The role of DNMT3a in fear memories

This 2018 Chinese rodent study found:

“Elevated Dnmt3a [a DNA methyltransferase] level in the dorsal dentate gyrus (dDG) of hippocampus was associated with the absence of fear renewal in an altered context after extinction training. Overexpression and knockdown of Dnmt3a in the dDG regulated the occurrence of fear renewal in a bi-directional manner.

We found that renewal of remote fear memory can be prevented, and the absence of renewal was concurrent with an elevated Dnmt3a level.

Our results indicate that Dnmt3a in the dDG is a key regulator of fear renewal after extinction, and Dnmt3a may play a critical role in controlling fear memory return and thus has therapeutic values.”


The study was a collection of five experiments investigating causes and effects of biology and behavior. The researchers used different techniques to achieve their goals. I’ve quoted extensively below to show some background and results.

“Alterations in histone acetylation and DNA methylation are involved in the formation and extinction of long-term memory..DNMTs catalyze the cytosine methylation and are required to establish and maintain genomic methylation. Dnmt3a and Dnmt3b are de novo DNA methyltransferases. Dnmt1 is the maintenance DNA methyltransferase.

  1. Dnmt3a expression was elevated in the dDG after extinction training followed by a brief memory retrieval (Rec+Ext), which was associated with the absence of fear renewal when tested in an altered context.
  2. Increasing Dnmt3a expression in the dDG using AAV [recombinant adeno-associated virus] expression led to the prevention of fear renewal following a standard extinction training protocol. 
  3. Knockdown of Dnmt3a in the dDG using CRISPR/Cas9 resulted in fear renewal following Rec+Ext protocol.
  4. Renewal of remote fear memory can be prevented using the Rec+Ext protocol.
  5. The absence of renewal was concurrent with an elevated Dnmt3a level.

Current exposure therapy, although effective in many patients, suffers from the inability to generalize its efficacy over time, or is limited by the potential return of adverse memory in the new/novel contexts. These limitations are caused by the context-dependent nature of extinction which is widely viewed as the biological basis of exposure therapy.

Thus, achieving a context-independent extinction may significantly reduce fear renewal to improve the efficacy of exposure therapy. Our current study suggests that the effectiveness of these approaches, and ultimately the occurrence of fear renewal, is determined by the level of Dnmt3a after extinction training, especially in the dDG.

There are two potential mechanisms underlying extinction, one is erasure or updating of the formed memory, and the other is the formation of a new extinction memory which suppresses or competes with the existing memory in a context-dependent manner. While most studies favor the suppression mechanism in the adult, limited studies do suggest that erasure occurs in the immature animals.

We propose that if Dnmt3a level is elevated with extinction training (such as with Rec+Ext protocol), modification to the existing memory occurs and as a consequence extinction does not act as a separate mechanism or form a new memory; but if Dnmt3a level is unaltered with extinction training, a separate extinction memory is formed which acts to suppress or compete with the existing memory.”


The relevant difference between humans and lab rats is that we can ourselves individually change our responses to experiential causes of ongoing adverse effects. Standard methodologies can only apply external treatments such as exposure therapy and manipulating Dnmt3a levels.

https://www.nature.com/articles/s41598-018-23533-w “Dnmt3a in the dorsal dentate gyrus is a key regulator of fear renewal”

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The purpose of epigenetic mechanisms

The concluding remarks of this 2018 Chinese review were:

“Using heterochromatin as a model, we have reviewed here the mechanisms behind the establishment and maintenance of silent chromatin domains. We conclude that almost every component of the chromatin environment, including DNA elements, RNAs, histones and other chromatin proteins, plays a role in the process of shaping and maintaining epigenetic states.

Epigenetic mechanisms have evolved..to solve the problem of orchestrating the differentiation of cells with the same genome. Just as any stable system must preserve some degree of flexibility, crosstalk and feedback among all elements in the system are mechanistically required.

