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The current state of play on the molecular genetics of depression

Published online by Cambridge University Press:  12 June 2012

S. Cohen-Woods*
Affiliation:
MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, UK
I. W. Craig
Affiliation:
MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, UK
P. McGuffin
Affiliation:
MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, UK
*
*Address for correspondence: Dr S. Cohen-Woods, Institute of Psychiatry, Box PO80, De Crespigny Park, London SE5 8AF, UK. (Email: sarah.cohen-woods@kcl.ac.uk)

Abstract

Background

It has been well established that both genes and non-shared environment contribute substantially to the underlying aetiology of major depressive disorder (MDD). A comprehensive overview of genetic research in MDD is presented.

Method

Papers were retrieved from PubMed up to December 2011, using many keywords including: depression, major depressive disorder, genetics, rare variants, gene–environment, whole genome, epigenetics, and specific candidate genes and variants. These were combined in a variety of permutations.

Results

Linkage studies have yielded some promising chromosomal regions in MDD. However, there is a continued lack of consistency in association studies, in both candidate gene and genome-wide association studies (GWAS). Numerous factors may account for variable results including the use of different diagnostic approaches, small samples in early studies, population stratification, epigenetic phenomena, copy number variation (CNV), rare variation, and phenotypic and allelic heterogeneity. The conflicting results are also probably, in part, a consequence of environmental factors not being considered or controlled for.

Conclusions

Each research group has to identify what issues their sample may best address. We suggest that, where possible, more emphasis should be placed on the environment in molecular behavioural genetics to identify individuals at environmental high risk in addition to genetic high risk. Sequencing should be used to identify rare and alternative variation that may act as a risk factor, and a systems biology approach including gene–gene interactions and pathway analyses would be advantageous. GWAS may require even larger samples with reliably defined (sub)phenotypes.

Type
Review Article
Copyright
Copyright © Cambridge University Press 2012

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