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

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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Publication Details

Journal
iScience
Published
2025-12-17
DOI
https://doi.org/10.1016/j.isci.2025.114445
Citations
1
Primary Topic
Treatment of Major Depression
Type
article
Field-Weighted Citation Impact
1.39
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Combining DNA methylation features and clinical characteristics predicts ketamine treatment response for PTSD

1 citations
iScience
Treatment of Major Depression
1.39
article

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

article en
1 citations

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.

iScienceVol. 29(1)
Boston University (US), Michael E. DeBakey VA Medical Center (US), Duke University (US), Baylor College of Medicine (US), Yale University (US), VA Connecticut Healthcare System (US), National Center for PTSD (US), Central Texas Veterans Health Care System (US), Minneapolis VA Health Care System (US), Durham VA Health Care System (US), University of Minnesota Medical Center (US), National Cancer Institute (US), South Texas Veterans Health Care System (US), The University of Texas at San Antonio (US), Joint Base San Antonio (US)
Good health and well-being
Openalex Percentile: Top 13%
Treatment of Major Depression
1.39
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Combining DNA methylation features and clinical characteristics predicts ketamine treatment response for PTSD · iScience (2025) | TGRS Research Map | TGRS