Newly Discovered Imaging Biomarkers Enable Hospitals to Predict Patients’ Response to Antidepressant Therapy

Hospitals can immediately begin using new precision medicine biomarkers to tailor depression treatments to be more effective in a shorter timeframe

Albert Montillo, PhD, was quoted in a UT Southwestern Medical Center news release. Montillo is an assistant professor at the Lyda Hill Department of Bioinformatics and directs the research at the Deep Learning for Precision Health Lab at UT Southwestern.
“In this study, we’re able to explain 48% of the variance in the symptom relief from sertraline, 34% for bupropion and 28% for placebo,” stated Albert Montillo, PhD (above), in a UT Southwestern news release. Noninvasive functional magnetic resonance imaging (fMRI) was conducted in over 300 participants to evaluate changes in brain function while testing two commonly used antidepressant medications. (Photo: UT Southwestern)

Precision medicine research led by the UT Southwestern Medical Center has discovered imaging biomarkers that can predict what response patients will have to antidepressants, allowing for personalized depression treatments that can be applied immediately, according to the researchers. These new biomarkers could enable hospitals to improve patients’ symptoms two to three months earlier than currently possible, reducing risk of complications that can occur while treating severe depression.

Published in Biological Psychiatry, a peer-reviewed journal of the Society of Biological Psychiatry, titled, “Patterns of Pretreatment Reward Task Brain Activation Predict Individual Antidepressant Response: Key Results from the EMBARC Randomized Clinical Trial,” this study used a combination of functional magnetic resonance imaging (fMRI) images, clinical assessments, and demographics to identify biomarkers that were specific to each of the 222 patients included in the study.

These biomarkers were then compared to how each patient responded to two commonly used antidepressants:

  • Sertraline (marketed under the brand name Zoloft), and
  • Bupropion (marketed under brand names Wellbutrin, Forfivo, Aplenzin, Zyban).

Reducing Treatment Time to Reduce Risk of Harm

“The signatures that we found are unique to each antidepressant’s response. Due to the human brain’s inherent complexity, neuroscientists typically find that brain activity can explain 15% of the variance in symptom relief. That would be a significant scientific finding. Twenty percent is huge,” stated Albert Montillo, PhD, in a UT Southwestern news release. Montillo is an assistant professor at the Lyda Hill Department of Bioinformatics and directs the research at the Deep Learning for Precision Health Lab at UT Southwestern Medical Center.

These finding aren’t just preliminary research, they are actionable in and of themselves. “This is a significant advance,” said Madhukar Trivedi, MD, the lead researcher on the project. “It’s noninvasive. It can be and should be used immediately.” Trivedi is Professor of Clinical Psychiatry, and Director of the Center for Depression Research and Clinical Care at UT Southwestern.

Trivedi estimates that using these new precision medicine biomarkers to guide which antidepressants are ordered could reduce the time it takes to effectively treat depression by two to three months. This could reduce the risks that depression could cause during that time frame—risks such as unemployment, loss of important relationships, or even attempts at self-harm.

One of the great benefits of this recent research is that the clinical data used comes from a variety of reputable sources, including:

The sound scientific approach—combined with the high degree to which the study predicted correlation between biomarkers and clinical efficacy of medications—makes these recent findings very important to the psychiatric field. “It’s a clear improvement from the standard prediction approaches currently used,” Trivedi explained. “We have also reached a point where our findings are stable and can provide a pathway for future work.”

Findings Can Be Used Now

According to Montillo, hospitals can use this information immediately to help guide the treatment of clinical depression.  

“The analytical approach we have developed can be readily adapted to identify biomarker signatures and predict outcomes for other treatments of depression, both pharmacological and non-pharmacological,” Montillo said.

Precision Medicine Research into Depression is Expanding

The UT Southwestern study comes at a time when precision medicine research into depression is expanding. The federal National Institute of Mental Health (NIMH) announced a $9 million research study in November 2021 with the goal of enrolling 20,000 women to study genetic risk factors of depression. This study will be the largest of its kind to date.

Genetic epidemiologist Kenneth S. Kendler, MD, a professor in both the Virginia Institute for Psychiatric and Behavioral Genetics at Virginia Commonwealth University and the Department of Psychiatry at the VCU School of Medicine, described the NIMH study as the “largest deeply phenotyped study of depression yet funded.”

Kendler is one of the three lead principals for the NIMH study.

“Depression is a complex condition with many factors, and we need large-scale projects to encompass that complexity to give us a real chance of getting to the underlying causes of major depressive disorder,” Kendler said. “Having a sample of this size allows us to more precisely pinpoint what factors influence how depression manifests.”

Depression presents multiple challenges to hospitals trying to find the best treatment options for their patients. As research into precision medicine treatments for depression continues, hospitals are beginning to see benefits.

UT Southwestern Medical Center’s recent study will be of particular interest to hospitals that offer treatments for depression, as its findings both improve the care that can be provided and can be put into immediate use. Precision medicine treatments for depression will ultimately empower hospitals to provide better care and improve outcomes for this difficult-to-treat psychiatric disease.

—Caleb Williams

Related Information:

Patterns of Pretreatment Reward Task Brain Activation Predict Individual Antidepressant Response: Key Results from the EMBARC Randomized Clinical Trial  

UTSW-led Research Identifies New Imaging Biomarkers That Predict Antidepressant Response

World’s Largest Study of Genetic Risk Factors for Depression Will Enroll 20,000 Women  

Albert Montillo, PhD

Madhukar Trivedi, MD

Kenneth S. Kendler, MD

Interviews With Precision Medicine Movers