A new specialized selection of suggestions based on statistical significance

Going to [Changing Microbiome] page you will see a new box appearing. It may or may not contains links to suggestions. It is scoped to BiomeSight interpretation of microbiome data. If you have Ombre/Thryve samples, do not despair, you can move your raw data to BiomeSight and send it to Microbiome Prescription. It is simple and fast as shown in this video 📹Video on Transferring Data from Ombre/Thryve to Biomrsight and then to Microbiome Prescription.

Actually, if you have done any of those listed below — you can follow the same process

Choices from BiomeSight.com
The counts are the number of matches to the sample currently selected.

What will appear in this list?

First, why Biomesight? — the reason is very simple, there are more samples (20% more at present and increasing then Ombre despite being in business for much less time). The bigger the sample size, the easier it is to find significant shifts.

The criteria is that there must be strong statistical significance for a good number of bacteria. My current threshold is: z-scores must all be 2.6 or higher, that is p <0.01 or 99% confidence. At least 50 bacteria needs to be identified as significant. I will be going thru the symptom list from most frequency reported to less frequently reported. Make sure that you annotate your samples with your symptoms.

NOTE: The numbers below reflect the statistics when various posts were done. The numbers are recomputed at least bi-weekly.

Long COVID15710.6-12-22.7
General ME/CFS1596.64.53.1
ME/CFS with IBS528.46.3n/a
Tinnitus (ringing in ear)736.37.1n/a
Histamine or Mast Cell Issues568.56.1n/a
Neurocognitive: Brain Fog1275.35.65.8
Neurocognitive: Can only focus on one thing at a time795.86.7n/a
Neurocognitive: Difficulty paying attention for along period of time755.25.0n/a
Neurocognitive: Problems remembering things696.35.9n/a
Difficulty finding the right word677.05.5n/a
Post-Exertional Malaise (PEM)626.27.0n/a
Unrefreshing Sleep1075.55.2n/a
General: Fatigue1305.25.73.9
Worsening of Symptoms with Stress.926.95.1n/a
Irritable Bowel Syndrome556.76.1n/a
Poor Gut Motility558.86.4n/a
Easily Irritated539.95.9n/a
Allergic Rhinitis (Hay Fever)428.66.8n/a
Hypersensitivity to Noise566.98.1n/a
Intolerance of Extremes of Heat and Cold548.86.7n/a
Cold Extremities7812.65.3n/a
Small intestinal bacterial overgrowth (SIBO)356.57.9n/a
Allergies And Food Sensitivity739.96.8n/a
Alcohol intolerance + Medication sensitivities598.67.9n/a
The bigger the z-score (positive or negative), the more significant
  • I should point out that these bacteria may not be the cause, rather they may be ‘the canaries in the coal mine’ of the microbiome. These studies’ methodology determines association and not causality.

An additional criteria is that they need to be clear abnormalities with the KEGG Enzymes estimate.

Enzyme (KEGG Identifier)Reference MeanLong COVID MeanZ-Score
S-adenosyl-L-methionine:16S rRNA (guanine1516-N2)-methyltransferase (
ATP phosphohydrolase (ABC-type, teichoic-acid-exporting) (
(S,S)-butane-2,3-diol:NAD+ oxidoreductase (
(S)-acetoin:NAD+ oxidoreductase (
UDP-N-acetyl-alpha-D-glucosamine:beta-D-mannosyl-glycoprotein 4-beta-N-acetyl-D-glucosaminyltransferase (configuration-inverting) (
acetyl-CoA:propanoate CoA-transferase (
Example for the enzyme shifts

I have done two with acceptable results and have made them available. More will be added over time (each one takes a fair amount of time).

US National Library of Medicine Studies are difficult to use

I have their results available and on the site, including as bacteria filters. The problem is that all of those results are very sensitive to the lab being used and the software processing the results. See The taxonomy nightmare before Christmas… for background. In the absence of better information, they are the best we have — until now. With these suggestions, the lab and the software being used are the same and also the one that your results are done by.


Interesting Observation

For both of the above, lower levels of a large number of bacteria was the common pattern. These bacteria are not present in all samples, and most of the studies seen on the US National Library of Medicine look only at bacteria found in all samples. That approach will exclude the bacteria that we find are significant.

You may find dozens (in this case 6 dozens!) of bacteria selected

A second item to be aware of is that often those PubMed studies may consist of just 50 people (control and patients). In our analysis, we have 1200+ people with often more then 120 people with a specific condition. Statistically, we are more likely to detect more associations than those studies. It’s a number’s game.

I am still tuning the suggestions engine, so expect reordering of suggestions occasionally. The suggestions pass the reasonableness test.

Quick Cross Validation

I ran the suggestions only for prescription drugs for ME/CFS and the top four suggestions are listed below. Three of the top four are used by ME/CFS physicians such as Dr. Cecile Jadin [Src], Philippe Bottero [src], G. L. Nicolson, M. Y. Nasralla, A. R. Franco, K. De Meirleir, N. L. Nicolson, R. Ngwenya & J. Haier [Src]. These physicians all report various degree of success.

  • azithromycin,(antibiotic)s
  • atorvastatin (prescription)
  • minocycline (antibiotic)s
  • doxycycline (antibiotic)s

Atorvastatin is an oddity with no studies for its use with ME/CFS. On the flip side, generic statins were high on the avoid list. It would be nice if someone did a clinical trail for this explicit type of statin.

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