Dear editor:
Neurostimulation is an increasingly implemented treatment for a range of psychiatric disorders [
[1]
]. Population and disorder specific approaches to brain stimulation continue to be documented, such as the utility of intermittent theta-burst stimulation (iTBS) for post-traumatic stress disorder (PTSD) [[2]
,- Cirillo P.
- Gold A.K.
- Nardi A.E.
- Ornelas A.C.
- Nierenberg A.A.
- Camprodon J.
- Kinrys G.
Transcranial magnetic stimulation in anxiety and trauma-related disorders: a systematic review and meta-analysis.
Brain Behav. 2019; 9e01284https://doi.org/10.1002/brb3.1284
[3]
]. Philip et al., 2019 [[4]
] conducted the first sham-controlled trial of iTBS in Veterans with PTSD, finding statistically significant improvement in social and occupational function, and clinically meaningful, albeit non-significant, reductions in PTSD symptoms following two-weeks of active iTBS treatment. Despite the growing body of literature demonstrating efficacy of iTBS, response variability persists, highlighting the need to identify inter-individual predictors of treatment outcomes [[5]
].Genetic and epigenetic factors may represent biomarkers for the prediction of TMS response. Polymorphisms of two candidate genes, catechol-o-methyltransferase (COMT) and brain-derived neurotrophic factor (BDNF) have been previously identified as moderators of TMS response [
[6]
,[7]
]. Evidence of genotypic moderation implicates the potential for genetic screening in clinical decision making, however the complexity of molecular processes involved in gene expression brings to question whether epigenetic systems further mediate TMS outcomes. Low level magnetic stimulation has been linked to DNA methylation, a regulatory mechanism of gene suppression, in human neural cells [- Jannati A.
- Block G.
- Oberman L.M.
- Rotenberg A.
- Pascual-Leone A.
Interindividual variability in response to continuous theta-burst stimulation in healthy adults.
Clin Neurophysiol : Off J Int Fed Clin Neurophysiol. 2017; 128: 2268-2278https://doi.org/10.1016/j.clinph.2017.08.023
[8]
]. The impact of magnetic stimulation on DNA methylation coupled with evidence of genetic moderation for TMS response warrants the study of whether DNA methylation contributes to TMS treatment response variability observed in clinical samples.To explore the relationship between epigenetic markers (particularly COMT and BDNF methylation) on iTBS treatment response, DNA samples from whole blood were obtained from a subset (n = 23) of Veterans enrolled in Philip et al., 2019 [
[4]
] at baseline and end of two-week double-blind treatment phase. Treatment response was operationalized via change across the following measures obtained at both time points: Clinical Administered PTSD Scale for DSM-5 (CAPS), PTSD Checklist for DSM-5 (PCL-5), Social and Occupational Functioning Assessment Scale (SOFAs), Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q) and Inventory of Depressive Symptomatology Self-Report (IDS-SR). Pyrosequencing across two COMT and three BDNF CpG sites were completed. The average across the COMT and BDNF sites were used to create COMT average and BDNF average scores with positive values representing a reduction in methylation over time and therefore a putative increase in genetic expression, and negative values denoting an increase in methylation and putatively greater genetic suppression.Statistical analyses included a series of linear regressions in which change on each self-report measure was predicted by treatment group (active (n = 11) vs. sham (n = 12)) and change in epigenetic values (Table 1). Additional models controlled for epigenetic interaction effects. The significant benefit of iTBS over sham on change in IDS-SR scores reported by Philip et al., 2019 [
[4]
] was reproduced in the subsample (β = −8.6, p = 0.049) with further significant changes in CAPS (β = −5.9, p = 0.02) and SOFAS (β = 7.2, p = 0.03) scores observed between treatment groups for those participants with epigenetic data. No main effects of change in BDNF average or change in COMT average values were found. However, a crossover interaction was detected in the PSTD model, indicating that for those in the active treatment group, a greater change in COMT average was related to an attenuation of PSTD symptom reduction at the end of the treatment phase when compared to those with lower change in COMT average values (β = 2.9, p = 0.007). Once controlling for this interaction, we saw significant main effects of treatment group (β = −23.3, p = 0.01) and change in COMT average (β = −2.1, p = 0.02). In contrast, within the sham condition, greater change in COMT average was associated with a modest increase in PCL-5 scores over time. Overall, active iTBS treatment and greater change in average COMT values (signifying a reduction in DNA methylation over time) resulted in greater PCL-5 improvement.Table 1Clinical outcomes comparing active iTBS versus sham, using mixed models.
