Technical Note: Microbiome Analysis is Fuzzier than a Peach with Mold!!

This is a post in this series !Technical Notes on Microbiome Analysis

The Question

A reader forwarded this study to me:

Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences [2018]

While this paper is dealing with fungi the tables can be eye opening for some people. A suitable quote from the paper “When the accuracy of genus predictions was averaged over a representative range of identities with the reference database (100%, 99%, 97%, 95% and 90%), all tested methods had ≤50% accuracy on the currently-popular V4 region of 16S rRNA.

My expertise is in statistics, operational research and artificial intelligence, with good expertise in reading medical studies; so I asked a colleague who has a Ph.D. in Molecular Genetics. His casual comments were:

There are several studies with ASVs out there. Especially the recent ones. Clustering pipeline is what matters here. But I agree that full length gives better taxonomic assignment.
Problem is full length is twice as expensive. So my point is when using V4, you will achieve incredibly better taxonomic assignments with ASV vs OTU. However, full length or V3-V5 gives a better resolution.

He also shared this graphic from Zymo Research. The V4 often cost around $50 and the full length can be 3-4x more.

What is ASV?

  • ASV stands for amplicon sequence variants.
  • OTU stands for operational taxonomic units

ChatGPT gives a good common man explanation:


Both methods aim to characterize and quantify the diversity of microorganisms in a given sample, but they differ in their underlying algorithms and conceptual frameworks.

  1. Amplicon Sequence Variants (ASVs):
    • ASVs are derived from high-throughput sequencing data by clustering sequences that differ by as little as a single nucleotide. This means that ASVs are defined at a very fine level of sequence resolution.
    • The goal of ASVs is to represent individual unique sequences within a dataset, thereby capturing the most detailed information about the microbial community present in a sample.
    • ASVs are typically generated using algorithms like DADA2 (Divisive Amplicon Denoising Algorithm 2), which infer exact sequence variants and correct sequencing errors.
    • ASVs are considered more accurate in capturing true biological diversity but may be more sensitive to sequencing errors.
  2. Operational Taxonomic Units (OTUs):
    • OTUs are clusters of similar sequences that are defined based on a chosen sequence similarity threshold (commonly 97% similarity for bacterial 16S rRNA gene sequences).
    • The 97% similarity threshold is often used to group sequences into OTUs to approximate the species level, although this can vary depending on the marker gene and research goals.
    • OTUs are generated using methods such as UCLUST, UPARSE, or others that involve sequence clustering. The resulting OTUs represent a consensus sequence for each cluster.
    • OTUs are considered more tolerant to sequencing errors, but they may group together closely related species or strains into the same cluster.

In summary, the main difference lies in the level of sequence resolution. ASVs aim for the highest possible resolution by identifying unique sequences, while OTUs represent clusters of similar sequences based on a chosen threshold. The choice between ASVs and OTUs depends on the specific research goals, the desired level of taxonomic resolution, and considerations related to sequencing error handling and computational resources.


To translate into human terms: ASV identifies criminals by fingerprints or DNA, while OTU identifies by the image from a security camera.

A Dilemma for Direct-To-Retail Tests

My colleague words makes the points clearly: Problem is full length is twice as expensive. Consumers are not knowledgeable about the differences but are very cost aware. The cheapest and least reliable way is often the norm. A direct to retail test costing less than $400 is likely to use the more inaccurate processes.

A Dilemma for Data from Studies

We encounter the same issue often for studies, budget! Searching the US National Library of Medicine for ASV, I get 2,955 results

Searching the US National Library of Medicine for OTU, I get 9,180 results. We also see that ASV is replacing OTU starting around 2021.

This means that many studies published before 2021 may have correctly identified the bacteria impacted as little as 50% of the time. So, does Barley increases or decreases Bifidobacterium?

In addition to possible confounders with selection of control and subjects in the study, we must now consider the possibility of misidentification of the bacteria. For myself and microbiome prescription’s expert system, this is not a major issue because we are using a fuzzy logic expert system. Suggestions are based on most probable given the data available.

Many medical practitioners (MDs and naturopaths) are not trained in this area and resort to a naïve deterministic approach.

Additional Suggested Literature

A comparison of bioinformatics pipelines for compositional analysis of the human gut microbiome [2023]

The differences of the same sample, Bacterial genera profile. Top 10 most abundant bacterial genera per pipeline resulted in a total of 16 unique genera.

Microbiome Analysis via OTU and ASV-Based Pipelines—A Comparative Interpretation of Ecological Data in WWTP Systems [2022]

  • Additional recent work has shown that individual pipelines themselves may be biased toward certain phyla [15,21]
  • The Illumina sequencing output reported an average quality of Q30 ≥ 81.9%.

Ranking the biases: The choice of OTUs vs. ASVs in 16S rRNA amplicon data analysis has stronger effects on diversity measures than rarefaction and OTU identity threshold [2021]

  • Based on mock communities, ASV-based approaches had a higher sensitivity in detecting the bacterial strains present, sometimes at the expense of specificity [1720]
  • OTUs detected much higher amounts of Verrucomicrobiae in the seston and sediment samples than were detected by the ASV approach. These differences are surprising given that both OTU and ASV approaches classified sequences to the same database.

Bottom Line

In dealing with microbiomes in a clinical setting, we have multiple fuzziness:

  • The actual bacteria being reported (and the amount) is not reliable (in the common sense of that word), it is probable.
  • When trying to modify the microbiome, the impact on the reported bacteria is not reliable (in the common sense of that word), it is probable.

