Examining new personalized and precision psychiatry approaches, a new study in Personalized Medicine in Psychiatry shows that body mass index (BMI), sex of the patient, and symptom profile can be used to determine a personalized treatment that guides antidepressant choice and significantly improves patient outcome.

“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, PhD, VA Palo Alto Health Care System and the Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine.

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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.”

The study found that for both men and women, having a larger BMI than patients of “normal” weight predicted remission for venlafaxine-XR specifically, due to 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.

Click here to read the full press release.

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