Hidden hypotheses of epigenetic studies

This 2018 UK review discussed three pre-existing conditions of epigenetic genome-wide association studies:

“Genome-wide technology has facilitated epigenome-wide association studies (EWAS), permitting ‘hypothesis-free’ examinations in relation to adversity and/or mental health problems. Results of EWAS are in fact conditional on several a priori hypotheses:

  1. EWAS coverage is sufficient for complex psychiatric problems;
  2. Peripheral tissue is meaningful for mental health problems; and
  3. The assumption that biology can be informative to the phenotype.

1. CpG sites were chosen as potentially biologically informative based on consultation with a consortium of DNA methylation experts. Selection was, in part, based on data from a number of phenotypes (some medical in nature such as cancer), and thus is not specifically targeted to brain-based, stress-related complex mental health phenotypes.

2. The assumption is often that distinct peripheral tissues are interchangeable and equally suited for biomarker detection, when in fact it is highly probable that peripheral tissues themselves correspond differently to environmental adversity and/or disease state.

3. Analyses result in general statements such as ‘neurodevelopment’ or the ‘immune system’ being involved in the aetiology of a given phenotype. Whether these broad categories play indeed a substantial role in the aetiology of the mental health problem is often hard to determine given the post hoc nature of the interpretation.”


The reviewers mentioned in item #2 the statistical flaw of assuming that measured entities are interchangeable with one another. They didn’t mention that this problem also affects item #1 methodologies of averaging CpG methylation measurements in fixed genomic bins or over defined genomic regions. This was discussed in:

The reviewers offered suggestions for reducing the impacts of these three hypotheses. But doing more of the same, only better, won’t necessarily advance science.

Is it too much to ask researchers whose paychecks and reputations depend on a paradigm – such as the “biomarker” mentioned a dozen and a half times – to admit the uselessness of gathering data when the framework in which the data operates isn’t viable?

The truth about complex traits and GWAS described one relevant example of how we already know this framework, its paradigms, and its related techniques aren’t effective:

“The most investigated candidate gene hypotheses of schizophrenia are not well supported by genome-wide association studies, and it is likely that this will be the case for other complex traits as well.”

https://www.sciencedirect.com/science/article/pii/S2352250X18300940 “Hidden hypotheses in ‘hypothesis-free’ genome-wide epigenetic associations”

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Restoration of a “normal” epigenetic landscape

This 2018 Texas human review subject was prostate cancer epigenetics:

“We comprehensively review the up-to-date roles of epigenetics in the development and progression of prostate cancer. We especially focus on three epigenetic mechanisms: DNA methylation, histone modifications, and noncoding RNAs. We elaborate on current models/theories that explain the necessity of these epigenetic programs in driving the malignant phenotypes of prostate cancer cells.

It is now generally accepted that epigenetics contributes to the development of nearly every stage of PCa [prostate cancer]. Considering the highly heterogeneous nature of PCa, it is quite likely that [the] effect of a particular epigenetic pattern on growth of cancer cells varies from case to case and [is] context specific.

Restoration of a “normal” epigenetic landscape holds promise as a cure for prostate cancer.”


The review’s Epigenetic Therapy section explained much of what’s going on in the above graphic. Its Table 3 was instructive for up-to-date clinical trial information on epigenetic treatments of prostate cancer.

“Restoration of a “normal” epigenetic landscape” won’t guarantee a healthy outcome once diseases start. Prevention seems desirable, especially to avoid:

“Numerous epigenetic alterations [that] reinforce the establishment of a context-specific transcriptional profile that favors self-renewal, survival, and invasion of PCa cells.”

http://www.ajandrology.com/preprintarticle.asp?id=238758 “Epigenetic regulation of prostate cancer: the theories and the clinical implications”

Measuring epigenetic changes at a single-cell level

This 2018 Canadian cell study described the development of a single-cell protocol to:

“Profile primitive hematopoietic cells of mouse and human origin to identify epigenetically distinct subpopulations. Deep sampling of the CpG content of individual HSCs allowed for the near complete reconstitution of regulatory states from epigenetically defined subpopulations of HSCs and revealed a high level of redundancy of CpG methylation states within these phenotypically defined hematopoietic cell types.

