C. Jadin Resources

This is the protocol that was responsible for one of my remissions. My current belief is that what she termed “occult rickettsia infection” is “post-infection stable microbiome dysfunction”. Regardless, the treatment works in a high ( > 75%) of ME/CFS patients. The treatment was evolved prior to the microbiome entering research, using real patients over many years at the Pasteur Institute for Tropical Medicine.

A disease called fatigue by [Jadin, Cecile]

Objective: To demonstrate the probable role of intracellular bacteria like Rickettsiae and Chlamydiae in the development of certain chronic psychopathological conditions and according to the efficiency of antibiotic regimes (minocyclines and/or macrolides). The letter aim is based on the fact that all the patients that I have seen since 1981 had a sera reaction positive for Rickettsiae and/or Chlamydiae using the micro-agglutination on blade technique of P. Giroud and M.L. Giroud (MAG) by Prof. J.B. Jadin of Antwerp, Belgium with special antigens cultured on guinea pig lungs and chicken embryos. Methods: This is an open study which began in 1981 in a private medical practice, not versus placebo; but with random choice. Treatment was for a minimum of six months (minocyclines and/or macrolides together with vasodilatory medication; chloroquine; warm baths). Group one: 98 CFS cases; women: 78, men: 20; for 67 cases, the ancientness of symptoms is more than 2 years. Group two: 59 psycho-somatic cases; 5 schizophrenia; 3 borderline; 10 children with aggressivity, excitement; 1 autistic child; 1 delirium with relapses. Results: Group one: 79.5% good and very good results; 4.1% fairly good; 16.4% failed. Group two: 82.3% good and very good results; 2.5% fairly good; 15.2% failed. Conclusion: This diagnostic and therapeutic study began in 1981. All of the Dr. Bottero’s therapeutic results are confirmed since 1991 by Dr. Cecile Jadin of Randburg (South Africa) for more than 3000 CFS and other psychopathological states (300): Sydney 98 CFS Conference, Australia. We have shown that Rickettsiae and Chlamydiae are probably causative factors in many “psychopathologies.”

Journal of Chronic Fatigue Syndrome . Available from: https://www.researchgate.net/journal/1547-0660_Journal_of_Chronic_Fatigue_Syndrome [accessed Feb 22 2020].

Notes from a Patient

Located here: http://lassesen.com/documentation/

FastQ Processing Comparisons

David M. ask me about comparing results from different providers of FastQ to Taxon. I had coded it out and was unhappy with what I saw and did not post about it . I had missed a bug and while the link was there – it would error out. That bug is now fixed, and you may use it..,

Select the ones to compare — it should be the same FastQ file for all. In this case I am processing a uBiome FastQ file (so that is a choice)

Click Compare. What you see may explain my earlier post, The taxonomy nightmare before Christmas… This is the SAME DIGITAL DATA being processed thru 4 different software applications …

MicrobiomeSight did not provide taxons so a text match up was attempted (prone to errors)

Bottom Line

Standards seekers put the human microbiome in their sights, 2019

Child Autism microbiome over time – Part 3

In my last post, End Products and Autism, etc, I looked at the end product shifts seen in autism patients uploaded to my analysis site. In this post, I am going to look at the significant ones over time for this child.

The process is simple, go to compare samples, select the desired ones and click [EndProduct Time Line], as shown below.


I will do all of those reported in the post above and on the page cited.

Watchout for Normal for Age!

We are dealing with a child, and should first look at the pattern seen for children. We do not have enough samples at the moment to be able to drill down into children with autism (as stated on the page).

Similarly, we cannot drill down further into autism until we get more samples.

A fishing expedition

The end products identified are the most likely involved with autism. More probable – not a certainty. Going thru the many charts below, I noted:

  • Between Feb 14 and April 26, 2019 there was major changes visible on many charts that cascaded onwards.
  • It may have been triggered by an increase in Acetate or Lactic Acid shown on the Feb 14 sample
    • DAO and GABA jumped massively on Apr 26, dropped down but slowly increasing afterwards
    • GABA
  • Formic acid, Thiamine and Urolithins kept increasing after that

April 26th Notes: Diet: up to this date still eating mainly soups and all organic home cooked meals and healthy snacks fruit and nuts. Taking full set of recommended supplements tho experiencing nose bleeds.
Feb 14 Notes: After Sample started probiotic L.reuterei and camel milk. Stools consistency soft, solid. Diet: consisted of vegetable soups and also had introduced celery juice in the mornings.
Addendum ” we stopped for a week because I started seeing more irritability as result. ” resumed.

