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Meta-Analysis
. 2017 Sep 1;82(5):322-329.
doi: 10.1016/j.biopsych.2016.11.013. Epub 2016 Dec 8.

An Analysis of Two Genome-wide Association Meta-analyses Identifies a New Locus for Broad Depression Phenotype

Nese Direk  1 Stephanie Williams  2 Jennifer A Smith  3 Stephan Ripke  4 Tracy Air  5 Azmeraw T Amare  6 Najaf Amin  7 Bernhard T Baune  5 David A Bennett  8 Douglas H R Blackwood  9 Dorret Boomsma  10 Gerome Breen  11 Henriette N Buttenschøn  12 Enda M Byrne  13 Anders D Børglum  14 Enrique Castelao  15 Sven Cichon  16 Toni-Kim Clarke  9 Marilyn C Cornelis  17 Udo Dannlowski  18 Philip L De Jager  19 Ayse Demirkan  7 Enrico Domenici  20 Cornelia M van Duijn  7 Erin C Dunn  21 Johan G Eriksson  22 Tonu Esko  23 Jessica D Faul  24 Luigi Ferrucci  25 Myriam Fornage  26 Eco de Geus  10 Michael Gill  27 Scott D Gordon  28 Hans Jörgen Grabe  29 Gerard van Grootheest  30 Steven P Hamilton  31 Catharina A Hartman  32 Andrew C Heath  33 Karin Hek  34 Albert Hofman  35 Georg Homuth  36 Carsten Horn  37 Jouke Jan Hottenga  10 Sharon L R Kardia  3 Stefan Kloiber  38 Karestan Koenen  39 Zoltán Kutalik  40 Karl-Heinz Ladwig  41 Jari Lahti  42 Douglas F Levinson  43 Cathryn M Lewis  11 Glyn Lewis  44 Qingqin S Li  45 David J Llewellyn  46 Susanne Lucae  38 Kathryn L Lunetta  47 Donald J MacIntyre  9 Pamela Madden  33 Nicholas G Martin  28 Andrew M McIntosh  9 Andres Metspalu  48 Yuri Milaneschi  30 Grant W Montgomery  28 Ole Mors  49 Thomas H Mosley Jr  50 Joanne M Murabito  51 Bertram Müller-Myhsok  52 Markus M Nöthen  53 Dale R Nyholt  54 Michael C O'Donovan  55 Brenda W Penninx  30 Michele L Pergadia  56 Roy Perlis  57 James B Potash  58 Martin Preisig  15 Shaun M Purcell  59 Jorge A Quiroz  60 Katri Räikkönen  61 John P Rice  33 Marcella Rietschel  62 Margarita Rivera  63 Thomas G Schulze  64 Jianxin Shi  65 Stanley Shyn  66 Grant C Sinnamon  67 Johannes H Smit  30 Jordan W Smoller  21 Harold Snieder  68 Toshiko Tanaka  25 Katherine E Tansey  55 Alexander Teumer  69 Rudolf Uher  70 Daniel Umbricht  37 Sandra Van der Auwera  71 Erin B Ware  72 David R Weir  24 Myrna M Weissman  73 Gonneke Willemsen  10 Jingyun Yang  8 Wei Zhao  3 Henning Tiemeier  74 Patrick F Sullivan  75
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Free PMC article
Meta-Analysis

An Analysis of Two Genome-wide Association Meta-analyses Identifies a New Locus for Broad Depression Phenotype

Nese Direk et al. Biol Psychiatry. .
Free PMC article

Abstract

Background: The genetics of depression has been explored in genome-wide association studies that focused on either major depressive disorder or depressive symptoms with mostly negative findings. A broad depression phenotype including both phenotypes has not been tested previously using a genome-wide association approach. We aimed to identify genetic polymorphisms significantly associated with a broad phenotype from depressive symptoms to major depressive disorder.

Methods: We analyzed two prior studies of 70,017 participants of European ancestry from general and clinical populations in the discovery stage. We performed a replication meta-analysis of 28,328 participants. Single nucleotide polymorphism (SNP)-based heritability and genetic correlations were calculated using linkage disequilibrium score regression. Discovery and replication analyses were performed using a p-value-based meta-analysis. Lifetime major depressive disorder and depressive symptom scores were used as the outcome measures.

Results: The SNP-based heritability of major depressive disorder was 0.21 (SE = 0.02), the SNP-based heritability of depressive symptoms was 0.04 (SE = 0.01), and their genetic correlation was 1.001 (SE = 0.2). We found one genome-wide significant locus related to the broad depression phenotype (rs9825823, chromosome 3: 61,082,153, p = 8.2 × 10-9) located in an intron of the FHIT gene. We replicated this SNP in independent samples (p = .02) and the overall meta-analysis of the discovery and replication cohorts (1.0 × 10-9).

Conclusions: This large study identified a new locus for depression. Our results support a continuum between depressive symptoms and major depressive disorder. A phenotypically more inclusive approach may help to achieve the large sample sizes needed to detect susceptibility loci for depression.

Keywords: CHARGE consortium; Depressive symptoms; FHIT gene; Genome-wide association study; Major depressive disorder; Psychiatric Genomics Consortium.

Conflict of interest statement

Conflict of Interest: The other authors report no conflicts.

Figures

Figure 1
Figure 1. Manhattan Plot
X-axis represents the chromosomal position for each SNP, and y-axis the −log10 P value for association with depression.

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