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Medical News Today: Brain scans could identify children at high depression risk


In 2014, approximately 15.7 million adults in the US experienced at least one episode of major depression in the past year. But in a new study, researchers reveal how brain scans could be used to identify children at high risk for later-life depression – information that could pave the way for early intervention and prevention.
[A sad little girl looking out the window]
Researchers suggest brain scans could be helpful in identifying children at high risk for later-life depression.

Study coauthor John Gabrieli, the Grover M. Hermann professor in health sciences and technology and a professor of brain and cognitive sciences at Massachusetts Institute of Technology (MIT), and colleagues publish their findings in the journal Biological Psychiatry.

The authors point out that a person who experiences a first episode of depression is significantly more likely to experience another, emphasizing the importance of early intervention.

“If you can avoid that first bout, maybe it would put the person on a different trajectory,” says Gabrieli.

In previous studies analyzing the brains of adults with depression, researchers have identified abnormal activity in certain regions, particularly the subgenual anterior cingulate cortex (sgACC) and the amygdala – a region involved in emotion processing – compared with healthy controls.

It has been unclear, however, whether these patterns of brain activity occur as a result of depression or whether they are a cause of the condition.

Gabrieli and colleagues set out to investigate the issue further with this latest study, using functional magnetic resonance imaging (fMRI) to scan the brains of 43 children without depression aged 8-14 years.

Of these children, 27 were at high risk for depression due to a family history of the condition, while 16 had no family history of depression.

High-risk children had brain activity similar to adults with depression

The team analyzed the brain scans for signs of synchronized activity between different brain regions during a state of rest; they explain that this allowed them to identify natural communication between regions because the children’s minds were not focused on other tasks.

The scans identified different brain activity patterns among children at high risk for depression, compared with controls. Specifically, they found high-risk children had much stronger synchronization between the sgACC and the default network mode, which are brain regions that are most active during a resting state.

What is more, high-risk children were found to have overactive connectivity between the amygdala and the inferior frontal gyrus – a region involved in language processing – while lower-than-normal connectivity was identified in the frontal and parietal cortexes, which are areas crucial to thinking and decision-making.

Interestingly, the team found that the brain activity patterns seen among children at high risk for depression are very similar to the patterns seen in the brains of adults with depression.

Commenting on the importance of this finding, Ian Gotlib, a psychology professor at Stanford University, CA, who was not involved with the study, says:

“The findings are consistent with an explanation that this is contributing to the onset of the disease. The patterns are there before the depressive episode and are not due to the disorder.”

As such, the researchers suggest that fMRI could be used to identify children who may be at high risk for depression, even those who do not have a family history of the condition.

“We’d like to develop the tools to be able to identify people at true risk, independent of why they got there, with the ultimate goal of maybe intervening early and not waiting for depression to strike the person,” says Gabrieli.

Medical News Today recently reported on a study suggesting childhood poverty may be associated with depression-related brain changes.

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