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. 2014 Oct 1;76(7):510-2.
doi: 10.1016/j.biopsych.2014.07.029.

Genetic studies of major depressive disorder: why are there no genome-wide association study findings and what can we do about it?

Douglas F Levinson  1 , Sara Mostafavi  2 , Yuri Milaneschi  3 , Margarita Rivera  4 , Stephan Ripke  5 , Naomi R Wray  6 , Patrick F Sullivan  7
Affiliations

Genetic studies of major depressive disorder: why are there no genome-wide association study findings and what can we do about it?

Douglas F Levinson et al. Biol Psychiatry. .
No abstract available

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Conflict of interest statement

The authors have no competing interests to declare.

Figures

Figure 1
Figure 1. The GWAS “inflection point”: discoveries in relation to sample size
Each point represents the number of independent chromosomal regions (loci) containing SNPs associated with the disease or trait at a genome-wide level of significance in a GWAS analysis with a given number of cases (and a control group of similar or greater size). The curve for adult height is truncated but the next datapoint is 180 loci with the equivalent of ~65,000 cases. The data points are results of unpublished meta-analyses carried out by S.R. on roughly chronological subsets of each dataset in order to demonstrate the linear relationship between sample size and discoveries once a minimum N (“inflection point”) has been achieved. The ratios for each trait are the approximate number of discoveries per 1,000 additional cases (plus controls). Each ratio results from a combination of the number of susceptibility loci for the trait and the size of their genetic effects. Large Ns would discover additional loci for each trait. (See Figure S1 for references.)
See this image and copyright information in PMC

References

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    1. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature - PMC - PubMed
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    1. Panagiotou OA, Willer CJ, Hirschhorn JN, Ioannidis JP. The power of meta- analysis in genome-wide association studies. Annual review of genomics and human genetics. 2013;14:441–465. - PMC - PubMed
    1. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010;42:565–569. - PMC - PubMed

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