Neuroticism Could Lead to Depression, Says Largest-ever Genetic Analysis
News Feb 04, 2019 | by Ruairi J Mackenzie, Science Writer for Technology Networks
Chord diagram of genes significantly associated (P< 2.80 × 10−6) with depression and the second-level Anatomical Therapeutic Chemical classifications to which interacting drugs have been assigned. The width of each line is determined by the number of drugs known to interact with each gene. Credit: Howard et al.
The paper, published in Nature Neuroscience, included evidence from three large datasets held by the UK Biobank, the Psychiatry Genomics Consortium and the privately held genomics research company 23andMe.
Authors identified 87 significant genetic variants associated with depression. Previous studies had identified that underlying genetics accounts for 30-40% of depression’s variance in the population. The new study is the largest of its kind ever conducted, including a meta-analysis of over 800,000 genomic data donors, and over two million people in total. Senior author Professor Andrew McIntosh, of the University of Edinburgh Centre for Clinical Brain Science, commented on the study’s contribution, “These findings are further evidence that depression is partly down to our genetics. 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.”
Statistical technique finds causality
Neuroticism, a tendency to be worried or fearful, is a stable personality trait. It has previously been associated with poorer physical and mental health.
Serotonin genes a curious omission
One of the potential clues that Stoyanova referred to is that whilst the analysis revealed as-yet investigated druggable genes associated with depression, there was an absence of genes related to the serotonergic system. Modulating this system using the SSRI class of drugs, which includes citalopram (Celexa) and fluoxetine (Prozac), is usually the first-choice pharmacologic approach for treating depression, although these drugs fail to be effective for a large number of patients.
This suggests that whilst serotonin-associated genes may be relevant for the treatment of depression, there may be another network of genes responsible for the onset and origin of depression. The authors conclude by highlighting the need to leverage multiple data sources to better explore the pharmacology of depression.