Researchers Identify Depression Recovery Biomarkers Using DBS Device
Alongside AI technology, researchers believe a novel DBS device can detect recovery biomarkers from treatment-resistant depression.
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- A recent study published in Nature with support from the National Institutes of Health (NIH) Brain Research Through Advancing Innovative Neurotechnologies Initiative, otherwise known as the BRAIN Initiative, identified biomarkers that could represent recovering treatment-resistant depression.
“This study demonstrates how new technology and a data-driven approach can refine DBS therapy for severe depression, which can be debilitating,” said John Ngai, PhD, director of the BRAIN Initiative, in the NIH press release. “It’s this type of collaborative work made possible by the BRAIN Initiative that moves promising therapies closer to clinical use.”
According to BMC Psychiatry, approximately 33% of patients with major depressive disorder (MDD) become resistant to standard treatments. Patients with treatment-resistant depression (TRD) do not react to typical antidepressants, including selective serotonin reuptake inhibitors (SSRIs), causing researchers to look for alternative treatment protocols.
Scientists have explored therapies such as ketamine, psilocybin, and deep brain stimulation (DBS) to manage TRD.
In this study, researchers enrolled ten patients with TRD to undergo DBA for approximately six months, starting with the same electrical stimulation and increasing doses once or twice weekly, depending on the patient.
“Nine out of 10 patients in the study got better, providing a perfect opportunity to use a novel technology to track the trajectory of their recovery,” said Helen Mayberg, MD, director of the Nash Family Center for Advanced Circuit Therapeutics at Icahn Mount Sinai in New York City and co-senior author of the study. “Our goal is to identify an objective, neurological signal to help clinicians decide when, or when not, to make a DBS adjustment.”
Based on data from six patients, the investigators recognized a common change in brain activity linked to reduced depression symptoms and improved stability according to patient-reported outcomes (PROs).
Additionally, the researchers noted that AI recognition of changes in electrical signaling could have predicted a major depressive episode in one patient four weeks before clinical interviews detected it.
“This biomarker suggests that brain signals can be used to help understand a patient’s response to DBS treatment and adjust the treatment accordingly,” said Joshua A. Gordon, MD, PhD, director of NIH’s National Institute of Mental Health. “The findings mark a major advance in translating a therapy into practice.”
