Widespread implementation of Alzheimer’s disease (AD) biomarkers in research settings introduces new opportunities and challenges for managing and returning complex, multi-modal testing results to research participants.
Objectives:
To describe a structured, participant-centered biomarker data management and return of results workflow developed at a U.S. Alzheimer’s Disease Research Center (ADRC), and to provide preliminary data on participant and clinician experience with return of results.
Methods:
We developed an automated, interdisciplinary workflow to integrate multimodal biomarker data (neuroimaging, fluid, and genetics) into research consensus diagnostic conferences and individualized participant Return of Results reports. To evaluate feasibility and participant experience, we conducted a non-randomized study in which participants receiving biomarker results rated anxiety, depression, and decision regret within one week and at 3-month follow-up.
Results:
The workflow was implemented using non-proprietary tools, with semi-automated data aggregation and nightly updates. Survey data indicated statistically significant changes in anxiety and depression following biomarker return of results, though the clinical relevance of these changes remains unclear, highlighting opportunities to improve utility.
Conclusions:
Using and returning biomarker results is feasible, scalable, and well-tolerated within a research setting. This model may guide broader adoption of AD biomarker management and return of results to participants in future study designs.
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