Genetic factors

An evolutionary view of transgenerational epigenetic inheritance

gettingwell4 2-3 stars Required further work, Epigenetics, Memory, Stress ,

This 2020 Swiss/German review mainly cited weed, worm, and yeast studies:

“RNA interference-related mechanisms can mediate the deposition and transgenerational inheritance of specific chromatin modifications in a truly epigenetic fashion.

Epigenetics was initially defined as any heritable change in gene expression patterns without changes in the DNA sequence. Now, epigenetic phenomena are often characterized as ‘gene expression changes that are mutation independent and heritable in the absence of the triggering event’, a definition we will follow in this review. We note that this definition can be expanded to include protein only-based inheritance mechanisms that do not necessarily cause changes in gene expression.

Gene silencing can persist over multiple generations in the germline of C. elegans. Gene repression is typically maintained without the initial trigger for three to seven generations and occasionally for tens of generations. In contrast, silencing of somatically expressed genes mostly affects only the subsequent generation through nonepigenetic parental effects.

In the presence of an ‘enabling’ mutation, primary siRNAs [small interfering RNAs] can trigger an RNAe [RNA-induced epigenetic silencing] response. Secondary siRNA amplification is required for transgenerational inheritance.

The fitness of a population in a dynamic environment strongly depends on the ability of individuals to adapt to the new condition as well as to remember, inherit, and forget such adaptation:

  • (A) A well-adapted population (grey) is at its maximal density (dotted line) in a given niche until an environmental change (1st stress) creates a bottleneck. Only few individuals can adapt through mutations and repopulate the niche. After the environment changes back to the initial blue state, only individuals that acquire rare counteracting mutations survive, often leading to extinction of the population.
  • (B) Individuals of a population in the red state can gain beneficial epimutations through siRNAs and repopulate the niche. When exposed again to the blue state, the epimutations can be quickly reversed and the population rapidly reaches maximal density. After recurrence of the red state, organisms establish de novo epimutations with the same low frequency as when they first encountered this state.
  • (C) In contrast, organisms that can maintain the memory of a beneficial silencing event can quickly re-establish beneficial epimutations and grow to full density. Such memory can be maintained by phenotypically neutral epimutations, marked by the continuously high production of siRNAs without substantial reductions in the expression of a gene. A population that can adapt through phenotypically plastic epimutations is predicted to have a maximal fitness advantage in a dynamic environment.”

The Concluding Remarks section included:

“RNA-mediated epigenetic responses could contribute to adaptation.

Even though RNAe may yield significant adaptive advantages, a high induction frequency could cause silencing of multiple essential genes and therefore be detrimental. Hence, it is plausible that mechanisms would have coevolved that counteract silencing.

Similarly, if constituting a bet-hedging strategy to cope with ever-changing environments, permanent fixation of an acquired silencing response would not constitute a selective advantage and mechanisms that modify and limit the duration of RNAe would be predicted.”

https://www.sciencedirect.com/science/article/pii/S0168952519302598 “Small RNAs in the Transgenerational Inheritance of Epigenetic Information”

The review’s arguments were based on evolutionary selective advantages and less-complex organisms. It predicted that there would be an endpoint generation as in the (A) case of the above graphic.

Were the mechanisms in the (B) case necessarily transgenerational throughout? The review further explained:

“Epimutations tend to occur in hot spots (e.g., in stress-related or nutritional pathway genes) and can potentially silence several homologous genes simultaneously. Incomplete penetrance of a beneficial epimutation by stochastic loss of siRNAs [59] can result in loss of adaptation in a given environment (red state), but can be beneficial if the previous blue state is re-established. However, when the environment changes back to the red state, epimutations must initiate de novo, at the same low frequency as when the population first encountered this state.”

The study cited at 59 found:

“A feedback between siRNAs and RNAi genes determines heritable silencing duration”

but not “Incomplete penetrance of a beneficial epimutation by stochastic loss of siRNAs.” Hmm.

In any event, the review stated:

“Evidence for naturally occurring RNAe-related phenomena in other animals is scarce and we should be cautious about inferring RNAe as a widely conserved phenomenon.”

It’s encouraging to read studies that find benefits to epigenetic transgenerational inheritance, albeit in organisms that are less complex than rodents and humans.