This means using a single study has significant risk. With a diverse collections of studies and facts, then a fuzzy logic expert system results in significantly reduced risk and a higher probability of successful manipulation. It also illustrates why the Large Language Model (i.e. ChatGPT style) is very inappropriate. and likely machine learning also.

As of this writing, Microbiome Prescription has 10,390 Citations from US National Library of Medicine resulting in 2,415,340 facts in it’s expert system.

Anticholinergic items should avoid taking if over 70 or with brain fog

A reader contacted me because she was concerned about cognitive issues after she started Dramamine. It is a microbiome modifier.

IMHO Brain Fog should be a condition that should result in de-prescribing or stopping any of the following.

From healthline, we have the following list

Over the counter anticholinergics

  • diphenhydramine (Benadryl, Tylenol PM, Advil PM, Unisom SleepGels)
  • brompheniramine (Dimetapp)
  • dimenhydrinate (Dramamine)
  • doxylamine (Unisom SleepTabs)

Prescription anticholinergics

  • atropine (Atropen)
  • belladonna alkaloids
  • benztropine mesylate (Cogentin)
  • clidinium
  • cyclopentolate (Cyclogyl)
  • darifenacin (Enablex)
  • dicylomine
  • fesoterodine (Toviaz)
  • flavoxate (Urispas)
  • glycopyrrolate
  • homatropine hydrobromide
  • hyoscyamine (Levsinex)
  • ipratropium (Atrovent)
  • orphenadrine
  • oxybutynin (Ditropan XL)
  • propantheline (Pro-banthine)
  • scopolamine
  • methscopolamine
  • solifenacin (VESIcare)
  • tiotropium (Spiriva)
  • tolterodine (Detrol)
  • trihexphenidyl
  • trospium

For more, from Drugs.com: Anticholinergic Drugs to Avoid in the Elderly

Some Literature

The amount of literature is HUGE, I will just cite back to September 2023….

Which Bacteria may be causing the Cognitive Declines?

Many of the drugs above are in the Microbiome Prescription database. Many of them impacts the same bacteria [ DECREASING] — implying that the cognitive loss may be connected with microbiome alteration.

The obvious way to improve recovery appears to be the following probiotics:

In Common Across DrugsBacteria
19Enterobacteriaceae
18Escherichia
18Escherichia coli
18Kluyvera
18Streptococcaceae
18Streptococcus
18Streptococcus parasanguinis
17Akkermansia
17Akkermansia muciniphila
17Bacteroidaceae
17Bacteroides
17Bacteroides caccae
17Bacteroides fragilis
17Bacteroides ovatus
17Bacteroides thetaiotaomicron
17Bacteroides uniformis
17Bacteroides xylanisolvens
17Bifidobacteriaceae
17Bifidobacterium
17Bifidobacterium adolescentis
17Bifidobacterium longum
17Bilophila
17Bilophila wadsworthia
17Blautia
17Clostridiaceae
17Clostridioides
17Clostridioides difficile
17Clostridium
17Collinsella
17Collinsella aerofaciens
17Coprococcus
17Coriobacteriaceae
17Desulfovibrionaceae
17Dorea
17Dorea formicigenerans
17Eggerthella
17Eggerthella lenta
17Eubacteriaceae
17Eubacterium
17Fusobacteriaceae
17Fusobacterium
17Fusobacterium nucleatum
17Lachnospiraceae
17Lacticaseibacillus paracasei
17Lactobacillus
17Lactobacillus casei group
17Odoribacter
17Odoribacter splanchnicus
17Parabacteroides
17Parabacteroides distasonis
17Parabacteroides merdae
17Peptoclostridium
17Peptostreptococcaceae
17Phocaeicola vulgatus
17Porphyromonadaceae
17Prevotella
17Prevotellaceae
17Roseburia
17Roseburia hominis
17Roseburia intestinalis
17Ruminococcaceae
17Ruminococcus
17Streptococcus salivarius
17Veillonella
17Veillonella parvula
17Veillonellaceae
17Verrucomicrobiaceae

Post Script:

A comment on this post wrote “I take Huperzine A and always wonder if that helps me out a little. (I can’t take any of those strong central anticholinergics anyway though!)“.

Huperzine A, the active ingredient derived from the traditional Chinese herb, is an efficacious, selective, and reversible acetylcholinesterase inhibitor (AChEI) 

So, does it impact cognitive issues in these groups? There is no clear evidence (mixed results in most reviews)

What is the best diet in your opinion?

This is a repost of a post from 6 years ago.

To this I should add, the goal is to disrupt dysbiosis.  Keeping the same items allows the dysbiosis to adapt. So, Keto for no more than 6 weeks, gluten free (if you tolerate gluten) for no more than 6 weeks, etc. Sticking religiously to a “cure-all diet” rarely ends well.

Once the dysbiosis is resolved, then the approach below should be considered.


I have been asked this often. My answer is extremely logical but not what you will get from most health experts (and unfortunately, may not be easy to determine for some).

The Diet….

Very simple — the type of diet that your ancestors ate 300+ years ago! Diet changes gene expression, i.e. microbiome AND dna adapts.

