Biomarker clustering in autosomal dominant Alzheimer's disease
| Autor: | Luckett, Patrick H., Chen, Charlie, Jucker, Mathias, Levin, Johannes, Masters, Colin L., Mori, Hiroshi, Noble, James M., Salloway, Stephen, Schofield, Peter R., Brickman, Adam M., Brooks, William S., Cash, David M., Gordon, Brian A., Fulham, Michael J., Ghetti, Bernardino, Jack, Clifford R., Vöglein, Jonathan, Klunk, William E., Koeppe, Robert, Su, Yi, Weiner, Michael, Wang, Qing, Marcus, Daniel, Wisch, Julie, Koudelis, Deborah, Joseph-Mathurin, Nelly, Cash, Lisa, Hornbeck, Russ, Xiong, Chengjie, Perrin, Richard J., Karch, Celeste M., Hassenstab, Jason, McDade, Eric, Morris, John C., Berman, Sarah B., Benzinger, Tammie L. S., Bateman, Randall J., Ances, Beau M., Chhatwal, Jasmeer P., Cruchaga, Carlos, Fagan, Anne M., Farlow, Martin R., Fox, Nick C. |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
Inflammation
Amyloid beta-Peptides Epidemiology Health Policy diagnosis [Alzheimer Disease] biomarkers Amyloidogenic Proteins tau Proteins cerebrospinal fluid [Amyloid beta-Peptides] Psychiatry and Mental health Cellular and Molecular Neuroscience genetics [tau Proteins] Cross-Sectional Studies machine learning Developmental Neuroscience cerebrospinal fluid [Biomarkers] cerebrospinal fluid [tau Proteins] Humans Neurology (clinical) ddc:610 Geriatrics and Gerontology Autosomal dominant Alzheimer's disease |
| Zdroj: | Alzheimer's and dementia 19(1), 274-284 (2023). doi:10.1002/alz.12661 |
| Popis: | INTRODUCTIONAs the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others.METHODSWe used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation.RESULTSThree primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors.DISCUSSIONThese results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression. |
| Databáze: | OpenAIRE |
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