An out-of-date review of epigenetic transgenerational inheritance

This December 3, 2019, French review title was “Transgenerational Inheritance of Environmentally Induced Epigenetic Alterations during Mammalian Development”:

“We attempt to summarize our current knowledge about the transgenerational inheritance of environmentally induced epigenetic changes. While the idea that information can be inherited between generations independently of the DNA’s nucleotide sequence is not new, the outcome of recent studies provides a mechanistic foundation for the concept.

The systematic resetting of epigenetic marks between generations represents the largest hurdle to conceptualizing epigenetic inheritance. Our understanding of the rates and causes of epimutations remains rudimentary.

Environmental exposure to toxicants could promote changes in germline cells at any developmental stage, with more dramatic effects being observed during embryonic germ cell reprogramming. Epigenetic factors and their heritability should be considered during disease risk assessment.”


The review showed an inexplicable lack of thorough research. 2017 was its latest citation of epigenetic transgenerational inheritance studies from the Washington State University labs of Dr. Michael Skinner. I’ve curated six of the labs’ 2019 studies!

  1. Transgenerational diseases caused by great-grandmother DDT exposure;
  2. Another important transgenerational epigenetic inheritance study;
  3. The transgenerational impact of Roundup exposure;
  4. Epigenetic transgenerational inheritance mechanisms that lead to prostate disease;
  5. A transgenerational view of the rise in obesity; and
  6. Epigenetic transgenerational inheritance extends to the great-great-grand offspring.

This lack led to – among other items – equivocal statements where current definitive evidence could have been cited. The review was submitted to the publisher on October 31, 2019, and the above studies were available.


The publisher provided insight into the peer review process via https://www.mdpi.com/2073-4409/8/12/1559/review_report:

  • Peer reviewer 1: “Taking into account that this is not my main area of expertise..Do the authors really believe in that?”
  • Peer reviewer 2 provided a one-paragraph non-review.
  • Peer reviewer 3: “The authors are missing a large sector of what types of environmental factors can influence methylation and do not acknowledge that other sources exist.”

The authors responded with changes or otherwise addressed peer reviewer comments.

https://www.mdpi.com/2073-4409/8/12/1559/htm “Transgenerational Inheritance of Environmentally Induced Epigenetic Alterations during Mammalian Development”

An epigenetic clock review by committee

This 2019 worldwide review of epigenetic clocks was a semi-anonymous mishmash of opinions, facts, hypotheses, unwarranted extrapolations, and beliefs. The diversity of viewpoints among the 21 coauthors wasn’t evident.

1. Citations of the coauthors’ works seemed excessive, and they apologized for omissions. However:

  • Challenge 5 was titled “Single-cell analysis of aging changes and disease” and
  • Table 1 “Major biological and analytic issues with epigenetic DNA methylation clocks” had single-cell analysis as the Proposed solution to five of the Significant issues.

Yet studies such as High-Resolution Single-Cell DNA Methylation Measurements Reveal Epigenetically Distinct Hematopoietic Stem Cell Subpopulations were unmentioned.

2. Some coauthors semi-anonymously expressed faith that using current flawed methodologies in the future – only more thoroughly, with newer equipment, etc. – would yield better results. If the 21 coauthors were asked their viewpoints of Proposed solutions to the top three Significant issues of epigenetic clocks, what would they emphasize when quoted?

3. Techniques were praised:

“Given the precision with which DNA methylation clock age can be estimated and evolving measures of biological, phenotype-, and disease-related age (e.g., PhenoAge, GrimAge)..”

Exactly why these techniques have at times produced inexplicable results wasn’t examined, though. Two examples:

  • In Reversal of aging and immunosenescent trends, the Levine PhenoAge methodology estimated that the 51-65 year old subjects’ biological ages at the beginning of the study averaged 17.5 years less than their chronological age. Comparing that to the Horvath average biological age of 3.95 years less raised the question: exactly why did PhenoAge show such a large difference?
  • The paper mentioned the GrimAge methodology findings about “smoking-related changes.” But it didn’t explain why the GrimAge methylation findings most closely associated with smoking history also accurately predicted future disease risk with non-smokers.

Eluding explanations for these types of findings didn’t help build confidence in the methodologies.

4. A more readable approach to review by committee could have coauthors – in at least one section – answer discussion questions, as Reversing epigenetic T cell exhaustion did with 18 experts.

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1824-y “DNA methylation aging clocks: challenges and recommendations”

A GWAS meta-analysis of two epigenetic clocks

This 2019 UK human study conducted a meta-analysis of genome-wide association studies of two epigenetic clocks using 13,493 European-ancestry individuals aged between ten and 98 years:

“Horvath-EAA, described in previous publications as ‘intrinsic’ epigenetic age acceleration (IEAA), can be interpreted as a measure of cell-intrinsic ageing that exhibits preservation across multiple tissues, appears unrelated to lifestyle factors, and probably indicates a fundamental cell ageing process that is largely conserved across cell types.

