One of the purposes of these blog posts is to learn. My thinking and thoughts are there with the ability of people to correct, to comment and to learn. This post looks at GI-MAP and Biomesight report for the same person, taken at the same time. The key objectives are:

• Comparing appropriate results between the two (same bacteria only)
• Comparing the suggestions produced from each
  • GI-MAP using US National of Medicine Library studies
  • BiomeSight using our Special Studies

Foreword – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that appears to have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.

Simple Back Story

” I got COVID at the end of Sept 2020 and have been much worse ever since.”

We have 2 samples from Biomesight April,2022 and Sept 2022 and will see if the microbiome shifts reflect getting worse

GI-MAP vs BiomeSight

We are comparing different lab results, so reading: The taxonomy nightmare before Christmas… is strongly recommended. While results may disagree, they may be both technically accurate given the testing methodologies.

Bacteria	GI MAP	BiomeSight Percentile
Enterobacter spp. ( Enterobacter)	High	78%ile
Bacteroidetes ( Bacteroidetes)	High	81%ile
Firmicutes ( Firmicutes)	High	8%ile
Bacillus spp. (Bacillus)	High	47%ile (seen in 66%)
Enterococcus faecalis	High	Not reported (Seen in 1%)
Enterococcus faecium	High	Not reported (seen in 2.2%)
Methanobacteriaceae (family)	High	Not reported (seen in 27%)

As is seen clearly, there are differences — some very striking (Firmicutes). I will leave it to the test providers to offer explanations on differences of techniques, etc. See Below One of the key issues is how labs handle not detected for determining ranges: some will exclude it from the calculation (thus range IF detected) and others will give it a zero value and include it.

I was curious about Bacillus distribution, which is shown below

Explanation of differences from GI-MAP

COMMENT FROM DIAGNOSTIC SOLUTIONS LAB

Thank you for contacting us and providing an opportunity for us to comment.  Metagenomic sequencing has been popular for untargeted characterization of microbiome composition, whereas qPCR is used primarily for accurate quantitation of selected targets (microbes and genes of interest) especially those with particular clinical implications, such as common pathogens and opportunists. Metagenomic sequencing and qPCR are not considered competing methodologies for the same purpose, so it’s not an apples-to-apples comparison. 

A major difference between the two methods is the type of quantitation that they provide. Metagenomic sequencing results are expressed as relative abundance (usually as a percentage), whereas qPCR results are expressed as absolute abundance (usually microbial cells per gram of stool). With relative abundance, it’s not possible to directly determine how much of a given taxon (species, genus, etc) is actually present, since its relative abundance is dependent upon the relative abundance of all of the other detected taxa. A couple of example references are included below. 

The differences between relative and absolute abundance are likely key factors contributing to any differences in results between GI-MAP and metagenomic tests. From a clinical standpoint, there are demonstrated advantages of using methods, such as qPCR, that provide absolute quantitation, since absolute quantitation has been shown in research studies to be more effective in identifying true correlations with quantitative clinical markers. Examples of clinical markers that are included on GI-MAP include calprotectin, secretory IgA, pancreatic elastase and occult blood.

A quantitative sequencing framework for absolute abundance measurements of mucosal and lumenal microbial communities

https://pubmed.ncbi.nlm.nih.gov/32444602/

“Thus, an inherent limitation of methods that use relative abundance is that they cannot determine whether an individual taxon is more abundant or less abundant (the direction of the change) or by how much (the magnitude of the change) between two experimental conditions or samples.”

Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases

https://pubmed.ncbi.nlm.nih.gov/34117246/

“Our results demonstrated that quantitative approaches performed better than their relative and compositional counterparts when it comes to identifying taxon–metadata associations or studying taxon–taxon interactions. The observed performance gap among the methods profiled widened with increasing unevenness of taxa distributions, as exemplified by our analyses of the blooming scenario.”

Explanation from BiomeSight

As many of your readers know, it is not possible to compare Biomesight and GI MAP directly due to the differences in what and how it is measured. The strength of a 16s test is in the ability to see the overall ecosystem and this technology is widely used today in clinical and academic research, often alongside shotgun or other WGS techniques. It allows for coverage of a range of bacteria that’s not included in more focused PCR tests.

Additionally, Biomesight already has around 400 samples from the long covid community allowing for better profiling of the condition. We have shared around half of these samples’ results with MicrobiomePrescription enabling a strong comparison base.

Here’s some of our blog articles covering our findings from the study:

https://biomesight.com/blog/long-covid-study-update-1

https://biomesight.com/blog/the-role-of-lps-in-long-covid

Suggestions from GIMAP

Without applying PUBMED filtering

All of the above bacteria were used.

With PubMed Filtering

Only the following bacteria was selected. This filtering is not available on the site because the quality of select drops too low (as seen here).

Bacteria Name	Analysis	Taxonomy Hierarchy Level
Bacteroidetes	Too High	phylum
Firmicutes	Too High	phylum

Suggestions from BiomeSight

Without Filtering – using Kaltoft-Moldrup for bacteria selection

We have 70 bacteria selected

Using Special Studies

We have 93 bacteria selected.

Getting Worst with Long COVID

Taking ME/CFS as a typical pattern, there tend to be three main paths:

• Slow or Spontaneous Remission
• Steady state with waxing and waning
• Slow progressive deterioration, sometimes ending in complete system failue

There are two others, suicide from hopelessness and Remission cause by specific treatment (which was my personal case).

The reader had a early-COVID sample which allows comparisons. It is especially nice that the Lab Read Quality are similar, which makes interpretation more robust.

Criteria	Current Sample	Old Sample
Lab Read Quality	10.3	10
Bacteria Reported By Lab	639	507
Bacteria Over 99%ile	6	3
Bacteria Over 95%ile	26	13
Bacteria Over 90%ile	40	26
Bacteria Under 10%ile	198	284
Bacteria Under 5%ile	173	229
Bacteria Under 1%ile	155	161
Lab: BiomeSight
Rarely Seen 1%	3	7
Rarely Seen 5%	16	25
Pathogens	34	36
Outside Range from JasonH	10	10
Outside Range from Medivere	19	19
Outside Range from Metagenomics	9	9
Outside Range from MyBioma	7	7
Outside Range from Nirvana/CosmosId	19	19
Outside Range from XenoGene	6	6
Outside Lab Range (+/- 1.96SD)	14	8
Outside Box-Plot-Whiskers	67	42
Outside Kaltoft-Moldrup	181	186
Condition Est. Over 99%ile	0	0
Condition Est. Over 95%ile	0	0
Condition Est. Over 90%ile	3	0
Enzymes Over 99%ile	8	0
Enzymes Over 95%ile	28	14
Enzymes Over 90%ile	52	30
Enzymes Under 10%ile	150	240
Enzymes Under 5%ile	120	161
Enzymes Under 1%ile	90	88
Compounds Over 99%ile	7	8
Compounds Over 95%ile	37	101
Compounds Over 90%ile	146	360
Compounds Under 10%ile	94	443
Compounds Under 5%ile	60	162
Compounds Under 1%ile	35	101

A summary of the above would be:

• More bacteria are in play over time, post COVID
  • More bacteria at extreme high values
  • Less bacteria at extreme low values
• No difference seen for canned selection of bacteria ( JasonH thru XenoGene)
• More extreme values seen from Outside Lab Range (+/- 1.96SD), and Outside Box-Plot-Whiskers
• Enzyme production became more extreme over time, after COVID
• Compound production extreme values dropped a lot

This agrees with Special Studies on a large population (n > 150) of long COVID, especially for Compounds. There were no statistically significant compounds detected. There were statistically significant bacteria and enzymes detected.

Looking at the From Special Studies, we see that the degree of match for all of the top items have increased significantly (with the lab quality being similar), which is in agreement with “getting worse”

	Older Sample	Latest Sample
Inflammatory bowel disease	52% match	63% match
Small intestinal bacterial overgrowth (SIBO)	45%	54%
Depression	43%	50%
ME/CFS without IBS	42%	50%
COVID19 (Long Hauler)	41%	46%
Unrefreshed sleep	41%	51%

Which set of Suggestions is likely best?

