SwePub
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Wallin A) ;pers:(Zetterberg H)"

Sökning: WFRF:(Wallin A) > Zetterberg H

  • Resultat 1-6 av 6
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  •  
2.
  • ten Kate, M., et al. (författare)
  • MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study
  • 2018
  • Ingår i: Alzheimers Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 10
  • 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.
  •  
3.
  • Zhang, Y. T., et al. (författare)
  • Predicting AT(N) pathologies in Alzheimer's disease from blood-based proteomic data using neural networks
  • 2022
  • Ingår i: Frontiers in Aging Neuroscience. - : Frontiers Media SA. - 1663-4365. ; 14
  • Tidskriftsartikel (refereegranskat)abstract
    • Background and objective: Blood-based biomarkers represent a promising approach to help identify early Alzheimer's disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. In the current study, we aim to harness the power of state-of-the-art deep learning neural networks (NNs) to identify plasma proteins that predict amyloid, tau, and neurodegeneration (AT[N]) pathologies in AD.Methods: We measured 3,635 proteins using SOMAscan in 881 participants from the European Medical Information Framework for AD Multimodal Biomarker Discovery study (EMIF-AD MBD). Participants underwent measurements of brain amyloid 13 (A13) burden, phosphorylated tau (p-tau) burden, and total tau (t-tau) burden to determine their AT(N) statuses. We ranked proteins by their association with A13, p-tau, t-tau, and AT(N), and fed the top 100 proteins along with age and apolipoprotein E (APOE) status into NN classifiers as input features to predict these four outcomes relevant to AD. We compared NN performance of using proteins, age, and APOE genotype with performance of using age and APOE status alone to identify protein panels that optimally improved the prediction over these main risk factors. Proteins that improved the prediction for each outcome were aggregated and nominated for pathway enrichment and protein-protein interaction enrichment analysis.Results: Age and APOE alone predicted A13, p-tau, t-tau, and AT(N) burden with area under the curve (AUC) scores of 0.748, 0.662, 0.710, and 0.795. The addition of proteins significantly improved AUCs to 0.782, 0.674, 0.734, and 0.831, respectively. The identified proteins were enriched in five clusters of AD-associated pathways including human immunodeficiency virus 1 infection, p53 signaling pathway, and phosphoinositide-3-kinase-protein kinase B/Akt signaling pathway.Conclusion: Combined with age and APOE genotype, the proteins identified have the potential to serve as blood-based biomarkers for AD and await validation in future studies. While the NNs did not achieve better scores than the support vector machine model used in our previous study, their performances were likely limited by small sample size.
  •  
4.
  • Blennow, K., et al. (författare)
  • EVOLUTION OF A beta 42 AND A beta 40 LEVELS AND A beta 42/A beta 40 RATIO IN PLASMA DURING PROGRESSION OF ALZHEIMER'S DISEASE: A MULTICENTER ASSESSMENT
  • 2009
  • Ingår i: Journal Of Nutrition Health & Aging. - 1279-7707. ; 13:3, s. 205-208
  • Konferensbidrag (refereegranskat)abstract
    • Objective: To better understand the seemingly contradictory plasma beta-amyloid (A beta) results in Alzheimer's disease (AD) patients by using a newly developed plasma A beta assay, the INNO-BIA plasma A beta forms, in a multicenter study. Methods: A combined retrospective analysis of plasma A beta isoforms on mild cognitive impairment (MCI) from three large cross-sectional studies involving 643 samples from the participating German and Swedish centers. Results: Detection modules based on two different amino (N)-terminal specific A beta monoclonal antibodies demonstrated that A beta in plasma could be reliable quantified using a sandwich immunoassay technology with high precision, even for low A beta 42 plasma concentrations. A beta 40 and A beta 42 concentrations varied consistently with the ApoE genotype, while the A beta 42/A beta 40 ratio did not. Irrespective of the decrease of the A beta 42/A beta 40 ratio with age and MMSE, this parameter was strongly associated with AD, as defined in this study by elevated hyperphosphorylated (P-tau181P) levels in cerebrospinal fluid (CSF). Conclusion: A highly robust assay for repeatedly measuring A beta forms in plasma such as INNO-BIA plasma A beta forms might be a useful tool in a future risk assessment of AD.
  •  
5.
  • Johansson, Per, et al. (författare)
  • Convergence of chromogranin and amyloid metabolism in the brain.
  • 2010
  • Ingår i: Alzheimer's & Dementia. - : Wiley. - 1552-5279 .- 1552-5260. ; 6:4, s. 511-511
  • Konferensbidrag (refereegranskat)abstract
    • Background: Much is unknown regarding the regulation of amyloid precursor protein (APP) processing in the human central nervous system. It has been hypothesized that amyloidogenic APP-processing preferentially occurs in the regulated secretory pathway of neurons. To test this hypothesis we looked for correlations of APP-derived molecules in CSF with chromogranin (Cg) derived peptides, representing the regulated secretion. Methods: Patients with Alzheimer's disease (AD, N = 32), multiple sclerosis (MS, N = 50) and healthy controls (N = 70) were enrolled. CSF was analyzed for the amyloid peptides Aβ1-42, Aβx-42, Aβx-40, Aβx-38, α-cleaved soluble APP (α-sAPP), β-cleaved soluble APP (β-sAPP), and peptides derived from CgB and SgII (Secretogranin-II, CgC). We investigated CSF levels of the protease BACE1, which processes APP into Aβ, in relation to Cg-levels. Finally, we measured Cg levels in cell media from untreated and BACE1-inhibited SH-SY5Y human neuroblastoma cells. Results: CSF Cg levels correlated to sAPP and Aβ peptides in AD, MS and controls, and to CSF BACE1. Cell medium from BACE1-inhibited cells had decreased CgB levels. Conclusions: These results suggest that a large part of APP in the human central nervous system is processed in the regulated secretory pathway of neurons.
  •  
6.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-6 av 6

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy