Tag Archives: health

Unknown's avatar lassesen 8:37 am on December 28, 2024
Tags: , health, lactobacillus-probiotics, , , ,   

ME/CFS: The Evils of Lactobacillus Probiotics?

A reader wrote me today with the following question

I read your article on microbial involvement, can you explain in more detail why you recommended cutting out Lactobacillus? If I interpreted your analysis, you said lactobacillus was rare in ME/CFS, doesn’t that mean increasing it could be beneficial? “..lactobacillus shows up barely in only one result..”.Meaning lactobacillus is rare for ME/CFS patients?

I meant that there is no clear evidence of a lactobacillus deficiency with ME/CFS patients microbiomes. There are reasons to believe that it may be harmful and helps maintain ME/CFS state.

History

I am a facts/study based individual that have been reading studies, conference reports since 1990’s. Back in 1999, on eGroups CFSFM-Experimental, taking probiotics were often suggested. Why? Because probiotics has been promoted as a cure-all for all conditions. A influencer snake oil. Reported results on CFSFM-Experimental were disappointing.

My mind proceeded logically. So ask the US National Library of Medicine (PubMed), “Which probiotics have been helpful for ME/CFS? Given that there were 2400 studies on ME/CFS then, I expected to find a few dozen by then — after all, it would likely be one of the first choices by naturopaths who would rush to publish their results!! There were none that used lactobacillus probiotics. Even today, we have just 32 studies mentioning “chronic fatigue syndrome” probiotics in the 8500 studies posted. [Sarcasm] “Surely, there would have been a rush with all of the ME/CFS specialists to use lactobacillus probiotics given all of this evidence”.

Being a scientist, I know that what gets published are positive results — not no result nor negative results.

Reading conference papers presented by specialist on ME Research UK, I came across a report of a conference panel by active practitioners where the consensus was no benefit. I have worked as a professional technical writer and very “phrasing aware”, I read the wording to indicate that probiotics likely did harm in some of their patients. Slamming probiotics tend to be view as a heresy with many health influencers.

There Appears No Significant Objective Evidence that lactobacillus helps!

Yes, you will find testimonials — but that is not objective evidence. They may have helped because the person did not have ME/CFS (self diagnosis) or a different condition. It is incomprehensible that there have not been dozens (or hundreds) of studies trying lactobacillus — studies that are unpublished because of unfavorable results.

Why may it be EVIL?

Again, conference papers from Australia’s Alison Hunter Memorial Foundation play an important role here. From the Way-Back machine I retrieved items no longer on their site and pasted it into 1998 Was a very good year…. The key finding was “The mean distribution of E.coli as percentage of the total aerobic microbial flora for the control subjects and CFS patients was 92.3% and 49% ” Not a little drop, but almost half the level!

NOTA BENA: The typical (cheap) 16s tests used for most modern microbiome studies effectively ignore E.Coli. Shotgun testing (much more expensive) finds E.Coli in almost every sample. Some 16s finds it in 1 in a thousand samples as shown by the table below. Modern studies not repeating these results is a direct consequence of their methodologies!!

This was the motivation for my trying Mutaflor Probiotics (E.Coli Nissle 1917) which I happen to have in the house because my wife has Crohn’s and it made a huge difference for her (with lots of studies reporting it too!!!). I had a severe Jarisch–Herxheimer reaction for two weeks and a rapid recovery from ME/CFS afterwards.

If you look at Odds Ratios for Metabolites and ME/CFS, you will see that E.Coli probiotics has the biggest impact on the metabolite imbalance with ME/CFS

Going over to the E.Coli page on Microbiome Prescription we see that Lactobacillus constantly reduces E.Coli. So we are moving from levels that are 50% of normal levels to even lower levels.

IMHO, for ME/CFS, Lactobacillus probiotics are EVIL

Yes there are a few lactobacillus that will help some symptoms (and likely make other symptoms worse). Unless you are very sure that it has the actual probiotic strain used in studies, don’t do it. See Probiotics — what is advertised may not be what you get.

IMHO, for brain fog, Lactobacillus probiotics are EVIL

Interesting study relative to ME/CFS and brain fog. Lactobacillus can trigger “thick blood”, decreasing oxygen delivery (hypo perfusion). The aggregation of human platelets by Lactobacillus species

This extends to a few other Conditions

Bottom line, checking for clinical studies if a probiotics clearly helps is recommended. This search engine may help.

Bifidobacterium also?

In Visual Exploration of Odds Ratios, we see that ME/CFS people have higher then general population amounts of Bifidobacterium. On the flip side, the average amount is reported lower on several studies. This compounds issues with several things that needs to be investigated.

  • Did the lower bifidobacterium count not found in their average as zero? We use the values only when detected. Looking at the dots, we see that the dots are sparse/rare for lower values suggesting a lower detection rate. This suggests a threshold behavior of bifidobacterium.

Looking at impact on E.Coli, we see most studies say that it decreases E.Coli

There is not enough data to come to a safe conclusion.

Unknown's avatar lassesen 6:18 am on December 25, 2024
Tags: , , health, ,   

Odds Ratios for Metabolites and ME/CFS

This post extends the analysis of microbial involvement in ME/CFS pathophysiology by focusing on metabolites produced or consumed by bacteria, rather than on individual bacterial species seen in the earlier post Microbial involvement in myalgic encephalomyelitis/chronic fatigue syndrome pathophysiology. . This shift in perspective is valuable because:

Metabolite-Centric Analysis

Bacterial Metabolic Activity: Bacteria produce and consume various metabolites, which can significantly impact the host’s metabolic environment13.Metabolic Imbalances: Different bacterial compositions can lead to similar metabolite imbalances, making metabolite profiles potentially more informative than bacterial species profiles alone7 8.

