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Updated: Jan 7, 2026

Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
Published on: January 28, 2014
Biomarkers
Sophie E Mastenbroek1,2,3, Lyduine E Collij1,2,3, Jacob W Vogel4
1Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands.
Background:
Cerebrospinal fluid (CSF) seed amplification assays (SAAs) for detecting α-synuclein (αsyn) seeds have recently emerged as robust in vivo biomarkers of Lewy body pathology (LBP). However, CSF sampling is invasive, costly, and time-consuming, limiting its widespread use. We aimed to develop and evaluate a neuropathologically-validated two-step workflow, leveraging smell function and CSF αsyn SAA to accurately determine postmortem LBP status. This approach could reduce the number of confirmatory lumbar punctures needed (Figure 1).
Methods:
The study included 358 individuals from the Arizona Study of Aging and Neurodegenerative Disorders with antemortem smell testing, CSF αsyn SAA results, and postmortem neuropathological assessments of regional LBP burden. Step-1 of the two-step workflow involved a risk-stratification model predicting postmortem cortical LBP-positivity (LBPctx, defined as at least mild pathology in any cortical region) using logistic regression models with University of Pennsylvania Smell Identification Test (UPSIT) scores (smell testing), age, and sex as predictors. In step-2, confirmatory CSF αsyn SAA testing was applied only to participants identified as high-risk in step-1. Workflow performance - accuracy, positive predictive value (PPV), negative predictive value (NPV), and reduction in CSF testing - was evaluated in (i) the entire study cohort; (ii) patients with clinical parkinsonism; (iii) patients with an Alzheimer's disease (AD) clinical syndrome; and (iv) clinically unimpaired (CU) individuals.
Results:
Participants had a mean age at death of 86.2±7.8 years, 42.6% were female, 35.2% had LBPctx, and the average time between UPSIT and death was 3.2±2.3 years (Table 1). Using a 95% sensitivity cut-off for the UPSIT-based algorithm, the two-step workflow achieved high accuracy in identifying LBPctx (whole cohort=94%; clinical parkinsonism=95%; clinical AD=94%; CU=93%; Figure 2a), while reducing CSF testing (whole cohort=-43%; clinical parkinsonism=-23%; clinical AD=-35%; and CU=-80%; Figure 2d). PPVs ranged from 75-96% and were highest in the clinical parkinsonism subgroup (96%) where LBPctx+ was highest (62.7%). NPVs ranged between 95-98% and were highest in the clinical AD subgroup (98%) (Figure 2b-c). The two-step approach reached accuracies similar to using CSF tests in all participants.
Conclusions:
Implementing a two-step workflow in different clinical scenarios may reduce invasive testing with CSF, minimizing the burden for individuals and costs for healthcare providers.
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