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Meta-Analysis
. 2013 Apr;18(4):497-511.
doi: 10.1038/mp.2012.21. Epub 2012 Apr 3.

A mega-analysis of genome-wide association studies for major depressive disorder

Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium  1 ; Stephan Ripke, Naomi R Wray, Cathryn M Lewis, Steven P Hamilton, Myrna M Weissman, Gerome Breen, Enda M Byrne, Douglas H R Blackwood, Dorret I Boomsma, Sven Cichon, Andrew C Heath, Florian Holsboer, Susanne Lucae, Pamela A F Madden, Nicholas G Martin, Peter McGuffin, Pierandrea Muglia, Markus M Noethen, Brenda P Penninx, Michele L Pergadia, James B Potash, Marcella Rietschel, Danyu Lin, Bertram Müller-Myhsok, Jianxin Shi, Stacy Steinberg, Hans J Grabe, Paul Lichtenstein, Patrik Magnusson, Roy H Perlis, Martin Preisig, Jordan W Smoller, Kari Stefansson, Rudolf Uher, Zoltan Kutalik, Katherine E Tansey, Alexander Teumer, Alexander Viktorin, Michael R Barnes, Thomas Bettecken, Elisabeth B Binder, René Breuer, Victor M Castro, Susanne E Churchill, William H Coryell, Nick Craddock, Ian W Craig, Darina Czamara, Eco J De Geus, Franziska Degenhardt, Anne E Farmer, Maurizio Fava, Josef Frank, Vivian S Gainer, Patience J Gallagher, Scott D Gordon, Sergey Goryachev, Magdalena Gross, Michel Guipponi, Anjali K Henders, Stefan Herms, Ian B Hickie, Susanne Hoefels, Witte Hoogendijk, Jouke Jan Hottenga, Dan V Iosifescu, Marcus Ising, Ian Jones, Lisa Jones, Tzeng Jung-Ying, James A Knowles, Isaac S Kohane, Martin A Kohli, Ania Korszun, Mikael Landen, William B Lawson, Glyn Lewis, Donald Macintyre, Wolfgang Maier, Manuel Mattheisen, Patrick J McGrath, Andrew McIntosh, Alan McLean, Christel M Middeldorp, Lefkos Middleton, Grant M Montgomery, Shawn N Murphy, Matthias Nauck, Willem A Nolen, Dale R Nyholt, Michael O'Donovan, Högni Oskarsson, Nancy Pedersen, William A Scheftner, Andrea Schulz, Thomas G Schulze, Stanley I Shyn, Engilbert Sigurdsson, Susan L Slager, Johannes H Smit, Hreinn Stefansson, Michael Steffens, Thorgeir Thorgeirsson, Federica Tozzi, Jens Treutlein, Manfred Uhr, Edwin J C G van den Oord, Gerard Van Grootheest, Henry Völzke, Jeffrey B Weilburg, Gonneke Willemsen, Frans G Zitman, Benjamin Neale, Mark Daly, Douglas F Levinson, Patrick F Sullivan
Affiliations
Meta-Analysis

A mega-analysis of genome-wide association studies for major depressive disorder

Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium et al. Mol Psychiatry. 2013 Apr.

Abstract

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

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Conflict of interest statement

Conflict of interest

Elisabeth Binder received grant support from Pharmaneuroboost. Hans J Grabe reports receiving funding from: German Research Foundation; Federal Ministry of Education and Research Germany; speakers honoraria from Bristol-Myers Squibb, Eli Lilly, Novartis, Eisai, Wyeth, Pfizer, Boehringer Ingelheim, Servier and travel funds from Janssen-Cilag, Eli Lilly, Novartis, AstraZeneca and SALUS-Institute for Trend-Research and Therapy Evaluation in Mental Health. Florian Holsboer is a shareholder of Affectis Pharmaceuticals and co-founder of HolsboerMaschmeyer-NeuroChemie. James A Knowles is on the Scientific Advisory Committee for Next-Generation Sequencing of Life Technologies and is a technical advisor to SoftGenetics. Pierandrea Muglia was a full-time employee of GSK when the work was performed. Bertram Müller-Myhsok consulted for Affectis Pharmaceuticals. Matthias Nauck reports funding from: the Federal Ministry of Education and Research Germany, Bio-Rad Laboratories, Siemens AG, Zeitschrift für Laboratoriumsmedizin, Bruker Daltronics, Abbott, Jurilab Kuopio, Roche Diagnostics, Dade Behring, DPC Biermann and Becton Dickinson. Rudolf Uher has received funding from a number of pharmaceutical companies as part of the European Union Innovative Medicine Initiative funded NEWMEDS project. Federica Tozzi was a full-time employee of GSK when the work was performed. Henry Völzke reports funding from: Sanofi-Aventis, Biotronik, the Humboldt Foundation, the Federal Ministry of Education and Research (Germany) and the German Research Foundation. No other author reports a conflict of interest.

Figures

Figure 1
Figure 1
Overview of results from the discovery genome-wide association study mega-analysis for major depressive disorder. The inset shows the quantile–quantile plot (observed by expected P-values on the −log10scale) showing conformity of the observed results to expectations under the null. The main part of the figure shows the Manhattan plot (−log10 of the P-value by genomic location) of the association results in genomic context. No region exceeded genome-wide significance in the discovery sample.
See this image and copyright information in PMC

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