LXR (Liver X Receptor) Inhibition as a Root Cause of ME/CFS?

[mariovitali]

@Valentijn

So do you agree that a TT in that particular Gene results in impaired LXR functioning or not?

Yes or No answer please, Thanks

 

[Valentijn]

@Valentijn

So do you agree that a TT in that particular Gene results in impaired LXR functioning or not?

Yes or No answer please, Thanks

Read the research into that SNP if you really care about finding the answer.

But if there isn't any research, then we can guess that the SNP probably doesn't have any impact, because most SNPs have no impact. As a SNP in an intron, it's especially unlikely to have any impact, and if it does it's going to be a very small one.

 

[mariovitali]

@Valentijn

So why does the link provided in selfdecode says that TT is associated with impaired LXR functioning?

I hope you don’t use the same “logic” here as the one where you suggest that normal liver enzymes Rule out Liver disease.

 

[Valentijn]

So why does the link provided in selfdecode says that TT is associated with impaired LXR functioning?

No idea. Do they list their source?

I hope you don’t use the same “logic” here as the one where you suggest that normal liver enzymes Rule out Liver disease.

Your repeated attempts to change the subject are transparent and tiresome.

 

[mariovitali]

@Valentijn

Yet one more example of "scientific" thinking from you.


Did you actually search before dismissing the information that was posted?

In a case-control study of 155 preeclamptic and 305 normal pregnancies based on a powerful high-resolution melting curve analysis technique, we showed that the NR1H2 polymorphism rs2695121 was strongly associated with PE (Pre-eclampsia)

From the same study :

Preeclampsia is a frequent complication of pregnancy and a leading cause of perinatal mortality. Both genetic and environmental risk factors have been identified. Lipid metabolism, particularly cholesterol metabolism, is associated with this disease. Liver X receptors alpha (NR1H3, also known as LXRalpha) and beta (NR1H2, also known as LXRbeta) play a key role in lipid metabolism. They belong to the nuclear receptor superfamily and are activated by cholesterol derivatives. They have been implicated in preeclampsia because they modulate trophoblast invasion and regulate the expression of the endoglin (CD105) gene, a marker of preeclampsia. The aim of this study was to investigate associations between the NR1H3 and NR1H2 genes and preeclampsia.

https://bmcmedgenet.biomedcentral.com/articles/10.1186/1471-2350-12-145

 

[Valentijn]

Yet one more example of "scientific" thinking from you.

Sorry, what is it that you think is unscientific about suggesting you verify your sources? Now you just need to do the same thing for all of the other SNPs you believe are relevant

But P-values of 0.039 and 0.049 are unusually high to be considered significant in a SNP study. We see a threshold of 0.05 commonly in psychological research, but that's because the field is a bit of a methodological joke.

Though apparently it's actually the major allele which has a slight increased risk of preclampsia. So that would be 34% heterozygous and 61% homozygous. Meaning 95% of people would be at risk. Hence the more sensible interpretation is that those 95% have a normal level of risk, and the remaining 5% got lucky and have abnormally low risk.

And, as predicted, it's a very small effect.

 

[adreno]

@mariovitali

I think focusing on SNPs is mostly a dead end for now. As Valentijn says, a single SNP isn't going to have much impact. Combinations of huge amounts of gene mutations might have impact, but is too difficult to map for now. This doesn't mean that the theory about e.g. LXR is necessarily wrong, though.

 

[mariovitali]

@adreno

I have stated many times in this Thread and other threads that my hypothesis is based on the combination of SNPs and not individual ones. As an example, a single SNP on LXR may have no effect but with combined SNPs on CYP27A1 + LXR + PPARs then you may make the hypothesis that this combination can create problems.

I saw studies of this particular Gene suggesting associations with several diseases and conditions. Yes, association does not imply causation but i still do not understand why all these studies are dismissed so easily as not being relevant.

How can we dismiss so easily things if there are so many factors at play? And since there are so many factors at play, does this mean that we should not give it a try?

 

[adreno]

I have stated many times in this Thread and other threads that my hypothesis is based on the combination of SNPs and not individual ones. As an example, a single SNP on LXR may have no effect but with combined SNPs on CYP27A1 + LXR + PPARs then you may make the hypothesis that this combination can create problems.

Well I don't know if a combination of three SNPs is gonna do it, or how many it would take. But I am by no means an expert. I suppose you would have to calculate how rare those combinations are, and how this compares to the prevalence of ME. But I believe that for most diseases and disorders, it has proven extremely difficult to map the the gene mutations involved. And research only seems available for relatively few SNPs ATM.