Hematopoietic stem cells (HSCs) are functionally defined cells that display evidence of extensive self-renewal of their ability to generate mature blood cells for the lifetime of the organism and following transplantation into myelosuppressed permissive hosts. Most of the epigenetic measurements underpinning these observations represent consensus values experimentally derived from thousands of cells partially enriched in HSCs or their progeny, thus failing to discern distinct epigenetic states within HSCs.

Current analytical strategies for single-cell DNA methylation measurements average DNA methylation in fixed genomic bins or over defined genomic regions. However, inference across cells (as well as sequence context) assumes homogeneity across cells, which is at cross-purposes with the generation of single-cell molecular measurements through the potential to mask rare subpopulations.

We identified donor as a significant source of consistent epigenetic heterogeneity, which was reduced but not eliminated by correcting for personal genetic variants. This observation is consistent with previous reports that showed genetic diversity as related to but not accountable for all DNA methylation differences and suggests that in utero environmental differences may be encoded within the HSC compartment.”


The study advanced science not only by measuring single-CpG methylation within each HSC but also by producing another data point “that in utero environmental differences may be encoded within the HSC compartment.”

The paragraph with “assumes homogeneity across cells” bold text provided another example of the statistical analysis flaw that gives individually inapplicable results per Group statistics don’t necessarily describe an individual. The above graphic of human hematopoietic phenotypes demonstrated that the researchers have potentially solved this problem by measuring individual cells.

The researchers discussed another aspect of the study that’s similar to the epigenetic clock methodology:

“Phenotype-specific methylation signatures are characterized by extensive redundancy such that distinct epigenetic states can be accurately described by only a small fraction of single-CpG methylation states. In support of such a notion, the unique components of a DNA methylation “age” signature are contained in ∼353 CpGs sites, presumably representing a random sample of a total age signature that involves many more sites not detected using the reduced representation strategies from which these signatures have been derived.”

Also, in The epigenetic clock theory of aging the originator of the epigenetic clock characterized HSCs as an effective intervention against epigenetic aging:

“In vivo, haematopoietic stem cell therapy resets the epigenetic age of blood of the recipient to that of the donor.”

https://www.cell.com/stem-cell-reports/article/S2213-6711(18)30308-4/fulltext “High-Resolution Single-Cell DNA Methylation Measurements Reveal Epigenetically Distinct Hematopoietic Stem Cell Subpopulations”

Epigenetic effects of breast cancer treatments

This 2018 UC San Diego review subject was the interplay between breast cancer treatments and their effects on aging:

“Although current breast cancer treatments are largely successful in producing cancer remission and extending lifespan, there is concern that these treatments may have long lasting detrimental effects on cancer survivors, in part, through their impact on non-tumor cells. It is unclear whether breast cancer and/or its treatments are associated with an accelerated aging phenotype.

In this review, we have highlighted five of nine previously described cellular hallmarks of aging that have been described in the context of cytotoxic breast cancer treatments:

  1. Telomere attrition;
  2. Mitochondrial dysfunction;
  3. Genomic instability;
  4. Epigenetic alterations; and
  5. Cellular senescence.”


The review was full of caveats weakening the above graphic’s associations. To their credit, these reviewers at least presented some of the contrary evidence, and didn’t continue on with a directed narrative as many other reviewers are prone to do:

  1. “Telomere attrition – Blood TL [telomere length] was not associated with chemotherapy in three out of four studies;
  2. Mitochondrial dysfunction – How cancer therapies affect cellular energetics as they relate to rate of aging is unclear;
  3. Genomic instability – Potentially contributing to accelerated aging;
  4. Epigenetic alterations – Although some of the key regulators of these processes have begun to be identified, including DNA and histone methylases and demethylases, histone acetylases and de-acetylases and chromatin remodelers, how they regulate the changes in aging through alteration of global transcriptional programs, remains to be elucidated; and
  5. Cellular senescence – Dysregulated pathways can be targeted by cytotoxic chemotherapies, resulting in preferential cell death of tumor cells, but how these treatments also affect normal cells with intact pathways is unclear.”

