Purpose of Review
Integrative networks combine multiple layers of biological data into a model of how genes work together to carry out cellular processes. Such networks become more valuable as they become more context-specific, for example, by capturing how genes work together in a certain tissue or cell type. We discuss the applications of these networks to the study of human disease.
Once constructed, these networks provide the means to identify broad biological patterns underlying genes associated with complex traits and diseases. We cover the different types of integrative networks that currently exist, and how such networks that encompass multiple biological layers are constructed. We highlight how specificity can be incorporated into the reconstruction of different types of biomolecular interactions between genes, using tissue specificity as a motivating example. We discuss examples of cases where networks have been applied to study human diseases and opportunities for new applications.
Integrative networks with specificity to tissue or other biological features provide new capabilities to researchers engaged in the study of human disease. We expect improved data and algorithms to continue and improve such networks, allowing them to provide more detailed and mechanistic predictions into the context-specific genetic etiology of common diseases.
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This work was supported in part by a grant from the Gordon and Betty Moore Foundation’s Data-Driven Discovery Initiative to CSG (GBMF 4552) and funding from the National Institutes of Health under award U01-TR001263.
Arjun Krishnan declares that he has no conflict of interest. Jaclyn N. Taroni reports grants from the NIH during the conduct of study. Casey S. Greene reports grants from the Gordon and Betty Moore Foundation and the National Institutes of Health during the conduct of the study. He also reports grants from the Cystic Fibrosis Foundation, the National Institutes of Health, the National Science Foundation, the Norris-Cotton Cancer Center, and the American Cancer Society, outside the submitted work.
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This article is part of the Topical collection on Genomics.
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Krishnan, A., Taroni, J.N. & Greene, C.S. Integrative Networks Illuminate Biological Factors Underlying Gene–Disease Associations. Curr Genet Med Rep 4, 155–162 (2016). https://doi.org/10.1007/s40142-016-0102-5
- Systems biology
- Genetic association
- Integrative biology
- Protein–protein interaction networks