 

The epigenetics of perinatal stress

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This 2019 McGill review discussed long-lasting effects of perinatal stress:

“Epigenetic processes are involved in embedding the impact of early-life experience in the genome and mediating between social environments and later behavioral phenotypes. Since these phenotypes are apparent a long time after early experience, changes in gene expression programming must be stable.

Although loss of methylation in a promoter is necessary for expression, it is not sufficient. Demethylation removes a barrier for expression, but expression might be realized at the right time or context when needed factors or signals are present.

DNA methylation anticipates future transcriptional response to triggers. Comparing steady-state expression with DNA methylation does not capture the full meaning and scope of regulatory roles of differential methylation.

A model for epigenetic programming by early life stress:

  1. Perinatal stress perceived by the brain triggers release of glucocorticoids (GC) from the adrenal in the mother prenatally or the newborn postnatally.
  2. GC activate nuclear glucocorticoid receptors across the body, which epigenetically program (demethylate) genes that are targets of GR in brain and white blood cells (WBC).
  3. Demethylation events are insufficient for activation of these genes. A brain specific factor (TF) is required for expression and will activate low expression of the gene in the brain but not in blood.
  4. During adulthood a stressful event transiently triggers a very high level of expression of the GR regulated gene specifically in the brain.

Horizontal arrow, transcription; circles, CpG sites; CH3 in circles, methylated sites; empty circles, unmethylated CpG sites; horizon[t]al curved lines, mRNA.”

Review points discussed:

  • “Epigenetic marks are laid down and maintained by enzymes that either add or remove epigenetic modifications and are therefore potentially reversible in contrast to genetic changes.
  • Response to early life stress and maternal behavior is also not limited to the brain and involves at least the immune system as well.
  • The placenta is also impacted by maternal social experience and early life stress.
  • Most studies are limited to peripheral tissues such as saliva and white blood cells, and relevance to brain physiology and pathology is uncertain.
  • Low absolute differences in methylation seen in most human behavioral EWAS raise questions about their biological significance.

  • Although post-mortem studies examine epigenetic programming in physiologically relevant tissues, they represent only a final and single stage that does not capture dynamic evolution of environments and epigenetic programming in living humans.”

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952743/ “The epigenetics of perinatal stress”

Other reviewers try to ignore times when we were all fetuses and newborns. For example, in the same journal issue was a Boston review of PTSD that didn’t mention anything about earliest times of human lives! Those reviewers speculated around this obvious gap on their way to being paid by NIH.

Why would researchers ignore perinatal stress events that prime humans for later-life PTSD? Stress generally has a greater impact on fetuses and newborns than on infants, and a greater impact on infants than on adults.

Masters of manipulating their host

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This 2020 French review subject was parasitical influences on host epigenetic processes:

“Parasites have become masters of manipulating their host cells, exploiting signaling, and metabolic pathways to hijack host gene expression to their own advantage. These intracellular parasites have developed a wide range of strategies that affect transcriptional machineries and epigenetic events in the host cell nucleus.

Parasite effectors regulate host transcription. Secretion of numerous parasite effector proteins are key processes during parasite infection. Parasite effectors deregulate host expression profile which lead to host cell transformation, or escape from the host immune system to allow parasite persistence and survival.”

parasites
The first two of the six strategies discussed are shown above:

  1. “Induction of a host epigenetic enzyme. Parasite infection leads to upregulation of SMYD3, a methyltransferase that activates genes involved in host transformation, through H3K4 trimethylation.
  2. Secreting effector proteins that drive epigenetic repression of host genes. TEEGR activates a host chromatin modifier able to repress transcription of immune system genes through H3K27 trimethylation.”

https://link.springer.com/article/10.1007/s00281-020-00779-z “The clever strategies used by intracellular parasites to hijack host gene expression” (not freely available)

I used a “parasites” paradigm while living in the Washington DC area for three decades to help understand what goes on there. Moved away several years ago, but haven’t changed my thinking that all six of this paper’s parasite strategies had analogous human actions.

Other curated papers that explored the review’s topic include:

Do epigenetic clocks measure causes or effects?

gettingwell4 2-3 stars Required further work, Epigenetics , ,

Starting the sixth year of this blog with a 2020 article authored by the founder of the PhenoAge epigenetic clock methodology:

“The Ge[r]oscience paradigm suggests that targeting the aging process could delay or prevent the risk of multiple major age-related diseases. We need clinically valid measures of the underlying biological process and/or classification criteria for what it means to be biologically, rather than chronologically, “aged”.

