36 research outputs found

    Differences between plasma and cerebrospinal fluid glial fibrillary acidic protein levels across the Alzheimer Disease continuum

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    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. Design, Setting, and Participants: This observational, cross-sectional study collected data from July 29, 2014, to January 31, 2020, from 3 centers. The Translational Biomarkers in Aging and Dementia (TRIAD) cohort (Montreal, Canada) included individuals in the entire AD continuum. Results were confirmed in the Alzheimer’s and Families (ALFA+) study (Barcelona, Spain), which included individuals with preclinical AD, and the BioCogBank Paris Lariboisière cohort (Paris, France), which included individuals with symptomatic AD. Main Outcomes and Measures: Plasma and CSF GFAP levels measured with a Simoa assay were the main outcome. Other measurements included levels of CSF amyloid-β 42/40 (Aβ42/40), phosphorylated tau181 (p-tau181), neurofilament light (NfL), Chitinase-3-like protein 1 (YKL40), and soluble triggering receptor expressed on myeloid cells 2 (sTREM2) and levels of plasma p-tau181 and NfL. Results of amyloid positron emission tomography (PET) were available in TRIAD and ALFA+, and results of tau PET were available in TRIAD. Results: A total of 300 TRIAD participants (177 women [59.0%]; mean [SD] age, 64.6 [17.6] years), 384 ALFA+ participants (234 women [60.9%]; mean [SD] age, 61.1 [4.7] years), and 187 BioCogBank Paris Lariboisière participants (116 women [62.0%]; mean [SD] age, 69.9 [9.2] years) were included. Plasma GFAP levels were significantly higher in individuals with preclinical AD in comparison with cognitively unimpaired (CU) Aβ-negative individuals (TRIAD: Aβ-negative mean [SD], 185.1 [93.5] pg/mL, Aβ-positive mean [SD], 285.0 [142.6] pg/mL; ALFA+: Aβ-negative mean [SD], 121.9 [42.4] pg/mL, Aβ-positive mean [SD], 169.9 [78.5] pg/mL). Plasma GFAP levels were also higher among individuals in symptomatic stages of the AD continuum (TRIAD: CU Aβ-positive mean [SD], 285.0 [142.6] pg/mL, mild cognitive impairment [MCI] Aβ-positive mean [SD], 332.5 [153.6] pg/mL; AD mean [SD], 388.1 [152.8] pg/mL vs CU Aβ-negative mean [SD], 185.1 [93.5] pg/mL; Paris: MCI Aβ-positive, mean [SD], 368.6 [158.5] pg/mL; AD dementia, mean [SD], 376.4 [179.6] pg/mL vs CU Aβ-negative mean [SD], 161.2 [67.1] pg/mL). Plasma GFAP magnitude changes were consistently higher than those of CSF GFAP. Plasma GFAP more accurately discriminated Aβ-positive from Aβ-negative individuals than CSF GFAP (area under the curve for plasma GFAP, 0.69-0.86; area under the curve for CSF GFAP, 0.59-0.76). Moreover, plasma GFAP levels were positively associated with tau pathology only among individuals with concomitant Aβ pathology. Conclusions and Relevance: This study suggests that plasma GFAP is a sensitive biomarker for detecting and tracking reactive astrogliosis and Aβ pathology even among individuals in the early stages of AD

    The accuracy and robustness of plasma biomarker models for amyloid PET positivity