We emphasize that:

  1. epigenetic information is inherited [from parent cell to child cell] in a relatively stable but imprecise fashion;
  2. multiple cis and trans factors are involved in the maintenance of epigenetic information during mitosis; and
  3. the maintenance of a repressive epigenetic state requires both recruitment and self-reinforcement mechanisms.”


Studies I’ve curated in 2018 whose methodologies may have benefited from investigating multiple epigenetic mechanisms included:

Only DNA methylation:

Only microRNAs:

A review of studies that investigated DNA methylation and microRNAs but not histone modifications:

https://link.springer.com/article/10.1007/s11427-018-9276-7 “Recruitment and reinforcement: maintaining epigenetic silencing” (not freely available)

Genomic imprinting and growth

This 2018 UK paper reviewed genomic imprinting:

“Since their discovery nearly 30 years ago, imprinted genes have been a paradigm for exploring the epigenetic control of gene expression. Moreover, their roles in early life growth and placentation are undisputed.

However, it is becoming increasingly clear that imprinted gene function has a wider role in maternal physiology during reproduction – both by modulating fetal and placental endocrine products that signal to alter maternal energy homeostasis, and by altering maternal energetic set points, thus producing downstream actions on nutrient provisioning.”

“Imprinted genes in the conceptus produce products that alter maternal resource allocation by:

  1. altering the transport capacity of the placenta;
  2. increasing fetal demand for resources by their action on the intrinsic growth rate; and
  3. signalling to the mother by the production of fetal/placental hormones that modify maternal metabolism.”

Other studies/reviews I’ve curated that covered genomic imprinting are:

http://jeb.biologists.org/content/jexbio/221/Suppl_1/jeb164517.full.pdf “Genomic imprinting, growth and maternal-fetal interactions”


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How well do single-mother rodent studies inform us about human fathers?

Two items before getting to the review:

This 2018 Australian review subject was paternal intergenerational and transgenerational transmission of biological and behavioral phenotypes per this partial outline:

“Evidence for non-genetic inheritance of behavioral traits in human populations

  • Intergenerational inheritance modulating offspring phenotypes following paternal exposure to trauma
  • Epigenetic inheritance via the germline following paternal environmental exposures
  • Limitations of research on epigenetic inheritance in human populations

The transgenerational impact of stressful paternal environments

  • Impact of paternal stress on affective behaviors and HPA-axis regulation of progeny
  • Influence of paternal stress exposure on offspring cognition
  • Role of sperm-borne microRNAs in the epigenetic inheritance of stress

Sexually dimorphic aspects of paternal transgenerational epigenetic inheritance”

The review was comprehensive, and filled in the above outline with many details towards the goal of:

“This exciting new field of transgenerational epigenomics will facilitate the development of novel strategies to predict, prevent and treat negative epigenetic consequences on offspring health, and psychiatric disorders in particular.”

The reviewers also demonstrated that current intergenerational and transgenerational research paradigms exclude a father’s child care behavior.


The fact that studies use rat and mouse species where fathers don’t naturally provide care for their offspring has warped the translation of findings to humans. The underlying question every animal study must answer is: how can its information be used to help humans? I asked in A limited study of parental transmission of anxiety/stress-reactive traits:

“How did parental behavioral transmission of behavioral traits and epigenetic changes become a subject not worth investigating? These traits and effects can be seen everyday in real-life human interactions, and in every human’s physiology.

Who among us doesn’t still have biological and behavioral consequences from our experiences of our father’s child care actions and inactions? Why can’t researchers and sponsors investigate these back to their sources that may include grandparents and great-grandparents?

Such efforts weren’t apparent in the review’s 116 cited references that included:

The reviewer in the latter has been instrumental in excluding behavioral inheritance mechanisms from these research paradigms, leading to my questions:

  1. “If the experimental subjects had no more control over their behavioral stress-response effects than they had over their DNA methylation, histone modification, or microRNA stress-response effects, then why was such behavior not included in the “epigenetic mechanisms” term?
  2. How do behavioral inheritance mechanisms fall outside the “true epigenetic inheritance” term when behavioral stress-response effects are shown to be reliably transmitted generation after generation?
  3. Wouldn’t the cessation of behavioral inheritance mechanisms confirm their status by falsifiability as was similarly done with studies such as the 1995 Adoption reverses the long-term impairment in glucocorticoid feedback induced by prenatal stress?”