The majority of aging biomarkers, including the first-generation epigenetic clocks, are developed using cross-sectional data, in which the researchers take a variable that proxies aging (e.g. chronological age) and apply supervised machine learning, or deep learning, approaches to predict that variable using tens to hundreds of thousands of input variables. The problem with this approach is that it doesn’t account for mortality selection. This biases the algorithm to select markers that are not causal, but instead correlative with aging.

When considering individuals of the same chronological age, do those with higher epigenetic age look phenotypically older on average (e.g. have higher mortality rates, greater disease burden, and worse physical and cognitive functioning)? FEV1 [forced expiratory volume in one second] declined at a faster rate for individuals with higher baseline GrimAge and/or PhenoAge. A similar finding was observed for the decline in grip strength as a function of GrimAge; however, the rate of change for any of the epigenetic clocks was not associated with rate of change in any performance measure.

Loci that show consistent trends with chronological age, even at higher ages, are likely not causal. By using a cross-sectional study design for biomarker development there was a propensity away from selecting causal loci, to the point where fewer causal loci were selected than if loci had been chosen at random.

The power of these measures as diagnostic and prognostic may stem from the use of longitudinal data in training them. Rather than continuing to train chronological age predictors using diverse data, it may be more advantageous to retrain some of the existing measures by predicting longitudinal outcomes.”

https://academic.oup.com/biomedgerontology/advance-article-abstract/doi/10.1093/gerona/glaa021/5717592 “Assessment of Epigenetic Clocks as Biomarkers of Aging in Basic and Population Research” (not freely available)

A cited 2019 study modeled corrections to “account for mortality selection.” It modified datasets “by incorporating correlates of mortality identified from longitudinal studies, allowing cross-sectional studies to effectively identify the causal factors of aging.”

https://academic.oup.com/biomedgerontology/advance-article-abstract/doi/10.1093/gerona/glz174/5540066 “Biomarkers for Aging Identified in Cross-sectional Studies Tend to Be Non-causative” (not freely available)

The article didn’t present a complete case to determine whether an individual’s epigenetic clock measurements over time may show causes of biological aging.

Other viewpoints include:

1. A blood plasma aging clock presented evidence with its 46-protein conserved aging signature that some causes of biological aging are under genetic control. If the principle of this finding applies to CpG DNA methylation, the statement:

Loci that show consistent trends with chronological age, even at higher ages, are likely not causal.

may not hold. Such epigenetic changes could be among both the causes of senescence and the effects of evolution’s selection mechanisms.

2. An epigenetic clock review by committee, particularly in:

  • Challenge 3 “Integration of epigenetics into large and diverse longitudinal population studies”;
  • Challenge 5 “Single-cell analysis of aging changes and disease”; and
  • Table 1 “Major biological and analytic issues with epigenetic DNA methylation clocks” with single-cell analysis as the solution to five Significant issues.

Drink tea today

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This 2020 Chinese paper reviewed this century’s research into tea:

“Tea plants contain rich and unique characteristic secondary metabolites, such as catechins, theanine, and caffeine, which are essential to the formation of tea quality. It is not only the three major types of secondary metabolites but also the volatile terpenoids, saponins, polysaccharides, and other phenolic conjugates that contribute to the beneficial health effects and the enjoyable flavors of various teas.

The contents of these secondary metabolites vary greatly among different varieties and Camellia species. They also differ significantly in several morphological traits (e.g., leaf size) and stress resistance characteristics (e.g., cold tolerance), showing a divergent genetic makeup. The genome sequence of a single individual of a tea plant variety cannot represent the entire gene pool.

Modern transgenic breeding technology has provided us a new solution for the molecular design of breeding strategies. Although great progress has been made in the last two decades, the genomics and molecular biology of tea plants are still not fully understood. Compared to other crops such as rice, there is a long way to go.”

https://www.nature.com/articles/s41438-019-0225-4 “Tea plant genomics: achievements, challenges and perspectives”

Clearing out the 2019 queue of interesting papers

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I’m clearing out the below queue of 27 studies and reviews I’ve partially read this year but haven’t taken the time to curate. I have a pesky full-time job that demands my presence elsewhere during the day. :-\

Should I add any of these back in? Let’s be ready for the next decade!

