Genetic Hotspots: The goal of this Phase 1 SBIR project is to develop and apply new methods to identify genes that harbor genetic variants that affect disease risk. The long-term objective of this work is to identify genes and gene variants that can improve human health by providing greater information about individual susceptibility to disease risk. The hypothesis driving this work is that multiple variants within a single gene may contribute independently to the risk of a single disease. This genetic heterogeneity is known to exist for familial diseases, and is anticipated for complex disorders. When individuals in a study may have one of a number of risk-enhancing alleles, this genetic heterogeneity decreases the power to detect such variants. The proposed work aims to increase the power of genome wide association studies (GWAS) to detect such genetic hotspots by developing new types of gene-based tests of association. Specific Aim 1 is to develop Bayesian regularization strategies that can reliably identify the correct model for a gene: the number of independent disease-linked variants it contains (0 for most genes), and the genotyped marker most highly correlated with each effect. The power of these methods to detect real associations will be compared to traditional SNP-based tests. Specific Aim 2 is to generalize these methods for application to actual, published genotype data sets where personal information has been censored for privacy concerns (such as the SHARe dataset from the Framingham Heart Study), leaving only summary p-values or regression statistics available to the public domain for analysis. Specific Aim 3 is to test the proposed gene-based methods in real data sets. If the proposed work in Phase 1 is successful, the Phase 2 aims will be to increase the computational efficiency, to develop related methods for genetic studies using ultra-high- throughput sequencing (also called Nextgen-sequencing methods) to analyze genetic variation, and to integrate these gene-based tests with pathway-based tests that require gene-specific p- values as input. The proposed methods have the potential to increase the ability to link specific genetic variants with disease risk, a critical step in predicting individual disease risk especially for new complete genome sequence data. In Phase 2 the developed methods will be integrated into the Genome Interpretation System, a commercial workflow software suite developed at Omicia. 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 1 study will be licensable intellectual property, useful both as the basis for future products in our internal pipeline, as well as potentially valuable additions to our patent portfolio. , ,
Public Health Relevance: , Genetic Hotspots: Project Narrative A single gene can have multiple independent variants that all contribute to risk for cardiovascular disease, cancer, or other complex disorders. Current genetic analysis methods focus on individual markers, usually single-nucleotide polymorphisms (SNPs), and are not designed to detect gene-based patterns. This proposal will develop new methods that are able to detect the presence of multiple independent risk-enhancing alleles within a gene, increasing the ability to predict individual risk for disease susceptibility. In Aim3 we will be testing the methods with respect to performance in ""known"" datasets with the focus in the area of cardiovascular disease (CVD). The improved methods will be used as part of the Omicia/s Genome Interpretation System (GIS) product pipeline, and can be licensed to third parties. In addition, any novel genetic markers identified as part of the Aim3 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.
Thesaurus Terms: Affect;Agreement;Alleles;Allelomorphs;Area;Automobile Driving;Biological Function;Biological Process;Biotechnology;Blood Pressure;Blood Pressure, High;Cancers;Cardiovascular;Cardiovascular Body System;Cardiovascular Diseases;Cardiovascular System;Cardiovascular System (All Sites);Caring;Complex;Computer Programs;Computer Software;Data;Data Banks;Data Bases;Data Set;Databank, Electronic;Databanks;Database, Electronic;Databases;Dataset;Diagnostic;Diathesis;Disease;Disease Marker;Disease Susceptibility;Disorder;Drivings, Automobile;Epidemiologic Research;Epidemiologic Studies;Epidemiological Studies;Epidemiology Research;Familial Disease;Family;Framingham Heart Study;Future;Gwas;Gene Variant;Genes;Genetic;Genetic Diversity;Genetic Heterogeneity;Genetic Markers;Genetic Variation;Genetic Analyses;Genome;Genotype;Goals;Health;Human;Human, General;Hypertension;Individual;Inheritance Patterns;Intellectual Property;Investigators;Lead;Left;Legal Patent;Licensing;Link;Malignant Neoplasms;Malignant Tumor;Man (Taxonomy);Man, Modern;Measures;Medicine;Methods;Modeling;Molecular Diagnostic Testing;Network Analysis;Organ System, Cardiovascular;Patents;Pathway Analysis;Pathway Interactions;Patients;Pattern;Pb Element;Performance;Phase;Policies;Polymorphism, Single Base;Population;Population Sizes;Predisposition;Prevalence;Prevention;Preventive;Privacy;Proxy;Public Domains;Public Health;Publishing;Reporting;Research Design;Research Personnel;Researchers;Risk;Running;Sbir;Sbirs (R43/44);Snp;Snps;Science Of Medicine;Science Of Statistics;Simulate;Single Nucleotide Polymorphism;Small Business Innovation Research;Small Business Innovation Research Grant;Software;Statistics;Study Type;Susceptibility;Symptoms;System;System, Loinc Axis 4;Technology;Testing;Thumb;Thumb Structure;Variant;Variation;Variation (Genetics);Vascular Hypertensive Disease;Vascular Hypertensive Disorder;Vascular, Heart;Work;Allelic Variant;Base;Biomarker;Cardiovascular Disease Risk;Cardiovascular Disorder;Cardiovascular Disorder Risk;Circulatory System;Clinical Data Repository;Clinical Data Warehouse;Clinical Relevance;Clinically Relevant;Computer Program/Software;Data Repository;Database Of Genotypes And Phenotypes;Design;Designing;Disease Risk;Disease/Disorder;Disease/Disorder Proneness/Risk;Disorder Risk;Driving;Familial Disorder;Genetic Analysis;Genetic Variant;Genome Sequencing;Genome Wide Association Scan;Genome Wide Association Studies;Genome Wide Association Study;Genome-Wide;Genome-Wide Scan;Genomewide Association Scan;Genomewide Association Studies;Genomewide Association Study;Genomewide Scan;Heavy Metal Pb;Heavy Metal Lead;High Risk;Human Data;Hyperpiesia;Hyperpiesis;Hypertensive Disease;Improved;Insight;Liability To Disease;Malignancy;Neoplasm/Cancer;Novel;Novel Marker;Pathway;Phase 1 Study;Public Health Medicine (Field);Public Health Relevance;Relational Database;Statistics;Study Design;Success;Therapeutic Development;Tool;Whole Genome Association Studies;Whole Genome Association Study
