SBIR-STTR Award

Rapid advances in biotechnology and clinical studies have produced an information bottleneck in data processing that has hindered application of such critical scientific data for use in medicine and disease diagnosis. Omicia will develop a novel genetics based informatics infrastructure to overcome this bottleneck that can predict the functional outcome of gene mutations and their relationship to human disease by integrating diverse knowledge bases in a consistent and structured manner. Implementation of the technology will reduce the cost and enhance the effectiveness of genetic association studies, population profiling analyses and pharmacogenomic applications, as well as potentially identify novel gene targets for disease. Our technology will mine classification systems for large number of genes and create statistical associations as well as integrate ontologies to allow for reliable inferences about functions of genes and their relation to disease phenotypes. Importantly, the predictive capabilities of the technology will assign functions to orphan genes and genetic markers for which very little functional information is available. The IT system will consist of a classification of genes into families using shared attributes in a number of well-structured domains to create a gene inference system (GIS) by comparing gene ontologies in GO with disease ontologies in MeSH. It will also use the well-annotated HGMD database to infer novel disease-related function to unannotated polymorphisms such as those in dbSNP. These studies are designed to demonstrate the feasibility of the technology so that it can be validated through future genetic association studies in a Phase II SBIR

High-throughput genotyping, expression, and sequencing technologies and the development of increasingly sophisticated methods for predicting gene-disease interactions have given the new field of genomic-based personalized medicine a wealth of data: more, in fact, than can easily be processed and interpreted. Omicia is in the business of developing computational tools and diagnostics in the field of personalized medicine for cardiovascular disease (CVD). As part of that effort we are developing a software infrastructure that uses these abundant data to identify and prioritize candidate genes and their sequence variations for clinical evaluation. The research proposed in this application has three aims. In Phase II, we will enhance and optimize Omicia's Gene Inference System (GIS), prototyped during the SBIR Phase I project. In Phase II we will add additional capabilities to its candidate gene identification methods. This will build upon the Omicia Disease Genes (ODG) ontology built in Phase I, and add pathway and protein-interaction data and include ""top"" candidates from external publicaly-available clinical studies. In Aim 2, we will enhance the ability of GIS to prioritize sequence variations by improving our novel paralogous-gene variation identification algorithm (iDIP) and by integrating existing amino-acid substitution (AAS) methods. By running these algorithms over all known human genes via dbSNP, we expect to identify a list of candidate variations that will be evaluated in Aim 3 including an in vitro experiment. The goal of Aim 3 is to test the gene- and variant-predictive power of GIS and to compare it to other selection methods. The clinical study will be a single-stage case control design to test the ""top"" variant candidates from Aims 1 & 2 and compare the potential association to well-established genetic markers for the risk of myocardial infarction (MI). With approximately 700 cases and 700 matched controls, our association study will be well powered to test our predicted functional markers for MI. The GIS infrastructure is an integral part of the commercial workflow of Omicia, and will form the basis of the product pipeline. As such, it will serve as licensable commercial technology for the company by helping other biotechnology companies to develop their genetic biomarkers for diagnostic and therapeutic developments (theranostics). In addition, any novel variants drawn from this Phase II study will be licensable and exploitable intellectual property, useful both as the basis for future products in our internal pipeline, as well as potentially valuable additions to our patent portfolio. The Phase II goals of enhancing and clinically validating GIS serve three purposes: proving our methodology as applied to CVD and opening the door to applications in other disease areas; showcasing GIS as a key technology for managing complexity in the post-genomic era and providing clinically-relevant insights; and finally, potentially identifying valuable IP in the form of novel genetic markers for MI.

Public Health Relevance:
The outcome of this project will be an evaluated gene inference system (GIS) for identifying gene-disease interactions, with a focus in the area of cardiovascular disease (CVD). This system will be used as part of the Omicia product pipeline, and can also be licensed to third parties. In addition, any novel genetic markers identified as part of the validation study will themselves be valuable additions to the Omicia product and IP portfolio. Omicia's goal is to provide content and analysis tools for molecular diagnostic tests for cardiovascular conditions, with the promise of identifying patients at high risk to enable them to begin preventive care before symptoms appear. Given the prevalence of CVD in the developed world, these products are potentially a great boon to public health, as well as being significant commercial opportunities.

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