Kynurenic Acid Offers Added Value in Predicting ECT Outcomes in Depression

Electroconvulsive therapy (ECT) is among the most effective treatments for severe depression, yet determining who will benefit remains challenging due to the lack of reliable predictors of treatment response. While clinical characteristics such as higher age and psychotic features are associated with increased odds of treatment success, their limited predictive value underscores the need for multimodal prediction models that integrate biological markers. Identifying such predictive biomarkers could facilitate a more personalized treatment strategy, optimize patient selection and increase ECT response rates.

In this prospective cohort study (n = 74), we developed multivariable linear and logistic regression models to assess the predictive value of plasma immune markers and their added contribution to clinical prediction models for ECT outcomes. Depressive symptom reduction was measured using the Inventory of Depressive Symptomatology (IDS-C).

Kynurenic acid (KYNA) emerged as a significant predictor of the percentage symptom reduction and remission after ECT and significantly improved the prediction of response when added to clinical predictors. Subgroup analyses revealed stronger predictive value for KYNA in unipolar depression, males, and patients without comorbid inflammation (i.e., without acute infections or chronic inflammatory disease), suggesting its relevance in specific patient populations.

KYNA shows promise as a predictive biomarker for ECT outcomes. Future research should validate its robustness across diverse cohorts and patient subgroups to enable its clinical integration into personalized treatment strategies.