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    Background: Plasma biomarkers for Alzheimer’s disease (AD) have broad potential as screening tools in primary care and disease-modifying trials. Detecting elevated amyloid-β (Aβ) pathology to support trial recruitment or initiating Aβ-targeting treatments would be of critical value. In this study, we aimed to examine the robustness of plasma biomarkers to detect elevated Aβ pathology at different stages of the AD continuum. Beyond determining the best biomarker—or biomarker combination—for detecting this outcome, we also simulated increases in inter-assay coefficient of variability (CV) to account for external factors not considered by intra-assay variability. With this, we aimed to determine whether plasma biomarkers would maintain their accuracy if applied in a setting which anticipates higher variability (i.e., clinical routine). Methods: We included 118 participants (cognitively unimpaired [CU, n = 50], cognitively impaired [CI, n = 68]) from the ADNI study with a full plasma biomarker profile (Aβ42/40, GFAP, p-tau181, NfL) and matched amyloid imaging. Initially, we investigated how simulated CV variations impacted single-biomarker discriminative performance of amyloid status. Then, we evaluated the predictive performance of models containing different biomarker combinations, based both on original and simulated measurements. Plasma Aβ42/40 was represented by both immunoprecipitation mass spectrometry (IP-MS) and single molecule array (Simoa) methods in separate analyses. Model selection was based on a decision tree which incorporated Akaike information criterion value, likelihood ratio tests between the best-fitting models and, finally, and Schwartz’s Bayesian information criterion. Results: Increasing variation greatly impacted the performance of plasma Aβ42/40 in discriminating Aβ status. In contrast, the performance of plasma GFAP and p-tau181 remained stable with variations >20%. When biomarker models were compared, the models “AG” (Aβ42/40 + GFAP; AUC = 86.5), “A” (Aβ42/40; AUC = 82.3), and “AGP” (Aβ42/40 + GFAP + p-tau181; AUC = 93.5) were superior in determining Aβ burden in all participants, within-CU, and within-CI groups, respectively. In the robustness analyses, when repeating model selection based on simulated measurements, models including IP-MS Aβ42/40 were also most often selected. Simoa Aβ42/40 did not contribute to any selected model when used as an immunoanalytical alternative to IP-MS Aβ42/40. Conclusions: Plasma Aβ42/40, as quantified by IP-MS, shows high performance in determining Aβ positivity at all stages of the AD continuum, with GFAP and p-tau181 further contributing at CI stage. However, between-assay variations greatly impacted the performance of Aβ42/40 but not that of GFAP and p-tau181. Therefore, when dealing with between-assay CVs that exceed 5%, plasma GFAP and p-tau181 should be considered for a more robust determination of Aβ burden in CU and CI participants, respectively

    Blood phospho-tau in Alzheimer disease: analysis, interpretation, and clinical utility

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    Well-authenticated biomarkers can provide critical insights into the biological basis of Alzheimer disease (AD) to enable timely and accurate diagnosis, estimate future burden and support therapeutic trials. Current cerebrospinal fluid and molecular neuroimaging biomarkers fulfil these criteria but lack the scalability and simplicity necessary for widespread application. Blood biomarkers of adequate effectiveness have the potential to act as first-line diagnostic and prognostic tools, and offer the possibility of extensive population screening and use that is not limited to specialized centres. Accelerated progress in our understanding of the biochemistry of brain-derived tau protein and advances in ultrasensitive technologies have enabled the development of AD-specific phosphorylated tau (p-tau) biomarkers in blood. In this Review we discuss how new information on the molecular processing of brain p-tau and secretion of specific fragments into biofluids is informing blood biomarker development, enabling the evaluation of preanalytical factors that affect quantification, and informing harmonized protocols for blood handling. We also review the performance of blood p-tau biomarkers in the context of AD and discuss their potential contexts of use for clinical and research purposes. Finally, we highlight outstanding ethical, clinical and analytical challenges, and outline the steps that need to be taken to standardize inter-laboratory and inter-assay measurements

    Association of the fibronectin type III domain–containing protein 5 rs1746661 single nucleotide polymorphism with reduced brain glucose metabolism in elderly humans

