Epigenetic causes of sexual orientation and handedness?

This 2018 Austrian human study subject was various associations of prenatal testosterone levels to fetal development:

“The available evidence suggests, albeit not conclusively, that prenatal testosterone levels may be one cause for the association of sexual orientation with handedness. Associations among women were consistent with predictions of the Geschwind–Galaburda theory (GGT), whereas those among men were consistent with predictions of the callosal hypothesis. However, research on the associations between sexual orientation and handedness appears to be compromised by various methodological and interpretational problems which need to be overcome to arrive at a clearer picture.

The GGT posits that high prenatal testosterone levels cause a delay in the fetal development of the left cerebral hemisphere which results in a right-hemisphere dominance and hence in a tendency for left-handedness. According to the GGT, high prenatal testosterone levels entail not only a masculinization of the female fetus, but also a feminization of the male fetus (contrary to neurohormonal theory). Overall, the male fetus is subjected to higher levels of intrauterine testosterone than the female fetus. The GGT is thus consistent with the higher prevalence of left-handedness among men than among women.

The callosal hypothesis applies to men only and assumes, in line with neurohormonal theory, that low prenatal testosterone levels are associated with later homosexuality. According to the CH, high prenatal testosterone enhances processes of cerebral lateralization through mechanisms of axonal pruning, thereby resulting in stronger left-hemisphere dominance and a smaller corpus callosum. Consistent with this, women have a larger corpus callosum than men.”


The study’s Limitations section included the following:

  1. “Limitations of the current study pertain to the self-report nature of our data. Behavioral data may provide differing results from those obtained here.
  2. Assessment of sexual orientation relied on a single-item measure. Utilization of rating scales (e.g., the Kinsey Sexual Orientation Scale) or of multi-item scales, and assessing different components of sexual orientation, would have allowed for a more fine-grained analysis and for a cross-validation of sexual orientation ratings with sexual attraction.
  3. Albeit both our samples were large, the proportions of bisexual and homosexual individuals were, expectedly, only small, as were effects of lateral preferences. Thus, in analysis we could not differentiate bisexual from homosexual individuals. Bisexual and homosexual individuals may differ with regard to the distribution of lateral preferences.
  4. Some effect tests in this study have been underpowered. Independent replications with even larger samples are still needed.”

The largest unstated limitation was no fetal measurements. When a fetus’ epigenetic responses and adaptations aren’t considered, not only can the two competing hypotheses not be adequately compared, but causes for the studied phenotypic programming and other later-life effects will also be missed.

https://link.springer.com/article/10.1007/s10508-018-1346-9 “Associations of Bisexuality and Homosexuality with Handedness and Footedness: A Latent Variable Analysis Approach”

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Burying human transgenerational epigenetic evidence

The poor substitutes for evidence in this 2018 US study guaranteed that human transgenerational epigenetically inherited effects wouldn’t be found in the generations that followed after prenatal diethylstilbestrol (DES) exposure:

“A synthetic, nonsteroidal estrogen, DES was administered to pregnant women under the mistaken belief it would reduce pregnancy complications and losses. From the late 1930s through the early 1970s, DES was given to nearly two million pregnant women in the US alone.

Use of DES in pregnancy was discontinued after a seminal report showed a strong association with vaginal clear cell adenocarcinoma in prenatally exposed women. A recent analysis of the US National Cancer Institute (NCI) DES Combined Cohort Follow-up Study showed elevated relative risks of twelve adverse health outcomes.

We do not have sufficient data concerning the indication for DES in the grandmother to determine whether adverse pregnancy outcomes in the third generation might resemble those of their grandmothers. Fourth generation effects of prenatal exposures in humans have not been reported.”


This study had many elements in common with its wretched cited reference [25] “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.

That study’s Methods section showed:

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

That 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.”

The current study similarly used the faulty methods 1-3 above to produce results such as:

“We do not have sufficient data concerning the indication for DES in the [F0] grandmother to determine whether adverse pregnancy outcomes in the [F2] third generation might resemble those of their grandmothers. [F3] Fourth generation effects of prenatal exposures in humans have not been reported.”

What did these researchers expect from a study design that permitted non-evidence like educational level?

Human studies of possible intergenerational and transgenerational epigenetic inheritance are urgently needed. There will be abundant evidence to discover if researchers will take their fields seriously.

https://www.sciencedirect.com/science/article/pii/S0890623818304684 “Reproductive and Hormone-Related Outcomes in Women whose Mothers were Exposed in utero to Diethylstilbestrol (DES): A Report from the US National Cancer Institute DES Third Generation Study” (not freely available)

Fear of feeling?

Here’s a 2018 article from two researchers involved in the Dunedin (New Zealand) Longitudinal Study. They coauthored many studies, including People had the same personalities at age 26 that they had at age 3.

The paper’s grand hypothesis was:

“A single dimension is able to measure a person’s liability to mental disorder, comorbidity among disorders, persistence of disorders over time, and severity of symptoms.”

