A reader requested an education analysis using the tool at Microbiome Prescription.
Back story-long history of gut issues/IBS.Terrible time post partum 22 years ago with sleep issues and mental health. I’ve been down the hell hole of modern medicine on all kinds of meds for years. Finally diagnosed with SIBO in 2019 and then no luck with treatment. More recently had bad reaction to high doses of Vitamin D-gut issues worse- total body pain, inflammation, food intolerances, terrible insomnia. I will add-horrific constipation not resolved unless I take herbal formulas [Microbe Formulas Bowel Mover and Dr. Christophers Lower Bowel Formula. I try to rotate. No specific order. I do think the garlic in the Microbe formulas does help.]
She also mentioned mold and Lyme markets. From Citizen Science we have Comorbid: Mold Sensitivity / Exposure and Infection: Lyme. I will do those separate at the bottom.
I am going to do layers of suggestion and see what evolves. We start with Dr. Jason Hawrelak criteria for a healthy gut. We find a lot of issues as shown below
|Bilophila wadsworthia||species||0||0.25||1.08||Not Ideal|
|Escherichia coli||species||0||0.01||0.047||Not Ideal|
|Faecalibacterium prausnitzii||species||10||15||0||Not Ideal|
The key suggestions computed by the AI are shown below. We will add more suggestions and end up with a consensus report joining all of these set of suggestions into a single report
A second approach is not to limit to a few key items, instead look for odd items across all bacteria. We use Kaltoft-Moltrup Ranges and get the following bacteria being identified:
|Bacteroides caccae||Too Low|
|Bacteroides gallinarum||Too Low|
|Bacteroides paurosaccharolyticus||Too High|
|Bacteroides thetaiotaomicron||Too High|
|Blautia hydrogenotrophica||Too Low|
|Catonella morbi||Too Low|
|Erysipelothrix muris||Too High|
|Parabacteroides distasonis||Too Low|
Our third pass, is using US National Library of Medicine studies that identify certain bacteria associated with IBS. We will use IBS but widen the criteria used to extreme 6%. Some of the bacteria are cited above, and some are new.
|Bacteroides ovatus||Too High|
|Bacteroides thetaiotaomicron||Too High|
|Bacteroides uniformis||Too Low|
|Bacteroides vulgatus||Too High|
|Dialister invisus||Too High|
We notice that soy, Cacao and lactobacillus casei (probiotics) seem to be included every time, although we have different bacteria being selected.
Going over to citizen science, we see four matches for SIBO
|Escherichia albertii||Too High|
|Serratia entomophila||Too High|
|Symbiobacterium toebii Rhee et al. 2002||Too Low|
Unfortunately the information we have for this is very limited.
Going back to US National Library of Medicine for SIBO, we get NO BACTERIA matches at all. My conclusion is that it may be atypical SIBO.
At this point, I want to check some specific items that she cited. There is a tool for that
- For Vitamin D, we appear to have adverse effects
- Categoric Sum:1
- Categoric Average:0.1
- Log(Count) Sum:-8.4
- Log(Count) Avg:-0.6
- For Garlic, we have a definite positive effect
- Categoric Sum:3
- Categoric Average:0.3
- Log(Count) Sum:7.4
- Log(Count) Avg:0.8
These predictions are solely from the microbiome and agree with what she has experienced.
Above tested two substances that had been tried and the prediction appear to agreed with her experience. She asked about an items she was planning to take or recently started.
- lactoferrin – which does not match any item, I selected iron and the results suggested that it will not improve matters. This looks at all undesired shifts.
- Categoric Sum:0
- Categoric Average:0
- Log(Count) Sum:-10
- Log(Count) Avg:-0.8
I also check the merge consensus report (see bottom) where we are selecting only the bacteria of concern. It is also an avoid
Each of the above list of suggestions are stored on the server (for 24 hours) and we can see all of them together.
Our top suggestions (i.e. items that moves everything above in the right direction without exceptions)
The complete list is below for the person to explore in more details. There are 400+ items that have good or bad impact.
My non-medical profession selection would be the following as shown below, using dosages from clinical studies,
|resveratrol (grape seed/polyphenols/red wine)||2000 mg/d|
|lactobacillus casei (probiotics)||48000 MCFU/day|
|fructo-oligosaccharides (prebiotic)||15 gm/day|
|folic acid,(supplement Vitamin B9)||5 mg/day|
|N-Acetyl Cysteine (NAC),||2400 mg/day|
|vitamin b3 (niacin)||1000 mg/day|
|lactobacillus reuteri (probiotics)||5 MCFU|
As always, this is produced from a computer AI model and not clinical experience. Before any change is done, it should be discussed with your medical professional. Some items, like 1000 mg of niacin per day may require testing (see this summary on niacin from the National Institute of Health)
Mold and Lyme Markers
Lyme is always a fuzzy area –if the person had ever had EBV and their microbiome is off, then false positives are well reported in the literature.
The suggestions are shown below, there are a few matches with the above
I did a side by side comparison and found that there was a lot of disagreement between the sets of suggestions. That is not unexpected, because the bacteria selected determines the suggestions.
My gut feeling is that the IBS/SIBO is the preferred one — the citizen science did not have a single item auto checked, I had to go with the secondary items 💡 to get suggestions. This implies a weak match. Second, the IBS/SIBO included the gold standard bacteria identified from formal clinical studies. In short, likely better quality of information.
For those that are interested in how I created the above comparison, see this video — just change the URL to Source and enter a name in the column before pasting between sheets.