Quote from Johannes on October 18, 2021, 8:12 am

Key points:

• 4-oxo-retinoic acid (4-oxo-RA) is chemically and functionally highly similar to the naturally occurring 5-oxo-eicosapentaenoic acid (5-oxo-EPE)
• The C20:5 fatty acid EPE is an integral component of cell membranes that is released either mechanically through physical damage to the membrane or enzymatically in response to hypoxia
• 5-oxo-EPE is a chemoattractant for immune cells and must likely be reduced to (5R)-OH-EPE before the immune response is stopped
• Retinoic acid is metabolized to mostly (4S)-OH-RA by PTGS1, which is the target of NSAID painkillers, in a chemical reaction highly similar to the formation of (5S)-OH-EPE by ALOX5
• Expression of PTGS1 was mildly correlated with STAT3, and strongly inversely correlated with STAT5A and PPARA
• It is likely that HSD17B12 catalyzes the reduction of 4-oxo-RA to (4R)-OH-RA, which is then potentially metabolized to a substance with estrogen-like activity by CYP2U1 and CYP19A1, that is finally inactivated by HSD11B2
• Expression of HSD17B12 was highly correlated with expression of lipogenic genes, and inversely correlated with pro-inflammatory genes
• RDH10 and the unexplored HSDL2 are the best candidates for oxidizing retinol in vivo, while AKR1B10 and DHRS9 are the best candidates for reducing retinal
• Expression of STAT5A, which is activated by retinol, was correlated with many of the most downregulated genes in obesity, and additionally with PPARA, PPARG and EGFR, while expression of STAT5B was correlated with PTGS1, RARA and RXRB
• In addition to STRA6/STAT5, it appears that retinol also activates the glucocorticoid receptor (NR3C1)

Methods

I analyzed the expression of various genes in adipose tissue samples (Civelek, Wu et al. 2017) with ESGS, an app I programmed. These samples—of greater quality (and quantity) than the liver samples I had been using previously—are from a subset of METSIM study participants, which was a prospective population-based study of 10,197 Finnish men related to metabolic syndrome and cardiovascular diseases. Importantly, all the samples were from people believed to be healthy. I categorized the samples into the following groups:

• Control: all participants with BMI < 22.5 (n = 79)
• BMI 20–22.5 (n = 76); I don’t remember why I added this group, since it’s almost identical the control group (only 3 people had BMI < 20)
• BMI 22.5–25 (n = 180)
• BMI 25–27.5 (n = 240)
• BMI 27.5–30 (n = 161)
• BMI 30–32.5 (n = 67)
• BMI 32.5–35 (n = 30)

The groups seem large enough to be confident in the significance and precision of the results.

Lipogenic genes are progressively downregulated with BMI

Since I had been reading a study about fatty acid metabolism in cancer (Kuo and Ann 2018) I decided to first look at the expression of lipogenic genes. I am also using the Numbers app to generate the charts again because of its curve fitting feature. Surprisingly, all four of the tested lipogenic genes were progressively downregulated as BMI increased (-28% to -46% at BMI 32.5–35, p < 0.001), which is not what would be expected in overweight and obese subjects.

Even more surprising are the R² values calculated by Numbers (0.95–0.993), which are a measure of how good the curves fit to the data (1 is the best). According to Google, in finance an R² value of 0.7 is considered good, and in academic research, an R² of 0.75 is considered “substantial”.

Expression of STAT3, STAT5A and PPARA was correlated

Next, I tried to figure out how weight gain is even possible if all the lipogenic genes are downregulated, by comparing the expression of PPARA, which induces fatty acid oxidation, STAT5A, which is activated directly by Vitamin A and induces lipogenesis, and STAT3, which repairs damage to membranes and cells and is not directly activated by Vitamin A but likely activated by damage caused by Vitamin A.

Again, there is an almost perfect correlation between all three genes. Notably STAT3 consistently increases, indicating that there is progressively more damage that needs to be repaired as BMI increases. Additionally STAT5A was downregulated just a tiny bit more than PPARA in almost every range.

