A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma.

@article{Sharma2015ADM,
  title={A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma.},
  author={Amitabh Sharma and J{\"o}rg Menche and C. Chris Huang and Tatiana Ort and Xiaobo Zhou and Maksim Kitsak and Nidhi Sahni and Derek M Thibault and Linh Voung and Feng Guo and Susan Dina Ghiassian and Natali Gulbahce and Fr{\'e}d{\'e}ric Baribaud and Joel E. Tocker and Radu Dobrin and Elliot S. Barnathan and Hao Liu and Reynold A. Panettieri and Kelan G Tantisira and Weiliang Qiu and Benjamin A. Raby and Edwin K. Silverman and Marc Vidal and Scott T. Weiss and A L Barabasi},
  journal={Human molecular genetics},
  year={2015},
  volume={24 11},
  pages={
          3005-20
        }
}
Recent advances in genetics have spurred rapid progress towards the systematic identification of genes involved in complex diseases. Still, the detailed understanding of the molecular and physiological mechanisms through which these genes affect disease phenotypes remains a major challenge. Here, we identify the asthma disease module, i.e. the local neighborhood of the interactome whose perturbation is associated with asthma, and validate it for functional and pathophysiological relevance… 

Figures and Tables from this paper

Discovering the genes mediating the interactions between chronic respiratory diseases in the human interactome

TLDR
Flow Centrality is introduced, a network-based approach to identify the genes mediating the interaction between two diseases in a protein-protein interaction network and predicts promising gene candidates for further study of disease-disease interactions.

A systems genomics approach to uncover patient-specific pathogenic pathways and proteins in a complex disease

TLDR
A novel precision medicine workflow designed to identify the exact mechanisms of how SNPs affect cellular regulatory networks, and how SNP co-occurrences contribute to disease pathogenesis in ulcerative colitis (UC).

Integration of Molecular Interactome and Targeted Interaction Analysis to Identify a COPD Disease Network Module

TLDR
This work provides a framework that integrates the existing human interactome information with experimental protein-protein interaction data for FAM13A, one of the most highly associated genetic loci to COPD, to find a more comprehensive disease network module.

Recent advances in network medicine: From disease mechanisms to new treatment strategies

TLDR
Network medicine offers a framework in which the complexity of different aspects of multiple sclerosis can be explored in an integrative fashion, which can ultimately provide insights about disease mechanisms and treatment.

Network-based modeling of drug effects on disease module in systemic sclerosis

TLDR
The results show that network-based drug-disease proximity offers a novel perspective into a drug’s therapeutic effect in the SSc disease module, and could be applied to drug combinations or drug repositioning, and be helpful guiding clinical trial design and subgroup analysis.

Interactome-transcriptome analysis discovers signatures complementary to GWAS Loci of Type 2 Diabetes

TLDR
A tissue-specific interactome (T2Di) was constructed to explain the multi-layered regulatory pathways in T2D and revealed a novel locus near a well-established GWAS loci AChE, in which SRRT interacts with JAZF1, a T1D-GWAS gene implicated in pancreatic function.

A novel network approach reveals tissue-specific cellular modulators of the immune-fibrotic axis in systemic sclerosis

TLDR
A novel computational method is developed, which allowed for the first time, identification of a disease-associated signature across multiple tissues and organs in systemic sclerosis, and it is found that genes modulated by immunosuppressive treatment occupy privileged positions in the skin-specific network.

Integrative network analysis interweaves the missing links in cardiomyopathy diseasome

Cardiomyopathies are progressive disease conditions that give rise to an abnormal heart phenotype and are a leading cause of heart failures in the general population. These are complex diseases that

The periphery and the core properties explain the omnigenic model in the human interactome

TLDR
A flower model is proposed to explain the organization of genes in the human interactome, with core genes of different diseases as the petals and the peripheral genes as the stem, and it is shown that this network model is an important step towards finding novel drug targets and improving disease classification.
...

References

SHOWING 1-10 OF 70 REFERENCES

A protein interaction network associated with asthma.

A functional and regulatory map of asthma.

TLDR
A gene expression compendium from five publicly available mouse microarray datasets and a gene knowledge base of 4,305 gene annotation sets is generated, generating a high-level map of the functional themes that characterize animal models of asthma, dominated by innate and adaptive immune response.

The human disease network

TLDR
It is found that essential human genes are likely to encode hub proteins and are expressed widely in most tissues, suggesting that disease genes also would play a central role in the human interactome, and that diseases caused by somatic mutations should not be peripheral.

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

TLDR
Results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.

Hubs in biological interaction networks exhibit low changes in expression in experimental asthma

TLDR
This analysis suggests that a combination of differential gene expression plus topological characteristics of the interaction network provides enhanced understanding of the biology in the authors' model of experimental asthma.

Walking the interactome for prioritization of candidate disease genes.

Variations in DNA elucidate molecular networks that cause disease

TLDR
Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome.

Network-based global inference of human disease genes

TLDR
A tool named CIPHER is developed to predict and prioritize disease genes, and it is shown that the global concordance between the human protein network and the phenotype network reliably predicts disease genes.

Network medicine: a network-based approach to human disease

TLDR
Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.

Gene prioritization through genomic data fusion

TLDR
A bioinformatics approach, together with a freely accessible, interactive and flexible software termed Endeavour, to prioritize candidate genes underlying biological processes or diseases, based on their similarity to known genes involved in these phenomena, offers an alternative integrative method for gene discovery.
...