Loretta Cochrane has lived with depression for decades. After being diagnosed, she struggled to find a workable treatment plan.
“It’s a guess,” said 46-year-old Cochrane, reflecting on her long search for the right medication. “It’s just been a big guess for 20 years on what to give me. … It’s frustrating because you have to taper off what you’ve been taking, then work your way up to what they hope is a therapeutic dose on something new.”
Without knowing why symptoms occur, the quest to find an effective treatment requires a lot of trial and error. Stanford University professor, LeAnne Williams, says finding the right treatment for depression "involves haphazard improvisation."
“The simplest analogy would be something like having a high temperature,” said Jonathan Flint, MD, professor of psychiatry and biobehavioral sciences at the University of California, Los Angeles (UCLA). “Fever could arise from anything, from a mild infection through to something life-threatening like cancer. So, if I just diagnose you with a fever and prescribe Aspirin to treat it, that clearly isn’t good medicine.”
“We’re in a pretty similar situation when someone comes and says they’re feeling depressed and we end up with a diagnosis of depression,” Flint continued. “We can break it down a bit in terms of severity, but at the moment, we have no way of connecting that diagnostic process with the correct treatment.”
What if we could go deeper?
What if we could use patterns of brain activity, genetic clues, and even specific chemical changes in the body to help find the right treatments at the right time?
Proponents of “precision psychiatry” are trying to do just that.
Precision psychiatry is a new approach to diagnosing and treating mental health disorders. It relies on modern technologies and growing knowledge of the way our brains work to guide clinical decisions.
While it’s still in its early stages, some researchers and clinicians believe that precision psychiatry could potentially change how depression and other psychiatric disorders are defined, diagnosed, and managed.
An emerging frontier in mental health management
Physicians use criteria laid out in the Diagnostic and Statistical Manual (DSM) to diagnose depression and other mental health disorders. The DSM groups each disorder by clusters of definitive signs and symptoms. Most mental health practitioners rely on the DSM criteria, their own observations, and patients’ self-reported experiences to guide their diagnoses and treatment plans.
It’s the most common approach and is generally considered the gold standard for mental health disorders. Because two people with depression can exhibit different symptoms, the DSM guidance takes a polythetic approach —that is, it outlines multiple symptoms to consider in diagnosing patients.
Even so, the complexity of genetic, biological, and social or behavioral factors involved make diagnosis difficult.
To address this and other issues in mental health research and treatment, the U.S. National Institute of Mental Health (NIMH) launched the Research Domain Criteria project (RDoC) in 2009.
RDoC creates a framework for new ways to research mental health. The ultimate goal is to develop a classification system based on the underlying causes of depression and other mental illnesses.
According to the NIMH, the RDoC hopes to figure out whether using a combination of “biology, behavior, and context” in diagnosing mental illnesses will be useful — and lead to better outcomes for people living with mental illness.
Predicting better treatment outcomes
There are early signs that some aspects of the precision psychology approach may already be helping patients.
For example, some researchers are studying whether genetic testing can be used to predict patients’ responses to different medications.
While more research is needed, the approach is already in use at some clinics.
“Earlier this year, my psychiatrist left the practice and I started seeing a new doctor. He recommended a genetic screening test,” said Megan LaFollet, an author and editor who was diagnosed with depression after giving birth to her third child.
“The test revealed a genetic mutation that indicated that my body doesn't produce enough of an enzyme that converts folate to a form that my brain can use” she said. After working with her doctor to help supplement the folate deficiency, LaFollet said she noticed an immediate difference.
“I felt like a whole new person,” she said.
Like LaFollet, Cochrane has also undergone genetic testing to learn which medications may be more likely to work for her.
“Since we’ve done that, my psychiatrist has been able to change my medication — took me off some things, changed some things — and I’m probably having some of the best outcomes I’ve had, in terms of quality of life,” Cochrane said.
With recent advancements in brain imaging, “big data” collection, and other technical fields, there are many different ways precision psychiatry may potentially be able to help patients.
One of the main areas of focus in the RDoC framework is “neural circuitry.” The term refers to the networks that nerve cells use to relay information in your brain.
Leanne Williams, PhD, is one of several researchers who study the role these networks play in depression. She works as a professor at Stanford University, where she directs the PanLab for Precision Psychiatry and Translational Neuroscience.
“Instead of thinking of depression as a one-size-fits-all diagnosis, it’s understanding the way that each person’s brain circuit function is disrupted and how that’s producing particular types of symptoms and experiences,” Williams said.
Under the mainstream approach to diagnosing and treating mental illness, less than a third of people who start on selective serotonin reuptake inhibitors (SSRIs) for depression are helped by the first drug they try.
Using brain scans, Williams’ team has identified potential predictive markers that might help clinicians choose more individualized — and potentially more effective — treatment strategies from the start.
“Instead of going down that whole trial-and-error path, you can jump ahead to something that works,” says Williams.
However, the team’s research is still in the very early stages, so their findings don’t yet have a practical application for most patients. It’s still not clear how well a patient’s biomarkers can be used to choose a specific treatment.
A less costly predictive model would be the use of a symptom clustering approach, and unlike the brain scans, clustering may provide insight into response to individual antidepressant medications.
Holistic approach essential
Many experts in the field believe that there’s value in studying the biological side of mental illness, but some are concerned about whether or not this research will create a practical benefit for people living with depression and other mental illnesses.
Jonathan Rottenberg, PhD, director of the Mood and Emotion Laboratory at the University of South Florida, believes there is value in studying the underlying biological causes of depression. But he warns that too much focus on this area might not lead to better treatments. That means it wouldn’t ultimately lead to better outcomes for the patients.
“While I believe this sort of research must go forward, I'm concerned about putting so many eggs in this basket. Based on the prior track record, it's a huge risk. In the meantime, the effort to find reliable biomarkers consumes a lot of the time, money, and effort that could be spent on other fruitful avenues. And ultimately, there may be little clinical benefit that comes out of this drive," he said.
“At present, precision psychiatry is mostly a dream,” he added. “There are no reliable biomarkers for depression, and the field has been littered with decades of false leads.”
Until more research is available, people living with depression might benefit most from a holistic approach that considers their background and personal experiences.
In a review article published in the Journal of Nervous and Mental Disease, Joel Paris, MD, and Laurence J. Kirmayer, MD, argued that RDoC relies on neuroscience models that are “insufficiently developed.” They also noted that the approach doesn’t fully account for how social interactions and experiences shape people’s mental health and treatment outcomes.
For her part, Williams supports taking an interdisciplinary approach. At the same time, she’s optimistic about the future of precision psychiatry.
The path forward, she suggests, lies in combining knowledge of patients’ lived experiences and social contexts with assessments of their biological functioning. This would provide a clearer overall picture of how depression affects each person individually. In turn, this information and understanding could be used to tailor better treatment programs.
“My hope would be that we don’t think a focus on one aspect is going to be the whole answer,” she said. “If we do have a way to anchor how we understand depression in biology, I think it gives us a richer understanding.”
There’s still more work to be done, she noted. In particular, more research is needed to understand the social risk factors and biological mechanisms that lead to mental illness. Further studies should also explore how to identify reliable biomarkers and then translate that research into clinical practice.
Even if precision psychiatry meets its supporters’ expectations, it may be years before it goes mainstream.
“I think it will be within this generation,” Williams said. “Certainly, what we’re doing, here in my lab and with my collaborators, is setting up a kind of model research clinic to show how that could work.”
NPS-US-NP-00294 MAY 2018