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    Fibronectin type III domain–containing protein 5 (FNDC5) and its derived hormone, irisin, have been associated with metabolic control in humans, with described FNDC5 single nucleotide polymorphisms being linked to obesity and metabolic syndrome. Decreased brain FNDC5/irisin has been reported in subjects with dementia due to Alzheimer’s disease. Since impaired brain glucose metabolism develops in ageing and is prominent in Alzheimer’s disease, here, we examined associations of a single nucleotide polymorphism in the FNDC5 gene (rs1746661) with brain glucose metabolism and amyloid-β deposition in a cohort of 240 cognitively unimpaired and 485 cognitively impaired elderly individuals from the Alzheimer’s Disease Neuroimaging Initiative. In cognitively unimpaired elderly individuals harbouring the FNDC5 rs1746661(T) allele, we observed a regional reduction in low glucose metabolism in memory-linked brain regions and increased brain amyloid-β PET load. No differences in cognition or levels of cerebrospinal fluid amyloid-β42, phosphorylated tau and total tau were observed between FNDC5 rs1746661(T) allele carriers and non-carriers. Our results indicate that a genetic variant of FNDC5 is associated with low brain glucose metabolism in elderly individuals and suggest that FNDC5 may participate in the regulation of brain metabolism in brain regions vulnerable to Alzheimer’s disease pathophysiology. Understanding the associations between genetic variants in metabolism-linked genes and metabolic brain signatures may contribute to elucidating genetic modulators of brain metabolism in humans

    Amyloid-dependent and amyloid-independent effects of Tau in individuals without dementia

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    Objective: To investigate the relationship between the topography of amyloid-β plaques, tau neurofibrillary tangles, and the overlap between the two, with cognitive dysfunction in individuals without dementia. Methods: We evaluated 154 individuals who were assessed with amyloid-β PET with [18F]AZD4694, tau-PET with [18F]MK6240, structural MRI, and neuropsychological testing. We also evaluated an independent cohort of 240 individuals who were assessed with amyloid-β PET with [18F]Florbetapir, tau-PET with [18F]Flortaucipir, structural MRI, and neuropsychological testing. Using the VoxelStats toolbox, we conducted voxel-wise linear regressions between amyloid-PET, tau-PET, and their interaction with cognitive function, correcting for age, sex, and years of education. Results: In both cohorts, we observed that tau-PET standardized uptake value ratio in medial temporal lobes was associated with clinical dementia rating Sum of Boxes (CDR-SoB) scores independently of local amyloid-PET uptake (FWE corrected at p < 0.001). We also observed in both cohorts that in regions of the neocortex, associations between neocortical tau-PET and clinical function were dependent on local amyloid-PET (FWE corrected at p < 0.001). Interpretation: In medial temporal brain regions, characterized by the accumulation of tau pathology in the absence of amyloid-β, tau had direct associations with cognitive dysfunction. In brain regions characterized by the accumulation of both amyloid-β and tau pathologies such as the posterior cingulate and medial frontal cortices, tau’s relationship with cognitive dysfunction was dependent on local amyloid-β concentrations. Our results provide evidence that amyloid-β in Alzheimer’s disease influences cognition by potentiating the deleterious effects of tau pathology

    Soluble amyloid-beta isoforms predict downstream Alzheimer’s disease pathology

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    Background: Changes in soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) are detectable at early preclinical stages of Alzheimer’s disease (AD). However, whether Aβ levels can predict downstream AD pathological features in cognitively unimpaired (CU) individuals remains unclear. With this in mind, we aimed at investigating whether a combination of soluble Aβ isoforms can predict tau pathology (T+) and neurodegeneration (N+) positivity. Methods: We used CSF measurements of three soluble Aβ peptides (Aβ1–38, Aβ1–40 and Aβ1–42) in CU individuals (n = 318) as input features in machine learning (ML) models aiming at predicting T+ and N+. Input data was used for building 2046 tuned predictive ML models with a nested cross-validation technique. Additionally, proteomics data was employed to investigate the functional enrichment of biological processes altered in T+ and N+ individuals. Results: Our findings indicate that Aβ isoforms can predict T+ and N+ with an area under the curve (AUC) of 0.929 and 0.936, respectively. Additionally, proteomics analysis identified 17 differentially expressed proteins (DEPs) in individuals wrongly classified by our ML model. More specifically, enrichment analysis of gene ontology biological processes revealed an upregulation in myelinization and glucose metabolism-related processes in CU individuals wrongly predicted as T+. A significant enrichment of DEPs in pathways including biosynthesis of amino acids, glycolysis/gluconeogenesis, carbon metabolism, cell adhesion molecules and prion disease was also observed. Conclusions: Our results demonstrate that, by applying a refined ML analysis, a combination of Aβ isoforms can predict T+ and N+ with a high AUC. CSF proteomics analysis highlighted a promising group of proteins that can be further explored for improving T+ and N+ prediction

