Document Type
Article
Source Publication Title
Brain Communications
DOI
http://dx.doi.org/10.1093/braincomms/fcaa065
Abstract
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. [This is a published version of an article published by Oxford University Press in Brain Communications on 11 June 2020, available online: https://doi.org/10.1093/braincomms/fcaa065.This article is available under the Creative Commons CC-BY-NC license (https://creativecommons.org/licenses/) and permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.]
Disciplines
Mathematics | Physical Sciences and Mathematics
Publication Date
6-11-2020
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Maia, Pedro D.; Pandya, Sneha; Freeze, Benjamin; Torok, Justin; Gupta, Ajay; Zeighami, Yashar; and Raj, Ashish, "Origins of atrophy in Parkinson linked to early onset and local transcription patterns" (2020). Mathematics Faculty Publications. 45.
https://mavmatrix.uta.edu/math_facpubs/45