Using BiomeSight data with Long COVID with Special Studies is by far the best. It detects 93 different bacteria at a detail level (low hierarchy – species, z-scores for each above 2.6) versus GI-MP with PubMed Long COVID studies which detects just 2 bacteria at the highest hierarchy level (phylum). While GI-MAP may be technically superior, there are two important factors:

• The number of bacteria reported is significantly less in GI-MAP. Ideally, they will, in time, provide a deep report with NCBI numbers available for download or automatic transfer.
  • Volume of data and volume of different bacteria has an exponential impact on the ability to detect what has statistical significance.
• We do not have a curated set of samples with Long COVID with GI-MAP. In other words, it does not point to the specific bacteria we should focus on.

Bottom Line

I am going to skip building a consensus here. The Special Studies filter for Long COVID feels right for a starting point. Doing the suggestions for 3 months and then doing a retest would be my way forward (after reviewing with your medical professional)

What we have not touched is probiotics.

From KEGG data, the top species were Azospirillum lipoferum, Streptomyces venezuelae, Azospirillum brasilense — all sitting in 110-120 range. These are from probiotics like Equilibrium and Prescript Assist (various versions) –  Prescript-Assist®/SBO Probiotic sits at the top of mixed impact.

Scanning down the list for familiar names, we see

• Bacillus subtilis subsp. natto, Bacillus subtilis, and other bacillus probiotics in the 75 to 83 range
• Escherichia coli is at 68
• Clostridium beijerinckii is at 63
• Clostridium butyricum is at 55
• Enterococcus faecalis at 40
• Lactococcus lactis at 39
• Lactobacillus plantarum at 36
• Lactobacillus gasseri at 23
• reg’activ / immune & vitality – contains lactobacillus brevis (Levilactobacillus brevis) at 28 and lactobacillus fermentum (Limosilactobacillus fermentum) at 24.3
• Pädia GmbH (DE)/Mambiotic Kapseln – contains lactobacillus fermentum (Limosilactobacillus fermentum) at 24.3
• spain (es) / lactanza hereditum – contains lactobacillus fermentum (Limosilactobacillus fermentum) at 24.3
  

Remember: The above are specific species, you may wish to view the Probiotic Mixtures page to see which species are in each mixture. My take for simplicity would be: Prescript Assist, Symbioflo-2 (E.Coli probiotic),  miyarisan (Clostridium butyricum) and one of those listed above containing lactobacillus fermentum (Limosilactobacillus fermentum).

Reminder: One set of probiotic suggestions is obtained from the (very few) studies using the probiotics species and seeing what is affected. The other set of suggestions is obtained from the genomics of the bacteria that you have and the genomics of probiotic species. Two very different approaches which lead to the same probiotics.

Questions

This person is a new person to microbiome intrepretation (with a dose of brain fog)

Q: Are the items on the green add or increase lists the things I should be adding to my diet to help lower the levels of the bad bacteria I have.?

A: Correct, Some items have a ruler beside it, 📏, This is a link to dosages used in clinical studies (i.e. likely both safe dosages, and likely sufficient dosage to cause change. They are slowly being added for more and more modifiers.

I have shown suggestions from BOTH of your samples below, you will note that they are very similar.

For example for walnuts we see that 40-80 gram/day (1.5 to 4 ounce) or 1/3 – 2/3 cups/day.

A: The Red ones are ones to reduce or eliminate from your diet when possible. These are substance that encourages the bad shifts. Often there can be surprises when the items to avoid are those often suggested. Best example is Vitamin B12 — I have a hypothesis (which some people agree with from their experience) that there are greedy bacteria in the gut that thrives on B-12 (thus accounting for low B-12 levels in the blood). It is suggested that B-Vitamins be taken by injection or transdermal (via skin patches).

Q: What should be the priorities in terms of diet and supplements to help reduce the levels of bad bacteria? 

A: After reducing as many red items slowly (don’t go cold turkey!) as practical, start adding the green items with the highest confidence items according to practically (cost, ease of preparation, other issues). Again, small steps, adding one every two days. For probiotics, do one for two weeks and then change to a different one (See this post for background)

Q: Also the top three probiotics that the AI program came up with are Symbiopharm/ symbioflo, Regactiv immune and vitality and LGasseri probiotic. Is that correct? I have started taking Visbiome? 

A: Yes, Visbiome has mixed benefits, some of it’s component may shift items in the wrong way. It’s estimated confidence is 11 versus another mixed item Global Healing Center / FloraTrex with a value of 95. I would suggest taking it for two weeks (or until one of the other arrives, which ever occurs last).

Q: Also I see that Enterobacter, Bacteroides, Firmicites and Bacillus are too high. Which of these is the biggest problem and what particular bacteria in these bacteria families are over grown? 

A: Unfortunately, there is no way to detects which is the biggest problem. People will often speculate. With specials studies, we get a measure of how strongly bacteria are associated (called a z-score), For you, the most statistically significant for Long Covid that you have are

• Catonella
• Catonella morbi
• much lower: Clostridia

For Chronic Fatigue Syndrome the top ones for significance that you have are:

• Sporolactobacillus
• Sporolactobacillus putidus
• Prevotella copri
• Shuttleworthia

Q: I see from watching your other videos that I fit the pattern of a CFS patients pattern with a high number of rare bacteria. Have you seen people being able to reverse this to a more healthy normal microbiome and recover? 

A: Yes, take a look at this recent review A History of Several 16s Tests and Suggestions where we see measurable objective improvement as well as the person reporting improvement of some symptoms. There are several people that are doing test-> suggestions –> retest repeat. They have been forwarding their new samples to do an update as they are done (usually 3 months between tests). The pattern has been improvement both subjectively and objectively — unfortunately, it is not an overnight recovery, rather a slow methodological journey.

Different combination of bacteria cause different symptoms so the progress is from waypoint to waypoint .

One of the common misconception is that there is a “normal” microbiome that can be used as a reference.  Below is a chart from “Metagenomic sequencing of fecal DNA“. Diet makes a major impact on the distribution and volume of the bacteria.

• “In a study of gut bacteria of children in Burkina Faso (in Africa), Prevotella made up 53% of the gut bacteria, but were absent in age-matched European children.”[2010]

The chart below is for healthy individuals in 12 different countries.  In some cases neighboring very similar countries (Sweden [SE] and Denmark [DK]) have very different compositions.

This great variation means that testing the microbiome can only be done as group of individuals living in the same area with similar eating habits…. An individual result without reference from people with the same eating habits and possibly ethnic background is very fuzzy to interpret. Yes, highlights may be common — like low E.Coli, Lactobacillus and Bifidobacteria….  but they likely apply to no more than 80-90%, others may have different shifts based on things like being gluten free and other diets.

For more information see: The gut microbiome of healthy Japanese and its microbial and functional uniqueness [2016]

Then we also find that DNA also impacts the microbiome,

Host genetic variation drives phenotype variation, and this study solidifies the notion that our microbial phenotype is also influenced by our genetic state. We have shown that the host genetic effect varies across taxa and includes members of different phyla. The host alleles underlying the heritability of gut microbes, once identified, should allow us to understand the nature of our association with these health-associated bacteria, and eventually to exploit them to promote health.

Human genetics shape the gut microbiome , 2014

People have asked me, “Did you get your microbiome done, what was it?” My honest answer was “No, such testing was not available when I last had CFS. I simply assumed that my pattern would be an appropriate match to that reported from the 1998 Australian studies”

Age changes the microbiome

” DNA of the Clostridium leptum group and pathogenic Enterobactericeae increase in the gut microbiome with age and can be detected in the same individual’s coronary plaques along with pathogenic Streptococcus spp., associating with more severe coronary atherosclerosis. ” [2019]

The presence of the Bifidobacterium, Faecalibacterium, Bacteroides group, and Clostridium cluster XIVa decreased with age up to 66-80 years of age, with differences reaching statistical significance for the latter group. Interestingly, the levels of some of these microorganisms recovered in the very old age group (>80 years), with these older individuals presenting significantly higher counts of Akkermansia and Lactobacillus group than adults and the younger elderly

Age-Associated Changes in Gut Microbiota and Dietary Components Related with the Immune System in Adulthood and Old Age: A Cross-Sectional Study. [2019]

Latitude changes the Microbiome

Latitude means the distance from the equator. This may be due to sunlight-vitamin D levels.

