Cerebrospinal Fluid 7-Ketocholesterol Level is Associated with Amyloid-β42 and White Matter Microstructure in Cognitively Healthy Adults

Background:Abnormal cholesterol metabolism changes the neuronal membrane and may promote amyloidogenesis. Oxysterols in cerebrospinal fluid (CSF) are related to Alzheimer’s disease (AD) biomarkers in mild cognitive impairment and dementia. Cholesterol turnover is important for axonal and white matter (WM) microstructure maintenance. Objective:We aim to demonstrate that the association of oxysterols, AD biomarkers, and WM microstructure occurs early in asymptomatic individuals. Methods:We studied the association of inter-individual variability of CSF 24-hydroxycholesterol (24-OHC), 27-hydroxycholesterol (27-OHC), 7-ketocholesterol (7-KC), 7β-hydroxycholesterol (7β-OHC), amyloid-β42 (Aβ42), total-tau (t-tau), phosphorylated-tau (p-tau), neurofilament (NfL), and WM microstructure using diffusion tensor imaging, generalized linear models and moderation/mediation analyses in 153 healthy adults. Results:Higher 7-KC levels were related to lower Aβ42, indicative of greater AD pathology (p = 0.041) . Higher 7-KC levels were related to lower fractional anisotropy (FA) and higher mean (MD), axial (AxD), and radial (RD) diffusivity. 7-KC modulated the association between AxD and NfL in the corpus callosum splenium (B = 39.39, p = 0.017), genu (B = 68.64, p = 0.000), and fornix (B = 10.97, p = 0.000). Lower Aβ42 levels were associated to lower FA and higher MD, AxD, and RD in the fornix, corpus callosum, inferior longitudinal fasciculus, and hippocampus. The association between AxD and Aβ42 was moderated by 7K-C (p = 0.048). Conclusion:This study adds clinical evidence to support the role of 7K-C on axonal integrity and the involvement of cholesterol metabolism in the Aβ42 generation process

Amyloid-β, Tau, and Cognition in Cognitively Normal Older Individuals: Examining the Necessity to Adjust for Biomarker Status in Normative Data

We investigated whether amyloid-β (Aβ) and tau affected cognition in cognitively normal (CN) individuals, and whether norms for neuropsychological tests based on biomarker-negative individuals would improve early detection of dementia. We included 907 CN individuals from 8 European cohorts and from the Alzheimer's disease Neuroimaging Initiative. All individuals were aged above 40, had Aβ status and neuropsychological data available. Linear mixed models were used to assess the associations of Aβ and tau with five neuropsychological tests assessing memory (immediate and delayed recall of Auditory Verbal Learning Test, AVLT), verbal fluency (Verbal Fluency Test, VFT), attention and executive functioning (Trail Making Test, TMT, part A and B). All test except the VFT were associated with Aβ status and this influence was augmented by age. We found no influence of tau on any of the cognitive tests. For the AVLT Immediate and Delayed recall and the TMT part A and B, we calculated norms in individuals without Aβ pathology (Aβ- norms), which we validated in an independent memory-clinic cohort by comparing their predictive accuracy to published norms. For memory tests, the Aβ- norms rightfully identified an additional group of individuals at risk of dementia. For non-memory test we found no difference. We confirmed the relationship between Aβ and cognition in cognitively normal individuals. The Aβ- norms for memory tests in combination with published norms improve prognostic accuracy of dementia

ALZUMERIC: a decision support system for diagnosis and monitoring of cognitive impairment