Advantages of This Approach

  1. Net Effect: By examining metabolites, we can assess the overall impact of the microbiome on the host, regardless of the specific bacterial species present5.
  2. Consistency: Metabolite imbalances may be more consistent across patients than bacterial species composition, which can vary widely7.
  3. Functional Insight: This approach provides insight into the functional consequences of microbiome dysbiosis in ME/CFS3 8.

KEGG Application

Using the KEGG: Kyoto Encyclopedia of Genes and Genomes,(KEGG) allows for:

  • Mapping of metabolites to specific pathways
  • Identification of key metabolic alterations in ME/CFS patients
  • Potential discovery of new biomarkers or therapeutic targets7

Metabolite Profiling in ME/CFS

Recent studies have identified several metabolic alterations in ME/CFS patients:

  • Disruptions in energy metabolism and mitochondrial function2 5
  • Alterations in lipid metabolism, including changes in ceramides and complex lipids4
  • Disturbances in amino acid metabolism8

Clinical Implications

Understanding metabolite profiles in ME/CFS could lead to:

  • Improved diagnostic tools
  • Identification of potential therapeutic targets
  • Personalized treatment approaches based on individual metabolic profiles58

I am showing the numbers for Biomesight sample below. Conclusions across Ombre, uBiome and Biomesight are at the bottom.

Warning: These are the chemical names — a few are available as supplements with more common name.

BiomeSight Results

I did three slice-and-dice

  • Producers
  • Consumers
  • Net metabolites (Producers – Consumers) – this is like the most important

Remember: results may be different for different labs. Also, these are estimates of the metabolites

Metabolite Producers

  • DNA N4-methylcytosine <= 31.1
  • Cytidine 5′-diphosphoramidate <= 28
  • Pyridoxal <= 24.3
  • Allantoate <= 23.6
  • [L-Glutamate:ammonia ligase (ADP-forming)] <= 22.9
  • Adenylyl-[L-glutamate:ammonia ligase (ADP-forming)] <= 22.9
  • Uridylyl-[protein-PII] <= 22.6
  • 4-Hydroxybenzoate <= 19.6
  • 5-Phospho-D-xylonate <= 18.5
  • 5-Phospho-L-arabinate <= 18.5
  • Formyl-CoA <= 18
  • Aminoacrylate <= 17.3
  • Methylaminoacrylate <= 17.3
  • Acetoacetate <= 17.3
  • 5-Carboxyamino-1-(5-phospho-D-ribosyl)imidazole <= 17.3
  • UDP-N-acetyl-alpha-D-muramoyl-L-alanyl-L-glutamate <= 17
  • N-Acyl-L-homoserine <= 16.7
  • (R)-Piperazine-2-carboxylate <= 16.1
  • 2-[(2-Aminoethylcarbamoyl)methyl]-2-hydroxybutanedioate <= 16
  • D-Mannitol 1-phosphate <= 16
  • D-Erythritol 1-phosphate <= 15.6
  • 2-Acetylphloroglucinol <= 15.5
  • 3-Dehydrocarnitine <= 15.2
  • Deoxynucleoside <= 14.9
  • Formaldehyde <= 14.5
  • (S)-3-Acetyloctanal <= 14.4
  • Pyrrole-2-carbonyl-[pcp] <= 14.4
  • (L-Prolyl)adenylate <= 14.4
  • (L-Arginyl)adenylate <= 14.4
  • 2”-Nucleotidylgentamicin <= 13.9
  • 4-O-(beta-L-Arabinofuranosyl)-(2S,4S)-4-hydroxyproline <= 13.3
  • beta-L-Arabinofuranosyl-(1->2)-beta-L-arabinofuranose <= 13.3
  • Polysulfide <= 13.2
  • 6-Deoxy-6-sulfo-D-fructose <= 13
  • 1-Phosphatidyl-1D-myo-inositol 5-phosphate <= 12.9
  • 2-Dehydro-3-deoxy-D-galactonate <= 12.8
  • beta-L-Arabinofuranose <= 12.8
  • Maltose 6′-phosphate <= 12.7
  • Cytidine <= 12.5
  • [beta-GlcNAc-(1->4)-Mur2Ac(oyl-L-Ala-gamma-D-Glu-6-N-(beta-D-Asp)-L-Lys-D-Ala-D-Ala)]n <= 12.5
  • O-Phospho-L-homoserine <= 12.3
  • 2,5-Diamino-6-(5-phospho-D-ribosylamino)pyrimidin-4(3H)-one <= 12.3
  • Butanoyl-CoA <= 12.2
  • 4-Amino-5-hydroxymethyl-2-methylpyrimidine <= 12.1
  • Oxalyl-CoA <= 12.1
  • 5-(2-Hydroxyethyl)-4-methylthiazole <= 11.8
  • 2-Hydroxyornithine lipid <= 11.5
  • N3-Acetyl-2-deoxystreptamine antibiotic <= 11.3
  • Protein histidine <= 11.3
  • Protein N6-acetyl-L-lysine <= 11.2
  • Protoporphyrinogen IX <= 11
  • Divinylprotochlorophyllide <= 10.9

Metabolite Consumers (Substrates)

We have a shorter list with 5 metabolites bubbling to the surface as excessive metabolites.