Expression of PPARA, RDH10, HSD17B12, CYP2U1 and HSD11B2 was correlated

I then began looking for other genes with the same distribution pattern as PPARA/STAT5A. A number of genes were correlated with PPARA and STAT5A, namely very-long-chain 3-oxoacyl-CoA reductase (HSD17B12), retinol-binding protein 1 (RBP1), retinol dehydrogenase 10 (RDH10), cytochrome P450 2U1 (CYP2U1) and corticosteroid 11-beta-dehydrogenase isozyme 2 (HSD11B2; data not shown for CYP2U1 and HSD11B2).

Interestingly, of all HSD17B enzymes none correlated with STAT5A as well as HSD17B12, which has not been reported to be active towards retinol. However, since the correlation is so strong, I believe that HSD17B12 is one of the primary enzymes responsible for metabolizing retinol in humans. It catalyzes the reduction of estrone’s oxo group to 17β-estradiol, which I believe is really (17R)β-estradiol, and additionally, it was recently shown to reduce the carcinogenic 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) from tobacco smoke to 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) in human lungs (Ashmore, Luo et al. 2018). Notably, 95% of the product formed was (R)-NNAL, and just 5% was (S)-NNAL. This enzyme is therefore one of the best candidates for reducing either 4-oxo-RA to (4R)-OH-RA or 4-oxo-retinol to (4R)-OH-retinol.

RDH10 oxidizes free retinol (i.e. not bound to RBP1) to retinal, with a strong preference for all-trans-retinol over 9-cis-retinol and 11-cis-retinol. Its downregulation is likely not related to substrate availability and instead a result of either PPARA, STAT5A, STAT3 or possibly other transcription factor activity. 

HSD11B2 catalyzes the inactivation of cortisol (11β-hydrocortisone) by oxidation to cortisone (11β-oxo-cortisone), and it is inhibited by licorice. While its role in retinol metabolism remains unclear, it is possible that HSD11B2 oxidizes hydroxylated retinol or RA to 4-oxo-retinol and 4-oxo-RA, respectively, contributing to the feedback loop in which 4-oxo-RA is not eliminated.

Finally, CYP2U1 is by far the most interesting of the tested enzymes due to its involvement in inflammation and the arachidonic acid signaling pathway. Recall that of all the fatty acids, retinoic acid is most chemically similar to arachidonic acid (AA; specifically eicosapentaenoic acid, EPE), since both RA and EPE are carboxylic acids, have 20 carbon atoms and five unsaturated double bonds. I believe the term EPE specifically refers to the all-cis configuration (5Z,8Z,11Z,14Z,17Z), whereas RA is either arranged with one (all-trans-RA) or two (9-cis-RA and 11-cis-RA) cis-double bonds, the first of which always being at the fifth carbon of the cyclohexene ring. The recently identified endogenous RXR receptor ligand 9-cis-13,14-dihydroretinoic acid (9CDHRA) is more similar to eicosatetraenoic acid (ETE), as both 9CDHRA and ETE have four unsaturated double bonds. The AA signaling pathway is activated in response to hypoxia, cellular insult or general stress and causes inflammation until the damage is resolved and it is inactivated. Even though it’s a little complicated, understanding the AA signaling pathway is absolutely crucial to understanding the effects of Vitamin A on the body.

The arachidonic acid signaling pathway

In general, when a cell is under stress and activates the AA pathway, the following events happen (adapted from Wikipedia):

1. Phospholipase A2 (PLA2) enzymes are activated and release all-trans-eicosapentaenoic acid (atEPE) from membrane phospholipids; atEPE is an integral component of cell membranes, and removing it not only weakens the membrane but signals to the immune system that the cell is in trouble and needs help
2. Polyunsaturated fatty acid 5-lipoxygenase (ALOX5) catalyzes oxygenation of atEPE to 5(S)-hydroperoxy-EPE, which is a radical very alike to 4-hydroperoxy-RA
3. Cellular peroxidases rapidly reduce 5(S)-hydroperoxy-EPE to 5(S)-OH-EPE
4. 5(S)-OH-EPE is oxidized to 5-oxo-EPE, which is 30–100x more potent (according to Wikipedia), by a 5-hydroxyeicosanoid dehydrogenase (5-HEDH), whose activity has been demonstrated in humans in vivo but for which no gene has yet been identified

