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Depression study seeks to predict treatment response

Aug. 27, 2015, 8:59 AM

Treating depressed individuals and figuring out who will and won’t respond to antidepressants is mostly trial and error — much to the frustration of patients and the health care providers who treat them.

But a National Institutes of Health-funded study conducted by Vanderbilt’s Center for Cognitive Medicine in the Department of Psychiatry may shed some light on predicting the response of a group of depressed individuals age 60 and older.

The study, which will include both men and women who are currently depressed and symptomatic, will use magnetic resonance imaging (MRI) to examine the relationship between how different parts of the brain communicate and how these individuals respond to antidepressants.

The findings may someday help predict how individuals respond to treatment with an antidepressant.

Warren Taylor, M.D.

“This is a very personalized approach — trying to understand why some people may respond well to antidepressant medications and why others don’t. We’re looking at differences in how different brain regions communicate in these individuals,” said Warren Taylor, M.D., associate professor of Psychiatry and director of the Mood Disorders Program.

Statistics show about 5 to 10 percent of the population over 60 suffers from depression, Taylor said. The incidence is much higher in the physically ill and in nursing homes, where about 40 to 50 percent of residents are believed to suffer from depression.

Depression is also more common in women than men (60 percent vs. 40 percent), Taylor said. And it’s often unrecognized and untreated in the African-American community, probably because of socioeconomic issues such as access to care.

Past research suggests that vascular disease, such as high blood pressure and heart disease, may contribute to depression in older adults. Also, older adults with depression more frequently have issues with memory and cognition.

Although memory issues may improve with successful antidepressant treatment, in some cases these problems may worsen over time.

The study will be divided into two eight-week sessions. During the first session, the depressed individuals will receive either an antidepressant or a placebo.

After eight weeks, those doing well will transition back to clinical care while those who did not improve will start a different antidepressant for another eight weeks.

“We monitor individuals very carefully during the study to make sure people aren’t getting worse. We hope to see improvement in most participants over the two eight-week periods,” Taylor said.
The study seeks those who are suffering from depression whether or not they are currently being treated.

“Depression in older adults is often linked to stress, and ultimately stress breeds depression,” Taylor said. “And here’s where memory issues get involved again. When people feel their memory isn’t as good as it was, it causes stress, and can lead to depression.”

Other warning signs of depression include being less active; withdrawing from friends and family; fatigue; lack of motivation; and tearfulness. Thoughts of death can also be common.

“You don’t have to be sad to be diagnosed with depression. It’s a very common symptom, but not always present,” Taylor said.

“Depression may present with a sad, low mood or a lack of enjoyment and interest in the world, when people withdraw and nothing brings them pleasure.”

Vanderbilt will be enrolling up to 130 individuals over the next five years.

Taylor said the investigators will be using the MRI to show the structure of the brain and any vascular issues, and also to examine how different parts of the brain communicate with each other.

This information may eventually give investigators clues as to which individuals will respond better to medication.

“If our theories are correct, the next step would be to develop automated ways of determining what treatment would be best for each individ

Other faculty members participating in the study are Neil Woodward, Ph.D., Bennett Landman, Ph.D., and Hakmook Kang, Ph.D.

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