  • Linalool >= 96.4
  • 6-Oxocyclohex-1-ene-1-carbonyl-CoA >= 96.4
  • 2-epi-5-epi-Valiolone >= 96.2
  • Lupanine >= 95.2
  • 4′-Hydroxyacetophenone >= 95.2
  • DNA cytosine <= 31.1
  • Xylitol <= 29.4
  • N5-(Cytidine 5′-diphosphoramidyl)-L-glutamine <= 28
  • 6-Hydroxynicotinate <= 27.6
  • Pyridoxine <= 24.1
  • [L-Glutamate:ammonia ligase (ADP-forming)] <= 22.9
  • Adenylyl-[L-glutamate:ammonia ligase (ADP-forming)] <= 22.9
  • 2-Amino-2-deoxyisochorismate <= 22.7
  • [Protein-PII] <= 22.6
  • Formyl-CoA <= 20.4
  • D-Erythrulose 4-phosphate <= 20 alpha-Maltose 1-phosphate <= 18.8
  • L-Arabino-1,4-lactone 5-phosphate <= 18.5
  • D-Xylono-1,4-lactone 5-phosphate <= 18.5
  • N-Acyl-L-homoserine lactone <= 18.1
  • Oxalyl-CoA <= 18
  • Methylureidoacrylate <= 17.3
  • Ureidoacrylate <= 17.3
  • UDP-N-acetyl-alpha-D-muramoyl-L-alanyl-L-glutamate <= 17
  • D-arabino-Hex-3-ulose 6-phosphate <= 17
  • beta-Alaninamide <= 16.1
  • (R)-Piperazine-2-carboxamide <= 16.1
  • 2-[(L-Alanin-3-ylcarbamoyl)methyl]-2-hydroxybutanedioate <= 16
  • Erythritol <= 15.6
  • alpha-L-Rhamnopyranosyl-(1->3)-N-acetyl-alpha-D-glucosaminyl-diphospho-trans,octacis-decaprenol <= 15.5 2,4-Diacetylphloroglucinol <= 15.5
  • (S)-Allantoin <= 15.1
  • L-Prolyl-[pcp] <= 14.4
  • trans-2-Octenal <= 14.4
  • (L-Prolyl)adenylate <= 14.4
  • (L-Arginyl)adenylate <= 14.4
  • (5-L-Glutamyl)-L-amino acid <= 13.6
  • 4-O-(beta-L-Arabinofuranosyl-(1->2)-beta-L-arabinofuranosyl-(1->2)-beta-L-arabinofuranosyl)-(2S,4S)-4-hydroxyproline <= 13.3
  • Sulfoquinovose <= 13
  • 1-Phosphatidyl-D-myo-inositol 4,5-bisphosphate <= 12.9
  • D-Galactonate <= 12.8
  • beta-L-Arabinofuranosyl-(1->2)-beta-L-arabinofuranose <= 12.8
  • Oxalate <= 12.7
  • N4-Acetylcytidine <= 12.5
  • D-Aspartate <= 12.5
  • [beta-GlcNAc-(1->4)-Mur2Ac(oyl-L-Ala-gamma-D-Glu-L-Lys-D-Ala-D-Ala)]n <= 12.5
  • 3′-Phosphoadenylyl sulfate <= 12.4
  • 2,5-Diamino-6-(5-phospho-D-ribitylamino)pyrimidin-4(3H)-one <= 12.3
  • D-Xylulose 5-phosphate <= 12.2
  • 4-Amino-5-aminomethyl-2-methylpyrimidine <= 12.1
  • Deoxynucleoside 5′-phosphate <= 11.9
  • Thiosulfate <= 11.6
  • Ornithine lipid <= 11.5
  • 2-Deoxystreptamine antibiotic <= 11.3
  • UDP-alpha-D-galactofuranose <= 11.2
  • 3′,5′-Cyclic AMP <= 11.1
  • [Sulfatase]-L-serine <= 11
  • trans-2,3-Dehydroacyl-CoA <= 10.9
  • D-Serine <= 10.6
  • 5,6-Dihydrothymine <= 10.4
  • Electron-transferring flavoprotein <= 10.3
  • D-Mannose <= 10.1
  • Ethanol <= 10.1

