Cohort-specific boolean models highlight different regulatory modules during Parkinson's disease progression.

Bioinformatics; Biological sciences; Computational bioinformatics; Multidisciplinary; Boolean models identify; Parkinson's disease; subtypes; Dysregulated pathways; include dopamine; mitochondrial dysfunction; Subtype-specific models

Abstract :

[en] Parkinson's disease (PD) involves complex molecular interactions and diverse comorbidities. To better understand its molecular mechanisms, we employed systems medicine approaches using the PD map, a detailed repository of PD-related interactions and applied Probabilistic Boolean Networks (PBNs) to capture the stochastic nature of molecular dynamics. By integrating cohort-level and real-world patient data, we modeled PD's subtype-specific pathway deregulations, providing a refined representation of its molecular landscape. Our study identifies key regulatory biomolecules and pathways that vary across PD subtypes, offering insights into the disease's progression and patient stratification. These findings have significant implications for the development of targeted therapeutic interventions.

Disciplines :

Human health sciences: Multidisciplinary, general & others

Author, co-author :

HEMEDAN, Ahmed ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine > Bioinformatics Core > Team Reinhard SCHNEIDER

SATAGOPAM, Venkata ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Clinical and Translational Informatics

SCHNEIDER, Reinhard ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core

OSTASZEWSKI, Marek ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core

External co-authors :

Language :

English

Title :

Cohort-specific boolean models highlight different regulatory modules during Parkinson's disease progression.

Publication date :

18 October 2024

Journal title :

iScience

eISSN :

2589-0042

Publisher :

Elsevier Inc., United States

Volume :

Issue :

Pages :

110956

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://api.elsevier.com/content/article/PII:S2589004224021813?httpAccept=text/xml

Funders :

European Commission Reforming and enhancing the European Research and Innovation system
Horizon 2020
Michael J. Fox Foundation for Parkinson's Research
Horizon 2020 Framework Programme

Funding text :

This work was supported by funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 733100: SYSCID\u2014A systems medicine approach to chronic inflammatory diseases. The authors acknowledge the Parkinson's progression markers Initiative (PPMI) for providing the data used in this research. PPMI, a public-private partnership, is funded by the Michael J. Fox Foundation for Parkinson's Research and funding partners.This work was supported by funding from the European Union\u2019s Horizon 2020 research and innovation program under grant agreement No. 733100 : SYSCID\u2014A systems medicine approach to chronic inflammatory diseases. The authors acknowledge the Parkinson\u2019s progression markers Initiative (PPMI) for providing the data used in this research. PPMI, a public-private partnership, is funded by the Michael J. Fox Foundation for Parkinson\u2019s Research and funding partners .

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since 28 January 2026

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