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.

Back Story

Typical for ME/CFS, fatigue and brain fog prevented much of a backstory. Fortunately, she was able to complete symptoms — which gives a good back story and also shows overlaps with many others:

•   Neurocognitive: Brain Fog [482 samples]
•   General: Fatigue [442 samples]
•   Sleep: Unrefreshed sleep [388 samples]
•   Neuroendocrine Manifestations: worsening of symptoms with stress. [367 samples]
•   Neurocognitive: Difficulty paying attention for a long period of time [360 samples]
•   Neurocognitive: Can only focus on one thing at a time [341 samples]
•   Neurological-Audio: Tinnitus (ringing in ear) [331 samples]
•   Neurological-Audio: hypersensitivity to noise [309 samples]
•   Gender: Female [299 samples]
•   DePaul University Fatigue Questionnaire : Fatigue [297 samples]
•   Immune Manifestations: general malaise [295 samples]
•   Onset: 2010-2020 [285 samples]
•   DePaul University Fatigue Questionnaire : Unrefreshing Sleep, that is waking up feeling tired [268 samples]
•   Neurological: Difficulty reading [253 samples]
•   General: Depression [242 samples]
•   Post-exertional malaise: Worsening of symptoms after mild physical activity [230 samples]
•   Post-exertional malaise: Physically tired after minimum exercise [226 samples]
•   Neuroendocrine Manifestations: cold extremities [224 samples]
•   Post-exertional malaise: Muscle fatigue after mild physical activity [223 samples]
•   Post-exertional malaise: Post-exertional malaise [215 samples]
•   Official Diagnosis: Allergic Rhinitis (Hay Fever) [211 samples]
•   Neuroendocrine Manifestations: intolerance of extremes of heat and cold [208 samples]
•   Post-exertional malaise: Inappropriate loss of physical and mental stamina, [205 samples]
•   Official Diagnosis: Chronic Fatigue Syndrome (CFS/ME) [201 samples]

Analysis

Following my usual path My Profile/Overview found an over population of rare bacteria and under population of common bacteria. This is important to note because most clinical studies focused on shifts of common bacteria, and exclude rare bacteria (sample sizes and lack of sufficient statistical training are the typical cause).

Dr. Jason Hawrelak’s criteria came in at 56%ile, not any clear issues, with the following main items of note:

• Akkermansia -none, which suggests Akkermansia Probiotics (which persists up to 30 days – from conversations with their staff)
• Bacteroides – significant overgrowth

I looked at a new feature to see the area of imbalances, and too much production of compounds is evident.

Looking at My Profile/Visualization/Microbiome Tree for colored items (and drilling down to the lowest level that are highlighted:

•  Insolitispirillum peregrinum (which makes up almost 99% of  Alphaproteobacteria)
• Under Bacteroides, the following stands out
  • Bacteroides eggerthii
  • Bacteroides finegoldii
  • Bacteroides xylanisolvens
  • Bacteroides caccae
  • Bacteroides rodentium
  •  Phocaeicola dorei
• Faecalibacterium prausnitzii is high (97%ile)
• Caloramator mitchellensis is border line concern (high)

My first analysis in building a consensus report is hand picking the above and seeing the results.

The top items are similar to other ME/CFS suggestions and repeats my often refrain “Have barley porridge with walnuts” sweeten with sucralose for breakfast each day:

WARNING ABOUT GLUTEN-FREE MIS-INFORMATION

Research your science well:”Gluten is a complex mixture of hundreds of related but distinct proteins, mainly [in wheat] gliadin and glutenin. Similar storage proteins exist as secalin in rye, hordein in barley, and avenins in oats and are collectively referred to as “gluten.” ” What is gluten? (US National Library of Medicine)
Barley is free of glutenins and gliadins, the troublesome glutens. You may be using “All black men are criminals” reasoning. You really need to be tested for which types of gluten proteins you reactive to and not go for internet-legend that all glutens are bad.

The avoid list suggests not to use soy milk with the porridge. Red wine for ME/CFS is a very typical avoid (most ME/CFS cannot tolerate wine… I wonder why 😉 ). Let us see how much consensus we get from doing the pro-forma consensus building

We go to Changing Microbiome/Consensus Suggestions

•  Use JasonH (15 Criteria) – 10 bacteria picked
•  Standard Lab Ranges (+/- 2 Std Dev) – 4 bacteria picked
•  Box Plot Whisker – 28 bacteria picked
•  Kaltoft-Moltrup Normal Ranges – 82 bacteria picked
•  Percentile in top or bottom 10 % – 83 bacteria picked

The Consensus report is attached.

