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      Genomewide pharmacogenomic study of metabolic side effects to antipsychotic drugs

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          Abstract

          Understanding individual differences in the susceptibility to metabolic side effects as a response to antipsychotic therapy is essential to optimize the treatment of schizophrenia. Here we perform genomewide association studies (GWAS) to search for genetic variation affecting the susceptibility to metabolic side effects. The analysis sample consisted of 738 schizophrenia patients, successfully genotyped for 492K SNPs, from the genomic subsample of the Clinical Antipsychotic Trial of Intervention Effectiveness (CATIE) study. Outcomes included twelve indicators of metabolic side effects, quantifying antipsychotic-induced change in weight, blood lipids, glucose and hemoglobin A1c, blood pressure and heart rate. Our criterion for genomewide significance was a pre-specified threshold that ensures, on average, only 10% of the significant findings are false discoveries. Twenty-one SNPs satisfied this criterion. The top finding indicated a SNP in MEIS2 mediated the effects of risperidone on hip circumference ( q =.004). The same SNP was also found to mediate risperidone's effect on waist circumference ( q =.055). Genomewide significant finding were also found for SNPs in PRKAR2B, GPR98, FHOD3, RNF144A, ASTN2, SOX5 and ATF7IP2, as well as several intergenic markers. PRKAR2B and MEIS2 both have previous research indicating metabolic involvement and PRKAR2B has previously been shown to mediate antipsychotic response. Although our findings require replication and functional validation, this study demonstrates the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antipsychotic medication.

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          Most cited references71

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Six new loci associated with body mass index highlight a neuronal influence on body weight regulation.

            Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.
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              Newly identified loci that influence lipid concentrations and risk of coronary artery disease.

              To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls.
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                Author and article information

                Journal
                9607835
                20545
                Mol Psychiatry
                Molecular psychiatry
                1359-4184
                1476-5578
                3 February 2010
                2 March 2010
                March 2011
                1 September 2011
                : 16
                : 3
                : 321-332
                Affiliations
                [a ] Center for Biomarker Research and Personalized Medicine, School of Pharmacy, Medical College of Virginia of Virginia Commonwealth University, Richmond, VA, USA
                [b ] Departments of Biomedical Informatics, Psychiatry, and Cancer Biology, Vanderbilt University Medical Center, Nashville, TN, USA
                [c ] Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA
                [d ] Department of Psychiatry, Duke University, Durham, NC, USA
                [e ] Department of Psychiatry, Columbia University, New York, NY, USA
                [f ] Departments of Genetics, Psychiatry, & Epidemiology, University of North Carolina at Chapel Hill, NC, USA
                [g ] Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, Sweden
                Author notes
                [* ]Corresponding author ( deadkins@ 123456vcu.edu )
                Article
                nihpa172050
                10.1038/mp.2010.14
                2891163
                20195266
                84b0e24f-653e-4459-b515-56ae7cf6da75

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                History
                Funding
                Funded by: National Institute of Mental Health : NIMH
                Funded by: National Human Genome Research Institute : NHGRI
                Award ID: R01 MH078069-03 ||MH
                Funded by: National Institute of Mental Health : NIMH
                Funded by: National Human Genome Research Institute : NHGRI
                Award ID: R01 MH077139-03 ||MH
                Funded by: National Institute of Mental Health : NIMH
                Funded by: National Human Genome Research Institute : NHGRI
                Award ID: R01 MH074027-02 ||MH
                Funded by: National Institute of Mental Health : NIMH
                Funded by: National Human Genome Research Institute : NHGRI
                Award ID: R01 HG004240-02S1 ||HG
                Categories
                Article

                Molecular medicine
                genomewide association,antipsychotics,pharmacogenomics,personalized medicine,metabolic side effects

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