This person has been using microbiome prescription to reduce the symptoms with success and with objective measurements of improved microbiome. His MD is willing to prescribe antibiotics and the top three items (from hundreds possible) are all used by ME/CFS specialist — indicating that the model is in agreement with clinical experience of ME/CFS specialist (a.k.a. Cross-Validation).

This is a follow up to these prior posts:

• Dec 30, 2021. Rosacea, Circulation and mild CFS.
• Apr 27, 2022 Follow up Microbiome Analysis from a prior post

Why Follow Up Posts are important

The first item is simple, does the model and suggestion appear to work. Everything is theoretically computed. The second item is that encourages people to try suggestions

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.

Comparisons between Samples

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.

Criteria	8/31/2021	12/3/2021	3/25/2022	8/11/2022
Lab Read Quality	7.8	3.6	6.2	5.5
Bacteria Reported By Lab	461	379	479	383
Bacteria Over 99%ile	7	5	3	3
Bacteria Over 95%ile	20	24	11	13
Bacteria Over 90%ile	32	40	21	23
Bacteria Under 10%ile	283	123	237	189
Bacteria Under 5%ile	222	66	143	107
Bacteria Under 1%ile	161	9	44	23
Rarely Seen 1%	3	2	14	7
Rarely Seen 5%	9	7	33	14
Pathogens	37	30	44	31
Outside Range from JasonH	4	4	7	7
Outside Range from Medivere	15	15	15	15
Outside Range from Metagenomics	6	6	8	8
Outside Range from MyBioma	7	7	7	7
Outside Range from Nirvana/CosmosId	18	18	23	23
Outside Range from XenoGene	5	5	7	7
Outside Lab Range (+/- 1.96SD)	14	9	6	8
Outside Box-Plot-Whiskers	41	58	38	33
Outside Kaltoft-Moldrup	211	100	123	111
Condition Est. Over 99%ile	0	0	0	0
Condition Est. Over 95%ile	4	3	1	1
Condition Est. Over 90%ile	9	6	5	7
Enzymes Over 99%ile	17	19	30	10
Enzymes Over 95%ile	105	82	219	68
Enzymes Over 90%ile	139	126	296	183
Enzymes Under 10%ile	783	369	514	645
Enzymes Under 5%ile	542	186	264	423
Enzymes Under 1%ile	271	37	49	86
Compounds Over 99%ile	33	28	62	47
Compounds Over 95%ile	140	127	231	254
Compounds Over 90%ile	346	307	298	338
Compounds Under 10%ile	310	227	297	308
Compounds Under 5%ile	211	111	224	173
Compounds Under 1%ile	132	47	67	65

The next table is also very dependent of Lab Read Quality. The apparent improvement on 12/3/2021 is likely artificial because the counts are low due to low read quality.

	8/31/2021	12/3/2021	3/25/2022	8/11/2022
Percentile	Genus	Genus	Genus	Genus
0 – 9	73	24	51	51
10-19	15	18	32	24
20 – 29	12	13	18	12
30 – 39	4	10	9	14
40 – 49	6	8	9	3
50 – 59	4	8	7	2
60 – 69	4	4	9	3
70 – 79	7	10	7	10
80 – 89	7	4	8	5
90 – 99	14	18	8	8

	8/31/2021	12/3/2021	3/25/2022	8/11/2022
Percentile	Species	Species	Species	Species
0 – 9	87	29	57	58
10-19	24	21	29	24
20 – 29	14	15	21	16
30 – 39	10	16	14	14
40 – 49	2	6	14	3
50 – 59	12	9	17	10
60 – 69	9	10	10	7
70 – 79	8	9	14	7
80 – 89	7	15	5	4
90 – 99	11	13	10	9

So how to interpret this wall of numbers? People can cherry-pick the numbers to say improvement or no improvement. The difference of lab read quality is a big factor because they impact the count for most of the items above. The Outside Box-Plot-Whiskers numbers show continued improvement. In short, the changes shown were less than I was hoping to see.

There is one more method of comparison — using special studies. In this case we see the average matches. Doing a little math, the expected drop of percentage due to lab quality size between 8/31/2021 and 8/11/2022 is a 10% drop. Those that exceeded 20% are color with 😊 below. Nothing became 10% worse. Note that the 😊 also agrees with comparing to 3/25/2022 (the prior sample). Other items remained unchanged. Items reported by this person are 😧 – Strong issue, 😟 – a bit of an issue

