Staff and Researcher Publications

Language

English

Publication Date

1-16-2026

Journal

iSicnece

DOI

10.1016/j.isci.2025.114445

PMID

41561376

PMCID

PMC12814687

PubMedCentral® Posted Date

12-17-2025

PubMedCentral® Full Text Version

Post-print

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.

Keywords

psychiatry, precision medicine, Mental state

Published Open-Access

yes

Additional Files
fx1 (1).jpg (307 kB)
Graphical Abstract
Download

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.