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Meta-Analysis
. 2016 Oct;21(10):1391-9.
doi: 10.1038/mp.2015.197. Epub 2016 Jan 12.

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

T Otowa  1   2 , K Hek  3   4 , M Lee  1 , E M Byrne  5   6 , S S Mirza  3 , M G Nivard  7 , T Bigdeli  1 , S H Aggen  1 , D Adkins  8 , A Wolen  9 , A Fanous  10   11 , M C Keller  12   13 , E Castelao  14 , Z Kutalik  15   16   17 , S Van der Auwera  18 , G Homuth  19 , M Nauck  20 , A Teumer  21 , Y Milaneschi  22   23 , J-J Hottenga  22   23 , N Direk  3 , A Hofman  3 , A Uitterlinden  3   24 , C L Mulder  25 , A K Henders  5   6 , S E Medland  5 , S Gordon  5 , A C Heath  26 , P A F Madden  26 , M L Pergadia  26   27 , P J van der Most  28 , I M Nolte  28 , F V A van Oort  29 , C A Hartman  30 , A J Oldehinkel  30 , M Preisig  14 , H J Grabe  18   31 , C M Middeldorp  7   32 , B W J H Penninx  22   23 , D Boomsma  7   23 , N G Martin  5 , G Montgomery  5 , B S Maher  33 , E J van den Oord  8 , N R Wray  5   6 , H Tiemeier  3   25   34 , J M Hettema  1
Affiliations
Meta-Analysis

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

T Otowa et al. Mol Psychiatry. 2016 Oct.

Erratum in

  • Meta-analysis of genome-wide association studies of anxiety disorders.
    Otowa T, Hek K, Lee M, Byrne EM, Mirza SS, Nivard MG, Bigdeli T, Aggen SH, Adkins D, Wolen A, Fanous A, Keller MC, Castelao E, Kutalik Z, der Auwera SV, Homuth G, Nauck M, Teumer A, Milaneschi Y, Hottenga JJ, Direk N, Hofman A, Uitterlinden A, Mulder CL, Henders AK, Medland SE, Gordon S, Heath AC, Madden PA, Pergadia ML, van der Most PJ, Nolte IM, van Oort FV, Hartman CA, Oldehinkel AJ, Preisig M, Grabe HJ, Middeldorp CM, Penninx BW, Boomsma D, Martin NG, Montgomery G, Maher BS, van den Oord EJ, Wray NR, Tiemeier H, Hettema JM. Otowa T, et al. Mol Psychiatry. 2016 Oct;21(10):1485. doi: 10.1038/mp.2016.11. Epub 2016 Feb 9. Mol Psychiatry. 2016. PMID: 26857599 No abstract available.

Abstract

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 × 10(-8)); for FS, rs1067327 within CAMKMT encoding the calmodulin-lysine N-methyltransferase on chromosomal band 2p21 (P=2.86 × 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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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Quantile-quantile plots of meta-analysis results for (a) case-control and (b) factor score phenotypes. Observed association results of −log10P , after LD-pruning at r2 of 0.4, are plotted against the expected distribution under the null hypothesis of no association.
Figure 1
Figure 1
Quantile-quantile plots of meta-analysis results for (a) case-control and (b) factor score phenotypes. Observed association results of −log10P , after LD-pruning at r2 of 0.4, are plotted against the expected distribution under the null hypothesis of no association.
Figure 2
Figure 2
Manhattan plots of meta-analysis results for (a) case-control and (b) factor score phenotypes. Red horizontal line indicates the genome-wide significant p-value 5×10−8; blue line indicates the suggestive p-value=1×10−5.
Figure 2
Figure 2
Manhattan plots of meta-analysis results for (a) case-control and (b) factor score phenotypes. Red horizontal line indicates the genome-wide significant p-value 5×10−8; blue line indicates the suggestive p-value=1×10−5.
Fig 3
Fig 3
Regional plots around most significant SNPs in (a) case-control and (b) factor score model.
Fig 3
Fig 3
Regional plots around most significant SNPs in (a) case-control and (b) factor score model.
See this image and copyright information in PMC

References

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