 

[aquariusgirl]

Fascinating. But we don't generally have all of the LXR related problems, do we? Atherosclerosis, diabetes, inflammation, and Alzheimer's disease. Well, inflammation for sure, but many possible causes of that. For those who have 23andMe results, might be interesting to check for the LXR bad genes.

1. RS1405655 (LXR)
2. RS17373080 (LXR)
3. RS2279238 (LXR)
4. RS2695121 (LXR)

My Snps:
TT
CC
CC
CT

 

[pattismith]

Fascinating. But we don't generally have all of the LXR related problems, do we? Atherosclerosis, diabetes, inflammation, and Alzheimer's disease. Well, inflammation for sure, but many possible causes of that. For those who have 23andMe results, might be interesting to check for the LXR bad genes.

1. RS1405655 (LXR)
2. RS17373080 (LXR)
3. RS2279238 (LXR)
4. RS2695121 (LXR)

mine are ( my 23andme data miss two)

TT
??
CC
??

 

[Jesse2233]

Mine:

T / T
C / C
C / T
T / T

 

[pattismith]

@adreno

I have stated many times in this Thread and other threads that my hypothesis is based on the combination of SNPs and not individual ones. As an example, a single SNP on LXR may have no effect but with combined SNPs on CYP27A1 + LXR + PPARs then you may make the hypothesis that this combination can create problems.

Combinations and haplotypes are very interesting to study, the easiest combinations to explore are those between genes involved in the same metabolism chains, for example:

Gene-gene interaction between heme oxygenase-1 and liver X receptor-beta and Alzheimer's disease risk.
Infante J1, Rodríguez-Rodríguez E, Mateo I, Llorca J, Vázquez-Higuera JL, Berciano J, Combarros O.
Author information
Abstract
Increasing cellular cholesterol levels results in high amyloid beta (Abeta) synthesis, which is central to the pathogenesis of Alzheimer's disease (AD). Heme oxygenase-1 (HO-1) stimulates oxidation of glial cholesterol to oxysterols, and increased oxysterol concentrations may protect neural tissues by activation of liver X receptor-beta (LXR-beta), which induces transcription of genes associated with reduction of cellular cholesterol concentrations and decrease of Abeta formation. Underexpression of HO-1 in concert with underexpression of LXR-beta would result in increased cholesterol accumulation, induction of Abeta production, and increased AD risk. We examined a functional polymorphism in the HO-1 promoter region (-413, rs2071746), and three LXR-beta polymorphisms in introns 2 (rs2695121), 5 (rs1052533), and 7 (rs1405655), in a group of 414 Spanish AD cases and 442 controls. Subjects carrying both the HO-1 (-413) TT genotype and the LXR-beta (intron 2 =rs2695121) TT genotype (OR=2.63), LXR-beta (intron 5 =rs1052533) AA genotype (OR=1.90), or LXR-beta (intron 7=rs1405655) TT genotype (OR=1.75) had a higher risk of developing AD than subjects without these risk genotypes. Considering synergistic effects between polymorphisms in cellular cholesterol efflux-related genes may help in determining the risk profile for AD.

 

[mariovitali]

@pattismith @adreno @Jesse2233

Cellular Cholesterol efflux is of particular importance i think. Note also below the mention on macrophages. For example :

In particular, accumulating levels of cellular cholesterol lead to the formation of specific sterols that activate the liver X receptor (LXR)–retinoid X receptor (RXR) heterodimeric transcription factors. The LXR–RXR heterodimers have a range of anti- inflammatory activities — including upregulating the expression of ATP-binding cassette transporters (ABC transporters) ABC subfamily A member 1 (ABCA1) and ABCG1, and promoting the efflux of cholesterol from macrophages — and thus may counter the amplification of TLR signalling by cellular cholesterol accumulation. ABCA1 and ABCG1 promote efflux of cholesterol onto HDL particles or onto the lipid-poor form of the main HDL protein, apolipoprotein A1 (APOA1), and initiate the process of reverse cholesterol transport (RCT), in which cholesterol is transported from peripheral tissues back to the liver via the lymphatics and bloodstream, followed by its excretion into bile and faeces9,10. Of note, TLR activation suppresses LXR activity on its target genes, causing decreased macrophage cholesterol efflux11, which probably results in an amplification of TLR signalling.

I looked at APOA1 and found rs670 with MAF=18%, minor allele = T

This gene was found to have in a sample of 62 people :

No mutation = 53.45%
Homozygous = 3.45%
Heterozygous = 41.38%

@Valentijn

a) Is the observed difference between MAF and Heterozygous considered significant and warrant this particular gene for further investigation? If you also can point me to relevant information on how you make these calculations it would be great.

b) Do you agree that combination of Gene SNPs may or may not result to a certain phenotype?

c) In the latest CFS/ME symposium G-Protein coupled receptors were mentioned. Do you know if any relevant SNPs were given?

