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Statistical Methods To Explore The Phenotypic Consequences Of Gene Regulation
Abstracts Results: We will also discuss how monitoring and controlling stress may help to prevent exacerbation of symptoms and possibly disease onset. Conclusions: Finally, the clinical implications and future outlook of the field will be discussed in light of current limitations.
S717
Disclosure Nothing to disclose. http://dx.doi.org/10.1016/j.euroneuro.2017.06.028
Disclosure
PHARMACOGENOMICS: TOWARDS A NEW ERA OF PERSONALIZED MEDICINE IN PSYCHIATRY?
Nothing to disclose.
Daniel Mueller
http://dx.doi.org/10.1016/j.euroneuro.2017.06.027
STATISTICAL METHODS TO EXPLORE THE PHENOTYPIC CONSEQUENCES OF GENE REGULATION Hae Kyung Im University of Chicago Abstract Background: Over the last 15 years, enormous advances have been made in the technology to interrogate the genome, which in turn has allowed us to discover thousands of genetic variants robustly associated with complex traits including psychiatric disorders. However, most of these variants are not located in coding regions making their interpretation challenging. It is generally accepted that an important mechanism that mediate the genotype phenotype relationship is the regulation of gene expression levels as well as alternative splicing of mRNAs. Methods: We will describe a method (PrediXcan) to integrate large scale of Genome-Wide Association Atudies (GWAS) with reference transcriptome studies in order to investigate the underlying mechanism behind these discoveries. PrediXcan imputes the transcriptome and computes the correlation between the genetically determined component and the phenotype to prioritize genes that are likely to be causal. Results: We will show the results of applying PrediXcan to several large scale GWAS studies using prediction models of 44 human tissues. We find that most associations are tissue specific and that because of sharing between tissues, we increase our chances to discover the mediating genes when we scan across a broad set of tissues. Conclusions: To take full advantage of the large amounts of genomic data that are being generated, methods that integrate multiple sources of high throughput data are needed. Here we present PrediXcan and its extension that addresses this need. Application to a broad set of phenotypes allows us to explore the phenotypic consequences of gene regulatory variation.
University of Toronto Abstract
Background: Pharmacogenomics (PGx) is a field of study and clinical tool that assesses how genetic variability influences drug response and tolerability. CYP450 enzymes are responsible for metabolizing most psychiatric medications. Based on their genetic make-up, an individual may be classified as an extensive metabolizer (EM), intermediate metabolizer (IM), poor metabolizer (PM), ultra-rapid metabolizer (UM). Given the increasing evidence for genetic influences on treatment response, we deemed it important to study physicians' opinions and patients' outcome following pharmacogenetic testing for CYP2D6, CYP2C19 among other genes. Methods: Initially, only CYP2D6 and CYP2C19 genes were genotyped and treatment recommendations for antidepressant and antipsychotic medications were provided to physicians. This initiative expanded to include additional CYP enzyme genotyping such as CYP2C9, CYP3A4, CYP2B6, CYP1A2 and serotonin-related genes SLC6A4 and HTR2A. Six to eight weeks after physicians were provided with their patients’ genetic information, we sent our Pharmacogenetics in Psychiatry Follow-up Questionnaire (PIP-FQ) survey to psychiatrists and primary care physicians. Results: From the 620 physicians who were sent PIP-FQ surveys for the PGx study, 383 returned the survey for a response rate of 61.8%. Of all respondents, 58.1% were female, 43.7% were over 50 years old, and 59.7% were general practitioners while 32.7% were psychiatrists. From all respondents, 90.6% indicated that they understood the PGx report they received, 79.1% were satisfied with it, and 75.7% would agree that PGx testing will become standard for psychotropic pharmacotherapy. Of those given treatment recommendations by the PGx report, 57.1% found the report helpful for further treatment decisions and 77.5% said they would remain interested in referring additional patients to the study. Remarkably, when physicians took treatment recommendations into consideration, 120 of 211 (56.9%) patients were reported to benefit from the recommendation compared to baseline, with only two patients worsening following the change (p o 0.01).