ALZUMERIC: Un sistema de apoyo a la decisión para el diagnóstico y la monitorización del deterioro cognitivo. – La Internet de las cosas o de las ciudades inteligentes se está convirtiendo en una realidad. Cada vez más dispositivos están interconectados y, para hacer frente a esta nueva situación, las velocidades de procesamiento de datos se incrementan. Los dispositivos inteligentes, como las tabletas y los teléfonos, son accesibles para una gran parte de la sociedad en los países desarrollados, y las mejoras en las conexiones a Internet para el intercambio de datos hacen posible manejar grandes volúmenes de información en menos tiempo. Esta nueva realidad ha abierto la posibilidad de desarrollar arquitecturas cliente-servidor centradas en el diagnóstico clínico en tiempo real y a un coste muy bajo. Este trabajo ilustra la concepción del sistema ALZUMERIC orientado al diagnóstico de la enfermedad de Alzheimer. Es una plataforma a partir de la cual el médico especialista puede tomar muestras de voz a través de métodos no invasivos a pacientes con y sin deterioro cognitivo leve (MCI), y en la cual se parametriza la señal de entrada automáticamente para posteriormente avanzar una propuesta de diagnóstico. El MCI es un tipo de deterioro neurológico que produce una pérdida cognitiva no lo suficientemente grave como para interferir en la vida cotidiana. El presente estudio está enfocado hacia la descripción de las patologías del habla con respecto a los siguientes perfiles: fonación, articulación, calidad del habla, análisis de la respuesta emocional, percepción del lenguaje y dinámica de sistemas complejos. También se consideran aspectos relativos a la privacidad, la confidencialidad y la seguridad de la información frente a las posibles amenazas que pudiera sufrir el sistema, por lo que este primer prototipo de servicios ofrecidos por ALZUMERIC se ha dirigido a un número predeterminado de médicos especialistas. ----------ABSTRACT---------- Internet of things and smart cities are becoming a reality. Nowadays, more and more devices are interconnected and in order to deal with this new situation, data processing speeds are increasing to keep the pace. Smart devices like tablets and smartphones are accessible to a wide part of society in developed countries, and Internet connections for data exchange make it possible to handle large volumes of information in less time. This new reality has opened up the possibility of developing client-server architectures focused on clinical diagnosis in real time and at a very low cost. This paper illustrates the design and implementation of the ALZUMERIC system that is oriented to the diagnosis of Alzheimer’s disease (AD). It is a platform where the medical specialist can gather voice samples through non-invasive methods from patients with and without mild cognitive impairment (MCI), and the system automatically parameterizes the input signal to make a diagnose proposal. Although this type of impairment produces a cognitive loss, it is not severe enough to interfere with daily life. The present approach is based on the description of speech pathologies with regard to the following profiles: phonation, articulation, speech quality, analysis of the emotional response, language perception, and complex dynamics of the system. Privacy, confidentiality and information security have also been taken into consideration, as well as possible threats that the system could suffer, so this first prototype of services offered by ALZUMERIC has been targeted to a predetermined number of medical specialists

Data from: Increased CAIDE dementia risk, cognition, CSF biomarkers and vascular burden in healthy adults

Objective: To investigate the cognitive profile of healthy individuals with increased CAIDE dementia risk score, and to explore whether this association is related to vascular burden and CSF biomarkers of amyloidosis and neurodegeneration. Method: Cognitively normal participants (mean age = 57.6 years) from the Gipuzkoa Alzheimer Project study were classified as having high risk (HR, n = 82) or low risk (LR, n = 293) for dementia according to a CAIDE score cut off of 9. Cognitive composites were compared between groups. We explored the role of APOE genotype, MRI white matter hyperintensities (WMH) and CSF (n = 218) levels of amyloid-β1-42 (Aβ1-42), total tau (t-tau) and phosphorylated tau (p-tau) in the association between CAIDE and cognition conducting generalized linear models. Results: HR participants obtained lower scores on executive function (EF) (p = .001) and visual perception and construction (VPC) (p < .001) composites. EFc was associated with CAIDEp-tau (p = .001), CAIDEt-tau (p = .001) and WMH (p = .003). VPCc was associated with APOE (p = .001), Aβ1-42 (p = .004), the interaction APOEAβ1-42 (p = .003), and WMH (p = .004). Performance on global memory was associated with Aβ1-42 (p = .006), APOE (p = .008), and their interaction (p = .006). Analyses were adjusted for age, education, sex, premorbid intelligence and stress. Conclusion: Healthy participants at increased dementia risk, based on CAIDE scores, show lower performance in executive function and visual perception and construction. This difference is related to APOE, WMH and Alzheimer’s biomarkers