And despite may ways of slicing and dicing, the same items appear as above on the top of the consensus.

And the worst items are also similar —

Watch the types of sugars!!!

The following are popular sugar alternatives (often deemed “more healthy”) which should be avoided: stevia, saccharin, xylitol. On the best alternatives for this microbiome: sucralose (Splenda), glucose (sugar), raffinose(sugar beet).

Getting Suggestions From Symptoms

The person has entered their symptoms (see above). Unfortunately, there are many different paths that can be taken. The intent of picking bacteria by symptoms is to allow suggestions to be based on the most likely bacteria for the most troublesome symptoms for a person.

This is on Research Feature / Experimental /Build a Hand Picked collection using Symptoms. I went with the following for illustration purposes.

Picked Symptoms

• Neurocognitive: Brain Fog
• Onset: 2010-2020
• Immune Manifestations: Hair loss
• Neurological-Audio: Tinnitus (ringing in ear)
• Neurological: Joint hypermobility

I used “Expected” settings and got the following list. All of these were items with low values,

The suggestion list is very different than above:

We see walnuts and for our morning porridge, add in blueberry.  Bofutsushosan is very interesting because it increases AKKERMANSIA (mentioned above). I have done Bofutsushosan with Akkermansia probiotic and found a major increase in Akkermansia. Choline Deficiency means avoid foods that are HIGH in choline – see NIH List here.

The avoid list (items that will reduce the above bacteria) includes a number of probiotics:

Summing up probiotics

The following are my suggestions (2-3 weeks of doing one, then rotate to the next one)

• Akkermansia Probiotic — take with Bofutsushosan (available on Amazon etc)
• lactobacillus salivarius
• bifidobacterium infantis
• Lactobacillus plantarum

I should note that in some conference notes, ME/CFS specialists hint that random probiotics results in worsening of ME/CFS symptoms.

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.

The Next Episode of the Story

This person’s early analysis is at IBS + BioNTech COVID Vaccine -> ME/CFS? He forwarded these notes:

• I have done everything as planned since your first review
• I maybe went up from 15% to 20%. I was able to reintroduce some new activities, but still am lying in bed most of the time. Also taking piracetam seems to help.
• I still won’t be able to do the analysis myself.
  • COMMENT: ME/CFS patients are a priority for me because I personally understand their brain fog and cognitive impairments from past experiences.
• I have had COVID in the meantime in case that matters for your analysis, but I did not notice any changes afterwards.

Analysis

Given the recent post for another ME/CFS person who had COVID too, with the result that their microbiome became a good match for long COVID and a poor match for ME/CFS, this was my first question. Fortunately, the sample was done via Biomesight, he did not needed with FASTQ files and transferring them. To keep the story short, I looked at his shifts compared to annotated sampled and compare to literature from the US National Library of Medicine nothing shifted between the samples. There is no shift towards Long COVID from ME/CFS in this case.

Comparing Samples

I do not know the answers. I have a model. Models often need adjustments so comparing samples (for better or worst) in a consistent manner is part of my learning process.

First thing we see a dramatic change with rare bacteria being seen much more often and common bacteria less often. There are more genus seen (184 vs 141) and more Species (230 vs 161) but this may be due the better sample reads in the latest sample (82,102 reads versus 55,117 reads).

• Hawrelak’s criteria was 95.6%ile for both samples.
• Potential Medical Condition dropped from 7 to 1. With Obesity being in common.
• Bacteria deemed Unhealthy increased from 9 to 17. With Collinsella, Dorea, Prevotella bivia, Prevotella copri, Rickettsia, Serratia and various Streptococcus being added and Mogibacterium disappearing. This may be a side-effect of the better sample.
• Kegg Probiotics
  • The maximum value went down from 18.45 to 4.61 (indicating less compound are an extremely low level).
    • There were 6 compound listed before and it dropped to just 1 (Aromatic aldehyde) when using 1% filtering level.
    • There were 18 compound listed before and it dropped to just 1 when using 5% filtering level.
    • There were 19 compound listed before and it dropped to just 3 when using 10% filtering level.

