Patient’s BMI May Help MDs Choose Right Drug for Depression

By Rick Naurert PhD
September 13th, 2022
Medically reviewed by Paul Sietes, MD.

New research suggests personalized and precision psychiatry can guide antidepressant choice and significantly help individuals with depression.

At present, selecting the best antidepressant that will be most effective for a specific person can be a trial and error  process. The new study shows that body mass index (BMI), sex of the patient, and symptom profile can be used to determine a personalized pharmacological treatment.

“We are in the midst of a paradigm shift in the field of psychiatry, to find specific clinical and biological signals that help clinicians and patients decide what is the best treatment,” explained lead investigator Leanne Williams, Ph.D., VA Palo Alto Health Care System and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine.

“This is the shift to incorporate precision medicine approaches to improve outcomes for patients. Our study adds new knowledge to this effort, and does so for two commonly associated chronic conditions, clinical depression, and obesity that need new treatment approaches.

“Our results have the potential for a significant impact on the majority of patients suffering from depression who are seen in primary care and community settings.”

In the study, researchers analyzed data from 659 adults (ages 18-65) with clinical depression who completed the International Study to Predict Optimized Treatment in Depression (iSPOT-D).

They were randomly assigned one of three antidepressants (venlafaxine-XR, sertraline, or escitalopram) and followed for eight weeks of treatment.

Height and weight were recorded and each participant completed the 17-item Hamilton Rating Scale (a self-reported depression inventory) before and after treatment to measure change in depression severity.

Patients who improved so substantially that they were no longer experiencing clinical symptoms were defined as “remitters.”

Researchers found that for both men and women, having a larger BMI than patients of “normal” weight, venlafaxine-XR predicted remission. Investigators believe this is associated with a reduction in physical symptoms, including sleep disturbance, somatic anxiety, and appetite.

Females with higher BMI were likely to remit regardless of medication type and this effect was related to a change in cognitive symptoms, including thoughts of suicide and guilt.

Researchers believe the findings can be immediately applied in primary care and community settings in which most patients are treated. Primary care doctors have access to information regarding patient sex, BMI (weight relevant to height), along with symptoms of depression.

According to lead author Erin Green, Ph.D., “Although these findings require replication, they are ready for ‘prime time’ translation into clinical practice where there are currently no indicators and algorithms available for guiding treatment choice for patients with both depression and obesity.

“The future of psychiatry is in a precision, personalized medicine approach to refining diagnosis and tailoring treatments accordingly.”

According to Williams, the study demonstrates that currently available markers are poised to improve patient outcomes without introducing new costs. “Markers such as BMI are likely to complement others being developed out of neuroimaging and genomics,” she said.

Source: Elsevier Health Sciences/EurekAlert

Photo: Predicted probabilities of remission for each treatment at different levels of body mass index (BMI).Credit: Personalized Medicine in Psychiatry.

Dr. Rick Naurert has over 25 years experience in clinical, administrative and academic healthcare. He is currently an associate professor for Rocky Mountain University of Health Professionals doctoral program in health promotion and wellness. Dr. Naurert began his career as a clinical physical therapist and served as a regional manager for a publicly traded multidisciplinary rehabilitation agency for 12 years. He has masters degrees in health-fitness management and healthcare administration and a doctoral degree from The University of Texas at Austin focused on health care informatics, health administration, health education and health policy. His research efforts included the area of telehealth with a specialty in disease management.