Supplementary tables Ecay-Torres

These supplemetary tables contain the results of the intermediate generalized linear models needed to select the variables of the finals models shown in the manuscript

e-References_Clinical and neuropsychological tests

The appendix includes the clinical and neuropsychological references list used in the GAP project

Alzheimer disease diagnosis based on automatic spontaneous speech analysis

Alzheimer's disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to im-provement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.Peer ReviewedPostprint (published version

Alzheimer disease diagnosis based on automatic spontaneous speech analysis

Alzheimer's disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to im-provement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.Peer Reviewe

Plasma lipids are associated with white matter microstructural changes and axonal degeneration

Dislipidemia is a risk factor for cognitive impairment. We studied the association between interindividual variability of plasma lipids and white matter (WM) microstructure, using diffusion tensor imaging (DTI) in 273 healthy adults. Special focus was placed on 7 regions of interest (ROI) which are structural components of cognitive neurocircuitry. We also investigated the effect of plasma lipids on cerebrospinal fluid (CSF) neurofilament light chain (NfL), an axonal degeneration marker. Low density lipoprotein (LDL) and triglyceride (TG) levels showed a negative association with axial diffusivity (AxD) in multiple regions. High density lipoproteins (HDL) showed a positive correlation. The association was independent of Apolipoprotein E (APOE) genotype, blood pressure or use of statins. LDL moderated the relation between NfL and AxD in the body of the corpus callosum (p = 0.041), right cingulum gyrus (p = 0.041), right fornix/stria terminalis (p = 0.025) and right superior longitudinal fasciculus (p = 0.020) and TG in the right inferior longitudinal fasciculus (p = 0.004) and left fornix/stria terminalis (p = 0.001). We conclude that plasma lipids are associated to WM microstructural changes and axonal degeneration and might represent a risk factor in the transition from healthy aging to disease.This work was supported by the Department of Economic Promotion, Rural Areas and Territorial Balance of the Provincial Government of Gipuzkoa (124/16); the Department of Health of the Basque Government (2016111096); and by the Carlos III Institute of Health (PI15/00919, PN de I + D + I 2013–2016). Predoctoral fellowship grant (Programa Predoctoral, de Formación de Personal Investigador no doctor, RBFI-2015-1-0231) was received from the Basque Government (AIJ). It was undertaken at CITA Alzheimer Foundation, Centre for Research and Advanced Therapies for Alzheimer’s disease (http://www.cita-alzheimer.org/english.asp), which is supported by the Ministry of Economy and Competitiveness of Spain, the Basque Country Government, Kutxa-Fundazioa and anonymous private sponsors.Peer reviewe

Functional brain network centrality is related to APOE genotype in cognitively normal elderly

Introduction: Amyloid plaque deposition in the brain is an early pathological change in Alzheimer's disease (AD), causing disrupted synaptic connections. Brain network disruptions in AD have been demonstrated with eigenvector centrality (EC), a measure that identifies central regions within networks. Carrying an apolipoprotein (APOE)-ε4 allele is a genetic risk for AD, associated with increased amyloid deposition. We studied whether APOE-ε4 carriership is associated with EC disruptions in cognitively normal individuals. Methods: A total of 261 healthy middle-aged to older adults (mean age 56.6 years) were divided into high-risk (APOE-ε4 carriers) and low-risk (noncarriers) groups. EC was computed from resting-state functional MRI data. Clusters of between-group differences were assessed with a permutation-based method. Correlations between cluster mean EC with brain volume, CSF biomarkers, and psychological test scores were assessed. Results: Decreased EC in the visual cortex was associated with APOE-ε4 carriership, a genetic risk factor for AD. EC differences were correlated with age, CSF amyloid levels, and scores on the trail-making and 15-object recognition tests. Conclusion: Our findings suggest that the APOE-ε4 genotype affects brain connectivity in regions previously found to be abnormal in AD as a sign of very early disease-related pathology. These differences were too subtle in healthy elderly to use EC for single-subject prediction of APOE genotype