Was there improvement? Despite the potential confusion because of sample quality we had 3 indicators of improvement:

• Significantly less matches to known medical conditions profiles
• Significantly less compound that the person appears to be low in (using data derived from Kyoto Encyclopedia of Genes and Genomes )
• The person feeling subjectively better and doing more activities

Most of the other measures are the same or difficult to interpret. There is one possible concern, the high levels of Prevotella copri is an indicator of mycotoxin, typically from moulds and fungi. Considering that the time between the samples was winter with close windows and heating — there could be an environment issues here – so lots of fresh air may be good.

Over to Suggestions

There are various algorithms to suggesting probiotics, the strongest results are for:

• From KEGG
  • At 10% Filtering: Prescript-Assist®/SBO Probiotic – and I would be find substituting Equilibrium as an alternative here.
  • At 1%, 5% – any of the following (remember we are short of one compound only and all of there produces it)
    • L. Plantarum Probiotic
    • L. Rhamnosus Probiotic
    • L. Salivarius Probiotic
    • etc
• I ran a few ways of picking bacteria based on Bacteria (and not genes) and  lactobacillus casei kept was the top in the consensus report (overall and in terms of probiotics)

Doing my usual consensus building

•  Use JasonH (15 Criteria) – 7 bacteria
•  Standard Lab Ranges (+/- 2 Std Dev) – 6 bacteria
•  Box Plot Whisker – 48 bacteria
•  Kaltoft-Moltrup Normal Ranges – 56 bacteria
•  Percentile in top or bottom 10 % – 66 bacteria

Among the top items are ones that are supported for ME/CFS in studies, including:

• Cacao [2010]
• lactobacillus casei [2009] [2018]
• resveratrol (grape seed/polyphenols/red wine) [2011]
• magnesium [many, going back to the Lancet in 1991 ]
• Cyanocobalamin (Vitamin B-12) [2015 et al]
• folic acid,(supplement Vitamin B9) [2015 et al]
• zinc [2021]
• melatonin supplement [2021]

Unfortunately, some of the items have no studies. Given that the suggestions are based solely on bacteria with no knowledge of the diagnosis, the convergence with the literature suggests that the suggestions are very appropriate. Two different roads came to the same conclusion. In data science this is sometimes called “cross validation”. In Scotland, “O ye’ll tak’ the high road, and I’ll tak’ the low road,
And I’ll be in Scotland a’fore ye,”

I looked at the antibiotic list for the latest sample and the top two are typically used for ME/CFS:

• metronidazole [British Medical Journal] [Patient Survey]
• macrolide antibiotics [2006] [2011]

And interesting that several others often used are NOT recommended: azithromycin (which is a macrolide ?!?), minocycline [2021], fluoroquinolone, doxycycline.

ME/CFS is a heterogeneous condition with a wide variety of microbiome dysfunctions. I believe that using the microbiome to target the best candidate antibiotics is the rational way to proceed.

ME2_Consensus Download

Questions and Answers

• Question: Sadly I do not tolerate chocolate, but I will try it out again.
  • Answer: These are suggestions, do only what you are comfortable with. Nothing is required. The chocolate issue is interesting, my daughter does not tolerate most chocolates, she discovered that it was the type of sugar (i.e. made with liquid sugar / liquid glucose — adverse reaction) made with solid sugar — happiness. See Health effects of glucose syrup
  • If you try again, you may wish to determine the type of sugar actually being used first.
• Question: Is there no avoid list?
  • Answer: Yes, in the download, any item with a NEGATIVE value in the priority is an avoid
    

• Question: Is 1 capsule of Equilibrium per day really enough?
  • Answer: I honestly do not know. There is no literature to work from. If you take more, than separate them (i.e. 12 hrs apart)
• Question: It seemed whenever I took turmeric that I was getting more nervous and anxious. Still take it now and then?
  • Answer: As above, do only what you are comfortable with — there are hundreds of items listed. Anxiety is contrary to the effects of turmeric / curcumin reported in the literature [2021] [2019] [2018] [2017]. If turmeric is causing die-off of bacteria that causes vascular constriction, that would result in anxiety. If you tolerate aspirin or niacin (flushing type), then try taking those with the turmeric.

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.

Finally, we have a significant improvement

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

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.

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.

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.

