A new study looks at the genetic makeup of thousands of adults with depression to try to find an accurate way of predicting which children and adolescents may be at risk of developing this mental health problem.
Many factors determine a person's risk of depression, and these include both genetic and environmental factors, such as going through difficult life events or taking medications with certain side effects.
However, while we already know some of the probable risk factors, it is not always easy to predict who is most at risk of depression, especially early on in life.
Recently, researchers from institutions all over the world have joined forces to investigate whether they can find a way of predicting a child or adolescent's risk of depression by analyzing the genetic makeup of adults with depression and coming up with a "map" of likely genetic culprits.
Their efforts, the investigators say, would also make it easier to understand which individuals have more exposure to mental health events before some potentially confounding factors set in.
The researchers hail from the Max Planck Institute of Psychiatry and the Ludwig-Maximilians-Universitaet in Munich, Germany, the Emory University in Atlanta, GA, the University of Coimbra in Portugal, and the University of Helsinki in Finland.
In their study, the researchers calculated polygenic risk score — the quantification of the possible effects of different combinations of genetic variations — using the findings of the Psychiatric Genomics Consortium, which looked at data from more than 460,000 adults.
They now report the results in the American Journal of Psychiatry.
Complex genetic risk score to the rescue
The researchers explain that on an individual basis, the different genetic variants that previous studies have associated with depression do not make a significant difference to the risk of depression. However, cumulatively, they have a substantial effect on this risk.
"The [polygenic risk] score was first calculated from genetic data obtained from a very large number of adults with depression," notes first author Thorhildur Halldorsdottir.
Following this first step, the researchers assessed this risk score in groups of children and adolescents aged 7–18 years, of whom 279 had symptoms of depression and 187 were healthy. The latter acted as the control group.
"This parameter was then evaluated in smaller cohorts of children and adolescents to determine whether it could predict depression and symptoms of depression in this age group," adds Halldorsdottir.
The researchers also looked at the effect of early experiences of abuse on the young participants' mental health, since this is a verified risk factor for depression. Doing this allowed the investigators to show just how important the polygenic risk score is in assessing depression risk.
"We found that both the polygenic risk score and exposure to childhood abuse were informative in identifying young people at risk for depression," notes Halldorsdottir.
The researchers believe that the results of this study and other similar research could, in the future, help mental health experts identify which young people are most at risk of developing depression, allowing them to implement prevention strategies where appropriate.
"By applying the findings of studies like this one, it should be possible in future to target young people who are at greatest risk for depression, i.e., those with a high polygenic risk score and/or a history of childhood abuse, for these effective interventions," says the study's joint lead investigator, Gerd Schulte-Körne.
Co-author Elisabeth Binder calls this "the first study to show that the polygenic risk score calculated from adults with depression can be used to identify [at-risk] children [...] before any clinical symptoms have emerged."
Although Binder admits that the work of finding the best methods of identifying young people at risk of mental health issues does not stop with this study, she believes that this is an important first step toward implementing better preventive strategies more effectively.
"[I]dentifying 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 health burden associated with depression."