@all
Before any hypotheses being considered, i am very concerned about the fact that several CFS patients where found having Liver Fibrosis. It is also worth saying that all of these patients had normal Liver enzymes (CC : @Valentijn )

I am not suggesting that everyone has Liver Fibrosis, i am just saying that this should be looked at. In case anyone takes a Fibroscan test, please let us know the results.

EDIT : @Jesse2233 Rapamycin appears to be important for yet one possible issue of CFS/ME. Will post more about this soon.

 

[Valentijn]

I looked at APOA1 and found rs670 with MAF=18%, minor allele = T

This gene was found to have in a sample of 62 people :

No mutation = 53.45%
Homozygous = 3.45%
Heterozygous = 41.38%

a) Is the observed difference between MAF and Heterozygous considered significant and warrant this particular gene for further investigation? If you also can point me to relevant information on how you make these calculations it would be great.

There's a couple simple formulas for calculating expected frequency (MAF = Minor Allele Frequency):
minor homozygous = MAF x MAF
heterozygous = (1-MAF) x MAF x 2
major homozygous = (1-MAF) x (1-MAF)

If your sample is primarily Caucasian (it probably is, due to the availability and use of the 23andMe test), then it's most meaningful to compare it to allele data from a European sample. Otherwise it might look like there is significant variation, but the variation between different ethnic groups may simply be down to a matter of chance and historical separation.

dbSNP is a good source of both very large overall samples, and various ethnic samples. If there isn't a large sample (100+) with similar ethnicity to your sample, then the sample might not be a very good one to draw any conclusions from. EUR samples are likely to be a lot better than CEU samples, due to the CEU samples being from Caucasians in a single state in the US where a smaller religion is very dominant, and has resulted in some insularity that is unlikely to represent wider populations.

If we scroll to the bottom of https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=rs670 we can see that the 2nd entry under "Population Diversity" is for EUR with a size of 1006. 1006 is the number of alleles, not people, so it's only 503 people. Which is still pretty big, for a specific ethnic sample. To the right of that entry, the percentage of alleles are listed, with 15.4% of alleles being the minor allele.

There's also a smaller European sample of 48, with a drastically different rate of 31.3%, which is a good illustration of the problem of working off of smaller samples As well as the amount of variation that can be seen in a completely normal sample, down to random chance when a great many samples are taken. Basically, it's illustrating why even a big difference in your sample compared to another sample might not mean anything. When hundreds or thousands of variables (SNPs) are compared, it's guaranteed that some rates will randomly be different.

With the equations listed above, we can determine the expected rate in your sample:
Minor homozygous = 0.154 x 0.154 = 2.4%
Heterozygous = (1 - 0.154) x 0.154 x 2 = 26.1%
Major homozygous = (1 - 0.154) x (1 - 0.154) = 71.6%

So that's very similar for the minor homozygous, but fairly different for heterozygous. But if it was particularly relevant, I'd expect to see both a much lower MAF, and more of an increase in being homozygous for the minor allele. Common heterozygous mutations are rarely having a sizable impact.

b) Do you agree that combination of Gene SNPs may or may not result to a certain phenotype?

Yes, to a limited extent. Compound heterozygous missense mutations (which can't be determined with 23andMe data) certainly can. But I'm not convinced regarding haplotypes. Those studies typically find no direct association between increased prevalence of a SNP and a condition, then start combining SNPs until they get a different prelevance compared to controls. I haven't seen any studies making proper statistical corrections to account for the extreme likelihood of randomly generating a meaningless correlation.

But the broader problem is that genes generally don't really seem to work in a way which supports a model where several SNPs have literally no impact on their own, but do have an impact when they're all present together. If a study is properly powered, it should be able to find even those individual tiny impacts.

And haplotypes involving different genes seems like an especially absurd proposition. If the SNP on each individual gene has absolutely no impact on its gene, then they are making a completely normal protein product. There's no conceivable way that those normal proteins will somehow interact differently. Actual differences can certainly aggregate, but there has to be some difference to start with.

