Reversing epigenetic changes with CRISPR/Cas9

This 2018 Chinese review highlighted areas in which CRISPR/Cas9 technology has, is, and could be applied to rewrite epigenetic changes:

“CRISPR/Cas9-mediated epigenome editing holds a great promise for epigenetic studies and therapeutics.

It could be used to selectively modify epigenetic marks at a given locus to explore mechanisms of how targeted epigenetic alterations would affect transcription regulation and cause subsequent phenotype changes. For example, inducing histone methylation or acetylation at the Fosb locus in the mice brain reward region, nucleus accumbens, could affect relevant transcription network and thus control behavioral responses evoked by drug and stress.

Epigenome editing has the potential for epigenetic treatment, especially for the disorders with abnormal gene imprinting or epigenetic marks. Targeted epigenetic silencing or reactivation of the mutant allele could be a potential therapeutic approach for diseases such as Rett syndrome and Huntington’s disease.

Noncoding RNA plays important roles in gene imprinting and chromatin remodeling. CRISPR/Cas9 has been shown to be potential for manipulating noncoding RNA expression, including microRNA, long noncoding RNA, and miRNA families and clusters.

In vivo overexpression of the Yamanaka factors have proven to be able to fully or partially help somatic cells to regain pluripotency in situ. These rejuvenated cells would subsequently differentiate again to replace the lost cell types.”

The last paragraph was described in The epigenetic clock theory of aging as a promising technique:

“To date, the most effective in vitro intervention against epigenetic ageing is achieved through expression of Yamanaka factors, which convert somatic cells into pluripotent stem cells, thereby completely resetting the epigenetic clock.”

The reviewers cited three references for in vivo studies of this technique. Overall, I didn’t see that any of the review’s references were in vivo human studies. “Novel Epigenetic Techniques Provided by the CRISPR/Cas9 System”


The epigenetic clock now includes skin

The originator of the 2013 epigenetic clock improved its coverage with this 2018 UCLA human study:

“We present a new DNA methylation-based biomarker (based on 391 CpGs) that was developed to accurately measure the age of human fibroblasts, keratinocytes, buccal cells, endothelial cells, skin and blood samples. We also observe strong age correlations in sorted neurons, glia, brain, liver, and bone samples.

The skin & blood clock outperforms widely used existing biomarkers when it comes to accurately measuring the age of an individual based on DNA extracted from skin, dermis, epidermis, blood, saliva, buccal swabs, and endothelial cells. Thus, the biomarker can also be used for forensic and biomedical applications involving human specimens.

The biomarker applies to the entire age span starting from newborns, e.g. DNAm of cord blood samples correlates with gestational week.

Furthermore, the skin & blood clock confirms the effect of lifestyle and demographic variables on epigenetic aging. Essentially it highlights a significant trend of accelerated epigenetic aging with sub-clinical indicators of poor health.

Conversely, reduced aging rate is correlated with known health-improving features such as physical exercise, fish consumption, high carotenoid levels. As with the other age predictors, the skin & blood clock is also able to predict time to death.

Collectively, these features show that while the skin & blood clock is clearly superior in its performance on skin cells, it crucially retained all the other features that are common to other existing age estimators.” “Epigenetic clock for skin and blood cells applied to Hutchinson Gilford Progeria Syndrome and ex vivo studies”

An introduction to the study highlighted several items:

“Although the skin-blood clock was derived from significantly less samples (~900) than Horvath’s clock (~8000 samples), it was found to more accurately predict chronological age, not only across fibroblasts and skin, but also across blood, buccal and saliva tissue. A potential factor driving this improved accuracy in blood could be related to the approximate 18-fold increase in genomic coverage afforded by using Illumina 450k/850k beadarrays.