The coauthors partially based this on:

“Repeated diagnostic interviews carried out over 25 years, when the research participants were 11, 13, 15, 18, 21, 26, 32, and 38 years old, and include information about seven diagnostic groups: anxiety, depression, attention deficit hyperactivity disorder, conduct disorder, substance dependence, bipolar disorder, and schizophrenia.”


https://ajp.psychiatryonline.org/doi/full/10.1176/appi.ajp.2018.17121383 “All for One and One for All: Mental Disorders in One Dimension” (not freely available)


More about the coauthors:

Two psychologists followed 1000 New Zealanders for decades. Here’s what they found about how childhood shapes later life

“Dunedin and other studies show that most people have at least one episode of mental illness during their lifetime.”


What compels people to search for “universal truths” instead of personal truths? Are we afraid of our feelings?

What if the grand hypothesis worth proving was: For one’s life to have meaning, each individual has to regain their feelings?

Eat your oats

Here’s some motivation to replenish your oats supply.

From a 2013 Canadian human review:

“Review of human studies investigating the post-prandial blood-glucose lowering ability of oat and barley food products” https://www.nature.com/articles/ejcn201325

“Change in glycaemic response (expressed as incremental area under the post-prandial blood-glucose curve) was greater for intact grains than for processed foods. For processed foods, glycaemic response was more strongly related to the β-glucan dose alone than to the ratio of β-glucan to the available carbohydrate.”

The review found that people don’t have to eat a lot of carbohydrates to get the glycemic-response benefits of β-glucan. Also, eating ~3 grams of β-glucan in whole oats and barley will deliver the same glycemic-response benefits as eating ~4 grams of β-glucan in processed oats and barley.

The glycemic index used in the review is otherwise a very flawed measure, however. It doesn’t help healthy people to rank food desirability using an unhealthy-white-bread standard.


The reviewer somewhat redeemed herself by participating in a 2018 review:

“Processing of oat: the impact on oat’s cholesterol lowering effect” https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5885279/

“For a similar dose of β-glucan:

  1. Liquid oat-based foods seem to give more consistent, but moderate reductions in cholesterol than semi-solid or solid foods where the results are more variable;
  2. The quantity of β-glucan and the molecular weight at expected consumption levels (∼3 g day) play a role in cholesterol reduction; and
  3. Unrefined β-glucan-rich oat-based foods (where some of the plant tissue remains intact) often appear more efficient at lowering cholesterol than purified β-glucan added as an ingredient.”

The review’s sections 3. Degree of processing and functionality and 4. Synergistic action of oat constituents were informative:

“Both in vitro and in vivo studies clearly demonstrated the beneficial effect of oat on cholesterolemia, which is unlikely to be due exclusively to β-glucan, but rather to a combined and synergetic action of several oat compounds acting together to reduce blood cholesterol levels.”


Another use of β-glucan is to improve immune response. Here’s a 2016 Netherlands study where the researchers used β-glucan to get a dozen people well after making them sick with lipopolysaccharide as is often done in animal studies:

β-Glucan Reverses the Epigenetic State of LPS-Induced Immunological Tolerance” https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5927328/

“The innate immune “training stimulus” β-glucan can reverse macrophage tolerance ex vivo.”

I’ve curated other research on β-glucan’s immune-response benefits in:

Adverse epigenetic effects of prenatal and perinatal anesthesia

This 2018 Chinese animal review subject was prenatal and perinatal anesthesia’s adverse epigenetic effects on a fetus/neonate:

“Accumulating evidence from rodent and primate studies has demonstrated that in utero or neonatal exposure to commonly used inhaled and intravenous general anesthetics is associated with neural degeneration and subsequent neurocognitive impairments, manifested in learning and memory disabilities.

So far, conflicting data exist about the effect of anesthetic agents on neurodevelopment in humans and no definite conclusion has been given yet.”

The inhibitors in the above graphic counter anesthesia’s effects on the fetus/neonate, summarized as:

“Epigenetic targeting of DNA methyltransferases and/or histone deacetylases may have some therapeutic value.”


Are there any physicians who take into consideration possible epigenetic alterations of a newborn’s chromatin structure and gene expression when they administer anesthesia to a human mother during childbirth?

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6079265/ “Epigenetic Alterations in Anesthesia-Induced Neurotoxicity in the Developing Brain”

A top-down view of biological goal-directed mechanisms

This 2016 US/Italy article was written from the perspective of regenerative bioengineering:

“Higher levels beyond the molecular can have their own unique dynamics that offer better (e.g. more parsimonious and potent) explanatory power than models made at lower levels. Biological systems may be best amenable to models that include information structures (organ shape, size, topological arrangements and complex anatomical metrics) not defined at the molecular or cellular level but nevertheless serving as the most causally potent ‘knobs’ regulating the large-scale outcomes.

