Integrative Network-based Association Studies: Leveraging cell regulatory models in the post-GWAS era

Andrea Califano,Trey Ideker,Eric Schadt,Stephen Friend,Atul Butte

doi:10.1038/npre.2011.5732.1

Abstract

AbstractAfter completion of a number of large scale Genome-Wide Association Studies (GWAS), there is still a significant amount of trait and disease variance that cannot be explained by existing genetic variability. This review introduces new, Integrative Network-based Association Study (INAS) approaches that aim to minimize the impact from multiple hypothesis testing statistics, thus allowing the identification of rare variants/alterations and epistatic interactions. In particular we discuss methods that rely on the de novo computational, experimental, and integrative dissection of context specific molecular interaction networks (or interactomes, for short). We provide several examples of how these approaches may be used to tackle discovery of genetic variants and somatic alterations causally related to the presentation of specific traits and diseases. We also discuss how more complex systems, including a variety of non-cell-autonomous traits and diseases will require new multicellular networks that explicitly represent short distance paracrine and long distance endocrine interactions.

Highlights

Over the last ten years, the genome wide study of both heritable and somatic human variability has gone from a theoretical concept to a broadly implemented, practical reality, covering the entire spectrum of human diseases: from cancer to obesity to neurodegenerative disorders
We explore current advances in Pathway-Wide Association Study (PWAS) and Integrative Network-based Association Study (INAS) research, the natural corollaries of a regulatory-network-oriented view of traits and disease, and future directions that are being pursued within the emerging community of Systems Genetics
Computational methods for reverse-engineering cellular networks were first developed for the study of prokaryotes and lower eukaryotes[45,46,47] and have more recently become highly successful in reconstructing the transcriptional[32], posttranslational, post-transcriptional[50], metabolic[51], and protein-complex[15] logic of human cells, as well as of their dependence on the genetic information encoded in the DNA molecule, paving the road to the regulatory network based study of human disease

Summary

Introduction

Over the last ten years, the genome wide study of both heritable and somatic human variability has gone from a theoretical concept to a broadly implemented, practical reality, covering the entire spectrum of human diseases: from cancer to obesity to neurodegenerative disorders. Adding yet another level of complexity, causal dependencies between the genetic, regulatory, and functional layers provide insight into the mechanisms by which rare germline allele variants and somatic alterations may impact the activity of entire constellations of transcription factors, which in turn regulate thousands of genes , see Fig. 2.

Results

Conclusion