All of these products are prone to wild variation of bacteria in it. So if you are trying to do targeted changes, you are tossing a hand grenade into the room. If you are wanting to do random experiments because someone said it helped them (or often believe it may help and are still waiting– and believing), then that’s fine. Some people win the lottery…
Here’s a partial listing of the reported variety of bacteria found…
This is a follow up post on ME/CFS x COVID :- Long COVID instead from June, 2022. The person on seeing the results stated “New Sample Looks Worse”. I am curious because so far all subsequent analysis showed objective improvements (and subjective improvements too!) for people with ME/CFS. I am prepared to be humbled. He used Ombre for the data processing.
Backstory
Lifestyle-wise, I’ve definitely been experiencing a big increase in stress due to working a full-time job for the first time in almost a decade. The job is remote, I couldn’t do it otherwise, but it still requires some late nights and lots of childcare complications since my wife also works full-time and then some.
Diet-Wise: Not much has changed in terms of my diet. I remain 95% Gluten Free with the occasional slip-up or cheat. What’s interesting is a lot has flip-flopped in this sample, so maybe I was overdoing it on the last round of food suggestions, especially in terms of adding fiber to my smoothies, mostly resistant starch.
Supplementation-wise, I had been taking the recommended probiotics from my last sample at a pretty high and aggressive dose to very mixed reactions. I probably wasn’t rotating them often enough.
PaxlovidExperience: As I mentioned in a previous email, I had a pretty bad case of Covid around Christmas time. And to my surprise Paxlovid not only helped my acute Covid symptoms, but it overall made me feel much better than baseline. I was able to confirm this experiment in mid-January when another member of my family got COVID, but couldn’t tolerate their Paxlovid. So as an experiment, I took the remaining three-day course, and again almost immediately my brain fog, executive function, and most neurological symptoms lifted.
Also, and this is where I think we might be able to confirm some of Dr. AI’s suggestions instead of you being humbled by them, I was getting desperate when starting the new job in January and coming off of my case of Covid. So I started throwing pretty much any “energy” and “anti-viral” supplement I had on hand or had short-term success in the past with, to try and get well enough to do a good job at my work. A lot of those herbs ended up on the avoid list on this sample, especially Baicalin, Oregano Oil, and Resveratrol (which is usually mostly Japanese Knotweed).
Other things on the avoid list now I had frequently been taking before this sample: salt (salty electrolyte packets added to water), fish oil, pulses (lots of beans, especially navy beans since those had been a strong Take for a few samples going), and Culturelle (lactobacillus rhamnosus gg) for diarrhea, because I’ve been experiencing more frequent and urgent loose stools since Covid.
My initial impression is positive using Enzymes. The number of under production of Enzymes has been reduced significantly – between 50% reduction to 99% reduction. I am not that concerned with over production, typically the body discard surplus of chemicals (with a very few exceptions). I tend to be more concern over enzyme starvation. Special studies found that Compounds tend to have much weaker relationships than Enzymes. While included, I usually do not over-read the compound significance.
Outside of ranges were interesting — my preferred range Kaltoft-Moldrup, had less in the latest sample (with the numbers dropping with each sample). All of the 3rd party lab results were unchanged. To remind readers on the 3 suggested ranges assumptions:
Outside Lab Range (+/- 1.96SD) – forces on the bacteria analysis the belief that data is a bell curve — very false
Box-Plot-Whiskers – this method was created to deal better with data that is not a bell curve, but with the underlying assumptions of a skewed bell curve. – better but not ideal
Kaltoft-Moldrup – is the bacteria whisperer. It listens to the data and looks for atypical patterns. IMHO it produces the best identification of data of concern.
Conceptually the numbers under 10%ile and over 90%ile should be in the same ratio 1:1. What we see is shown below:
2/2/2023 – 2.4 or 1.7 ratio
11/1/2022 – 0.36 or 0.29
4/11/2022 – 0.2 or 0.15
There was a major change, a flip in ratio with the latest sample. This was seen by the reader.
