The information below comes from Integrated analysis of gut microbiome and host immune responses in COVID-19 [2022]. While the data comes from COVID patients, there is a good chance that it may apply to other conditions. The items below are for the strongest p-values (most likely). My intent is to add all items with a value with a p Value of 0.05 or less as an experimental page, before creating the page I hope people will find similar studies that can be combined with this data. Please add as comments.
Gut_microbes
Blood_clinical_features
Correlation
Pvalue
Coprococcus_comes
CD8_counts
0.73173549
1.95E-06
Coprococcus_comes
CD3_counts
0.714258257
4.41E-06
Coprococcus_comes
Lymphocytes_counts
0.649787455
5.71E-05
Coprococcus_comes
CD45_counts
0.647009338
6.29E-05
Roseburia_intestinalis
CD8_counts
0.63669604
8.94E-05
Roseburia_intestinalis
CD3_counts
0.619860729
0.00015457
Roseburia_intestinalis
CD45_counts
0.611747625
0.000199038
Streptococcus_oralis
Eosinophil_counts
0.603056198
0.000258997
Gut_microbes
Organ_damage_related_factors
Correlation
Pvalue
Akkermansia_muciniphila
Creatine_kinase_isoenzymes
0.889522704
1.00E-11
Bacteroides_cellulosilyticus
Creatine_kinase_isoenzymes
0.88177523
2.63E-11
Streptococcus_oralis
Gamma_glutamyltransferase
0.788443186
8.39E-08
Akkermansia_muciniphila
Aspartate_Transaminase
0.784368908
1.08E-07
Bacteroides_cellulosilyticus
Aspartate_Transaminase
0.766075518
3.22E-07
Gut_microbes
Cytokines
Correlation
Pvalue
Ruminococcus_gnavus
IL17
0.513431966
0.002652723
Klebsiella_pneumoniae
IFNG
0.484801301
0.004922183
Klebsiella_pneumoniae
IL10
0.431582818
0.01364772
Lachnospira_eligens
IL2
0.393008018
0.026072229
Gut_microbes
Coagulation_factors
Correlation
Pvalue
Enterococcus_durans
APTT
0.358216937
0.044101648
Enterococcus_faecium
APTT
0.357152676
0.044780215
APTT is activated partial thromboplastin time, the time to form blood clots
I started Microbiome Prescription site using data uploads from ubiome, a firm that was founded by a crowdfunding campaign, went to venture capitalists, and went unethical due to pressure from venture capitalists and died. I received over 800 samples processed by ubiome.
Readers started to request the microbiome reports to be processed on the Microbiome Prescription site and I started adding them according to constraints of the reports available. BiomeSight.com, a UK firm, has been the most cooperative. We worked together to allow automatic transfers directly from their web site to the Microbiome Prescription site by using a API.
Xenogene | Metagenómica y Biología Molecular Reports were shared to me. I found that I could do an accurate extract from one of the reports they made available to users. The result was that they became the most comprehensive report as see by the statistics below
There were few uploads because of their higher costs. The report that I used is shown below.
They Changed Their Report
Recently I have had two people trying to upload their reports. The report was different than the above. I asked them to contact Xenogene to get the above; they were not successful. I examined their reports (they were several years apart), and found two different formats, as shown below:
While both give the same information, the structure of the page was different. The report do not give the hierarchy, for example, Eubacteriaceae was found in neither report. I looked for Blautia and could find species and strains — but no total, so you cannot apply Dr Jason Hawrelak criteria.
Summing up all of the species and strains under Blautia does not give a correct total, in some cases the Blautia total will be 2x higher. Why, because many strains and species has not received names and / or “fingerprints”.
Example of the synthesis to higher levels… Issues at the species level and below can be identified
Bottom line: I no longer recommend this lab
Despite these issues, I have updated the import to support both of the above PDF formats and synthesize all of the missing layers of the bacteria hierarchy. The new import should be on line by November 13th.
WARNING: the genus level and above may often be low because of the total synthesis.
