Computational Disease Genomics and Networks
My group is gaining insights in to complex neurodevelopmental and neuropsychiatric disorders using functional, integrative and network genomics. We exploit large-scale genetic data sets to identify significant molecular features that can determine which genes contribute to these complex disorders and how. In particular, we identify the complex gene networks whose perturbation underlies the etiopathology of complex multigenic disease.
In order to identify genes whose variants contribute to genetic disease, we exploit large genomics datasets that describe the genomes of hundreds, sometimes thousands, of individuals. Through novel methodologies, we discover statistically-significant functional differences that distinguish the mutations observed in the patient cohort from those observed in an appropriate control cohort. The functional characteristics that differentiate case mutations from control mutations yield insights in to the pathogenic mechanisms underlying the disorder and propose novel, experimentally-tractable hypotheses (see Noh et al., Shaikh et al., Webber et al.)
In particular, we have applied the phenotypic-associations made by disrupting genes in the mouse (“mouse knockouts”) as a novel large-scale functional genomics resource to seed network approaches. In a proof-of-concept publication, we showed how significant biases could be detected among the set of mouse phenotypes associated with those human genes affected by mutations in patients with intellectual disability (Webber et al). We are now extending this approach using integrative genomics to incorporate annotations from gene expression, protein-protein interactions and other resources thereby creating functional linkage networks of relevance to particular disorders.
We focus on rare, dispersed, genetic mutations that each may be observed in only a few individuals. To do this, we must first have a clear understanding of how and where mutations arise in the human genome. In this respect, we have contributed significantly to the understanding of structural variation within the human population (see Webber et al., Nguyen et al. and Mills et al.) identifying distinct regions of the human genome that are prone to particular mutational and selectional biases.
Although our approaches are applicable generally to human genetic disease, we are particularly interested in neurodevelopmental disorders, such as intellectual disability, developmental delay, autism and ADHD, along with neuropsychiatric disorders such as biopolar disorder and schizophrenia. The group is a major contributor to the FP7-funded GENCODYS (Genetic and Epigenetic Networks in Cognitive Dysfunction) project (http://www.gencodys.eu/). Our network and integrative genomics technologies lie at the heart of the Omics interpretation package within the IMI's StemBANCC project to create a bank of patient-derived induced pluripotent stem cell lines to understand and develop treatment assays for a range of challenging disorders (Webber: Informatics work package leader). Our research is collaborative by nature and we welcome inquiries.