Bit by bit, a growing body of evidence is leading psychiatry toward the goal of being able to treat patients on a highly individualized basis, based on their distinctive biology.

Results of a new study contribute to this move toward “precision medicine,” revealing patterns of functional connectivity in the brain—observable before treatment begins—that correspond with the likelihood that a patient with major depressive disorder will respond to a specific treatment, in this case, the commonly prescribed antidepressant medicine sertraline (Zoloft).

Researchers enrolled 279 people with major depressive disorder, who received functional MRI (fMRI) brain scans prior to treatment and then were assigned to groups that received either sertraline or a placebo for 8 weeks. An additional 38 individuals with no psychiatric symptoms were also scanned, for comparative purposes. The team was led by Madhukar Trivedi, M.D., a 2002 BBRF Independent Investigator and 1992 Young Investigator, and included eight other BBRF grantees.

During the course of treatment, clinicians systematically evaluated changes in individual patients’ depressive symptoms. At the end of the treatment period, patient outcomes were assessed. Researchers then evaluated whether specific brain connectivity patterns aligned with particular outcomes. Analyses of this kind are potential guides to treatment in broader patient populations, if statistical and biological criteria indicate the data are indeed significant—i.e., not merely coincidental.

Scientifically significant patterns—potential biomarkers—were in fact discovered. The discoveries are grounded in results of a type of fMRI scan that visualizes connectivity when the brain is in a non-active or resting state. These scans reveal what researchers call the brain’s default-mode network. In prior research, aberrations within this network, in brain regions involved in processing emotions, executive function, and reward processing, have been associated with major depressive disorder.

No one yet understands why certain patients respond to a given treatment while others don’t. The team was looking for telltale connectivity patterns that corresponded with how different patients fared, depending on whether they received sertraline or placebo. In this set-up, it’s just as relevant to discover patterns of non-response as those corresponding with response, whether to medicine or the placebo.

The team discovered that in general, patients with very strong, or hyper-connectivity within the default mode network were more likely to respond to sertraline. Sertraline responders were also found, in general, to have stronger connectivity between the default-mode network and other networks involved in executive control. Executive control refers to higher brain processes that enable us to process and control our emotions; they include such functions as inhibition, attention, cognitive flexibility, and memory.

Another finding from the study, which was published in the American Journal of Psychiatry, concerned the response to placebo—which has often been found to be large in clinical studies of antidepressant medicines. Placebo response was found to correlate “robustly” with connections between certain networks. Specifically, stronger connectivity between the hippocampus and the executive control network and lower connectivity between the thalamus and the visual and salience networks predicted better outcomes with placebo than with sertraline.

On the basis of these results, the team was able to develop what they called “a composite moderator,” a statistical measure designed to identify the treatment most likely to succeed—importantly, based on resting-state fMRI data obtained before treatment begins. While this work is preliminary, the researchers indicated a number of next steps to bring this work closer to the clinic. They hope to extend the findings to other specific depression treatments; investigate whether there is a relationship between the speed of response, remission rates, and connectivity levels in the brain; and scanning patients after treatment to investigate whether pretreatment connectivity patterns changed over time, with treatment.

The team also included: First author Cherise R. Chin Fatt, Ph.D.; Amit Etkin, M.D., Ph.D., 2012 BBRF Young Investigator; Mary Phillips, M.D., BBRF Scientific Council member, 2017 Colvin Prize winner and 2005 BBRF Independent Investigator; Myrna Weissman, Ph.D., Scientific Council member, 2005, 2001 and 1995 BBRF Distinguished Investigator and 1994 Selo Prize winner; Ramin Parsey, M.D., Ph.D., 2009 BBRF Independent Investigator, 2000 and 1998 Young Investigator; Melvin McInnis, M.D., 1999 BBRF Independent Investigator and 1992 Young Investigator; Patrick McGrath, M.D., 2002 BBRF Independent Investigator; Maurizio Fava, M.D., 1994 BBRF Young Investigator; and Tracy Greer, Ph.D., 2004 BBRF Young Investigator.