MECOVID_Consensus Download

Some highlights

• linseed(flaxseed) is #1 by a wide margin
• thiamine hydrochloride (vitamin B1), pyridoxine hydrochloride (vitamin B6), vitamin b3 (niacin), vitamin b7 biotin (supplement) (vitamin B7), Vitamin C (ascorbic acid)
  • Cyanocobalamin (Vitamin B-12) and folic acid,(supplement Vitamin B9) has less predicted impact
  • B Complex appears negative, as does Vitamin E, D, K2 and A
• glycyrrhizic acid (licorice) – which means to me, usually means Spezzatina
• Then a stack of antibiotics and prescription items (checking items listed on this page)
  • I checked the typical ME/CFS ones
    • minocycline (antibiotic)s -250 AVOID
    • tetracycline (antibiotic)s -207 AVOID
    • fluoroquinolone (antibiotic)s -29 AVOID
    • rifaximin (antibiotic)s – 134 AVOID
    • azithromycin,(antibiotic)s +49
    • fludrocortisone acetate,(prescription) +353
    • gabapentin,(prescription) +353
    • naltrexone hydrochloride dihydrate,(prescription) +353
    • nimodipine,(prescription) + 353
    • pentoxifylline,(prescription) + 353
    • magnesium  -180.2 If supplementing, pause
    • melatonin supplement + 266.3

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).

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.

Back story 

I’ve had ME/CFS 14 years (symptoms came on stronger after breast augmentation 2008) but the last 9 yrs I’ve been mostly housebound & bed bound 21 hours per day. I’d say I’m moderate/severe. (I live in the Uk) 

My diet:- 

• Brekkie :- muesli (take raisins out) with coconut milk or almond milk  Or poached egg on 1 seeded brown bread Or scrambled egg with cumin, coconut milk, salt & black pepper on 1 seeded brown bread Or porridge with coconut milk, frozen blueberries or dried goji berries 
• Lunch:-A banana, nuts (walnuts, pecans, almonds) & mixed seeds 
• Dinner:-Salad (bistro salad leaves with a little shredded beetroot) cucumber, celery, grated carrot, with jacket potato (or sweet potato) & vegan cheese on top.. I’ve just started to add a sprinkle of organic olive oil & black pepper (tasty)  Or Steamed veg – carrots, green beans, broccoli, stringless beans & sugar snap peas (or mangetout) with sweet potato & usually something out the freezer I pop in oven… which I know I need to stop as it’s processed. I will begin to change that for chicken or salmon (it’s just been easier) 

More information on diet and supplements was also sent.

Analysis

Looking at Bacteria Deemed Unhealthy, the sole item that stands out was moderately high Streptococcus oralis. Dr. Jason Hawrelak Recommendations came out to 90%ile — so better than most people.

For this person, we have a shift towards rarer bacteria with those seen in only 30-50% of samples being over represented.

Since ME/CFS is the condition, I checked the list of antibiotics often prescribed with the following being the top of the list. It is interesting to note that the literature finds that they do improve some ME/CFS patients

1. gentamicine sulfate (antibiotic)   (1) [See 2021] [2017]
2. rifaximin (antibiotic)s   (0.949) [Health Rising] [2011] and many more
3. amikacin hydrate (antibiotic)   (0.845) – no significant literature
4. gentamicin (antibiotic)s   (0.745) [2017]
5. metronidazole (antibiotic)s   (0.727) “Metronidazole/Flagyl is reported to have 75% of CFS patients improving ” [Src] also [BMJ]

On the avoid list are some antibiotics that are also prescribed for ME/CFS

1. rifampicin (antibiotic)s   ( – 0.423 )
2. tetracycline (antibiotic)s   ( – 0.291 )
3. azithromycin,(antibiotic)s   ( – 0.289 )
4. rifampicin (antibiotic)   ( – 0.289 )
5. doxycycline (antibiotic)s   ( – 0.191 )

She provided some of the items that she is taking so I looked at the estimated impact on her microbiome

• sertraline,(prescription) which she is reducing. This is likely a good course of action
  • Take Estimate:  20.4, Avoid Estimate:  24.7
• dopamine (prescription) – this is a bit of a concern to me because it is likely to contribute to microbiome dysfunction
  • Take Estimate:  13.2, Avoid Estimate:  23.1
• Vitamin C, — keep taking
  • Take Estimate:  22.3, Avoid Estimate:  13.9
• Cetirizine:
  • Take Estimate:  20.4, void Estimate:  29.1

Note: the above are estimates on whether they will improve or contribute to the microbiome dysfunction. Medical concerns should always dominate.

Suggestions

Doing my usual pick the bacteria to change using different criteria we have:

•  Use JasonH (15 Criteria) – 8
•  Standard Lab Ranges (+/- 2 Std Dev) – 3
•  Box Plot Whisker – 19
•  Kaltoft-Moltrup Normal Ranges – 34
•  Percentile in top or bottom % – 27

The number of bacteria selected for each of the above was lower than I often seen.