I did extract their recommended ranges and added it as an option:
Citizen Science Action
I would suggest emailing them and asking them if they make a CSV file available of the results (including the bacteria NCBI taxon number), if so, can you get a sample. If you do not get a positive results, do a return email asking you to be informed if they change and indicating that you are going to use Ombre or Biomesight instead…… The risk of loosing customers can often change business practice.
I emailed about six months ago with questions. Since then I’ve attempted an evaluation of my microbiome’s needs through a thorough look at your site’s AI suggestions. I attempted to implement some of those, with my primary care’s approval. I didn’t have much luck and I was looking to have another go at it, with a fresh Ombre analysis. I’m formally requesting a review for an educational post. Before I jump back into trying the AI’s suggestions again, I thought it would be foolish if I didn’t seek out the assistance of the one who designed it. I understand there are others in line and you may decline the request, but I appreciate that you are offering this to people. Hope is such a necessary lifeline with CFS.
It feels a little odd to be giving such detailed information about myself without having a firm “go ahead” from you. From what I understand though, you want all the info before you’ll consider the request. I’ll attempt to make it brief. I have also uploaded my symptoms to the website. I consent to your use of my information.
Symptoms
Fatigue
Exaggerated loss of muscle strength with exertion
Brain fog
Trouble reading and comprehending
Post exertional malaise
Constipation
Panic Attacks
-Intolerance to any probiotics, *DAIRY*, caffeine, alcohol, refined sugars, and a growing list of fruits and vegetables.
-Whatever herbs I try there is almost always an initial benefit, but then things go back to the way they were. (Possible bacterial adaptation?)
Diagnosed
“Chronic Lyme”
ME/CFS
IBS-C
Panic Attacks
Depression
~ Backstory ~
Dec 2012 – I had been working multiple full time jobs while eating very poorly. Essentially fasting, and what I did eat was high carb, low nutrient foods. No fruits, vegetables, or other nutrient rich items. I felt something snap in me in an instant. I felt panicky and went and ate a large meal immediately. From that moment on I’ve suffered from CFS. The most prominent features being fatigue, exaggerated loss of muscle strength with exertion, brain fog, trouble reading and comprehending, post exertional malaise, and constipation. My symptoms were the most exaggerated at that time, although recently they have started to get back to that point in time. Examples: I would eat a carb rich food like pasta and 30 minutes later I would literally be on the floor in a quasi lucid state; Two and a half weeks without a BM. My primary care at the time put me on antidepressants and thyroid medications, which did nothing for me.
March 2016 – I started to see an integrative medicine MD who thought that I had reactivated Lyme. He reasoned that it was dormant in my system from when I had it as a 5-6 year old, and that the stress allowed it to manifest itself again. I was on an absurd amount of supplements and various antibiotics. I found initial improvement that I felt stopped my decline and helped with some symptoms, but didn’t solve the CFS. The one drug that I felt the best on was Tinidazole. I stopped seeing him in 2017.
July 2017 – I stopped working as my symptoms had continued to get worse over the years. I started taking care of my sister who was diagnosed with terminal brain cancer. She died in 2019.
July 2018 – Started to see a new primary care. He confirmed the CFS diagnosis but refuses to help in any way. He encourages me to seek solutions on my own however.
Dec 2018 – Started to see another Lyme specialist who told me about the herbalist Stephen Buhner. I bought his book and attempted a slew of his proscribed herbs over the course of a year or two, with little benefit. He also put me back on doxycycline for 6-12 months. It did help but just by taking the edge off of my symptoms.
Fall 2019 – I started to develop panic attacks. It was clear to me that stress made them worse but that it was primarily an issue stemming from a physical problem, rather than an emotional one. This was evinced by the fact that certain foods could manifest them. I felt that whatever my problems were, they were physical and were slowing progressing.
Summer 2021 – I started looking into gut health as a cause of CFS. I started the Wahl’s diet and found some improvement through that. It afforded me enough strength to go back to work for six months. I never entered fully onto the diet as it was prohibitively expensive, but I did keep some of the foods that helped.
2021 – I started to see a gastrointestinal dr. who was absolutely no help. He diagnosed me with IBS-C but didn’t have any answers or solutions. He did proscribe Amoxicillin, which I declined to take as I was not sure if it would help or hurt my gut bacteria.
