The Search for the Best Depression Treatment
Brain scans, blood samples, and other diagnostic tests could one day direct doctors to the best treatments for depression patients and uncover the biological basis of the condition.
Depression affects nearly 15 million American adults every year, but the condition is not well understood and can vary greatly from patient to patient.
When someone is diagnosed with depression, patient and doctor often begin a long trial-and-error process of testing different treatments. Sometimes they work, sometimes they don’t, so patients may try several options before finding the best one. But in the future, a brain scan, blood test, or some combination could help guide doctors to the best drugs, or lead them to suggest talk therapy.
Recently, Emory University researcher Helen Mayberg reported that a PET scan, a commonly used imaging method, can reveal whether a patient will respond better to an antidepressant or cognitive behavioral therapy. And in May, Medscape reported that David Mischoulon of Massachusetts General Hospital presented findings that the amount of a particular protein in the blood of depression patients could indicate whether a patient would do better by adding a form of folic acid to his or her treatment.
A key goal of such research is to distinguish between causes of depression. “The presence of certain biomarkers might give us a clue whether [a particular patient’s] depression is truly biologically driven, or whether it is depression like sadness over an event,” says Mischoulon. “If we can identify people who have these biological bases, it might suggest these patients might do better with medications, as opposed to psychotherapies or meditation.”
According to the World Health Organization, depression is the leading cause of disability globally. Many people do not seek or do not have access to treatment, and among those who do, fewer than 40 percent of depression patients improve with the first type of treatment they try. The problem is not that treatments like antidepressants and cognitive behavioral therapy don’t work, it’s that no one treatment works for every patient. Researchers from many disciplines, from neuroscience to genomics, are studying this complex disorder, which likely represents many different conditions with unique origins and treatments. Large clinical trials to predict a patient’s response to therapy or drugs based on brain or body biomarkers could improve treatment for future patients and perhaps uncover a clearer understanding of depression’s origins.
“You see now a number of big studies on predictive biomarkers,” says Mayberg, who has pioneered pacemaker-like implants as a treatment for severe cases of depression. She’s also involved in a large study of patients who will be treated with antidepressants or cognitive behavioral therapy based on brain scans. “It’s going to be interesting over the next year or two to see how this plays out,” she says. One question will be whether researchers will be able to identify markers that are both unambiguous but also practical to test. Brain scans may be the best place to start, she says, because they focus on the origin of the condition, but once good biomarkers are identified via brain scan, surrogates found in the blood may provide a simpler and more affordable option.
One challenge for researchers is that depression is probably a conglomeration of many diseases, says Madhukar Trivedi, a University of Texas Southwestern researcher heading a large trial that is trying to distinguish patients who respond better to one type of antidepressant compared to another. “There are a lot of subtypes in depression, so any given marker, whether genetic, protein, imaging, or EEG, ends up accounting for only a small percentage of variance for any group of patients,” says Trivedi.
If these researchers are successful, they could dramatically change how depression is treated and perhaps diagnosed. Doctors in the United States use the Diagnostic and Statistical Manual of Mental Disorders, or DSM, to diagnose depression. The diagnoses are largely based on the collection of symptoms presented or described by patients. In May, the head of the National Institute of Mental Health, Thomas Insel, announced that his institution would focus its research in areas other than the categories presented by the DSM. “Patients with mental disorders deserve better,” he said.
Bruce Cuthbert is heading the NIMH’s project to establish new ways of studying mental illness and potentially to improve future versions of the DSM by more precisely identifying the brain abnormalities in various diseases, including depression. The idea behind the project is to map out the genetic, circuit, and cognitive aspects of mental illness and to focus on individual features of disorders instead of clinical diagnoses. It could provide the information necessary to improve the DSM so that it is based on neuroscience and not just collections of symptoms. “In the future, we might define the disorders differently, or we might not. But this project will provide a framework to look at neural systems and how they operate and how that contributes to disease,” says Cuthbert.
Perhaps more immediately, the NIMH project could help researchers tune clinical trials of drugs to the right patients by focusing on discrete symptoms. For example, anhedonia, the inability to feel pleasure or seek pleasure, is a major symptom of depression, but it is also found in other patients, such as those with schizophrenia. By recruiting patients with measurable anhedonia, drug developers may be more likely to succeed in clinical trials than if they focused only on depression patients, says Cuthbert.
The NIMH project could also help to identify biomarkers of depression. “It could give us a structure to look at the pathology through different markers of the disease,” says Trivedi. “The goal is fantastic, but the proof is going to come in doing it.”
Become an MIT Technology Review Insider for in-depth analysis and unparalleled perspective.Subscribe today