If you exercised recently impacts the microbiome

Underlying these macro-level microbial alterations were demonstrable increases in select bacterial genera such as Veillonella (+14,229%) and Streptococcus (+438%) concomitant with reductions in Alloprevotella (-79%) and Subdolingranulum (-50%). To our knowledge, this case study shows the most rapid and pronounced shifts in human gut microbiome composition after acute exercise in the human literature. 

Rapid gut microbiome changes in a world-class ultramarathon runner. 2019

Some Population Studies

“We analyzed the combined microbiome data from five previous studies with samples across five continents. We clearly demonstrate that there are no consistent bacterial taxa associated with either Bacteroides– or Prevotella-dominated communities across the studies. By increasing the number and diversity of samples, we found gradients of both Bacteroides and Prevotella and a lack of the distinct clusters in the principal coordinate plots originally proposed in the “enterotypes” hypothesis. The apparent segregation of the samples seen in many ordination plots is due to the differences in the samples’ Prevotella and Bacteroides abundances and does not represent consistent microbial communities within the “enterotypes” and is not associated with other taxa across studies.” [2016]

” All Egyptian gut microbial communities belonged to the Prevotella enterotype, whereas all but one of the U.S. samples were of the Bacteroides enterotype.

• The intestinal environment of Egyptians was characterized by higher levels of short-chain fatty acids, a higher prevalence of microbial polysaccharide degradation-encoding genes, and a higher proportion of several polysaccharide-degrading genera.
• Egyptian gut microbiota also appeared to be under heavier bacteriophage pressure.
• In contrast, the gut environment of U.S. children was rich in amino acids and lipid metabolism-associated compounds; contained more microbial genes encoding protein degradation, vitamin biosynthesis, and iron acquisition pathways; and was enriched in several protein- and starch-degrading genera.
• Levels of 1-methylhistamine, a biomarker of allergic response, were elevated in U.S. guts, as were the abundances of members of Faecalibacterium and Akkermansia, two genera with recognized anti-inflammatory effects.
• The revealed corroborating differences in fecal microbiota structure and functions and metabolite profiles between Egyptian and U.S. teenagers are consistent with the nutrient variation between Mediterranean and Western diets.” [2017]

“This suggests that similarities between the Inuit diet and the Western diet (low fiber, high fat) may lead to a convergence of community structures and diversity. However, certain species and strains of microbes have significantly different levels of abundance and diversity in the Inuit, possibly driven by differences in diet.” [2017]

Bottom Line

IMHO: There is no clear definitive benefit from doing an individual microbiome testing — there is no reference that is reliable for it on an individual basis at a fine level of details. On the other hand, having results showing abnormalities help in several ways:

• It encourages you to make changes in eating which will usually be for the better
• It confirms that you have significant shifts and supports the concept that the gut is causing your symptoms.

” This work supports that sex is a critical factor in colonic bacterial composition of an aged, genetically-heterogenous population. Moreover, this study establishes that the effectiveness of dietary interventions for health maintenance and disease prevention via direct or indirect manipulation of the gut microbiota is likely dependent on an individual’s sex, age, and genetic background. ” [2019]

The source of this blog comes from SCIENCE,VOLUME 377|ISSUE 6612|16 SEP 2022, , pp. 1328-1332 DOI: 10.1126/science.abm7759, Codiversification of gut microbiota with humans

 An awareness of differences in gut microbial strains between populations has already led to the notion that probiotics for treating malnutrition should be locally sourced (38).

From Bifidobacterium infantis treatment promotes weight gain in Bangladeshi infants with severe acute malnutrition. Sci. Transl. Med.14, eabk1107 (2022).

I have held to the hypothesis that a person DNA and their microbiome evolved thru their ancestors and their ancestors’ diet together. This study demonstrated that the strains diverge .

Suzuki et al. noted that the global distribution of some human gut microbial strains mirrors historical human migration patterns out of Africa … However, within a species, some strains can show remarkable population specificity. The question is whether such specificity arises from a shared evolutionary history (codiversification) between humans and their microbes.

Evolutionary history of someone from the Hebrides Islands produces a high incidence of red hair. Evolutionary history of someone from the South Africa will be black haired, and  low and high curl individuals [2017]. Similarly, their microbiome will be different and reflect the DNA inherited by their host.

This was nicely illustrated in a series of diagrams in the above article. In the middle of each circle, you will see how the different strains branched from each other:

I noticed the following in the article:

 For mother-child pairs, strain sharing is often interpreted as vertical transmission, but acquisition of strains from a shared environment cannot be excluded (8). Indeed, our data also support strain sharing between community members: Within sampling locations in Gabon and Vietnam, we observed instances of the same strains in the microbiomes of mothers and unrelated children

Mother passing bacteria on to the children — breast feeding is the likely mechanism

We hypothesized that species that codiversified with their hosts are better adapted to the host environment than those that did not….together with the observed functional attributes, such as smaller genomes and oxygen and temperature sensitivity, codiversified species likely evolved host dependency.

This means issues such as diet and environment (hot, cold, humid, dry) impacts the evolution of the bacteria in the microbiome

Bottom Line

Probiotics should be sourced locally/from same genetic heritage. This is very technically feasible — just isolate the bacteria from stools of a suitable population, sequence it to insure no undesirable genetics, culture it and produce a local version.

Personally, I chuckle because the probiotic that I have responded best to was one that was one obtained from Germans in 1917, which in a match for my ancestry (Duchy of Slesvig, and southern islands of Denmark).

If you are of East Indian Descent (perhaps living in the US), you may wish to obtain probiotics from India and not your local health store. IMHO, you should contact the distributor of any probiotic that you use to obtain the provenance of the strain being used. Demand it!

To rephrase for some:

• If the probiotic kosher?
• If the probiotic halal?

Unfortunately, many probiotics being sold out there are not even from human sources, little more appropriate (regional) human sources for the consumers.

There is no Normal or Ideal Microbiome!

The parents provided rich information:

• OmbreLab results
• OmbreLab results processed thru BiomeSight (preferred because of Special Studies)
• OATS

Both children are in the same household, so diet will be similar.

The Son

 Our son is 14 and weighs 90 pounds and is Autistic.  It’s amazing that he sleeps well (10 hours) although the minute he gets up he is not stop moving, spinning, stimming, etc.  He can be redirected and can follow directions and can slowly progress is school although if we could calm him down I think he could learn a ton.  He understands everything we say and can ask for things if he slows down although he is not conversation.  Every 6-8 weeks he seems to have face flair (although hasn’t been that bad the last 6-10 months although we don’t know if it’s yeast, bacteria, etc.  Once he has it his OCD kicks in and he can’t stop putting lotions and creams on it.  He’s a skinny kid with not much muscle although can ride a bike, run a mile or two, etc.  

The Daughter

Our daughter is almost 16 and is not verbal although uses a device.  She has the autism diagnosis as well although also has a genetic mutation of the WDR45 gene (BPAN) which can create iron accumulation in the brain.  We spend a lot of time with supplements, organic nutrition, gluten free, time on the treadmill and sauna and more to make sure her body is detoxing the best it can.  She understands everything you say just can’t speak back.  Where my son is not stop she would cuddle all day and be 100% content.  She also  has fine and gross motor delays and in general is just cautious in her physical movement.  We’ve treated for SIBO several times, etc. although we’ve obviously never solved the problem.  She isn’t necessarily constipated although 95% of the time needs assistance with a small suppository for her to go the bathroom.  The stool is always there it’s just like she doesn’t have the urge to release it. 