I would suspect that Lactobacillus Reuterei

From 8 bins and 16 bins


The data driving end-products is not as complete as I would like it (if you know of a good source of end product to taxa, please email to me!). I refer to it as experimental because of the lack of solid data. Many of the taxa reported to produce some end products are not reported on by 16s labs.

For this person, we see that Lactobacillus Reuteri appears to have triggered significant changes. “Role of Lactobacillus reuteri in Human Health and Diseases“[2018]. It would account for the increase of Lactic acid and periodic courses may be advantageous. Also with L. Reuteri, “acetate is produced at much higher concentrations 76.” 

The production of formic acid is a little concern. This does not mean you will find high levels in the body; you may find some very fat bacteria that feeds on it and it’s salts ( Formate) .

As a result, I want to identify the bacteria that is causing this. First a Visual:

Then I added a new page,

Clicking and then selecting the End Product
We see what the high producers are.. child and parent (a double count scenario)
We can see that almost every sample is sky high

Going over to Peter D’Adamo Data Punk site, we see that this bacteria inhibits a lot of things:

At this point we have several choices – we could click on Eubacteriaceae or Eubacterium and pick up items to add or remove from the menu. Instead, recall in my Child Autism microbiome over time – Part 2 post, we had a hand picked taxa. I am going to add it to that existing mixture:

Doing it on the already selected taxa
Just click the two, and click Create a custom
Our new collection of bacteria taxa that we wish to modify

We now have similar, but also different suggestions then before. The artificial intelligence engine attempts to find the optimal combination for the above bacteria

Note that we have contrary results for the species lactobacillus rhamnosus (probiotics) versus a specific strain lactobacillus rhamnosus gg (probiotics)

Explicit manipulation of end produces is beyond my comfort level. Formate is water soluble, so this may be a moot issue apart from changing pH. I will leave that speculation to medical professionals.

Bottom Line

This is my first detailed end product analysis connected to a symptom or medical. I ended up writing two more analysis page with the final results being interested. This autism child has one bacteria extremely high and because of using end products we discovered that it would end up with a high amount of formic acid altering the gut and from the literature, also see that it would alter the gut pH — causing more changes of gut bacteria. I have seen another “out of control bacteria (top 2% of values)” in another child with autism (but totally different bacteria) after a different probiotic was started. This may be just two unusual cases, but I thought that it should be mentioned.

We ended up combining several parts of this analysis into one hand picked taxa to adjust and have a good list of changes to consider in consultation with your medical professional.

P.S. One more sample result arrived and was uploaded. The predicted symptoms are matches to earlier ones. I will leave it to the mother to inspect the updated charts shown above.

The microbiome of autistic children is challenging because of several factors:

  • Medical studies (over a dozen) do not replicate each other (see Technical Study on Autism Microbiome)
  • Not many samples to work with using citizen science
  • There is a feeling of “instability”

On the positive side, by this series of post – we can make logical deductions of experiments that may be worthwhile. With regular 16s testing (always the same lab please!!!) you can actually see if something made a difference (for better or worst).

A big KUDO to the mother for keeping detailed daily detail notes and granting permission to use the child’s microbiome results.

Feed Back

I feel I got to keep thanking you for all your observations regarding the data. These give me huge clues in which I can find more bread crumbs in how to better help my daughter.

In you 3rd part of your observations on end products you mentioned that Formic acid was increasing, so from studies that is linked to inflammation in the large colon and increase in bad bacteria.  But I also found an interesting study that indicates the following:

“ This study was conducted to explore the in vitrofermentation characteristics for different ratios of soluble to insolubledietary fiber in pig fecal microbiota. The fermentation substrates consistedof inulin and a non-starch polysaccharide mixture and were divided intofive groups according to different soluble dietary fiber (SDF) to insolubledietary fiber (IDF) ratios (SDF 25, 50, 75, and 100%). With the increasedSDF ratio, the total gas production increased, and the pH in the substratedecreased as the fermentation proceeded. The concentrations of lactic acid,formic acid, and acetic acid increased in the high SDF ratio group, whereasthe concentrations of propionic acid and butyric acid increased in the lowSDF ratio group. The genera Clostridium_sensu_stricto_1, Ruminococca-ceae_NK4A214_group, Christensenellaceae_R-7_group, and Rikenella-ceae_RC9_gut_group were enriched in the high SDF ratio group.Correlation analysis indicated that these differential bacteria had thepotential to degrade polysaccharides. These results revealed that high SDF ratios could stimulate the proliferation of fibrolytic bacteria, which in turn degrade fibers to produce organic acids and monosaccharides. Collectively, these findings add to our   understanding of the mechanisms responsible for interaction the rational use of dietary fiber.”