Outcomes: Difference (Post-pre) Those with epigen data (N = 23) | Clinician-Administered PTSD Scale for DSM-5 | PTSD Checklist for DSM-5 | Social and Occupational Functioning Assessment Scale | Quality of Life Enjoyment and Satisfaction Questionnaire | Inventory of Depressive Symptomatology–Self-Report | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Beta | 95%CI | p | Beta | 95%CI | p | Beta | 95%CI | p | Beta | 95%CI | p | Beta | 95%CI | p | ||||||
Group (Active compared to SHAM) | −5.92 | −20.76 | −1.08 | 0.0188 ∗ | −8.71 | −19.54 | 2.13 | 0.11 | 7.19 | 0.71 | 13.67 | 0.0313 ∗ | 0.19 | −0.28 | 0.66 | 0.41 | −8.59 | −17.16 | −0.03 | 0.0494 ∗ |
R2 | 0.24 | 0.12 | 0.20 | 0.03 | 0.17 | |||||||||||||||
Controlling for epigenetic data (N = 23) | Estimate | 95%CI | Pr > |t| | Estimate | 95%CI | Pr > |t| | Estimate | 95%CI | Pr > |t| | Estimate | 95%CI | Pr > |t| | Estimate | 95%CI | Pr > |t| | |||||
Group (Active compared to SHAM) | −5.41 | −10.61 | −0.22 | 0.042 ∗ | −8.52 | −20.20 | 3.20 | 0.14 | 6.07 | −0.68 | 12.82 | 0.08 | 0.16 | −0.34 | 0.65 | 0.52 | −7.79 | −16.62 | 1.04 | 0.08 |
Epigenetic variables∗ | ||||||||||||||||||||
COMT average | −0.20 | −0.68 | 0.29 | 0.41 | −0.15 | −1.25 | 0.94 | 0.77 | 0.39 | −0.24 | 1.02 | 0.21 | 0.01 | −0.04 | 0.05 | 0.77 | −0.43 | −1.25 | 0.40 | 0.29 |
BDNF average | −0.07 | −0.72 | 0.57 | 0.81 | −0.44 | −1.89 | 1.01 | 0.53 | −0.03 | −0.86 | 0.80 | 0.94 | −0.02 | −0.08 | 0.04 | 0.44 | −0.72 | −1.81 | 0.37 | 0.18 |
R2 | 0.26 | 0.14 | 0.28 | 0.08 | 0.26 | |||||||||||||||
Controlling for epigenetic interaction effects (N = 23) | Estimate | 95%CI | Pr > |t| | Estimate | 95%CI | Pr > |t| | Estimate | 95%CI | Pr > |t| | Estimate | 95%CI | Pr > |t| | Estimate | 95%CI | Pr > |t| | |||||
Group (Active compared to SHAM) | −4.27 | −0.15 | 5.34 | 0.36 | −23.39 | −41.28 | −5.49 | 0.0135 ∗ | 0.00 | −12.26 | 12.26 | 1.00 | 0.28 | −0.64 | 1.19 | 0.53 | −12.57 | −26.55 | 1.41 | 0.07 |
Epigenetic variables∗ | ||||||||||||||||||||
COMT average | −0.27 | −1.20 | 0.66 | 0.55 | −2.11 | −3.84 | −0.38 | 0.0199 ∗ | 0.02 | −1.17 | 1.21 | 0.97 | 0.04 | −0.05 | 0.12 | 0.40 | −0.03 | −2.70 | 0.01 | 0.0521 ∗ |
group(active)∗COMTavg | 0.23 | −0.86 | 1.32 | 0.66 | 2.93 | 0.90 | 4.96 | 0.0072 ∗∗ | 0.32 | −1.07 | 1.71 | 0.63 | −0.05 | −0.16 | 0.05 | 0.31 | 1.52 | −0.07 | 3.10 | 0.06 |
BDNF average | 0.24 | −0.69 | 1.17 | 0.60 | −0.96 | −2.69 | 0.78 | 0.26 | −0.76 | −1.95 | 0.42 | 0.19 | −0.04 | −0.12 | 0.05 | 0.41 | −0.54 | −1.90 | 0.81 | 0.41 |
group(active)∗BDNFavg | −1.00 | −2.37 | 0.37 | 0.14 | −0.84 | −3.40 | 1.72 | 0.50 | 1.71 | −0.04 | 3.46 | 0.06 | 0.07 | −0.06 | 0.20 | 0.27 | −1.61 | −3.61 | 0.38 | 0.11 |
R2 | 0.39 | 0.51 | 0.42 | 0.25 | 0.55 |
∗Averages over markers of pre-post differences in methylation %.