Last year, researchers discovered that these kinds of environmental genetic changes can be passed down for a whopping 14 generations in an animal – the largest span ever observed in a creature, in this case being a dynasty of C. elegans nematodes (roundworms)…. Usually, environmental changes to genetic expression only last a few generations.
…  studies have shown that both the children and grandchildren of women who survived the Dutch famine of 1944-45 were found to have increased glucose intolerance in adulthood.Scientists Have Observed Epigenetic Memories Being Passed Down For 14 Generations

From a post that I did three years ago:

Some nuggets that I found in a Christmas Present…

My wife gave me “Danish Cookbooks” by Carol Gold. This is NOT a cook book, but rather an academic study of cookbooks published in Denmark.  I’m 100% Danish and very interested in history.

I have always been inclined towards going for ancestral diet patterns, and did Paleo for a while. My problem with Paleo is that it is more idealogical based than actual (scientific) archeologically based. It is also trying to jump the diet back thousands of years which effectively ignores how our bacteria evolved to meet our changes of diet.

A diet based on typical diet of your ancestors 400 – 1400 years ago is likely a better choice. You avoid the newly introduced foods, for example, potatoes. You also avoid process foods and modern additives. On the plus side, your gut bacteria is likely closer to the optimized bacteria your ancestors evolved from eating the same food for a thousand years.

In this book, I found two gems from the historical records:

  • We have decreased the use of spice considerably — in 1600, the common spices were:
    • cumin, anise, coriander, dill, fennel, lavender, sage, rosemary, mint, bay leaves, cloves, pepper, saffron, thyme, marjoram, nutmeg, cardamon, ginger, cinnamon, hyssop, wormwood, lemon balm, angelica-root.
    • “The issue here is … the use of seasonings in general slackens” p.47
    • Many of these spices (like wormwood and ginger) have strong antibacterial characteristics which would have kept some gut bacteria families in control well.
  • “Their most common food was meat” p. 122
  • White (wheat) bread was very uncommon, expensive, and typically seen only in upper class homes on special occasions(not as part of the regular menus). It appears that most of the carbohydrates came from Rye Bread.

I am sure that some readers who favor a diet that is vegan or vegetarian on ideological grounds would object to these suggestions.  My response is simple, if your ancestors were vegetarians for centuries or millenniums (as some friends who were born in India can validly claim), then that is the right diet without any doubts.

Evidence shows that gut bacteria is inherited through generations — hence it is good to know what your ancestors ate because your gut bacteria have likely adapted to that diet. Given my heritage (which likely applies to people from the UK, Poland, northern France and Germany etc), this boils down to:

  • Rye Bread without any wheat flour
  • Meat and Fish (especially since the family seemed to always been within 5 miles of the coast back to 1500..)
  • Vegetables:

No potatoes — they really did not enter my ancestor dies until the early 1800’s – after one of my great-grandfathers was born. Little or no sugar (“Worldwide through the end of the medieval period, sugar was very expensive[1] and was considered a “fine spice“,[2] but from about the year 1500, technological improvements and New World sources began turning it into a much cheaper bulk commodity.” – Wikipedia)

This Wikipedia article may be a helpful start for many.

The last item needs to be taken with a touch of salt and sung: “A spoonful of soil helps the microbiome recover!” We have become hyper-hygienic. See the Hygiene hypothesis. This comes from a post in 2016:

“The Amish and Hutterites are U.S. agricultural populations whose lifestyles are remarkably similar in many respects but whose farming practices, in particular, are distinct; the former follow traditional farming practices whereas the latter use industrialized farming practices….Despite the similar genetic ancestries and lifestyles of Amish and Hutterite children, the prevalence of asthma and allergic sensitization was 4 and 6 times as low in the Amish” – i.e. industrialized farming practices resulted in six times (600%) the rate of asthma and allergies. See Innate Immunity and Asthma Risk in Amish and Hutterite Farm Children(2016). This is also echoed in their farm products!!! Amish and Hutterite Environmental Farm Products Have Opposite Effects on Experimental Models of Asthma [2016]. Given a choice of buying groceries from a Hutterite farm or a Amish farm, buy the Amish (non industrialized) groceries!!!!

So I advocate not a Paleo diet, but a regional medieval-food diet (modified for modern nutritional needs). No prepared foods (talk about being extremely unnatural!), so food prepared from scratch — ideally organic with heritage seeds.

ME/CFS Continues Improvement + Lab Read Quality Issues

Prior Posts

Analysis

A summary of his seven results are below. The Lab Read Quality bounces around, and with that, other values may echo these shifts (i.e. up to 20% shifts for some measures). A low read quality means less bacteria are reported, for example, when it was low, the Outside Kaltoft-Moldrup has low, when it was high, the value became high.

Another way to view it is this: If 10% are out of range and 400 are reported then we have 40. If we have 660 in another report then we would expect 66. This could be misread as a 66/40 or a 65% increase in out of range bacteria when the same percentage is out of range. Technically, it is more complicated but that should explain the problem.

Looking only at high read quality ( 1/22/2024, 2/22/2023, 8/31/2021) we see improvements where there are 🙂 below. This is an unfortunate aspect of 16s tests.

I have added at the bottom Forecast Symptoms compared to actual.

