Validation study of "Santé-Cerveau", a digital tool for early cognitive changes identification.

BACKGROUND: There is a need for a reliable, easy-to-use, widely available, and validated tool for timely cognitive impairment identification. We created a computerized cognitive screening tool (Santé-Cerveau digital tool (SCD-T)) including validated questionnaires and the following neuropsychological tests: 5 Word Test (5-WT) for episodic memory, Trail Making Test (TMT) for executive functions, and a number coding test (NCT) adapted from the Digit Symbol Substitution Test for global intellectual efficiency. This study aimed to evaluate the performance of SCD-T to identify cognitive deficit and to determine its usability. METHODS: Three groups were constituted including 65 elderly Controls, 64 patients with neurodegenerative diseases (NDG): 50 AD and 14 non-AD, and 20 post-COVID-19 patients. The minimum MMSE score for inclusion was 20. Association between computerized SCD-T cognitive tests and their standard equivalent was assessed using Pearson's correlation coefficients. Two algorithms (a simple clinician-guided algorithm involving the 5-WT and the NCT; and a machine learning classifier based on 8 scores from the SCD-T tests extracted from a multiple logistic regression model, and data from the SCD-T questionnaires) were evaluated. The acceptability of SCD-T was investigated through a questionnaire and scale. RESULTS: AD and non-AD participants were older (mean ± standard deviation (SD): 72.61 ± 6.79 vs 69.91 ± 4.86 years old, p = 0.011) and had a lower MMSE score (Mean difference estimate ± standard error: 1.74 ± 0.14, p < 0.001) than Controls; post-COVID-19 patients were younger than Controls (mean ± SD: 45.07 ± 11.36 years old, p < 0.001). All the computerized SCD-T cognitive tests were significantly associated with their reference version. In the pooled Controls and NDG group, the correlation coefficient was 0.84 for verbal memory, -0.60 for executive functions, and 0.72 for global intellectual efficiency. The clinician-guided algorithm demonstrated 94.4% ± 3.8% sensitivity and 80.5% ± 8.7% specificity, and the machine learning classifier 96.8% ± 3.9% sensitivity and 90.7% ± 5.8% specificity. The acceptability of SCD-T was good to excellent. CONCLUSIONS: We demonstrate the high accuracy of SCD-T in screening cognitive disorders and its good acceptance even in individuals with prodromal and mild dementia stages. SCD-T would be useful in primary care to faster refer subjects with significant cognitive impairment (and limit unnecessary referrals) to specialized consultation, improve the AD care pathway and the pre-screening in clinical trials.

Theta Band-Power Shapes Amyloid-Driven Longitudinal EEG Changes in Elderly Subjective Memory Complainers At-Risk for Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) includes progressive symptoms spread along a continuum of preclinical and clinical stages. Although numerous studies uncovered the neuro-cognitive changes of AD, very little is known on the natural history of brain lesions and modifications of brain networks in elderly cognitively-healthy memory complainers at risk of AD for carrying pathophysiological biomarkers (amyloidopathy and tauopathy). OBJECTIVE: We analyzed resting-state electroencephalography (EEG) of 318 cognitively-healthy subjective memory complainers from the INSIGHT-preAD cohort at the time of their first visit (M0) and two-years later (M24). METHODS: Using 18F-florbetapir PET-scanner, subjects were stratified between amyloid negative (A-; n = 230) and positive (A+; n = 88) groups. Differences between A+ and A- were estimated at source-level in each band-power of the EEG spectrum. RESULTS: At M0, we found an increase of theta power in the mid-frontal cortex in A+ compared to A-. No significant association was found between mid-frontal theta and the individuals' cognitive performance. At M24, theta power increased in A+ relative to A- individuals in the posterior cingulate cortex and the pre-cuneus. Alpha band revealed a peculiar decremental trend in posterior brain regions in the A+ relative to the A- group only at M24. Theta power increase over the mid-frontal and mid-posterior cortices suggests an hypoactivation of the default-mode network in the A+ individuals and a non-linear longitudinal progression at M24. CONCLUSION: We provide the first source-level longitudinal evidence on the impact of brain amyloidosis on the EEG dynamics of a large-scale, monocentric cohort of elderly individuals at-risk for AD.

Association of APOE-Independent Alzheimer Disease Polygenic Risk Score With Brain Amyloid Deposition in Asymptomatic Older Adults.

