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- de Rojas, I., et al.
(författare)
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Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores
- 2021
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease. © 2021, The Author(s).
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| 4. |
- Kruse, N., et al.
(författare)
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Validation of a quantitative cerebrospinal fluid alpha-synuclein assay in a European-wide interlaboratory study
- 2015
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Ingår i: Neurobiology of Aging. - : Elsevier BV. - 0197-4580. ; 36:9, s. 2587-2596
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Tidskriftsartikel (refereegranskat)abstract
- Decreased levels of alpha-synuclein (aSyn) in cerebrospinal fluid (CSF) in Parkinson's disease and related synucleinopathies have been reported, however, not consistently in all cross-sectional studies. To test the performance of one recently released human-specific enzyme-linked immunosorbent assay (ELISA) for the quantification of aSyn in CSF, we carried out a round robin trial with 18 participating laboratories trained in CSF ELISA analyses within the BIOMARKAPD project in the EU Joint Program -Neurodegenerative Disease Research. CSF samples (homogeneous aliquots from pools) and ELISA kits (one lot) were provided centrally and data reported back to one laboratory for data analysis. Our study showed that although factors such as preanalytical sample handling and lot-to-lot variability were minimized by our study design, we identified high variation in absolute values of CSF aSyn even when the same samples and same lots of assays were applied. We further demonstrate that although absolute concentrations differ between laboratories the quantitative results are comparable. With further standardization this assay may become an attractive tool for comparing aSyn measurements in diverse settings. Recommendations for further validation experiments and improvement of the interlaboratory results obtained are given. (C) 2015 Elsevier Inc. All rights reserved.
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| 7. |
- Mattsson, Niklas, 1979, et al.
(författare)
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Age and diagnostic performance of Alzheimer disease CSF biomarkers.
- 2012
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Ingår i: Neurology. - : American Academy of Neurology (AAN). - 1526-632X .- 0028-3878. ; 78:7, s. 468-76
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Tidskriftsartikel (refereegranskat)abstract
- Core CSF changes in Alzheimer disease (AD) are decreased amyloid β(1-42), increased total tau, and increased phospho-tau, probably indicating amyloid plaque accumulation, axonal degeneration, and tangle pathology, respectively. These biomarkers identify AD already at the predementia stage, but their diagnostic performance might be affected by age-dependent increase of AD-type brain pathology in cognitively unaffected elderly.
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| 8. |
- 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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| 9. |
- Tijms, B. M., et al.
(författare)
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CSF Proteomic Alzheimer's Disease-Predictive Subtypes in Cognitively Intact Amyloid Negative Individuals
- 2021
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Ingår i: Proteomes. - : MDPI AG. - 2227-7382. ; 9:3
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Tidskriftsartikel (refereegranskat)abstract
- We recently discovered three distinct pathophysiological subtypes in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics: one with neuronal hyperplasticity, a second with innate immune system activation, and a third subtype with blood-brain barrier dysfunction. It remains unclear whether AD proteomic subtype profiles are a consequence of amyloid aggregation, or might exist upstream from aggregated amyloid. We studied this question in 127 older individuals with intact cognition and normal AD biomarkers in two independent cohorts (EMIF-AD MBD and ADNI). We clustered 705 proteins measured in CSF that were previously related to AD. We identified in these cognitively intact individuals without AD pathology three subtypes: two subtypes were seen in both cohorts (n = 49 with neuronal hyperplasticity and n = 44 with blood-brain barrier dysfunction), and one only in ADNI (n = 12 with innate immune activation). The proteins specific for these subtypes strongly overlapped with AD subtype protein profiles (overlap coefficients 92%-71%). Longitudinal p(181)-tau and amyloid beta 1-42 (A beta 42) CSF analysis showed that in the hyperplasticity subtype p(181)-tau increased (beta = 2.6 pg/mL per year, p = 0.01) and A beta 42 decreased over time (beta = -4.4 pg/mL per year, p = 0.03), in the innate immune activation subtype p(181)-tau increased (beta = 3.1 pg/mL per year, p = 0.01) while in the blood-brain barrier dysfunction subtype A beta 42 decreased (beta = -3.7 pg/mL per year, p = 0.009). These findings suggest that AD proteomic subtypes might already manifest in cognitively normal individuals and may predispose for AD before amyloid has reached abnormal levels.
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| 10. |
- Vermunt, L., et al.
(författare)
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Duration of preclinical, prodromal, and dementia stages of Alzheimer's disease in relation to age, sex, and APOE genotype
- 2019
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Ingår i: Alzheimers & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 15:7, s. 888-898
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: We estimated the age-specific duration of the preclinical, prodromal, and dementia stages of Alzheimer's disease (AD) and the influence of sex, setting, apolipoprotein E (APOE) genotype, and cerebrospinal fluid tau on disease duration. Methods: We performed multistate modeling in a combined sample of 6 cohorts (n = 3268) with death as the end stage and estimated the preclinical, prodromal, and dementia stage duration. Results: The overall AD duration varied between 24 years (age 60) and 15 years (age 80). For individuals presenting with preclinical AD, age 70, the estimated preclinical AD duration was 10 years, prodromal AD 4 years, and dementia 6 years. Male sex, clinical setting, APOE epsilon 4 allele carriership, and abnormal cerebrospinal fluid tau were associated with a shorter duration, and these effects depended on disease stage. Discussion: Estimates of AD disease duration become more accurate if age, sex, setting, APOE, and cerebrospinal fluid tau are taken into account. This will be relevant for clinical practice and trial design. (C) 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.
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