So is he better? IMHO — yes, the objective evidence is not as strong as I would like to see but:
None of the 3rd party ranges got worse (they remain unchanged)
His microbiome is producing a much richer amount of enzymes — which should cascade into a more balance system
The Kaltoft-Moldrup count continued to drop.
There are several events that adds noise to this analysis:
Going back to work (the fact that he continues to work must be viewed as solid evidence)
COVID and Paxlovid will alter the microbiome
I was unable to find any studies on the impact of Paxlovid on the microbiome 😞
Randomly tossing supplements into the mixture
There were huge differences in lab quality between samples (from 5.3 to 15.3)
Additional Analysis Points
Potential Medical Conditions Detected
The improvement seen in earlier post have persisted
4/11/2022 : 26 items
11/1/2022 : 5 items
02/02/2023: 7 items
Bacteria Deemed Unhealthy
Nothing that is clear, randomness can explain the numbers well.
4/11/2022 : 10 items
11/1/2022 : 15 items
02/02/2023: 12 items
Below we see the extreme %iles (0-9) improving over time. He went from a multitude of bacteria with token amounts to a more appropriate number with token amounts.
2/2/2023
11/1/2022
4/11/2022
2/2/2023
11/1/2022
4/11/2022
Percentile
Genus
Genus
Genus
Species
Species
Species
0 – 9
10
40
93
18
59
126
19-Oct
22
40
19
35
58
22
20 – 29
34
26
19
55
24
22
30 – 39
34
22
11
38
34
14
40 – 49
14
13
14
19
24
21
50 – 59
16
18
11
21
20
13
60 – 69
24
18
12
28
26
26
70 – 79
17
21
13
23
37
19
80 – 89
21
19
12
31
28
16
90 – 100
26
15
16
43
25
24
Going Forward
First thing is that my own experience in a significant ME/CFS flare was lots of swings in the microbiome results as I altered supplements and diet. The analogy that I often use is that the trip from the Port of ME/CFS to the Port of Health is not a straight flight like hoping on a plane (“as the crow flags”) but similar to travelling by a sailing ship that needs to make a lot of tacks (changes of boat directions) because of winds, shoals and reefs. A bad microbiome happens as a result of a long series of minor changes, we need to undo those.
Doing the usual trio of suggestions to build a consensus report.
A specific strain was recommended: Lactobacillus salivarius UCC118, but lactobacillus salivarius (probiotics) was a to-avoid — so I would skip that suggestion. The absence of any probiotics in this top list would inclined me to suggest skipping probiotics for the next round of doing and then testing.
The New Artificial Intelligence Diet (see More information) had #1 being … Cheerios!! — the reason was all of the fortifications added! Being gluten-free, then this is an easy to ignore.
Filtering by Roots, Tubers etc, had low values with only one nutrient contributing. Nuts etc had Sesame being the top item. Other items of note included: Avocado, Barleygrass, Coca (as in source of cocaine – have fun asking for that at your health food store!).
What I find interesting is that vegetable/fruit juice-based diets, is pretty broad. Using the AI Diet, we can likely isolate which food and vegetables are the best choices and may well explain the “why” for the general vague diet term.
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.
Largely recovered. Post exertional malaise (PEM) persists selectively,
I am ramping up my workouts. Weights 10 -15 minutes even if I’m lifting close to max , I have no problems.
Basketball is the kicker.
Using a fit bit watch to monitor found a threshold that impacts severity heart rate. generally tried to stay at 110. Keeping it lower I think netted a less sever crash, but still happened.
My PEM crash starts exactly 5 hours post work out for 24 hours. I played basketball till 5pm, these stats are reflective of me in a crashed state through the night till the following morning.