BACKGROUND AND OBJECTIVES: Brain amyloid deposition, a major risk factor for Alzheimer's disease (AD), is currently estimated by measuring cerebrospinal fluid or plasma amyloid peptide levels, or by positron-emission tomography imaging. Assessing genetic risks relating to amyloid deposition before any accumulation has occurred would allow for earlier intervention in persons at increased risk for developing AD. Previous work linking amyloid burden and genetic risk relied almost exclusively on APOE, a major AD genetic risk factor. Here, we ask whether a polygenic risk score (PRS) that incorporates an optimized list of common variants linked to AD and excludes APOE is associated with brain amyloid load in cognitively unimpaired elderly adults. METHODS: We included 291 elderly asymptomatic participants from the INveStIGation of AlzHeimer's PredicTors (INSIGHT-preAD) cohort who underwent amyloid imaging, including 83 amyloid-positive (+) participants. We used an Alzheimer's (A) PRS composed of 33 AD risk variants excluding APOE, and selected the 17 variants that showed the strongest association with amyloid positivity to define an optimized (oA) PRS. Participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study [228 participants, 90 amyloid (+)] were tested as a validation cohort. Finally, 2,300 AD patients and 6,994 controls from the European Alzheimer's Disease Initiative (EADI) were evaluated. RESULTS: A-PRS was not significantly associated with amyloid burden in the INSIGHT or ADNI cohorts with or without correction for APOE genotype. However, oA-PRS was significantly associated with amyloid status independently of APOE adjustment (INSIGHT OR: 5.26 [1.71-16.88]; ADNI OR: 3.38 [1.02-11.63]). Interestingly, oA-PRS accurately discriminated amyloid (+) and (-) APOE ε4 carriers (INSIGHT OR: 181.6 [7.53-10,674.6]; ADNI OR: 44.94 [3.03-1,277]). A-PRS and oA-PRS showed a significant association with disease status in the EADI cohort (OR: 1.68 [1.53-1.85] and 2.06 [1.73-2.45] respectively). Genes assigned to oA-PRS variants were enriched in ontologies related to Aß metabolism and deposition. DISCUSSION: PRSs relying on AD genetic risk factors excluding APOE may improve risk prediction for brain amyloid, allowing stratification of cognitively unimpaired individuals at risk of AD independent of their APOE status.

Pilot study of repeated blood-brain barrier disruption in patients with mild Alzheimer's disease with an implantable ultrasound device.

BACKGROUND: Temporary disruption of the blood-brain barrier (BBB) using pulsed ultrasound leads to the clearance of both amyloid and tau from the brain, increased neurogenesis, and mitigation of cognitive decline in pre-clinical models of Alzheimer's disease (AD) while also increasing BBB penetration of therapeutic antibodies. The goal of this pilot clinical trial was to investigate the safety and efficacy of this approach in patients with mild AD using an implantable ultrasound device. METHODS: An implantable, 1-MHz ultrasound device (SonoCloud-1) was implanted under local anesthesia in the skull (extradural) of 10 mild AD patients to target the left supra-marginal gyrus. Over 3.5 months, seven ultrasound sessions in combination with intravenous infusion of microbubbles were performed twice per month to temporarily disrupt the BBB. 18F-florbetapir and 18F-fluorodeoxyglucose positron emission tomography (PET) imaging were performed on a combined PET/MRI scanner at inclusion and at 4 and 8 months after the initiation of sonications to monitor the brain metabolism and amyloid levels along with cognitive evaluations. The evolution of cognitive and neuroimaging features was compared to that of a matched sample of control participants taken from the Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS: A total of 63 BBB opening procedures were performed in nine subjects. The procedure was well-tolerated. A non-significant decrease in amyloid accumulation at 4 months of - 6.6% (SD = 7.2%) on 18F-florbetapir PET imaging in the sonicated gray matter targeted by the ultrasound transducer was observed compared to baseline in six subjects that completed treatments and who had evaluable imaging scans. No differences in the longitudinal change in the glucose metabolism were observed compared to the neighboring or contralateral regions or to the change observed in the same region in ADNI participants. No significant effect on cognition evolution was observed in comparison with the ADNI participants as expected due to the small sample size and duration of the trial. CONCLUSIONS: These results demonstrate the safety of ultrasound-based BBB disruption and the potential of this technology to be used as a therapy for AD patients. Research of this technique in a larger clinical trial with a device designed to sonicate larger volumes of tissue and in combination with disease-modifying drugs may further enhance the effects observed. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03119961.