High Level Comparisons

Below are summaries of the two children for comparison

	Daughter	Son
Biomesight Gut Wellness	77.37	85.89
Potential Medical Conditions Detected	none	a few fuzzy issues
Bacteria deemed Unhealthy	7	7
Dr. Jason Hawrelak Recommendations	98.8 %ile	99.7 %ile
KEGG Enzymes – Low Levels	Over reported (18.5)	Over reported (158)
Percentile Representation	High in rare bacteria	High in rare bacteria
Special Studies: Autism	49 matches	63 matches
Special Studies: Constipation	28 matches	19 matches
Probable Symptoms	Nothing	High Anxiety 85 Depression 85 ME/CFS with IBS 72

Comments on the above

Going thru the above, we see little difference between the two on may ways to evaluate the microbiome. However, there were a few where we see a great contrast:

• Enzymes at both extremes are very much higher for the son (4x higher at both top and bottom 1%iles)
• Bacteria under 1%ile is much higher with the son
• Box-Whisker and Kaltoft-Moldrup are much higher with the daughter
• Having profiles matching predicted symptoms, son only has significant matches

Daughter Action Plan

For the daughter, build up a consensus report from:

• Special Studies Autism (49 all low)
• Special Studies Constipation (28 all low)
• PubMed Autism (6)
• Box-Whisker (all were high)
• Kaltoft-Moldrup (17 low, 72 high)

Obtain Probiotics from:

• OATS
• From KEGG Computation
• From Consensus

Son Action Plan

For the son, build up a consensus report from:

• Special Studies Autism (49 all low)
• Special Studies Anxiety (30 all low)
• Special Studies Depression (39 all low)
• Special Studies ME/CFS with IBS (49 all low)
• PubMed Autism (6)
• Box-Whisker (5 too low, 44 too high)
• Kaltoft-Moldrup (36 low, 39 high)

Obtain Probiotics from:

• OATS
• From KEGG Computation
• From Consensus

This looks like a lot of work!

Actually, it’s not — I have done a video doing the son to illustrate the steps better.

Son Consensus

My person picks from the list are below. I was not overly happy with the To Take suggestions.

• gluten-free diet
• carboxymethyl cellulose (prebiotic)
• navy bean
• beef
• blueberry
• glycyrrhizic acid (licorice)
• iron supplements
• sesame cake/meal
• Conjugated Linoleic Acid

Looking at the avoid items, I would be inclined to try shifting these items out of his diet (if it is in it)

• walnuts
• brown rice
• apples
• inulin (prebiotic)
• chicken (beef is a to take)
• all probiotics except those below
• Barley

Son Probiotics

See video for details, the key items that occured at the

• Escherichia coli – symbioflor 2 e.coli probiotics or Mutaflor
• bacillus subtilis (many retail products have it)

Daughter Consensus

Some of the items may please the daughter.

• Top item is Cacao — trying shifting her to 85% or higher
• lactobacillus casei (probiotics) – I would suggest Yakult probiotic drink (it is well studied – lactobacillus casei shirota (probiotics))
• pea (fiber, protein) – perhaps pea soup occasionally
• Human milk oligosaccharides (prebiotic, Holigos, Stachyose)
• trametes versicolor(Turkey tail mushroom)
• mediterranean diet

On the avoid side, we see also:

• barley
• grapes, wine, and grape seed extract (which is interesting because aspirin is a to take)
• cannabinoids – which you likely approve of, as a parent
• inulin (prebiotic)
• saccharomyces cerevisiae (probiotics)

Daughter Probiotics

The consensus probiotics were much different than her brother

Looking at the OATS results, we see Bifidobacterium dominating it. This is not a surprise because Human milk oligosaccharides usually shows up when Bifidobacterium needs good encouragement. Please note: the list below did not use any microbiome data — just the OATS results.

The revised KEGG Probiotic had two items that tend to be frequent:

• Bacillus subtilis (which the brother also had suggested in multiple ways)
• Escherichia coli (symbioflor 2 e.coli probiotics was a positive take on the consensus report)

If there are any Lactobacillus probiotics being taken, I would eliminate them.

Bottom Line

Everything in this post is created by modelling data and nothing has been validated clinically. The advantage with modelling is that it is usually better than than a MD tossing an idea out in frustration.

All suggestions should be reviewed by a qualified medical professional before starting.

This is an old drug with most of the studies in 1970-1990. It is very different in action from antihistamines (i.e. it is NOT an antihistamine) with an awesome safety record. A reader asked me to assemble and review the literature. Mast cell and histamine issues are often reported with other conditions; the domination of other symptoms may mask the mast cell issues.

Conditions Often Comorbid With Mast Cell Diseases

• Chronic inflammatory response syndrome (CIRS)

• Fibromyalgia syndrome (FMS)

• Ehlers-Danlos Syndrome (EDS)

• Gulf War Illness (GWI)

• Interstitial cystitis/bladder pain syndrome (IC/BPS)

• Irritable bowel syndrome (IBS)

• Kounis syndrome

• Multiple chemical sensitivity syndrome (MCSS)

• Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)

• Post-Lyme syndrome

• Postural orthostatic tachycardia syndrome (POTS)

• Post-traumatic stress disorder (PTSD)

Cromolyn sodium is a medication used to manage bronchial asthma, allergic rhinitis, and certain allergic eye conditions such as vernal conjunctivitis, keratitis, and keratoconjunctivitis. It is a mast cell stabilizer. 

Cromolyn Sodium – Continuing Education Activity – StatPearls [NIH site – 2022]

Notes from the above:

• Derived from Mediterranean herb called Ammi visnaga
• Cromolyn sodium metered spray is used to prevent and relieve nasal symptoms of hay fever and other nasal allergies like runny or itchy nose, sneezing, and allergic stuffy nose.[7]
• Cromolyn sodium is off-labeled used for preventing serious reactions to foods.[8]
• The effect of cromolyn sodium on mast cells lasts for approximately 6 hours
• Cromolyn sodium inhibits immediate and late reactions.[15][12] 
• Adverse reactions reported with the inhalation solution were throat irritation and hoarseness, esophagitis, laryngeal and pharyngeal edema, drowsiness, dizziness, bronchial irritation, pulmonary infiltrates, and cough.[19]
• Given its safety profile and current evidence, its use is likely most favorable for those who cannot tolerate intranasal corticosteroids or require short-term prevention before known exposures.^6,7 

I was unable to find any generic clinical studies for Cromolyn with Myalgic encephalomyelitis/chronic fatigue syndrome or ASD (despite mast cell issues being associated with inflammation of the brain.

Availability

In the US available at retail (Walmart etc) from several brand,

• NasalCrom Nasal Spray Allergy Symptom Controller, 200 Sprays, – $16.26 – i.e. 1 cent per spray
• HealthGuard Cromolyn Sodium Nasal Spray, 200 Sprays – $12.99

The Herb Ammi Visnaga (Visnaga daucoides )

Used for over 2000 years

• “it is used in modern medicine to treat many aliments such as renal colic and coronary insufficiency, and is used as an antioxidant, antifungal, and antibacterial, with a larvicidal effect on mosquito larvae…. A.K.A. Khella Baldi or toothpick weed, In Arabic countries A. visnaga has many common names such as Khella baladi, Khella, Khellah, Khellakl, Chellah, Kella, Gazar sheitani, Kammon habashi, Bizer Al-Khilla, Kulla, and Swak Al-Nabi. In Turkey, it is known as disotu, kilir, and hiltan.” [2020]

Headaches — likely a spray symptom

A study of this spray against a placebo was found “The most common adverse events in both groups were headache and rhinitis, and there was no significant difference in the rates of such events between groups.” [2002]. This suggests that the spraying is a more likely cause, not the cromolyn nasal spray.

