Epistasis Blog

From the Artificial Intelligence Innovation Lab at Cedars-Sinai Medical Center (www.epistasis.org)

Saturday, August 15, 2009

Biodefense Bioinformatics

My NIH/NIAID R01 (AI59694) that supports our development of algorithms and software for detecting and characterizing gene-gene interactions has been renewed for four years of funding. The abstract and specific aims are below.

Abstract

Infectious bioterrorism agents such as smallpox and anthrax represent a critical public health concern. Important goals of biodefense research include the development of predictors of pathogenicity of bioterrorism agents for rapid response and the prediction of clinical outcomes such as adverse events following vaccination. Our success in these biodefense endeavors will depend critically on the bioinformatics methods and software that are available for making sense of high-dimensional data generated by technologies such as DNA microarrays and mass spectrometry. The goal of this research program is to continue the development, evaluation, distribution and support of our successful open-source Multifactor Dimensionality Reduction (MDR) software package for identifying combinations of genetic and environmental predictors of clinically important biodefense outcomes. We will first evaluate new methods from our research group and those that have been proposed by other research groups and assess the best approaches for inclusion in new versions of the MDR software (AIM 1). The inclusion of new methods such as stochastic search algorithms for genome-wide analysis and linear models for continuous endpoints will ensure that the MDR software stays on the cutting edge. Second, we propose to develop a web server that biodefense researchers can use as a source of expert knowledge in the form of gene weights that are generated from biochemical pathways, Gene Ontology (GO), chromosomal location and protein-protein interactions, for example (AIM 2). Expert knowledge files generated by the web server will be used by the MDR software to prioritize single nucleotide polymorphisms (SNPs) for interaction analysis in genome-wide association studies or GWAS. These additions will ensure that MDR is ready for application to GWAS that are now commonplace. We will then apply these methods to GWAS data from an ongoing study of adverse events following vaccination for smallpox (AIM 3). Finally, we will identify opportunities to address other important bioterrorism research questions with our software that are consistent with the research objectives of the NIAID/NIH (AIM 4). All bioinformatics methods and tools will be provided in a timely manner for free as open-source software.

AIM 1. Develop, extend, evaluate, distribute and support the open-source Multifactor Dimensionality Reduction (MDR) software package for the identification, characterization and interpretation of gene-gene interactions that are associated with discrete clinical outcomes such as adverse events following vaccination for smallpox. We propose in the next phase of this biodefense research program to extend, improve and update the MDR software package by adding new MDR-related algorithms from our research group and from other research groups. We will evaluate newly developed algorithms and then assess each for inclusion in a new version of the MDR software package. This will ensure the MDR software stays on the cutting edge and is ready for genome-wide genetic analysis.

AIM 2. Develop and make available a web server for weighting SNPs and genes using expert knowledge in the form of biochemical pathways, Gene Ontology (GO), chromosomal location and protein-protein interactions for use by the MDR software to prioritize SNPs for interaction analysis in genome-wide association studies (GWAS). This new resource will provide biodefense researchers an easy to use web interface for selecting a source of expert knowledge (e.g. GO) and the appropriate weights for each gene that can then be loaded in MDR and used to prioritize SNPs for interaction analysis.

AIM 3. Apply MDR to a genome-wide association study (GWAS) of adverse events following smallpox vaccination. We will apply these software packages and methods to a GWAS of adverse events following vaccination for smallpox that includes approximately 500,000 SNPs measured using the Illumina BeadArray platform in a detection sample of 103 volunteers and a replication sample of 60 volunteers that are part of an ongoing NIAID/NIH-sponsored trial to evaluate the Aventis Pasteur Smallpox Vaccine (APSV).

AIM 4. Explore other important biodefense applications of MDR. We will extend the range of MDR applications by applying these methods to other problems such as the prediction of pathogenicity of different Variola virus isolates, the prediction of metabolic features of bacteria using DNA sequence information and the prediction of human immune response endpoints. These new applications will play an important role in the refinement of our methods and software to ensure they are of general use to the biodefense research community and the broader biomedical research community.

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