Summary: Polygenetic risk scores calculated from adults can be used to identify children and adolescents who may be at greater risk of developing depression, even before clinical symptoms have emerged. Source: Max Planck Institute An international team led by Munich-based researchers have found a genetic score that reliably predicts in youths who will have depression, the severity of the depression and the age of onset. Furthermore, an additive effect was seen in the youths who had experienced childhood abuse. According to the World Health Organization, depression is now the leading cause of disability, globally affecting over 300 million people. Depression occurs through the interplay between biological, psychological and social factors. Although depression can happen at any age, it often first emerges during adolescence. Identifying the risk factors for depression before clinically interfering symptoms arise is crucial for effective and targeted prevention strategies. A study now published by a team from the Max Planck Institute of Psychiatry and the LMU Medical Center in collaboration with researchers from Emory University, Atlanta, USA, University of Coimbra, Portugal and University of Helsinki, Finland, brings us a step closer to being able to prevent depression in youths. The team investigated whether the genetic scores from adult studies can also be applied to predict if children and adolescents will have depression, the severity of depression and the age of onset of the disease. Researchers used a relatively new method of calculating the genetic risk of depression. Traditional genetic studies focus on one genetic difference at a time and how it associates with risk of disease. In this study, information from many genetic variants associated with depression identified in a sample of over 460,000 adults was used to create a score of the aggregated genetic risk for depression, or a so-called polygenic risk score. Individually, these variants have little impact on risk, but when taken together they can reveal hidden disease risk thus generating a much clearer picture. The method has already been successfully used to look at the genetic risk for many common diseases such as heart disease or diabetes. The first author of the study, Thorhildur Halldorsdottir from MPI explains what she did in more detail: “The score is first calculated from genetic data gathered in the past year from a huge number of adults with depression. This score was then applied to see if it could predict depression and symptoms of depression in smaller cohorts of children and adolescents”. In another aspect of the study, she investigated the impact of an environmental factor, childhood abuse, which has been found to predict depression. Halldorsdottir adds: “We also looked to see how a history of childhood abuse affected the risk. We found that both the polygenic risk score and exposure to childhood abuse were informative in identifying youth at risk for depression”. Max Planck director and head of the department carrying out this research, Elisabeth Binder summarizes: “This is the first study to show that the polygenic risk score calculated from adults with depression can be used to identify those children at risk of developing depression before any clinical symptoms have emerged”. Researchers used a relatively new method of calculating the genetic risk of depression. Traditional genetic studies focus on one genetic difference at a time and how it associates with risk of disease. The image is in the public domain. Effective psychological and pharmacological interventions for depression are already well known. A combined approach of these interventions has been found to be most effective. Unfortunately, these interventions are not feasible within the realms of public health, in part due to lack of resources. Director and Chair of the Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy at the LMU University Hospital and co-investigator of the study, Gerd Schulte-Körne adds: “In the future, by applying the findings of studies like this one, it would be possible to target youth at the greatest risk for depression, i.e., those with a high polygenic risk score and/or history of childhood abuse, for these effective interventions.” Binder concludes: “There is still a lot of work that needs to be done to perfect the early identification of youth at risk for depression. However, knowing which children are more likely to go on to develop depression would give us the opportunity to implement effective prevention strategies and reduce the huge burden of depression”. [divider]About this neuroscience research article[/divider] Source: Max Planck Institute Media Contacts: Anke Schlee – Max Planck Institute Image Source: The image is in the public domain. Original Research: Closed access Thorhildur Halldorsdottir, Charlotte Piechaczek, Ana Paula Soares de Matos, Darina Czamara, Verena Pehl, Petra Wagenbuechler, Lisa Feldmann, Peggy Quickenstedt-Reinhardt, Antje-Kathrin Allgaier, Franz Joseph Freisleder, Ellen Greimel, Tuomas Kvist, Jari Lahti, Katri Räikkönen, Monika Rex-Haffner, Eiríkur Örn Arnarson, W. Edward Craighead, Gerd Schulte-Körne, Elisabeth B. Binder “Polygenic Risk: Predicting Depression Outcomes in Clinical and Epidemiological Cohorts of Youth”. American Journal of Psychiatry doi:10.1176/appi.ajp.2019.18091014 AbstractSee alsoFeaturedNeuroscience·April 1, 2020How the novel coronavirus binds to human cells Polygenic Risk: Predicting Depression Outcomes in Clinical and Epidemiological Cohorts of Youth Objective: Identifying risk factors for major depression and depressive symptoms in youths could have important implications for prevention efforts. This study examined the association of polygenic risk scores (PRSs) for a broad depression phenotype derived from a large-scale genome-wide association study (GWAS) in adults, and its interaction with childhood abuse, with clinically relevant depression outcomes in clinical and epidemiological youth cohorts. Methods: The clinical cohort comprised 279 youths with major depression (mean age=14.76 years [SD=2.00], 68% female) and 187 healthy control subjects (mean age=14.67 years [SD=2.45], 63% female). The first epidemiological cohort included 1,450 youths (mean age=13.99 years [SD=0.92], 63% female). Of those, 694 who were not clinically depressed at baseline underwent follow-ups at 6, 12, and 24 months. The replication epidemiological cohort comprised children assessed at ages 8 (N=184; 49.2% female) and 11 (N=317; 46.7% female) years. All cohorts were genome-wide genotyped and completed measures for major depression, depressive symptoms, and/or childhood abuse. Summary statistics from the largest GWAS to date on depression were used to calculate the depression PRS. Results: In the clinical cohort, the depression PRS predicted case-control status (odds ratio=1.560, 95% CI=1.230–1.980), depression severity (β=0.177, SE=0.069), and age at onset (β=−0.375, SE=0.160). In the first epidemiological cohort, the depression PRS predicted baseline depressive symptoms (β=0.557, SE=0.200) and prospectively predicted onset of moderate to severe depressive symptoms (hazard ratio=1.202, 95% CI=1.045–1.383). The associations with depressive symptoms were replicated in the second epidemiological cohort. Evidence was found for an additive, but not an interactive, effect of the depression PRS and childhood abuse on depression outcomes. Conclusions: Depression PRSs derived from adults generalize to depression outcomes in youths and may serve as an early indicator of clinically significant levels of depression. 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