Predictive model of spread of Parkinson's pathology using network diffusion

Abstract

Growing evidence suggests that a "prion-like" mechanism underlies the pathogenesis of many neurodegenerative disorders, including Parkinson's disease (PD). We extend and tailor previously developed quantitative and predictive network diffusion model (NDM) to PD, by specifically modeling the trans-neuronal spread of alpha-synuclein outward from the substantia nigra (SN). The model demonstrated the spatial and temporal patterns of PD from neuropathological and neuroimaging studies and was statistically validated using MRI deformation of 232 Parkinson's patients. After repeated seeding simulations, the SN was found to be the most likely seed region, supporting its unique lynchpin role in Parkinson's pathology spread. Other alternative spread models were also evaluated for comparison, specifically, random spread and distance-based spread; the latter tests for Braak's original caudorostral transmission theory. We showed that the distance-based spread model is not as well supported as the connectivity-based model. Intriguingly, the temporal sequencing of affected regions predicted by the model was in close agreement with Braak stages III-VI, providing what we consider a "computational Braak" staging system. Finally, we investigated whether the regional expression patterns of implicated genes contribute to regional atrophy. Despite robust evidence for genetic factors in PD pathogenesis, NDM outperformed regional genetic expression predictors, suggesting that network processes are far stronger mediators of regional vulnerability than innate or cell-autonomous factors. This is the first finding yet of the ramification of prion-like pathology propagation in Parkinson's, as gleaned

Network diffusion modeling predicts neurodegeneration in traumatic brain injury

“…The NDM framework was also recently used for capturing the spatiotemporal progression of Parkinson's disease. 9,11 These studies revealed that the substantia nigra was the most likely seed region, highlighting its role as one of the most atrophied and Lewy-body-rich regions in Parkinson's disease. Another interesting finding was that the temporal sequencing of the regions predicted by the NDM was in close correspondence with the Braak's Lewy-bodybased staging scheme.…”

“…The present study employed a model of spread of pathology via brain networks based on the network diffusion model (NDM) . A growing number of studies have utilized NDM as a means to model the progression of neurodegenerative pathology on brain networks . Using longitudinal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, Torok and colleagues (2018) showed that NDM and an inference optimization algorithm can successfully infer the regions of disease initiation (referred as seed regions) from which Alzheimer’s disease or Mild Cognitive Impairment tau pathology most likely originated.…”

“…Our recent study demonstrated that the spread of mutant huntingtin protein, via the human brain connectome, accurately predicted the cortico‐striatal spatial pattern of degeneration in patients with Huntington’s disease. The NDM framework was also recently used for capturing the spatiotemporal progression of Parkinson’s disease . These studies revealed that the substantia nigra was the most likely seed region, highlighting its role as one of the most atrophied and Lewy‐body‐rich regions in Parkinson’s disease.…”

“…8,12 A growing number of studies have utilized NDM as a means to model the progression of neurodegenerative pathology on brain networks. [9][10][11][12][13][14][15] Using longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, Torok and colleagues (2018) 15 showed that NDM and an inference optimization algorithm can successfully infer the regions of disease initiation (referred as seed regions) from which Alzheimer's disease or Mild Cognitive Impairment tau pathology most likely originated. Our recent study 12 demonstrated that the spread of mutant huntingtin protein, via the human brain connectome, accurately predicted the cortico-striatal spatial pattern of degeneration in patients with Huntington's disease.…”

Regional transcriptional architecture of Parkinson’s disease pathogenesis and network spread

“…Multiple lines of evidence have suggested that pathology propagates from a small number of early disease sites along neural connectivity pathways (Desplats et al, 2009;Luk et al, 2012), ultimately affecting most of the brain. Previous work using network diffusion modelling (NDM) has shown that this process can be described by considering the spread of pathology as a diffusion process on the structural connectome (Raj et al, 2012;Pandya et al, 2019), with grey matter atrophy serving as a measure of local pathology. By seeding NDM pathology at every possible brain region, and comparing NDM predictions of atrophy with the true atrophy map, the regional origin of pathology can be inferred (Torok et al, 2018;Pandya et al, 2019).…”