How genomics is influencing treatment of depression and other mental health conditions

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Advances in large-scale genome sequencing, data storage, and analysis, combined with extensive scientific research, are accelerating the development of personalised medicine and disease prevention. These advancements are already helping to improve outcomes for patients with chronic diseases such as coronary artery disease and breast cancer. But one of the most prevalent conditions is depression, a debilitating mental illness ranked by the World Health Organization as the leading cause of worldwide disability which impacts approximately one in six people during their lifetime. In this blog, we explore the latest research in genetic causes of depression, and whether precision medicine in this area is on the horizon.

Understanding the genetic causes of depression

Ongoing research is focused on fully understanding the causes of depression. Through twin studies, researchers have identified that depression has a heritable component estimated to be between 30-40%. However, as depression is a heterogeneous condition, it is influenced by many different genetic variants and each individual genetic variant has a very small effect on risk. As a result, researchers need to study very large numbers of individuals to discover the numerous variants that play a role in depression. To overcome this challenge and recruit the large number of participants required to conduct the study, researchers around the world are pooling their resources together, and collaborating with genomic research platforms to onboard patents much faster through their global communities with genomic information.

The Psychiatric Genomics Consortium reported new findings in a paper titled “Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of prefrontal brain regions.” This case-control study compared the genetic information of 246,363 people diagnosed with depression with a control group of 561,190 healthy individuals, to find gene variants that occur more frequently in those with depression. Researchers identified 102 different genetic variants associated with depression. These genetic variants were aggregated to derive the cumulative risk for depression, known as a polygenic risk score. Researchers used the polygenic risk score “to assess the predictive ability of the current genome-wide meta-analysis of depression.”

While these findings are very promising, this is just the beginning of understanding the genetic factors in depression. Researchers emphasise that the different genetic variants only account for 2% of the risk for developing depression. The remaining 98% is influenced by environmental factors and unknown variants which require further research. “That 98% of unknown information is always going to swamp that 2% of known information, and until that balance changes, there is no utility in a genetic test for depression,” says Dr Cathryn Lewis, Professor of Genetic Epidemiology and Statistics at King's College London. You can learn more about her inspiring research in The Genetics Podcast.

We are not yet at the stage to use polygenic risk scores or offer genetic tests at an individual level to predict the risk of depression. However, these large cumulative studies capture useful information that, with more research, will clarify the causal effects of depression. These insights will move us closer to applying research in a clinical setting for better screening, preventative therapies, and precision medicine treatments.

Understanding patient response to treatment

Using genetic variants to personalise treatment of depression is another area of research with huge potential impact. Currently, only one-third of patients with depression respond to the first antidepressant they try, and it can take up to 8 weeks to identify whether or not the antidepressant is working. Personalised treatments offer a way to provide individuals with the most suitable therapies based on their genetic variations.

One study titled Using genetic drug-target networks to develop new drug hypotheses for major depressive disorder by Héléna Gaspar, King's College London, investigated drug-target relationships that could be impacting major depressive disorder (MDD). The study involved examining the causal genetic variants of MDD that are located around “key drug-target hubs” including calcium channels, dopamine, serotonin, histamine, GABA receptors, and estrogen, to identify potential targets for the treatment of depression. This knowledge will help to ensure that patients receive the most appropriate drug to inhibit or enhance the effect of the target. However, the study highlights the challenge of identifying the direction of effect when using data from genome wide association studies, recommending that further research be undertaken before drawing conclusions. The published report states “the relationship between a drug and a phenotype cannot easily be inferred; an association may reflect either a depression-inducing effect or an antidepressant effect. We partially address this issue via imputation and prediction of gene expression, but pharmacological, molecular, and clinical validation will be needed before drawing definitive conclusions. However, we suggest that our findings may represent a source of new therapeutic hypotheses for MDD—a common and currently only partially treatable disorder.”

In the UK, research is being undertaken by the Genetic Links to Anxiety and Depression Study (GLAD). Leader of the GLAD Study and the NIHR Mental Health BioResource, Dr Gerome Breen, states that “by recruiting 40,000 volunteers willing to be re-contacted for research, the GLAD Study will take us further than ever before. It will allow researchers to solve the big unanswered questions, address how genes and environment act together and help develop new treatment options.” This is an interesting study to watch, to hear about the findings. There is no denying that genomics in mental health is advancing at a rapid pace and will help significant numbers of people with personalised treatments and reliable prevention treatments.

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