Criteria1/22/20249/12/20232/22/20238/11/20223/25/202212/3/20218/31/2021
Eubiosis56.41003710010068.167.4
Lab Read Quality7.93.59.75.56.23.67.8
Outside Range from GanzImmun Diagostics16161515171720
Outside Range from JasonH7777446
Outside Range from Lab Teletest20 🙂202424222225
Outside Range from Medivere16161515151519
Outside Range from Metagenomics7799778
Outside Range from Microba Co-Biome2277111
Outside Range from MyBioma5 🙂577778
Outside Range from Nirvana/CosmosId20202323181821
Outside Range from Thorne (20/80%ile)198 🙂198223223217217246
Outside Range from XenoGene24 🙂243232363639
Outside Lab Range (+/- 1.96SD)5 🙂1510119914
Outside Box-Plot-Whiskers54564236425942
Outside Kaltoft-Moldrup123 🙂70139567859140
Bacteria Reported By Lab511399666478613456572
Bacteria Over 90%ile20 🙂542624265746
Bacteria Under 10%ile108418248442999
Shannon Diversity Index1.3681.181.0381.2871.5610.8950.903
Simpson Diversity Index0.1150.0630.050.0420.0580.0220.02
Chao1 Index760350571253480531323455639209
Pathogens26 🙂253023392430
Condition Est. Over 90%ile0000000
Actual Symptoms in top 10 Forecasted581088109
Max Forecast Symptom Factor38.522.325.316.915.826.433.1

Explaining the new Symptom Forecast Algorithm

This algorithm is similar to the Eubiosis algorithm. We compute the expected number of matches to bacteria shifts associated with the symptoms. The expected theoretical threshold by randomness is 16%. A higher number indicate increased odds, a lower number decreased odds. This is based on the existing annotated samples uploaded. It is not definitive and often there can be multiple subsets of bacteria associated with a symptom. The match is on too much or too few of a collection of bacteria

The checkmarks are the entered symptoms, the list are the predictions from most likely to lesser.

This data actually clarifies that the ideal 16+ for a factor is dependent on the Lab Read Quality and that 16 may apply to shotgun results but for 16s results, some flexibility with the 16 is warranted.

As a general FYI, hitting 80-100% correct prediction of symptoms implies that the algorithm performs well and the change of algorithm was appropriate.

It also implies that we are successfully identifying the bacteria associated with the symptoms..

The drop of matches with this sample is difficult to clearly interpret. It was not intended to be an indicator but a tool to correctly identify the bacteria of concern. Getting suggestions solely from the symptoms have been added. See the video below.

Going Forward

Again, using Just give me suggestions include Symptoms is how we are going to proceed. And then add in the two Special Studies. This results in 7 packages of suggestions.

Thresholds: High is 524 thus 260 or higher, Low is -346 this -170 or lower

For our first pass, we are going to look items that all 7 agrees upon, the list is very short

The two take list is very short. Prescription items dominates the list with metronidazole (antibiotic)s[CFS] at 524(the TOP), followed by amoxicillin (antibiotic)s[CFS], ciprofloxacin (antibiotic)s[CFS]. The top NOT-PRESCRIPTION is 232, so we will drop the threshold to 116

The avoid list is much bigger

For myself, I would try to obtain and rotate the antibiotics listed above and use Splenda where practical.

Bottom Line

This analysis has been both challenging and informative. We see that 16s Lab Read Quality can confuse analysis because it will alter many measures significantly. Care must be taken when comparing two or more samples with different Read Quality. Additionally, having the top suggestions full of prescription items means that we needed to adjust the threshold based on the top non-prescription item.

On the positive side, we see that the revised symptom forecasts appear to perform well, actually better than I was expecting.

Postscript – 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 result 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.

The answers above describe my logic and thinking and is not intended to give advice to this person or anyone. Always review with your knowledgeable medical professional.

A Youth’s Microbiome with Marfan

This is the son of a person with issues: Bad Diet and Antibiotics? ME/CFS like symptoms. As I have often cautioned, young people’s and children’s microbiomes are different than adults and we do not have appropriate reference ranges. We will do best efforts.

  • Tired all the time
  • Cannot gain weight (very skinny)
  • Diagnosed with Marfan syndrome (a genetic disease he has since birth)
    [editor] About 1 in 5,000 people have Marfan syndrome
  • Stomach pain
  • Disgestion issues (yellow stool and fat in stool)
  • Joint and Muscle pain
  • Dark circles around the eyes

Analysis

There is no available literature on microbiome shifts with Marfan syndrome. Marfan syndrome (MFS) results from heterozygous mutations in the fibrillin-1 gene (FBN1; OMIM #134797), located on chromosome 15 at band q21. 1 (15q21. 1), which encodes for the glycoprotein fibrillin. [MedScape]. Coagulation plays a major role in Marfan syndrome. Both procoagulation and bleeding disorders participate in the disease. Platelet function abnormalities, compatible with von Willebrand syndrome or congenital thrombocytopathies, have been identified in 29% of patients. [2014].

 FBN1 is the causative gene for Marfan syndrome, an inherited disorder of connective tissue whose major features include tall stature and arachnodactyly, ectopia lentis, and thoracic aortic aneurysm and dissection. More than one thousand individual mutations in FBN1 are associated with Marfan syndrome, making genotype-phenotype correlations difficult. [2016]

At a high level we see potential issues. [NOTE: The Eubiosis value changed for many people after a defect was detected in how percentile was computed for some bacteria – often 100% dropped, which how agrees with people symptoms ].

