How Genetic Testing Can Help Match Patients with Medications

Genetic clues reveal which patients will be helped or harmed by antipsychotics.

Posted Jan 29, 2019

Ravil Sayfullin/Shutterstock
Source: Ravil Sayfullin/Shutterstock

Scientists are tapping individuals’ genetic profiles to learn which patients will respond to antipsychotic medication for schizophrenia.

The pursuit is part of a global shift toward precision medicine—diagnosing and treating illnesses based on a person’s unique genetic makeup. Tailoring psychiatric treatment to individual patients is a critical thread. In the case of schizophrenia, for example, around 30 percent of patients do not respond to antipsychotics. Identifying those patients proactively can prevent them from suffering harmful side effects of the medication and dangerous symptoms of the disorder.

“Normally it’s a bit of a trial and error to determine what drugs patients will respond to,” says Edwin van den Oord, of the Center for Biomarker Research and Precision Medicine at Virginia Commonwealth University. “Schizophrenia and other diseases have additional risks, including the risk of suicide, so the sooner you can improve symptoms for a patient, the better.”

An international team of researchers recently assessed 510 individuals who had experienced psychosis for the first time, measuring symptoms of schizophrenia before and after 12 weeks of antipsychotic medication. The scientists also calculated each patient’s polygenic risk score for schizophrenia—a predictor based on one’s personal DNA sequence. They discovered that polygenic risk scores were linked to how well a patient responded to antipsychotic medication: Lower scores predicted a more successful outcome for three of the four patient groups. The results were published in The American Journal of Psychiatry.

“This will move us toward using risk scores as a tool to predict how responsive patients in a clinic will be to antipsychotics,” says James Kennedy, an expert in pharmacogenetics at the University of Toronto who was not involved in the study. “If the patient is predicted to be a very poor responder, they might get referred to a different kind of treatment, like transcranial magnetic stimulation.”

Previous research has aimed to uncover individual genes responsible for different responses to medication, says lead study author Jianping Zhang, a psychiatrist at Northwell Health. But a polygenic risk score encompasses thousands of variants that contribute to the emergence of a particular trait. “The fundamental principle of looking at one gene at a time is not a good one,” Zhang says. “Antipsychotic medication works on so many places in the brain. If we’re going to figure out how to use genetics to predict treatment response, we need to take into account the many genes at play.”

Despite its advantages, the polygenic risk score explained just 6 percent of the difference in the patients’ symptoms, on average. This seems low, Zhang says, but is actually a valuable signal. In practice, it means that a patient with a low score is twice as likely to respond to medication than a patient with a high score. To be deployed clinically, the score, together with other factors, should explain 50 percent, Zhang says. The first key is to study larger pools of people to further determine which genes contribute to treatment response. The second key is to create an algorithm that combines genetic factors with clinical factors such as gender, race, and medication history, which would create a tool with greater predictive power. No one can be sure of a precise timeline, Zhang says, but he expects the next 10 years to be “prime time for real personalized medicine using genomics.”

However, the polygenic risk score employed by Zhang and his colleagues represents the risk of developing schizophrenia rather than the risk of responding to treatment, van den Oord says. Knowing that the schizophrenia score predicts treatment response is helpful, van den Oord says, but it doesn’t yet measure exactly what it should.

A research team in China approached treatment response to antipsychotics by searching for specific genes. The researchers analyzed more than 3,000 individuals with schizophrenia who were prescribed antipsychotic medication after their first psychotic episode. After assessing patients’ symptoms, they pinpointed which patients experienced the most improvement and the least improvement and sequenced the genomes of those individuals. The scientists found that damaging mutations in genes associated with glutamine transmission were linked to poor treatment outcomes. The results were published in the journal JAMA Psychiatry.

“Genetic differences of glutamine transmitters may have a predictive role in the future,” says senior study author Tao Li, of the West China Hospital of Sichuan University. These genes could also provide a target for drug discovery, Li says.

Schizophrenia is an important focus for precision psychiatry because genetics play a key role in the disorder. Whether one develops schizophrenia or not is 70 to 80 percent attributable to genetic influence, Zhang says, and differences in the response to antipsychotics (although less researched) are estimated to be around 50 percent attributable to genetics. Those numbers signal biological forces at play, which, once harnessed, will hold predictive power. This principle applies to any mental health condition with a strong genetic component, such as bipolar disorder and major depression, Zhang says.

One method of leveraging genetics to predict treatment response has already reached the clinic. The GeneSight Psychotropic test analyzes a DNA sample to produce a treatment recommendation based on how a patient will respond to 56 drugs. The test lists which drugs to take, which drugs to avoid, and whether a patient needs a higher dose.

The test is based on 12 genes, the majority of which are responsible for the way a patient’s liver breaks down medications including antipsychotics and antidepressants. For example, when the liver metabolizes drugs too quickly, the amount of medication that circulates through the bloodstream and reaches the brain may be insufficient. And when the liver metabolizes drugs too slowly, the medication may accumulate in the bloodstream at excessive levels and produce harmful side effects. When the liver metabolizes drugs at a normal pace, the appropriate level of medication reaches the brain to perform its duties. “There’s a lot of genetic variation in how our bodies handle drugs,” Kennedy says.

A recent clinical trial assessed more than 1,100 patients with depression who had not responded to antidepressants. Patients who received the GeneSight test were 30 percent more likely to respond to medication and 50 percent more likely to achieve remission after 8 weeks than those who did not take a genomic test. In another study, although one without a control arm, 1,800 patients with depression who took the GeneSight test experienced a 27 percent improvement in symptoms, on average.

More than 1 million have taken the test worldwide, Kennedy says. The team is addressing two hurdles to expand the product’s use. The first is working to ensure that all forms of insurance cover the test. The second is that doctors, who are often skeptical of adopting a new medication, device, or technology, continue to be educated about the benefits, Kennedy says. Other companies are commercializing similar pharmacogenomic tests, such as the RightMed Test from OneOme and the Genecept Assay from GenoMind.

The first episode of schizophrenia often occurs in a person’s late teens or early twenties. Keeping a patient on track through this pivotal period raises the stakes for prescribers. “When patients are treated by trial and error, and it doesn’t work, they can go off the rails. Schizophrenia can eradicate the upper years of high school. Can you imagine all the skills built in that time? It blows that all apart and that’s a tragedy,” Kennedy says. In addition to avoiding side effects of ineffective medications, including severe muscle stiffness and weight gain, patients who find the right drug are more likely to maintain their social circle, stay in high school, and get into college, Kennedy says. With the right medication, “their life course changes.”

The future of personalized medicine for treatment response rests at the intersection of these different approaches, according to Kennedy. He would like his team to eventually incorporate a polygenic risk score and believes that other teams should add liver enzyme testing. To achieve the overarching goal of developing tools with greater predictive power, Kennedy says, “the two strategies together are the best solution.”

This post has been updated to correct factual inaccuracies related to the GeneSight Test.