Experiment: I got the Gammacore vagus nerve stimulator earlier this week and seeing some positive results. Body feel calmer overall. HRV looks better and balanced by fight or flight. My ANS almost always showed as sympathetic dominant . The Gammacore tvns device does seem to help push me to balance a little bit. I feel more social . Have to be careful not to overdo it, I feel like it flares up my allergies. If I hit the sweet spot, I feel more social/chatty and relaxed.
PEM starting to think it could be MCAS. I feel flushed in the face at the 5 hour post workout. I crash , but also get a stuffy nose and then disrupted sleep. Seems allergy like.
Zyrtec and reservatol hasn’t stopped it.
Going to try the cromlyn spray you mentioned. I read it could take weeks to work though?
Dec, 2022 Unfortunately I was unsuccessful and caught the stomache plague . Had to take a couple zofran.
It took me 3 ombré tests to get one that didn’t get rejected. So strange!
Sample Comparison
The past 16 months of samples is shown below. Some general observations:
The number of different bacteria detected is reducing (while sample quality is improving — thus likely a true reduction)
Number of pathogenic bacteria is tending downwards
Bacteria patterns are starting to match some of the patterns from PubMed (i.e. moving into “normal” patterns)
This type of matches is not intended to predict, rather, if you have these conditions then these are the bacteria shifts that may likely contribute to the severity of symptoms.
Going Forward
I am going to build a consensus using the 4 ME/CFS or Chronic Fatigue associated items above in addition to my usual ones – thus 7 sets of suggestions.
Speculation on ongoing Post Exertional Malaise issue
One of my dark fears with ME/CFS is that it will cause epigenetic changes. Epigenetic means that parts of your DNA is turned on or off. Reprogramming such a DNA change is outside of my focus.
There are some interesting studies on MCAS and epigenetics
“In TET2-deficient mast cells, chronic activation via the oncogenic KITD816V allele associated with mastocytosis, selects for a specific epigenetic signature characterized by hypermethylated DNA regions (HMR) at immune response genes” [2022]
“Hypoxia-mediated regulation of mast cell adhesion to extracellular matrix components might be involved in the pathogenic accumulation of mast cells observed in the course of certain diseases including rheumatoid arthritis and cancer.”
“In this manuscript, we investigated the ability of mast cells primed with different stimuli to respond to a second stimulation with the same or different ligands, and determined the molecular and epigenetic drivers of these responses.” [2022]
“This study confirms that epigenetic changes are involved in mastocytosis, and suggests that allergy may be an important epigenetic modifier of the disease. ” [2021]
My current most probable hypothesis is that the higher level of activity with basketball than weight lifting results in more hypoxia (low oxygen levels) when then triggers a histamine cascade which takes some time to clear.
” the secretion of the prestored mediator histamine was increased under hypoxia alone.” [2017]
The logical testing would be taking the following pre-basketball and then at hour 4, to see if they alter the pattern:
Going down the hypoxia path, my favorite experiment to suggest would be:
Oral Heparin (put in mouth for 2-3 minutes and then spit out) with Piracetam. [Heparin-piracetam complex and its effect on blood and blood circulation, 1998], I used it on flights to and from India from the US and had no jet lag or other issues connected to lower oxygen levels in flight.
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.
This weekend I further integrated the microbiome prescription artificial intelligence with the Food and Nutrients database. A common problem is that many flavonoids and other stuff are not well known to most people. On the other hand, most dietician will be clueless on converting the suggestions to menus and food planning. This addition attempts to bridge this disconnect.
Video Walk Thru Below
How do I get to it?
It appears automatically on the usual suggestions page
Clicking will open a new tab so you do not loose your place
It is also on the consensus page
Clicking opens in a new tab
The Artificial Intelligence Dietician
This will open a page with often 2000+ food items
From single suggestions
Clicking on a food group button will filter it — for example, what would be a good fish to have?
Filtered Simple Suggestions
The Benefit Est is based on the estimates from suggestions. For consensus, the numbers will be higher because the consensus weight is not scaled.
