Computational modelling of pathogenic protein spread in neurodegenerative diseases

Abstract

Pathogenic protein accumulation and spread are fundamental principles of neurodegenerative diseases and ultimately account for the atrophy patterns that distinguish these diseases clinically. However, the biological mechanisms that link pathogenic proteins to specific neural network damage patterns have not been defined. We developed computational models for mechanisms of pathogenic protein accumulation, spread and toxic effects in an artificial neural network of cortical columns. By varying simulation parameters we assessed the effects of modelled mechanisms on network breakdown patterns. Our findings suggest that patterns of network breakdown and the convergence of patterns follow rules determined by particular protein parameters. These rules can account for empirical data on pathogenic protein spread in neural networks. This work provides a basis for understanding the effects of pathogenic proteins on neural circuits and predicting progression of neurodegeneration.

Mathematical Biology Models of Parkinson's Disease

“…Authors showed that origination of seed and diffusive spread were crucial in determining pathogenic propagation patterns. 68 Yau and coworkers 69 studied cortical thinning in PD patients and showed that the atrophy pattern correlated with neuronal connectivity to a "disease reservoir," adding support to the Braak hypothesis. Almost all of these models are agnostic with respect to the pathologic protein they describe.…”

“…Transport of misfolded proteins was modeled as axonal active transport (anterograde and retrograde), trans‐synaptic transport, and passive diffusion. Authors showed that origination of seed and diffusive spread were crucial in determining pathogenic propagation patterns . Yau and coworkers studied cortical thinning in PD patients and showed that the atrophy pattern correlated with neuronal connectivity to a “disease reservoir,” adding support to the Braak hypothesis.…”

Exploring the toxic effects and mechanism of methoxylated polybrominated diphenyl ethers (MeO‐PBDEs) on thyroxine‐binding globulin (TBG): Synergy between spectroscopic and computations

“…Based on the root mean square fluctuation (RMSF) of free TBG, the fluctuation of amino acid residues in protein after the binding with ligand was further analyzed. [43] After the binding of MeO-PBDEs to TBG, most of the amino acid residues did not fluctuate obviously and were relatively stable. However, the amino acid residues (Leu246, Leu248, Asn273, Arg31, Arg378, and Leu37) fluctuate greatly (Figure 8c).…”

Frontotemporal Dementia: A Clinical Review

“…This idea has received some support from computational modeling and human functional neuroimaging studies. 38,39 However, individual variation and convergence of phenotypes as disease evolves greatly complicate the picture. Moreover, the closeness , and clinical features (filled oblongs, top), which varies across the FTD spectrum (see text).…”