Net Modifiers

Here we have shorter list with

  • (R)-3-(4-Hydroxyphenyl)lactoyl-CoA >= 98.9
  • 14alpha-Formylsteroid >= 98.7
  • (E)-2-Methylgeranyl diphosphate >= 98.3
  • Harderoheme III >= 97
  • D-Erythritol 1-phosphate >= 83.4
  • 1-(5-O-Phospho-beta-D-ribofuranosyl)-5-(sulfanylcarbonyl)pyridin-1-ium-3-carbonyl adenylate >= 56.8
  • 8-Oxo-GDP <= 32.5 8-Oxo-dGDP <= 32.5
  • 2,4-Diketo-3-deoxy-L-fuconate <= 27.2
  • S-(Hercyn-2-yl)-L-cysteine S-oxide <= 27
  • L-Formylkynurenine <= 24.6
  • 2-[(2-Aminoethylcarbamoyl)methyl]-2-hydroxybutanedioate <= 23.5
  • alpha-Oxo-benzeneacetic acid <= 23.4
  • trans-o-Hydroxybenzylidenepyruvate >= 22.8
  • 2-(alpha-D-Mannosyl)-3-phosphoglycerate <= 22
  • Reduced FMN <= 20.6
  • Deamino-NAD+ <= 19.7
  • 5-(5-Phospho-D-ribosylaminoformimino)-1-(5-phosphoribosyl)-imidazole-4-carboxamide <= 18.5
  • cis-2,3-Dihydroxy-2,3-dihydro-p-cumate >= 18.2
  • Phthalate <= 17.9
  • alpha-Ribazole <= 17.7
  • beta-D-Fructose 6-phosphate <= 17.5
  • Reduced electron-transferring flavoprotein <= 16.5
  • GDP-L-fucose <= 16.4
  • 3-Hydroxy-5,9,17-trioxo-4,5:9,10-disecoandrosta-1(10),2-dien-4-oate <= 15.4
  • 2-Keto-D-gluconic acid <= 14.6
  • 6-(Hydroxymethyl)-7,8-dihydropterin <= 14.4
  • Formaldehyde <= 13.9
  • Adenosyl cobyrinate hexaamide <= 13.6
  • 3-Deoxy-D-manno-octulosonate <= 12.9
  • L-Fuculose 1-phosphate <= 12.8
  • D-Glutamate <= 12.5
  • L-Tyrosyl-tRNA(Tyr) <= 12.1
  • Maltose 6′-phosphate <= 11.8
  • O-Phospho-L-serine <= 11.8
  • 4-Guanidinobutanal <= 11.7
  • 7-Carboxy-7-carbaguanine <= 11.7
  • CDP-diacylglycerol <= 11.1
  • Protoporphyrinogen IX <= 11.1
  • 5-Guanidino-2-oxopentanoate <= 11
  • N5-Phospho-L-glutamine <= 10.9
  • D-1-Aminopropan-2-ol O-phosphate <= 10.5
  • Thymine <= 10.5
  • (2-Amino-1-hydroxyethyl)phosphonate <= 10.5
  • Hydrogenobyrinate a,c diamide <= 10.2
  • 2-Amino-3-carboxymuconate semialdehyde <= 10

Across Labs Consolidation

The analysis of metabolites across multiple microbiome testing platforms (Ombre, Biomesight, and uBiome) reveals a more consistent pattern of metabolite imbalances compared to bacterial species identification.

Potential Consequences of Low GDP-L-fucose (the top one)

The deficiency in GDP-L-fucose could have several implications:

  • Altered Immune Response: It may affect the proper functioning of the immune system, potentially impacting inflammatory processes12.
  • Cancer-Related Changes: Low levels might influence tumor progression or immune evasion mechanisms, as fucosylation is often altered in cancer24.
    • First-degree relatives: A clinic-based study reported that first-degree relatives of ME/CFS patients had a significantly higher(four times) prevalence of any cancer compared to controls (OR 4.06) [2022]
  • Cellular Communication: It could disrupt normal cell-cell interactions and signaling pathways dependent on fucosylated glycans3.
MetaboliteThresholdLowHigh
GDP-L-fucose16.512.121.2
Holo-[citrate (pro-3S)-lyase]12.71.823.4
N,N’-Diacetyllegionaminate12.15.422
alpha-Oxo-benzeneacetic acid11.81.923.4
Oxalyl-CoA11.3222.4
S-Methyl-5-thio-D-ribose 1-phosphate11.21.330.6
Malonyl-CoA10.62.526.3
1,2-Diacyl-3-alpha-D-glucosyl-sn-glycerol10.55.420

Translate Low Metabolites to Probiotics

Many of these metabolites are produced by probiotics, so in terms of highest importance and reasonably available probiotics, I produced the list below.

The top one is one is one that had very dramatic positive effect for me when I relapsed into ME/CFS (after the worse herxheimer reaction that I have ever experienced): Mutaflor (E.Coli Nissle 1917). I took it as a result of a 1999 study in Australia reporting very low levels of E.Coli in CFS patients [As a FYI, 16s tests do a very poor reporting on E.Coli].

The retail product microbiome labs/ megasporebiotic has several of the next on the list.

  1. Escherichia coli (Mutaflor, SymbioFlor-2) : 100%
  2. Bacillus thuringiensis: 70%
  3. Bacillus licheniformis: 67%
  4. Bacillus subtilis: 66%
  5. Bacillus subtilis subsp. natto: 67%
  6. Clostridium butyricum: 57% of the top
  7. Heyndrickxia coagulans (a.k.a. Bacillus coagulans): 65%
  8. Lactiplantibacillus plantarum: 59%
  9. Enterococcus faecalis: 57%
  10. Akkermansia muciniphila: 54%

I asked perplexity, which foods may increase any of the above metabolites. The following were reported:

  • Spinach
  • Rhubarb
  • Beets
  • Nuts
  • Chocolate
  • Tea
  • Wheat bran
  • Strawberries

Bottom Line

While the metabolite-focused approach provides valuable insights into the biochemical imbalances associated with ME/CFS, its immediate clinical applications are somewhat limited. The probiotics and the food suggestions are reasonable and I see several of the items appearing on suggestions from the expert system for ME/CFS patients.

Unknown's avatar lassesen 12:18 pm on December 23, 2024
Tags: , health, , ,   

Microbial involvement in myalgic encephalomyelitis/chronic fatigue syndrome pathophysiology

This is the title of a new publication in Microbes & Immunity, available here.

