Impact of Pre-Analytical Differences on Biomarkers in the ADNI and PPMI Studies: Implications in the Era of Classifying Disease Based on Biomarkers.

Abstract

Neurodegenerative diseases require characterization based on underlying biology using biochemical biomarkers. Mixed pathology complicates discovery of biomarkers and characterization of cohorts, but inclusion of greater numbers of patients with different, related diseases with frequently co-occurring pathology could allow better accuracy. Combining cohorts collected from different studies would be a more efficient use of resources than recruiting subjects from each population of interest for each study. To explore the possibility of combining existing datasets by controlling pre-analytic variables in the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Parkinson's Progression Markers Initiative (PPMI) studies. Cerebrospinal fluid (CSF) was collected and processed from 30 subjects according to both the ADNI and PPMI protocols. Relationships between reported levels of Alzheimer's disease (AD) and Parkinson's disease (PD) biomarkers in the same subject under each protocol were examined. Protocol-related differences were observed for Aβ, but not t-tau or α-syn, and trended different for p-tau and pS129. Values of α-syn differed by platform. Conversion of α-syn values between ADNI and PPMI platforms did not completely eliminate differences in distribution. Factors not captured in the pre-analytical sample handling influence reported biomarker values. Assay standardization and better harmonized characterization of cohorts should be included in future studies of CSF biomarkers.