I'm also not aware of any studies which have demonstrated a functional difference in the protein created by a haplotype composed of SNPs which have no impact at all on their own. Instead, haplotype studies are comparing the prevalence of SNPs in people with a certain physical, personality, or behavioral trait, against normal controls. Good genetic research should go deeper, and demonstrate how the genetic variation results in the difference in phenotype. Most researchers playing with SNPs lack the skills to do that. But at the very least, there needs to be independent replication with new samples from different patients and different controls - this will usually make false-positives evaporate.

c) In the latest CFS/ME symposium G-Protein coupled receptors were mentioned. Do you know if any relevant SNPs were given?

It's "ME/CFS". But no, I didn't watch the OMF conference, since I have trouble processing informational videos, and I do much better with text. Additionally, claims at conferences lack subtlety and context that is included in the published version, so I tend not to get too excited about that sort of thing anyhow. Better to wait for the paper.

 

[pattismith]

And haplotypes involving different genes seems like an especially absurd proposition. If the SNP on each individual gene has absolutely no impact on its gene, then they are making a completely normal protein product. There's no conceivable way that those normal proteins will somehow interact differently. Actual differences can certainly aggregate, but there has to be some difference to start with.

I'm also not aware of any studies which have demonstrated a functional difference in the protein created by a haplotype composed of SNPs which have no impact at all on their own. Instead, haplotype studies are comparing the prevalence of SNPs in people with a certain physical, personality, or behavioral trait, against normal controls.

Well, I'm not good at giving myself explanation about it, so I will call Katarina Tengvall (Uppsala University) scientist publications for help, she worked mostly on Canine Atopic Dermatitis (which is a complexe syndrome with hereditary and environmental factors and different patways involved) and especially on German Sheperd breed....

https://uu.diva-portal.org/smash/get/diva2:846337/FULLTEXT01.pdf

extracts:

"Genetic mapping of complex traits
The mapping of complex diseases, which are caused by multiple genes/mutations and most often influenced by environmental factors, is perhaps the biggest challenge in medical genetics. Mutations can be SNPs, insertions or deletions of single nucleotides or larger DNA segments, and duplications resulting incopy number variants (CNVs). When mutations occur in functionally important genetic regions, either coding or cis-regulatoryele ments, they can result in phenotypic changes (Figure 2).
Cis-regulatory elements are DNA-stretches, includingpromoters, enhancers, and silencers that regulate the transcription of genes. Mutations that cause simple Mendelian traits are usually protein-coding mutations, resulting in a dysfunctional protein across all tissues where it is expressed. In complex diseases, the majority of the mutations are in regulatory elements with an effect limited to certain tissues or developmental stages depending on the location of the mutation. These mutations may alter the binding capability of RNA-polymerase and transcription factors,thus affecting the expression of the gene."


"In human, the small effect sizes of most associated SNPs (OR<1.5) in GWAS account for only a small proportion of the heritability (i.e.the proportion of the phenotype explained by genetics) of the studied complex traits. This limits the applicability of the identified mutations for risk predictions. Furthermore, a large proportion ofthe genetic risk is still unexplained, often referred to as the missing heritability. The missing heritability has been widely discussed and there are various strategies proposed to improve the methodology. These include: increasing sample sizes by combining GWAS (meta-analyses), investigating rare variants through targeted/exome sequencing, and evolving the more complicated methodologies that take into account epistasis and epigenetic effects on complex traits [3]. Two opposing models have been proposed to explain the missing heritability: the common disease/common variant
(CD/CV model) and the common disease/rare variant (CD/RV model) hypotheses. The proportions between the two are likely to vary between different complex phenotypes. Detection of less-common SNPs and CNVs involved in diseases has just started to accumulate in the scientific literature. The increased coverage of SNPs on the human SNP-chips will also aid in detecting more common variants than previously.
However, the high density SNP-chips also require even larger sample sizes to detect the associations. "
...

"In the all breeds association analysis, we identified an associated haplotype consisting of seven SNPs spanning intron 6 of PKP2 across the 3’UTR and19kb downstream of PKP2 . The risk haplotype was present in 37.3% of the
GSD cases and 9.6% of the GSD controls and was carried also by Labrador retrievers (LRs) and by one Golden retriever (GR), but not detected in any of the other breeds. Half of the haplotype was shared by West Highland white
terriers (WHWTs). Despite being rare, the risk haplotype conferred an OR in GSDs of 5.7 compared to 4.1 for the
top GWAS SNP. Using the re-sequence data from Paper I, we searched for candidate variants based on the
risk/control haplotype pattern and the presence of the risk alleles in HRCAD breeds, human, or other species, and identified nine candidates."