April 2022 – I found your website, uploaded an Ombre test, and attempted some of the suggested herbs. I found initial benefits from cinnamon but any long-term attempt at any of the herbs is really a trial (and I’m not one to back down from a fight or a stranger to discomfort). I continued on some of them until I thought there might actually be a chance of dying from it. I just couldn’t tell if it was herxing or hurting.
Spring 2022 – Developed food sensitivities, primarily to dairy. Dairy gives me intense psychological issues. The best I can describe them is that they are like racing thoughts accompanied by the feeling that my head will explode and there is no way to escape. Food that once helped, like carrots and berries, now make my intestines feel like overinflated balloons: a lot of pain.
August-October 2022 – I started to care for my mother who was diagnosed with terminal stomach cancer. She died and the stress of it has amplified my already mounting symptoms to a fevered pitch. It almost feels like when things started back in 2012.
This story is unfortunately very typical for many people. My wish is that Microbiome Prescription will be able to help. I do not have “the cure”; what is generated are suggestions (many — so pick and choose what works for you), items modelled to have better than random impact on the microbiome.
First Look at the sample
We have two Ombre samples on the account:
May 2,2022
Oct 18,2022
With two samples from the same lab, my first step is typically to compare them. I omitted the KEGG data which was not illustrative of changes.
Criteria
Old Sample
New Sample
Lab Read Quality
4.2
5.6
Bacteria Reported By Lab
561
677
Bacteria Over 99%ile
2
7
Bacteria Over 95%ile
18
21
Bacteria Over 90%ile
38
43
Bacteria Under 10%ile
92
121
Bacteria Under 5%ile
37
62
Bacteria Under 1%ile
3
11
Lab: Thryve
Rarely Seen 1%
5
8
Rarely Seen 5%
23
54
Pathogens
40
30
Outside Range from JasonH
3
3
Outside Range from Medivere
14
14
Outside Range from Metagenomics
9
9
Outside Range from MyBioma
12
12
Outside Range from Nirvana/CosmosId
21
21
Outside Range from XenoGene
8
8
Outside Lab Range (+/- 1.96SD)
9
40
Outside Box-Plot-Whiskers
67
128
Outside Kaltoft-Moldrup
136
244
Condition Est. Over 99%ile
0
0
Condition Est. Over 95%ile
0
0
Condition Est. Over 90%ile
0
1
My read is that between the samples, the person has gotten worse. Why?
Outside Lab Range (+/- 1.96SD), Outside Box-Plot-Whiskers, Outside Kaltoft-Moldrup all have very significant increases,
This is also reflected in Bacteria Over ??%ile and Under
Not having any strong matches to (PubMed Studies) Conditions is unusual. It suggests that the compounding of issues results in the microbiome not falling into any established “box”.
We see that also with the distributions, a massive surge of under-represented bacteria (0-9)
While he attempted suggestions after the first sample, we see a mountain of microbiome changing events also occurred (especially stress which, for me, has been very significant cause of my own historic dysbiosis). Whether the suggestions helped or hurt cannot be determined.
Approach
Building a consensus fromLab Range, Box-Plot-Whiskers and Kaltoft-Moldrup seems the best approach.
Early Sample
From the consensus we see a list which agrees with what is often reported as helping ME/CFS from the earlier sample.
From Earlier Sample
Some illustrations from the literature of the suggestions
What I did above is called, cross-validation. This means checking if the suggestions generated by the model agrees with clinical experience. It does. This implies that items not seen in studies (like a grapefruit for breakfast) seems likely to have positive effects.
Cross validation is always a good step after getting suggestions. The suggestions using this trio of methods to select will mostly be good — but odd cases may produce poor results.
Example of how to do it
Latest Sample
Given the stress etc. I know that the microbiome will shift and may not be so easy to cross-validate. We see many of the same things, they have just rearrange themselves.
We have the simplified suggestions (shown above) with the to-take probiotics being:
bifidobacterium (animalis) lactis
lactobacillus gasseri
bacillus coagulans (with bacillus subtilis being a very strong avoid).
KEGG suggested Escherichia coli Probiotics — which is to be expected from ME/CFS. A low level of Escherichia coli has been reported in the 1999 Australian Conference papers.
