More than 100 independent variants and 269 genes have been linked to depression by scientists in Edinburgh.

The results - from a new genome-wide meta-analysis of depression, published in Nature Neuroscience - highlighted links between depression and other traits, the role of prefrontal brain regions, and potential treatment approaches.

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.

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.

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.

When the researchers examined the shared architecture between depression and more than 200 other behavioural 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.

"These findings are further evidence that depression is partly down to our genetics," senior author Andrew McIntosh from Edinburgh's Centre 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.