Correlations between soluble alpha/beta forms of amyloid precursor protein and Abeta38, 40 and 42 in human cerebrospinal fluid

International audienceCerebrospinal fluid (CSF) biomarkers are now widely used for diagnosis of Alzheimer disease (AD) in atypical clinical forms, for differential and early diagnosis, or for stratification of patients in clinical trials. Among these biomarkers, different forms of amyloid peptides (Aβ) produced by the cleavage of a transmembrane precursor protein called APP (amyloid precursor protein) have a major role. Aβ peptides exist in different length the most common ones having 40 (Aβ40), 42 (Aβ42), or 38 (Aβ38) amino acids in length. APP processing by gamma-secretase releases also an amino-terminal secreted fragment called sAβPP-beta while an alternative nonamyloidogenic cleavage of APP, through an alpha-secretase, liberates another fragment called sAβPP-alpha. To decipher the molecular and pathological mechanisms leading to the production and the detection of these entities is essential for the comprehension and the prevention of AD. In this report, we present the results of the Keywords: Biomarkers CSF Soluble amyloid precursor proteins Aβ fragment peptides Alzheimer disease Dementi

Measures of Resting State EEG Rhythms for Clinical Trials in Alzheimer’s Disease:Recommendations of an Expert Panel

The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12Hz) and widespread delta (<4Hz) and theta (4-8Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes

Alzheimer's Disease: Advances in Drug Development.

International audienceAs of 2018, Alzheimer's disease (AD) is the most common form of neurodegenerative dementia. It contributes to a progressive neuron loss, deterioration of memory, and cognitive impairment. Current therapies may provide a symptomatic benefit, but do not treat the underlying process. Ongoing researches focus on understanding the causal mechanisms and finding neuropathological hallmarks of AD. Therapeutic approaches targeting senile plaques or neurofibrillary tangles have not yet resulted in a significant cognitive improvement. However, recent data according to the analysis of AD clinical trials (clinicaltrials.gov database) show promising results. This literature review aims at summarizing the recent advances and at highlighting the most promising results of the ongoing researches. It compares the merits of small-molecules, antibodies, cell, and gene-based therapies and emphasizes the need for treatment at earlier stages of the disease

Cognitive Event-Related Potential, an Early Diagnosis Biomarker in Frail Elderly Subjects: The ERP-MAPT-PLUS Ancillary Study

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Excessive Sleepiness and Longer Nighttime in Bed Increase the Risk of Cognitive Decline in Frail Elderly Subjects: The MAPT-Sleep Study

International audienceObjective: To identify self-reported sleep-wake disturbances that increase the risk of cognitive decline over 1-year follow-up in frail participants.Background:Risk factors for cognitive impairment need to be better identified especially at earliest stages of the pathogenesis. Sleep-wake disturbances may be critical factors to consider and were thus being assessed in this at-risk population for cognitive decline.Methods:Frail elderly participants aged >=70 years were selected from a subsample of the Multi-domain Alzheimer Preventive Trial (MAPT) for a sleep assessment (MAPT-sleep study) at 18-month follow-up (M18). Sleep-wake disturbances were evaluated using a clinical interview (duration of daytime and nighttime sleep, time in bed, number of naps, and presence of clinically-defined sleep disorders) and numerous validated questionnaires [Epworth Sleepiness Scale for excessive daytime sleepiness (EDS), Insomnia Severity Scale and Berlin Questionnaire]. Cognitive decline was defined as a difference between the MMSE and cognitive composite scores at M24 and M36 that was ranked in the lowest decile. Multivariate logistic regression models adjusted for several potential confounding factors were performed.Results:Among the 479 frail participants, 63 developed MMSE-cognitive decline and 50 cognitive composite score decrease between M24 and M36. Subjects with EDS had an increased risk of MMSE decline (OR = 2.46; 95% CI [1.28; 4.71],p= 0.007). A longer time spent in bed during night was associated with cognitive composite score decline (OR = 1.32 [1.03; 1.71],p= 0.03). These associations persisted when controlling for potential confounders. Patients with MMSE score decline and EDS had more naps, clinically-defined REM-sleep Behavior Disorder, fatigue and insomnia symptoms, while patients with cognitive composite score decline with longer time in bed had increased 24-h total sleep time duration but with higher wake time after onset.Conclusions:The risk of cognitive decline is higher in frailty subjects with EDS and longer nighttime in bed. Early detection of sleep-wake disturbances might help identifying frail subjects at risk of cognitive decline to further propose sleep health strategies to prevent cognitive impairment. http://www.clinicaltrials.gov NCT00672685; Date of registration May, 2nd 2008