    Cerebrospinal fluid p-tau231 as an early indicator of emerging pathology in Alzheimer's disease

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    Background: Phosphorylated tau (p-tau) epitopes in cerebrospinal fluid (CSF) are accurate biomarkers for a pathological and clinical diagnosis of Alzheimer's disease (AD) and are seen to be increased in preclinical stage of the disease. However, it is unknown if these increases transpire earlier, prior to amyloid-beta (Aβ) positivity as determined by position emission tomography (PET), and if an ordinal sequence of p-tau epitopes occurs at this incipient phase. Methods: We measured CSF concentrations of p-tau181, p-tau217 and p-tau231 in 171 participants across the AD continuum who had undergone Aβ ([18F]AZD4694) and tau ([18F]MK6240) position emission tomography (PET) and clinical assessment. Findings: All CSF p-tau biomarkers were accurate predictors of cognitive impairment but CSF p-tau217 demonstrated the largest fold-changes in AD patients in comparison to non-AD dementias and cognitively unimpaired individuals. CSF p-tau231 and p-tau217 predicted Aβ and tau to a similar degree but p-tau231 attained abnormal levels first. P-tau231 was sensitive to the earliest changes of Aβ in the medial orbitofrontal, precuneus and posterior cingulate before global Aβ PET positivity was reached. Interpretation: We demonstrate that CSF p-tau231 increases early in development of AD pathology and is a principal candidate for detecting incipient Aβ pathology for therapeutic trial application

    A two-step workflow based on plasma p-tau217 to screen for amyloid β positivity with further confirmatory testing only in uncertain cases

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    Cost-effective strategies for identifying amyloid-β (Aβ) positivity in patients with cognitive impairment are urgently needed with recent approvals of anti-Aβ immunotherapies for Alzheimer’s disease (AD). Blood biomarkers can accurately detect AD pathology, but it is unclear whether their incorporation into a full diagnostic workflow can reduce the number of confirmatory cerebrospinal fluid (CSF) or positron emission tomography (PET) tests needed while accurately classifying patients. We evaluated a two-step workflow for determining Aβ-PET status in patients with mild cognitive impairment (MCI) from two independent memory clinic-based cohorts (n = 348). A blood-based model including plasma tau protein 217 (p-tau217), age and APOE ε4 status was developed in BioFINDER-1 (area under the curve (AUC) = 89.3%) and validated in BioFINDER-2 (AUC = 94.3%). In step 1, the blood-based model was used to stratify the patients into low, intermediate or high risk of Aβ-PET positivity. In step 2, we assumed referral only of intermediate-risk patients to CSF Aβ42/Aβ40 testing, whereas step 1 alone determined Aβ-status for low- and high-risk groups. Depending on whether lenient, moderate or stringent thresholds were used in step 1, the two-step workflow overall accuracy for detecting Aβ-PET status was 88.2%, 90.5% and 92.0%, respectively, while reducing the number of necessary CSF tests by 85.9%, 72.7% and 61.2%, respectively. In secondary analyses, an adapted version of the BioFINDER-1 model led to successful validation of the two-step workflow with a different plasma p-tau217 immunoassay in patients with cognitive impairment from the TRIAD cohort (n = 84). In conclusion, using a plasma p-tau217-based model for risk stratification of patients with MCI can substantially reduce the need for confirmatory testing while accurately classifying patients, offering a cost-effective strategy to detect AD in memory clinic settings