My suggestion would be ONLY bifidobacterium (animalis) lactis (Custom Probiotics has it available as a single species without additives) and E.Coli (i.e. Symbioflor-2 )
The last version of suggestions is a food list derived from flavonoids etc in food. It is an experimental exploration (so a grain of caution is suggested).
The only thing that was positive was Barley which is on the avoid list. So nothing (safe) useful from this experimental method.
As a FYI, I checked for items that are adaptogens (helps with stress) and the following were on the to-take list.
The suggestions often have numbers beside them. The numbers are relative numbers for things in the same list. In simpler words:
One in Metric, – meters
One is Imperial/American, miles
One is Roman, league
One is nautical, knots
One is astronautical – parsec
They cannot be compared to each other. The goal of each list is find the best given the approach.
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 appears to 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.
I use modelling and various mathematical technique to estimate forecasts when there is no hard data available.
This person did his tests using OmbreLabs.com and then transfer the data to biomesight.com.
I did the special studies for a couple months taking symbio, florastor, GOS,Arabox., d ribose, pea fiber, etc.
Feel in general more energized, specially after the round of florastor which I had done just a four days then tested at the time so impact probably won’t fully show in this test. Where to go from here? Drop special studies focus or stay the course?
Why Follow Up Posts are important
The first item is simple, does the model and suggestion appear to work. Everything is theoretically computed, not based on clinical practice or clinical studies. The second item is that these posts encourages people to try suggestions, or to do “self-serve” with the site.
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 appears to 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.
Comparisons between Samples
We will start by adding new columns for the latest sample. The person measured with Ombre and then transferred data to Biomesight to get a second interpretation of the raw digital data.
Criteria
BS 6/6
BS 7/19
BS 11/22
OL 6/6
O 7/19
O 11/22
Lab Read Quality
2.1
5.4
4.2
2.1
5.4
4.2
Bacteria Reported By Lab
280
497
468
365
628
473
Bacteria Over 99%ile
2
7
0
5
6
1
Bacteria Over 95%ile
24
31
2
27
24
9
Bacteria Over 90%ile
49
58
12
49
51
21
Bacteria Under 10%ile
17
62
187
18
60
87
Bacteria Under 5%ile
5
30
90
10
28
46
Bacteria Under 1%ile
0
13
22
1
7
2
Rarely Seen 1%
0
4
0
0
9
0
Rarely Seen 5%
4
18
15
8
40
9
Pathogens
15
25
39
19
28
33
Outside Range from JasonH
4
4
9
7
2
9
Outside Range from Medivere
17
17
20
16
16
20
Outside Range from Metagenomics
7
7
7
7
7
7
Outside Range from MyBioma
9
9
10
14
14
10
Outside Range from Nirvana/CosmosId
22
22
22
23
23
22
Outside Range from XenoGene
6
6
10
11
11
10
Outside Lab Range (+/- 1.96SD)
6
13
2
10
14
2
Outside Box-Plot-Whiskers
70
84
29
64
61
25
Outside Kaltoft-Moldrup
70
113
70
112
182
91
Condition Est. Over 99%ile
1
1
0
0
0
0
Condition Est. Over 95%ile
2
4
0
0
0
0
Condition Est. Over 90%ile
5
6
0
2
2
0
Enzymes Over 99%ile
3
10
1
13
15
5
Enzymes Over 95%ile
46
32
16
69
82
147
Enzymes Over 90%ile
90
51
103
155
411
405
Enzymes Under 10%ile
102
219
354
55
138
169
Enzymes Under 5%ile
45
132
154
22
67
78
Enzymes Under 1%ile
6
47
29
5
2
0
Compounds Over 99%ile
9
7
29
104
126
19
Compounds Over 95%ile
56
76
233
385
397
89
Compounds Over 90%ile
292
313
347
533
548
118
Compounds Under 10%ile
72
125
264
183
248
133
Compounds Under 5%ile
39
64
163
109
127
100
Compounds Under 1%ile
5
21
41
16
17
42
Note: I just cut and pasted from “Multiple Samples” tab to Excel to make the above table.
What do I see above?