Study	8/31/2021	12/3/2021	3/25/2022	8/11/2022	Average
Inflammatory bowel disease	49	32	47	47	43.8
Small intestinal bacterial overgrowth (SIBO) 😟	51	29	48	34😊	40.5
Allergic Rhinitis (Hay Fever) 😧	41	27	45	41	38.5
Autism	45	34	44	27😊	37.5
COVID19 (Long Hauler)	40	24	43	29😊	34.0
Irritable bowel syndrome 😟	40	22	44	30😊	34.0
Alcohol intolerance or Medication sensitivities	43	23	39	29😊	33.5
Histamine or Mast Cell issues 😧	44	17	43	24😊	32.0
Post-exertional malaise 😧	36	23	40	29😊	32.0
ME/CFS without IBS 😟	39	22	36	30😊	31.8
Poor gut motility	42	21	40	24😊	31.8
Brain Fog 😧	37	23	33	33	31.5
Depression	32	27	32	34	31.3
Allergies And Food Sensitivity 😧	38	23	36	25😊	30.5
Cold Extremities 😧	42	23	33	22😊	30.0
Intolerance of Extremes of Heat and Cold 😟	38	16	39	27😊	30.0
ME/CFS with IBS 😟	36	21	36	27	30.0
Bloating 😧	37	22	34	26😊	29.8
General Fatigue 😧	34	20	31	34	29.8
Unrefreshed sleep	31	22	36	28	29.3
Constipation	37	21	29	25😊	28.0
High Anxiety 😟	33	17	33	29	28.0
Easily irritated 😟	32	16	34	23😊	26.3
Tinnitus (ringing in ear) 😟	24	15	29	22	22.5
Chronic Fatigue Syndrome (CFS/ME) 😧	25	21	20	23	22.3
Average	37.8	22.4	37.0	28.9	31.5
Lab Quality	7.8	3.6	6.2	5.5

What is my conclusion? Most of the measures above deteriorates into noise with the exception of data from Special Studies, where we seen improvement in many measures, but not all. In one real statistical sense this makes sense: many are based on common sense and the ones showing clear improvement on statistical significance.

Going Forward

For most of my prior posts used the logical reasoning and clinical studies (which used different labs and software than the samples that I was looking at). With the special studies, we have upped our game (potentially) – the bacteria deemed significant were determined by the same lab and software of our sample, plus the study sizes was much larger than published clinical studies — hence better detection.

To build the consensus I will use the special studies, I filtered to reported issues and high percentage of matches, namely:

• Allergic Rhinitis (Hay Fever)
• Histamine or Mast Cell issues
• Post-exertional malaise
• Brain Fog
• Allergies And Food Sensitivity
• Cold Extremities
• General Fatigue

Remember that most of the special studies found that infrequent bacteria with a low value was what was statistically significant. This is turning the usual logic on it’s head. As I state, this is all experimental but based on studies and statistics.

The top suggestions are below

• navy bean
• Pulses ( dry peas, beans, lentils, chickpeas, etc)
• arabinoxylan oligosaccharides (prebiotic)
• non-starch polysaccharides
• red wine
• wheat bran
• proton-pump inhibitors (prescription)
• l-citrulline
• xylan (prebiotic)
• pea (fiber, protein)

Antibiotics

As expected, most antibiotics and prescription drugs are to be avoided. A few with positive impact includes:

• macrolide ((antibiotic)s) – used by Dr. Cecile Jadin in treating ME/CFS
• sulfonamide (antibiotic)s – suggested for treated ME/CFS [2019]

In terms of generic suggestions, rifaximin (antibiotic)s is by far the top antibiotics, cited here on Health Rising: Rifaxamin – citing use by Dr. Teitelbaum, Dr. Peterson, De De Meirleir and Dr. Myhill (all ME/CFS specialists).

In short, all of the top suggested antibiotics are applicable. My personal approach would be do all three of them in a pulse manner a la Jadin, 10 days on, 20 days off and then move to the next one.

Both above and generic suggestions have proton-pump inhibitors (prescription) being the top choice for other prescription drugs.

Probiotics

The top probiotics list have the usual dilemma: both e.coli probiotics and lactobacillus probiotics. It’s a dilemma because they tend to be hostile to each other. My typical rotation resolution would be 2 weeks of each and then move to the next:

• saccharomyces boulardii (probiotics)
• e.coli probiotics (take it with d-ribose, on the to take list and a food for e.coli)
• bifidobacterium
• lactobacillus
• Equilibrium and/or Prescript Assist

I should note that some are strong to be avoided (watch out for mixtures!!!)

KEGG Suggestions

The KEGG suggestions top items were the bacteria found in Equilibrium and Prescription Assist, except for the top choice, Escherichia coli. A probiotic suggested by Dr. Myhill, a ME/CFS specialist in the UK. The next common conventional items are

Bottom Line

The suggestions above were done solely from special studies. The key question is are they reasonable? I would say yes based on the antibiotics suggestions — all of them have been reported to help ME/CFS patients. We also have agreement between KEGG probiotics and these suggestions.

There is a potential conceptual symmetry between the two approaches (working off extremes and using special studies that are often dealing with rare low bacteria). Bacteria influences each other in very complex ways.

The full list of suggestions is available above.