Translational Biomarkers in Aging and Dementia (TRIAD) study, Alzheimer's and Families (ALFA) study, and BioCogBank Paris Lariboisière cohort IMPORTANCE Glial fibrillary acidic protein (GFAP) is a marker of reactive astrogliosis that increases in the cerebrospinal fluid (CSF) and blood of individuals with Alzheimer disease (AD). However, it is not known whether there are differences in blood GFAP levels across the entire AD continuum and whether its performance is similar to that of CSF GFAP.OBJECTIVE To evaluate plasma GFAP levels throughout the entire AD continuum, from preclinical AD to AD dementia, compared with CSF GFAP.

In Alzheimer's disease (AD), tau phosphorylation in the brain and its subsequent release into cerebrospinal fluid (CSF) and blood is a dynamic process that changes during disease evolution. The main aim of our study was to characterize the pattern of changes in phosphorylated tau (p-tau) in the preclinical stage of the Alzheimer's continuum. We measured three novel CSF p-tau biomarkers, phosphorylated at threonine-181 and threonine-217 with an Nterminal partner antibody and at threonine-231 with a mid-region partner antibody. These were compared with an automated midregion p-tau181 assay (Elecsys) as the gold standard p-tau measure. We demonstrate that these novel p-tau biomarkers increase more prominently in preclinical Alzheimer, when only subtle changes of amyloid-b (Ab) pathology are detected, and can accurately differentiate Ab-positive from Ab-negative cognitively unimpaired individuals. Moreover, we show that the novel plasma N-terminal p-tau181 biomarker is mildly but significantly increased in the preclinical stage. Our results support the idea that early changes in neuronal tau metabolism in preclinical Alzheimer, likely in response to Ab exposure, can be detected with these novel p-tau assays.

Introduction: The biological pathways involved in the preclinical stage of the Alzheimer's continuum are not well understood. Methods: We used NeuroToolKit and Elecsys ® immunoassays to measure cerebrospinal fluid (CSF) amyloid-β (Aβ)42, Aβ40, phosphorylated tau (p-tau), total tau (t-tau), neurofilament light (NfL), neurogranin, sTREM2, YKL40, GFAP, IL6, S100, and α-synuclein in cognitively unimpaired participants of the ALFA+ study, many within the Alzheimer's continuum. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Blood biomarkers indicating elevated amyloid-β (Aβ) pathology in preclinical Alzheimer’s disease are needed to facilitate the initial screening process of participants in disease-modifying trials. Previous biofluid data suggest that phosphorylated tau231 (p-tau231) could indicate incipient Aβ pathology, but a comprehensive comparison with other putative blood biomarkers is lacking. In the ALFA+ cohort, all tested plasma biomarkers (p-tau181, p-tau217, p-tau231, GFAP, NfL and Aβ42/40) were significantly changed in preclinical Alzheimer’s disease. However, plasma p-tau231 reached abnormal levels with the lowest Aβ burden. Plasma p-tau231 and p-tau217 had the strongest association with Aβ positron emission tomography (PET) retention in early accumulating regions and associated with longitudinal increases in Aβ PET uptake in individuals without overt Aβ pathology at baseline. In summary, plasma p-tau231 and p-tau217 better capture the earliest cerebral Aβ changes, before overt Aβ plaque pathology is present, and are promising blood biomarkers to enrich a preclinical population for Alzheimer’s disease clinical trials.

