Trained immunity responses to bacterial infections

This 2019 Swiss rodent study investigated immune responses to five types of bacterial infections:

“The innate immune system recalls a challenge to adapt to a secondary challenge, a phenomenon called trained immunity. Trained immunity protected mice from a large panel of clinically relevant bacterial pathogens inoculated systematically and locally to induce peritonitis, enteritis and pneumonia.

Induction of trained immunity remodeled bone marrow and blood cellular compartments, providing efficient barriers against bacterial infections. Protection was remarkably broad when considering the pathogens and sites of infection tested.

We are running experiments to delineate the length of protection conferred by trained immunity. Trained immunity is most typically induced with β-glucan.

Mice were injected with methicillin-resistant Staphylococcus aureus (MRSA). Trained mice survived better than control mice (31% vs. 0% survival) and had 10-fold less bacteria in blood 2 days post-infection.

Mice were challenged with a lethal dose of Listeria monocytogenes. Most strikingly, all trained mice survived infection while all control mice died within 5 days. Bacteria were not detected in blood collected from trained mice 2 and 3 days post-infection.”


One of the coauthors also published:

https://academic.oup.com/jid/advance-article/doi/10.1093/infdis/jiz692/5691195 “Trained immunity confers broad-spectrum protection against bacterial infections”

Clearing out the 2019 queue of interesting papers

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/s00702-019-02048-2miRNAs 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

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 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”

Too cheap for clinical trials

Let’s compare and contrast a 2019 meta-analysis and a 2017 review of using acetyl-L-carnitine to treat diabetic neuropathy.

A 2019 Brazilian meta-analysis Acetyl‐L‐carnitine for the treatment of diabetic peripheral neuropathy of four previous trials stated:

  • “The risk of bias was high in both trials of different ALC doses and low in the other two trials.
  • No included trial measured the proportion of participants with at least moderate (30%) or substantial (50%) pain relief.
  • At doses greater than 1500 mg/day, ALC reduced pain more than placebo. This subgroup analysis should be viewed with caution as the evidence was even less certain than the overall analysis, which was already of very low certainty.
  • The placebo-controlled studies did not measure functional impairment and disability scores.
  • No study used validated symptom scales.
  • Two studies were funded by the manufacturer of ALC and the other two studies had at least one co-author who was a consultant for an ALC manufacturer.

Authors’ conclusions:

  • We are very uncertain whether ALC causes a reduction in pain after 6 to 12 months treatment in people with DPN, when compared with placebo, as the evidence is sparse and of low certainty.
  • Data on functional and sensory impairment and symptoms are lacking, or of very low certainty.
  • The evidence on adverse events is too uncertain to make any judgements on safety.”

A 2017 Italian review Effects of acetyl-L-carnitine in diabetic neuropathy and other geriatric disorders stated:

“A long history of diabetes mellitus and increasing age are associated with the onset of diabetic neuropathy, a painful and highly disabling complication with a prevalence peaking at 50% among elderly diabetic patients. The management of diabetic neuropathy is extremely difficult: in addition to the standard analgesics used for pain control, common treatments include opioids, anticonvulsants, antidepressants, and local anesthetics, alone or in combination. Such therapies still show a variable, often limited efficacy, however.

Many patients do not spontaneously report their symptoms to physicians, but, if asked, they often describe having experienced a persistent and non-abating pain for many years. The prevalence of painful symptoms is just as high in patients with mild neuropathy as in those with more advanced DPN.

Through the donation of acetyl groups, ALC exerts a positive action on mitochondrial energy metabolism. ALC has cytoprotective, antioxidant, and antiapoptotic effects in the nervous system.

ALC has also been proposed for the treatment of other neurological and psychiatric diseases, such as mood disorders and depression, dementia, Alzheimer’s disease, and Parkinson’s disease, given that synaptic energy states and mitochondrial dysfunctions are core factors in their pathogenesis. Compared to other treatments, ALC is safe and extremely well tolerated.”

“In nerve injury, the mGlu2 receptor overexpressed by ALC binds the glutamate, reducing its concentration in the synapses with an analgesic effect. ALC may improve nerve regeneration and damage repair after primary nerve trauma.”


Where will the money come from to realize what the 2017 review promised, as well as provide what the 2019 meta-analysis required?

Do we prefer the current “limited efficacy” treatments of “opioids, anticonvulsants, antidepressants, and local anesthetics?”

Who will initiate clinical trials of a multiple of the normal dietary supplement dose (500 mg at $.25 a day, retail)? How profitable is a product whose hypothetical effective dosage for diabetic neuropathy (3000 mg) sells for only $1.50 a day?