Going to the Consensus

The following suggestions stand out:

• whole-grain barley (she does report porridge, she may wish to make sure that it includes barley)
• Vitamins: Note ME/CFS usually benefit for B-Vitamins [1999] [2019]
  • thiamine hydrochloride (vitamin B1) –
  • vitamin b3 (niacin)
  • vitamin b7 biotin (supplement) (vitamin B7)
  • Cyanocobalamin (Vitamin B-12)
  • Vitamin C (ascorbic acid)
• Conjugated Linoleic Acid
• quercetin,resveratrol
• melatonin supplement
• N-Acetyl Cysteine (NAC),
• Cacao
• lauric acid(fatty acid in coconut oil,in palm kernel oil,) – She does use coconut milk, this is good. She may wish to increase.

Dropping down to the avoid list, we see

• saccharin
• stevia
• nuts (including walnuts, almonds/ almond skins ) – she currently use these as snacks. banana and plantain bananas are fine to use as snacks
• peppermint (spice, oil) – she may wish to change to use ginger and especially Echinacea tea instead

The full list is attached.

Trying out an Experimental feature

I have used this feature of the several recent blogs on autism (Bacteria to Hand-Pick for Autism with Ombre/Thryve samples, Bacteria to Hand-Pick for Autism with Biomesight samples). I have posted the bacteria identified here. Unfortunately sample size are small (1/3 of the Long COVID samples)

• ME/CFS bacteria shifts for Ombre/Thryve tests
• ME/CFS bacteria shifts for BiomeSight tests

Using the 61 samples annotated with CFS and processed thru the same lab (Biomesight.com). We found 11 bacteria identified as statistically associated with CFS. Three were too high and 8 were too low.

The results from this custom picked set are shown below.

We have some contradictions between these suggestions and the ones above. Why? The data we are using is very very incomplete. It is the best that is available. In keeping with my principle of less risk, when suggestions are in disagreement (for example Nuts and almonds – recommended here but to avoid above), then omit them. There are a lot of possible items, keeping to positive items where there are no disagreement is the best path.

Because this person suffers from brain fog, they may wish to sit down with a nutritionist to go thru the download list above to craft a diet plan. The suggestions are in no way a balanced nor complete diet. For example increase food rich in magnesium on the take suggestions, or using supplements.

As always, this information is computed from the best available data and is not based on clinical experience. Always review with your medical professional for appropriateness of suggestions before starting.

Bottom Line

I check with this person and the breast augmentation has not been undone. In other words, there is a reasonable chance that it is a significant contributor to the ongoing symptoms. I expect some progress from microbiome manipulation, but I suspect the side effects from augmentation will limit it. The literature seems to confirm it.

• “Subclinical bacterial infections (biofilms) are strongly implicated in breast augmentation” [2021]
• “The most common cause of surgical readmission after breast implant surgery remains infection. Six causative organisms are principally involved: Staphylococcus epidermidis and S. aureus, Escherichia, Pseudomonas, Propionibacterium, and Corynebacterium.” [2015]
• “The researchers found that the women with silicone gel-filled breast implants were significantly more likely to be diagnosed with autoimmune or rheumatic disorders, such as Sjögren syndrome, systemic sclerosis, and sarcoidosis, compared with women without breast implants of a similar age and socioeconomic status.” [2022]
• “Silicone breast implants(SBI)  are associated in a proportion of patients with complaints such as fatigue, cognitive impairment, arthralgias, myalgias, pyrexia, dry eyes and dry mouth. Silicones can migrate from the implant through the body and can induce a chronic inflammatory process. Explantation[Removal] of SBI results in the majority of patients in an amelioration of the symptoms.” [2017]

This post is intended for researchers by pointing to bacteria whose genetics are likely significant for ME/CFS. The microbiome specific raw data is below. Preliminary z-scores indicated that they are significant (Pr < 0.01) and no filtering has occurred for False Detection Rate. Users are advised to perform their own statistics. For bacteria associated using BiomeSight tests, see this post.

Note: These results are lab-specific, using the data from OmbreLabs / formerly known as Thryve.

The raw data is available at: http://citizenscience.microbiomeprescription.com/.

NOTE: The sample size is very low (less than 1/3 of the size of current Long COVID Study)