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Background: Over the last decade, teleneuropsychology has increased substantially. There is a need for valid neuropsychological batteries to be administered home-to-home. Since 2006, the neuropsychological battery of Fundació ACE (NBACE) has been administered face-to-face in our clinical settings. Recently, we adapted the NBACE for teleneuropsychology use to be administered home-to-home (NBACEtn). Objective: The aims of the present study are: 1) to determine the home-to-home NBACE equivalence compared to its original face-to-face version; and 2) to examine home-to-home NBACE discriminant capacity by differentiating among cognitively healthy, mild cognitive impairment, or mild dementia subjects and comparing it with the face-to-face version. Methods: Data from 338 individuals assessed home-to-home (NBACEtn) were contrasted with 7,990 participants assessed with its face-to-face version (NBACE). Exploratory and confirmatory factorial structure, and invariance analysis of the two versions of the battery were performed. Results: Exploratory and confirmatory factor analysis supported the four-factor model (attention, memory, executive, and visuospatial/constructional functions). Configural, metric, and scalar measurement invariance was found between home-to-home and face-to-face NBACE versions. Significant differences in most of the neuropsychological variables assessed were observed between the three clinical groups in both versions of administration. No differences were found between the technological devices used by participants (computer or tablet and mobile devices). Conclusion: For the first time, invariance analysis findings were addressed by determining a teleneuropsychological battery’s equivalence in comparison with its face-to-face version. This study amplifies the neuropsychological assessment’s applicability using a home-to-home format, maintaining the original measure’s structure, interpretability, and discriminant capacity.

International audience; Introduction: Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an important role.Methods: Well-defined participants groups were recruited. Lipid peroxidation compounds were determined in plasma using a validated analytical method. Statistical studies consisted of an elastic-net-penalized logistic regression adjustment.Results: The regression model fitted to the data included six variables (lipid peroxidation biomarkers) as potential predictors of early AD. This model achieved an apparent area under the receiver operating characteristics (AUC-ROCs) of 0.883 and a bootstrap-validated AUC-ROC of 0.817. Calibration of the model showed very low deviations from real probabilities.Conclusion: A satisfactory early diagnostic model has been obtained from plasma levels of 6 lipid peroxidation compounds, indicating the individual probability of suffering from early AD.

Alzheimer Disease (AD) is the main cause of dementia, and it has a great social and economic impact worldwide. It is a complex multifactorial disease, and we still do not know enough about its causes. For this reason, omics studies could be a useful tool for the search for new biomarkers and for enhancing the knowledge of different metabolic pathways that may be altered in the initial stages of the disease. Metabolomic analysis was carried out for plasma samples from early AD patients and healthy controls. Obtained data were normalized and analyzed by volcano plot and supervised orthogonal-least-squares-discriminant analysis. Fifteen variables were selected as the most important variables for the groups' discrimination, and the different levels of 6 identified metabolites could discriminate between patients with different ApoE4 genotypes (e4-carriers and non e4-carriers). In conclusion, ApoE4 genotype is associated with changes in lipid metabolomics profile in AD patients, and it could be relevant for the development of AD since early stages.

Alzheimer Disease (AD) is a pathology that causes millions of deaths every year and it also generates severe economic consequences for families and public health systems. Oxidative stress is related to neurodegenerative diseases damage. In fact, brain lipid oxidation could produce brain atrophy. The main objective of this study is the evaluation of atrophy and lipid peroxidation damage in AD patients. We studied medial temporal brain atrophy by magnetic resonance imaging (MRI) and a set of lipid peroxidation biomarkers from plasma samples, respectively. The participants were AD patients in early stages (n = 80) and healthy controls (n = 32). Some lipid peroxidation compounds (neuroprostanes, isoprostanes, neurofurans, isofurans, 17-epi-17-F2t-dihomo-IsoP, PGF2α) in plasma showed statistically significant correlation with medial temporal atrophy. So, they were selected to generate an AD diagnosis model, showing an AUC-ROC of 0.900, close to accuracy achieved by the model based on neuroimaging analysis (AUC-ROC 0.929). In addition, the new model showed suitable specificity, so it could be used as screening test. The developed model based on plasma biomarkers could reflect white and grey matter lipid peroxidation, which occurs in medial temporal lobe in early AD patients. Nevertheless, more studies are needed in this field in order to evaluate specificity against other dementias or neurodegenerative diseases.