This is also giving me a clue on the type of food that may be contributing to the increase of Formic acid..  as I explore the type of diet I had changed to e.g. no wheat  I reduced the intake of insoluble fiber, then I furthered explored what level of IDF vs SDF foods I have been giving my daughter.  I’ll be looking at my food logs to see the trend.  

THANK YOU!  As I continue in my search.

End Products and Autism, etc

Many months ago, I extracted information from various sources on what end products/metabolites are produced by various bacteria. My reasoning was simple: the symptom may be due to too much OR too little of some metabolite/chemical, like lactic acid. Lactic acid is produced by many different bacteria. If we try looking for patterns with the end products then the specific bacteria become less important, and the combined results of many taxa become apparent.

Over the last weekend, I attend a conference on Autism and the speakers mentioned finding some metabolites too high or too low. I decided to revisit the end product pages and added some new pages. My focus is autism but the approach in this post can be applied on other matters.

The quick summary page

This page just lists the symptoms (like autism, POTS, FM, ME/CFS) and how many metabolites appear to be statistically significant. I should mention that often the pattern is not autism has the lowest values or highest values, but often land in the high medium range — missing high values and low values.


Looking at AGE 60-70, you can see a lot of age related changes! Lower vitamin B12 and butyrate, higher hydrogen sulfide

Age: 60-70, http://microbiomeprescription.com/Data/EndProductExplorer2?includes=192

My original thinking is that by taking select supplements you can bring up (or take down) the levels in the gut. My rationale is simple, end products are used by other bacteria. If you are short on one, it will alter the microbiome balance across many taxa, a cascading effect.

Autism: http://microbiomeprescription.com/Data/EndProductExplorer2?includes=262

With autism, looking at the numbers above there is a pattern of “not in the middle”. The amounts being produced are too high OR too low often. Some items are in one direction:

  • Formic Acid: Too high

We also have finer resolution available which (a surprise to me) often find more items, as shown below.

When we go to finer levels, we actually get more stronger relationships

For Lactic Acid, there are a number that are sky-high. A similar pattern is also seen with a subset of ME/CFS. Trytophan has the values at the highest and lowest 6%. Etc

Bottom Line

Unlike taxa where diet and supplements modifications are obvious steps, a lot of eurekas here may need physicians to know how to proceed. A few items like low production of Vitamin B12 and some amino acids have over the counter supplements available.

Child Autism microbiome over time – Part 2

In Child Autism microbiome over time – Part 1 , I reviewed the predicted symptoms for each samples and saw a regular pattern. As a result, I wrote some code to cluster the taxa from most common predicted symptoms… in english, identified the bacteria that appears to be causing most of the regular predictions.

To get to this new report, on the samples page, click [Compare Samples to Each Other]

On the next page, select the samples to be included and click [Probable Symptoms Cluster]

The next page does the analysis automatically, showing the common symptoms and then ranking the bacteria matching these symptoms

Just check the ones that you wish to include. My rule of thumb is to go down to 1/2 of the highest value (i.e. 16.5 or higher, since the high is 33). Then create the custom profile. At this point it will evaluate all of the samples and add this hand picked to the best sample. (You may wish to delete other hand picked taxas before doing this — so you can find it!)

The handpicked list is in gold.

You can view the choices if you wish

At this point, we are ready to try suggestions

What happens here is not unexpected. Because we are dealing with a different selection of bacteria, suggestions may contradict, others in agreement with Child Autism microbiome over time – Part 1

There is no easy solution.

  • Items recommended by both or avoid by both are the easy part.
  • When there is disagreement, I usually opt to omit them unless there is a specific reason to include.
  • If it is one one but not the other, I am inclined to go with the suggestion.


This is artificial intelligence and that usually mean that it can be tuned or adjusted. Whether it makes the results better or worst may be subjective.

Raising the value reduces the symptoms, reduce the bacteria identified
Lowering, increases the symptoms and the number of taxa

A Second Child

There is another mother with a boy with autism who has also been doing regular samples. To my surprise (and likely my AI’s delight!!!) we came up with similar results for symptoms

Bottom Line

This will likely work with many different conditions. I tried it for myself across all of my samples (in remission of ME/CFS and in relapse) as shown below… Needless to say, the AI did an awesome job!

We do not want to work from a single sample. We want to take regular samples to quiet down random noise in the microbiome and identify the masterminds behind any issues.

Getting Started

If you are new, use Thryve Inside (there is a Gut Club Discount Code ) because it is the most used and thus we have more data on it.