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Biomarkers That May Predict Cognitive Impairment in Parkinson’s Discovered

Summary: Researchers have identified biomarkers that can help predict which patients with Parkinson’s disease will suffer from significant cognitive deficits within three years of diagnosis.

Source: University of Pennsylvania.

New biomarkers identified by a research team in the Perelman School of Medicine at the University of Pennsylvania could help predict which Parkinson’s disease patients will suffer significant cognitive deficits within the first three years of their diagnosis. The results of the analysis from the international Parkinson’s Progression Markers Initiative (PPMI) are published this week in the open-access journal PLoS ONE.

“The results of this study improve our understanding of the changes in brain function that occur with initial cognitive changes in early Parkinson’s disease,” said Daniel Weintraub, MD, a professor of Psychiatry and lead author. “This could eventually lead to improved clinical care and development of therapies to treat this symptom.”

Dr. Weintraub led the team that analyzed data and samples from 423 newly diagnosed and untreated Parkinson’s disease patients who showed no signs of dementia at the time of their enrollment in PPMI, a landmark observational study launched in 2010 and sponsored by The Michael J. Fox Foundation for Parkinson’s Research.

Three years after enrollment, between 15 and 38 percent of these participants had developed cognitive impairment. The authors assessed brain scans, genetic tests and analyses of cerebrospinal fluid (CSF) and found cognitive decline correlated with several biomarkers: changes in the dopamine system, global brain atrophy, particular genetic mutations, and markers of Alzheimer’s disease.

This is the first investigation to find each of these biomarkers, a mix of baseline and longitudinal biomarkers, contributes independently to cognitive decline in early Parkinson’s disease. These results may improve the ability of clinicians to predict future cognitive performance in Parkinson’s disease patients — an important part of patient education and clinical management — and may guide efforts to develop new cognition-enhancing treatments for Parkinson’s disease.

Other Penn co-investigators include Leslie Shaw, PhD, a professor of Pathology and Laboratory Medicine; John Trojanowski, MD, PhD, professor of Geriatric Medicine and Gerontology; and Lama Chahine, MD, an assistant professor of Neurology.

In this study, researchers found an association between cognitive decline and (i) dopamine deficiency and (ii) decreased brain volume or thickness observed in brain scans; (iii) lower levels in CSF of beta-amyloid protein, a marker of Alzheimer’s disease, and (iv) single nucleotide polymorphisms in the genes COMT and BDNF, which previously had been associated with cognitive impairment.

Image shows a brain.

This is the first investigation to find each of these biomarkers, a mix of baseline and longitudinal biomarkers, contributes independently to cognitive decline in early Parkinson’s disease. NeuroscienceNews.com image is for illustrative purposes only.

This cohort of PPMI participants are 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 the identified risks are important in later-onset or more advanced cognitive dysfunction in Parkinson’s disease.

As many as one million Americans and more than five million people worldwide are living with Parkinson’s disease. An additional 60,000 Americans are diagnosed with Parkinson’s disease each year, and this number does not reflect the thousands of cases that go undetected.

About this neuroscience research article

Funding: The Parkinson’s Progression Markers Initiative is a public-private partnership funded by The Michael J. Fox Foundation and 20 industry partners. This analysis was also funded in part by the National Institute of Neurological Disorders and Stroke, part of the National Institutes for Health (P50 NS053488).

Source: Queen Muse – University of Pennsylvania
Image Source: NeuroscienceNews.com image is credited to Gil Costa (Champalimaud Centre for the Unknown).
Original Research: Full open access research for “Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease” by 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, the Parkinson’s Progression Markers Initiative (PPMI) in PLOS ONE. Published online May 17 2017 doi:10.1371/journal.pone.0175674

Cite This NeuroscienceNews.com Article
University of Pennsylvania “Biomarkers That May Predict Cognitive Impairment in Parkinson’s Discovered.” NeuroscienceNews. NeuroscienceNews, 17 May 2017.
<http://neurosciencenews.com/cognition-parkinsons-biomarkers-6707/>.
University of Pennsylvania (2017, May 17). Biomarkers That May Predict Cognitive Impairment in Parkinson’s Discovered. NeuroscienceNew. Retrieved May 17, 2017 from http://neurosciencenews.com/cognition-parkinsons-biomarkers-6707/
University of Pennsylvania “Biomarkers That May Predict Cognitive Impairment in Parkinson’s Discovered.” http://neurosciencenews.com/cognition-parkinsons-biomarkers-6707/ (accessed May 17, 2017).

Abstract

Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease

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.

“Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease” by 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, the Parkinson’s Progression Markers Initiative (PPMI) in PLOS ONE. Published online May 17 2017 doi:10.1371/journal.pone.0175674

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