ME/CFS x COVID :- Long COVID instead

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.

Backstory of Latest Sample

In light of your recent few blog posts about uploads without many microbiome shifts to work with, I was thinking this could be a beneficial walkthrough video for what seems to be the opposite.

I was doing pretty well on my antibiotic rotations (mainly tetracycline two weeks on, two weeks off since Aug of 2021) until Feb or so when I had a major crash / flare that I’m still suffering from.

I did have a very mild case of Covid in mid January that felt no worse than a regular cold.

But from what little I can parse from this sample, it seems I may be struggling with long Covid. I say little, because my brain fog is extremely dense. 

And all of the results I’m getting for this sample via your site seem so drastically different from what has been going on over the last 7  years (my oldest sample is from 2015).

Comparison of samples

This person has samples going back to 2015 using uBiome. Unfortunately for comparison we need to keep to the same lab (why? read The taxonomy nightmare before Christmas…).

Jason Hawrelak Criteria etc

We finally see an improvement with Jason’s criteria. We also may be seeing more diversity with the increase of Genus and Species found. I say may because this could be a side-effect of a low raw count in some samples.

DatePercentileUnhealthy BacteriaGenusSpecies
2022-04-1198.8 %ile8220303
2022-01-1189 %ile1189141
2021-03-0989 %ile8108153
2020-05-2789% ile7153223
Finally, we have a significant improvement
Expected values ar 10% for each line

I decided to look at the raw reads (which are captured from Thryve and Biomesights)

Sample DateRaw Reads
5/27/202043311
3/9/202129247
1/11/202217630
4/11/2022153194
The cause of the jumps above may be the number of reads from the sample

This lead me to look at what typical raw counts are from Ombre/Thryve

To find the raw counts for your sample, open the csv and look for this line

taxon_id,rank,name,parent,count,...
2,kingdom,Bacteria,,45341,...

What is the consequences? It means that rarer bacteria may be ghost-like, appearing or disappearing from sample to sample. This adds let one more layer of fuzziness to doing analysis and generating suggestions.

First Question: ME/CFS or Long COVID microbiome or both?

This person uploaded the Ombre FASTQ files to BiomeSight so I may used data from the Long COVID study there. Both condition present similarly, I am curious to see if we have sufficient reference data to decide which condition is a better match.

RankName ( 👍 match National Library of Medicine Citations for Long COVID)Your valuePercentile
clade FCB group250605.9
class Bacteroidia 👍227004.1
class Betaproteobacteria 👍151013.3
class Spirochaetia14086.1
family Bacteroidaceae 👍206905.4
family Eubacteriaceae 👍65030.9
genus Caloramator 👍 [family]152068.5
genus Nostoc2030.6
genus Roseburia 👍1223034.6
norank Eubacteriales incertae sedis 👍 [family]6011.9
order Bacteroidales 👍227004.1
order Burkholderiales147012.9
phylum Spirochaetes14086
species Butyrivibrio proteoclasticus 👍[genus]103.6
species Faecalibacterium prausnitzii 👍30195098.5
species Roseburia faecis 👍 [family]62024.3
Long Covid matches against Biomesight 154 Samples


RankName
(👍 matches National Library of Medicine Citations for Chronic Fatigue Syndrome
Your valuePercentile
family Halanaerobiaceae2037
genus Anaerovibrio57065.1
genus Finegoldia207
genus Halanaerobium2031.8
genus Leuconostoc103.2
genus Pediococcus103.9
order Syntrophobacterales103.9
species Anaerotruncus colihominis85060.2
species Anaerovibrio lipolyticus57065.4
species Bacteroides acidifaciens 👎[sibling]100.9
species Bacteroides fluxus 👎[sibling]209.8
species Clostridium akagii 👎[sibling]105.5
species Clostridium cadaveris 👎[sibling]103.8
species Finegoldia magna101.8
species Odoribacter denticanis 👍[sibling]102.5
species Prevotella copri 👍[sibling]100.6
ME/CFS matches against Biomesight 62 Samples

We have concurrent matches for both both conditions

  • Finegoldia magna, which is not reported in the literature
  • The table above hints that he is at present much closer to Long COVID than ME/CFS.

I am not sure about the political correctness of saying “Congrads! You no longer have ME/CFS, you have Long COVID!” is what the microbiome reads like.

What is interesting is that the microbiome constantly shifts/evolves, with Long COVID the infection is constant and the duration since the infection is short — hence less evolution of the microbiome over all patients. With ME/CFS the triggering infection possibilities are huge with 20, 30, 40 years of evolution of the microbiome — hence patterns are diffused by time and original infection.

Looking at deficiency of compounds produced, we see a dramatic drop from the previous sample suggesting that bacteria are getting the needed inputs for correct functioning.

Sample Date1%ile5%ile10%ile
5/27/202041460
3/9/202121416
1/11/2022197233244
4/11/202262852
Kegg Compounds below %ile shown

Where do we go from here

I am going to do consensus, but do only 3 items:

  • Hand Picked Bacteria using the study in progress data using BiomeSight (16 bacteria)
  • Using US National Library of medicine filter to Long COVID using BiomeSight and Box-Whiskers (14 bacteria)
  • Using US National Library of medicine filter to Long COVID using Ombre and Box-Whiskers (14 bacteria)

The consensus is below as a download. Since antibiotics are being prescribed at present, I included that in the suggestions criteria.

Some highlights

Why did I focus on the ME/CFS ones? Path of least resistance for the prescribing MD – the MD accepts ME/CFS and thus will have low resistance to prescriptions often used for ME/CFS. Asking for them for Long COVID could get rolling of eyes…. As always, we are using these off-label for their computed microbiome effect. For the prescription items, I would suggest rotation (one item for 10 days, then a 0-10 day break, then another item (or repeat if limited to one item).

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