Microbiome fluctuations or metabolic endotoxemia are proposed as possible disorder biomarkers. Based on the fact that gut microbiota dysbiosis reverts to a state of eubiosis in long-term patients with this condition, it may be hypothesized that disease progression begins with the loss of beneficial gut microorganisms, particularly short-chain fatty acid producers, leading to more widespread gastrointestinal phenotypes that are subsequently reflected in plasma metabolite levels. These alterations, specific of each individual, thereby result in metabolic and phenotypic shifts and in ME/CFS.

Microbial involvement in myalgic encephalomyelitis/chronic fatigue syndrome pathophysiology 6 Sep 2024

This has been my primary hypothesis for many years and lead to my writing Microbiome Prescription to normalize the dysbiosis. The bacteria shifts will be reported differently from different labs because of a lack of standardization of microbiome tests (See The taxonomy nightmare before Christmas… ).

Recently, I implemented an Odds Ratio analysis of the 5000+ sample microbiomes that have been upload to Microbiome Prescription. A quick overview is here: Bacteria Associated with General Fatigue.

Below I have pulled the lab specific dysbiosis shifts for ME/CFS at thhe genus level.

Biomesight Tests

The number are the percentile ranking for the bacteria listed. Each match increases the odds of ME/CFS by 1.5.

  • Methylonatrum >= 99
  • Planifilum >= 98.9
  • Thiohalorhabdus >= 98.9
  • Granulicatella >= 98.7
  • Amedibacillus >= 98.6
  • Enterococcus >= 98
  • Methylobacillus >= 98
  • Emticicia >= 97.7
  • Candidatus Tammella >= 97.7
  • Dokdonella >= 97.6
  • Runella >= 97.4
  • Collinsella <= 18
  • Pseudobutyrivibrio <= 16.4
  • Calothrix <= 13.8
  • Lachnospira <= 11.4
  • Veillonella <= 10.8
  • Shuttleworthia <= 8.5
  • Parabacteroides <= 8.4
  • Bifidobacterium <= 8.4
  • Faecalibacterium <= 7.5
  • Actinobacillus <= 7.5
  • Pedobacter <= 7.2
  • Coprococcus <= 4.6
  • Moorella <= 3.5
  • Natronincola <= 2.9
  • Mediterraneibacter <= 2.5
  • Oscillospira <= 1.8
  • Anaerovibrio <= 1.7
  • Sphingobacterium <= 1.6

Thryve

  • Collinsella <= 44.2
  • Bifidobacterium <= 41.1
  • Gemmiger <= 23
  • Dorea <= 19
  • Butyrivibrio <= 8
  • Fusicatenibacter <= 5.7
  • Lachnoclostridium <= 5.2
  • Gordonibacter <= 5.1
  • Eubacterium <= 4.8
  • Prevotella <= 4
  • Brassicibacter <= 3.9
  • Sporobacter <= 3.5
  • Johnsonella <= 3.5
  • Phascolarctobacterium <= 3.4
  • Dialister <= 3.4
  • Agathobacter <= 3.3
  • Lactonifactor <= 3.2
  • Murimonas <= 3.2
  • Moryella <= 3.1
  • Niabella <= 3.1
  • Ruminococcus <= 3
  • Hungatella <= 3
  • Anaerotruncus <= 2.8
  • Odoribacter <= 2.7
  • Lactobacillus <= 2.4
  • Eggerthella <= 2.3
  • Cellulosilyticum <= 2.1
  • Haemophilus <= 2
  • Holdemania <= 2
  • Terrisporobacter <= 2
  • Anaerobutyricum <= 1.9
  • Howardella <= 1.8
  • Hydrogenoanaerobacterium <= 1.8
  • Lachnobacterium <= 1.8
  • Hespellia <= 1.7
  • Agathobaculum <= 1.6
  • Pseudoflavonifractor <= 1.6
  • Desulfotomaculum <= 1.6
  • Intestinibacter <= 1.6
  • Barnesiella <= 1.5
  • Eisenbergiella <= 1.5
  • Facklamia <= 1.5
  • Acetatifactor <= 1.5
  • Ruminiclostridium <= 1.5
  • Natranaerovirga <= 1.5
  • Enterocloster <= 1.4
  • Caloramator <= 1.4
  • Thomasclavelia <= 1.4
  • Desulfovibrio <= 1.4
  • Parabacteroides <= 1.4
  • Shuttleworthia <= 1.3
  • Peptoniphilus <= 1.3
  • Akkermansia <= 1.3
  • Alistipes <= 1.3
  • Marvinbryantia <= 1.3
  • Acetivibrio <= 1.2
  • Paraprevotella <= 1.2
  • Veillonella <= 1.2
  • Bacteroides <= 1.2
  • Butyricimonas <= 1.2
  • Romboutsia <= 1.2
  • Ethanoligenens <= 1.2
  • Phocaeicola <= 1.2
  • Anaerocolumna <= 1.2
  • Blautia <= 1.1
  • Coprococcus <= 1
  • Lachnospira <= 1

uBiome

  • Veillonella <= 22.4
  • Hespellia <= 19
  • Bifidobacterium <= 15.1
  • Anaerosporobacter <= 7.2
  • Streptococcus <= 6.8
  • Eggerthella <= 6.4
  • Phascolarctobacterium <= 4.1
  • Eisenbergiella <= 3.9
  • Marvinbryantia <= 3.4
  • Holdemania <= 3.1
  • Dorea <= 3
  • Anaerostipes <= 3
  • Oscillibacter <= 2.7
  • Dialister <= 2.3
  • Kluyvera <= 2.1
  • Peptoclostridium <= 1.7
  • Erysipelatoclostridium <= 1.4
  • Intestinimonas <= 1.3
  • Sarcina <= 1.3
  • Roseburia <= 1.3
  • Phocaeicola <= 1.2
  • Terrisporobacter <= 1.2
  • Bacteroides <= 1.1

Bottom Line

Bifidobacterium is common across all of these, and lactobacillus shows up barely in only one result. Since there can be some hostility between Bifidobacterium and Lactobacillus, I would suggest cutting out lactobacillus probiotics.