Literature

• Ways to Address Perinatal Mast Cell Activation and Focal Brain Inflammation, including Response to SARS-CoV-2, in Autism Spectrum Disorder. [2021]
• Mast Cells, Stress, Fear and Autism Spectrum Disorder. [2019]

Bottom Line

Given its awesome safety record, I would suggest a discussion with your medical professional on doing a course of over-the-counter nasal spray (done before each meal and at bed time – because it effects lasts only 6 hours). A single bottle should last for 50 days.

With regular testing and following suggestions, Hawrelak’s criteria out of range items went from 9 , to 7, to 4. Suggestions appear to work (slowly). This is a follow up of prior posts, the bottom line is that with

• Jan 25,2022 A review of a ME/CFS Microbiome
• Jul 16,2022 Comparing 4 ME/CFS Samples with New Tool

I am going to start with the same comparison as I did in the prior post above, and then move on to do an analysis using the latest tools available.

Why Follow Up Posts are important

The first item is simple, does the model and suggestion appear to work. Everything is theoretically computed, not based on clinical practice or clinical studies. The second item is that these posts encourages people to try suggestions, or to do “self-serve” with the site.

Foreword – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that appears to have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.

Comparisons between Samples

We have the latest test processed through both Ombre and Biomesight. This analysis will use Ombre because that is what was used in prior; latest one will use Biomesight so we can use the new special studies for suggestions

The high lights are:

• Sample quality is better than the prior samples, we see more bacteria reported
  • Ombre is reporting more (as we saw in a prior post)
• Improvement in the critical bacteria identified by Dr. Jason Hawrelak, we are down to just 4 bacteria outside of range for both (from prior 7 and 9)
• Similar with Medivere, MyBioma,Nirvana/CosmosId, and XenoGene ranges
• On the opposite side, we have more outside of Box-Plot-Whiskers, Lab Range (+/- 1.96SD) and Kaltoft-Moldrup – this is not unexpected because we have a lot more bacteria. The criteria improved are the criteria with a fix set of bacteria that are usually there in most samples.
• The number of extreme enzymes levels (using Ombre) have been significantly reduced. Compounds have no clear shift

Measure	8/22/2022 BIOMESIGHT	8/22/2022 OMBRE	6/15/2022	5/16/2022	3/15/2022	11/21/2021
Lab Read Quality	5	5	4.8	4.8	3.6	4.2
Bacteria Reported By Lab	657	765	515	669	593	473
Bacteria Over 99%ile	0	9	0	1	0	1
Bacteria Over 95%ile	15	45	4	22	21	9
Bacteria Over 90%ile	38	82	22	40	48	21
Bacteria Under 10%ile	168	35	43	112	23	87
Bacteria Under 5%ile	84	16	18	60	5	46
Bacteria Under 1%ile	24	3	0	9	0	2
Lab Read Quality	BiomeSight	Ombre	Ombre	Ombre	Ombre	Ombre
Pathogens	47	43	37	42	38	33
Outside Range from JasonH	4	4	7	7	9	9
Outside Range from Medivere	15	15	17	17	20	20
Outside Range from Metagenomics	8	8	8	8	7	7
Outside Range from MyBioma	4	4	8	8	10	10
Outside Range from Nirvana/CosmosId	20	20	23	23	22	22
Outside Range from XenoGene	4	4	8	8	10	10
Outside Lab Range (+/- 1.96SD)	16	14	2	7	6	2
Outside Box-Plot-Whiskers	135	118	42	71	72	25
Outside Kaltoft-Moldrup	155	209	113	148	143	91
Condition Est. Over 99%ile	0	0	0	0	0	0
Condition Est. Over 95%ile	0	0	0	0	0	0
Condition Est. Over 90%ile	0	0	0	0	1	0
Enzymes Over 99%ile	2	8	91	48	53	5
Enzymes Over 95%ile	48	78	599	305	182	147
Enzymes Over 90%ile	99	154	719	629	438	458
Enzymes Under 10%ile	175	75	70	71	38	169
Enzymes Under 5%ile	101	33	19	28	4	78
Enzymes Under 1%ile	20	3	2	0	0	0
Compounds Over 99%ile	31	36	6	93	143	19
Compounds Over 95%ile	131	265	186	277	190	89
Compounds Over 90%ile	371	380	303	435	220	118
Compounds Under 10%ile	212	282	321	528	333	133
Compounds Under 5%ile	54	186	195	378	310	100
Compounds Under 1%ile	23	62	0	118	267	42

The data suggests further improvement with the latest sample — in terms of numbers, dramatic!

Going Forward

We are going to use the Special Studies to generate the next set of suggestions. Remember that the numbers below are sensitive to the number of bacteria detected (i.e. lab quality). The latest sample had the highest quality which means that percentages may increase due to that alone.

	Percentage Matches	8/22/2022	7/21/2022	4/20/2022	2/22/2022	11/22/2021
1	Alcohol intolerance or Medication sensitivities	52	34	36	36	39
1	Allergic Rhinitis (Hay Fever)	33	31	35	35	36
0	Allergies And Food Sensitivity	30	32	32	32	34
0	Autism	38	28	31	31	44
1	Bloating	24	22	24	24	32
2	Brain Fog	28	32	39	39	26
2	Chronic Fatigue Syndrome (CFS/ME)	33	30	28	28	30
0	Cold Extremities	31	36	29	29	31
0	Constipation	17	18	15	15	29
2?	COVID19 (Long Hauler)	39	36	31	31	39
0	Depression	40	30	33	33	35
0	Easily irritated	28	31	24	24	27
2	General Fatigue	26	26	28	28	28
1	High Anxiety	28	26	25	25	26
1	Histamine or Mast Cell issues	28	24	27	27	32
0	Inflammatory bowel disease	43	48	28	38	43
0	irritable bowel syndrome	31	30	26	26	36
1	Intolerance of Extremes of Heat and Cold	32	30	24	24	36
0	ME/CFS with IBS	31	24	24	24	27
2	ME/CFS without IBS	30	25	23	23	28
0	Poor Gut Motility	25	37	31	31	35
2	Post-exertional malaise	22	24	23	23	26
0	SIBO	38	36	27	27	34
0	Tinnitus (ringing in ear)	32	34	24	24	28
2	Unrefreshed sleep	37	27	26	26	29

What surprised me, and delighted me, was the relative consistency of the numbers for the same person over time for many symptoms. This time, because of the special studies, we are going to focus on generating suggestions specific to the issues of greatest concerns (2) above.

• Brain Fog
• Chronic Fatigue Syndrome (CFS/ME)
• COVID19 (Long Hauler)
• General Fatigue
• ME/CFS without IBS
• Post-exertional malaise
• Unrefreshed sleep

Having high IBS or IBD values does not equate to ME/CFS with IBS — prior to my latter flares, I saw no gut issues at all.

The top Items are similar to each other:

• Pulses (Black Beans,Broad Beans,dry beans, dry broad beans, dry peas, chickpeas, cow peas, pigeon peas, lentils, Bambara beans, vetches, lupins), navy bean, pea (fiber, protein)
• symbioflor 2 e.coli probiotics,colinfant e.coli probiotics and d-ribose (which feeds e.coli)
• arabinoxylan oligosaccharides (prebiotic)
• lactulose
• green-lipped mussel
• levan
• fasting
• galacto-oligosaccharides (prebiotic)
• non-starch polysaccharides
• carob
• raffinose(sugar beet)
• wheat bran
• barley,oat
• sesame cake/meal
• Reduce choline (Beef, Chicken Eggs)

The top of the avoid list are many B-Vitamins. In prior posts, I speculated that the low vitamin B-levels seen in the blood of ME/CFS patients etc is because of greedy gut bacteria that prevents it being absorbed. I just did some literature browsing and this speculation appears to agree with some research.

Now, Wexler et al. show that some gut microbes may be able to pirate vitamin B12 from us as it passes through the digestive tract. Wexler et al. showed that a protein called BtuG on the surface of a type of gut bacteria called Bacteriodes grabs onto vitamin B12 with extraordinary strength. In fact, these bacterial proteins bind to vitamin B12 so strongly that they can even pry it away from our own vitamin B12 collecting protein.

