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Background: Neuropsychological assessments are essential to define the cognitive profile and contribute to the diagnosis of Alzheimer’s disease (AD). The progress in knowledge about the pathophysiological process of the disease has allowed conceptualizing AD through biomarkers as a biological continuum that encompasses different clinical stages. Objective: To explore the association between cerebrospinal fluid (CSF) biomarkers of AD and cognition using the NEURONORMA battery, in a sample of cognitively unimpaired (CU), mild cognitive impaired (MCI), and mild dementia of the Alzheimer type (DAT) subjects, and to characterize the cognitive profiles in MCI subjects classified by A/T/N system. Methods: 42 CU, 35 MCI, and 35 mild DAT were assessed using the NEURONORMA battery. Core AD biomarkers [amyloid-β42 (Aβ42) peptide, total tau (t-tau), and phosphorylated tau 181 (p-tau181)] proteins were measured in CSF. Correlation coefficients, multivariate regression, and effect sizes were calculated. We explored the age- and education-adjusted cognitive profiles by A/T/N variants within the MCI group. Results: Cognitive outcomes were directly associated with CSF Aβ42 and inversely with CSF tau measures. We found differences in both biomarkers and cognitive outcomes comparing all pairs except for CSF measures between cognitively impaired groups. The highest effect size was in memory tasks and biomarkers ratios. Lower performances were in memory and executive domains in MCI subjects with AD pathology (A+T+N±) compared to those with normal levels of AD biomarkers (A– T– N). Conclusion: This study provides further evidence of the validity of Spanish NEURONORMA cognitive battery to characterize cognitive impairment in the AD pathological continuum.

MRI atrophy predicts cognitive status in AD. However, this relationship has not been investigated in early-onset AD (EOAD

Sex is believed to drive heterogeneity in Alzheimer's disease (AD), although evidence in early-onset AD (EOAD;lt;65 years) is scarce.We included 62 EOAD patients and 44 healthy controls (HCs) with core AD cerebrospinal fluid (CSF) biomarkers, neurofilament light chain levels, neuropsychological assessment, and 3-T magnetic resonance imaging. We measured cortical thickness (CTh) and hippocampal subfield volumes (HpS) using FreeSurfer. Adjusted linear models were used to analyze sex-differences and the relationship between atrophy and cognition.Compared to same-sex HCs, female EOAD subjects showed greater cognitive impairment and broader atrophy burden than male EOAD subjects. In a direct female-EOAD versus male-EOAD comparison, there were slight differences in temporal CTh, with no differences in cognition or HpS. CSF tau levels were higher in female EOAD than in male EOAD subjects. Greater atrophy was associated with worse cognition in female EOAD subjects.At diagnosis, there are sex differences in the pattern of cognitive impairment, atrophy burden, and CSF tau in EOAD, suggesting there is an influence of sex on pathology spreading and susceptibility to the disease in EOAD.

Background and ObjectivesBlood-based biomarkers have emerged as minimally invasive options for evaluating cognitive impairment. Most studies to date have assessed them in research cohorts, limiting their generalization to everyday clinical practice. We evaluated their diagnostic performance and clinical applicability in a prospective, real-world, memory clinic cohort.MethodsAll patients referred with suspected cognitive impairment between July 2019 and June 2021 were prospectively invited to participate. Five plasma biomarkers (tau phosphorylated at threonine 181 [p-tau181], glial fibrillary acidic protein [GFAP], neurofilament light chain [NfL], total tau [t-tau], and ubiquitin C-terminal hydrolase L1 [UCH-L1]) were determined with single-molecule array. Performance was assessed in comparison to clinical diagnosis (blinded to plasma results) and amyloid status (CSF/PET). A group of cognitively unimpaired (CU) controls was also included.ResultsThree hundred forty-nine participants (mean age 68, SD 8.3 years) and 36 CU controls (mean age 61.7, SD 8.2 years) were included. In the subcohort with available Alzheimer disease (AD) biomarkers (n = 268), plasma p-tau181 and GFAP had a high diagnostic accuracy to differentiate AD from non-neurodegenerative causes (area under the receiver operating characteristic curve 0.94 and 0.92, respectively), with p-tau181 systematically outperforming GFAP. Plasma p-tau181 levels predicted amyloid status (85% sensitivity and specificity) with accurate individual prediction in approximately 60% of the patients. Plasma NfL differentiated frontotemporal dementia (FTD) syndromes from CU (0.90) and non-neurodegenerative causes (0.93), whereas the discriminative capacity with AD and between all neurodegenerative and non-neurodegenerative causes was less accurate. A combination of p-tau181 and NfL identified FTD with 82% sensitivity and 85% specificity and had a negative predictive value for neurodegenerative diagnosis of 86%, ruling out half of the non-neurodegenerative diagnoses. In the subcohort without AD biomarkers, similar results were obtained. T-tau and UCH-L1 did not offer added diagnostic value.DiscussionPlasma p-tau181 predicted amyloid status with high accuracy and could have potentially avoided CSF/amyloid PET testing in approximately 60% of subjects in a memory clinic setting. NfL was useful for identifying FTD from non-neurodegenerative causes but behaved worse than p-tau181 in all other comparisons. Combining p-tau181 and NfL improved diagnostic performance for FTD and non-neurodegenerative diagnoses. However, the 14% false-negative results suggest that further improvement is needed before implementation outside memory clinics.Classification of EvidenceThis study provides Class I evidence that plasma p-tau181 correlates with the presence or absence of AD and a combination of plasma p-tau181 and NfL correlates moderately well with a diagnosis of FTD.