However, there were no statistically significant matches (this page was just updated to use the latest algorithm). This algorithm is similar to the Eubiosis algorithm. We compute the expected number of matches to bacteria shifts associated with the symptoms. The expected number by randomness is 16%. A higher number indicate increased odds, a lower number decreased odds. This is based on the existing annotated samples uploaded data. It is not definitive and often there can be multiple subsets of bacteria associated with a symptom. The match is on too much or too few of a collection of bacteria associated to symptoms.

We will still check the matching symptoms. The top one is a match for symptoms but not a match for the typical bacteria seen for this symptom. We have to hope that there is sufficient matches to be worth while.

First, looking at all of the common, popular measuring sticks –

  • General Health Predictors has a low number (just 8) with only one of possible concern: Veillonella atypica 
  • All of the usual ratios are between 20%ile and 80%ile
  • Anti inflammatory Bacteria Score is at 89%ile — very good
  • No Potential Medical Conditions Detected detected
  • Histamine issues are a potential health issue
  • Bacteria deemed Unhealthy: Bacteroides fragilis and Parabacteroides merdae are the only one, both are potentially infectious bacteria.
  • Dr. Jason Hawrelak Recommended Levels came in at 94%ile

So, everything looks like a reasonably healthy person.

Going Forward

With no clear issue associations, we are going to do two runs: One with symptoms and one without.. Using the standard ‘Just give me Suggestions’ The list below are for the items at a priority of 50% or more of the highest priority [506] [Symptoms: 440]. This limit has no rationale apart from reducing the volume of suggestions.

Suggestions

Let us look at AVOIDS, given the general healthy state, just try reducing if taking,

At this point, I attempted to do cross validation: Are there any literature of items suggested (or avoid) on improving Marfan syndrome. This is done to test the suggestions – for other conditions with lots of literature, we have usually seen 90-95% agreement. For ME/CFS, I know the literature well — for this condition, not. I found only symptom treatment (Mayo, NHS). Since this is a DNA condition and I know DNA can influence the microbiome (and the reverse), then trying to improve towards typical this youth’s microbiome is a reasonable (and low risk) approach.

Because of the platelet function abnormalities that could be present, as well as thick blood (procoagulation) — both areas that I am familiar with from ME/CFS. I checked suggestions for possible items that could be related to coagulation:

Questions and Answers

Q: Do you know why it suggest gluten Free diet? Could he have gluten intolerence/celiac maybe?

  • The why is because of that type of diet impacts on bacteria that are off balance. We cannot detect  gluten intolerance/celiac. Only the impact of that type of diet on different bacteria. Some source papers to illustrate:

Bottom Line

The thing that strikes me most about the suggestions, the items to avoid are prebiotics and probiotics; the opposite of common advice for anyone with health issue, especially digestive issues. There are no studies on PubMed for probiotics and this condition which infers to me (given the popularity of trying probiotics) that there were studies with no effect or negative effect. In the sparse literature, we did have one of the take suggestions computing matching the literature.

If this was my own child, I would likely follow the items in suggestions above. There is low risk in following them and one suggestion does cross-validate with the available literature (which has almost nothing published in this area).

I work off the axiom that a disease or conditions modifies the microbiome to be favorable to the condition. Undoing those shifts have a reasonable change of slowing, and in some cases, reversing the condition. I have had antidotal reports of this approach speeding cancer treatment.

Postscript – 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 result 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.

The answers above describe my logic and thinking and is not intended to give advice to this person or anyone. Always review with your knowledgeable medical professional.

ME/CFS + 3 times COVID + food poisoning

This is part of a continuing series of analysis for ME/CFS or/and Long COVID.

Background

I am contacting you as you may provide a microbiome analysis for you has cfs – long Covid 19.
I have been struggling for years with cfs-me. I also have Covid 3 times (the last one was in December 2023). When I did the test, I just had few days before a food poisoning that led me to ER.
I did a GI map last year because I wanted to have more information after failing to cure a methane SIBO with herbs. I have a very bad infection (enterohemorrhagic e choli).
I was suggested by the functional doctor whom I ordered the test some thyme and probiotics but obviously it had no impact. I redid a stool test (biomesight) but I am really overwhelmed by the results.

Would you mind give me some insight on those tests ?

  • joint pain, neck pain, TMJ, migraines
  • hypothyroidy, insulin resistance, low cortisol,
  • possibly Lyme (low nk57 but negative test)
  • possibly mold intoxication 
  • heavy metal intoxication 
  • brain fog
  • Attention-Deficit/Hyperactivity Disorder (ADHD)
  • skin issues on the face and eczema on my hand 

Analysis

We have some dysbiosis (i.e. Eubiosis is not 100).

Looking at reported symptoms, we see a number of matches to reported symptoms over 16%ile, with one of the unchecked,  inability to focus eye/vision , being a potential missed item. There are 67 symptoms entered with 58 of them above 16% (the threshold)

Explaining the new Algorithm

This algorithm is similar to the Eubiosis algorithm. We compute the expected number of matches to bacteria shifts associated with the symptoms. The expected number by randomness is 16%. A higher number indicate increased odds, a lower number decreased odds. This is based on the existing annotated samples uploaded. It is not definitive and often there can be multiple subsets of bacteria associated with a symptom. The match is on too much or too few of a collection of bacteria

Looking at Health Indicators

  • General Health Predictors: 11 items, with Veillonella atypica being the greatest concern
  • Potential Medical Conditions Detected: None. I double checked, and there were no significant matches.
  • Dr. Jason Hawrelak Recommendations: 94%ile

Going Forward

Doing just give me suggestion with symptoms gives the following suggestions for items to add (50% of 516 or hgh

The Avoid List

The lowest value was -550, so items below -275 should be the highest priority.

