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VUMC-led study set to explore risk factors for depression recurrence

Feb. 13, 2020, 9:39 AM

Warren Taylor, MD, MHSc, and colleagues are exploring why older adults who have successfully been treated for depression experience a recurrence within four to five years.
Warren Taylor, MD, MHSc, and colleagues are exploring why older adults who have successfully been treated for depression experience a recurrence within four to five years. (photo by Donn Jones)

by Kelsey Herbers

Almost 60% of older adults who have successfully been treated for depression experience a recurrence within four to five years, but little is known about why this happens or who may be at highest risk.

Backed by nearly $5 million in funding, Vanderbilt University Medical Center researchers are conducting a five-year multisite trial to explore potential methods for predicting which patients may have a worse course of depression or are most vulnerable to recurrent episodes.

The longitudinal study, conducted in collaboration with University of Illinois at Chicago and University of Pittsburgh, will enroll 300 adults over the age of 60 who are in remission from depression. Participants will be followed over two years to assess when depression recurs, how symptoms change over time and what factors may be predictive of a return of depression.

“Depression is insidious. It’s not like you wake up one morning and your ‘check engine’ light is on. Stress can build up, things gradually become harder, and over the course of weeks or months, you’ve now slipped into a serious depression,” said Warren Taylor, MD, MHSc, James G. Blakemore Professor of Psychiatry and lead investigator for the study. “Sometimes, it takes a while before a patient even realizes what is happening.”

Study visits will include an MRI to examine whether changes in the brain are associated with depression recurrence, memory testing to see if accelerated memory problems can be linked to long-term outcomes and clinical assessments to determine whether specific symptoms can serve as flags for impending recurrence.

Participants will also be asked to wear a Fitbit activity tracker at various points in the study to explore how physical activity level plays a role in recurrence.

Quick smartphone surveys to assess mood, symptoms and memory performance at different times of day will also be used to monitor patients outside of clinic visits. This will help determine whether using technology for day-to-day monitoring is viable for evaluating those at higher risk to help uncover early warning signs.

Taylor hopes the study will lead to more personalized treatment plans and earlier interventions for recurrent episodes, which currently can only be predicted based on a patient’s history and reported stress level.

“Right now, we know more about how to get someone better than how to keep someone better. We want to see if there are simple, minimally invasive ways to monitor how people are doing to see if we can find triggers,” he said.

According to Taylor, also director of the Division of Geriatric Psychiatry at VUMC, depression in older adults can be more challenging to treat, as many patients have a lifetime history of depressive episodes and are more prone to medical illness or disability, putting them at higher risk.

Roughly 1 in 20 older adults has a diagnosis of depression, with many first having experienced symptoms in their teens or 20s.

“I always come back to what my patients care about. Once they get better, they become worried about whether they’ll have to go through this again. They ask me how they can avoid it. Beyond advising them to maintain a healthy lifestyle, I don’t have a good answer for them,” said Taylor.

Because depression severity is difficult to measure and bad days are a normal part of life, letting patients know when to be concerned about recurrence is difficult.

“I can’t put a blood pressure cuff on someone and measure their depression, so it’d be nice to have a concrete way of determining an individual’s risk for recurrence. This could guide how we treat people.”

The research is supported by the National Institute of Mental Health (grant MH121620).

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