I repeated this for Bifidobacterium species and one species shone.

  • Bifidobacterium longum <= 9.9

My personal preference for a source is Maple Life Science which sells direct from factory resulting in very fresh and alive probiotics.

Some examples of analysis people with Long COVID and ME/CFS are there. I am working on building an algorithm to build suggestions based on odds ratio which should improve the suggestions more.

Unknown's avatar lassesen 12:56 pm on September 28, 2024
Tags: , health, , ,   

ME/CFS Patient continues the trek to recovery

Prior Posts

Dealing with ME/CFS and many microbiome dysfunction is rarely a short journey

Recent Story

Some supplements that I have been taking since the last test:

  • Tetracycline 
  • Clove 
  • Holy basil (Neem)
  • Augmentin + Bromelain 
  • Grapefruit seed extract 
  • Monolaurin
  • Apple peel powder 
  • Thyme

My symptoms:

  • Still get the red nose (some form of rosacea). 
  • Still feel fatigued (both physically and mentally). But it is better than before.
  • Feeling stressed. But it is better than before.
  • Brain fog.
  • Bloated.
  • Lots of gas – I fart and burps a lot. 
  • Issues with allergies (itching eyes, stuffed nose and itchy skin)

Video

Analysis

We will start with the high-level comparison. Note that some numbers will change with time. There are no major changes. Since the latest sample reports 20% more bacteria, many counts are expected to be 20% higher – for example: Thorne Ranges: old: 230 + 20% = 276, with the seen count being 253 (so an apparent improvement although the number went up)

Criteria9/2/20241/22/20249/12/20232/22/20238/11/20223/25/202212/3/20218/31/2021
Lab Read Quality9.17.93.59.75.56.23.67.8
Outside Range from GanzImmun Diagostics1616161515171720
Outside Range from Lab Teletest2320 202424222225
Outside Range from Medivere1416161515151519
Outside Range from Metagenomics67799778
Outside Range from Microba Co-Biome32277111
Outside Range from MyBioma65 577778
Outside Range from Nirvana/CosmosId2120202323181821
Outside Range from Thorne (20/80%ile)253230198223223217217246
Outside Range from XenoGene3232 243232363639
Outside Lab Range (+/- 1.96SD)125 1510119914
Outside Box-Plot-Whiskers4852564236425942
Outside Kaltoft-Moldrup113123 70139567859140
Bacteria Reported By Lab600508399666478613456572
Bacteria Over 85%ile4852      
Bacteria Under 15%ile118157      
Pathogens2326 253023392430
Condition Est. Over 85%ile25      

There is a new comparison table added that compares sets of symptoms bacteria for symptoms reported in either sample. This is a thought experiment on a different way of evaluating the microbiome, i.e. are symptom bacteria reducing. Remembering that we have 20% more bacteria reported, the improvement may be slightly under-reported.

Going Forward

My current preference is to use symptom associations suggestions with KEGG suggested suggestions. This assumes that the person has added their symptoms.

Using Entered symptoms

Since this person has access to antibiotics, I opted to include all classes of modifiers. We have 38 bacteria selected — a reasonable number

The suggests were a nice mixture for ME/CFS. Typically, I see the top being just antibiotics, in this case we have several probiotics there.

And suggested retail probiotics are:

Using Diagnosis and PubMed

Using a diagnosis provides less precise filtering compounded by different labs (with different identification of bacteria). If the person is using a lab that lacks a large number of annotated samples from that lab, then it is the best path.

The suggested path is to go down the list and pick the ones that has the highest value(s) that agrees with one or more of the diagnoses that you have.

In this case we have only 4 bacteria in the selection, so the suggestions will be likely more generic than specific.

There are no antibiotics in this list

The probiotic list is below. It has some similarities to the above list.

Using KEGG Derived Probiotics

This is an experimental approach that attempts to do a metagnòmia approach from the available data. We estimate which compounds are too high or too low. Then we match them to probiotics which produce or consumes them. Postbiotics can be used for items that are too low. There is no filtering of any type; we look at the entire microbiome.

The results are different — as to be expected. Why expected? The prior ways depended on studies being done what each probiotics bacterium does. Often there are no studies. This way uses the DNA/RNA sequences of everything and thus we do not need studies.

I usually focus on too low, with the assumption that a surplus will just be ignored or has less impact (i.e. starvation versus obesity) We can see where there is agreement between the lists.

  • aor / probiotic-3 is [30]
  • bioflorin (deu) / bioflorin is [25]
  • miyarisan (jp) / miyarisan is [22]
  • Microbiome Labs / MEGA Genesis is [27]
  • Bulk Probiotics / L. Reuteri Probiotic Powder is [27]

Consensus View?

You can build consensus views, a.k.a. Monte Carlo model, but IMHO that is likely done by those that want to “over work the problem”.

