Genome-wide association study of major recurrent depression in the U.K. population

Cathryn M Lewis, Mandy Y Ng, Amy W Butler, Sarah Cohen-Woods, Rudolf Uher, Katrina Pirlo, Michael E Weale, Alexandra Schosser, Ursula M Paredes, Margarita Rivera, Nicholas Craddock, Mike J Owen, Lisa Jones, Ian Jones, Ania Korszun, Katherine J Aitchison, Jianxin Shi, John P Quinn, Alasdair MacKenzie, Peter VollenweiderGerard Waeber, Simon Heath, Mark Lathrop, Pierandrea Muglia, Michael R Barnes, John C Whittaker, Federica Tozzi, Florian Holsboer, Martin Preisig, Anne E Farmer, Gerome Breen, Ian W Craig, Peter McGuffin

Research output: Contribution to journalArticlepeer-review

194 Citations (Scopus)

Abstract

OBJECTIVE: Studies of major depression in twins and families have shown moderate to high heritability, but extensive molecular studies have failed to identify susceptibility genes convincingly. To detect genetic variants contributing to major depression, the authors performed a genome-wide association study using 1,636 cases of depression ascertained in the U.K. and 1,594 comparison subjects screened negative for psychiatric disorders.

METHOD: Cases were collected from 1) a case-control study of recurrent depression (the Depression Case Control [DeCC] study; N=1346), 2) an affected sibling pair linkage study of recurrent depression (probands from the Depression Network [DeNT] study; N=332), and 3) a pharmacogenetic study (the Genome-Based Therapeutic Drugs for Depression [GENDEP] study; N=88). Depression cases and comparison subjects were genotyped at Centre National de Génotypage on the Illumina Human610-Quad BeadChip. After applying stringent quality control criteria for missing genotypes, departure from Hardy-Weinberg equilibrium, and low minor allele frequency, the authors tested for association to depression using logistic regression, correcting for population ancestry.

RESULTS: Single nucleotide polymorphisms (SNPs) in BICC1 achieved suggestive evidence for association, which strengthened after imputation of ungenotyped markers, and in analysis of female depression cases. A meta-analysis of U.K. data with previously published results from studies in Munich and Lausanne showed some evidence for association near neuroligin 1 (NLGN1) on chromosome 3, but did not support findings at BICC1.

CONCLUSIONS: This study identifies several signals for association worthy of further investigation but, as in previous genome-wide studies, suggests that individual gene contributions to depression are likely to have only minor effects, and very large pooled analyses will be required to identify them.
Original languageEnglish
Pages (from-to)949-957
Number of pages9
JournalAmerican Journal of Psychiatry
Volume167
Issue number8
DOIs
Publication statusPublished - 1 Jun 2010

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