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Origins of atrophy in Parkinson linked to early onset and local transcription patterns

There is enormous clinical value in inferring the brain regions initially atrophied in Parkinson disease for individual patients and understanding its relationship with clinical and genetic risk factors. The aim of this study is to leverage a new seed-inference algorithm demonstrated for Alzheimer’s...

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Autores principales: Maia, Pedro D, Pandya, Sneha, Freeze, Benjamin, Torok, Justin, Gupta, Ajay, Zeighami, Yashar, Raj, Ashish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472895/
https://www.ncbi.nlm.nih.gov/pubmed/32954322
http://dx.doi.org/10.1093/braincomms/fcaa065
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author Maia, Pedro D
Pandya, Sneha
Freeze, Benjamin
Torok, Justin
Gupta, Ajay
Zeighami, Yashar
Raj, Ashish
author_facet Maia, Pedro D
Pandya, Sneha
Freeze, Benjamin
Torok, Justin
Gupta, Ajay
Zeighami, Yashar
Raj, Ashish
author_sort Maia, Pedro D
collection PubMed
description There is enormous clinical value in inferring the brain regions initially atrophied in Parkinson disease for individual patients and understanding its relationship with clinical and genetic risk factors. The aim of this study is to leverage a new seed-inference algorithm demonstrated for Alzheimer’s disease to the Parkinsonian context and to cluster patients in meaningful subgroups based on these incipient atrophy patterns. Instead of testing brain regions separately as the likely initiation site for each patient, we solve an L1-penalized optimization problem that can return a more predictive heterogeneous, multi-locus seed patterns. A cluster analysis of the individual seed patterns reveals two distinct subgroups (S1 versus S2). The S1 subgroup is characterized by the involvement of the brainstem and ventral nuclei, and S2 by cortex and striatum. Post hoc analysis in features not included in the clustering shows significant differences between subgroups regarding age of onset and local transcriptional patterns of Parkinson-related genes. Top genes associated with regional microglial abundance are strongly associated with subgroup S1 but not with S2. Our results suggest two distinct aetiological mechanisms operative in Parkinson disease. The interplay between immune-related genes, lysosomal genes, microglial abundance and atrophy initiation sites may explain why the age of onset for patients in S1 is on average 4.5 years later than for those in S2. We highlight and compare the most prominently affected brain regions for both subgroups. Altogether, our findings may improve current screening strategies for early Parkinson onsetters.
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spelling pubmed-74728952020-09-17 Origins of atrophy in Parkinson linked to early onset and local transcription patterns Maia, Pedro D Pandya, Sneha Freeze, Benjamin Torok, Justin Gupta, Ajay Zeighami, Yashar Raj, Ashish Brain Commun Original Article There is enormous clinical value in inferring the brain regions initially atrophied in Parkinson disease for individual patients and understanding its relationship with clinical and genetic risk factors. The aim of this study is to leverage a new seed-inference algorithm demonstrated for Alzheimer’s disease to the Parkinsonian context and to cluster patients in meaningful subgroups based on these incipient atrophy patterns. Instead of testing brain regions separately as the likely initiation site for each patient, we solve an L1-penalized optimization problem that can return a more predictive heterogeneous, multi-locus seed patterns. A cluster analysis of the individual seed patterns reveals two distinct subgroups (S1 versus S2). The S1 subgroup is characterized by the involvement of the brainstem and ventral nuclei, and S2 by cortex and striatum. Post hoc analysis in features not included in the clustering shows significant differences between subgroups regarding age of onset and local transcriptional patterns of Parkinson-related genes. Top genes associated with regional microglial abundance are strongly associated with subgroup S1 but not with S2. Our results suggest two distinct aetiological mechanisms operative in Parkinson disease. The interplay between immune-related genes, lysosomal genes, microglial abundance and atrophy initiation sites may explain why the age of onset for patients in S1 is on average 4.5 years later than for those in S2. We highlight and compare the most prominently affected brain regions for both subgroups. Altogether, our findings may improve current screening strategies for early Parkinson onsetters. Oxford University Press 2020-06-11 /pmc/articles/PMC7472895/ /pubmed/32954322 http://dx.doi.org/10.1093/braincomms/fcaa065 Text en © The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Article
Maia, Pedro D
Pandya, Sneha
Freeze, Benjamin
Torok, Justin
Gupta, Ajay
Zeighami, Yashar
Raj, Ashish
Origins of atrophy in Parkinson linked to early onset and local transcription patterns
title Origins of atrophy in Parkinson linked to early onset and local transcription patterns
title_full Origins of atrophy in Parkinson linked to early onset and local transcription patterns
title_fullStr Origins of atrophy in Parkinson linked to early onset and local transcription patterns
title_full_unstemmed Origins of atrophy in Parkinson linked to early onset and local transcription patterns
title_short Origins of atrophy in Parkinson linked to early onset and local transcription patterns
title_sort origins of atrophy in parkinson linked to early onset and local transcription patterns
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472895/
https://www.ncbi.nlm.nih.gov/pubmed/32954322
http://dx.doi.org/10.1093/braincomms/fcaa065
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