Liver and Giblets looks like the best meats
Remember, clicking on the food will show what is in it. Nutrients that are used by the AI are marked with “Significant”
As a FYI on both Retinol and Vitamin A, being in the list. They are the same and yet different.
Vitamin A comes from two sources. One group, called retinoids, comes from animal sources and includes retinol. The other group, called carotenoids, comes from plants and includes beta-carotene
As usual, clicking on column headers reverse the sort order. In this case, classic Norwegian Goat Cheese should be dropped from my diet (with tears)
Sorting to find items to avoid
Walk Thru
A special shout out to people who have been donating to running costs for the site. To get this working smoothly I had to get SSL Certificates for multiple parts of Microbiome Prescription, You should see 🔒 on all of the component sites now (if not, update the link to https://)
As always, having your plans reviewed by a human dietician and/or medical professional is always recommended.
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.
The article below from The Economist, Feb 24, 2023 hints that ChatGPT and similar machine learning programs being used in Medicine will likely kill people “By one estimate, this approach may have caused 10,000 deaths a year in Britain alone.”
Believe it or not, none is expected. Machine learning is not used. We use a very old school fuzzy logic expert system model. Additionally, we make microbiome samples available at http://citizenscience.microbiomeprescription.com/ and give the evidence trail as shown in this video.
This is actually a referral from a person from a previous blog, Another ME/CFS person has gone to Firmicutes!. He shared his experience (see that post) “My energy levels are perhaps the best they’ve been in the last 5 years. I’ve still got a very long way to go but the results thus far are promising!” and a friend decided to try
Back Story
I became symptomatic around 19, progressively got worse so that by the age of 23 I had fully crashed with classic CFS symptoms. Severe symptoms persisted for 5 years during which time I was unable to work due to unrelenting fatigue. Slowly got about 50% better through an extremely low stress lifestyle and dietary/food changes. I’ve tested positive for a few Lyme co infections, chronically low cortisol and pretty much anything else the chronic illness community tests for, I’ve tested and treated. I’m now 38 and my recovery seems to hang at about 40% of optimal capacity. I wake up unrefreshed and have lagging energy all day long. I have to live an extremely low stress life, if I don’t, my sympathetic system kick into high gear. I seem to have issues with histamines (though I can ingest them, I just get flushed, puffy and hot at times), and my fatigue gets profoundly worse around my cycle. I don’t have any significant digestive issues that I’m aware of.
Analysis
The first thing that I should mention is that I recall a study finding that the duration of ME/CFS does not impact the probability of remission. So 19 years with ME/CFS is not a factor.
Dr. Jason Hawrelak Recommendations came in at 99.9%ile, so no pro-forma general issues. That is not unusual, most labs on ME/CFS patients report normal. Looking at the Potential Medical Conditions Detected list, nothing of concern.
Looking at specific bacteria, a few bacteria stand out:
Mogibacterium at 100%ile — i.e. the highest level in over 1000 samples!
Lactobacillus is at 94%ile, a level many people would love to see (for ideological reasons). With ME/CFS, this causes the “D-Lactic Acidosis Claxton” to sound in my mind… D-lactic acidosis is deemed to be a common contributor to ME/CFS. A few past posts on this:
Looking at bacteria distributions we see a good pattern except with the rare bacteria which appear under represented. An ideal microbiome would have the same count in this range. This suggests a well established microbiome, perhaps with a touch of “inbreeding”.
Diving into the species of Lactobacillus interests me. We find just one species dominates, Lactobacillus rogosae. A 2018 review,”Occurrence and Dynamism of Lactic Acid Bacteria in Distinct Ecological Niches: A Multifaceted Functional Health Perspective“, states “All in all, no consistent marker for any pathology or a healthy state is simply defined by a specific proportion of Lactobacillus“. This strain being classified as a Lactobacillus has been challenged [1974] with the suggestion that they may belong to Propionibacterium, a family associated with Acne. We are back to the fuzziness of 16s lab software as well as challenge of RNA/DNA being exchanged between different bacteria.
