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Despite advances in pharmacogenetics, the majority of heritability for treatment response cannot be explained by common variation, suggesting that factors such as epigenetics may play a key role. Regulatory genes, such as those involved in DNA methylation and transcriptional repression, are therefore excellent candidates for investigating antipsychotic treatment response. This study explored the differential expression of regulatory genes between patients with schizophrenia (chronic and antipsychotic-naïve first-episode patients) and healthy controls in order to identify candidate genes for association with antipsychotic treatment response. Seven candidate differentially expressed genes were identified, and four variants within these genes were found to be significantly associated with treatment response (DNMT3A rs2304429, HDAC5 rs11079983, and HDAC9 rs1178119 and rs11764843). Further analyses revealed that two of these variants (rs2304429 and rs11079983) are predicted to alter the expression of specific genes (DNMT3A, ASB16, and ASB16-AS1) in brain regions previously implicated in schizophrenia and treatment response. These results may aid in the development of biomarkers for antipsychotic treatment response, as well as novel drug targets.
Pubmed ID: 31354789
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Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.
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