Importantly, the fourth step in the pathway does not happen under normal physiological conditions, because it requires NADP⁺ as a co-factor, which is not present in large enough quantities in cells under normoxia. It is however present in large enough quantities after cellular insult and the resulting hypoxia. 5-oxo-ETE (which has one less double bond than 5-oxo-EPE) directly induces an immune response by activating oxoeicosanoid receptor 1 (OXER1):

“5-Oxo-ETE is a potent chemoattractant for eosinophils and has similar effects on neutrophils, basophils and monocytes. It elicits infiltration of eosinophils and, to a lesser extent, neutrophils into the skin after intradermal injection in humans. It also promotes the survival of tumor cells and has been shown to block the induction of apoptosis by 5-LO inhibitors.” (Grant, Rokach et al. 2009)

However, a different study found that 5-oxo-ETE did not promote the survival of tumor cells and instead arrested growth and induced apoptosis in all four of the tested cancer cell lines (O'Flaherty, Rogers et al. 2005). 5-oxo-15-OH-ETE, but importantly not 5-OH-ETE, produced the same results. It should be investigated whether 4-oxo-RA is an OXER1 receptor ligand.

In any case, the sequence of events is terminated either when the insulted cell is destroyed by immune cells, or when NADPH is restored, which prevents the formation of 5-oxo-EPE. The AA pathway is usually activated by the body directly in response to stress, such as bacterial infection, however it can also be induced by foreign substances, with one crucial difference in Step 2:

• Cytochrome P450 enzymes, and not ALOX5, catalyze the formation of (5R)-OH-EPE instead of (5S)-OH-EPE

This is where CYP2U1 comes into play. CYP2U1 normally terminates inflammatory signaling through the AA pathway by hydroxylating the tail of EPE at either the 20th or 19th carbon, which in the nomenclature of retinoic acid would translate to the 16th or 17th carbon. CYP2U1 was reported to metabolize many fatty acids including ETA (C20:4) and EPA (C20:5) (Chuang, Helvig et al. 2004), but its activity towards 5-hydroxylated fatty acids is unclear. Since its expression was highly correlated with the other retinol-related genes, we can assume that it plays some kind of role in metabolizing retinol, possibly oxidizing 4-OH-RA to 4,16-(OH)₂-RA, 4-oxo-RA to 4-oxo-16-OH-RA, RA to 16-OH-RA or retinol to 16-OH-retinol, however it is unlikely to be involved in the biosynthesis of 4- or 18-hydroxylated retinol derivatives like 4-oxo-RA and 4-oxo-18-OH-RA. If RA behaves similar to EPE, that would suggest that hydroxylation at the 16 position is required to inactivate RA and that hydroxylation at the 18 position promotes the inflammatory cycle.

PTGS1 could be the most important enzyme in the biotransformation of retinol

While looking at various CYP enzymes to determine which is primarily responsible for forming 4-OH-RA, I remembered the involvement of the prostaglandin G/H synthase 1 (PTGS1) enzyme. Specifically, “RA undergoes hydroperoxide (H₂O₂ or PPHP)- or arachidonic acid-dependent, PGH synthase-catalyzed metabolism as evidenced by ultraviolent [sic] spectroscopic analysis of reaction mixtures” (Samokyszyn, Chen et al. 1995). Furthermore, the formation of 4-OH-RA described by Samokyszyn et. al. is virtually identical to the biotransformation of EPE in the AA signaling pathway, since it involves formation of either a 4-hydroperoxy or a 5,6-epoxy radical. Most importantly, I discovered that expression of PTGS1 was weakly correlated with STAT3 and strongly inversely correlated with PPARA and STAT5A.