Summary of Suggestions

Remember these are suggestions, and NOT a protocol. What you actually do should be reviewed by a knowledgeable medical professional before starting.

My own proposal for discussion would be:

This can be made more complex by using consensus / Monte Carlo Model

Reader Plan

Microbiome Prescription produces suggestions, the weights/priorities are the odds of causing a change and not the amount of change (there is simply no objective data to compute the amount). This reader did their own evaluation of what they felt comfortable with (excellent idea).

I have also bought 2 more tests so I will do them with max 3 months apart as you said in the video.

I came up with this protocol by using the “Beginner-Symptoms: Select bacteria connected with symptoms”:

  • Week 1-2: Gum arabic
  • Week 3-4: Monolarin (lauric acid)
  • Week 5-6: Psyllium
  • Week 7-8: Rosemary 
  • Week 9-10: Parsley
  • Week 11-12: SymbioFlor-2

I found that I get best results from herbs, prebiotics and antibiotics. The only probiotic I’ve got good results from is Symbioflor 2 (an E.Coli probiotic) [Editor: E.Coli probiotics also worked best for me]

A lot of probiotics that I’ve tested I’ve got bad results from. 

Postscript and Reminder

As a statistician with relevant degrees and professional memberships, I present data and statistical models for evaluation by medical professionals. I am not a licensed medical practitioner and must adhere to strict laws regarding the appearance of practicing medicine. My work focuses on academic models and scientific language, particularly statistics. I cannot provide direct medical advice or tell individuals what to take or avoid.My analyses aim to inform about items that statistically show better odds of improving the microbiome. All suggestions should be reviewed by a qualified medical professional before implementation. The information provided describes my logic and thinking and is not intended as personal medical advice. Always consult with your knowledgeable healthcare provider.

Implementation Strategies

  1. Rotate bacteria inhibitors (antibiotics, herbs, probiotics) every 1-2 weeks
  2. Some herbs/spices are compatible with probiotics (e.g., Wormwood with Bifidobacteria)
  3. Verify dosages against reliable sources or research studies, not commercial product labels. This Dosages page may help.
  4. There are 3 suppliers of probiotics that I prefer: Custom Probiotics , Maple Life Science™, Bulk Probiotics: see Probiotics post for why
  5. My preferred provider for herbs etc is Maple Life Science™ – they are all organic, fresh, without fillers, and very reasonably priced.

Professional Medical Review Recommended

Individual health conditions may make some suggestions inappropriate. Mind Mood Microbes outlines some of what her consultation service considers:
A comprehensive medical assessment should consider:

  • Terrain-related data
  • Signs of low stomach acid, pancreatic function, bile production, etc.
  • Detailed health history
  • Specific symptom characteristics (e.g., type and location of bloating)
  • Potential underlying conditions (e.g., H-pylori, carbohydrate digestion issues)
  • Individual susceptibility to specific probiotics
  • Nature of symptoms (e.g., headache type – pressure, cluster, or migraine)
  • Possible histamine issues
  • Colon acidity levels
  • SCFA production and acidification needs

A knowledgeable medical professional can help tailor recommendations to your specific health needs and conditions.

Unknown's avatar lassesen 7:23 am on March 17, 2024
Tags: , , , health, mental-health   

Gender based Microbiome Shifts for ME/CFS

A question was ask – are there significant gender differences with ME/CFS. A partial answer is possible from our citizen science data (Available here). The number of bacteria identify as statistical drops because we are reducing sample sizes. The table below shows the shifts that are seen in common with P < 0.01.

For Symptom of ME/CFS

SourceTax_nametax_rankMaleFemaleMale_Chi2FeMale_Chi2
thryveThermodesulfobacteriaphylumincreasesincreases234.0375138.4544
biomesightVerrucomicrobiaceaefamilyincreasesincreases8.3333337.262051
biomesightRhodothermaeotaphylumincreasesincreases179.2217.3071
biomesightAkkermansiaceaefamilyincreasesincreases8.7183789.965634
biomesightErysipelothrix murisspeciesincreasesincreases9.53388910.08333
biomesightAkkermansiagenusincreasesincreases8.7183789.965634
biomesightRhodothermalesorderincreasesincreases179.2217.3071
biomesightAkkermansia muciniphilaspeciesincreasesincreases8.7183789.965634
biomesightErysipelothrixgenusincreasesincreases9.6632899.663289
biomesightRhodothermiaclassincreasesincreases179.2217.3071
biomesightThermodesulfobacteriaphylumincreasesincreases281.1738299.9112

ME/CFS With IBS

We find differences here.

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
biomesightSutterellagenus40544decreaseincreases8.33333311.25018
biomesightRhodothermalesorder1853224increasesincreases139.9274114.5716
biomesightDoreagenus189330increasesdecrease18.7516.17875
biomesightRhodothermiaclass1853222increasesincreases139.9274114.5716
biomesightThermodesulfobacteriaphylum200940increasesincreases280.3333187.9779
biomesightSutterellaceaefamily995019decreaseincreases8.33333311.25018
biomesightAlcaligenaceaefamily506decreaseincreases8.3333339.120714
biomesightRhodothermaeotaphylum1853220increasesincreases139.9274114.5716

ME/CFS Without IBS

We found no differences yet (given the sample size)

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
biomesightBacteroides fluxusspecies626930increasesincreases7.3551617.910588
biomesightThermodesulfobacteriaphylum200940increasesincreases124.4571170.4624