Comparing to Suggestions from GIMAP

The data transcribed is below. Our consensus report above picked 67 bacteria of concern

As expected (See this post) there was agreement and disagreements between these reports on what is high or low, and some agreements. For example,  Faecalibacterium prausnitzii was at the 81%ile on Biomesight data and very low above.

Suggestions will always be different because of the much smaller set of bacteria being used. We do note the following agreement in suggestions:

Many suggestions are not found at all in the GIMap suggestions because there is no literature for those substances and the bacteria reported.

Questions and Answers

Q: Would you have any specific recommendations about enterohemorrhagic e coli (ehec) ?

Q: Another question about the antibiotics protocol for me/cfs (in case I succeed to convince my GP). Dr Jardin suggests : 1 week on with one antibiotics then 3 weeks off, then another cycle with another antibiotics. Is it right ? 

  • Correct for Jadin.  One week on and 3 weeks off… and then change antibiotics.  This comes from old clinical experience at the Pasteur Institute.  I have read studies dealing with sewage plants that found this pattern works better.

Q: On your blog, it also says to pick one of the 4 suggestions of supplements and switch every week during 8 weeks and retest. Does it mean I must choose 4 supplements, take 1 supplement during 1 week then switch to another 8 times and so on. Am I right ? (I am not English fluent so I struggle a little to understand everything)

  • 4 SETS of supplements…. so each week you change sets.  This again is suggested to prevent dysbiosis adapting. I have too often heard “It works for 3 months and then stopped working” . As an analogy, think of cops setting up cameras to stop people speeding, their existence improves traffic — but once people learn that they are always at the same place … bad behavior returns.

Q: Last question : could symbioflor1 help for my enterrococcus faecalis overgrowth? Or is it the opposite?

  • There is nothing that I could find for  symbioflor1 impact on enterrococcus faecalis overgrowth in the 13 studies I have processed. So we are again into the “fuzzy knowledge area”, in general (especially the EU), probiotics are not troubles strains and thus can be used to shift related bacteria.
  • From https://link.springer.com/article/10.1007/s11259-024-10324-0, we see that it is hard to treat. BUT Curcumin is better than 2 antibiotics tested.

Postscript – 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.

The answers above describe my logic and thinking and is not intended to give advice to this person or any one. Always review with your knowledgeable medical professional.

Fifth Analysis of IBS/Long COVID/ME/CFS

We have a varied history with some storms blowing us off courses. Here’s a list of the tests and prior blog posts:

This is one of two set of ongoing samples from readers that “have appeared to almost stalled”. The other reader sent me this note at the same time (and another sample) “I have to say, symptoms are pretty dead on accurate to what I’m experiencing like all but one box. PEM is my highest ,”

This implies strongly that the association between symptoms and bacteria shifts are strong. The microbiome is just stubborn.

Feedback

He has 49 different symptoms checked and unusually, have a friendly MD in terms of antibiotics.

I would say some small subjective improvements since last time, but no major changes. Also I increased squats from 14 to 15 and push-ups from 9 to 10 at the time of the sample. (I also increased walking distance a little, but only after the sample was taken. I probably could have increased them by more, but I wanted to start really slowly with increasing those things.)

Between the last test and this sample, Amoxicillin was the only antibiotic I did. I also did some of the top herbs and probiotics (B. infantis, Mutaflor and L. Kefiri).

Also anxiety is a bit of a problem, but only sometimes, not every day. I’m not really sure what the cause is. I think it might be connected with winter, cold, rarely seeing the sun, maybe piracetame, people around me coming to me with suggestions on what I should do, maybe noise. (Noise has been a problem for me since the beginning of CFS. I really can’t endure noise well.) But those all don’t have to be the cause, they can also just be triggers or be connected to it. (Eating might also be connected to it. It seems to me that on the days I eat bacon for breakfast and a large portion of potatoes and beef for lunch (like once a week), it is better. On the days I eat sth. made from corn flour for breakfast (like every four days), it is worse. But I cannot eat the same things multiple days in a row because I quickly develop food intolerances if I do that, so I have to eat alternating things that I tolerate.) I am just wondering whether something can be done to help with that (anxiety).

Analysis

The eubiosis index is a recent addition and I am curious on how it behaves compared to other measures. Having a magic number to indicate health is an ideological goal, my gut feeling is that there is no such magic — rather many aspects need to be examined.

SampleEubiosis (balanced) gut.Unhealthy Bacteria
2021-11-1899.68
2022-05-2048.512
2023-06-2238.512
2023-09-0410012
2023-11-2310012

