4.7 Article

Meta-analysis of genome-wide association studies for panic disorder in the Japanese population

Journal

TRANSLATIONAL PSYCHIATRY
Volume 2, Issue -, Pages -

Publisher

SPRINGERNATURE
DOI: 10.1038/tp.2012.89

Keywords

BDKRB2; gene ontology; GWAS; NPY5R; panic disorder; polygenic score

Categories

Funding

  1. Ministry of Education, Culture, Sports, Science and Technology of Japan [17019029, 21300242]
  2. Japan Society for the Promotion of Science [21-8373]
  3. Grants-in-Aid for Scientific Research [23689022, 24591679, 21300242, 24500452] Funding Source: KAKEN

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Panic disorder (PD) is a moderately heritable anxiety disorder whose pathogenesis is not well understood. Due to the lack of power in previous association studies, genes that are truly associated with PD might not be detected. In this study, we conducted a genome-wide association study (GWAS) in two independent data sets using the Affymetrix Mapping 500K Array or Genome-Wide Human SNP Array 6.0. We obtained imputed genotypes for each GWAS and performed a meta-analysis of two GWAS data sets (718 cases and 1717 controls). For follow-up, 12 single-nucleotide polymorphisms (SNPs) were tested in 329 cases and 861 controls. Gene ontology enrichment and candidate gene analyses were conducted using the GWAS or meta-analysis results. We also applied the polygenic score analysis to our two GWAS samples to test the hypothesis of polygenic components contributing to PD. Although genome-wide significant SNPs were not detected in either of the GWAS nor the meta-analysis, suggestive associations were observed in several loci such as BDKRB2 (P = 1.3 x 10(-5), odds ratio = 1.31). Among previous candidate genes, supportive evidence for association of NPY5R with PD was obtained (gene-wise corrected P = 6.4 x 10(-4)). Polygenic scores calculated from weakly associated SNPs (P<0.3 and 0.4) in the discovery sample were significantly associated with PD status in the target sample in both directions (sample I to sample II and vice versa) (P<0.05). Our findings suggest that large sets of common variants of small effects collectively account for risk of PD.

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