Abstract. 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 .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.

Apolipoprotein E (apoE) is a 34 kDa glycoprotein involved in lipid metabolism. The human APOE gene encodes for three different apoE protein isoforms: E2, E3 and E4. The interest in apoE isoforms is high for epidemiological research, patient stratification and identification of those at increased risk for clinical trials and prevention. The isoform apoE4 is associated with increased risk for coronary heart and Alzheimer’s diseases. This paper describes a method for specifically detecting the apoE4 isoform from biological fluids by taking advantage of the capacity of apoE to bind “specifically” to polystyrene surfaces as capture and a specific anti-apoE4 monoclonal antibody as reporter. Our results indicate that the apoE-polystyrene binding interaction is highly stable, resistant to detergents and acid and basic washes. The methodology here described is accurate, easily implementable, fast and cost-effective. Although at present, our technique is unable to discriminate homozygous APOE ε4/ε4 from APOE ε3/ε4 and ε2/ε4 heterozygous, it opens new avenues for the development of inexpensive, yet effective, tests for the detection of apoE4 for patients’ stratification. Preliminary results indicated that this methodology is also adaptable into turbidimetric platforms, which make it a good candidate for clinical implementation through its translation to the clinical analysis routine.

The allele ε4 of the apolipoprotein E gene (APOE ε4) is the major genetic risk factor for non-dominantly inherited Alzheimer’s Disease (AD). Current techniques for APOE ε4 carriers identification show good accuracy but have several disadvantages that limit its implementation in a clinical laboratory. These include the need for sample preprocessing, poor automation, low throughput, requirement of additional equipment, and high cost. We followed ISO 13485 guidelines to validate the e4Risk test, a new latex-enhanced immunoturbidimetric blood assay for apolipoprotein E4 (ApoE4) determination in human plasma samples. The test showed high performance in terms of lot to lot variability, precision, interferences, reagents stability, prozone, and detectability. Furthermore, diagnostic accuracy is almost equal (99%) to the gold standard, APOE ε4 genotyping by polymerase chain reaction (PCR). Furthermore, we demonstrated that the e4Risk test can be adapted to any clinical chemistry analyzer, including the high throughput analyzers present in most hospitals and clinical laboratories. The e4Risk test versatility, low cost, and easiness provides an excellent solution for APOE ε4 carriers identification using the same blood sample drawn for biochemical diagnostic work-up of AD patients, which can have important advantages for patient stratification in clinical trials, preventative strategies for AD, and clinical assessment of risk for brain amyloidosis.

Metabolomics is the comprehensive analysis of small molecules (metabolites) that are intermediates or endpoints of metabolism. Since metabolites change more rapidly to both external and internal stimuli than genes and proteins, metabolomics provides a more sensitive tool to study physiological changes to a wide range of factors such age, medication, or disease status. Therefore, metabolomics is being increasingly used for the study of several pathological states, including complex diseases like Alzheimer's disease (AD).Both untargeted and targeted metabolomics have been applied for AD and both have provided diagnostic algorithms that accurately discriminate healthy patients from patients with AD by combining different metabolites. However, none of these algorithms have been replicated in larger, different cohorts, and a consensus in methodology has been claimed by the scientific community. The AbsoluteIDQ p180 Kit (Biocrates, Life Science AG, Innsbruck, Austria) is to date the only commercially available, validated, and standardized assay that measures up to 188 metabolites in biological samples. This kit unifies methodology in a common user manual and provides quantitative measurements of metabolites, thus facilitating an easier comparison among studies and reducing the technical variability that might contribute to replication failures. Nevertheless, recent studies showed no replication even when using this kit, suggesting that additional measures should be taken to achieve replication of metabolite-based discriminative algorithms. The aim of this chapter is to provide technical guidance on how to apply quantitative metabolomic data to the definition of discriminative algorithms for the diagnosis of neurodegenerative diseases such as AD. This chapter will provide an overview of technical aspects on the whole process, from blood sampling to raw data handling, and will highlight several technical aspects in the process that could hamper replication attempts even when using validated and standardized assays, such as the AbsoluteIDQ p180 Kit.

changes in concentration of and in the CSF and plasma of 5-, 7-, 9-and 12-month-old female transgenic mice using sandwich-ELISA to define a relationship between the plasma Ab and AD progression and, also, to confirm the diagnostic potential of the plasma Ab prior to the plaque formation. Results: We found that plasma Ab(1-42) concentration increases with age, while the concentration of Ab(1-42) in the cerebrospinal fluid (CSF) decreases in 3xTg-AD mice, if measurements were made before formation of ThS-positive plaques in the brain. Conclusions:There is an inverse correlations between the plasma and CSF Ab(1-42) levels until plaques form in transgenic mice's brains and that the plasma Ab concentration possesses the diagnostic potential as a biomarker for diagnosis of early AD stages.