Combining DNA methylation features and clinical characteristics predicts ketamine treatment response for PTSD.

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作者:Valizadeh Amir, Roache John D, Zhang Xinyu, Hu Ying, Gueorguieva Ralitza, Averill Lynnette A, Ranganathan Mohini, Wang Zuoheng, Williamson Douglas E, Shiroma Paulo R, Girgenti Matthew J, Petrakis Ismene L, López-Roca Argelio L, Young-McCaughan Stacey, Keane Terence M, Peterson Alan L, Abdallah Chadi G, Krystal John H, Xu Ke
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.

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