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Meta-Analysis Ties 44 Loci to Major Depression Risk

NEW YORK (GenomeWeb) – Researchers have linked 44 loci to major depression risk in a new meta-analysis of about half a dozen genome-wide association studies.

According to the National Institute of Mental Health, more than 16 million people in the US, or about 6.7 percent of all adults, were affected by depression in 2016. Though depression risk is thought to be partially heritable, only a few genetic loci have been linked to the condition.

In a new study appearing in Nature Genetics this week, the University of Queensland's Naomi Wray and her colleagues combined data from 135,458 cases and 344,901 controls from different GWAS to tease out 30 novel loci linked to depression. They also combined their genetic findings with functional genomic and clinical data to uncover ties between depression and gene expression in certain regions of the brain as well as between depression and schizophrenia.

"We show that we all carry genetic variants for depression, but those with a higher burden are more susceptible," Wray said in a statement. "We know that many life experiences also contribute to risk of depression, but identifying the genetic factors opens new doors for research into the biological drivers."

The researchers took what they called a "pragmatic approach" for their analysis. To boost their sample size, they included not only cohorts in which cases were traditionally assessed for depression, but also self-reported cases. They reasoned that the benefit of increased sample size would overshadow the variability introduced.

A study appearing in Nature Genetics earlier this month took a similar approach and included people who had sought help for depression symptoms in addition to those who had been clinically diagnosed. That approach linked 17 loci to depression-related phenotypes.

For the new analysis, Wray and her colleagues combined data from the PGC29, Decode, GenScotland, GERA, iPSYCH, UK Biobank, and 23andMe cohorts. They identified 44 independent, statistically significant loci linked to depression, some of which were supported by more than one SNP. Genes near the lead SNPs included OLFM4, NEGR1, RBFOX1, and LRFN5. A gene-wise analysis likewise found 153 significant genes, including ones in the major histocompatibility complex and potentially druggable targets.

The researchers developed a genetic risk score based on these loci to find that increased disease risk correlated with clinical severity.

Wray and her colleagues also compared their findings to bulk tissue mRNA-seq data generated by the Genotype-Tissue Expression project. Brain samples, particularly cortical samples, showed enrichment, they reported. A previous MRI-based study, the researchers noted, implicated the prefrontal cortex and anterior cingulate cortex in major depression.

Additionally, by folding in data from gene expression and methylation quantitative trait locus studies, the researchers noted that 13 depression-linked SNPs appeared to control local gene expression in at least one tissue and nine influenced local methylation.

Pathway analyses, meanwhile, implicated a number of regulatory pathways as well as neuronal morphogenesis, central nervous system neuron differentiation, and voltage-gated calcium channels pathways.

Wray and her colleagues also explored connections between depression and other traits. With a LD score regression approach, they noted an overlap between depression and every other psychiatric condition tested, including schizophrenia. They further reported six shared loci between major depression and schizophrenia.

They also found a link between depression and sleep quality, which, they said, when combined with the importance of sleep and fatigue in major depression, suggests a possible mechanistic relationship.

There were also ties between depression risk and increased BMI and decreased educational attainment.

The researchers said that their results could serve as a jumping-off point for further studies, such as ones looking into the common variant genetic architecture of major depression as well as ones examining whether patients may be stratified into groups with likely better or worse prognosis.