Sample Quality are the same (expected from using the same FASTQ file)
Rare and very high bacteria have a significant improvement
All of the statistical out-of-range measures(Std Dev, Box-Plot, K/M) reduced the count significantly.
Most of the expert suggested ranges increased.
Condition profiles dropped to zero.
We see the fragileness of some measures to the software being used to interpret the raw data.
Enzymes Over… one dropped from prior and the other increased from the prior
My general opinion is that the person has improved objectively. The algorithm explicit goal is to reduce all of the statistical out-of-range measures. Ideally, it will also “fix” the person but that is more complex, we lack sufficient knowledge to hand pick the bacteria. We can get associations to specific bacteria — association is NOT causality often (despite many politicians claiming such!).
Going Forward
KEGG Computed Probiotics
Both labs resulted in the same priority: Escherichia coli at the top, the soil based mixtures, then Bacillus subtilis (I personally prefer to get it “au natural”, i.e. in the traditional Japanese Soy based food, Natto).
I am going to skip them, mainly because the results are erratic until I get a better understanding of this. See Caution: Special Studies Suggestions.
There is a possibility of both being right. Right meaning shifting from the current dysfunctional equilibrium. This could be visualize as shown below. I am seeking understanding and building different approaches. Each approach could work for some (but not others). Too many factors for certainity.
Flavonoids: Only Barley was a positive (for Ombre) , it was not on Biomesight list
Food Contents: Again, only Ombre had positive suggestions: Brazil Nuts and Olive Oil. Biomesight data disagreed on the Brazil Nuts
Why so few? Why labs contradict? This comes down to two key challenges: Different interpretation of the bacteria from the digital data; a low volume of studies on the substances we are using to build food suggestions. Also, the suggestions are based on some of the contents of the food; there are other parts of the food that will have other effects. This is why direct food, herb and spice studies are best. Every food is a complex mixture of chemicals. Some may help, some may hurt. Care must be taken to avoid the simplistic logic that “Super Breakfast Food contains barley, thus it is good/healthy to eat!” Ignoring the 10 grams of sugar in this product.
Thus, these suggestions should be taken with a grain of salt. They are better than random choices, but far short of what we would ideally like.
Bottom Line
I ran some of the Special Studies suggestions and did a download of simplified consensus. Between approaches, we had agreement on taking:
Probiotics:
akkermansia muciniphila
bifidobacterium (animalis)lactis
lactobacillus salivarius
saccharomyces boulardii
Other
Vitamin K2
Calcium
Echinacea
Omega-3 fatty acids
Pomegranate
Rutin
Tea Tree oil
As well as agreement on avoiding
fructooligosaccharides (FOS)
jerusalem artichoke
Flaxseed
Vitamin B2 Riboflavin
“This is too complicated” is what I can hear some people saying. This analysis digs into the nature of the data which is really not needed for most people. I am trying to get better understanding. It looks at some of alternative methods of getting suggestions. It is likely of interest to those treating microbiome dysfunctions as it illustrates many of the challenges in interpreting.
For most people, the best process stays the same:
Upload the data
Try several different ways of generating suggestions, building a consensus from
Why is consensus important? Simple, we have very incomplete data and also have limited accuracy with the microbiome tests. Going the consensus approach is similar to using a Monte Carlo Simulation, an appropriate approach to deal with complex processes with many parameters that are fuzzy that produces better results.
The numbers reported on most tests for these bacteria are extremely questionable. The one exception is Xenogene (based in Spain). This can be seen on these summary pages. These bacteria are grossly under reported on 16s tests.
What does this mean for manipulation? If you take Symbioflor-2 or Mutaflor, you may not see any changes in your tests (or they may become worse), when in reality they have taken up residency and are increasing. Either you go and do tests with Xenogene; or you use subjective measurements. My subjective measurement from Mutaflor was a massive severe herx for the first two weeks.
I got messages as shown below, and thought that I should share my thinking and suggestions.
Hi Ken I needed some help from you on some inputs. My mom she is 63 years old and from past few months she is getting recurrent urinary tract infections and she is been taking antibiotics. She takes one antibiotic for Ecoli UTI and next time urine culture shows Pseudomonas and again she takes another antibiotic and another infection starts.