https://www.sciencedirect.com/science/article/pii/S1879406818301176 “Breast cancer treatment and its effects on aging” (not freely available)


The originator of the epigenetic clock methodology was a coauthor of the review. Only one of his works was cited in the Epigenetic alterations subsection:

https://link.springer.com/article/10.1007%2Fs10549-017-4218-4 “DNA methylation age is elevated in breast tissue of healthy women”

This freely-available 2017 study quoted below highlighted that epigenetic clock measurements as originally designed were tissue-specific:

“To our knowledge, this is the first study to demonstrate that breast tissue epigenetic age exceeds that of blood tissue in healthy female donors. In addition to validating our earlier finding of age elevation in breast tissue, we further demonstrate that the magnitude of the difference between epigenetic age of breast and blood is highest in the youngest women in our study (age 20–30 years) and gradually diminishes with advancing age. As women approach the age of the menopausal transition, we found that the epigenetic of age of blood approaches that of the breast.”

Additional caution was justified in both interpreting age measurements and extending them into “cellular hallmarks” when the tissue contained varying cell types:

“Our studies were performed on whole breast tissue. Diverse types of cells make up whole breast tissue, with the majority of cells being adipocytes. Other types of cells include epithelial cells, cuboidal cells, myoepithelial cells, fibroblasts, inflammatory cells, vascular endothelial cells, preadipocytes, and adipose tissue macrophages.

This raises the possibility that the magnitude of the effects we observe, of breast tissue DNAm age being greater than other tissues, might be an underestimation, since it is possible that not all of the cells of the heterogenous sample have experienced this effect. Since it is difficult to extract DNA from adipose tissue, we suspect that the majority of DNA extracted from our whole breast tissues was from epithelial and myoepithelial cells.”

Allergies and epigenetic histone modifications

This 2018 German review provided short summaries of 44 studies on the contribution of histone modifications to allergies. An overall summary of their search results was:

“There are at least two levels at which the role of histone modifications is manifested.

  • One is the regulation of cells that contribute to the allergic inflammation (T cells and macrophages) and those that participate in airway remodeling.
  • The other is the direct association between histone modifications and allergic phenotypes.

Inhibitors of histone-modifying enzymes may potentially be used as anti-allergic drugs. Furthermore, epigenetic patterns may provide novel tools in the diagnosis of allergic disorders.”


This type of search is what’s expected of researchers who will perform either:

  • A meta-analysis of studies selected from the search results; or
  • Their own study.

These reviewers didn’t indicate that they were proceeding along either path.

The review was fine for the purpose of presenting current studies of the subject. But the review was just the preparatory stage of research.

https://aacijournal.biomedcentral.com/articles/10.1186/s13223-018-0259-4 “Histone modifications and their role in epigenetics of atopy and allergic diseases”

Epigenetic variations in metabolism

This 2018 German review was comprehensive for its subject, epigenetic control of variation and stochasticity in metabolic disease. I’ll focus on one aspect, phenotypic variation:

“Phenotypic [Mendelian] variation can result both from gain- and loss-of-function mutations. Because of the extreme interconnectivity of cell regulatory networks, even at the cellular level, predicting the impact of a sequence variant is difficult as the resultant variation acts:

  • In the context of all other variants and
  • Their potential additive, synergistic and antagonistic interactions.

This phenomenon is known as epistasis.

∼98.5% of our genome is non-protein-coding: it is pervasively transcribed, and its transcripts can support regulatory function. Among the best functionally characterized non-coding RNAs (ncRNAs) arising from these sequences are microRNAs (miRNAs)

Environmental [non-Mendelian] variation or ‘stimuli’ occurring during critical windows of susceptibility can elicit lifelong alterations in an individual’s phenotype. Intergenerational metabolic reprogramming [in fruit flies] results from global alterations in chromatin state integrity, particularly from reduced H3K27me3 and H3K9me3 [histone] domains.

The broad variation of fingerprints in humans is thought to depend to a large degree on stochastic variation in mechanical forces. These clear examples of inducible multi-stable or stochastic variation highlight how little we know about the landscape of potential phenotypic variation itself.

