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 Microbiome 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

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).

CurrentPrior
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 for the latest microbiome sample to get some suggestions.


The highest suggested value/priority 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.

Tool for getting suggestions for your specific ME/CFS Symptoms

After I posted List of Bacteria significant for ME/CFS from the shared samples uploaded to Microbiome Prescription, several readers asked “How do I use this”. This took me a few days to come up with, code and implement an answer.

I wanted this to go beyond just ME/CFS because there is a huge variety of symptoms and co-morbidity seen with ME/CFS. After testing and tuning the algorithm, I am pleased with the current results.

The process is show below.

The Steps

  1. First get a suitable microbiome test done (See this list of supported tests)
  2. Transfer or upload your results to Microbiome Prescription
  3. An email will be sent to you to login
  4. Login in.
  5. Enter your symptoms
  • Return to “My Profile”
  • A new button will appear

Clicking it will move to the page below. YOU MAY FIND THAT IT TAKES UP TO A MINUTE (We are doing a massive number of computation)

This will show a tree of the bacteria involved. The Species are under the genus they below to. In the example below we see the ENTIRE phylum that Bifidobacterium is in are low (none found) of 9 species whose presence would likely reduce your symptoms.


Elsewhere you may see highs with certain bacteria species desired to higher. Often the symptom key is at the species level.

At the bottom you will see a button to get suggestions

The next page shows the symptoms being targeted to and choices of what you want to consider.

Make any changes desired and click show suggestions

REMEMBER these are suggestions for ONE person using their Symptoms and their microbiome profile. It is intended for them only. Your own suggestions may be very different with many items exchanged between ADD and REMOVE.

Technical Methodology Details are described here Technical Note: Prevalence, Average and Not Reported.

Post-Script

This approach sidestep the proforma process often drilled into researchers (you must have a healthy control group and a verified, criteria matching target population). I kept to rigorous statistical analysis while ignoring these constraints which are philosophical in nature. We used the available data and set our significance level to P < 0.005; instead of the typical research level of P < 0.05. In other words, we are 10 times more certain about our results.