    Reactive astrogliosis is associated with higher cerebral glucose consumption in the early Alzheimer's continuum

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    PURPOSE: Glial activation is one of the earliest mechanisms to be altered in Alzheimer's disease (AD). Glial fibrillary acidic protein (GFAP) relates to reactive astrogliosis and can be measured in both cerebrospinal fluid (CSF) and blood. Plasma GFAP has been suggested to become altered earlier in AD than its CSF counterpart. Although astrocytes consume approximately half of the glucose-derived energy in the brain, the relationship between reactive astrogliosis and cerebral glucose metabolism is poorly understood. Here, we aimed to investigate the association between fluorodeoxyglucose ([18F]FDG) uptake and reactive astrogliosis, by means of GFAP quantified in both plasma and CSF for the same participants. METHODS: We included 314 cognitively unimpaired participants from the ALFA + cohort, 112 of whom were amyloid-β (Aβ) positive. Associations between GFAP markers and [18F]FDG uptake were studied. We also investigated whether these associations were modified by Aβ and tau status (AT stages). RESULTS: Plasma GFAP was positively associated with glucose consumption in the whole brain, while CSF GFAP associations with [18F]FDG uptake were only observed in specific smaller areas like temporal pole and superior temporal lobe. These associations persisted when accounting for biomarkers of Aβ pathology but became negative in Aβ-positive and tau-positive participants (A + T +) in similar areas of AD-related hypometabolism. CONCLUSIONS: Higher astrocytic reactivity, probably in response to early AD pathological changes, is related to higher glucose consumption. With the onset of tau pathology, the observed uncoupling between astrocytic biomarkers and glucose consumption might be indicative of a failure to sustain the higher energetic demands required by reactive astrocytes

    A three-range approach enhances the prognostic utility of CSF biomarkers in Alzheimer's disease

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    Introduction: Alzheimer's disease consensus recommends biomarker dichotomization, a practice with well-described clinical strengths and methodological limitations. Although neuroimaging studies have explored alternative biomarker interpretation strategies, a formally defined three-range approach and its prognostic impact remains under-explored for cerebrospinal fluid (CSF) biomarkers. Methods: With two-graph receiver-operating characteristics based on different reference schemes, we derived three-range cut-points for CSF Elecsys biomarkers. According to baseline CSF status, we assessed the prognostic utility of this in predicting risk of clinical progression and longitudinal trajectories of cognitive decline and amyloid–beta (Aβ) positron emission tomography (PET) accumulation in non-demented individuals (Alzheimer's Disease Neuroimaging Initiative [ADNI]; n = 1246). In all analyses, we compared herein-derived three-range CSF cut-points to previously described binary ones. Results: In our main longitudinal analyses, we highlight CSF p-tau181/Aβ1-42 three-range cut-points derived based on the cognitively normal Aβ-PET negative versus dementia Aβ-PET positive reference scheme for best depicting a prognostically relevant biomarker abnormality range. Longitudinally, our approach revealed a divergent intermediate cognitive trajectory undetected by dichotomization and a clearly abnormal group at higher risk for cognitive decline, with power analyses suggesting the latter group as potential trial enrichment candidates. Furthermore, we demonstrate that individuals with intermediate-range CSF status have similar rates of Aβ deposition to those in the clearly abnormal group. Discussion: The proposed approach can refine clinico-biological prognostic assessment and potentially enhance trial recruitment, as it captures faster biomarker-related cognitive decline in comparison to binary cut-points. Although this approach has implications for trial recruitment and observational studies, further discussion is needed regarding clinical practice applications
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