely rare cause of early-onset autosomal dominant Alzheimer's disease (AD), accounting for only 5% of these families. These cases represent a particular model of AD, and the scarcity of reports on their clinical phenotypes makes them of great interest. We report a family with early-onset autosomal dominant AD in four members, where the two living siblings were found to carry the novel PS2 mutation Gly212Val (exon 7, transmembrane domain IV) with highly predicted pathogenicity. Age at onset ranged from 60 to 65 years and three of the cases died between ages 74 and 76 years. Clinical phenotype was quite homogeneous among affected members of the family, and overall features, including cognitive decline, tau/p-tau and amyloid-ß cerebrospinal fluid markers, neuroimaging, and neuropathology were consistent with typical AD. Lewy bodies were present but restricted to the amygdala.

Amyloid precursor protein metabolism and inflammation markers in preclinical Alzheimer disease.

OBJECTIVE: To investigate CSF markers involved in amyloid precursor protein processing, neuronal damage, and neuroinflammation in the preclinical stages of Alzheimer disease (AD) and participants with suspected non-Alzheimer pathology (SNAP). METHODS: We collected CSF from 266 cognitively normal volunteers participating in a cross-sectional multicenter study (the SIGNAL study) to investigate markers involved in amyloid precursor protein processing (Aß42, sAPPß, ß-secretase activity), neuronal damage (total-tau [t-tau], phospho-tau [p-tau]), and neuroinflammation (YKL-40). We analyzed the relationship among biomarkers, clinical variables, and the APOE genotype, and compared biomarker levels across the preclinical stages of the National Institute on Aging-Alzheimer's Association classification: stage 0, 1, 2, 3, and SNAP. RESULTS: The median age in the whole cohort was 58.8 years (range 39.8-81.6). Participants in stages 2-3 and SNAP had higher levels of YKL-40 than those in stages 0 and 1. Participants with SNAP had higher levels of sAPPß than participants in stage 0 and 1. No differences were found between stages 0, 1, and 2-3 in sAPPß and ß-secretase activity in CSF. Age correlated with t-tau, p-tau, and YKL-40. It also correlated with Aß42, but only in APOE ε4 carriers. Aß42 correlated positively with t-tau, sAPPß, and YKL-40 in participants with normal Aß42. CONCLUSIONS: Our findings suggest that inflammation in the CNS increases in normal aging and is intimately related to markers of neurodegeneration in the preclinical stages of AD and SNAP. sAPPß and ß-secretase activity are not useful diagnostic or staging markers in preclinical AD.

A blood-based, 7-metabolite signature for the early diagnosis of Alzheimer's disease.

Accurate blood-based biomarkers of Alzheimer's disease (AD) could constitute simple, inexpensive, and non-invasive tools for the early diagnosis and treatment of this devastating neurodegenerative disease. We sought to develop a robust AD biomarker panel by identifying alterations in plasma metabolites that persist throughout the continuum of AD pathophysiology. Using a multicenter, cross-sectional study design, we based our analysis on metabolites whose levels were altered both in AD patients and in patients with amnestic mild cognitive impairment (aMCI), the earliest identifiable stage of AD. UPLC coupled to mass spectrometry was used to independently compare the levels of 495 plasma metabolites in aMCI (n = 58) and AD (n = 100) patients with those of normal cognition controls (NC, n = 93). Metabolite alterations common to both aMCI and AD patients were used to generate a logistic regression model that accurately distinguished AD from NC patients. The final panel consisted of seven metabolites: three amino acids (glutamic acid, alanine, and aspartic acid), one non-esterified fatty acid (22:6n-3, DHA), one bile acid (deoxycholic acid), one phosphatidylethanolamine [PE(36:4)], and one sphingomyelin [SM(39:1)]. Detailed analysis ruled out the influence of potential confounding variables, including comorbidities and treatments, on each of the seven biomarkers. The final model accurately distinguished AD from NC patients (AUC, 0.918). Importantly, the model also distinguished aMCI from NC patients (AUC, 0.826), indicating its potential diagnostic utility in early disease stages. These findings describe a sensitive biomarker panel that may facilitate the specific detection of early-stage AD through the analysis of plasma samples.