Alzheimer Disease (AD) standard biological diagnosis is based on expensive or invasive procedures. Recent research has focused on some molecular mechanisms involved since early AD stages, such as lipid peroxidation. Therefore, a non-invasive screening approach based on new lipid peroxidation compounds determination would be very useful. Well-defined early AD patients and healthy participants were recruited. Lipid peroxidation compounds were determined in urine using a validated analytical method based on liquid chromatography coupled to tandem mass spectrometry. Statistical studies consisted of the evaluation of two different linear (Elastic Net) and non-linear (Random Forest) regression models to discriminate between groups of participants. The regression models fitted to the data from some lipid peroxidation biomarkers (isoprostanes, neuroprostanes, prostaglandines, dihomo-isoprostanes) in urine as potential predictors of early AD. These prediction models achieved fair validated area under the receiver operating characteristics (AUC-ROCs > 0.68) and their results corroborated each other since they are based on different analytical principles. A satisfactory early screening approach, using two complementary regression models, has been obtained from urine levels of some lipid peroxidation compounds, indicating the individual probability of suffering from early AD.

An untargeted metabolomics study has been carried out using plasma samples from patients with Mild Cognitive Impairment due to Alzheimer's disease patients (MCI-AD, n = 29) and healthy people (n = 29)). They have been classified following the National Institute on Aging and Alzheimer's Association (NIA-AA) recommendations and cerebrospinal fluid biomarkers. The analytical method was based on liquid chromatography coupled to high resolution mass spectrometry. The data process from the corresponding metabolic profiles retained 1158 molecular features in positive and 424 in negative ionization mode. Differences between metabolomic profiles from MCI-AD patients and healthy participants were investigated using a penalized logistic regression analysis (ElasticNet), and being able to select automatically the most informative variables (53 molecular features). From the molecular features selected for the elastic net models, 16 variables were preliminarily identified by The Human Metabolome Database (amino acids, lipids…). However, only 4 of these variables were tentatively identified by MS/MS and all ions fragmentation modes, being choline the only confirmed metabolite. Regarding their metabolic pathways, they could be involved in cholinergic system, energy metabolism, amino acids and lipids pathways. To conclude, this is a reliable approach to early AD mechanisms, and choline has been identified as a promising AD diagnosis metabolite. Significance The untargeted analysis carried out in human plasma samples from early Alzheimer's disease patients and healthy individuals, and the use of sophisticated statistical tools, identified some metabolic pathways and plasma biomarkers. Preliminarily, cholinergic system, energy metabolism, and aminoacids and lipids pathways may be involved in early Alzheimer's disease development.

We aimed to identify new cell-membrane antigens implicated in opsoclonus-myoclonus with neuroblastoma. The sera of 3 out of 14 patients showed IgG electron-microscopy immunogold reactivity on SH-SY5Y neuroblastoma cells. Immunoprecipitation experiments using rat brain synaptosomes and SH-SY5Y cells led to the identification of: (1) thirty-one nuclear/cytoplasmic proteins (including antigens HuB, HuC); (2) seven neuronal membrane proteins, including the Shaw-potassium channel Kv3.3 (KCNC3), whose genetic disruption in mice causes ataxia and generalized muscle twitching. Although cell-based assays did not demonstrate direct antigenicity, our findings point to Shaw-related subfamily of the potassium voltage-gated channels complexed proteins as hypothetical antigenic targets.