BACKGROUND: Genetic variation may contribute to differential gene expression in the brain of individuals with psychiatric disorders. To test this hypothesis, we identified genes that were differentially expressed in individuals with bipolar disorder, along with nearby single nucleotide polymorphisms (SNPs) that were associated with expression of the same genes. We then tested these SNPs for association with bipolar disorder in large case-control samples. METHODS: We used the Stanley Genomics Database to extract gene expression and SNP microarray data from individuals with bipolar disorder (n = 40) and unaffected controls (n = 43). We identified 367 genes that were differentially expressed in the prefrontal cortex of cases vs. controls (fold change > 1.3 and FDR q-value < .05) and 45 nearby SNPs that were associated with expression of those same genes (FDR q-value < .05). We tested these SNPs for association with bipolar disorder in a meta-analysis of genome-wide association studies (GWAS) including 4,936 cases and 6,654 healthy controls. RESULTS: We identified 45 SNPs that were associated with expression of differentially expressed genes, including HBS1L (15 SNPs), HLA-DPB1 (15 SNPs), AMFR (8 SNPs), PCLO (2 SNPs) and WDR41 (2 SNPs). Of these, one SNP (rs13438494), in an intron of the piccolo (PCLO) gene, was significantly associated with bipolar disorder (FDR adjusted p < .05) in the meta-analysis of GWAS. CONCLUSIONS: These results support the previous findings implicating PCLO in mood disorders and demonstrate the utility of combining gene expression and genetic variation data to improve our understanding of the genetic contribution to bipolar disorder.
BACKGROUND: Genetic variation may contribute to differential gene expression in the brain of individuals with psychiatric disorders. To test this hypothesis, we identified genes that were differentially expressed in individuals with bipolar disorder, along with nearby single nucleotide polymorphisms (SNPs) that were associated with expression of the same genes. We then tested these SNPs for association with bipolar disorder in large case-control samples. METHODS: We used the Stanley Genomics Database to extract gene expression and SNP microarray data from individuals with bipolar disorder (n = 40) and unaffected controls (n = 43). We identified 367 genes that were differentially expressed in the prefrontal cortex of cases vs. controls (fold change > 1.3 and FDR q-value < .05) and 45 nearby SNPs that were associated with expression of those same genes (FDR q-value < .05). We tested these SNPs for association with bipolar disorder in a meta-analysis of genome-wide association studies (GWAS) including 4,936 cases and 6,654 healthy controls. RESULTS: We identified 45 SNPs that were associated with expression of differentially expressed genes, including HBS1L (15 SNPs), HLA-DPB1 (15 SNPs), AMFR (8 SNPs), PCLO (2 SNPs) and WDR41 (2 SNPs). Of these, one SNP (rs13438494), in an intron of the piccolo (PCLO) gene, was significantly associated with bipolar disorder (FDR adjusted p < .05) in the meta-analysis of GWAS. CONCLUSIONS: These results support the previous findings implicating PCLO in mood disorders and demonstrate the utility of combining gene expression and genetic variation data to improve our understanding of the genetic contribution to bipolar disorder.
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Authors: Hong Chang; Lingyi Li; Tao Peng; Maria Grigoroiu-Serbanescu; Sarah E Bergen; Mikael Landén; Christina M Hultman; Andreas J Forstner; Jana Strohmaier; Julian Hecker; Thomas G Schulze; Bertram Müller-Myhsok; Andreas Reif; Philip B Mitchell; Nicholas G Martin; Sven Cichon; Markus M Nöthen; Stéphane Jamain; Marion Leboyer; Frank Bellivier; Bruno Etain; Jean-Pierre Kahn; Chantal Henry; Marcella Rietschel; Xiao Xiao; Ming Li Journal: Mol Neurobiol Date: 2016-08-25 Impact factor: 5.590
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