We have irony here, because the friend was high in Firmicutes and we have 77% of the microbiome in this sample also being Firmicutes with heavy domination of several ones as shown in the Krona chart below
I am inclined to do the customary ones PLUS one just trying to reduce Lactobacillus to build the consensus.
The top items had one little surprise – Cadium! There is a source for this that is also known to be good for ME/CFS – dark chocolate! See Dark chocolate is high in cadmium and lead. Prior studies on ME/CFS found that dark chocolate/ cacao improves ME/CFS symptoms.
The avoid list containing many popular items claimed to help the microbiome (which it does in some cases). Some are obvious with high lactobacillus — i.e. avoid lactobacillus probiotics. lactulose is a key food for lactobacillus.
In short, avoid Lactobacillus and Bifidobacterium probiotics. We want to greatly reduce the Lactobacillus from the 94%ile – it is very likely that d-lactic acid from lactobacillus is responsible for many symptoms. Bifidobacterium INCREASES Lactobacillus which is the opposite of what we want to do. We want to get lactobacillus down as a first priority, later we look at increasing bifidobacterium once it is down far enough.
Q: Is there any reason you chose to focus on the lowering Lactobacillus, as opposed to the Bifidobacterium being low? Is it because the “bacteria deemed unhealthy” table is a more important focus to you than the jason hawrelak recommendations?
A: The medical condition of ME/CFS and Lactobacillus has a long connection to each other. Both “bacteria deemed unhealthy” and Hawrelak are general criteria. Being at the top of Hawrelak’s rating (99+% of people are worst), would imply no issues — you have issues.
Q: Why not focus on the Mogibacterium that’s in the 100 percentile?
A: We could — it was a factor included in the bacteria picked to modify. The list of items is here. Some people go after a single bacteria with a “all other factors be ignored”. For example, Fennel reduces Mogibacterium BUT it also increases Lactobacillus!! The AI algorithm attempts to balance the dozens or substances impact on dozens (or thousands) of bacteria. You are welcome to do it by hand for the 123 bacteria flagged and the several thousand modifiers.
Q: the last question is about interpreting Krona charts. The Krona chart doesn’t seem to provide standard ranges
A: This form of visual display will get extremely busy and confusing with ranges. If you attempt to draw a high range line it will sit over a different bacteria.
Q: So is there any easy way to know when a bacteria is high or low by looking at that chart?
A: Use the hierarchy chart. You can pick one set of ranges at the top of the page. Items that are high (by the selected ranges) are in blue, and low in pink. You can also hand pick bacteria to alter.
On My Profile TabChecking the checkboxes, then clicking Create… allows a hand picked set of targets.
So doing a microbiome test is like collecting the DNA from a bunch of people at a major airport and then asking: Which country did this person originated from according to their DNA. You will find some people that are good matches to an ethnic origin and some people that are “Heinz 57” aka “Mutts”. These people are unclassified — just like some living components are unclassified.
Let us look at my own DNA to illustrate the issue better. The same DNA file was used for ALL of the following charts. Why do they not agree? Simple — thing are done by matching patterns. The reference library determines where matches are done. Every provider use difference reference libraries. There is no universal reference for Human DNA, nor for the microbiome.
From 23 and Me
From Ancestry
and one more site, this one almost causes whip lapse!
FamilyTreeDNA
One site offers the choice of reference library to use and how to match
GEDMatch
GEDMATCH show where your DNA matches historical samples
I look very Irish here
When we drill down to the next level, we see different “species names”
From 23 and meAncestry
Wait — we are talking about where
The above patterns are based on matching to current populations. We really would like older populations. There is a site that does that! My True Ancestry. The same DNA file suggests more UK or southern Germany. We could view this as an illustration between 16s and shotgun reports.