In contrast, Hannum-EAA, referred to in previous studies as ‘extrinsic’ epigenetic age acceleration (EEAA), can be considered a biomarker of immune system ageing, explicitly incorporating aspects of immune system decline such as age-related changes in blood cell counts, correlating with lifestyle and health-span related characteristics, and thus yielding a stronger predictor of all-cause mortality.

The meta-analysis of Horvath-EAA identified ten independent associated SNPs [single nucleotide polymorphisms], doubling the number reported to date, and highlighted 21 genes involved in Horvath-based epigenetic ageing. Four of the ten Horvath-EAA-associated SNPs are mQTL [methylation quantitative trait loci] for CpGs used in the Horvath/Hannum epigenetic clocks. A possible interpretation of this is that the functional mechanism by which these SNPs influence the rate of biological ageing is via altering methylation levels.

Father’s age at death, a rough proxy for lifespan, was nominally significantly correlated with both EAA measures, and parents’ age at death was additionally correlated with Hannum-EAA. Aside from these, genetic correlations with age-related traits were surprisingly few: it is possible that this could reflect an overly conservative correction for the multiple tests carried out, or low statistical power, rather than a genuine lack of correlations.

Genetic correlation analysis should be restricted to GWAS with a heritability Z-score of 4 or more, on the grounds of interpretability and power, so the Horvath-based results particularly should be interpreted with caution.”


A non-apologetic way to explain the above graphic is that NONE of these 218 “health and behavioral traits” were any more associated with the studied genetic measurements than would be expected by chance!

Fervent believers in the GWAS methodology’s capability to exactly predict individual phenotypes eventually become victims of the scientific method. These GWAS researchers griped about “overly conservative correction, or low statistical power” and other predictable shortfalls, and ended a long limitations statement with:

“While we have identified a number of SNPs and genes significantly associated with EAA, including genes already known to be related to ageing, the analyses presented here fall short of providing a mechanistic explanation for how these variants and genes act to influence biological age.”

Outside of beliefs, it’s hard to understand why research money keeps pouring into the GWAS dead end. If these researchers and their employing institution and sponsors want to make a difference in human lives, they need to get busy in other areas.

These researchers were employed by the same institution that couldn’t be bothered to scrape together six more weeks of funds to study the transgenerational damaging effects of acetaminophen – an analgesic available to billions of people – in Epigenetics research that was designed to fall one step short of wonderful.

https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1008104 “A meta-analysis of genome-wide association studies of epigenetic age acceleration”

Organismal aging and cellular senescence

I’ll curate this 2019 German review through its figures:

“With the discovery of beneficial aspects of cellular senescence and evidence of senescence being not limited to replicative cellular states, a redefinition of our comprehension of aging and senescence appears scientifically overdue.

Figure 1. Current determinants and relevant open questions, marking the processes of aging and senescence as discussed in the text. Aspects represented in green are considered as broadly accepted or scientifically consolidated. Novel aspects that are yet unproven, or are under debate, are highlighted in red.

SASP = senescence-associated secretory phenotype. AASP = putative aging-associated secretory phenotype as suggested in the text.

Figure 2. Theories on the causality and purpose of aging. Graphically summarized are four contrasting concepts crystallized from current evidence addressing the inductive driving force of aging. Apart from a stochastic deleteriome, there are arguments for a pseudo-programmed, programmed or at least partially programmed nature of aging.

Figure 3. Comparative representation of the aging and senescence processes highlighting different levels of interaction and putative sites of interventions.

(1) As discussed in the text, causative mechanisms of aging are still not well understood, however, multiple factors including genetic, epigenetic and stress-related effects seem to have an orchestrated role in the progression of aging. Senescence on the other hand, is seen as a programmed response to different kinds of stressors, which proceed in defined stages. Whether, in analogy, aging also follows a defined program or sequential stages is not known.

(2) Senescence involves autocrine and paracrine factors, which are responsible for a ‘seno-infection’ or bystander effect in neighboring cells. There is currently no direct evidence for a similar factor composition propagating the aging process via a kind of ‘gero-infection’.

(3) Accumulation of senescent cells has been described as a hallmark of aging; however, whether they are a causative factor or a consequence of tissue and organismal aging is still unknown. As discussed in the text, it appears possible that aging and senescence mutually influence each other through positive feedback at this level, leading to accelerated tissue damage and aging.

