Computable cause‐and‐effect models of healthy and Alzheimer's disease states and their mechanistic differential analysis

Kodamullil, Alpha Tom; Younesi, Erfan; Naz, Mufassra; Bagewadi, Shweta; Hofmann‐Apitius, Martin

doi:10.1016/j.jalz.2015.02.006

Cited by 48 publications

(49 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, AD ontology (ADO) has been developed to provide such a reference for AD knowledge domain [593]. ADO was used by Kodamullil and colleagues (2015) to represent scientific findings in a computable, cause-and-effect model of AD pathology, which was designed and coded in Open Biological Expression Language (available at http://openbel.org/) [594]. This model contains causal and correlative relationships between biomolecules, pathways, and clinical readouts and was used for model-guided interpretation of genetic variation data for a comorbidity analysis between AD and type 2 diabetes mellitus.…”

Section: The Emerging Field Of Systems Pharmacology In Alzheimer’s DImentioning

confidence: 99%

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

Hampel

Toschi

Babiloni

et al. 2018

JAD

Self Cite

131

113

View full text Add to dashboard Cite

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an “omics”-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer’s disease (AD). The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group “Alzheimer Precision Medicine” (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development towards breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

show abstract

Section: The Emerging Field Of Systems Pharmacology In Alzheimer’s DImentioning

confidence: 99%

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

Hampel

Toschi

Babiloni

et al. 2018

JAD

Self Cite

131

113

View full text Add to dashboard Cite

show abstract

“…This leads to decrease in Aβ clearance [ 45, 46 ]. This disease mechanism has been described already in detail by Kodamullil et al [ 15 ].…”

Section: Resultsmentioning

confidence: 57%

“…Computational systems models can facilitate this task by gathering both experimental data and published knowledge, standardizing this information, integrating them across various biological scales, and representing this species-specific information in the form of consolidated cause-and-effect digital models. We have already shown the value of such approach for identification of disease-specific pathways in AD as compared to normal bioprocesses in the human brain [ 15 ], and Pappalardo et al built computational model in immune system, which predicts how immune system activates in different conditions [ 16 ]. Motivated by these results, we sought to systematically model and mechanistically compare neuroinflammatory pathways specific to microglia, astrocytes, macrophages, and neurons between human and mouse in the context of AD.…”

Section: Introductionmentioning

confidence: 99%

Of Mice and Men: Comparative Analysis of Neuro-Inflammatory Mechanisms in Human and Mouse Using Cause-and-Effect Models

Kodamullil

Iyappan

Karki

et al. 2017

JAD

Self Cite

View full text Add to dashboard Cite

Perturbance in inflammatory pathways have been identified as one of the major factors which leads to neurodegenerative diseases (NDD). Owing to the limited access of human brain tissues and the immense complexity of the brain, animal models, specifically mouse models, play a key role in advancing the NDD field. However, many of these mouse models fail to reproduce the clinical manifestations and end points of the disease. NDD drugs, which passed the efficacy test in mice, were repeatedly not successful in clinical trials. There are numerous studies which are supporting and opposing the applicability of mouse models in neuroinflammation and NDD. In this paper, we assessed to what extend a mouse can mimic the cellular and molecular interactions in humans at a mechanism level. Based on our mechanistic modeling approach, we investigate the failure of a neuroinflammation targeted drug in the late phases of clinical trials based on the comparative analyses between the two species.

show abstract

“…The extracted information comprises cause-and-effect relationships representing protein-protein interactions, protein inhibitory and activating patterns, protein-complex formation, insights from disease animal model studies, patterns from knockout and gene expression studies, other genetic associations; from gene mapping (fine-mapping) and GWAS meta-analysis studies, and from drug effects; all with high specificity for either AD or PD or both. The vast amount of information extracted was subsequently encoded using the OpenBEL (Open Biological Expression Language) syntax to construct a cause-and-effect computable model [27]. Models were developed separately for human and mouse.…”

Section: Resultsmentioning

confidence: 99%

Systematic Analysis of GWAS Data Reveals Genomic Hotspots for Shared Mechanisms between Neurodegenerative Diseases

Naz¹,

Younesi²,

Hofmann‐Apitius³

2017

J Alzheimers Dis Parkinsonism

Self Cite

View full text Add to dashboard Cite

Computable cause‐and‐effect models of healthy and Alzheimer's disease states and their mechanistic differential analysis

Abstract: The two computable, literature-based models introduced here provide a powerful framework for the generation and validation of rational, testable hypotheses across disease areas.

Cited by 48 publications

References 50 publications

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

Of Mice and Men: Comparative Analysis of Neuro-Inflammatory Mechanisms in Human and Mouse Using Cause-and-Effect Models

Systematic Analysis of GWAS Data Reveals Genomic Hotspots for Shared Mechanisms between Neurodegenerative Diseases

Contact Info

Product

Resources

About