Comparison of ultrasensitive and mass spectrometry quantification of blood-based amyloid biomarkers for Alzheimer’s disease diagnosis in a memory clinic cohort

International audienceBackground: Alzheimer’s disease (AD) is a complex neurodegenerative disorder with β-amyloid pathology as a key underlying process. The relevance of cerebrospinal fluid (CSF) and brain imaging biomarkers is validated in clinical practice for early diagnosis. Yet, their cost and perceived invasiveness are a limitation for large-scale implementation. Based on positive amyloid profiles, blood-based biomarkers should allow to detect people at risk for AD and to monitor patients under therapeutics strategies. Thanks to the recent development of innovative proteomic tools, the sensibility and specificity of blood biomarkers have been considerably improved. However, their diagnosis and prognosis relevance for daily clinical practice is still incomplete.Methods: The Plasmaboost study included 184 participants from the Montpellier’s hospital NeuroCognition Biobank with AD ( n = 73), mild cognitive impairments (MCI) ( n = 32), subjective cognitive impairments (SCI) ( n = 12), other neurodegenerative diseases (NDD) ( n = 31), and other neurological disorders (OND) ( n = 36). Dosage of β-amyloid biomarkers was performed on plasma samples using immunoprecipitation-mass spectrometry (IPMS) developed by Shimadzu (IPMS-Shim Aβ 42 , Aβ 40 , APP 669–711 ) and Simoa Human Neurology 3-PLEX A assay (Aβ 42 , Aβ 40 , t-tau). Links between those biomarkers and demographical and clinical data and CSF AD biomarkers were investigated. Performances of the two technologies to discriminate clinically or biologically based (using the AT(N) framework) diagnosis of AD were compared using receiver operating characteristic (ROC) analyses.Results: The amyloid IPMS-Shim composite biomarker (combining APP 669–711 /Aβ 42 and Aβ 40 /Aβ 42 ratios) discriminated AD from SCI (AUC: 0.91), OND (0.89), and NDD (0.81). The IPMS-Shim Aβ 42/40 ratio also discriminated AD from MCI (0.78). IPMS-Shim biomarkers have similar relevance to discriminate between amyloid-positive and amyloid-negative individuals (0.73 and 0.76 respectively) and A−T−N−/A+T+N+ profiles (0.83 and 0.85). Performances of the Simoa 3-PLEX Aβ 42/40 ratio were more modest. Pilot longitudinal analysis on the progression of plasma biomarkers indicates that IPMS-Shim can detect the decrease in plasma Aβ 42 that is specific to AD patients.Conclusions: Our study confirms the potential usefulness of amyloid plasma biomarkers, especially the IPMS-Shim technology, as a screening tool for early AD patients

Absence of Relationship Between Self-Reported Sleep Measures and Amyloid Load in Elderly Subjects

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Excessive Sleepiness and Longer Nighttime in Bed Increase the Risk of Cognitive Decline in Frail Elderly Subjects: The MAPT-Sleep Study

