Abstract
Biomarkers from multiple modalities have been shown to correlate with cognition in Parkinson’s disease (PD) and in Alzheimer’s disease (AD). However, the relationships of these markers with each other, and the use of multiple markers in concert to predict an outcome of interest, are areas that are much less explored. Our objectives in this study were (1) to evaluate relationships among 17 biomarkers previously reported to associate with cognition in PD or AD and (2) to test performance of a five-biomarker classifier trained to recognize AD in identifying PD with dementia (PDD). To do this, we evaluated a cross-sectional cohort of PD patients (n = 75) across a spectrum of cognitive abilities. All PD participants had 17 baseline biomarkers from clinical, genetic, biochemical, and imaging modalities measured, and correlations among biomarkers were assessed by Spearman’s rho and by hierarchical clustering. We found that internal correlation among all 17 candidate biomarkers was modest, showing a maximum pairwise correlation coefficient of 0.51. However, a five-marker subset panel derived from AD (CSF total tau, CSF phosphorylated tau, CSF amyloid beta 42, APOE genotype, and SPARE-AD imaging score) discriminated cognitively normal PD patients vs. PDD patients with 80% accuracy, when employed in a classifier originally trained to recognize AD. Thus, an AD-derived biomarker signature may identify PDD patients with moderately high accuracy, suggesting mechanisms shared with AD in some PDD patients. Based on five measures readily obtained during life, this AD-derived signature may prove useful in identifying PDD patients most likely to respond to AD-based crossover therapies.
Highlights
Parkinson disease (PD) is the second most common adult-onset neurodegenerative disease, affecting an estimated 1 million people in the United States alone [1,2]
After Bonferroni correction, significant associations were detected between PD with dementia (PDD) and two candidate biomarkers
PDD patients trended towards lower levels of cerebrospinal fluid (CSF) Aβ42
Summary
Parkinson disease (PD) is the second most common adult-onset neurodegenerative disease, affecting an estimated 1 million people in the United States alone [1,2]. While common uses of the term often refer to biochemical or imaging-based measures, in the most generic form, biomarkers might originate from multiple types of data. Reported biochemical correlates of cognitive decline in PD include lower levels of cerebrospinal fluid (CSF) amyloid beta, the disease-implicated form of amyloid beta known as Aβ42 [22,23], and lower levels of plasma epidermal growth factor (EGF) [24,25], while higher levels of CSF total tau (t-tau) and phosphorylated tau (p-tau) associate with poorer cognition in Alzheimer disease (AD) [23]. It is notable that many of the biochemical and imaging-based biomarkers for cognitive performance in PD are “crossover” biomarkers from AD. No doubt this reflects in part the relative paucity of available candidate PD biomarkers [29]. Because 5/17 markers in our panel have been strongly implicated in AD, we tested the hypothesis that an AD-derived biomarker signature might identify PDD as well
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