Early life

https://link.springer.com/article/10.1007/s12035-018-1328-x “Early Behavioral Alterations and Increased Expression of Endogenous Retroviruses Are Inherited Across Generations in Mice Prenatally Exposed to Valproic Acid” (not freely available)

https://www.sciencedirect.com/science/article/pii/S0166432818309392 “Consolidation of an aversive taste memory requires two rounds of transcriptional and epigenetic regulation in the insular cortex” (not freely available)

https://www.nature.com/articles/s41380-018-0265-4 “Intergenerational transmission of depression: clinical observations and molecular mechanisms” (not freely available)

mother

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454089/ “Epigenomics and Transcriptomics in the Prediction and Diagnosis of Childhood Asthma: Are We There Yet?”

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628997/ “Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels”

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6770436/ “Mismatched Prenatal and Postnatal Maternal Depressive Symptoms and Child Behaviours: A Sex-Dependent Role for NR3C1 DNA Methylation in the Wirral Child Health and Development Study”

https://www.sciencedirect.com/science/article/pii/S0889159119306440 “Environmental influences on placental programming and offspring outcomes following maternal immune activation”

https://academic.oup.com/mutage/article-abstract/34/4/315/5581970 “5-Hydroxymethylcytosine in cord blood and associations of DNA methylation with sex in newborns” (not freely available)

https://physoc.onlinelibrary.wiley.com/doi/full/10.1113/JP278270 “Paternal diet impairs F1 and F2 offspring vascular function through sperm and seminal plasma specific mechanisms in mice”

https://onlinelibrary.wiley.com/doi/full/10.1111/nmo.13751 “Sex differences in the epigenetic regulation of chronic visceral pain following unpredictable early life stress” (not freely available)

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811979/ “Genome-wide DNA methylation data from adult brain following prenatal immune activation and dietary intervention”

https://link.springer.com/article/10.1007/s00702-019-02048-2 “miRNAs in depression vulnerability and resilience: novel targets for preventive strategies”

Later life

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6543991/ “Effect of Flywheel Resistance Training on Balance Performance in Older Adults. A Randomized Controlled Trial”

https://www.mdpi.com/2411-5142/4/3/61/htm “Eccentric Overload Flywheel Training in Older Adults”

https://www.nature.com/articles/s41577-019-0151-6 “Epigenetic regulation of the innate immune response to infection” (not freely available)

https://link.springer.com/chapter/10.1007/978-981-13-6123-4_1 “Hair Cell Regeneration” (not freely available)

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6422915/ “Histone Modifications as an Intersection Between Diet and Longevity”

https://www.sciencedirect.com/science/article/abs/pii/S0306453019300733 “Serotonin transporter gene methylation predicts long-term cortisol concentrations in hair” (not freely available)

https://www.sciencedirect.com/science/article/abs/pii/S0047637419300338 “Frailty biomarkers in humans and rodents: Current approaches and future advances” (not freely available)

https://onlinelibrary.wiley.com/doi/full/10.1111/pcn.12901 “Neural mechanisms underlying adaptive and maladaptive consequences of stress: Roles of dopaminergic and inflammatory responses”

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6627480/ “In Search of Panacea—Review of Recent Studies Concerning Nature-Derived Anticancer Agents”

https://www.sciencedirect.com/science/article/abs/pii/S0028390819303363 “Reversal of oxycodone conditioned place preference by oxytocin: Promoting global DNA methylation in the hippocampus” (not freely available)

https://www.futuremedicine.com/doi/10.2217/epi-2019-0102 “Different epigenetic clocks reflect distinct pathophysiological features of multiple sclerosis”

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6834159/ “The Beige Adipocyte as a Therapy for Metabolic Diseases”

https://www.sciencedirect.com/science/article/abs/pii/S8756328219304077 “Bone adaptation: safety factors and load predictability in shaping skeletal form” (not freely available)

https://www.nature.com/articles/s41380-019-0549-3 “Successful treatment of post-traumatic stress disorder reverses DNA methylation marks” (not freely available)

https://www.sciencedirect.com/science/article/abs/pii/S0166223619301821 “Editing the Epigenome to Tackle Brain Disorders” (not freely available)

A blood plasma aging clock

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This 2019 Stanford human study developed an aging clock using blood plasma proteins:

“We measured 2,925 plasma proteins from 4,331 young adults to nonagenarians [18 – 95] and developed a novel bioinformatics approach which uncovered profound non-linear alterations in the human plasma proteome with age. Waves of changes in the proteome in the fourth, seventh, and eighth decades of life reflected distinct biological pathways, and revealed differential associations with the genome and proteome of age-related diseases and phenotypic traits.