Statistical model (∗p < 0.05, ∗∗p < 0.01).
Note: CAPS, SOFAS and QLESQ obtained at the end of every two weeks. PCL-5 and IDS-SR obtained at the end of every week (Data from Phillips et al., 2019).
These findings preliminarily indicate an interaction between epigenetic change in COMT methylation and verum iTBS response, such that an increase in DNA methylation over time was associated with poorer response. These interpretations require caution given the small sample size and relatively narrow assessment of DNA methylation. More comprehensive and costly analytic procedures, such as methylome wide association studies, might serve to better classify the biomarkers implicated in response variability. These caveats aside, to our knowledge this is the first indication of a relationship between iTBS and changes in epigenetic status, indicating novel mechanism(s) related to TMS. Once precise epigenetic markers are identified, they have the potential to inform the development of pharmacological adjuncts that either bolster iTBS response or result in a similar effect. An additional line of inquiry involves the dose-dependent nature of neurostimulation. Philip et al., 2019 [
[4]
] reported the majority of iTBS benefit was observed within the first week of treatment. Earlier and more frequent DNA collection may aid in our understanding of whether epigenetic changes are implicated in the temporal track of treatment response. In summary, epigenetic mechanisms are associated with TMS response variability and therefore may represent a novel target for combined neurostimulation and pharmacological interventions in those with psychiatric disorders.Declaration of interest
The authors declare that there are no known conflicts of interest.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This work was supported by the Center for Neurorestoration and Neurotechnology (N2864–C) from the United States (U.S.) Department of Veterans Affairs , Rehabilitation Research and Development Service , Providence, RI and the National Center of Research Resources to JEM (RR023457). Additional support was provided by Shared Equipment grants (ShEEP) from the Medical Research Service of the Department of Veterans Affairs . The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.
References
- Updated review on the clinical use of repetitive transcranial magnetic stimulation in psychiatric disorders.Neurosci Bull. 2017; 33: 747-756https://doi.org/10.1007/s12264-017-0185-3
- Transcranial magnetic stimulation in anxiety and trauma-related disorders: a systematic review and meta-analysis.Brain Behav. 2019; 9e01284https://doi.org/10.1002/brb3.1284
- 5-Hz transcranial magnetic stimulation for comorbid posttraumatic stress disorder and major depression.J Trauma Stress. 2016; 29: 93-96https://doi.org/10.1002/jts.22065
- Theta-burst transcranial magnetic stimulation for posttraumatic stress disorder.Am J Psychiatr. 2019; 176: 939-948https://doi.org/10.1176/appi.ajp.2019.18101160
- Inter-individual variability in response to non-invasive brain stimulation paradigms.Brain Stimul. 2014; 7: 372-380https://doi.org/10.1016/j.brs.2014.02.004
- Genetic modulation of transcranial direct current stimulation effects on cognition.Front Hum Neurosci. 2016; 10: 651https://doi.org/10.3389/fnhum.2016.00651
- Interindividual variability in response to continuous theta-burst stimulation in healthy adults.Clin Neurophysiol : Off J Int Fed Clin Neurophysiol. 2017; 128: 2268-2278https://doi.org/10.1016/j.clinph.2017.08.023
- Assessing the combined effect of extremely low-frequency magnetic field exposure and oxidative stress on LINE-1 promoter methylation in human neural cells.Radiat Environ Biophys. 2017; 56: 193-200https://doi.org/10.1007/s00411-017-0683-8
Article Info
Publication History
Published online: March 26, 2022
Accepted:
March 22,
2022
Received:
March 10,
2022
Identification
Copyright
© 2022 Published by Elsevier Inc.
User License
Creative Commons Attribution – NonCommercial – NoDerivs (CC BY-NC-ND 4.0) | How you can reuse
Elsevier's open access license policy

Creative Commons Attribution – NonCommercial – NoDerivs (CC BY-NC-ND 4.0)
Permitted
For non-commercial purposes:
- Read, print & download
- Redistribute or republish the final article
- Text & data mine
- Translate the article (private use only, not for distribution)
- Reuse portions or extracts from the article in other works
Not Permitted
- Sell or re-use for commercial purposes
- Distribute translations or adaptations of the article
Elsevier's open access license policy