The NIH has invested heavily in obtaining genomic data on a large number of individuals. The challenge now is to use the data on genetic variations to improve health care and clinical practice. Investigating functional consequences of genetic variants associated with a given disorder can inform us of the mechanistic basis of the disorder and potential future therapeutic targets. G protein coupled receptors (GPCRs) comprise a large gene family that represents the most druggable portion of the genome. Although a large number of GPCR variants have been identified, the functional consequence and potential clinical impact of most of these GPCR variants have not been determined. We propose to combine phenome- and function-based approaches to identify the most clinically important GPCR variants. Attesting to both rationale and feasibility, the Geisinger Health System is one of the pioneers of the electronic health record system. For nearly two decades, we have collected detailed clinical data on ~3,000,000 patients, including rich, categorical information (eg, ICD9 codes, lab values, medications, insurance claims) on >750,000 individuals that has been entered into a highly standardized, searchable, and exportable database. Moreover, we have genotyped ~18,000 patients in this group and have collected DNA samples on another ~20,000 subjects for on-going genotyping efforts. Building on these resources, we will collaborate with Penn State University to perform a phenome-wide association (PheWAS) approach to identify major clinical phenotypes associated with GPCR variants that are present in >1% of the population. We will then use rapid but comprehensive approaches to test the functional consequence of each GPCR variant to determine whether functional defects exist that could contribute to the pathobiology of the associated phenotype. Finally, we will use Geisinger's unique consent process to re- contact study participants for the purpose of collecting additional blood from those carrying dysfunctional GPCR variants. This blood will be used to derive inducible pluripotent stem cells that will be made available to the scientific community for further derivation and functional analysis.
Using genomic information to improve healthcare is an enormous undertaking that will require novel strategies to rapidly separate 'the wheat from the chaff'. Offering an innovative approach to this problem, this grant application will combine a disease-based filtering algorithm with a functional testing platform to rapidly identify G protein-coupled receptor variants producing functional defects that could contribute to disease pathology or treatment response.
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