It is interesting to note that this seems closer to Family Tree DNA results shown above.
In some cases, it is not where the ancestors came from BUT where ancestor siblings settled, as in Iceland and the Shetland Island. The same can happen with bacteria identification. All that we know is that some components are shared.
Some people get concerned about finding unclassified stuff in their microbiome sample. This does not happen with some labs because they elected not to report what is not classified. Why? It leads to support calls asking for explanations (which means $$$$ spent for the company).
Labs could create synthetic proprietary names for the unclassified to make the issue disappear — that causes the issue to disappear but really does not help.
Bacteria is like the population of a country or the world. They interbred to some extent
Genetic exchanges among bacteria occur by several mechanisms. In transformation, the recipient bacterium takes up extracellular donor DNA. In transduction, donor DNA packaged in a bacteriophage infects the recipient bacterium. In conjugation, the donor bacterium transfers DNA to the recipient by mating.
So doing a microbiome test is like collecting the DNA from a bunch of people at a major airport and then asking: Which country did this person originated from according to their DNA. You will find some people that are good matches to an ethnic origin and some people that are “Heinz 57” aka “Mutts”. These people are unclassified — just like some living components are unclassified.
If I was picked, the answer is pretty clear for the “genus” that fits me
Which agrees with paper records back to 1500
If we want to get a more precise name, the “species”, then some fuzziness appears
There is a possible misidentification, my father’s ancestors (all lines) records go back to 1600 on an island that is low probability.
Lolland/Falster
The process of giving names to bacteria in the microbiome is extremely similar. For some bacteria (like me) we fit into a nice box. For the person below, the box is not so clear
Would this person be classified as Irish or English
Bottom Line
A wise man knows what he does not know, and what cannot be known.
COVID in February 2021. 37 y.o. Male at the time, athletic/fit. Crossfit x 3 a week, playing football weekly Only mild gastritis prior to Covid. No other health issues.
Moderate severity Covid, lots of symptoms.
And then Long COVID and CFS/ME type of symptoms mostly fatigue, PEM and GI problems (pain, food intolerance, bloating..etc) I’d say it’s a moderate/mild case of CFS/ME. But after 18 months still not back to previous levels, can’t walk too long otherwise i crash. I’d say i am around %75.
We have two samples available, one early in Long COVID and one more recent
2021-10-01
2022-08-17
With this type of information, let us start by comparing them. We are fortunate that both samples are similar read quality which reduces fuzziness. Unfortunately, it appears that the microbiome dysfunction has increased in many aspects. One aspect that it has improved in terms of bacteria with very low counts. We went from 74% of bacteria with low counts down to 51% with low count. Ideally we would love to see the low count to drop to a modelled 15%.
I should note that the increase in some Outside Ranges is likely because many of the ranges are 0 to some amount, hence the older sample had less because it was full of different trace amounts. The same apply to many other criteria, the low abundance of many bacteria skewed the criteria to appear better.