Objective: To identify self-reported sleep-wake disturbances that increase the risk of cognitive decline over 1-year follow-up in frail participants.Background: Risk factors for cognitive impairment need to be better identified especially at earliest stages of the pathogenesis. Sleep-wake disturbances may be critical factors to consider and were thus being assessed in this at-risk population for cognitive decline.Methods: Frail elderly participants aged ≥70 years were selected from a subsample of the Multi-domain Alzheimer Preventive Trial (MAPT) for a sleep assessment (MAPT-sleep study) at 18-month follow-up (M18). Sleep-wake disturbances were evaluated using a clinical interview (duration of daytime and nighttime sleep, time in bed, number of naps, and presence of clinically-defined sleep disorders) and numerous validated questionnaires [Epworth Sleepiness Scale for excessive daytime sleepiness (EDS), Insomnia Severity Scale and Berlin Questionnaire]. Cognitive decline was defined as a difference between the MMSE and cognitive composite scores at M24 and M36 that was ranked in the lowest decile. Multivariate logistic regression models adjusted for several potential confounding factors were performed.Results: Among the 479 frail participants, 63 developed MMSE-cognitive decline and 50 cognitive composite score decrease between M24 and M36. Subjects with EDS had an increased risk of MMSE decline (OR = 2.46; 95% CI [1.28; 4.71], p = 0.007). A longer time spent in bed during night was associated with cognitive composite score decline (OR = 1.32 [1.03; 1.71], p = 0.03). These associations persisted when controlling for potential confounders. Patients with MMSE score decline and EDS had more naps, clinically-defined REM-sleep Behavior Disorder, fatigue and insomnia symptoms, while patients with cognitive composite score decline with longer time in bed had increased 24-h total sleep time duration but with higher wake time after onset.Conclusions: The risk of cognitive decline is higher in frailty subjects with EDS and longer nighttime in bed. Early detection of sleep-wake disturbances might help identifying frail subjects at risk of cognitive decline to further propose sleep health strategies to prevent cognitive impairment.http://www.clinicaltrials.gov NCT00672685; Date of registration May, 2nd 2008

Cerebrospinal Fluid and Plasma Biomarkers do not Differ in the Presenile and Late-Onset Behavioral Variants of Frontotemporal Dementia

International audienceMemory troubles and hippocampal atrophy are considered more frequent and focal atrophy less severe in late-onset (>65 years) than in presenile behavioral variant of frontotemporal dementia (bvFTD)

Validity and Performance of Blood Biomarkers for Alzheimer Disease to Predict Dementia Risk in a Large Clinic-Based Cohort.

International audienceBACKGROUND: Blood biomarkers for Alzheimer's disease (AD) have consistently proven to be associated with CSF or PET biomarkers and effectively discriminate AD from other neurodegenerative diseases. Our aim was to test their utility in clinical practice, from a multicentric unselected prospective cohort where patients presented with a large spectrum of cognitive deficits or complaints. METHODS: The MEMENTO cohort enrolled 2323 outpatients with subjective cognitive complaint (SCC) or mild cognitive impairment (MCI) consulting in 26 French memory clinics. Participants had neuropsychological assessments, MRI and blood sampling at baseline. CSF sampling and amyloid PET were optional. Baseline blood Aβ42/40 ratio, total-tau, p181-tau, and neurofilament light chain (NfL) were measured using a Simoa HD-X analyzer. An expert committee validated incident dementia cases during a 5-year follow-up period. RESULTS: Overall, 2277 individuals had at least one baseline blood biomarker available (n=357 for CSF subsample, n=649 for PET subsample), among whom 257 were diagnosed with clinical AD/mixed dementia during follow-up. All blood biomarkers but total-tau were mildly correlated with their equivalence in the CSF (r=0.33 to 0.46, p<0.0001) and were associated with amyloid-PET status (p<0.0001). Blood p181-tau was the best blood biomarker to identify amyloid-PET positivity (AUC=0.74 [95%CI=0.69-0.79]). Higher blood and CSF p181-tau and NfL concentrations were associated with accelerated time to AD dementia onset with similar incidence rates, whereas blood Aβ42/40 was less efficient than CSF Aβ42/40. Blood p181-tau alone was the best blood predictor of 5-year AD/mixed dementia risk (c-index=0.73 [95%CI=0.69-0.77]); its accuracy was higher in patients with CDR=0 (c-index=0.83 [95% CI=0.69;0.97]) than in patients with CDR=0.5 (c-index=0.70 [95% CI=0.66;0.74]). A "clinical" reference model (combining demographics and neuropsychological assessment) predicted AD/mixed dementia risk with a c-index=0.88 [95%CI=0.86-0.91] and performance increased to 0.90 [95%CI=0.88;0.92] when adding blood p181-tau+Aβ42/40. A "research" reference model (clinical model+ApoE genotype and AD-signature on MRI) had a c-index=0.91 [95%CI=0.89-0.93] increasing to 0.92 [95%CI=0.90;0.93] when adding blood p181-tau+Aβ42/40. Chronic kidney disease and vascular comorbidities did not impact predictive performances. DISCUSSION: In a clinic-based cohort of patients with SCC or MCI, blood biomarkers may be good hallmarks of underlying pathology but add little to 5-year dementia risk prediction models including traditional predictors