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Depression GWAS Meta-Analysis Uncovers New Loci, Potential Drug Targets

NEW YORK (GenomeWeb) – A new genome-wide meta-analysis of depression has linked more than 100 independent variants to depression.

As depression is partially heritable, a number of genes influence its development. A team led by researchers at the University of Edinburgh combined three large genome-wide association studies into a meta-analysis of more than 807,000 people to tease out additional genetic contributors to the disease. As they reported yesterday in Nature Neuroscience, the researchers linked more than 100 variants and 269 genes to depression, while highlighting links between depression and other traits, the role of prefrontal brain regions, and potential treatment approaches.

"These findings are further evidence that depression is partly down to our genetics," senior author Andrew McIntosh from Edinburgh's Center for Clinical Brain Sciences said in a statement. "We hope the findings will help us understand why some people are more at risk of depression than others, and how we might help people living with depression more effectively in future."

The meta-analysis pooled data from three previous depression GWAS. After eliminating overlapping cases and controls, the meta-analysis included 246,363 cases and 561,190 controls from 23andMe, UK Biobank, and Psychiatric Genomics Consortium cohorts. These cases included individuals with diagnosed major depressive disorder, self-reported depression, and broad depression phenotypes.

In all, the researchers tested the effect of more than 8 million genetic variants on depression to find 102 variants in 101 loci that independently segregated with the condition. In a replication dataset of 414,574 cases and 892,299 controls, 87 variants remained significant.

When the researchers examined the shared architecture between depression and more than 200 other behavioral and disease traits, they noted ties between depression and other mental health conditions like schizophrenia and bipolar disorder, but also between depression and the age at which someone starts smoking and between depression and age at menopause.

They tested causal relationships between depression and these other traits to find a bidirectional relationship between depression and neuroticism. However, when they removed regions harboring both variants used to test the effect of depression on neuroticism and neuroticism on depression, only a putative effective of neuroticism on depression remained, a finding they said made intuitive sense as neuroticism is a stable trait and depression is typically episodic.

Using the MAGMA software package, the researchers homed in on 269 putative genes linked to depression. The most significant of these, they noted, was SORCS3, which is linked to sortilin. Additionally, they found DRD2, which encodes the dopamine receptor D2 subtype; CELF4, which has a role in excitatory neurons; and VRK2, which has been linked to schizophrenia, to be implicated in depression.

Notably, the analysis did not highlight any serotonin-linked genes, which the researchers found surprising, as most antidepressants affect the serotonergic system.

Their analysis did, though, implicate cortical brain regions, particularly the frontal cortex and the anterior cingulate cortex, in depression.

The team also found that of the 269 putative genes tied to depression, 57 interacted with 514 drugs. In particular, they discovered a large number of interactions between the DRD2 gene and a class of drugs that includes typical and atypical antipsychotics.

"Given that current treatments work for only half of those who need them, the study provides some intriguing clues for future research to follow up — for example that biological pathways involved in developing the condition may not be the same as those involved in responding to treatment," Raliza Stoyanova from the Wellcome Trust, which funded the study in part, said in a statement.