BackgroundThe Centiloid scale has been developed to standardize measurements of amyloid PET imaging. Reference cut-off values of this continuous measurement enable the consistent operationalization of decision-making for multicentre research studies and clinical trials. In this study, we aimed at deriving reference Centiloid thresholds that maximize the agreement against core Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarkers in two large independent cohorts.MethodsA total of 516 participants of the ALFA+ Study (N = 205) and ADNI (N = 311) underwent amyloid PET imaging ([18F]flutemetamol and [18F]florbetapir, respectively) and core AD CSF biomarker determination using Elecsys® tests. Tracer uptake was quantified in Centiloid units (CL). Optimal Centiloid cut-offs were sought that maximize the agreement between PET and dichotomous determinations based on CSF levels of Aβ42, tTau, pTau, and their ratios, using pre-established reference cut-off values. To this end, a receiver operating characteristic analysis (ROC) was conducted, and Centiloid cut-offs were calculated as those that maximized the Youden’s J Index or the overall percentage agreement recorded.ResultsAll Centiloid cut-offs fell within the range of 25–35, except for CSF Aβ42 that rendered an optimal cut-off value of 12 CL. As expected, the agreement of tau/Aβ42 ratios was higher than that of CSF Aβ42. Centiloid cut-off robustness was confirmed even when established in an independent cohort and against variations of CSF cut-offs.ConclusionsA cut-off of 12 CL matches previously reported values derived against postmortem measures of AD neuropathology. Together with these previous findings, our results flag two relevant inflection points that would serve as boundary of different stages of amyloid pathology: one around 12 CL that marks the transition from the absence of pathology to subtle pathology and another one around 30 CL indicating the presence of established pathology. The derivation of robust and generalizable cut-offs for core AD biomarkers requires cohorts with adequate representation of intermediate levels.Trial registrationALFA+ Study, NCT02485730ALFA PET Sub-study, NCT02685969Electronic supplementary materialThe online version of this article (10.1186/s13195-019-0478-z) contains supplementary material, which is available to authorized users.

Objective:To develop and evaluate a model for staging cortical amyloid deposition using PET with high generalizability.Methods:3027 subjects (1763 Cognitively Unimpaired (CU), 658 Impaired, 467 Alzheimer’s disease (AD) dementia, 111 non-AD dementia, and 28 with missing diagnosis) from six cohorts (EMIF-AD, ALFA, ABIDE, ADC, OASIS-3, ADNI) who underwent amyloid PET were retrospectively included; 1049 subjects had follow-up scans. Applying dataset-specific cut-offs to global Standard Uptake Value ratio (SUVr) values from 27 regions, single-tracer and pooled multi-tracer regional rankings were constructed from the frequency of abnormality across 400 CU subjects (100 per tracer). The pooled multi-tracer ranking was used to create a staging model consisting of four clusters of regions as it displayed a high and consistent correlation with each single-tracer ranking. Relationships between amyloid stage, clinical variables and longitudinal cognitive decline were investigated.Results:SUVr abnormality was most frequently observed in cingulate, followed by orbitofrontal, precuneal, and insular cortices, then the associative, temporal and occipital regions. Abnormal amyloid levels based on binary global SUVr classification were observed in 1.0%, 5.5%, 17.9%, 90.0%, and 100.0% of stage 0-4 subjects, respectively. Baseline stage predicted decline in MMSE (ADNI: N=867, F=67.37, p<0.001; OASIS: (N=475, F=9.12, p<0.001) and faster progression towards an MMSE≤25 (ADNI: N=787, HRstage1=2.00, HRstage2=3.53, HRstage3=4.55, HRstage4=9.91, p<0.001; OASIS: N=469, HRstage4=4.80, p<0.001).Conclusion:The pooled multi-tracer staging model successfully classified the level of amyloid burden in >3000 subjects across cohorts and radiotracers, and detects pre-global amyloid burden and distinct risk profiles of cognitive decline within globally amyloid-positive subjects.