Translating rodent studies into human mothers’ behavioral transmission of biological and behavioral phenotypes isn’t hampered by the studied species’ traits as it is for human fathers. But sponsors would have to support human research that may not produce politically-correct findings.


http://www.translatingtime.org provides an inter-species comparative timeline. For example, an input of:

  • Species 1: Human
  • Process: Lifespan
  • Location: Whole Organism
  • Days (post-conception): 270
  • Species 2: Mouse

produces a list of event predictions. Note how many significant events occur before humans are born at day 270, assuming everything goes right with our developmental processes! Also, the model predictions for humans end at post-conception day 979, three weeks short of when we celebrate our second birthday.

https://www.nature.com/articles/s41380-018-0039-z “Transgenerational epigenetic influences of paternal environmental exposures on brain function and predisposition to psychiatric disorders” (not freely available) Thanks to Dr. Shlomo Yeshurun for providing a full copy.

Dealing with big data in epigenetic studies

There’s been a long-standing need for tools and mathematical techniques which effectively deal with the large amount of data present in epigenetic studies. Complete experimental conditions and results aren’t accurately described when researchers fail to transform large sets of data into information.

This 2018 Baltimore review/promotional paper described an approach that promised to resolve the following data issues.

1. Epigenetic changes occur in many ways and areas, and they often aren’t isolated from each other:

“Fully characterizing the polymorphic and stochastic nature of DNA methylation requires specification of joint probability distributions of methylation patterns formed by sets of spatially coupled CpG sites.”

2. The absence of DNA methylation or gene expression provide signals that should be processed into information. A study of DNA methylation and age reported this situation as:

“Due to the methods applied in the present study, not all the effects of DNA methylation on gene expression could be detected; this limitation is also true for previously reported results.

The textbook case of DNA methylation regulating gene expression (the methylation of a promoter and silencing of a gene) remains undetected in many cases because in an array analysis, an unexpressed gene shows no signal that can be distinguished from background and is therefore typically omitted from the analysis.”

The current review described the problem as:

“These techniques assign zero probabilities to unobserved methylation patterns despite their biological plausibility, which results in underestimating the true biological heterogeneity of methylation patterns.”

3. A subset of the above is that unknown or random past causes and effects of epigenetic changes aren’t adequately modeled:

“..We demonstrated..that the empirical approach to joint methylation analysis..does not perform well when dealing with highly stochastic methylation data.”


The paper’s approach is tailored for whole genome bisulfite sequencing (WGBS), the “gold-standard experimental technique for studying DNA methylation.” It’s named informME and is publicly available at https://github.com/GarrettJenkinson/informME.

https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-018-2086-5 “An information-theoretic approach to the modeling and analysis of whole-genome bisulfite sequencing data”

This dietary supplement is better for depression symptoms than placebo

This 2018 Italy/UK meta-analysis subject was the use of dietary supplement acetyl-L-carnitine to treat depression symptoms:

“Deficiency of acetyl-L-carnitine (ALC) appears to play a role in the risk of developing depression, indicating dysregulation of fatty acids transport across the inner membrane of mitochondria. However, the data regarding ALC supplementation in humans are limited. We thus conducted a systematic review and meta-analysis investigating the effect of ALC on depressive symptoms across randomized controlled trials (RCTs).

Pooled data across nine RCTs (231 treated with ALC versus 216 treated with placebo and 20 no intervention) showed that ALC significantly reduced depressive symptoms.


In three RCTs comparing ALC versus antidepressants (162 for each group), ALC demonstrated similar effectiveness compared with established antidepressants [fluoxetine (Prozac), duloxetine (Cymbalta), amisulpride (Solian) respectively below] in reducing depressive symptoms. In these latter RCTs, the incidence of adverse effects was significantly lower in the ALC group [79%] than in the antidepressant group.