The traditional analysis

Criteria11/23/20239/4/20236/22/20235/20/202211/18/2021
Lab Read Quality5.44.77.28.15.5
Outside Range from GanzImmun Diagostics1211111515
Outside Ran ge from JasonH79966
Outside Range from Lab Teletest2522222020
Outside Range from Medivere1115151616
Outside Range from Metagenomics87799
Outside Range from Microba Co-Biome33311
Outside Range from MyBioma66655
Outside Range from Nirvana/CosmosId2223232020
Outside Range from Thorne (20/80%ile)235241241231231
Outside Range from XenoGene3335352929
Outside Lab Range (+/- 1.96SD)2 🙂21786
Outside Box-Plot-Whiskers31 🙂58423769
Outside Kaltoft-Moldrup47 🙂51929448
Bacteria Reported By Lab508568582674527
Bacteria Over 90%ile17 🙂41243852
Bacteria Under 10%ile835014717736
Shannon Diversity Index1.591.2721.5561.8531.826
Simpson Diversity Index0.0470.0870.090.0560.038
Chao1 Index6986100619016147447390
Shannon Diversity Percentile43.812.74081.878.2
Simpson Diversity Percentile45.377.578.654.833.6
Chao1 Percentile2548.941.479.427.8
Pathogens2223293220
Condition Est. Over 90%ile50934

At first look, there seem to be little change. Looking at specific items, there is improvement (highlighted in red above), namely less bacteria with extremes levels. For all of the reference ranges from 3rd party labs, there is no effective change.

Going Forward

Since symptoms were also entered, we proceeded with [Just give me Suggestions Include Symptoms]. The results surprised me a little; the top items were CFS antibiotics and whole-grain barley (likely a proxy for beta glucan — see this post: Beta-Glucan: The Microbiome Fixer; ß-glucan is on the to take list). The following was sorted by Take Count descending (which means that all five sets agreed)

Personally, given the slow progress, I would be inclined to try talking a medical professional into prescribing one of these.

Let us do the usual breakdown by types, most are below 1/2 of the highest value.

Further analysis

I did a second run, but excluded symptoms, there was no significant shifts. The top items were the same but other antibiotics shifted position.

From the early draft, this reader responded with more information:

  • He has started nicotine patches which has a significant positive score of 113

I used the ability to do a double sort (Descending Take Count, Descending Priority) to get a double conservative list.

Tudca is Tauroursodeoxycholic Acid and available as a supplement. Based on this clinical study: Safety, Efficacy and Pharmacokinetics of Doxycycline Plus Tauroursodeoxycholic Acid in Transthyretin Amyloidosis, I would suggest that it be taken concurrently with the metronidazole. There are 34 clinical studies using it. It is interesting that metformin (a diabetes drug) is suggested at the same time we see avoid all natural sugars in our suggestions – there is an interesting symmetry here. Teicoplanin is also interesting and very suitable (literature here). Literature for Ceforanide is here.

My prescription model to be discussed with the MD would be:

  • Week 1:A course of metronidazole with Tudca
  • Week 2-4: metformin (possibly with Tudca)
  • Week 5: Teicoplanin with Tudca
  • Week 6-8: metformin (possibly with Tudca)
  • At end of week 8 do another sample
  • Week 9: Ceforanide with Tudca
  • Week 10- new report: metformin (possibly with Tudca)

Barley porridge and similar alternating with beta-glucan supplements (since food sensitivities appear to develop quickly). Perhaps consider a diabetes-like diet (to keep the natural sugars low).

For Tudca, we read about some possible adverse effects in this paper Pharmacokinetics, Safety, and Tolerability of Orally Administered Ursodeoxycholic Acid in Patients With Parkinson’s Disease—A Pilot Study [2021] namely ” gastrointestinal discomfort, rated by subjects as mild to moderate“. It has a half-life of 2.1 ± 0.71 hr, so taking 4 staggered 500mg dosages per day should be considered.

Speculation: monitoring blood glucose levels (like what diabetics do) may be a waste or time OR may provide insight. I have a smart watch that monitors blood glucose ($30 from Banggoods to Temu). There are also more professional monitors.

Question:  I ate cornflour for breakfast, which I wrote about in my first mail. On those days anxiety is worse

Large Language Model vs Expert Systems for Medicine and the Microbiome

I tried out a new medical Large Language Model (LLM) API, https://www.drgupta.ai/ to see what it would suggest for a simple microbiome shift compared to what the Expert System(ES) (NOT LLM) AI system does on microbiome prescription. The first significant one Expert System for Medicine was called MYCIN and was written by Stanford University in 1972.

The main business differences between LLM and ES are costs. LLM run heavy computer costs, ES runs heavy human costs. An ES often require article by article review with suitably skilled reader (or example, a grad student). LLM are easy targets for getting venture capital funds — often based on pie-in-the-sky beliefs of how easy it would be to do that is sold to venture capitalists. Earlier I had several sessions with folks at the The Allen Institute for Artificial Intelligence exploring machine analysis of the literature. Their conclusion was that existing AI is still incapable of good analysis of medical and clinical studies.

LLM Report

I tossed a simple, three taxa problem at the API. Reality is that typically we are seeing 40-80 taxa of interest.

Expert System Response

Compared to:

We do not have vague “probiotics” but provide their specific names and dosages. We also include probiotics to avoid.

With information on suggested dosage for probiotics with links to sources.

As well as the names and links to studies used to make these suggestions.


Nothing in the LLM indicates that Pectobacteriaceae was considered. The Expert system does consider it:

And provide background

Bottom Line

This post intent was to contrast the difference between LLM and ES systems. Both can have data entry/text interpretation issues. With a suitable ES system, the suggestions can be audited and issues addressed. With LLM, this does not seem to be available with common code bases.

The table below from PubMedQA shows that accuracy is barely over 80% for the best models out there. Expert systems can exceed 95%. Is 80% “good enough” for treating patients especially if the ability to audit the logic is missing? By Audit, I mean provide links to all source studies).