To determine whether the plasma proteome can predict chronological age and serve as a “proteomic clock,” we used 2,858 randomly selected subjects to fine-tune a predictive model that was tested on the remaining 1,473 subjects. We identified a sex-independent plasma proteomic clock consisting of 373 proteins. Subjects that were predicted younger than their chronologic age based on their plasma proteome performed better on cognitive and physical tests.

The 3 age-related crests were comprised of different proteins. Few proteins, such as GDF15, were among the top 10 differentially expressed proteins in each crest, consistent with its strong increase across lifespan. Other proteins, like chordin-like protein 1 (CHRDL1) or pleiotrophin (PTN), were significantly changed only at the last two crests, reflecting their exponential increase with age.

We observed a prominent shift in multiple biological pathways with aging:

  • At young age (34 years), we observed a downregulation of proteins involved in structural pathways such as the extracellular matrix. These changes were reversed in middle and old ages (60 and 78 years, respectively).
  • At age 60, we found a predominant role of hormonal activity, binding functions and blood pathways.
  • At age 78, key processes still included blood pathways but also bone morphogenetic protein signaling, which is involved in numerous cellular functions, including inflammation.

These results suggest that aging is a dynamic, non-linear process characterized by waves of changes in plasma proteins that are reflective of a complex shift in the activity of biological processes.”

https://www.biorxiv.org/content/10.1101/751115v1.full “Undulating changes in human plasma proteome across lifespan are linked to disease”

A non-critical review of the study was published by the Life Extension Advocacy Foundation. Frequent qualifiers like “could,” “may,” and “possible” were consistent with the confirmation biases of their advocacy.

There were several misstatements of what the study did, including the innumerate:

  1. “used around half of the participant data to build a “proteomic clock”
  2. tested it on the other half of the participants
  3. a total of 3000 proteins”

Per the above study quotation, the numbers were actually:

  1. Closer to two thirds (2,858 ÷ 4,331), not “around half”;
  2. The other third (1,473 ÷ 4,331), not “the other half”; and
  3. 2,925 not 3000.

The final paragraph and other parts of the review bordered on woo. Did a review of the findings have to fit LEAF’s perspective?

In contrast, Josh Mitteldorf did his usual excellent job of providing contexts for the study with New Aging Clock based on Proteins in the Blood, emphasizing comparisons with epigenetic clock methodologies:

“For some of the proteins that feature prominently in the clock, we have a good understanding of their metabolic function, and for the most part they vindicate my belief that epigenetic changes are predominantly drivers of senescence rather than protective responses to damage.

Wyss-Coray compared the proteins in the new (human) proteome clock with the proteins that were altered in the (mouse) parabiosis experiments, and found a large overlap [46 proteins change in the same direction and define a conserved aging signature]. This may be the best evidence we have that the proteome changes are predominantly causal factors of senescence.

46 plasma proteins

Almost all the proteins identified as changing rapidly at age 78 are increasing. In contrast, a few of the fastest-changing proteins at age 60 are decreasing (though most are increasing). GDF15 deserves a story of its own.

The implication is that a more accurate clock can be constructed if it incorporates different information at different life stages. None of the Horvath clocks have been derived based on different CpG sites at different ages, and this suggests an opportunity for a potential improvement in accuracy.”

A commentator linked the below study:

https://www.sciencedirect.com/science/article/pii/S0092867419308323 “GDF15 Is an Inflammation-Induced Central Mediator of Tissue Tolerance” (not freely available)

which prompted his response:

“Thanks, Lee! This is just the kind of specific information that I was asking for. It would seem we should construct our clocks without GDF15, which otherwise might loom large.”

An out-of-date review of epigenetic transgenerational inheritance

gettingwell4 0-1 star Wasted resources, Epigenetics, Stress, Telomeres , , ,

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

Systematic resetting of epigenetic marks between generations represents the largest hurdle to conceptualizing epigenetic inheritance. Our understanding of 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.”

This review showed an inexplicable lack of thorough research. 2017 was its latest citation of epigenetic transgenerational inheritance studies from 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. This review was submitted on October 31, 2019, and all 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.”