Human gut Bacteroides capture vitamin B₁₂ via cell surface-exposed lipoproteins [2018]

This means that to avoid B-vitamins via food or supplements, despite having low blood level may be a rational approach. Getting Vitamin-B injections bypassing the gut bacteria may be a more effective approach to dealing with low vitamin-B. Choline is connected with B-Vitamins, see The B Vitamins and Choline: Overview and Methods [1998], hence the reduce choline suggestion above.

Probiotics

Escherichia coli was the top probiotic on the consensus. Using Ombre reading of the sample and the Kyoto Encyclopedia of Genes and Genomes, Escherichia coli is the top suggestion with items like Bacillus subtilis being 1/3 of contribution. The same results appear with the BiomeSight processing.

For flavonoids and polyphenols — it seems that supplementing with any should be avoided. The very few with a positive value has ‘equivalents’ being negative values. For amino acids: Conjugated Linoleic Acid, l-citrulline and proline (amino acid) are the top choices. Diet choices are low animal protein (which agrees with avoiding b-vitamins) and high fiber (which agrees with pulses above)

Bottom Line

Remember, these are not generic suggestion for anybody with ME/CFS. These are specific to this person’s microbiome. We see that the numbers for his microbiome has improved, but some items are still of concern. Our method of getting suggestions shifted over to using the Special Studies because he had a number of symptoms that were significant which were covered by the special studies, as well as his data being processed thru BiomeSight which we are using for special studies (apples to apples comparisons).

Again, the computations are based on the odds of items helping the microbiome to shift in the desired direction. Odds are just that, some will work, some will not — but ideally more will work than not. For the suggestions, remember ROTATION (Rotation — Essential for Changing the Microbiome), and pick items that work for you and your medical professional. The suggestions can be viewed as a series of dresses on a rack, you do not need to buy all of them to be fashionable. Use the ones that work for you.

Rotation as a key facet of fixing or keeping a microbiome healthy was first introduced to me in 1999 by Cecile Jadin, MD (Surgeon in South Africa) with the Occult Rickettsia Protocol from the Pasteur Institute of Tropical Disease (where her father worked). I have written about this prior, Rotation and Pulsing: Herbs, Probiotics, Antibiotics [2017], Rotate, Rotate, Rotate and Curcumin [2016], Continuous or Pulse Supplements? [2015]

Some literature on it:

• The effects of antibiotic cycling and mixing on acquisition of antibiotic resistant bacteria in the ICU: A post-hoc individual patient analysis of a prospective cluster-randomized crossover study [2022]
• Optimising efficacy of antibiotics against systemic infection by varying dosage quantities and times. [2020
• The effects of antibiotic cycling and mixing on antibiotic resistance in intensive care units: a cluster-randomised crossover trial. [2018]
• Fighting antibiotic resistance in the intensive care unit using antibiotics[2015].
• “with a 28-day on-off regimen with tobramycin or aztreonam” [2015]
• Antibiotic rotation strategies to reduce antimicrobial resistance in Gram-negative bacteria in European intensive care units: study protocol for a cluster-randomized crossover controlled trial [2014].
• Antibiotic rotation for febrile neutropenic patients with hematological malignancies: clinical significance of antibiotic heterogeneity[2013].
• The impact of an antibiotic cycling program on empirical therapy for gram-negative infections. [2006]

The Microbiome is not a Mechanical System

Think in terms of societies. Think about a gang that steals quality goods at a store. The antibiotic may be having a store detective. Issue solved – no more crime! Wrong, the gang will change to a different crime, they will adapt. It will become a continuous battle and escalation by both sides. Many people view the microbiome as a simple mechanical system unfortunately, bacteria continuously mutate (think of COVID mutations). If the antibiotic kills off 99% of the bacteria, the remaining 1% likely has a mutation that allowed it to survive. Give this 1% a few weeks and we are back to old levels with the antibiotics making no difference.

How does this apply to vitamins, amino acids, even food? The simplest explanation is that those items affect the growth of different bacteria. Different bacteria strains produces different compounds, including  bacteriocins (natural antibiotics). When you think about probiotics, remember that they often work due to their natural antibiotics (see above for literature).

To jump to the human body for an example, when you were 20 you likely drank a lots of pop, smoked.. ate a lot of fast food… and were “healthy” and fine. As you body ages (evolved), the same diet would worsen diabetes, weight, and a dozen other conditions that will evolve. The microbiome changes with time, in fact, it changes faster than your body. When you make one set of changes, like running 2 miles a day, the body may act up with structure damage as you age. Professional players in sports do not age well. Going on a specific type of diet may address one issue and trigger a different issue eventually.

What is the answer? All things in moderation. Instead of just one type of exercise, do a variety of appropriate exercises. Instead of a specific diet (which may deliver insufficient minerals or vitamins), rotate around different diets that addresses the issue you are trying to address. Every change you make, changes the microbiome– sometimes in unexpected ways.

In terms of suggestions from the microbiome prescription site, rotating suggestions is desired — usually there are many suggestions so it should not be hard.

What is the Ideal Rotation?

I do not know, I have inferred from the typical duration of antibiotic prescription that 7-10 days is a reasonable guess. I will give a simple example of one rotation that I do (maintaining), alternating the various forms of gluten (the specific types are listed after each).

• Oats – as porridge: avenin, C-hordeins, γ-hordeins, B-hordeins and D-hordeins
• Rye – as German 100% rye bread: γ-40k-secalins and high-molecular-weight secalins
• Wheat — as typical western baked goods: (ω5-gliadins, ω1,2-gliadins, α-gliadins, γ-gliadins and high- and low-molecular-weight glutenin
• Barley – as porridge: C-hordeins, γ-hordeins, B-hordeins and D-hordeins

My stools will change every cycle – IMHO, there is no perfect stool.

From Isolation and characterization of gluten protein types from wheat, rye, barley and oats for use as reference materials [2017].

The goal is almost like trying to herd a group of cats.

Most of the analysis that I have done recently has been either ME/CFS, Long COVID or Autism. If you look at the page entitled Medical Conditions with Microbiome Shifts from US National Library of Medicine you will see a lot of different conditions that may be influence by microbiome manipulation..

Today I got an email asking “My mother in law has Progressive supranuclear palsy (PSP), and Diabetes  and is in a very bad state, there is no help from the mainstream medicine” with samples of her.

My first action is to see if there are any published studies on PSP and the microbiome. There was just one study: “Unraveling gut microbiota in Parkinson’s disease and atypical parkinsonism‘ 2018.

Progressive supranuclear palsy (PSP) is a less well-known neurodegenerative brain condition which is sometimes misdiagnosed as Parkinson’s disease or Alzheimer’s disease (or other forms of dementia). Because of the similarity to some Parkinson’s symptoms during the early stages of the disease, PSP is included in a group of diseases called Parkinson’s Plus Syndrome or Atypical Parkinsonism. However, PSP progresses much faster, causes more severe symptoms, responds very poorly to Parkinson’s medication, and has a significantly reduced life expectancy.

Parkinson’s Europe

At this point out a recent news story, Woman who smelled her husband’s Parkinson’s helps scientists come up with diagnostic test, Sky News, Sep 7,2022. When some ones gut bacteria changes, their smell change. On a little morbid note, in WW2, they could tell dead soldiers apart from their smell (he’s a German, he’s an Italian, he’s an American) [Story]. So avoiding scented products may have health benefits. In Vietnam war, it was different — the Viet Cong favorite smell was Old Spice, it means that there were Americans close by.

Foreword – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.