Accuracy of MRI Classification Algorithms in a Tertiary Memory Center Clinical Routine Cohort.

BACKGROUND: Automated volumetry software (AVS) has recently become widely available to neuroradiologists. MRI volumetry with AVS may support the diagnosis of dementias by identifying regional atrophy. Moreover, automatic classifiers using machine learning techniques have recently emerged as promising approaches to assist diagnosis. However, the performance of both AVS and automatic classifiers have been evaluated mostly in the artificial setting of research datasets. OBJECTIVE: Our aim was to evaluate the performance of two AVS and an automatic classifier in the clinical routine condition of a memory clinic. METHODS: We studied 239 patients with cognitive troubles from a single memory center cohort. Using clinical routine T1-weighted MRI, we evaluated the classification performance of: 1) univariate volumetry using two AVS (volBrain and Neuroreader™); 2) Support Vector Machine (SVM) automatic classifier, using either the AVS volumes (SVM-AVS), or whole gray matter (SVM-WGM); 3) reading by two neuroradiologists. The performance measure was the balanced diagnostic accuracy. The reference standard was consensus diagnosis by three neurologists using clinical, biological (cerebrospinal fluid) and imaging data and following international criteria. RESULTS: Univariate AVS volumetry provided only moderate accuracies (46% to 71% with hippocampal volume). The accuracy improved when using SVM-AVS classifier (52% to 85%), becoming close to that of SVM-WGM (52 to 90%). Visual classification by neuroradiologists ranged between SVM-AVS and SVM-WGM. CONCLUSION: In the routine practice of a memory clinic, the use of volumetric measures provided by AVS yields only moderate accuracy. Automatic classifiers can improve accuracy and could be a useful tool to assist diagnosis.

Multimorbidity Is Associated with Preclinical Alzheimer's Disease Neuroimaging Biomarkers.

BACKGROUND: Identifying comorbidities that influence preclinical Alzheimer's disease (AD) can give some insight into the AD early stages trajectories to allow new treatment venues and to guide public health systems to prevent subsequent dementia. OBJECTIVE: To examine the association of multimorbidity with AD neuroimaging markers in cognitively normal older adults. METHODS: This study had a cross-sectional design. Data regarding 14 comorbidities were obtained for all 318 adults aged 70-85 years, recruited from the community to an ongoing prospective monocentric cohort. They underwent standardized neuropsychological and neuroimaging assessment with automated methods that measured hippocampal volumes, white matter hyperintensity volumes, fluorodeoxyglucose positron emission tomography (FDG-PET) standardized uptake values (SUV) in AD signature regions, and amyloid positron emission tomography (amyloid-PET) SUV ratios. Linear regression was used to assess the association of multimorbidity with AD neuroimaging biomarkers. RESULTS: Multimorbidity is signif icantly associated with lower hippocampal volumes (-0.03 ± 0.01; p = 0.012; R2 = 0.017) and lower FDG-PET SUV (-0.027 ± 0.009; p = 0.005; R2 = 0.022), with no association with amyloid deposition (0.001 ± 0.007; p = 0.884; R2 = 0.0001). Taken individually, obesity and excessive alcohol use are associated with lower FDG-PET values, whereas obstructive sleep apnea and mood disorders are related to lower amyloid-PET SUV ratios. CONCLUSION: Multimorbidity is associated with preclinical AD imaging markers of neurodegeneration, but not with amyloid.

MULTBLAST: A web application for multiple BLAST searches.

UNLABELLED: Basic Local Alignment Search Tool, (BLAST) allows the comparison of a query sequence/s to a database of sequences and identifies those sequences that are similar to the query above a user-defined threshold. We have developed a user friendly web application, MULTBLAST that runs a series of BLAST searches on a user-supplied list of proteins against one or more target protein or nucleotide databases. The application pre-processes the data, launches each individual BLAST search on the University of Nevada, Reno's-TimeLogic DeCypher® system (available from Active Motif, Inc.) and retrieves and combines all the results into a simple, easy to read output file. The output file presents the list of the query proteins, followed by the BLAST results for the matching sequences from each target database in consecutive columns. This format is especially useful for either comparing the results from the different target databases, or analyzing the results while keeping the identification of each target database separate. AVAILABILITY: The application is available at the URLhttp://blastpipe.biochem.unr.edu/