Epigenetic and blood markers associated with response to electroconvulsive therapy in patients with depressive disorders
Bibliographic record
Abstract
Electroconvulsive therapy (ECT) is an effective antidepressant treatment. The mechanisms behind the therapeutic effect are not fully understood, and reliable biomarkers for response are needed. Epigenetic modifications, such as DNA methylation (DNAm), can reflect both genetic and environmental impacts; they may shed light on the mechanisms behind treatment effects and they have the potential to inform response prediction. We performed an epigenome-wide association study (EWAS) in peripheral blood from patients before and after ECT in a Norwegian cohort (n = 65). The methylation levels of 12 differentially methylated CpG positions (DMPs) and 18 differentially methylated regions (DMRs) were significantly associated with percent clinical response. In addition, 29 DMPs and 23 DMRs were significantly associated with remission (Montgomery and Åsberg Depression Rating Scale MADRS < 10 post treatment). Two DMRs were also significantly associated with percent response at baseline and four DMRs were significantly associated with remission at baseline (FDR < 0.05). We did not identify any longitudinal (pre-post) changes in DNAm. We further performed the first meta-analysis (n = 99) between ECT cohorts, combining this Norwegian cohort and a German ECT cohort (n = 34). Seven of the DMRs found to be associated with response in the meta-analyses were previously identified in the Norwegian or the German cohort (FDR < 0.05). Methylation risk scores (MS) calculated using DMPs associated with ECT in the Norwegian cohort showed promising association with response to ECT in the German cohort (p = 0.06). Finally, we found increased neutrophil to lymphocyte ratios, calculated from estimated cell proportions, to be associated with remission (p < 0.003) in the Norwegian cohort.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".