A simple DNA test can reveal which antidepressant is right for you

However, for many, finding the right treatment can be a slow and frustrating process. When patients first seek help, prescribed medications often fail. In fact, nearly half of people treated for depression or anxiety get little or no benefit from their initial prescription, forcing them to try multiple medications over weeks or even months before finding relief.

A new genetic approach to treatment

A research team from Germany, Sweden and Denmark believes they may have found a solution. They have developed a genetic approach that can help doctors predict which antidepressant or anxiety medications will actually work for a particular person.

This method uses what is known as a polygenic risk score (PRS), which analyzes a person’s DNA to assess how their genetic variations affect their response to certain medications. With just one genetic test, scientists can now estimate which drugs are most likely to help an individual patient.

Although this technology has so far only been tested using genetic research databases and not on real patients, the results are promising.

Lead author Professor Fredrik Ahas from the Department of Psychology and Social Work at Sweden’s Med University hopes to take the research into clinical trials soon.

“We think this technology can be used to develop more targeted tests,” Ahas says. “The long-term goal is a test that doctors can use to choose the right drug, and looking at our genes is one way to do that.” “We are interested in looking at biomarkers as well. Hopefully, in the future, we will have a cheap and effective test that will enable us to relieve people’s suffering much faster.”

Building on genetic research from Aarhus University

The project began two years ago when Åhs contacted Professor Doug Speed ​​from the Center for Quantitative Genetics and Genomics at Aarhus University in Denmark. Åhs wanted to apply Speed’s advanced polygenic risk score models to his research on mental health treatment.

Speed ​​has spent years improving methods for analyzing complex human genetic data, with a particular focus on how genes influence psychological states.

“For the past 10 years, we’ve been working on using polygenic risk scores to predict disease,” Speed ​​explains. “It’s very difficult because many diseases are caused by thousands of variations across the genome.” “It turns out that these genetic risk scores can predict our response to medications, which is a bit surprising, but an important step forward.”

He has already developed PRS models for several psychiatric disorders, including schizophrenia, anxiety, bipolar disorder, and depression — all of which were used in this new study.

What are the degrees of genetic risk?

Since mapping the human genome in the early 2000s, scientists have discovered thousands of small differences in DNA that can affect health. Humans have approximately 20,000 genes, each of which comes in multiple versions (known as alleles). Some alleles are associated with a greater likelihood of developing certain diseases.

Researchers like Speed ​​compile this information to create polygenic risk scores — tools that combine the effects of many genetic variations to estimate a person’s risk for certain conditions.

For example, when developing a depression-reduction strategy for depression, researchers analyze a person’s genome to see how many variants associated with depression they carry. The greater the number of risk-related variations, the greater the individual’s genetic risk score. However, some variables have a stronger effect than others.

Twin data reveal how genes influence response to drugs

Genetic risk scores do not diagnose mental illness and instead, they estimate the likelihood of developing one. But it may also help explain why some treatments work better for some people.

To explore this, Aahs and his team applied polygenic risk scores to data from the Swedish Twin Registry, the largest of its kind in the world. This database allows researchers to compare the relative influences of genetics and environment on health and behavior.

Because twins share nearly identical DNA, patterns that appear consistently across pairs of twins often point to genetic causes. Åhs identified 2,515 people from the registry who were prescribed medications to treat depression or anxiety. By examining the medications they used, whether they changed prescriptions, and how their treatment progressed, the researchers were able to infer which medications were most effective.

“We then looked at the polygenic risk scores for these individuals, and it became clear that if you had a higher risk score for depression or anxiety, medications like benzodiazepine and histamine had less of an effect,” Ahas says. “More research is needed, but hopefully we can develop accurate tests in the future that can predict what type of drugs are most likely to have an effect on you.”

Important limitations and next steps

Like most scientific research, the study has some limitations. Åhs explains that although the data set was extensive, it was not perfect.

“The data on a patient’s response and non-response to different medications was based on the medications they were prescribed, not clinical observations,” he says. “We can infer a lot from the prescription data, but we can’t be sure if there is a slight bias.”

“In other words, we don’t know exactly why the medications were changed. Was it because of side effects, lack of recovery, or something else? We compared our results with other studies that used clinical assessment, and they were consistent with our results.”

The researchers also had to limit their analysis to a specific time window, meaning some previous prescriptions may not have been included.

“This may have affected the number of individuals who received only one drug in our study,” Ahas adds. “It is possible that some of them had received other drugs before that that were not captured in our data. This is one of the reasons why we wanted to conduct a clinical follow-up study.”

Toward personalized psychiatry

Although more research is needed, the results suggest a future in which choosing an antidepressant may no longer be based on trial and error. A simple genetic test could one day help doctors match patients to the most effective treatment right from the start — potentially saving time, reducing side effects, and improving the lives of millions around the world.