Analysis

We lack any special studies nor any Medical Conditions with Microbiome Shifts from US National Library of Medicine(PubMed) which matches this person except for Diabetes. We do not have enough samples for Special Studies for Diabetes. For the PubMed, this person is sitting at the 95%, so a definite include. There is another PubMed that seem appropriate and which is at the 99%ile, Brain Trauma

Looking at data in detail, we see a definitely interesting microbiome. We have a high quality sample

Criteria	Current Sample	Comment
Lab Read Quality	10.6	High Quality
Bacteria Reported By Lab	960	Very high Count
Bacteria Over 99%ile	23	7 is expected, so high
Bacteria Over 95%ile	85	48 is expected
Bacteria Over 90%ile	155	96 is expected
Bacteria Under 10%ile	296	96 is expected
Bacteria Under 5%ile	267	48 is expected
Bacteria Under 1%ile	242	7 is expected
Rarely Seen 1%	56
Rarely Seen 5%	182
Pathogens	59
Outside Range from JasonH	8
Outside Range from Medivere	16	Candidate
Outside Range from Metagenomics	8
Outside Range from MyBioma	7
Outside Range from Nirvana/CosmosId	19	Candidate
Outside Range from XenoGene	5
Outside Lab Range (+/- 1.96SD)	37	Candidate
Outside Box-Plot-Whiskers	194	Candidate
Outside Kaltoft-Moldrup	347	Candidate
Condition Est. Over 99%ile	3
Condition Est. Over 95%ile	20
Condition Est. Over 90%ile	29

Dr. Jason Hawrelak Recommendations are at 99.7% so no red flags from that. There is a huge number of PubMed matches, I will only use the best ones for what was reported for this person. The following sets of suggestions are going to be used for our Consensus Report

• PubMed: Brain Trauma
• PubMed: Type 2 Diabetes
• Outside Range from Medivere
• Outside Range from Nirvana/CosmosId
• Outside Lab Range (+/- 1.96SD)
• Outside Box-Plot-Whiskers
• Outside Kaltoft-Moldrup

The consensus download is below

Probiotics

From KEGG, we see many of the Equilibrium and PrescriptAssist bacteria listed with the following further down the list (in descending order) (Remember : Lacticaseibacillus is the new name for Lactobacillus)

• Escherichia coli
• Bacillus subtilis
• Clostridium butyricum
• Akkermansia muciniphila
• Lacticaseibacillus casei
• Enterococcus faecium
• Lactiplantibacillus plantarum
• Enterococcus faecalis
• Lacticaseibacillus rhamnosus

From the consensus we have (in decreasing order), a similar list.

• lactobacillus rhamnosus gg (probiotics)
• enterococcus faecium (probiotic)
• Akkermansia muciniphila (probiotic)
• mutaflor escherichia coli nissle 1917 (probiotics)
• bacillus coagulans (probiotics)
• NEITHER Equilibrium nor PrescriptAssist were positive

My gut feeling is that the following products are likely a reasonable choice.

• L.Plantarium – Custom Probiotics
• Escherichia coli – mutaflor escherichia coli nissle 1917 (probiotics), if not available, Symbioflor-2 as an alternative.
• Akkermansia Muciniphila — Pendulum
• Clostridium butyricum – Miyarisan
• Enterococcus faecalis + Bacillus subtilis + bacillus coagulans – ThreeLac

I would suggest starting with whatever arrives first, starting with a low dosage and increasing every second day. Remember to review with your medical professional.

Vitamins

A vitamin B complex and Vitamin C are recommended

Supplements

The top items are all available on Amazon and other stores:

• melatonin supplement
• l-taurine
• epicatechin
• Hesperidin (polyphenol)
• mastic gum (prebiotic)
• sucralose

Herbs And Spices

Diet Style

Bottom Line

This person wife also has issues, see And now for a different condition… Part 2. The suggestions are different but creating two different menus everyday would be challenging. See that post for a possible solution.

One of the items cited that I did not include above was dopamine (prescription). Looking at a treatment site for PSP in an attempt to do cross-validation, we see that dopamine is a factor, but things are more complex, see: Excessive dopamine neuron loss in progressive supranuclear palsy [2008].

When I started this project, I saw the potential of using the microbiome as a method to identify candidate treatments in the absence of successful clinical treatments. This is the first attempt of putting this into practice.

Most of the analysis that I have done recently has been either ME/CFS, Long COVID or Autism. If you look at the page entitled Medical Conditions with Microbiome Shifts from US National Library of Medicine you will see a lot of different conditions that may be influence by microbiome manipulation..

In the same email I got an second challenge: “Father In Law – Diabetes, Heart conditions and High Blood Pressure” with samples of her.

Foreword – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.

Analysis

In this case we have an even higher lab quality than the wife, but a lot less bacteria reported. This means that the microbiome is likely a lot less fragmented than the wife.

Criteria	Current Sample
Lab Read Quality	11.5
Bacteria Reported By Lab	628
Bacteria Over 99%ile	4
Bacteria Over 95%ile	27
Bacteria Over 90%ile	48
Bacteria Under 10%ile	330
Bacteria Under 5%ile	295
Bacteria Under 1%ile	237
Rarely Seen 1%	12
Rarely Seen 5%	41
Pathogens	50
Outside Range from JasonH	7
Outside Range from Medivere	21
Outside Range from Metagenomics	9
Outside Range from MyBioma	4
Outside Range from Nirvana/CosmosId	25
Outside Range from XenoGene	6
Outside Lab Range (+/- 1.96SD)	14
Outside Box-Plot-Whiskers	54
Outside Kaltoft-Moldrup	246
Condition Est. Over 99%ile	1
Condition Est. Over 95%ile	1
Condition Est. Over 90%ile	8

Dr. Jason Hawrelak Recommendations has him at the 75%ile — so off, but not really bad. Following the same pattern of analysis as the wife (since we have no matching special studies):

• PubMed: Hypertension (High Blood Pressure 
• PubMed: Type 2 Diabetes
• PubMed: Coronary artery disease
• Outside Range from Medivere
• Outside Range from Nirvana/CosmosId
• Outside Lab Range (+/- 1.96SD)
• Outside Kaltoft-Moldrup

The consensus download is below

Probiotics

From KEGG, we do NOT find Escherichia coli near the top of the list. We see the usual odd bacteria strains from Equilibrium and Prescript Assist then:

• Bacillus subtilis
• Bacillus licheniformis

With microbiome labs/ megasporebiotic being a good match.

From the consensus we have (in decreasing order), a similar list.

• lactobacillus reuteri (probiotics) see this list for products that combines this with one or more of the following (also recommended)
  • lactobacillus plantarum (probiotics)
  • lactobacillus rhamnosus gg (probiotics)
• pediococcus acidilactic (probiotic) – for example: Imagilin / NutriLots
• bacillus subtilis (probiotics) – see above
• The following are shared with his wife (but lower priority)
  • enterococcus faecium (probiotic)
  • Clostridium butyricum
    

I would suggest starting with whatever arrives first, starting with a low dosage and increasing every second day.

Prebiotics

Vitamins

Most of the vitamin B’s are to be avoided. Selenium, magnesium, vitamin a and folic acid,(supplement Vitamin B9) are the top items.

Supplements

The top items are all available on Amazon and other stores:

• polymannuronic acid
• glycine
• proline (amino acid)
• Taxifolin
• grape polyphenols

Herbs And Spices

Diet Style

Specific Foods

One item really jumps out — Burdock Root (Gobo in Japan)- which is available as a supplement if not available as a fresh vegetable. It is high in Inulin (but inulin is much lower, just 81 — so other components may be playing a significant role)

Bottom Line

The diet style is a major contrast with the wife — this creates the frustration of needing almost a double food preparation. To address this issue, I imported both consensus list into Excel, used a VlookUp function to display the values besides each modifier and then identified items that are positive for both and then order by the total of each.

This allows one menu to be used for both of them. Perhaps a little less effective, but likely a lot less frustrating (and thus better compliance). I attached it as an example.

This is a follow up to a prior post:

• Jul 8, 2022. A Complex Microbiome Situation

This person did his tests using OmbreLabs.com and then transfer the data to biomesight.com. This allows us to use special studies to select bacteria. I am also, as part of my own learning (as well as the readers), going to do some comparison between the OmbreLabs and BiomeSight reports on the same data (i.e. FASTQ files).