S717
Disclosure Nothing to disclose. http://dx.doi.org/10.1016/j.euroneuro.2017.06.028
Disclosure
PHARMACOGENOMICS: TOWARDS A NEW ERA OF PERSONALIZED MEDICINE IN PSYCHIATRY?
Nothing to disclose.
Daniel Mueller
http://dx.doi.org/10.1016/j.euroneuro.2017.06.027
STATISTICAL METHODS TO EXPLORE THE PHENOTYPIC CONSEQUENCES OF GENE REGULATION Hae Kyung Im University of Chicago Abstract Background: Over the last 15 years, enormous advances have been made in the technology to interrogate the genome, which in turn has allowed us to discover thousands of genetic variants robustly associated with complex traits including psychiatric disorders. However, most of these variants are not located in coding regions making their interpretation challenging. It is generally accepted that an important mechanism that mediate the genotype phenotype relationship is the regulation of gene expression levels as well as alternative splicing of mRNAs. Methods: We will describe a method (PrediXcan) to integrate large scale of Genome-Wide Association Atudies (GWAS) with reference transcriptome studies in order to investigate the underlying mechanism behind these discoveries. PrediXcan imputes the transcriptome and computes the correlation between the genetically determined component and the phenotype to prioritize genes that are likely to be causal. Results: We will show the results of applying PrediXcan to several large scale GWAS studies using prediction models of 44 human tissues. We find that most associations are tissue specific and that because of sharing between tissues, we increase our chances to discover the mediating genes when we scan across a broad set of tissues. Conclusions: To take full advantage of the large amounts of genomic data that are being generated, methods that integrate multiple sources of high throughput data are needed. Here we present PrediXcan and its extension that addresses this need. Application to a broad set of phenotypes allows us to explore the phenotypic consequences of gene regulatory variation.
University of Toronto Abstract
Background: Pharmacogenomics (PGx) is a field of study and clinical tool that assesses how genetic variability influences drug response and tolerability. CYP450 enzymes are responsible for metabolizing most psychiatric medications. Based on their genetic make-up, an individual may be classified as an extensive metabolizer (EM), intermediate metabolizer (IM), poor metabolizer (PM), ultra-rapid metabolizer (UM). Given the increasing evidence for genetic influences on treatment response, we deemed it important to study physicians' opinions and patients' outcome following pharmacogenetic testing for CYP2D6, CYP2C19 among other genes. Methods: Initially, only CYP2D6 and CYP2C19 genes were genotyped and treatment recommendations for antidepressant and antipsychotic medications were provided to physicians. This initiative expanded to include additional CYP enzyme genotyping such as CYP2C9, CYP3A4, CYP2B6, CYP1A2 and serotonin-related genes SLC6A4 and HTR2A. Six to eight weeks after physicians were provided with their patients’ genetic information, we sent our Pharmacogenetics in Psychiatry Follow-up Questionnaire (PIP-FQ) survey to psychiatrists and primary care physicians. Results: From the 620 physicians who were sent PIP-FQ surveys for the PGx study, 383 returned the survey for a response rate of 61.8%. Of all respondents, 58.1% were female, 43.7% were over 50 years old, and 59.7% were general practitioners while 32.7% were psychiatrists. From all respondents, 90.6% indicated that they understood the PGx report they received, 79.1% were satisfied with it, and 75.7% would agree that PGx testing will become standard for psychotropic pharmacotherapy. Of those given treatment recommendations by the PGx report, 57.1% found the report helpful for further treatment decisions and 77.5% said they would remain interested in referring additional patients to the study. Remarkably, when physicians took treatment recommendations into consideration, 120 of 211 (56.9%) patients were reported to benefit from the recommendation compared to baseline, with only two patients worsening following the change (p o 0.01).