Development of a SNP genotyping panel and a medical decision support algorithm to predict drug response in schizophrenia

Genome Wide Association Studies (GWAS) of Single Nucleotide Polymorphisms (SNPs) is leading the development of personalized medicine approaches to predict and diagnose diseases or to determine drug response in individual patients. As the basic research provides all the genomic information and interpretation of these data, translational research has to be conducted in order to develop genomic diagnostics to apply this information into practice in medical clinics. In this perspective, our goal is to design a diagnostic assay for the Prediction of Drug Response for Schizophrenia to especially guide the initial selection of antipsychotics based on the individual genomic information of the patients. Initially a literature search has been done to identify previously described SNPs associated with schizophrenia that are known to effect the response to antipsychotics or predict the side effects of antipsychotic drugs. Twenty-two SNPs are identified, that map to 8 genes. Next, we have applied the novel AHP based SNP prioritization approach implemented in the METU-SNP software for GWAS to the SNP Genotyping data for the European American population (from dbGAP database), with 1351 patients and 1378 controls genotyped for over 729454 SNPs. The 22 SNPs selected based on the literature were cross-checked with the results of GWAS and prioritized in order to finalize the pharmacogenomics of the SNP (p-SNP) panel for schizophrenia and to determine the order of SNPs to be targeted in the assay development process. The pyro-sequencing approach was used during the development of the assay to determine the genotypes of the patients for the SNPs selected for the panel. After the next phase of our project, which is the development and optimization of primer sets, is completed a validation study will be designed in collaboration with psychiatric clinics for the described p-SNP kit panel and the supporting software that is in-line, for development of easy translation of the genotyping results to support the clinical decision of the choice of therapy. Application of personalized medicine approaches and utilizing genomic diagnostic assays as presented here will eliminate or decrease the number of trials-and-errors in selecting sthe right treatment and dosage for particuler patient, and will also minimize emergency visits due to side effects of the drugs. In addition, the prescription of the right medicine and treatment plan at the initial diagnosis of schizophrenia will increase trust between healthcare professionals and patients, which in return is expected to provide higher cooperation and adherance rates of patients to their treatment. Overall the personalized medicine approach is expected to decrease the cost of healthcare in psychiatry and other disciplines, while offering higher quality healthcare.