I had another sample analyzed at Ombre, and there were already changes in my flora, even in a short amount of time. And they correlate with me feeling a bit better. So thank you. I’m still trying to crunch the data and make sense of the new results, and other than your great Dr. AI, I am using this new feature by Ombre which I find very clear (old sample first, new sample after)

Why Follow Up Posts are important

The first item is simple, does the model and suggestion appear to work. Everything is theoretically computed, not based on clinical practice or clinical studies. The second item is that these posts encourages people to try suggestions, or to do “self-serve” with the site.

Foreword – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that appears to have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.

Comparisons between Samples

See this other review of a series of ME/CFS microbiomes from another person that I recently did, ME/CFS Follow Up Microbiome Samples. If you are new to this series, you may wish to review A new specialized selection of suggestions based on statistical significance for symptoms.

First, I do not know the best way to compare samples — what I usually do is put all of the numbers side by side. Special attention needs to be paid to Lab Read Quality. A poorer read quality results in less bacteria being identified.

Lab Quality is a measure of the total number of bacteria counted. The processing of a sample may detect just 30,000 bacteria or 300,000 bacteria. This impacts the number of bacteria detected and also the accuracy of the measures.

Also, Special Studies Percentage Matches is helpful to interpret these numbers better.

Criteria	BS 6/6	BS 7/19	OL 6/6	O 7/19
Lab Read Quality	2.1	5.4	2.1	5.4
Bacteria Reported By Lab	280	497	365	628
Bacteria Over 99%ile	2	7	5	6
Bacteria Over 95%ile	24	31	27	24
Bacteria Over 90%ile	49	58	49	51
Bacteria Under 10%ile	17	62	18	60
Bacteria Under 5%ile	5	30	10	28
Bacteria Under 1%ile	0	13	1	7
Rarely Seen 1%	0	4	0	9
Rarely Seen 5%	4	18	8	40
Pathogens	15	25	19	28
Outside Range from JasonH	4	4	7	2
Outside Range from Medivere	17	17	16	16
Outside Range from Metagenomics	7	7	7	7
Outside Range from MyBioma	9	9	14	14
Outside Range from Nirvana/CosmosId	22	22	23	23
Outside Range from XenoGene	6	6	11	11
Outside Lab Range (+/- 1.96SD)	6	13	10	14
Outside Box-Plot-Whiskers	70	84	64	61
Outside Kaltoft-Moldrup	70	113	112	182
Condition Est. Over 99%ile	1	1	0	0
Condition Est. Over 95%ile	2	4	0	0
Condition Est. Over 90%ile	5	6	2	2
Enzymes Over 99%ile	3	10	13	15
Enzymes Over 95%ile	46	32	69	82
Enzymes Over 90%ile	90	51	155	411
Enzymes Under 10%ile	102	219	55	138
Enzymes Under 5%ile	45	132	22	67
Enzymes Under 1%ile	6	47	5	2
Compounds Over 99%ile	9	7	104	126
Compounds Over 95%ile	56	76	385	397
Compounds Over 90%ile	292	313	533	548
Compounds Under 10%ile	72	125	183	248
Compounds Under 5%ile	39	64	109	127
Compounds Under 1%ile	5	21	16	17

What are the key things seen above (most of the numbers are similar):

• Sample Quality are the same (expected from using the same FASTQ file)
• Ombre reports more bacteria
• Outside Range from Jason Hawrelak show a major improvement with Ombre Labs and no change with BiomeSight
  • As a historic notes, Jason’s numbers were developed using uBiome labs (adding more fuzziness to everything).
  • I view this major improvement per OmbreLab, to indicate the person’s improvement.
• For Enzymes we see more high production rates and less low production rate with Ombre
  • Remember that enzymes are estimated based on the bacteria reported and is an estimate only.
  • The percentiles for both Ombre and BiomeSight are based on other samples from the same lab (they are NOT intermixed – I removed that earlier this year)
• For Compounds, we see the same thing!

KEGG Computed Enzymes

I was curious what the top items were. Most of the bacteria are the bacteria only available in Equilibrium and PrescriptAssist, excluding those and looking at the top few — we see similar suggestions (and note E.Coli is not always #1 for ME/CFS people on all tests, just a frequent pattern what dates back to 1998 in some conference papers from Australia).

• BiomeSight 6/6: Escherichia coli
• BiomeSight 7/19: Escherichia coli
• Ombre 6/6: Streptomyces venezuelae, Escherichia coli
• Ombre 7/19: Escherichia coli

Special Studies Numbers

Only BiomeSight was used in the Special Studies (because of higher sample population). The person’s rating for each of the symptoms (2 – worst, 0 -none) is also added.

Why did the number increased so much? Look below at Lab Sample quality! We cannot pick a percentage match as being critical — because that percentage depends very much on lab quality!

BS 6/6	BS 7/19	Person	Symptom
2.1	5.4		Lab Quality
13	25	2	Allergies And Food Sensitivity
13	20	2	Bloating
11	24	2	Brain Fog
9	34	2	Depression
13	23	2	Easily irritated
8	22	2	General Fatigue
11	23	2	High Anxiety
12	20	2	Histamine or Mast Cell issues
13	23	1.5	Chronic Fatigue Syndrome (CFS/ME)
11	20	1.5	irritable bowel syndrome
13	23	1.5	ME/CFS with IBS
12	30	1	Alcohol intolerance or Medication sensitivities
10	23	1	Intolerance of Extremes of Heat and Cold
9	17	1	Post-exertional malaise
21	30	1	Small intestinal bacterial overgrowth (SIBO)
12	28	1	Unrefreshed sleep
16	28	0	Allergic Rhinitis (Hay Fever)
23	28	0	Autism
12	22	0	Cold Extremities
15	20	0	Constipation
21	29	0	COVID19 (Long Hauler)
26	45	0	Inflammatory bowel disease
8	23	0	ME/CFS without IBS
11	21	0	Poor gut motility
8	20	0	Tinnitus (ringing in ear)

Intrepretation

As cited in the introduction, the person reported feeling better. We also see a major improvement against Jason Hawrelak Criteria for a healthy gut (using Ombre numbers). With both labs we see an increased of rarely seen bacteria — which is open to many interpretations; statistically both increases looks like a move towards a typical gut. 5% of 628 bacteria is 31, we see 40.

Going forward

I am building a consensus report from the items marked 2 above using the Special Studies. The list is similar to other people with ME/CFS. We see 2 E.Coli probiotics (symbioflor 2 e.coli probiotics, colinfant e.coli probiotics) at the top with d-ribose (a sugar used by E.Coli). This is then followed by the earth based probiotics( General Biotics Equilibrium, Prescript Assist (Original Formula), Prescript Assist (2018 Formula)).

These suggestions agrees with the top KEGG suggestions (despite being calculated in a totally different way — one set used Genomics and one set used Clinical Trials)

The rest of the to take probiotics mainly fall into 3 groups: Saccharomyces boulardii (probiotics) bacillus (probiotics), bifidobacterium with bacillus coagulans (probiotics) being the top of this set. As is typical, lactobacillus is usually a negative.

Going over to vitamins, the strongest take is Ferric citrate. We have almost all of the B-vitamins being strong avoid — this is contrary to the conventional treatment wisdom which says vitamin B helps ME/CFS. I discuss this in a prior post and speculate that the reason that Vitamin B is low in blood test ME/CFS is that part of the microbiome dysfunction are bacteria that are greedy for vitamin B, hence it does not get to the body. Conceptually this speculation is testable with a lab reactor using the microbiome from a ME/CFS person.

Bottom Line

“This is too complicated” is what I can hear some people saying. This analysis digs into the nature of the data which is really not needed for most people. It is likely of interest to those treating microbiome dysfunctions as it illustrates many of the challenges in interpreting.

For most people, the process stays the same:

• Upload the data
• Try several different ways of generating suggestions
• Look at the consensus

Why is consensus important? Simple, we have very incomplete data and also have limited accuracy with the microbiome tests. Going the consensus approach is similar to using a Monte Carlo Simulation, an appropriate approach to deal with complex processes with many parameters that are fuzzy.