MRI atrophy predicts cognitive status in AD. However, this relationship has not been investigated in early-onset AD (EOAD, 65 years) patients with a biomarker-based diagnosis.Forty eight EOAD (MMSE ≥ 15; A + T + N +) and forty two age-matched healthy controls (HC; A - T - N -) from a prospective cohort underwent full neuropsychological assessment, 3T-MRI scan and lumbar puncture at baseline. Participants repeated the cognitive assessment annually. We used linear mixed models to investigate whether baseline cortical thickness (CTh) or subcortical volume predicts two-year cognitive outcomes in the EOAD group.In EOAD, hemispheric CTh and ventricular volume at baseline were associated with global cognition, language and attentional/executive functioning 2 years later (p 0.0028). Regional CTh was related to most cognitive outcomes (p 0.0028), except verbal/visual memory subtests. Amygdalar volume was associated with letter fluency test (p 0.0028). Hippocampal volume did not show significant associations.Baseline hemispheric/regional CTh, ventricular and amygdalar volume, but not the hippocampus, predict two-year cognitive outcomes in EOAD.

Large datasets of longitudinal data, made available for the neuroimage community, offer the possibility to study trajectories of biomarkers throughout the course of the diseases. For such modelling, approaches emerging from both the frequentist and the Bayesian frameworks have been suggested. When datasets are large, homogeneous, and balanced, both approaches seem to perform similarly. However, in compromised datasets, with limited number of samples and unbalanced data, this is not clear. Here we included data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to study the behaviour of different statistical approaches using different dataset configurations. We used the hippocampal volume (HV) at different timepoints and we analysed the capability of the methods to find differences across clinical groups. For that, we used a Linear Mixed Effects (LME) modelling under both the frequentist and the Bayesian approaches. We started with a large, homogeneous, and symmetric database, and we created different configurations, by sequentially removing data points, to simulate different real-life situations. Using the frequentist approach to predict conversion on mild cognitively impaired patients, we found that we need a mean of 115 subjects to differentiate converters vs non converters. When classifying between the five ADNI clinical groups we need 147 subjects (mean across datasets) to differentiate between all clinical groups. With the Bayesian approach, we demonstrated that the results were stronger and of higher interpretability, specially at the borderline significant datasets.

Highlights • Posterior cortices, hippocampus and amygdala track atrophy in EOAD over two years. • The medial temporal cortex is unaltered in EOAD at early stages. • EOAD exhibited a posterior-to-anterior gradient of cortical loss after two years. • EOAD subcortical volume loss extends beyond hippocampus and amygdala after two years. • Cerebrospinal fluid biomarkers might predict atrophy rates in EOAD., There is evidence longitudinal atrophy in posterior brain areas in early-onset Alzheimer’s disease (EOAD; aged

La investigación se plantea como un aporte para el proceso de reformulación del Proyecto Educativo Institucional iniciado el año 2009 por el Liceo Luís Cruz Martínez de la ciudad de Calama. Contribuye con el levantamiento de un perfil identitario del alumnado con el propósito de atender los requerimientos contextuales y subjetivos de la dinámica escolar. El perfil identitario nace a partir de la identificación de rasgos y particularidades juveniles de los alumnos del citado Liceo, en complemento con algunas de las variables de interés en temática juvenil propuestas por la Política de Convivencia e Inclusión Escolar.