A computational neurodegenerative disease progression score: Method and results with the Alzheimer's disease neuroimaging initiative cohort
| Autor: | Brian Caffo, Elyse Katz, Yanwei Zhang, Bo Liu, Bradley T. Wyman, Andrew Lang, Bruno Jedynak, C. Pierre Jedynak, Jerry L. Prince, David Raunig |
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| Rok vydání: | 2012 |
| Předmět: |
Amyloid beta
Cognitive Neuroscience Population Disease Bioinformatics Severity of Illness Index Article Cohort Studies Neuroimaging Alzheimer Disease Humans Medicine education education.field_of_study biology business.industry Neurodegenerative Diseases medicine.disease Neurology Cohort Disease Progression biology.protein Biomarker (medicine) Alzheimer's disease business Neuroscience Algorithms Biomarkers Alzheimer's Disease Neuroimaging Initiative |
| Zdroj: | NeuroImage. 63:1478-1486 |
| ISSN: | 1053-8119 |
| Popis: | While neurodegenerative diseases are characterized by steady degeneration over relatively long timelines, it is widely believed that the early stages are the most promising for therapeutic intervention, before irreversible neuronal loss occurs. Developing a therapeutic response requires a precise measure of disease progression. However, since the early stages are for the most part asymptomatic, obtaining accurate measures of disease progression is difficult. Longitudinal databases of hundreds of subjects observed during several years with tens of validated biomarkers are becoming available, allowing the use of computational methods. We propose a widely applicable statistical methodology for creating a disease progression score (DPS), using multiple biomarkers, for subjects with a neurodegenerative disease. The proposed methodology was evaluated for Alzheimer’s disease (AD) using the publicly available AD Neuroimaging Initiative (ADNI) database, yielding an Alzheimer’s DPS or ADPS score for each subject and each time-point in the database. In addition, a common description of biomarker changes was produced allowing for an ordering of the biomarkers. The Rey Auditory Verbal Learning Test delayed recall was found to be the earliest biomarker to become abnormal. The group of biomarkers comprising the volume of the hippocampus and the protein concentration amyloid beta and Tau were next in the timeline, and these were followed by three cognitive biomarkers. The proposed methodology thus has potential to stage individuals according to their state of disease progression relative to a population and to deduce common behaviors of biomarkers in the disease itself. |
| Databáze: | OpenAIRE |
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