Combining DNA methylation features and clinical characteristics predicts ketamine treatment response for PTSD.
Amir Valizadeh, John D Roache, Xinyu Zhang, Ying Hu, Ralitza Gueorguieva, Lynnette A Averill, Mohini Ranganathan, Zuoheng Wang, Douglas E Williamson, Paulo R Shiroma, Matthew J Girgenti, Ismene L Petrakis, Argelio L López-roca, Stacey Young-McCaughan, Terence M Keane, Alan L Peterson, Chadi G Abdallah, John H Krystal, Ke Xu
iScience January 16, 2026 DOI: 10.1016/j.isci.2025.114445 via PubMed
Summary
AI-generated from the abstractPost-traumatic stress disorder varies greatly in its clinical and biological features, making treatment difficult. The largest randomized trial of ketamine for PTSD found no overall benefit over placebo, highlighting the need to identify which patients might respond. Using pre-treatment blood DNA methylation profiles and clinical data from that trial, machine learning models predicted treatment response. A model based on 1,208 methylation sites outperformed models using only clinical variables, and combining both data types improved accuracy further. The methylation-derived score identified responders with 92.9% accuracy. Predictive methylation sites were near genes involved in glutamatergic signaling, immune regulation, and known PTSD risk loci, suggesting peripheral DNA methylation patterns can guide precision pharmacotherapy for PTSD.
Study at a glance
| Characteristics | Randomized controlled trial Peer reviewed |
|---|---|
| Population | Participants in the CAP-ketamine trial with PTSD |
| Keywords | Mental state Precision medicine Psychiatry |
| Citations | 2 |
| Key finding | Peripheral DNA methylation patterns can identify individuals likely to benefit from ketamine for PTSD, with a methylation-derived score achieving 92.9% accuracy in distinguishing responders. |
Abstract
Post-traumatic stress disorder (PTSD) exhibits extensive clinical and biological variability, making treatment challenging. The Consortium to Alleviate PTSD (CAP)-ketamine trial, the largest randomized study of ketamine for PTSD, found no overall benefit of ketamine over placebo, underscoring the necessity to identify responsive subgroups. Using pre-treatment blood DNA methylation profiles and clinical measures from the CAP-ketamine trial, we applied machine learning to predict treatment response. A model based on 1,208 methylation sites achieved higher predictive accuracy than models using clinical variables alone, and combining both data types further improved performance. The methylation-derived score distinguished responders with 92.9% accuracy. The predictive CpGs were enriched near genes involved in glutamatergic signaling and immune regulation, as well as established PTSD risk loci. These findings suggest that peripheral DNA methylation patterns can identify individuals likely to benefit from ketamine, advancing precision approaches to PTSD pharmacotherapy.