(4,5) Clearance of senescent or aging cells might constitute putative targets for interventional approaches aimed to reduce or reverse the impact of aging and improve cell and tissue homeostasis by inducing a ‘rejuvenation’ process.

Figure 4. Pathological and beneficial functions of aging and senescence, according to current knowledge. In red are represented pathological consequences and in green beneficial functions of aging and senescence.

The impact of aging has mainly been described at the organismal level, since a complete cellular functional profile has not yet been established. Accordingly, whether beneficial consequences of the aging process exist at the cellular level is unclear.”


The reviewers’ position on Figure 2 was:

“In our view, recent evidence that senescence is based on an unterminated developmental growth program and the finding that the concept of post-mitotic senescence requires the activation of expansion, or ‘growth’ factors as a second hit, favor the assumption that aging underlies a grating of genetic determination similarly to what is summarized above under the pseudo-programmed causative approach.”

Their position on Figure 4’s beneficial effects of aging began with the sentence:

“If we assume that aging already starts before birth, it can be considered simply a developmental stage, required to complete the evolutionary program associated with species-intrinsic biological functions such as reproduction, survival, and selection.”

Cited studies included:

https://www.mdpi.com/2073-4409/8/11/1446 “Dissecting Aging and Senescence-Current Concepts and Open Lessons”

A strawman argument against epigenetic clocks

This 2019 review of epigenetic clocks by Washington cancer researchers repeatedly returned to an argument for randomness as a cause for aging and disease:

“A time-dependent stochastic event process, like epigenetic drift, could lead to cancer formation through the accumulation of random epigenetic alterations that, through chance, eventually alter epigenetic driver gene expression leading to a clone of cells destined to become cancer..

It is plausible that the stochastic process inherent in epigenetic drift can induce aberrant methylation events that accumulate in normal cells and eventually induce cancer formation.

Epigenetic drift relates to a biological process that changes the DNA methylome with age via stochastic gains or losses of DNA methylation. Epigenetic drift can be understood in terms of errors in DNA methylation maintenance during DNA-replication.

The phenomenon of (epi)genetic drift is generally associated with phenotypic neutrality.

For patients who develop cancer around age 80, the most likely initiation time for the founder adenoma cell is predicted to be very early in life, roughly between the ages 15 to 20 years. This unexpected and provocative finding suggests that the optimal age-range for prevention of colorectal cancer may be in adolescence and early adulthood (and ideally through lifelong) dietary and lifestyle interventions.”


The reviewers’ strawman arguments intentionally mischaracterized aspects of the epigenetic clock:

1. The epigenetic clock founder’s actual view on aging was in The epigenetic clock 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 age estimators.”

The reviewers omitted this intrinsic view of aging, which didn’t fit into their block labeled Extrinsic per the above graphic.

2. Another misrepresentation was:

“In contrast to epigenetic clocks, epigenetic drift refers to a stochastic process that involves both gains and losses of the methylation state of CpG dinucleotides over time.”

A reader of the original 2013 epigenetic clock study would understand that epigenetic clocks measure “both gains and losses of methylation” as in:

“The 193 positively and 160 negatively correlated CpGs get hypermethylated and hypomethylated with age, respectively.”

3. The reviewers omitted recent epigenetic clock significant developments. For example, there was no mention of the GrimAge study, although it was published before the review was submitted.

4. Epigenetic drift as the cause of aging and disease has abundant contrary evidence. The reviewers tossed in a little toward the end of their directed narrative:

“We found only a small number of drift-related CpG island-gene pairs for which drift correlated positively and significantly with gene expression.

The functional consequences of epigenetic drift need to be further elucidated.”

However, they didn’t acknowledge the elephant in the room: The epigenetic drift paradigm is generally inapplicable to humans because the vast majority of our cells don’t divide/proliferate!

https://cancerres.aacrjournals.org/content/early/2019/11/06/0008-5472.CAN-19-0924 “Epigenetic aging: more than just a clock when it comes to cancer” (not freely available)

Caloric restriction’s epigenetic effects

This 2019 US review subject was caloric restriction (CR) without malnutrition:

“Cellular adaptation that occurs in response to dietary patterns can be explained by alterations in epigenetic mechanisms such as DNA methylation, histone modifications, and microRNA. Epigenetic reprogramming of the underlying chronic low-grade inflammation by CR can lead to immuno-metabolic adaptations that enhance quality of life, extend lifespan, and delay chronic disease onset.

Short- and long-term CRs produce significant changes in different tissues and across species, in some animal models even with sex-specific effects. Early CR onset may cause a different and even an opposite effect on physiological outcomes in animal models such as body weight.”

