Alzheimer’s disease (AD) and other dementias are becoming increasingly common in the older population, and the number of people affected is expected to increase in a few years. Nowadays, biomarkers used in early AD diagnosis are expensive and invasive. Therefore, this research field is growing. In fact, peroxidation by-products derived from the oxidation of brain lipids (arachidonic (AA), docosahexanoic (DHA) and adrenic acid (AdA)) could be potential biomarkers, participating in the mechanisms of inflammation, neurotoxicity and cell death in AD pathology. Previous studies have shown specificity between lipid peroxidation compounds and other dementias (e.g., Lewy bodies (DLB), frontotemporal dementia (FTD)), but more research is required. Lipid peroxidation compounds (prostaglandins, isoprostanes, isofurans, neuroprostanes, neurofurans, dihomo-isoprostanes and dihomo-isofurans) were analysed by liquid chromatography and mass spectrometry in plasma samples from participants classified into a healthy group (n = 80), a mild cognitive impairment due to AD group (n = 106), a mild dementia due to AD group (n = 70), an advanced dementia due to AD group (n = 11) and a group of other non-AD dementias (n = 20). Most of these compounds showed statistically significant differences between groups (p < 0.05), showing higher levels for the healthy and non-AD groups than the AD groups. Then, a multivariate analysis was carried out on these compounds, showing good diagnosis indexes (AUC 0.77, sensitivity 81.3%, positive predictive value 81%). Moreover, evaluating AD disease prognosis, two compounds (15-F_2t-IsoP and 14(RS)-14-F_4t-NeuroP) and three total parameters (isoprostanes, isofurans and neurofurans) showed significant differences among groups. Some compounds derived from the oxidation of AA, DHA and AdA have demonstrated their potential use in differential AD diagnosis. Specifically, 15-F_2t-IsoP, 14(RS)-14-F_4t-NeuroP and the total parameters for isoprostanes, isofurans and neurofurans have shown prognostic value for AD from its earliest stages to its most severe form.

Alzheimer’s disease (AD) is the primary type of dementia, followed by frontotemporal lobar degeneration (FTLD). They share some clinical characteristics, mainly at the early stages. So, the identification of early, specific, and minimally invasive biomarkers is required. In this study, some plasma biomarkers (Amyloid β42, p-Tau181, t-Tau, neurofilament light (NfL), TAR DNA-binding protein 43 (TDP-43)) were determined by single molecule array technology (SIMOA^®) in control subjects (n = 22), mild cognitive impairment due to AD (MCI-AD, n = 33), mild dementia due to AD (n = 12), and FTLD (n = 11) patients. The correlations between plasma and cerebrospinal fluid (CSF) levels and the accuracy of plasma biomarkers for AD early diagnosis and discriminating from FTLD were analyzed. As result, plasma p-Tau181 and NfL levels correlated with the corresponding CSF levels. Additionally, plasma p-Tau181 showed good accuracy for distinguishing between the controls and AD, as well as discriminating between AD and FTLD. Moreover, plasma NfL could discriminate dementia-AD vs. controls, FTLD vs. controls, and MCI-AD vs. dementia-AD. Therefore, the determination of these biomarkers in plasma is potentially helpful in AD spectrum diagnosis, but also discriminating from FTLD. In addition, the accessibility of these potential early and specific biomarkers may be useful for AD screening protocols in the future.

Background: The VALCODIS (Valencian Cognitive Diseases Study) cohort was designed and studied at the Hospital Universitari i Politècnic La Fe (Valencia, Spain) for the research of cognitive diseases, especially in the search for new biomarkers of Alzheimer’s disease (AD). Methods: Participants in the VALCODIS cohort had cerebrospinal fluid (CSF) and blood samples, neuroimaging, and neuropsychological tests. The ApoE genotype was evaluated to identify its relationship with CSF biomarkers and neuropsychological tests in AD and non-AD participants. Results: A total of 1249 participants were included. They were mainly AD patients (n = 547) but also patients with other dementias (frontotemporal lobar dementia (n = 61), Lewy body dementia without AD CSF signature (n = 10), vascular dementia (n = 24) and other specific causes of cognitive impairment (n = 442), and patients with subjective memory complaints (n = 165)). In the ApoE genotype evaluation, significant differences were found for Aβ42 levels between genotypes in both AD and non-AD patients, as well as a negative correlation between tau values and a cognitive test in non-carriers and ε4 heterozygous. Conclusions: The VALCODIS cohort provides biologically diagnosed patients with demographical, clinical and biochemical data, and biological samples for further studies on early AD diagnosis. Also, the ApoE genotype evaluation showed correlations between CSF biomarkers and neuropsychological tests.