Top-down models can be as quantitative as the familiar bottom-up systems biology examples, but they are formulated in terms of building blocks that cannot be defined at the level of gene expression and treat those elements as bona fide causal agents (which can be manipulated by interventions and optimization techniques). The near-impossibility of determining which low-level components must be tweaked in order to achieve a specific system-level outcome is a problem that plagues most complex systems.

The current paradigm in biology of exclusively tracking physical measurable and ignoring internal representation and information structures in patterning contexts quite resemble the ultimately unsuccessful behaviourist programme in psychology and neuroscience. For example, even if stem cell biologists knew how to make any desired cell type from an undifferentiated progenitor, the task of assembling them into a limb would be quite intractable.

The current state of the art in the field of developmental bioelectricity is that it is known, at the cellular level, how resting potentials are transduced into downstream gene cascades, as well as which transcriptional and epigenetic targets are sensitive to change in developmental bioelectrical signals. What is largely missing however is a quantitative understanding of how the global dynamics of bioelectric circuits make decisions that orchestrate large numbers of individual cells, spread out over considerable anatomical distances, towards specific pattern outcomes.”


Regenerative research is gathering evidence for goal-directed memory and learning that doesn’t meet current definitions. For example:

salamander

“A tail grafted to the flank of a salamander slowly remodels to a limb, a structure more appropriate for its new location, illustrating shape homeostasis towards a normal amphibian body plan. Even the tail tip cells (in red) slowly become fingers, showing that the remodelling is not driven by only local information.”

The reviewers compared their findings to several existing research and real-world-operations domains. Other models may also benefit from the concepts of:

“Quantitative, predictive, mechanistic understanding of goal-directed morphogenesis.”

I came across this article as a result of its citation in The Body Electric blog post.

“Levin drops a hint that there are photo-sensitive drugs that can control ion gates that can be used to translate a projected geometric image into a pattern of membrane potentials. He argues that the patterns encode ‘blueprints’ rather than a ‘construction manual’ based on the fact that the program is adaptive in the face of physical barriers and disruptions.”

https://royalsocietypublishing.org/doi/full/10.1098/rsif.2016.0555 “Top-down models in biology: explanation and control of complex living systems above the molecular level”

Epigenetic clock statistics and methods

This 2018 Chinese study was a series of statistical and methodological counter-arguments to a previous epigenetic clock study finding that:

“Only [CpG] sites mapping to the ELOVL2 promoter constitute cell and tissue-type independent aDMPs [age-associated differentially methylated positions].”

The study used external data sets and the newer epigenetic clock’s fibroblast data in its analyses to find:

“While we agree that specific sites mapping to ELOVL2 are special aDMPs in the sense that their effect sizes are particularly large across a number of different tissue-types, our analysis suggests that most aDMPs are valid across multiple different tissue types, suggesting that shared aDMPs are common.”

The details of each of the study’s counter-arguments were compelling. For example:

“We analyzed Illumina 850k data from an EWAS profiling blood, buccal and cervical samples from a common set of 263 women. Because blood is a complex mixture of many immune-cell subtypes, and buccal and cervical samples are highly contaminated by immune cells, we identified aDMPs in each tissue after adjustment for batch effects and cell-type heterogeneity.

Using either an FDR [false discovery rate] < 0.05 or Bonferroni adjusted P-value < 0.05 thresholds, the overlap of aDMPs between the 3 tissues was highly significant, mimicking the result obtained on blood cell subtypes. We observed a total of 2200 aDMPs in common between blood, buccal and cervix, an overlap which cannot be explained by random chance.”

The study’s Discussion section provided qualifications and limitations such as:

“It is important to point out that even if age-associated DNAm changes are widespread across the genome, downstream functional effects may be rare. While specific aDMPs may be shared between tissue-types, it is only in specific tissues or cell-types that any associated functional deregulation may be of biological and clinical significance.

https://www.aging-us.com/article/101666/text “Cell and tissue type independent age-associated DNA methylation changes are not rare but common”


The November 2018 issue of Aging also contained other articles of interest:

https://www.aging-us.com/article/101626/text “Accelerated DNA methylation age and the use of antihypertensive medication among older adults”

“DNAmAge and AA [age acceleration] may not be able to capture the preventive effects of AHMs [antihypertensive medications] that reduce cardiovascular risks and mortality.”

https://www.aging-us.com/article/101633/text “Azithromycin and Roxithromycin define a new family of senolytic drugs that target senescent human fibroblasts”

“Azithromycin preferentially targets senescent cells, removing approximately 97% of them with great efficiency. This represents a near 25-fold reduction in senescent cells.”

https://www.aging-us.com/article/101647/text “Disease or not, aging is easily treatable”

“Aging consists of progression from (pre)-pre-diseases (early aging) to diseases (late aging associated with functional decline). Aging is NOT a risk factor for these diseases, as aging consists of these diseases: aging and diseases are inseparable.”