Strangely, the sum of all quadratic coefficients just barely exceeded zero:

(-0.0058) + (-0.0209) + 0.0146 + 0.0123 = 0.0002

I have not yet figured out the significance of this, but I feel like the 0.0002 is too close to zero for this to just be a random statistical effect. I also tried summing the expression of STAT3, STAT5A, PPARA and PTGS1, producing the chart below, but I’m also not sure what it means or whether it’s important.

In any case, the ratio of 4-OH-RA enantiomers produced by PTGS1 has not ben  experimentally determined, but it was shown to prefer forming (15S)-OH-ETE over (15R)-OH-ETE with a 15S/15R ratio of 7:3, or 2.3x greater production of (15S)-OH-ETE (Johnsson, Rönnberg et al. 2021), making it likely that PTGS1 preferentially forms (4S)-OH-RA. The reason for this could very plausibly be that PTGS1 has no known exogenous ligands (except atRA), and transformation of atRA by PTGS1 would therefore signal to other cells that damage to cell membranes has occurred, even though damage did not actually occur. It is also plausible that such a situation would elicit an immune response even if there was no actual damage, and that the only real damage is subsequently caused by the immune response and modulation of gene expression.

Surprisingly, PTGS1-null mice do not exhibit any major abnormalities except reduced inflammatory response after topical challenge with ETE, and decreased platelet activation, which I believe leads to increased bleeding and decreased clotting (Palma-Barqueros, Bohdan et al. 2021). Therefore, even though RA has been reported to damage cell membranes, it now appears possible that retinoic acid doesn’t directly cause this in vivo (because PTGS1-null mice showed no abnormalities), probably because RA immediately associates with transport proteins like albumin (ALB), RABP and FABP. It also appears that the damage is instead caused by immune cells recruited after progressive oxidation of free retinol to (4S)-OH-RA by PTGS1. The immune response is attenuated by formation of the (4R)-OH-RA enantiomer.

Furthermore, all available nonsteroidal anti-inflammatory drugs (NSAIDs) inhibit PTGS1 and PTGS2 with different affinities, notably flurbiprofen and ketoprofen specifically inhibit PTGS1, ibuprofen (Advil) and naproxen (Aleve) inhibit both PTGS1 and PTGS2, and diclofenac inhibits PTGS2 (Cryer and Feldman 1998). It is entirely possible that NSAIDs reduce inflammation by simply preventing pro-inflammatory metabolism of retinoic acid by PTGS. It is also possible that dietary retinol increases the risk of blood clots by increasing expression of PTGS1, although my results are only from adipocytes.

Additional verification of the correlations

In order to mathematically verify the visually apparent correlations, I updated ESGS to calculate the Pearson correlation coefficient (r) for the tested genes. I believe that this value is only meaningful for genes with 100% quantifiability (because otherwise the zero values interfere with the correlation), which notably excludes RBP1, STRA6, AKR1B10 and more. I also updated ESGS to calculate the Top 25 most up- and downregulated genes (of all 18,000 genes tested, excluding those with <75% quantifiability), in addition to the Top 25 most correlated and inversely correlated genes for any query gene.

Interestingly, STAT5A was correlated with 3 of the 5 most downregulated genes overall, namely tetratricopeptide repeat protein 36 (TTC36; r = 0.355), glycerol-3-phosphate acyltransferase 3 (GPAT3, 0.378) and spexin (SPX; 0.432), in addition to PPARA (0.665), PPARG (0.537), retinoic acid receptor RXR-beta (RXRB; 0.247), HSD17B12 (0.285), RDH10 (0.407) and epidermal growth factor receptor (EGFR; 0.477). It was also inversely correlated with PTGS1 (-0.223) and platelet-activating factor acetylhydrolase (PLA2G7; -0.337).