Alzheimer’s disease (AD) is the most prevalent dementia, but it shows similar initial symptoms to other neurocognitive diseases (Lewy body disease (LBD) and frontotemporal dementia (FTD)). Thus, the identification of reliable AD plasma biomarkers is required. The aim of this work is to evaluate the use of a few plasma biomarkers to develop an early and specific AD screening method. Plasma p-Tau181, neurofilament light (NfL), and glial fibrillary acid protein (GFAP) were determined by Single Molecule Assay (SIMOA^® Quanterix, Billerica, MA, USA) in patients with mild cognitive impairment due to AD (MCI-AD, n = 50), AD dementia (n = 10), FTD (n = 20), LBD (n = 5), and subjective cognitive impairment (SCI (n = 21)). Plasma p-Tau181 and GFAP showed the highest levels in AD dementia, and significant correlations with clinical AD characteristics; meanwhile, NfL showed the highest levels in FTD, but no significant correlations with AD. The partial least squares (PLS) diagnosis model developed between the AD and SCI groups showed good accuracy with a receiver operating characteristic (ROC) area under curve (AUC) of 0.935 (CI 95% 0.87–0.98), sensitivity of 86%, and specificity of 88%. In a first screen, NfL plasma levels could identify FTD patients among subjects with cognitive impairment. Then, the developed PLS model including p-Tau181 and GFAP levels could identify AD patients, constituting a simple, early, and specific diagnosis approach.

Background: Alzheimer’s disease (AD) is the leading cause of dementia in the elderly population. Currently, diagnosis is based on invasive and expensive techniques, so there is a growing need to look for other possible tests, as well as carry out clinical validation. Studies from the literature showed potential diagnosis models, including some AD risk factors (age, gender, ApoE-ε4 genotype) and other variables (biomarkers levels, neuroimaging). Specifically, a recent model was performed from lipid peroxidation compounds in plasma samples to identify patients with early AD. However, there is a lack of studies about clinical validation of these preliminary diagnosis models. Methods: Plasma samples from participants classified into AD (n = 61), non-AD (n = 17), and healthy (n = 44) were analyzed. In fact, lipid peroxidation compounds were determined by liquid chromatography and mass spectrometry. Then, a previously developed diagnosis model was clinically validated, evaluating some diagnosis indexes. Results: The validation of the preliminary diagnosis model showed satisfactory diagnosis indexes (accuracy 77%, sensitivity 89%, specificity 61%, diagnostic odds ratio 12.5, positive predictive value 76%). Next, a useful screening tool, including the ApoE genotype, was developed, identifying patients with a higher risk of developing AD and improving the corresponding diagnosis indexes (accuracy 82%, sensitivity 81%, specificity 85%, diagnostic odds ratio 23.2, positive predictive value 90.5%). Conclusion: A new screening approach could improve the early, minimally invasive, and differential AD diagnosis in the general population.

Background: Nowadays, there is a lack of reliable and minimally invasive diagnosis methods for the early detection of Alzheimer’s disease. The development and validation of such tools could significantly reduce the dependence on more invasive and costly confirmatory procedures, such as cerebrospinal fluid biomarkers analysis and neuroimaging techniques. Objectives: The main objective of this study is to validate the clinical performance of a previously developed diagnosis model based on plasma biomarkers from patients in a cognitive disorder unit. Methods: A new cohort of patients was recruited from the same cognitive disorder unit (n = 93). Specifically, demographic data (gender, age, and educational level), plasma biomarkers levels, and genotype (glial fibrillary acidic protein, phosphorylated Tau 181, amyloid-beta42/amyloid-beta40, apolipoprotein E) were collected to evaluate both approaches of the previous diagnosis model (one-cut-off, two-cut-off). Results: The one-cut-off approach showed a sensitivity of 74.3%, a specificity of 89.5%, and an area under the curve of 0.888, while the values for the two-cut-off approach were sensitivity of 66.7%, specificity of 99.9%, and area under the curve of 0.867. Conclusions: A multivariate diagnostic tool was temporally validated for implementation in a clinical unit. In fact, satisfactory results were obtained from both approaches (one-cut-off, two-cut-offs), but the two cut-offs approach was more consistent in correctly identifying non-Alzheimer’s disease cases, allowing us to identify a large number of cases with high specificity.