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

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

1. Citations of 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 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 all 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, 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 Horvath average biological age of 3.95 years less raised the question: exactly why did PhenoAge show such a large difference?
  • The paper mentioned GrimAge methodology findings about “smoking-related changes.” But it didn’t explain why 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 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 review of fetal adverse events

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This 2019 Australian review subject was fetal adversities:

“Adversity during the perinatal period is a significant risk factor for the development of neurodevelopmental disorders long after the causative event. Despite stemming from a variety of causes, perinatal compromise appears to have similar effects on the developing brain, thereby resulting in behavioural disorders of a similar nature.

These behavioural disorders occur in a sex‐dependent manner, with males affected more by externalizing behaviours such as attention deficit hyperactivity disorder (ADHD) and females by internalizing behaviours such as anxiety. The term ‘perinatal compromise’ serves as an umbrella term for intrauterine growth restriction, maternal immune activation, prenatal stress, early life stress, premature birth, placental dysfunction, and perinatal hypoxia.

The above conditions are associated with imbalanced excitatory-inhibitory pathways resulting from reduced GABAergic signalling. Methylation of the GAD1/GAD67 gene, which encodes the key glutamate‐to‐GABA synthesizing enzyme Glutamate Decarboxylase 1, resulting in increased levels of glutamate is one epigenetic mechanism that may account for a tendency towards excitation in disorders such as ADHD.

The posterior cerebellum’s role in higher executive functioning is becoming well established due to its connections with the prefrontal cortex, association cortices, and limbic system. It is now suggested that disruptions to cerebellar development, which can occur due to late gestation compromises such as preterm birth, can have a major impact on the region of the brain to which it projects.

Activation of the maternal hypothalamic-pituitary adrenal (HPA) axis and placental protection. Psychological stress is perceived by the maternal HPA axis, which stimulates cortisol release from the maternal adrenal gland.

High levels of maternal cortisol are normally prevented from reaching the fetus by the 11β-hydroxysteroid dehydrogenase 2 (HSD11B2) enzyme, which converts cortisol to the much less active cortisone. Under conditions of high maternal stress, this protective mechanism can be overwhelmed, with the gene encoding the enzyme becoming methylated, which reduces its expression allowing cortisol to cross the placenta and reach the fetus.”

The reviewers extrapolated many animal study findings to humans, although most of their own work was with guinea pigs. The “suggest” and “may” qualifiers were used often – 22 and 37 times, respectively. More frequent use of the “appears,” “hypothesize,” “propose,” and “possible” terms was justified.

As a result, many reviewed items such as the above graphic and caption should be viewed as hypothetical for humans rather than reflecting solid evidence from quality human studies.

The reviewers focused on the prenatal (before birth) period more than the perinatal (last trimester of pregnancy to one month after birth) period. There were fewer mentions of birth and early infancy adversities.

https://onlinelibrary.wiley.com/doi/abs/10.1111/jne.12814 “Perinatal compromise contributes to programming of GABAergic and Glutamatergic systems leading to long-term effects on offspring behaviour” (not freely available)

A transgenerational view of the rise in obesity

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This 2019 Washington State University rodent study found epigenetically inherited transgenerational effects in great-grand offspring due to their great-grandmothers’ toxicant exposures during pregnancy:

“Previous studies found an increased susceptibility to obesity in F3 generation rats ancestrally exposed to the pesticide DDT, and an increase in a lean phenotype in the F3 generation rats ancestrally exposed to the herbicide atrazine. The present study investigated whether there were common DMR [differential DNA methylated region] and associated genes between the control, DDT, and atrazine lineage male and female adipocytes in order to identify potential novel gene pathways modulated by DNA methylation.

Comparison of epigenetic alterations indicated that there were substantial overlaps between the different treatment lineage groups for both the lean and obese phenotypes. Novel correlated genes and gene pathways associated with DNA methylation were identified, and may aid in the discovery of potential therapeutic targets for metabolic diseases such as obesity.

Given that the first widespread [DDT] exposures to gestating human females started in the 1950s, the majority of the subsequent F3 generation are adults today. Ancestral exposures to environmental toxicants like DDT may have had a role in the dramatic rise in obesity rates worldwide.”

This same research group noted in Transgenerational diseases caused by great-grandmother DDT exposure:

“DDT was banned in the USA in 1973, but it is still recommended by the World Health Organization for indoor residual spray. India is by far the largest consumer of DDT worldwide.