 The correlation between STAT5B and these genes was usually weaker or absent, except for RXRB (0.287), retinoic acid receptor alpha (RARA; 0.567), EGFR (-0.288) and PTGS1 (0.464). It is unclear why the r value for EGFR is negative for STAT5A and positive for STAT5B. STAT3 was found to be inversely correlated with PPARG (-0.409), CYP2U1 (-0.402) and RDH10 (-0.507). Furthermore, CYP2U1 was found to correlate with RARA (-0.53), PPARG (0.37) and HSD17B12 (0.32).

I then tried to identify transcription factors for retinol-related genes. The transcription factor with the highest correlation to RDH10 was identified as the glucocorticoid receptor (NR3C1; r = 0.62), whose endogenous ligands are cortisol, cortisone and aldosterone, that is pharmacologically activated by the steroid dexamethasone and inhibited by ketoconazole. Additionally, it has been reported to function as a co-activator for transcription of STAT5 target genes. Of all genes, the #3 most correlated gene with RDH10 was hydroxysteroid dehydrogenase-like protein 2 (HSDL2; r = 0.649), which has not been researched much, but appears to be theoretically capable of oxidizing retinol.

Interestingly, of all genes, HSD17B12 was most correlated with acetyl-CoA carboxylase 1 (ACACA; r = 0.669), which catalyzes the rate-limiting step in fatty acid synthesis, and it was also highly correlated with NADH-ubiquinone oxidoreductase 75 kDa subunit, mitochondrial (NDUFS1; r = 0.605), a mitochondrial enzyme that catalyzes the oxidation of NADH during respiration. In fact, none of the Top 25 genes most correlated with HSD17B12 were transcription factors, and most of them were related to mitochondrial beta-oxidation. Unexpectedly, the gene most inversely correlated with HSD17B12 was herpesvirus entry mediator (TNFRSF14; r = -0.425), and many of the other inversely correlated genes were related to immune response and membrane lipids, for example retinoic acid receptor responder protein 3 (PLAAT4; -0.405), mitogen-activated protein kinase kinase kinase 3 (MAP3K3; -0.394) and phosphoinositide 3-kinase regulatory subunit 5 (PIK3R5; -0.391).

The transcription factor most correlated with CYP2U1 was GDNF-inducible zinc finger protein 1 (GZF1; 0.678), which has been linked to morphogenesis and Larsen syndrome. Interestingly, of all genes, the circular RNA septin-9 (SEPTIN9) was most inversely correlated with CYP2U1 (-0.701), and SEPTIN9 was reported to be formed by transcription factor E2F1 (Zheng, Huang et al. 2020).

Finally, PTGS1 was highly correlated with a number genes, all of which I’m not too familiar with, most prominently acrosin-binding protein (ACRBP; 0.911), platelet factor 4 (PF4; 0.877), tetraspanin-33 (TSPAN33; 0.874) and small membrane A-kinase anchor protein (C2orf88; 0.873). Additionally, PTGS1 was inversely correlated with alpha-aminoadipic semialdehyde dehydrogenase (ALDH7A1; -0.488).

Proposed biotransformation of retinol

Based on the data, I propose the following biotransformation of retinol:

1. Retinol is oxidized to retinal by RDH10 and HSDL2
2. Retinal is either oxidized to retinoic acid by ALDH1A, or reduced back to retinol by DHRS9 and AKR1B10, and I believe the amount of retinoic acid formed is determined by the ALDH1A to (DHRS9 + AKR1B10) ratio
3. Retinoic acid is oxidized (producing free radical intermediates), in highly variable ratios, to (4S)-OH-RA and (4R)-OH-RA by numerous enzymes, the most important enzymes likely being PTGS1 (7:3 4S/4R ratio); of the CYP enzymes CYP1A1, CYP26B1 and CYP3A4 (1:1 ratio each) and CYP26C1 and CYP2C9 (both preferring 4R)
4. Under normoxia, I believe both 4-OH-RA enantiomers can be conjugated by UGT2B7 and possibly UGT1A10, resulting in their elimination, or further oxidized to 4,16-(OH)₂-RA by CYP2U1, however it is unclear how much 4-oxo-RA is formed under normoxia
   1. 4-OH-RA glucuronide is eliminated in feces
   2. 4,16-(OH)₂-RA undergoes aromatization by CYP19A1 to a substance similar to the synthetic retinoid acitretin, which I have previously posted about and will be calling “arominoic acid” (ROA), with “arominol” (ROOL; portmanteau of “aromatic” and “retinol”) being the corresponding alcohol; the product formed by CYP19A1 would therefore be called (4R)-OH-ROA; expression of CYP19A1 was not correlated with STAT5A as much as the other genes but up at BMI 32.5–35 (+118%; p < 0.001), down in VAD rat liver samples (-50%; p < 0.05; n = 7) and off in VAD mouse small intestine samples (n = 3); it seems like 4-OH-ROA would be active as an estrogen, since the aromatization of testosterone (which contains a cyclohexene ring) by CYP19A1 produces estradiol (which contains a benzene ring); is is possible that in a subsequent reaction HSD11B2 inactivates ROA by oxidizing the hydroxy group at the four position to form 4-oxo-ROA
5. Under hypoxia, substantial amounts of retinoic acid are oxidized to (4S)-OH-RA and subsequently to 4-oxo-RA, and 4-oxo-RA is reduced to (4R)-OH-RA by HSD17B12; this cycle continues indefinitely until normoxia is restored or the cell undergoes apoptosis

 Discussion

It is now no longer difficult to imagine how retinoic acid could cause auto-immune disease, since the data appears to show that retinoic acid is essentially a pro-inflammatory cytokine that is stored in the liver and, once the liver is saturated, in different types of tissue all over the body, especially in epithelial cells that constitute blood–tissue barriers, and in adipocytes, both of which were shown to express STRA6 (Amengual, Zhang et al. 2014).

To give an example, let me point out the pathogenesis of acne. It is believed that acne is caused by the opportunistic bacterium C. acnes, which resides in hypoxic areas of the skin and metabolizes cobalamin (vitamin B12). It has previously been suggested that C. acnes normally biosynthesizes vitamin B12, but when vitamin B12 from the host becomes available to it, it transforms it into porphyrins, which have been implicated by investigators as a causal factor for the inflammation in acne (Kang, Shi et al. 2015). However, it has also been shown that C. acnes synthesizes lipolytic enzymes, and that it derives energy from lipase-mediated sebum lipid degradation (Kim, Lee et al. 2020).

I propose that C. acnes is not pathogenic at all, and that it causes inflammation not by synthesizing porphyrins, but instead by hydrolyzing retinyl esters, which are abundant in epithelial cells and possibly in sebum itself. The initial liberation of retinol and subsequent oxidation to retinoic acid attracts immune cells to the region, which proceed to attack C. acnes. During this attack, which causes oxidative stress and damages healthy cells in the vicinity, even more retinol is liberated from surrounding cells, resulting in a detrimental cycle that is difficult to stop. In fact, it seems to me that one strategy that could potentially halt this chain of events is the formation of scar tissue, which I would imagine is impenetrable to lipids and retinoic acid. This would explain not only scarring in skin diseases but also for example the scarring of the liver in NASH.

It is also no longer difficult to imagine how retinoic acid could cause carcinogenesis directly. From an evolutionary standpoint, organisms and individual cells evolve when they are confronted with danger and must adapt to survive. Recall that the AA signaling pathway consists of a challenge (e.g. damage to membranes), a response which includes formation of an S-enantiomer, and a resolution which includes the formation of an R-enantiomer. When cells are challenged with retinoic acid, however, as described previously there is no simple resolution, and progressively more S-enantiomers are liberated. Since the pro-inflammatory cycle does not simply progress, but constantly escalates (through the auto-regulatory loop), progressively more evolutionary pressure is exerted on cells to resolve the challenge through mutation. It is therefore not difficult at all to imagine that, under that kind of pressure, and additionally in the presence of the ultimate morphogen retinoic acid, cells undergo transformation, which can also result in malignant transformations. Some circumstantial evidence for this theory is the dysregulation of many retinol-related genes in many different cancer cell lines.

