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- Bos, I., et al.
(författare)
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Cerebrospinal fluid biomarkers of neurodegeneration, synaptic integrity, and astroglial activation across the clinical Alzheimer's disease spectrum
- 2019
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Ingår i: Alzheimers & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 15:5, s. 644-654
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: We investigated relations between amyloid-beta (A beta) status, apolipoprotein E (APOE) e4, and cognition, with cerebrospinal fluid markers of neurogranin (Ng), neurofilament light (NFL), YKL-40, and total tau (T-tau). Methods: We included 770 individuals with normal cognition, mild cognitive impairment, and Alzheimer's disease (AD)-type dementia from the EMIF-AD Multimodal Biomarker Discovery study. We tested the association of Ng, NFL, YKL-40, and T-tau with A beta status (Ab beta- vs. A beta+), clinical diagnosis APOE epsilon 4 carriership, baseline cognition, and change in cognition. Results: Ng and T-tau distinguished between A beta+ from A beta- individuals in each clinical group, whereas NFL and YKL-40 were associated with A beta+ in nondemented individuals only. APOE epsilon 4 carriership did not influence NFL, Ng, and YKL-40 in A beta+ individuals. NFL was the best predictor of cognitive decline in A beta+ individuals across the cognitive spectrum. Discussion: Axonal degeneration, synaptic dysfunction, astroglial activation, and altered tau metabolism are involved already in preclinical AD. NFL may be a useful prognostic marker. (C) 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.
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- ten Kate, M., et al.
(författare)
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MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study
- 2018
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Ingår i: Alzheimers Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: With the shift of research focus towards the pre-dementia stage of Alzheimer's disease (AD), there is an urgent need for reliable, non-invasive biomarkers to predict amyloid pathology. The aim of this study was to assess whether easily obtainable measures from structural MRI, combined with demographic data, cognitive data and apolipoprotein E (APOE) epsilon 4 genotype, can be used to predict amyloid pathology using machine-learning classification. Methods: We examined 810 subjects with structural MRI data and amyloid markers from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, including subjects with normal cognition (CN, n = 337, age 66.5 +/- 72, 50% female, 27% amyloid positive), mild cognitive impairment (MCI, n = 375, age 69. 1 +/- 7.5, 53% female, 63% amyloid positive) and AD dementia (n = 98, age 67.0 +/- 7.7, 48% female, 97% amyloid positive). Structural MRI scans were visually assessed and Freesurfer was used to obtain subcortical volumes, cortical thickness and surface area measures. We first assessed univariate associations between MRI measures and amyloid pathology using mixed models. Next, we developed and tested an automated classifier using demographic, cognitive, MRI and APOE epsilon 4 information to predict amyloid pathology. A support vector machine (SVM) with nested 10-fold cross-validation was applied to identify a set of markers best discriminating between amyloid positive and amyloid negative subjects. Results: In univariate associations, amyloid pathology was associated with lower subcortical volumes and thinner cortex in AD-signature regions in CN and MCI. The multi-variable SVM classifier provided an area under the curve (AUC) of 0.81 +/- O. 07 in MCI and an AUC of 0.74 +/- 0.08 in CN. In CN, selected features for the classifier included APOE epsilon 4, age, memory scores and several MRI measures such as hippocampus, amygdala and accumbens volumes and cortical thickness in temporal and parahippocampal regions. In MCI, the classifier including demographic and APOE epsilon 4 information did not improve after additionally adding imaging measures. Conclusions: Amyloid pathology is associated with changes in structural MRI measures in CN and MCI. An automated classifier based on clinical, imaging and APOE epsilon 4 data can identify the presence of amyloid pathology with a moderate level of accuracy. These results could be used in clinical trials to pre-screen subjects for anti-amyloid therapies.
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- Bos, I., et al.
(författare)
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The EMIF-AD Multimodal Biomarker Discovery study: design, methods and cohort characteristics
- 2018
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Ingår i: Alzheimers Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: There is an urgent need for novel, noninvasive biomarkers to diagnose Alzheimer's disease (AD) in the predementia stages and to predict the rate of decline. Therefore, we set up the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study. In this report we describe the design of the study, the methods used and the characteristics of the participants. Methods: Participants were selected from existing prospective multicenter and single-center European studies. Inclusion criteria were having normal cognition (NC) or a diagnosis of mild cognitive impairment (MCI) or AD-type dementia at baseline, age above 50 years, known amyloid-beta (A beta) status, availability of cognitive test results and at least two of the following materials: plasma, DNA, magnetic resonance imaging (MRI) or cerebrospinal fluid (CSF). Targeted and untargeted metabolomic and proteomic analyses were performed in plasma, and targeted and untargeted proteomics were performed in CSF. Genome-wide SNP genotyping, next-generation sequencing and methylation profiling were conducted in DNA. Visual rating and volumetric measures were assessed on MRI. Baseline characteristics were analyzed using ANOVA or chi-square, rate of decline analyzed by linear mixed modeling. Results: We included 1221 individuals (NC n = 492, MCI n = 527, AD-type dementia n = 202) with a mean age of 67.9 (SD 8.3) years. The percentage A beta+ was 26% in the NC, 58% in the MCI, and 87% in the AD-type dementia groups. Plasma samples were available for 1189 (97%) subjects, DNA samples for 929 (76%) subjects, MRI scans for 862 (71%) subjects and CSF samples for 767 (63%) subjects. For 759 (62%) individuals, clinical follow-up data were available. In each diagnostic group, the APOE e4 allele was more frequent amongst A beta+ individuals (p < 0.001). Only in MCI was there a difference in baseline Mini Mental State Examination (MMSE) score between the A groups (p< 0.001). A beta+ had a faster rate of decline on the MMSE during follow-up in the NC (p < 0.001) and MCI (p < 0.001) groups. Conclusions: The characteristics of this large cohort of elderly subjects at various cognitive stages confirm the central roles of A beta and APOE epsilon 4 in AD pathogenesis. The results of the multimodal analyses will provide new insights into underlying mechanisms and facilitate the discovery of new diagnostic and prognostic AD biomarkers. All researchers can apply for access to the EMIF-AD MBD data by submitting a research proposal via the EMIF-AD Catalog.
