Enabling Genomics-Based Patient Risk Assessment: BRCA1 Information Consolidation and Interpretation
VariantMapper demonstrates how genomics can be integrated into clinical decision support, including BRCA1. Comparing patients' DNA variants and those from databases documenting genotype-phenotype association, this use case can alert clinicians about potential risk factors. By dynamically binding the knowledge database and patients' genotype, the application also allows clinicians to learn more about their patients as the database grows. This project seeks to integrate genomic, clinical, and patient questionnaire information for improved breast cancer diagnosis and treatment of mutation carrying individuals. A demonstration of VariantMapper, using GA4HGH Read API 0.1, has been implemented by a Harvard lab and can be found here. Other examples include the Genomics Advisor and DB EMR (for diabetes) at the Apple iTunes store.
Combining Genomes Across Sites to enabling Research for Cancer and Rare/Undiagnosed Diseases
Tissue-specific somatic mutations create many different variations that need large patient samples. Combining genomic information across many institutions, via an API, would enable such research to take place. Rare/undiagnosed diseases present a challenging problem because a single institution rarely has enough patients to quantify genotype and phenotype links. An example of this use case is the new Undiagnosed Disease Network sponsored by the NIH
Microorganisms can be identified based on genetic sequence. For example, tuberculosis virulence and drug resistance profiles can be predicted based on the underlying sequences, as is being done by TBResist. Host-organism interactions based on genetics can also be analyzed. In order to fully categorize mycobacterial variants, it is necessary to develop high-density DNA probe arrays. A recent study reported an array containing all 16S rRNA polymorphisms over a 200bp region of a mycobacterial database. This allows for accurate and specific diagnosis of the infection.
Predicting Drug Response and Integration with Electronic Medical Records for Research
Systems such as SMART and i2b2 are enabling apps to access clinical and genomic information associated with Electronic Health Records and other sources. For example, the Genomics Advisor presents pharmocogenomic information based on patient genetic information. Integration with GA4GH is will enable further research into genotype-phenotype links as well as a new generation of apps that provide real-time feedback to physicians. For example, physicians can now predict patient response to different drugs based on pharmocogenomics. An example is the PREDICT system at Vanderbilt which suggests warfarin dosage based on underlying genetic information.
Prenatal genetic testing has been recorded and researched for nearly two decades. At first its use was limited to identifying gender, trisomy 21 and RhD. Recently, focus has turned to using genetic markers to monitor development, noting any abnormalities that may have consequences when the baby is born and later in life. An example of a currently available, noninvasive prenatal genetic screening test tool is Panorama. It is a tool that can be shared and used by a pregnant woman’s provider to give her the most accurate health advice. Panorama works by testing a particular set of microdeletions.