Scientists from Sweden, Denmark, and Germany have created a genetic test using polygenic risk scores to help predict which antidepressants and anti-anxiety medications will work best for individuals. The approach, tested on research databases, could reduce the trial-and-error process that affects nearly half of patients with depression or anxiety. Lead researcher Professor Fredrik Åhs envisions a future with cheap, effective tests to speed up relief for millions.
Depression affects around 300 million people worldwide, while anxiety impacts 301 million, together reaching nearly 8% of the global population. Yet, finding effective treatment often involves frustration, as nearly half of patients experience little benefit from their first prescribed medication, requiring weeks or months of adjustments.
A team led by Professor Fredrik Åhs from the Department of Psychology and Social Work at Mid Sweden University, in collaboration with researchers from Germany and Denmark, has developed a promising solution. Their method employs polygenic risk scores (PRS), which analyze DNA variations to estimate a person's response to specific drugs. The project started two years ago when Åhs partnered with Professor Doug Speed from Aarhus University's Center for Quantitative Genetics and Genomics.
Speed, who has refined PRS models over the past decade for disorders like schizophrenia, anxiety, bipolar disorder, and depression, explained the challenge: "The last 10 years, we've been working towards using polygenic risk scores to predict disease. It's very challenging because many diseases are caused by thousands of variations across the genome. It turns out that these polygenic risk scores can predict our response to drugs, which is a bit surprising, but a significant step forward."
The team applied these scores to data from the Swedish Twin Registry, examining 2,515 individuals prescribed medications for depression or anxiety. They found that higher PRS for these conditions correlated with reduced effectiveness of drugs like benzodiazepines and antihistamines. Åhs noted: "We then looked at the polygenic risk scores of these individuals, and it became clear that if you had a higher risk score for depression or anxiety, drugs like benzodiazepine and histamines had a smaller effect. More research is needed, but hopefully, we'll be able to develop accurate tests in the future that can predict which kind of drugs will most likely have an effect on you."
While promising, the study has limitations. It relied on prescription data rather than clinical notes, potentially introducing bias, and was limited to a specific time window. Åhs acknowledged: "The data on the patient's response and nonresponse to different drugs was based on which drugs were prescribed to them, not clinical notes. We can infer a lot from the prescription data, but we can't be sure if there was a slight bias. In other words, we don't know exactly why they changed drugs. Was it because of side effects, lack of remission, or something else? We did compare our results with other studies that used clinical assessment, and they were consistent with ours."
The findings, published in Biological Psychiatry Global Open Science (2025; 5(3):100470), suggest a path toward personalized psychiatry, though clinical trials are needed next. Åhs hopes: "We believe this technology could be used to develop more targeted tests. The long-term goal is a test that doctors can use to choose the right medicine, and looking at our genes is one way of doing it. Hopefully, in the future, we'll have a cheap and effective test that enables us to alleviate people's suffering much faster."