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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, untrea...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5435130/ https://www.ncbi.nlm.nih.gov/pubmed/28520803 http://dx.doi.org/10.1371/journal.pone.0175674 |
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author | Caspell-Garcia, Chelsea Simuni, Tanya Tosun-Turgut, Duygu Wu, I-Wei Zhang, Yu Nalls, Mike Singleton, Andrew Shaw, Leslie A. Kang, Ju-Hee Trojanowski, John Q. Siderowf, Andrew Coffey, Christopher Lasch, Shirley Aarsland, Dag Burn, David Chahine, Lana M. Espay, Alberto J. Foster, Eric D. Hawkins, Keith A. Litvan, Irene Richard, Irene Weintraub, Daniel |
author_facet | Caspell-Garcia, Chelsea Simuni, Tanya Tosun-Turgut, Duygu Wu, I-Wei Zhang, Yu Nalls, Mike Singleton, Andrew Shaw, Leslie A. Kang, Ju-Hee Trojanowski, John Q. Siderowf, Andrew Coffey, Christopher Lasch, Shirley Aarsland, Dag Burn, David Chahine, Lana M. Espay, Alberto J. Foster, Eric D. Hawkins, Keith A. Litvan, Irene Richard, Irene Weintraub, Daniel |
author_sort | Caspell-Garcia, Chelsea |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5435130 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54351302017-05-26 Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease Caspell-Garcia, Chelsea Simuni, Tanya Tosun-Turgut, Duygu Wu, I-Wei Zhang, Yu Nalls, Mike Singleton, Andrew Shaw, Leslie A. Kang, Ju-Hee Trojanowski, John Q. Siderowf, Andrew Coffey, Christopher Lasch, Shirley Aarsland, Dag Burn, David Chahine, Lana M. Espay, Alberto J. Foster, Eric D. Hawkins, Keith A. Litvan, Irene Richard, Irene Weintraub, Daniel PLoS One Research Article 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. Public Library of Science 2017-05-17 /pmc/articles/PMC5435130/ /pubmed/28520803 http://dx.doi.org/10.1371/journal.pone.0175674 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Caspell-Garcia, Chelsea Simuni, Tanya Tosun-Turgut, Duygu Wu, I-Wei Zhang, Yu Nalls, Mike Singleton, Andrew Shaw, Leslie A. Kang, Ju-Hee Trojanowski, John Q. Siderowf, Andrew Coffey, Christopher Lasch, Shirley Aarsland, Dag Burn, David Chahine, Lana M. Espay, Alberto J. Foster, Eric D. Hawkins, Keith A. Litvan, Irene Richard, Irene Weintraub, Daniel Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease |
title | Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease |
title_full | Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease |
title_fullStr | Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease |
title_full_unstemmed | Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease |
title_short | Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease |
title_sort | multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo parkinson disease |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5435130/ https://www.ncbi.nlm.nih.gov/pubmed/28520803 http://dx.doi.org/10.1371/journal.pone.0175674 |
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