Substituting Blood-Based Biomarkers for Imaging Measures in Alzheimer's Disease Studies: Implications for Sample Size and Bias
Ackley, S. F.; La Joie, R.; Caunca, M.; Mukherjee, S.; Choi, S.-E.; Trittschuh, E. H.; Crane, P. K.; Hayes-Larson, E.
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BackgroundBlood-based biomarkers for Alzheimers disease (AD) pathology are appealing options in large population-based studies due to their low cost, minimal invasiveness, and feasibility of collection in non-clinical settings. Despite these benefits, blood-based biomarkers have lower test-retest reliability than neuroimaging measures like amyloid positron emission tomography (amyloid-PET) Centiloids; trade-offs in power and bias remain unexplored. MethodsWe use data from Alzheimers Disease Neuroimaging Initiative (ADNI) and the Anti-Amyloid Treatment in Asymptomatic Alzheimers Disease (A4) studies, which include both amyloid-PET and blood-based measures, to assess differences in statistical power, required sample size, and bias when replacing a neuroimaging measure with a blood-based measure. We use simulations parameterized based on these studies to show potential implications of using plasma p-tau181 or p-tau217, blood-based AD biomarkers, in place of Centiloids from amyloid-PET, when the biomarker is either the exposure or the outcome in an analysis of interest. ResultsWe demonstrated that substituting amyloid-PET Centiloids with a blood-based measure of p-tau can substantially reduce power, requiring 3 to 6 times the sample size to achieve 80% power compared to amyloid-PET. In addition, using a blood-based biomarker as the exposure can introduce significant regression dilution bias, attenuating estimated associations. ConclusionsDue to their lower cost and ease of collection compared with neuroimaging, blood-based biomarkers facilitate AD pathology measures on larger, more diverse samples with longitudinal follow-up. Consideration of the sample sizes they necessitate and their potential for bias is critical for the design and interpretation of studies employing these biomarkers.
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