IIT Kanpur Study Finds Brain-Gut Signals Can Predict Antidepressant Response in Days

Researchers at the Indian Institute of Technology (IIT) Kanpur, working with Ganesh Shankar Vidyarthi Memorial (GSVM) Medical College in Kanpur, have found that combining brain and gut electrical signals with clinical symptoms can predict how a patient will respond to antidepressant treatment within just 7 to 10 days of starting it. That is far sooner than the usual 4 to 6 weeks needed to assess whether a treatment is working.

Depression affects an estimated 5% of adults worldwide and about 4.5% of India's population, the researchers said. More than half of patients do not respond adequately to their first antidepressant, often facing weeks of trial and error before an effective treatment is found. "Our study shows that objective, non-invasive brain and gut signals collected in about the first week of treatment already contain valuable information about treatment response," said Dr. Pragathi Priyadharsini Balasubramani, assistant professor in IIT Kanpur's Department of Cognitive Science and the study's corresponding author.

The study measured brain and stomach electrical activity using electroencephalography (EEG) and electrogastrography (EGG), plus symptom data, in 206 participants, including 144 treatment-naive patients. Signals were recorded at the start of treatment and again about a week later, then compared with outcomes assessed 4 to 6 weeks in. The resulting model identified likely non-responders with 84% sensitivity and 78% specificity; tested on an independent patient group, it reached 77.3% overall accuracy, with 80% specificity and 71.4% sensitivity.

"We found that different symptom profiles were associated with distinct patterns of brain and gut physiology linked to treatment outcomes," said Amal Jude Ashwin Francis, a PhD scholar and the study's first author, adding that recognising these biological subtypes could help explain why patients respond differently to the same medication. The tools used are currently accessible through Neuroclinical Innovative Solutions, which received support from the Biotechnology Industry Research Assistance Council for the project; researchers say larger, more diverse patient groups are needed to validate the approach.