A proteomic predictor of conversion from mild cognitive impairment to dementia with potential utility in enhancing productivity of emerging clinical trials
Abstract
- A significant proportion of individuals with mild cognitive impairment (MCI) develop dementia, with annual conversion rates exceeding 10%.
- Earlier dementia diagnosis and intervention can improve outcomes, and new disease-modifying drugs are being repositioned for the preclinical stages of illness.
- Identifying individuals at risk for conversion from MCI to dementia could offer substantial benefits to public healthcare and
pharmaceutical industries. Given the absence of a surrogate endpoint for dementia actual clinical diagnoses are needed to
develop in trials. - Therefore, we sought to develop a protein-based tool with potential for trial population enrichment through risk prediction of
dementia in individuals with MCI.
Methods
- Using modified-aptamer proteomics technology, SomaScan® Assay v4.0 (Figure 1), we scanned ~5,000 proteins in 1,132 EDTA plasma samples from individuals aged 67-89 with MCI at visit 5 blood draw of the Atherosclerosis Risk in Communities (ARIC) study.
- 236 incident dementia diagnoses (25% conversion rate) occurred within 5 years of blood draw.
- Time to dementia diagnosis events were modeled with protein measurements using machine learning methods in a training
dataset. A model was selected based on performance in a holdout sample subset. Model performance, dynamic range and calibration was assessed. - Model performance was compared to that of the predictive performance of age and APOE risk genotype.
Authors
Clare Paterson PhD1
Bryan Dawkins PhD1
Hannah Biegel PhD1
Yolanda Hagar PhD1
Stephen A Williams MD PhD.1
1Standard BioTools, Boulder, Colorado
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