Older adults with late-in-life-depression age biologically older than their chronological peers.

Older adults with depression are actually aging faster than their peers, UConn Center on Aging researchers report.

"These patients show evidence of accelerated biological aging, and poor physical and brain health," which are the main drivers of this association, says Breno Diniz, a UConn School of Medicine geriatric psychiatrist and author of the study, which appears in Nature Mental Health on March 22.

Diniz and colleagues from several other institutions looked at 426 people with late-in-life depression. They measured the levels of proteins associated with aging in each person's blood. When a cell gets old, it begins to function differently, less efficiently, than a "young" cell. It often produces proteins that promote inflammation or other unhealthy conditions, and those proteins can be measured in the blood. Diniz and the other researchers compared the levels of these proteins with measures of the participants' physical health, medical problems, brain function, and the severity of their depression.

To their surprise, the severity of a person's depression seemed unrelated to their level of accelerated aging. However, they did find that accelerated aging was associated with worse cardiovascular health overall. People with higher levels of aging-associated proteins were more likely to have high blood pressure, high cholesterol, and multiple medical problems. The accelerated aging was also associated with worse performance on tests of brain health such as working memory and other cognitive skills.

"Those two findings open up opportunities for preventive strategies to reduce the disability associated with major depression in older adults, and to prevent their acceleration of biological aging," Diniz says.

The researchers are now looking at whether therapies to reduce the number of aged, "senescent" cells in a person's body can improve late in life depression. They are also looking at specific sources and patterns of proteins associated with aging, to see if this might lead to personalized treatments in the future.