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J Biomed Inform. 2016 Oct;63:366-378. doi: 10.1016/j.jbi.2016.08.008. Epub 2016 Aug 10.

A model-driven methodology for exploring complex disease comorbidities applied to autism spectrum disorder and inflammatory bowel disease.

Author information

1
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Information Systems, University of Haifa, Haifa, Israel. Electronic address: judith_somekh@hms.harvard.edu.
2
Department of Information Systems, University of Haifa, Haifa, Israel.
3
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA; Department of Life Sciences, Ben Gurion University of the Negev, Beer-Sheva, Israel.
4
Department of Genetics, Harvard Medical School, Boston, MA, USA; Division of Genetics, Brigham and Women's Hospital, Boston, MA, USA; Howard Hughes Medical Institute, Boston, MA, USA.
5
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
6
Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, Israel.
7
Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
8
Computer Science Institute, Brandenburg University of Technology, Cottbus, Germany.
9
Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA.

Abstract

We propose a model-driven methodology aimed to shed light on complex disorders. Our approach enables exploring shared etiologies of comorbid diseases at the molecular pathway level. The method, Comparative Comorbidities Simulation (CCS), uses stochastic Petri net simulation for examining the phenotypic effects of perturbation of a network known to be involved in comorbidities to predict new roles for mutations in comorbid conditions. To demonstrate the utility of our novel methodology, we investigated the molecular convergence of autism spectrum disorder (ASD) and inflammatory bowel disease (IBD) on the autophagy pathway. In addition to validation by domain experts, we used formal analyses to demonstrate the model's self-consistency. We then used CCS to compare the effects of loss of function (LoF) mutations previously implicated in either ASD or IBD on the autophagy pathway. CCS identified similar dynamic consequences of these mutations in the autophagy pathway. Our method suggests that two LoF mutations previously implicated in IBD may contribute to ASD, and one ASD-implicated LoF mutation may play a role in IBD. Future targeted genomic or functional studies could be designed to directly test these predictions.

KEYWORDS:

ASD; Autism; Autophagy; IBD; Modeling; Petri nets

PMID:
27522000
PMCID:
PMC5155638
DOI:
10.1016/j.jbi.2016.08.008
[Indexed for MEDLINE]
Free PMC Article

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