ImportanceAlzheimer disease (AD) pathology starts with a prolonged phase of β-amyloid (Aβ) accumulation without symptoms. The duration of this phase differs greatly among individuals. While this disease phase has high relevance for clinical trial designs, it is currently unclear how to best predict the onset of clinical progression.ObjectiveTo evaluate combinations of different plasma biomarkers for predicting cognitive decline in Aβ-positive cognitively unimpaired (CU) individuals.Design, Setting, and ParticipantsThis prospective population-based prognostic study evaluated data from 2 prospective longitudinal cohort studies (the Swedish BioFINDER-1 and the Wisconsin Registry for Alzheimer Prevention [WRAP]), with data collected from February 8, 2010, to October 21, 2020, for the BioFINDER-1 cohort and from August 11, 2011, to June 27, 2021, for the WRAP cohort. Participants were CU individuals recruited from memory clinics who had brain Aβ pathology defined by cerebrospinal fluid (CSF) Aβ42/40 in the BioFINDER-1 study and by Pittsburgh Compound B (PiB) positron emission tomography (PET) in the WRAP study. A total of 564 eligible Aβ-positive and Aβ-negative CU participants with available relevant data from the BioFINDER-1 and WRAP cohorts were included in the study; of those, 171 Aβ-positive participants were included in the main analyses.ExposuresBaseline P-tau181, P-tau217, P-tau231, glial fibrillary filament protein, and neurofilament light measured in plasma; CSF biomarkers in the BioFINDER-1 cohort, and PiB PET uptake in the WRAP cohort.Main Outcomes and MeasuresThe primary outcome was longitudinal measures of cognition (using the Mini-Mental State Examination [MMSE] and the modified Preclinical Alzheimer Cognitive Composite [mPACC]) over a median of 6 years (range, 2-10 years). The secondary outcome was conversion to AD dementia. Baseline biomarkers were used in linear regression models to predict rates of longitudinal cognitive change (calculated separately). Models were adjusted for age, sex, years of education, apolipoprotein E ε4 allele status, and baseline cognition. Multivariable models were compared based on model R2 coefficients and corrected Akaike information criterion.ResultsAmong 171 Aβ-positive CU participants included in the main analyses, 119 (mean [SD] age, 73.0 [5.4] years; 60.5% female) were from the BioFINDER-1 study, and 52 (mean [SD] age, 64.4 [4.6] years; 65.4% female) were from the WRAP study. In the BioFINDER-1 cohort, plasma P-tau217 was the best marker to predict cognitive decline in the mPACC (model R2 = 0.41) and the MMSE (model R2 = 0.34) and was superior to the covariates-only models (mPACC: R2 = 0.23; MMSE: R2 = 0.04; P &amp;lt; .001 for both comparisons). Results were validated in the WRAP cohort; for example, plasma P-tau217 was associated with mPACC slopes (R2 = 0.13 vs 0.01 in the covariates-only model; P = .01) and MMSE slopes (R2 = 0.29 vs 0.24 in the covariates-only model; P = .046). Sparse models were identified with plasma P-tau217 as a predictor of cognitive decline. Power calculations for enrichment in hypothetical clinical trials revealed large relative reductions in sample sizes when using plasma P-tau217 to enrich for CU individuals likely to experience cognitive decline over time.Conclusions and RelevanceIn this study, plasma P-tau217 predicted cognitive decline in patients with preclinical AD. These findings suggest that plasma P-tau217 may be used as a complement to CSF or PET for participant selection in clinical trials of novel disease-modifying treatments.

Background: Mounting evidence links poor sleep quality with a higher risk of late-life dementia. However, the structural and cognitive correlates of insomnia are still not well understood. The study aims were to characterize the cognitive performance and brain structural pattern of cognitively unimpaired adults at increased risk for Alzheimer's disease (AD) with insomnia. Methods: This cross-sectional study included 1683 cognitively unimpaired middle/late-middle-aged adults from the ALFA (ALzheimer and FAmilies) study who underwent neuropsychological assessment, T1-weighted structural imaging (n = 366), and diffusion-weighted imaging (n = 334). The World Health Organization's World Mental Health Survey Initiative version of the Composite International Diagnostic Interview was used to define the presence or absence of insomnia. Multivariable regression models were used to evaluate differences in cognitive performance between individuals with and without insomnia, as well as potential interactions between insomnia and the APOE genotype. Voxel-based morphometry and tractbased spatial statistics were used to assess between-group differences and potential interactions between insomnia and the APOE genotype in gray matter volume and white matter diffusion metrics. Results: Insomnia was reported by 615 out of 1683 participants (36.5%), including 137 out of 366 (37.4%) with T1-weighted structural imaging available and 119 out of 334 (35.6%) with diffusion-weighted imaging. Individuals with insomnia (n = 615) performed worse in executive function tests than non-insomniacs and displayed lower gray matter volume in left orbitofrontal and right middle temporal cortex, bilateral precuneus, posterior cingulate cortex and thalamus, higher gray matter volume in the left caudate nucleus, and widespread reduction of mean and axial diffusivity in right hemisphere white matter tracts. Insomnia interacted with the APOE genotype, with APOE-ε4 carriers displaying lower gray matter volumes when insomnia was present, but higher volumes when insomnia was not present, in several gray matter regions, including the left angular gyrus, the bilateral superior frontal gyri, the thalami, and the right hippocampus.