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A Subset of Cerebrospinal Fluid Proteins from a Multi-Analyte Panel Associated with Brain Atrophy, Disease Classification and Prediction in Alzheimer's Disease.
Khan, Wasim; Aguilar, Carlos; Kiddle, Steven J; Doyle, Orla; Thambisetty, Madhav; Muehlboeck, Sebastian; Sattlecker, Martina; Newhouse, Stephen; Lovestone, Simon; Dobson, Richard; Giampietro, Vincent; Westman, Eric; Simmons, Andrew.
Afiliación
  • Khan W; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; NIHR Biomedical Research Centre for Mental Health, London, United Kingdom; NIHR Biomedical Research Unit for Dementia, London, United Kingdom.
  • Aguilar C; Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
  • Kiddle SJ; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; NIHR Biomedical Research Centre for Mental Health, London, United Kingdom.
  • Doyle O; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.
  • Thambisetty M; Laboratory of Behavioural Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America.
  • Muehlboeck S; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; NIHR Biomedical Research Centre for Mental Health, London, United Kingdom; NIHR Biomedical Research Unit for Dementia, London, United Kingdom.
  • Sattlecker M; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; NIHR Biomedical Research Centre for Mental Health, London, United Kingdom.
  • Newhouse S; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; NIHR Biomedical Research Centre for Mental Health, London, United Kingdom.
  • Lovestone S; Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
  • Dobson R; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; NIHR Biomedical Research Centre for Mental Health, London, United Kingdom; NIHR Biomedical Research Unit for Dementia, London, United Kingdom.
  • Giampietro V; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom.
  • Westman E; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
  • Simmons A; King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; NIHR Biomedical Research Centre for Mental Health, London, United Kingdom; NIHR Biomedical Research Unit for Dementia, London, United Kingdom.
PLoS One ; 10(8): e0134368, 2015.
Article en En | MEDLINE | ID: mdl-26284520
In this exploratory neuroimaging-proteomic study, we aimed to identify CSF proteins associated with AD and test their prognostic ability for disease classification and MCI to AD conversion prediction. Our study sample consisted of 295 subjects with CSF multi-analyte panel data and MRI at baseline downloaded from ADNI. Firstly, we tested the statistical effects of CSF proteins (n = 83) to measures of brain atrophy, CSF biomarkers, ApoE genotype and cognitive decline. We found that several proteins (primarily CgA and FABP) were related to either brain atrophy or CSF biomarkers. In relation to ApoE genotype, a unique biochemical profile characterised by low CSF levels of Apo E was evident in ε4 carriers compared to ε3 carriers. In an exploratory analysis, 3/83 proteins (SGOT, MCP-1, IL6r) were also found to be mildly associated with cognitive decline in MCI subjects over a 4-year period. Future studies are warranted to establish the validity of these proteins as prognostic factors for cognitive decline. For disease classification, a subset of proteins (n = 24) combined with MRI measurements and CSF biomarkers achieved an accuracy of 95.1% (Sensitivity 87.7%; Specificity 94.3%; AUC 0.95) and accurately detected 94.1% of MCI subjects progressing to AD at 12 months. The subset of proteins included FABP, CgA, MMP-2, and PPP as strong predictors in the model. Our findings suggest that the marker of panel of proteins identified here may be important candidates for improving the earlier detection of AD. Further targeted proteomic and longitudinal studies would be required to validate these findings with more generalisability.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Encéfalo / Proteínas del Líquido Cefalorraquídeo / Progresión de la Enfermedad / Enfermedad de Alzheimer Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2015 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Encéfalo / Proteínas del Líquido Cefalorraquídeo / Progresión de la Enfermedad / Enfermedad de Alzheimer Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2015 Tipo del documento: Article País de afiliación: Reino Unido
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