Biomarkers may help predict which Parkinson’s disease patients will suffer significant cognitive deficits within the first three years of their diagnosis, according to a study by Daniel Weintraub from the Perelman School of Medicine at the University of Pennsylvania and colleagues.
The researchers conducted an international, prospective study of 423 newly diagnosed and untreated Parkinson’s disease patients who showed no signs of cognitive impairment at the time of their enrollment in 2010. Three years later, between 15% and 38% of these participants had developed cognitive impairment. The authors conducted brain scans, genetic tests and analyses of cerebrospinal fluid (CSF) and found that this cognitive decline correlated with biomarkers. Brain scans identified dopamine deficiency and decreased brain volume or thickness as biomarkers. The researchers also found an association with the presence in CSF of beta-amyloid protein, a marker of Alzheimer’s disease, and with single nucleotide polymorphisms in the genes COMT and BDNF that had previously been associated with cognitive impairment.
The study’s participants were mostly male, white and highly educated, limiting the application of these findings to other groups. Nonetheless, future validation of these biomarkers could help with clinical trial design for early therapies that may improve cognitive outcomes. Longer follow up of this cohort will also reveal whether genetic risks are important in later-onset or more advanced cognitive dysfunction in Parkinson’s disease.
Weintraub summarises: “Cognitive impairment in de novo Parkinson's disease increases in frequency 50-200% in the first several years of disease depending on the definition used, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer's disease amyloid plaque pathology, and a mix of genetic factors.”
Abstract
Objectives: To assess the neurobiological substrate of initial cognitive decline in Parkinson’s disease (PD) to inform patient management, clinical trial design, and development of treatments.
Methods: We longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models.
Results: By year 3, cognitive impairment was diagnosed in 15–38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer’s disease Aβ amyloid pathology (lower CSF Aβ 1–42); and (4) genes (COMT val/val and BDNF val/val genotypes).
Conclusions: Cognitive impairment in PD increases in frequency 50–200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer’s disease plaque pathology, and genetic factors.
Authors
Chelsea Caspell-Garcia, Tanya Simuni, Duygu Tosun-Turgut, I-Wei Wu, Yu Zhang, Mike Nalls, Andrew Singleton, Leslie A Shaw, Ju-Hee Kang, John Q Trojanowski, Andrew Siderowf, Christopher Coffey, Shirley Lasch, Dag Aarsland, David Burn, Lana M Chahine, Alberto J Espay, Eric D Foster, Keith A Hawkins, Irene Litvan, Irene Richard, Daniel Weintraub
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[link url="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0175674"]PLOS One abstract[/link]