Criteria
Current Sample
Old Sample
Lab Read Quality
5.8
5.9
Bacteria Reported By Lab
393
399
Bacteria Over 99%ile
8
1
Bacteria Over 95%ile
26
21
Bacteria Over 90%ile
42
35
Bacteria Under 10%ile
135
160
Bacteria Under 5%ile
56
108
Bacteria Under 1%ile
9
29
Lab: BiomeSight
Rarely Seen 1%
1
0
Rarely Seen 5%
9
8
Pathogens
30
33
Outside Range from JasonH
10
10
Outside Range from Medivere
15
15
Outside Range from Metagenomics
10
10
Outside Range from MyBioma
8
8
Outside Range from Nirvana/CosmosId
22
22
Outside Range from XenoGene
34
34
Outside Lab Range (+/- 1.96SD)
16
8
Outside Box-Plot-Whiskers
49
43
Outside Kaltoft-Moldrup
147
108
Condition Est. Over 99%ile
18
0
Condition Est. Over 95%ile
38
0
Condition Est. Over 90%ile
50
0
Enzymes Over 99%ile
561
115
Enzymes Over 95%ile
793
282
Enzymes Over 90%ile
866
680
Enzymes Under 10%ile
289
294
Enzymes Under 5%ile
149
149
Enzymes Under 1%ile
29
23
Compounds Over 99%ile
480
50
Compounds Over 95%ile
600
214
Compounds Over 90%ile
677
298
Compounds Under 10%ile
581
315
Compounds Under 5%ile
563
242
Compounds Under 1%ile
548
91
I next went to the Krona Charts to try to understand the shifts better. We see a massive increase of unclassified Bacteroides
2021-10-01 Sample2022-08-17 Sample
Going to sample comparison, we see that (genus) Bacteroides was at the 99%ile on both samples. Looking at members of this genus, we see several of the identified species at high levels
Then create a handpicked bacteria focused on Bacteroides and the high species under it. To express another way: Feed the weak and destitute, Bring down the mighty.
Doing the first step, we see at the top of the consensus:
The hand picked collection is below with percentiles
genus Bacteroides 99
species Bacteroides faecis 93
species Bacteroides graminisolvens 86
species Bacteroides ovatus 99
species Bacteroides rodentium 95
species Bacteroides stercorirosoris 91
species Bacteroides thetaiotaomicron 93
species Bacteroides uniformis 97
species Bacteroides xylanisolvens 100
The suggestions for just these are shown below. The pattern is similar to other peoples suggestions with ME/CFS – lots of specific B-Vitamins, dark chocolate etc:
whole-grain barley
sucralose
Caffeine
Hesperidin (polyphenol)
polymannuronic acid
momordia charantia(bitter melon, karela, balsam pear, or bitter gourd)
Bottom line for probiotics to try (add just one new one a week so you can see the response to each). See Simple Suggestions download below for suggested dosages or look them up on 📏🍽️ Dosages for Supplements. Using too small (almost homeopathic) dosages is a common error – the dosages on bottles are determined for profit margin (repeat business) and not from effective dosages from clinical studies.
I would suggest getting another sample 6 weeks after implementing the above to see what the progress is.
As always, review with your medical professional before implementing.
Bottom Line
This patient history and their microbiome are in agreement. The antibiotics suggestions (off label usage) matches the history.
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.
On Microbiome Prescription we have Look up a modifier of bacteria with many entries. It would be good for everyone if we increase the number of entries especially for atypical items.
YOU can help make it happen!
Find a herb, spice, food, drug of special interest to you
Look at the summary or the full study if available
The study should be on a human or an animal (there is not enough studies to be picky), skip fishes.
Look for bacteria names. We need to know the name and how they shift. i.e.
A Ruminococcus ASV, a Lachnospiraceae Anerostipes ASV, two Lachnospiraceae NK4A136 group ASVs, and a Muribaculaceae ASV were enriched in the vitamin K deficient group, whereas a Bacteroides ASV was enriched in the MK4 group, and a Lactobacillus ASV in the MK9 group.
Then comes the thinking part. Trying to describe the results.
Can you write a sentence such as “Vitamin K may increase Bacteroides and Lactobacillus and a reduce Ruminococcus, Anerostipes ,Muribaculaceae ”
If so, include that in the file sent. (I will verify and it will serve as a double check the reading)
If the study was done on a person (or mouse) with a specific condition, we still include it.
Sometimes you will find that a substance with a common name may have multiple breakdowns.
Ideally, find other names of the substance and search each one.
Sending the Information to Me
I would suggest putting the links (i.e. like https://pubmed.ncbi.nlm.nih.gov/36471554/ ) in a text file or excel and sending to me. Where practical, include a sentence on the impact.
The information sent (when added to database) is available to everyone! This is citizen science! As I remarked to someone earlier today “I do not have a business model, I have a pro bono model“.
Recent Comments