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Imaging technology may diagnose melancholic depression

In the brain, low levels of the inhibitory transmitter GABA and high levels of the excitatory neurotransmitter glutamate appear to be strongly associated with a particular type of depression, according to a study by Yale researchers.
The findings were made using proton magnetic resonance spectroscopy to observe the levels of GABA and glutamate in 38 healthy persons and 33 subjects with major depressive disorder. From Yale University:
Imaging technology may be used to diagnose melancholic depression

In the brain, low levels of the inhibitory transmitter GABA and high levels of the excitatory neurotransmitter glutamate appear to be strongly associated with a particular type of depression, according to a study by Yale researchers.

The findings were made using proton magnetic resonance spectroscopy to observe the levels of GABA and glutamate in 38 healthy persons and 33 subjects with major depressive disorder. The study is published in the Archives of General Psychiatry.

Author Gerard Sanacora, assistant professor of psychiatry at Yale School of Medicine and director of the Yale Depression Research Program, said the reductions in cortical GABA and increased glutamate were particularly associated with the presence of melancholic and psychotic features in patients with major depressive disorder. Melancholia is a relatively common form of depression marked by insomnia, loss of appetite, and loss of pleasure.

”Depressed subjects with melancholic features appear to have the largest and most consistent GABA reductions,” Sanacora said. ”This appears to be especially clear in the subset of melancholic subjects who also have psychotic features. In contrast, normal or near normal GABA concentrations were found in the majority of atypically depressed subjects.”

Sanacora said the findings add to mounting evidence suggesting that in addition to the monoaminergic systems (serotonin and norepinepherine), both the GABA and glutamate systems also contribute to the pathophysiology and treatment of mood disorders. By demonstrating that the abnormalities are limited to a subset of depressed subjects, these results may ultimately help doctors make more accurate diagnoses that could more effectively guide treatment planning.

”At the moment, we have limited ability to predict how a patient will respond to one treatment for depression compared to another,” he said. ”We are very interested in exploring the usefulness of these and other biological markers in identifying various subtypes of depression and predicting specific treatment responses.” The work was supported by The Patrick and Catherine Weldon Donaghue Medical Research Foundation, the National Alliance for Research in Schizophrenia and Depression, and the National Institute of Mental Health.




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