 


1. Charts usually don’t have two different values plotted on the same axis. There wasn’t evidence that equated survival with methylation drift per the above graphic. Methylation drift should point in the opposite direction of survival, if anything.

2. No mention was made of the epigenetic clock method of measuring age acceleration, although it’s been available since 2013 and recent diet studies have used it. The sole citation of an age acceleration study was from 2001, which was unacceptable for a review published in 2019.

3. The review provided many cellular-level details about the subject. However, organism-level areas weren’t sufficiently evidenced:

A. Arguments for an effect usually include explanations for no effect as well as opposite effects. The reviewers didn’t provide direct evidence for why, if caloric restriction extended lifespan, caloric overabundance produced shorter lifespans.

B. Caloric restriction evidence was presented as if only it was responsible for organism-level effects. Other mechanisms may have been involved.

An example of such a mechanism was demonstrated in a 2007 rodent study Reduced Oxidant Stress and Extended Lifespan in Mice Exposed to a Low Glycotoxin Diet which compared two 40%-calorie-restricted diets.

The calories and composition of both diets were identical. However, advanced glycation end product (AGE) levels were doubled in standard chow because heating temperatures were “sufficiently high to inadvertently cause standard mouse chow to be rich in oxidant AGEs.”

The study found that a diet with lower chow heating temperatures increased lifespan and health span irrespective of caloric restriction!

  • The low-AGE calorie-restricted diet group lived an average of 15% longer (>20 human equivalent years) than the CR group.
  • 40% of the low-AGE calorie-restricted diet group were still alive when the last CR group member died.
  • The CR group also had significantly more: 1) oxidative stress damage; 2) glucose and insulin metabolism problems; and 3) kidney, spleen, and liver injuries.

https://academic.oup.com/advances/article-abstract/10/3/520/5420411 “Epigenetic Regulation of Metabolism and Inflammation by Calorie Restriction” (not freely available)

A drug that countered effects of a traumatizing mother

This 2019 US rodent study concerned transmitting poor maternal care to the next generation:

“The quality of parental care received during development profoundly influences an individual’s phenotype, including that of maternal behavior. Infant experiences with a caregiver have lifelong behavioral consequences.

Maternal behavior is a complex behavior requiring the recruitment of multiple brain regions including the nucleus accumbens, bed nucleus of the stria terminalis, ventral tegmental area, prefrontal cortex, amygdala, and medial preoptic area. Dysregulation within this circuitry can lead to altered or impaired maternal responsiveness.

We administered zebularine, a drug known to alter DNA methylation, to dams exposed during infancy to the scarcity-adversity model of low nesting resources, and then characterized the quality of their care towards their offspring.

  1. We replicate that dams with a history of maltreatment mistreat their own offspring.
  2. We show that maltreated-dams treated with zebularine exhibit lower levels of adverse care toward their offspring.
  3. We show that administration of zebularine in control dams (history of nurturing care) enhances levels of adverse care.
  4. We show altered methylation and gene expression in maltreated dams normalized by zebularine.

These findings lend support to the hypothesis that epigenetic alterations resulting from maltreatment causally relate to behavioral outcomes.”


“Maternal behavior is an intergenerational behavior. It is important to establish the neurobiological underpinnings of aberrant maternal behavior and explore treatments that can improve maternal behavior to prevent the perpetuation of poor maternal care across generations.”

The study authors demonstrated intergenerational epigenetic effects, and missed an opportunity to also investigate transgenerational epigenetically inherited effects. They cited reference 60 for the first part of the above quotation, but the cited reviewer misused the transgenerational term by applying it to grand-offspring instead of the great-grand-offspring.

There were resources available to replicate the study authors’ previous findings, which didn’t show anything new. Why not use such resources to uncover evidence even more applicable to humans by extending experiments to great-grand-offspring that would have no potential germline exposure to the initial damaging cause?

Could a study design similar to A limited study of parental transmission of anxiety/stress-reactive traits have been integrated? That study’s thorough removal of parental behavior would be an outstanding methodology to confirm by falsifiability whether parental behavior is both an intergenerational and a transgenerational epigenetic inheritance mechanism.

Rodent great-grand-offspring can be studied in < 9 months. It takes > 50 years for human studies to reach the great-grand-offspring transgenerational generation. Why not attempt to “prevent the perpetuation of poor maternal care across generations?”

Isn’t it a plausible hypothesis that humans “with a history of maltreatment mistreat their own offspring?” Isn’t it worth the extra effort to extend animal research to investigate this unfortunate chain?

https://www.nature.com/articles/s41598-019-46539-4 “Pharmacological manipulation of DNA methylation normalizes maternal behavior, DNA methylation, and gene expression in dams with a history of maltreatment”