The fact that introduction of additional exogenous retinoic acid is detrimental to cancer cells appears to further support this theory. Since the transformed cells have only mutated to adapt to endogenous concentrations of retinoic acid, they are unable to defeat the secondary challenge with even more retinoic acid. However, if additional retinoic acid is administered for a long enough period time, exactly as is the case during chemotherapy, it is only logical to expect that the transformed cells will undergo additional mutations to resist the secondary and subsequent challenges. KEYTRUDA (pembrolizumab), for example, has been widely praised as a breakthrough immunotherapy drug for various types of cancer, however in clinical trials for breast cancer its duration of response (a euphemism for how long it took until the cancer defeated the treatment) was determined to be 9.9–29.8 months, which is substantially longer than chemotherapy (5.3–15.8 months) but indicates that nonetheless, after 2.5 years, 100% of the patients were either cured or had developed resistance to the drug (in fact, only 17% of patients had tumors disappear).

(Note: Readers that are sensitive to COVID-19-related topics may skip to the next section)

During my research I really could not help but notice the striking similarities between the biological function of vitamin A and the function of COVID-19 mRNA vaccine products. Conceptually, retinoic acid is a pro-inflammatory substance that is distributed throughout the body in lipid droplets. Similarly, mRNA vaccines introduce a pro-inflammatory substance (the spike glycoprotein) that is distributed throughout the body in lipid droplets. It has been demonstrated that administration of the spike protein, without actual SARS-CoV-2 infection, is sufficient to produce COVID-19 symptoms (Lei, Zhang et al. 2021). From regulatory filings, it is also apparent that distribution from the injection site to other tissues does indeed occur, and notably, of the particles that did not remain at the injection site, 22% were recovered in the liver after intramuscular injection into rats (EMA Assessment Report, page 47). If there are indeed nefarious intentions behind the supplementation of food with vitamin A, as opposed to incompetence, and if there are also nefarious intentions behind the COVID-19 vaccine products (which has not been shown), it could be concluded that both SARS-CoV-2 (which was man-made with funding from both the US and Chinese governments) and the COVID-19 vaccines were built to perform the same function as vitamin A, namely causing illness in the long but not short term.

Final Thoughts

I hope that my investigation has helped shed some light on the biotransformation of vitamin A. The following propositions still need to be confirmed experimentally:

• (4R),16-(OH)₂-RA is aromatized by CYP19A1, forming the speculative (4R)-OH-ROA
• (4R)-OH-ROA is active as an estrogen
• (4R)-OH-ROA is oxidized by HSD11B2, forming 4-oxo-ROA
• 4-oxo-ROA, unlike 4-oxo-RA, is inactive
• 4-oxo-RA is reduced to (4R)-OH-RA by HSD17B12
• HSD17B12 metabolizes retinoids
• CYP2U1 metabolizes retinoids
• PTGS1 preferentially forms (4S)-OH-RA over (4R)-OH-RA
• (4S)-OH-RA and 4,18-(OH)₂-RA are pro-inflammatory whereas (4R)-OH-RA and (4R),16-(OH)₂-RA are anti-inflammatory and lipogenic
• Retinol or retinoic acid activate the the glucocorticoid receptor

Since retinol is stored in cells all over the body, I still cannot think of any therapeutical approaches that would attenuate retinoid toxicity, apart from not consuming any more retinol. Nonetheless, I will try to focus more on therapeutics during future research.

Finally, I will try sending my results to some of the research teams investigating Vitamin A, which will hopefully motivate them to experimentally verify some of my propositions. These experiments should not be too difficult or expensive, and the results will hopefully raise awareness about retinol toxicity in the mainstream. If my theory is correct, especially regarding cancer, the evolution of the human species as a whole has been set back an entire generation, because after chronic administration of retinol, humans have stopped evolving in the face of actual danger, and have instead begun adapting to chemically induced danger by dietary retinol.

To download or learn more about the ESGS app, see my thread on Vitamin A-induced weight gain.

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