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- Perez-Grijalba, V, et al.
(författare)
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Plasma Aβ42/40 ratio alone or combined with FDG-PET can accurately predict amyloid-PET positivity: a cross-sectional analysis from the AB255 Study
- 2019
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Ingår i: Alzheimer's research & therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 11:1, s. 96-
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundTo facilitate population screening and clinical trials of disease-modifying therapies for Alzheimer’s disease, supportive biomarker information is necessary. This study was aimed to investigate the association of plasma amyloid-beta (Aβ) levels with the presence of pathological accumulation of Aβ in the brain measured by amyloid-PET. Both plasma Aβ42/40 ratio alone or combined with an FDG-PET-based biomarker of neurodegeneration were assessed as potential AD biomarkers.MethodsWe included 39 cognitively normal subjects and 20 patients with mild cognitive impairment from the AB255 Study who had undergone PiB-PET scans. Total Aβ40 and Aβ42 levels in plasma (TP42/40) were quantified using ABtest kits. Subjects were dichotomized as Aβ-PET positive or negative, and the ability of TP42/40 to detect Aβ-PET positivity was assessed by logistic regression and receiver operating characteristic analyses. Combination of plasma Aβ biomarkers and FDG-PET was further assessed as an improvement for brain amyloidosis detection and diagnosis classification.ResultsEighteen (30.5%) subjects were Aβ-PET positive. TP42/40 ratio alone identified Aβ-PET status with an area under the curve (AUC) of 0.881 (95% confidence interval [CI] = 0.779–0.982). Discriminating performance of TP42/40 to detect Aβ-PET-positive subjects yielded sensitivity and specificity values at Youden’s cutoff of 77.8% and 87.5%, respectively, with a positive predictive value of 0.732 and negative predictive value of 0.900. All these parameters improved after adjusting the model for significant covariates. Applying TP42/40 as the first screening tool in a sequential diagnostic work-up would reduce the number of Aβ-PET scans by 64%. Combination of both FDG-PET scores and plasma Aβ biomarkers was found to be the most accurate Aβ-PET predictor, with an AUC of 0.965 (95% CI = 0.913–0.100).ConclusionsPlasma TP42/40 ratio showed a relevant and significant potential as a screening tool to identify brain Aβ positivity in preclinical and prodromal stages of Alzheimer’s disease.
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- Perez-Grijalba, V, et al.
(författare)
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Plasma Aβ42/40 Ratio Detects Early Stages of Alzheimer's Disease and Correlates with CSF and Neuroimaging Biomarkers in the AB255 Study
- 2019
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Ingår i: The journal of prevention of Alzheimer's disease. - : SERDI. - 2426-0266 .- 2274-5807. ; 6:1, s. 34-41
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Tidskriftsartikel (refereegranskat)abstract
- Background: Easily accessible biomarkers are needed for the early identification of individuals at risk of developing Alzheimer’s disease (AD) in large population screening strategies. Objectives: This study evaluated the potential of plasma β-amyloid (Aβ) biomarkers in identifying early stages of AD and predicting cognitive decline over the following two years. Design: Total plasma Aβ42/40 ratio (TP42/40) was determined in 83 cognitively normal individuals (CN) and 145 subjects with amnestic mild cognitive impairment (a-MCI) stratified by an FDG-PET AD-risk pattern. Results: Significant lower TP42/40 ratio was found in a-MCI patients compared to CN. Moreover, a-MCIs with a high-risk FDG-PET pattern for AD showed even lower plasma ratio levels. Low TP42/40 at baseline increased the risk of progression to dementia by 70%. Furthermore, TP42/40 was inversely associated with neocortical amyloid deposition (measured with PiB-PET) and was concordant with the AD biomarker profile in cerebrospinal fluid (CSF). Conclusions: TP42/40 demonstrated value in the identification of individuals suffering a-MCI, in the prediction of progression to dementia, and in the detection of underlying AD pathology revealed by FDG-PET, Amyloid-PET and CSF biomarkers, being, thus, consistently associated with all the well-established indicators of AD.
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