Irritable Bowel Syndrome

Following up from above and noting that there is a gender bias in incidence, we find some differences

thryveThermodesulfobacteriaphylum200940increasesincreases252.823295.10095
biomesightRhodothermalesorder1853224increasesincreases125.1467110.6182
biomesightRhodothermiaclass1853222increasesincreases125.1467110.6182
biomesightThermodesulfobacteriaphylum200940increasesincreases314.4971174.6182
biomesightRhodothermaeotaphylum1853220increasesincreases125.1467110.6182
biomesightSharpea azabuensisspecies322505increasesincreases16.185266.80625
biomesightSharpeagenus519427increasesincreases16.185266.80625
thryveMycoplasmagenus2093increasesdecrease12.8152420.3229
thryveMycoplasmataceaefamily2092increasesdecrease14.8858120.3229
thryvePhocaeicola vulgatusspecies821increasesdecrease7.89349217.06273
thryveMycoplasmatalesorder2085increasesdecrease14.8858126.01485

Depression

Another condition with a gender association

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
thryveThermodesulfobacteriaphylum200940increasesincreases227.7557148.4336
thryveParabacteroides distasonisspecies823decreaseincreases9.11835613.46941
thryveEubacterium oxidoreducensspecies1732decreaseincreases12.995076.76
biomesightRhodothermalesorder1853224increasesincreases121.200291.125
biomesightRhodothermiaclass1853222increasesincreases121.200291.125
biomesightThermodesulfobacteriaphylum200940increasesincreases223.4402189.2431
biomesightRhodothermaeotaphylum1853220increasesincreases121.200291.125
thryveLactobacillus rogosaespecies706562decreasedecrease23.8836812.12781

Symptom: Problems remembering things

This is one of the characteristics of ME/CFS, Long Covid, etc

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
thryveThermodesulfobacteriaphylum200940increasesincreases316.4446120.0944
biomesightRhodothermalesorder1853224increasesincreases171.7445133.3333
biomesightRhodothermiaclass1853222increasesincreases171.7445133.3333
biomesightThermodesulfobacteriaphylum200940increasesincreases369.0078289.0992
biomesightOdoribacteraceaefamily1853231increasesincreases12.793117.962632
biomesightRhodothermaeotaphylum1853220increasesincreases171.7445133.3333
biomesightAcetivibriogenus35829decreaseincreases9.18086517.49208
biomesightOdoribactergenus283168increasesincreases9.33494912
biomesightAcetivibrio alkalicellulosispecies320502decreaseincreases9.18086519.95636
biomesightHathewaya histolyticaspecies1498decreaseincreases9.1808657.262051
biomesightHathewayagenus1769729decreaseincreases9.1808657.262051
biomesight[Clostridium] thermoalcaliphilumspecies29349increasesincreases7.356.880909
thryveIntestinimonasgenus1392389decreaseincreases168.552727
thryveIntestinimonas butyriciproducensspecies1297617decreaseincreases16.486469.992258
ubiomeBacteroides sp. EBA5-17species447029increasesdecrease9.0555777.314286

Symptom: Worsening of symptoms with stress.

Another common symptom of ME/CFS

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
thryveThermodesulfobacteriaphylum200940increasesincreases282.4023185.22
biomesightThermoanaerobacterales Family III. Incertae Sedisfamily543371decreaseincreases22.004548.491649
biomesightSharpeagenus519427increasesincreases17.5562512.38345
biomesightHathewayagenus1769729decreaseincreases16.9861211.70814
biomesightRhodothermalesorder1853224increasesincreases142.9353188.8704
biomesightHathewaya histolyticaspecies1498decreaseincreases16.9861211.70814
biomesightSharpea azabuensisspecies322505increasesincreases17.5562512.97965
biomesightRhodothermiaclass1853222increasesincreases142.9353188.8704
biomesightThermodesulfobacteriaphylum200940increasesincreases352.2616362.7038
biomesightAcetivibrio alkalicellulosispecies320502decreaseincreases12.658188.491649
biomesightRhodothermaeotaphylum1853220increasesincreases142.9353188.8704
biomesightAcetivibriogenus35829decreaseincreases12.658188.491649

Other Symptoms with Significant Gender Differences in patterns

  • Immune Manifestations: Abdominal Pain
  • Sleep: Unrefreshed sleep
  • Comorbid: High Anxiety
  • General: Fatigue
  • Neurological-Audio: hypersensitivity to noise
  • DePaul University Fatigue Questionnaire : Unrefreshing Sleep, that is waking up feeling tired
  • DePaul University Fatigue Questionnaire : Fatigue
  • Neurocognitive: Brain Fog
  • Neurocognitive: Problems remembering things
  • DePaul University Fatigue Questionnaire : Anxiety/tension
  • General: Myalgia (pain)
  • Immune Manifestations: Constipation
  • Post-exertional malaise: Rapid muscular fatigability,
  • Neuroendocrine Manifestations: Poor gut motility
  • Comorbid: Restless Leg
  • Comorbid: Small intestinal bacterial overgrowth (SIBO)
  • DePaul University Fatigue Questionnaire : Difficulty finding the right word
  • DePaul University Fatigue Questionnaire : Mood swings
  • DePaul University Fatigue Questionnaire : Pain in Multiple Joints without Swelling or Redness
  • Sleep: Problems falling asleep
  • Sleep: Problems staying asleep