4.8 Article

Meta-analysis of genome-wide association studies of anxiety disorders

Journal

MOLECULAR PSYCHIATRY
Volume 21, Issue 10, Pages 1391-1399

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/mp.2015.197

Keywords

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Funding

  1. NIH grant [R01MH87646]
  2. Japan Society for the Promotion of Science [21-8373]
  3. IMH Schizophrenia Genetics Initiative U01s [MH046276, MH46289, MH46318]
  4. MGS Part 1 (MGS1)
  5. Research Institute for Diseases in the Elderly (RIDE2) [014-93-015]
  6. Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Ageing (NCHA) [050-060-810]
  7. Vidi [017.106.370]
  8. Erasmus Medical Center, Rotterdam
  9. Netherlands Organization for the Health Research and Development (ZonMw)
  10. Ministry of Education, Culture and Science
  11. Ministry for Health, Welfare and Sports
  12. Federal Ministry of Education and Research [01ZZ9603, 01ZZ0103, 01ZZ040, 03ZIK012]
  13. Ministry of Cultural Affairs
  14. Social Ministry of the Federal State of Mecklenburg-West Pomerania
  15. Siemens Healthcare, Erlangen, Germany
  16. Federal State of Mecklenburg-West Pomerania
  17. Grants-in-Aid for Scientific Research [25461723, 26461712] Funding Source: KAKEN

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Anxiety disorders (ADs), namely generalized AD, panic disorder and phobias, are common, etiologically complex conditions with a partially genetic basis. Despite differing on diagnostic definitions based on clinical presentation, ADs likely represent various expressions of an underlying common diathesis of abnormal regulation of basic threat-response systems. We conducted genome-wide association analyses in nine samples of European ancestry from seven large, independent studies. To identify genetic variants contributing to genetic susceptibility shared across interview-generated DSM-based ADs, we applied two phenotypic approaches: (1) comparisons between categorical AD cases and supernormal controls, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. We used logistic and linear regression, respectively, to analyze the association between these phenotypes and genome-wide single nucleotide polymorphisms. Meta-analysis for each phenotype combined results across the nine samples for over 18 000 unrelated individuals. Each meta-analysis identified a different genome-wide significant region, with the following markers showing the strongest association: for case-control contrasts, rs1709393 located in an uncharacterized non-coding RNA locus on chromosomal band 3q12.3 (P = 1.65 x 10(-8)); for FS, rs1067327 within CAMKMT encoding the calmodulin-lysine N-methyltransferase on chromosomal band 2p21 (P = 2.86 x 10(-9)). Independent replication and further exploration of these findings are needed to more fully understand the role of these variants in risk and expression of ADs.

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