Consensus estimates of heritability for obesity and T2D are ∼70% and ∼35% respectively. The remaining, unexplained component is known to involve gene–environment interactions as well as non-Mendelian players.”


Although the above graphic displays transgenerational inheritance for humans, the reviewers didn’t cite any human studies that adequately demonstrated causes for and effects of transgenerational epigenetic inheritance.

I’ve read the cited Swedish and Dutch studies. Their designs, methods, and “correlate with” / “was associated with” results didn’t provide incontrovertible evidence from the F0 great-grandparents, F1 grandparents, F2 parents, and F3 children. It’s necessary to thoroughly study each generation to confirm definitive transgenerational epigenetic inheritance causes and effects.

As noted in How to hijack science: Ignore its intent and focus on the 0.0001%, there aren’t any such published studies to cite. Researchers urgently need to do this human research, and stop using these poor substitutes [1] to pretend there are already adequately evidenced transgenerational epigenetic inheritance human results.

I downgraded the review for treating research of this and other subjects as faits accomplis. It’s opposite ends of the evidential spectrum to state “how little we know about the landscape of potential phenotypic variation,” and in the same review, speciously extrapolate animal experiments into putative human results.

https://www.sciencedirect.com/science/article/pii/S2212877818301984 “Epigenetic control of variation and stochasticity in metabolic disease”


[1] As an example of the poor substitutes for evidence, a researcher referred me to the 2013 “Transgenerational effects of prenatal exposure to the 1944–45 Dutch famine” which is freely available at https://obgyn.onlinelibrary.wiley.com/doi/full/10.1111/1471-0528.12136 as a study finding human transgenerational epigenetic inheritance.

The methods section showed:

  • The study’s non-statistical data was almost all self-reported by a self-selected sample of the F2 grandchildren, average age 37.
  • No detailed physical measurements or samples were taken of them, or of their F1 parents, or of their F0 grandparents, all of which are required as baselines for any transgenerational epigenetic inheritance.
  • No detailed physical measurements or samples were taken of their F3 children, which is the generation that may provide evidence for transgenerational findings if the previous generations also have detailed physical baselines.

The study’s researchers drew enough participants (360) such that their statistics package allowed them to impute and assume into existence a LOT of data. But the scientific method constrained them to make factual statements of what the evidence actually showed. They admitted:

“In conclusion, we did not find a transgenerational effect of prenatal famine exposure on the health of grandchildren in this study.”

Yet this study is somehow cited for evidence of human transgenerational epigenetically inherited causes and effects.

A study of our evolutionary remnants

This 2018 Michigan human cell study subject was factors affecting the expression of human endogenous retroviruses:

“We provide a comprehensive genomic and epigenomic map of the more than 500,000 endogenous retroviruses (ERVs) and fragments that populate the intergenic regions of the human genome.

The repressive epigenetic marks associated with the ERVs, particularly long terminal repeats (LTRs), show a remarkable switch in silencing mechanisms, depending on the evolutionary age of the LTRs:

  • Young LTRs tend to be CpG-rich and are mainly suppressed by DNA methylation, whereas
  • Intermediate age LTRs are associated predominantly with histone modifications, particularly histone H3 lysine 9 (H3K9) methylation.
  • The evolutionarily old LTRs are more likely inactivated by the accumulation of loss-of-function genetic mutations.

Because the expression of ERVs is potentially dangerous to the host cell, understanding the repressive mechanisms is important. Earlier studies have implicated the aberrant expression of ERVs in autoimmune disease pathogenesis. However, this “enemy within” may also play a beneficial role in cancer therapy.

The same kinds of chromatin dynamics appear to be used both by LTRs and genes.”


I wasn’t going to curate this study before I saw the above graphic of our Boreoeutherian ancestor. Evolutionary subjects seem very abstract until an artist reconstructs the data visually.

https://genome.cshlp.org/content/early/2018/07/03/gr.234229.118.full.pdf “Switching roles for DNA and histone methylation depend on evolutionary ages of human endogenous retroviruses” (not freely available)