...
"We phased the four SNPs and defined two risk haplotypes and one common control haplotype in GSDs. One risk haplotype consisted of the risk alleles at all four loci,whereas the other did not carry the rare risk allele at SNP 27: 19093355. In GSDs, 61.5% of the cases carried risk haplotype(s) compared to 29.8% of the controls (p=3.7x10
-5, OR=3.8). The risk haplotypes were also detected in WHWTs, Labrador Rs, and Golden Rs."

and Conclusion of paper II:

"Breed-specific risk factors. The complex nature of CAD where many genetic risk factors, some of which
are breed-specific, likely act together may explain why the risk haplotype was not associated in LRs or WHWTs. Possibly, this risk haplotype is merely a modifying locus, additional to a major locus in these breeds. Thus, the
PKP2-risk haplotype may solely predispose the whole breed to CAD and the 50 final trigger for an individual to become atopic may be due to another hither to unknown major risk factor. For the WHWTs, the low number of cases and controls, and thereby the lack of statistical power, may be another reason for the lack of association."

 

[mariovitali]

@Valentijn

First of all, Thank you for the time you spent writing all this.


I never suggested that i have knowledge about SNPs. It is not my job to evaluate SNPs and having incomplete knowledge on a subject -and even worse- having the false assumption that i am knowledgeable where in fact i am not, leads to several problems.

What i was hoping (and still am) is to combine Man (=Researchers) and Machine (=Machine Learning) to come up with informed hypotheses as to what causes ME/CFS. My lack of knowledge on SNPs has nothing to do with the possibility that Machine Learning -if done properly- can shed new light on what is going on.

Unfortunately, I am still unable to understand how all of the published research and numerous SNPs found to be associated with disease are not relevant and can be dismissed that easily though.

Also let me elaborate to this further :

So that's very similar for the minor homozygous, but fairly different for heterozygous. But if it was particularly relevant, I'd expect to see both a much lower MAF, and more of an increase in being homozygous for the minor allele. Common heterozygous mutations are rarely having a sizable impact.

OK, i understand your point here. But this way of thinking does not take into consideration the compounding effects of having small issues along a specific pathway. Do we agree on this?

 

[Valentijn]

Well, I'm not good at giving myself explanation about it, so I will call Katarina Tengvall (Uppsala University) scientist publications for help, she worked mostly on Canine Atopic Dermatitis (which is a complexe syndrome with hereditary and environmental factors and different patways involved) and especially on German Sheperd breed....

She's referring to SNPs which actually have an impact on their own, even if they aren't likely to cause disease or observable changes on their own. Most haplotypes claimed in research in humans seem to consist of SNPs which are not having any impact at all on their own.

Could you explain if you think what she has said contradicts what I said in my prior post?

 

[Valentijn]

I never suggested that i have knowledge about SNPs. It is not my job to evaluate SNPs and having incomplete knowledge on a subject -and even worse- having the false assumption that i am knowledgeable where in fact i am not, leads to several problems.

I'm very aware of your lack of understanding. Unfortunately your own awareness of it did not stop you from making treatment recommendations based on demonstrably false assumptions about genetics.

Unfortunately, I am still unable to understand how all of the published research and numerous SNPs found to be associated with disease are not relevant and can be dismissed that easily though.

I'm not dismissing those. I'm dismissing your "count the minor alleles" approach as being dishonest pseudoscience used to suck people into a treatment by falsely claiming there's a specific basis for the treatment.

You're using exactly the same methodology as Yasko, except you're selling a liver theory instead of a methylation theory. Some SNPs may be relevant, but most aren't, or the normal and overwhelmingly common allele is listed as being a problem, meaning everyone you target will supposedly have that problem. I have no objection to someone talking about how a treatment helped them, or how it might make sense based on what's known of the biochemistry, or even just "what the fuck, let's give it a try". But it's inappropriate and unethical to invent a pseudoscientific explanation to make a treatment sound more plausible.

It takes a lot of work to determine if SNPs are having an impact or not, and in many cases there is simply no research, and those SNPs cannot be assumed to be relevant. Each SNP might require an hour or more of looking over research summaries and then reading some papers more carefully to find risk alleles, effect sizes, and methodological flaws which can make the results untrustworthy. And then you need to go through the papers which showed no impact to determine which papers are more likely to be right for that SNP.

If you're going to incorporate SNPs into your theory or treatment, you have a duty to know what you're talking about. I have repeatedly referred you to free resources, but you don't seem to care enough to even spend a few hours a week learning the basics. Knowing how absurd your genetic claims are, I have absolutely no faith in anything else you are doing, and that is why I can't be bothered to look into your liver claims. I'm not going to waste my time on theories which persist in destroying their own credibility.

 

[mariovitali]

@Valentijn

I am really glad you attacked me in this way. I am also really glad that what we all say is documented here.