India has experienced a 5-fold increase of type II diabetes over the last three decades with a predisposition to obesity already present at birth in much of the population. Although a large number of factors may contribute to this increased incidence of obesity, the potential contribution of ancestral toxicant exposures in the induction of obesity susceptibility requires further investigation.”

https://www.tandfonline.com/doi/full/10.1080/21623945.2019.1693747 “Adipocyte epigenetic alterations and potential therapeutic targets in transgenerationally inherited lean and obese phenotypes following ancestral exposures”

A GWAS meta-analysis of two epigenetic clocks

gettingwell4 0-1 star Wasted resources, Beliefs, Cerebrum, Epigenetics, Immune system, Telomeres , , ,

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

gettingwell4 2-3 stars Required further work, Brain development, Epigenetics, Hypothalamus, Immune system, Limbic system, Memory, Stress, Telomeres , , , , ,

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 assertion of Figure 3 (2) that:

“There is currently no direct evidence for a similar factor composition propagating the aging process via a kind of ‘gero-infection.”

was shown to be false in Reevaluate findings in another paradigm:

“It was demonstrated that increased aging occurred as a result of lack of gonadotropin-releasing hormone and that increased lifespan resulted from its provision during aging.

In this manner:

  1. Aging of hypothalamic microglia leads to
  2. Aging of the hypothalamus, which leads to
  3. Aging elsewhere in the body.

So here we have a multi-level interaction:

  1. Activation of NF-κB leads to
  2. Cellular aging, leading to
  3. A diminished production of GnRH, which then
  4. Acts (through cells with a receptor for it, or indirectly as a result of changes to GnRH-receptor-possessing cells) to decrease lifespan.

So the age state of hypothalamic cells, at least with respect to NF-κB activation, is communicated to other cells via reduced output of GnRH.”

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

gettingwell4 < 0 Detracted from science, Epigenetics, Immune system, Stress, Telomeres , ,

This 2019 review of epigenetic clocks by Washington cancer researchers ignored the elephant in the room: Their epigenetic drift paradigm is generally inapplicable to humans because the vast majority of our cells don’t divide/proliferate. They 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 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. These reviewers omitted recent epigenetic clock significant developments. For example, there was no mention of the GrimAge study, although it was published before this review was submitted.

4. Epigenetic drift as the cause of aging and disease has abundant contrary evidence. These 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 never acknowledged the elephant in the room!

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)

Epigenetic transgenerational inheritance extends to the great-great-grand offspring

gettingwell4 5+ stars Premium, Epigenetics, Memory , , , , ,

This 2019 rodent study by the Washington State University labs of Dr. Michael Skinner continued to F4 generation great-great-grand offspring, and demonstrated that epigenetic inheritance mechanisms are similar to imprinted genes:

“Epigenetic transgenerational inheritance potentially impacts disease etiology, phenotypic variation, and evolution. An increasing number of environmental factors from nutrition to toxicants have been shown to promote the epigenetic transgenerational inheritance of disease.

Imprinted genes are a special class of genes since their DNA methylation patterns are unchanged over the generation and are not affected by the methylation erasure occurring early in development. The transgenerational epigenetic alterations in the germline appear to be permanently reprogrammed like imprinted genes, and appear protected from this DNA methylation erasure and reprogramming at fertilization in the subsequent generations. Similar to imprinted genes, the epigenetic transgenerational germline epimutations appear to have a methylation erasure in the primordial germ cells involving an epigenetic molecular memory.

Comparison of the transgenerational F3 generation, with the outcross to the F4 generation through the paternal or maternal lineages, allows an assessment of parent-of-origin transmission of disease or pathology. Observations provided examples of the following:

  1. Pathology that required combined contribution of both paternal and maternal alleles to promote disease [testis and ovarian disease];
  2. Pathology that is derived from the opposite sex allele such as father to daughter [kidney disease] or mother to son [prostate disease];
  3. Pathology that is derived from either parent-of-origin alleles independently [obesity];
  4. Pathology that is transmitted within the same sex, such as maternal to daughter [mammary tumor development]; and
  5. Pathology that is observed only following a specific parent-of-origin outcross [both F4 male obesity and F4 female kidney disease in the vinclozolin lineage].”

https://www.sciencedirect.com/science/article/pii/S0012160619303471 “Epigenetic transgenerational inheritance of parent-of-origin allelic transmission of outcross pathology and sperm epimutations”

This study showed that epigenetically inherited legacies extend to the fifth generation. Do any of us know our ancestors’ medical histories back to our great-great-grandparents?

Will toxicologists take their jobs seriously, catch up to current science, and investigate possible effects in at least the F3 generation that had no direct toxicant exposure?