It serves as a roadmap for future clock studies, pointing towards the importance of constructing tissue or cell-type specific epigenetic clocks, to more accurately measure biological aging in the given tissue/cell-type, and therefore with the potential to be more informative of disease-risk or the success of disease interventions in the tissue or cell-type of interest.” “Epigenetic clocks galore: a new improved clock predicts age-acceleration in Hutchinson Gilford Progeria Syndrome patients”

A mid-year selection of epigenetic topics

Here are the most popular of the 65 posts I’ve made so far in 2018, starting from the earliest:

The pain societies instill into children

DNA methylation and childhood adversity

Epigenetic mechanisms of muscle memory

Sex-specific impacts of childhood trauma

Sleep and adult brain neurogenesis

This dietary supplement is better for depression symptoms than placebo

The epigenetic clock theory of aging

A flying human tethered to a monkey

Immune memory in the brain

The lack of oxygen’s epigenetic effects on a fetus

A disturbance in the paradigm of child abuse

The principal way science advances is through the principle Einstein expressed as:

“No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”

Members of the scientific community and of the public should be satisfied that the scientific process is working well when hypotheses are discarded due to nonconfirming evidence. Researchers should strive to develop evidence that rejects paradigms, and be lauded for their efforts.

The opposite took place with this 2018 commentary on two studies where the evidence didn’t confirm current biases. I curated one of these studies in DNA methylation and childhood adversity.

The commentators’ dismissive tone was set in the opening paragraph:

“Is early exposure to adversity associated with a genetic or an epigenetic signature? At first glance, two articles in this issue -..and the other from Marzi et al., who measured genome-wide DNA methylation in a prospective twin cohort assessed at age 18 – appear to say that it is not.”

The two commentators, one of whom was a coauthor of Manufacturing PTSD evidence with machine learning, went on to protect their territory. Never mind the two studies’ advancement of science that didn’t coincide with the commentators’ vested interests.

My main concern with the study was that although the children had been studied at ages 5, 7, 10, 12, and 18, the parents had never been similarly evaluated! The researchers passed up an opportunity to develop the parents as a F0 generation for understanding possible human transgenerational inherited epigenetic causes and effects.

The study focused on the children’s intergenerational epigenetic effects. However, animal studies have often demonstrated transgenerational effects that skip over the F1 generation children!

For example: “Considering the Genetic and Epigenetic Signature of Early Adversity Within a Biopsychosocial Framework” (not freely available)

An evolutionary view of stress and cancer

This 2018 Michigan review subject was cancer evolution:

“Based on the fact that cancer typically represents a complex adaptive system, where there is no linear relationship between lower-level agents (such as each individual gene mutation) and emergent properties (such as cancer phenotypes), we call for a new strategy based on the evolutionary mechanism of aneuploidy [abnormal number of chromosomes] in cancer, rather than continuous analysis of various individual molecular mechanisms.

Cancer evolution can be understood by the dynamic interaction among four key components:

  1. Internal and external stress;
  2. Elevated genetic and non-genetic variations (either necessary for cellular adaptation or resulting from cellular damages under stress);
  3. Genome-based macro-cellular evolution (genome replacement, emergent as new systems); and
  4. Multiple levels of system constraint which prevent/slow down cancer evolution (from tissue/organ organization to the immune system interaction).

Since the sources of stress are unlimited and unavoidable (as they are required by all living systems), there are large numbers of gene mutations / epigenetic events / chromosomal aberrations, such as aneuploidy, that can be linked to stress-mediated genomic variants. Furthermore, as environmental constraints are constantly changing, even identical instances of aneuploidy will have completely different outcomes in the context of cancer evolution, as the results of each independent run of evolution will most likely differ.

Most current research efforts are focusing on molecular profiles based on an average population, and outliers are eliminated or ignored, either by the methods used or statistical tools. The traditional view of biological research is to identify patterns from “noise,” without the realization that the so-called “noise” in fact is heterogeneity, which represents a key feature of cancer evolution by functioning as the evolutionary potential.

Understanding the molecular mechanism (both cause and effect) of aneuploidy is far from enough. A better strategy is to monitor the evolutionary process by measuring evolutionary potential. For example, the overall degree of CIN [chromosome instability] is more predictive than individual gene mutation profile.”