Subgroup analyses suggested that ALC was most efficacious in older adults..Future large scale trials are required to confirm/refute these findings.”

From the Study selection subsection:

“Studies were excluded if:

  1. did not include humans;
  2. did not include a control group;
  3. did not use validated scales for assessing depression;
  4. did not report data at follow-up evaluation regarding tests assessing depression;
  5. included the use of ALC with another agent vs. placebo/no intervention.”

The Discussion section was informative regarding possible mechanisms of ALC affecting depression, pain, and linked symptoms. Several citations were of a review rather than of the original studies, however.


Research needs to proceed on to investigate therapies that address ultimate causes for depression and pain. Researchers and sponsors shouldn’t stop at just symptoms and symptom relief, notwithstanding the requirement from a statistical point of view for “future large scale trials.”

Here are other acetyl-L-carnitine topics I’ve curated:

https://journals.lww.com/psychosomaticmedicine/Citation/2018/02000/Acetyl_L_Carnitine_Supplementation_and_the.4.aspx “Acetyl-L-Carnitine Supplementation and the Treatment of Depressive Symptoms: A Systematic Review and Meta-Analysis” (not freely available)


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Placebo is better than these drugs

Consider this post a reblog of Neuroskeptic’s informative About that New Antidepressant Study.

“Here’s why the new study doesn’t tell us much new. The authors..conclude that “all antidepressants were more effective than placebo,” but the benefits compared to placebo were “mostly modest.” Using the Standardized Mean Difference (SMD) measure of effect size, Cipriani et al. found an effect of 0.30, on a scale where 0.2 is considered ‘small’ and 0.5 ‘medium.’

The thing is, “effective but only modestly” has been the established view on antidepressants for at least 10 years. Just to mention one prior study, the Turner et al. (2008) meta-analysis found the overall effect size of antidepressants to be a modest SMD=0.31 – almost exactly the same as the new estimate.”


From the comments section:

“I put his data in a Forest plot and ALL of the positive effect[s] by CBT [cognitive behavior therapy] could be explained by publication bias.

Paroxetine was developed in 1975 and FDA approved for MDD in 1992. It was 2017 before we discovered the true data behind suicides in these trials. That is 25 years. The order of SSRI approval is fluoxetine-> sertraline-> paroxetine-> citalopram-> escitalopram. We know from court cases and other efforts that the suicide data for the first three are false.

PhRMA never got serious about studying clinically meaningful subtypes of “depression” so most data in the meta-analysis just bear on a weak construct called “major depression.”

The reality is these drugs do not help depression much (if any) at all – their effect is to numb the emotions in most people.

The only thing worse than Paxil is Paxil withdrawal.”

Another review of the study, Rewarding the Companies That Cheated the Most in Antidepressant Trials, from which this post is titled, had these comments:

“Patients who take part in these drug trials have been on an antidepressant before the trial. They are then put on placebo for 10 days, a so-called washout. Then half the group, now in cold turkey wit[h]drawal, is now put back on a similar drug to what they had 10 days earlier, and the other group gets to continue their Cold turkey withdrawal.

The fact that these studies are just testing relief from abstinence symptoms by taking a similar drug, could explain why there is no effect in children and young adults.

Most people don’t realize that we are talking about statistical significance, and not clinical significance..The so-called significant difference between drug and placebo is approximately two points on the Hamilton depression scale. The difference has to be at least three for either patient or therapist to notice a difference.

According to this study (https://www.ncbi.nlm.nih.gov/pubmed/23357658), changes of three points or less on the HAM-D correspond to ratings of “no change” on clinician‐rated global symptom severity.

What this study has confirmed is that antidepressants can create a totally insignificant difference compared to a placebo pill. The placebo pill is often combined with attention and close follow up with a professional, and this has a very positive effect.”