Global fitting and parameter identifiability for amyloid-β aggregation with competing pathways

Pratip Rana, Priyankar Bose, Ashwin Vaidya, Vijay Rangachari, Preetam Ghosh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aggregation of the amyloid-\beta(A\beta) protein has been implicated in Alzheimer's disease (AD). Since, low molecular weight A\beta aggregates are hypothesized to serve as the primary toxic species in AD pathogenesis, significant research has been conducted to understand the mechanistic details of the aggregation process. We previously demonstrated that heterotypic interactions between A\beta and fatty acids (FAs) can lead to competing pathways of A\beta aggregation, termed as the off-pathway; this off-pathway kinetics can also be modulated by FA concentrations as captured by mass action models. We employed ensemble kinetics simulations which uses a system of Ordinary Differential Equations to model the competing on-and off-pathways of A\beta aggregation that were trained and validated by biophysical experiments. However, these models had several rate constants, treated as free parameters to be estimated, which resulted in over-fitting of the model. Hence, in this paper, we present a global fitting based method to accurately identify the rate constants involved in the complex competing pathway model of A\beta aggregation. We additionally employ detailed parameter identifiability tests for uncertainty quantification using the profile likelihood method. Since, the emergence of off-or on-pathway aggregates are typically controlled by a narrow set of rate constants, it is imperative to rigorously identify the proper rate constants involved in these pathways. These rate constants serve as a basis for future experiments on modulating the aggregation pathways to populate a particular possibly less toxic oligomeric species. The obtained rate constants also motivate new biophysical experiments to better understand the mechanisms of amyloid aggregation in other neurodegenerative diseases.

Original languageEnglish
Title of host publicationProceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages73-78
Number of pages6
ISBN (Electronic)9781728195742
DOIs
StatePublished - Oct 2020
Event20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020 - Virtual, Cincinnati, United States
Duration: 26 Oct 202028 Oct 2020

Publication series

NameProceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020

Conference

Conference20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020
CountryUnited States
CityVirtual, Cincinnati
Period26/10/2028/10/20

Keywords

  • global fitting
  • optimization
  • profile likelihood
  • protein aggregation
  • systems biology

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