Although I read many abstracts of cancer research papers every week, I usually don’t curate them. I curated this paper because the reviewers emphasized several themes of this blog, including:

  • Further examples of how stress may shape one’s life.
  • How researchers miss information when they ignore or process away variation:

    Studies have demonstrated the importance of outliers in cancer evolution, as cancer is an evolutionary game of outliers. While this phenomenon can provide a potential advantage for cellular adaptation, it can also, paradoxically, generate non-specific system stress, which can further produce more genetic and non-genetic variants which favor the disease condition.”

Epigenetics researchers may benefit from evolutionary viewpoints that incorporate the interactions of stress and “genetic and non-genetic variants.”

Since epigenetic changes require inheritance in order to persist, it would be a step forward to see researchers start “measuring evolutionary potential” of these inheritance processes. “Understanding aneuploidy in cancer through the lens of system inheritance, fuzzy inheritance and emergence of new genome systems”

Common features of autoimmune diseases

This 2018 French review subject was mechanisms of autoimmunity:

“Autoimmune diseases (AIDs) encompass more than 80 distinct chronic disorders characterized by inflammatory reactions that can either be systemic or organ specific. In all cases, the disease development is the consequence of the effects of environmental factors in predisposed individuals.

Most of the genes identified by genome-wide association studies (GWAS) on AIDs are related to immunity. However, functional immune parameters that are commonly dysregulated in AIDs do not necessarily stem from these genetic variants. Rather than performing even larger GWAS, understanding complex traits, such as human diseases, may require meticulous analysis or cell-specific gene networks and take into account not only core genes but also seemingly irrelevant genes that may overall have an impact on the disease.

Treg cell defects have been considered a primary cause of AIDs. However, one could ask whether the Treg cell dysfunction exists before the onset of the disease or is provoked by the inflammatory event induced by the triggering components. The defect of Treg cells generally coexists with the inflammatory processes, suggesting several hypotheses:

  1. The inflammation might develop because of a poor regulation of the immune system,
  2. The Treg cells could become inefficient because of the inflammatory environment, or
  3. A common factor concomitantly leads to both effects.

It is likely that autoimmunity results from a chronic imbalance involving both environmental and intrinsic factors. It is now clear that polygenic explanations did not fulfill expectations and that more efforts are needed to understand how the interplay of environmental clues may have a phenotypic impact.” “Pathophysiological mechanisms of autoimmunity” (not freely available) Thanks to Dr. Julien Verdier for providing a copy.

The epigenetic clock theory of aging

My 400th blog post curates a 2018 US/UK paper by two of the coauthors of Using an epigenetic clock to distinguish cellular aging from senescence. The authors reviewed the current state of epigenetic clock research, and proposed a new theory of aging:

“The proposed epigenetic clock theory of ageing views biological ageing as an unintended consequence of both developmental programmes and maintenance programmes, the molecular footprints of which give rise to DNAm [DNA methylation] age estimators.

It is best to interpret epigenetic age estimates as a higher-order property of a large number of CpGs much in the same way that the temperature of a gas is a higher-order property that reflects the average kinetic energy of the underlying molecules. This interpretation does not imply that DNAm age simply measures entropy across the entire genome.

To date, the most effective in vitro intervention against epigenetic ageing is achieved through expression of Yamanaka factors, which convert somatic cells into pluripotent stem cells, thereby completely resetting the epigenetic clock. In vivo, haematopoietic stem cell therapy resets the epigenetic age of blood of the recipient to that of the donor.

Future epidemiological studies should consider other sources of DNA (for example, buccal cells), because more powerful estimates of organismal age can be obtained by evaluating multiple tissues. Other types of epigenetic modifications such as adenine methylation or histone modifications may lend themselves for developing epigenetic age estimators.”

I’ve previously curated four other papers cited in this review:

The challenge is: do you want your quality of life to be under or over this curve?

What are you doing to reverse epigenetic processes and realize what you want? Do you have ideas and/or behaviors that interfere with taking constructive actions to change your phenotype?

If you aren’t doing anything, are you honest with yourself about the personal roots of beliefs in fate/feelings of helplessness? Do beliefs in technological or divine interventions provide justifications for inactions? “DNA methylation-based biomarkers and the epigenetic clock theory of ageing” (not freely available)