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Polygenic Risk Scores for Three Psychiatric Disorders Linked to Depression Diagnoses

NEW YORK (GenomeWeb) – Higher genetic risk scores for depression and other psychiatric disorders are associated with an increased risk of a diagnosis of depression within a general population cohort, a new study has found.

A number of genetic loci have been linked to risk of developing major depressive disorder and polygenic risk scores based on these loci are associated with disease risk, but researchers from the Psychiatric Genomics Consortium noted that such tools have not been examined deeply in a general population context.

Researchers led by Aarhus University's Esben Agerbo have now examined whether polygenic risk score for major depression and other psychiatric conditions are associated with a depression diagnosis in a general population using the Danish iPSYCH2012 case-cohort study.

As they reported today in JAMA Psychiatry, the researchers found a link between polygenic liability and first depressive episode. They also noted that polygenic risk scores for bipolar disorder and schizophrenia were also associated with depression, suggesting a genetic overlap between the conditions.

"These results suggest that estimates of genetic liability ascertained using prevalent samples are tapping in to an underlying genetic predisposition for developing depression, not just a predisposition to maintain the disorder once it has been established," the authors wrote in their paper.

For this study, the researchers first randomly selected a subcohort of 30,000 individuals from the iPSYCH2012 study. They then selected individuals from both this subcohort and the full cohort whose first diagnosis of depression was coded as a depressive episode using ICD-10 codes and who had undergone genotyping. Additionally, the researchers focused on individuals with Danish-born parents and who were at least 10 years old and living in Denmark at follow up. In all, this cohort included 34,573 individuals, between the ages of 10 and 31 years old.

They then calculated the individuals' polygenic risk scores for not only major depression, but also for bipolar disorder and schizophrenia using data from recently published genome-wide association studies from the Psychiatric Genomics Consortium.

Each standard deviation increase in polygenic risk score for depression was associated with a 30 percent increase in depression risk, the researchers reported. That is, they noted, that someone whose polygenic risk is one standard deviation more than the average has a 30 percent increased risk of getting a diagnosis of depression by the age of 31.

Additionally, as compared to individuals in the bottom 10 percent of the polygenic risk distribution, individuals in the top 10 percent were 2.55 times more likely to be diagnosed with depression.

The researchers also examined whether a high polygenic risk score for depression was associated with an earlier age of onset, but found only a slight increase.

Likewise, the researchers reported that each standard deviation increase in polygenic risk score for bipolar disorder and schizophrenia was associated with a 5 percent increase and a 12 increase in depression risk, respectively.

The researchers also investigated whether these three polygenic risk scores were associated with disease severity, as based on ICD-10 coding. They noted that there was a suggestive, but not significant, association between polygenic risk score for schizophrenia and depression with psychotic symptoms, which the researchers said made intuitive sense.

These links between genetic risk of bipolar disorder or schizophrenia and depression, the researchers said, could reflect that many individuals with bipolar disorder and schizophrenia are diagnosed with depression early in their illnesses.

Still, the researchers said that as the bipolar disorder and schizophrenia polygenic risk scores were associated with depression — though to a smaller extent than the depression polygenic risk score — this could support the notion that the disorders have a shared genetic etiology.