A follow up ME/CFS Analysis

This is a follow up on the prior post below. The reader’s comments are “I am feeling much better but still very fatigued and lately been quite achey.  The recommendations have changed significantly except for whole grain barley.”

For more analysis see: Analysis Posts on Long COVID and ME/CFS

Comparison of Samples

Let us first do the simple numbers. A lot of values are the same (typical) but many of them show improvement. 😃 indicate significant reduction is out of range values See Technical Note: Lab Quality Versus Bacteria Reported We would expect a 15% drop from lower lab quality, the drops shown are well below that).

CriteriaCurrent SampleOld Sample
Eubiosis Index62.8%😃59%
Lab Read Quality4.38.4
Outside Range from JasonH88
Outside Range from Medivere2020
Outside Range from Metagenomics1010
Outside Range from MyBioma88
Outside Range from Nirvana/CosmosId1818
Outside Range from XenoGene4242
Outside Lab Range (+/- 1.96SD)9😃16
Outside Box-Plot-Whiskers38😃98
Outside Kaltoft-Moldrup56😃139
Bacteria Reported By Lab494752
Bacteria Over 90%ile20😃82
Bacteria Under 10%ile66😃232
Shannon Diversity Index1.4651.701
Simpson Diversity Index0.0350.028
Chao1 Index747417093
Shannon Diversity Percentile28.561.4
Simpson Diversity Percentile30.221.5
Chao1 Percentile28.987.7
Lab: BiomeSight
Pathogens18😃39
Condition Est. Over 90%ile44
Kegg Compounds Low969😃1242
Kegg Compounds High5😃23
Kegg Enzymes Low272284
Kegg Enzymes High17😃75
P or P Chi2.9999245.999999999
Percentages of Percentiles Chi2 is a proxy for severity of abnormality, it has decreased.

Health Analysis Comparisons

I have not created an automatic compare yet (on to do list). Many values were similar, some interesting ones with improvements are below. Jason Hawrelak Criteria got worse, but I have deep reservations on using his criteria on Biomesight tests (he based them on a very different test method).

RecentPrior
General Health Predictors: Flagged Bacteria8😃10
Anti inflammatory Bacteria Score14.4%ile😃13.3 %ile
Lactate (controls many bad bacteria) 📚33.1 %ile😃20 %ile
L-Lactic Acid (controls many bad bacteria) 📚47.1 %ile😃25.2 %ile
NADH (Typically low with ME/CFS) 📚📚26.5 %ile😃13.7 %ile
Hydrogen peroxide (controls many bad bacteria) 📚17.3 %ile😃5.8 %ile
D-Lactic Acid (Associated with brain fog) 📚6.5 %ile😃7.9 %ile
Potential Medical Conditions Detected2😃7
Bacteria deemed Unhealthy7😃22
Jason Hawrelak Criteria56.4 %ile75.8 %ile

Going Forward

A review of the Health Analysis was done above, with the two items: Mood Disorders and COVID-19 (a proxy for ME/CFS IMHO). A secondary review of all the items on [Changing Microbiome]/[US National Library of Medicine Studies] for high items not flagged. Nothing added.

Doing what is becoming a regular pattern: “Just give me suggestions” and then using given symptoms under Special Studies using these items:

Note: items like age and gender are omitted as well as any other symptoms that we do not have sufficient data.

First the filtered PDF suggestions. The list is much longer than usual:

And the to avoid list is more typical.

Let us go over to viewing the consensus to get some priorities


The highest value was 485 (so 240 for cutoff), lowest value was -574 ( so-287 for cutoff)

So in summary, shift a diet to low sugar, gluten free with moderation in meat (no guidance on chicken or fish). If your MD is willing, I would suggest reviewing Cecile Jadin📚 approach with antibiotics and rotate with those suggested above. IMHO Continuous on a single antibiotic is more likely to complicate the microbiome.

Postscript – 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.

The answers above describe my logic and thinking and is not intended to give advice to this person or any one. Always review with your knowledgeable medical professional.

Beware of false statements on sites: Jonas Health

A reader asked me to evaluate their offerings. Remember, I do NOT sell testing, I offer a free citizen science analysis on over 3 dozen different microbiome tests using Artificial Intelligence. One of the first thing that strikes me is false and misleading statements on some sites. The following is from Jonas Health for illustration purposes. A few are below, taken from their site in November 2023.

This is incorrect. They cannot identify ALL organisms, they can only identify the items in their reference library. For example, there are 30 new fungi species being added every year in 2004 ( Biodiversity of Fungi, 2004) and I would expect that rate to be increasing. NCBI currently lists over 2.5 million taxa. In 2012 it was just 235,000. That’s a 10 fold increase in 10 years.

It is unlikely to be “all”

Looking at their sample report we see numbers given with no scale.

As for research, we see two papers, neither titles suggests that lactose was the focus of the study. One seems focuses on Rice and oats. The article is here – the word lactose is never mentioned in the article. As this is a demo report, I would expect correctness. Also, the journal was Front Immunol. 2021; 12: 787797. and NOT Nature.

Next we see what may be correct per the sample, but no guidance on how to:

  • Increase Faecalibacterium Prausnitzii WHILE CONCURRENLTY Decreasing Faecalibacterium .

Bottom Line

Based on this sample report, I see ugly problems. Thorne Gut Testing is 40% of the cost and much more useful, especially if used with Microbiome Prescription. I attach a copy of their sample report below.