TY - JOUR
T1 - Combining DNA methylation features and clinical characteristics predicts ketamine treatment response for PTSD
AU - for the Consortium to Alleviate PTSD
AU - Valizadeh, Amir
AU - Roache, John D.
AU - Zhang, Xinyu
AU - Hu, Ying
AU - Gueorguieva, Ralitza
AU - Averill, Lynnette A.
AU - Ranganathan, Mohini
AU - Wang, Zuoheng
AU - Williamson, Douglas E.
AU - Shiroma, Paulo R.
AU - Girgenti, Matthew J.
AU - Petrakis, Ismene L.
AU - López-Roca, Argelio L.
AU - Young-McCaughan, Stacey
AU - Keane, Terence M.
AU - Peterson, Alan L.
AU - Abdallah, Chadi G.
AU - Krystal, John H.
AU - Xu, Ke
N1 - Publisher Copyright:
© 2025
PY - 2026/1/16
Y1 - 2026/1/16
N2 - 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.
AB - 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.
KW - Mental state
KW - precision medicine
KW - psychiatry
UR - https://www.scopus.com/pages/publications/105026888019
UR - https://www.scopus.com/pages/publications/105026888019#tab=citedBy
U2 - 10.1016/j.isci.2025.114445
DO - 10.1016/j.isci.2025.114445
M3 - Article
C2 - 41561376
AN - SCOPUS:105026888019
SN - 2589-0042
VL - 29
JO - iScience
JF - iScience
IS - 1
M1 - 114445
ER -