Do you know any good probiotics which are live and multi strains?
I was thinking about sending my mom suffering with UTIs the below 2
So you need to find ones that have been documented to help, and also persists, and last — be able to get fast delivery so they can be sent to India with a friend that is travelling there.
The ones that you suggest may work — but there is no evidence (peer reviewed studies) for them being either effective for UTI or persists. The three above have the best odds of doing the correction. Enterogermina is antibiotic resistant.
Quantity
I would suggest at least a 90 day supply for all of the above. 30 days may be sufficient, but given the challenges of re-supply, it is likely better to be safe.
This email arrived and contributed in two changes:
Warning on using Special Studies — suggestions can be erratic and should not be used if they conflict with the usual consensus building algorithms.
Adding Modelled Food Suggestions — this should also partially address some challenges doing suggestions in Japan
Back Story
Love your work, I have read many of your posts on CFSremission, and based on that and my own research I think your microbiome-based view of ME/CFS is generally correct.
I have been suffering from cfs since 2009, I did a study abroad in South Korea and had a weird fever there, after that I got tired easily, often felt light-headed, head felt hot, but I was able to mostly live a normal life and actually spent a lot of time in the gym. (I think this supports the microbiome theory, my diet changed radically when I went to Korea)
I dealt with the fatigue with regular consumption of coffee/tea throughout the day, often going out drinking at night. I also used to lift weights in the gym almost every day. Full body lifts like squats, deadlifts, etc. During this time I drank about a quart of milk a day as part of my bodybuilding routine. My sleep always seemed unrefreshing.
Then in late 2019 I got sick with a EBV/Mono-type illness, swollen lymph nodes and tonsils, crushing fatigue, sore throat, that lasted a month. Sore throat resolved, but the tonsils were still a bit swollen and the lymph nodes got smaller but seemed to be permanently hard. I thought I might have thyroid issues or cancer, but multiple screenings ruled that out.
I tried multiple times to go back to the gym, but my workouts were poor and I got hit with what I now understand to be PEM the next day. Eventually I had to stop trying to exercise. I’ve tried various supplements such as methyl-b12, doses of tumeric or curcumin, too many to count, then I discovered your website. I think it lines up with my experience and is a good model to explain the so-called “anomalous” way that some treatments work for some CFS sufferers and not for others.
So I am writing this email to you now hoping I can get some insight. I have read your blog posts about other CFS sufferers analyzing their samples, so I hope you could take a look at mine as well. Feel free to use this or parts of it as a blog post, but don’t use my name or email address obviously.
Some background, I had to get a sample manually added from a lab here in japan, based on those suggestions I took two rounds of miyarisan, (I live in Japan, so it was the most easily obtained of the probiotics suggested) as well as added lots of inulin, oats, whole grains etc. to my diet. Similar to some of your other posts, including the suggestions to avoid Vitamin B supplements (the greedy bacteria taking the B-vitamins!) But, I feel like it made me worse. These days my legs are very heavy and tired.
I had another sample taken between the two rounds of miyarisan which i sent to Biomesight (a much better choice.) It took over a month for the results to get back. When they came back, it suggested a totally different course, putting miyarisan and inulin into the strong-avoid category! With the inulin+oats+miyarisan diet, I am more tired and my libido dropped a lot.
So I made a new analysis based on the national and special studies for unrefreshing sleep, ME/CFS without IBS, cold intolerance, general fatigue, etc.
1. As attached, it suggests “alcoholic beverages” pretty high. How should I interpret this? Beer? Wine? Vodka shots every evening? Is there more context for this?
2. Not many foods with any strong suggestions, what can I eat realistically (here in Japan) off this list of suggestions? It suggests a milk diet, but whole milk is not suggested? Seems to have a lot of contradictory suggestions.
3. I decided to go with national + special studies, but the “general consensus” is totally different. I assume the studies are better for my condition?
Feel free to look at the data of both of my samples, or offer a different way of getting a consensus, I really need some guidance here!
Regards,
From a reader (with permission to post)
Initial Impressions
“EBV/Mono-type illness” — EBV, HHV5 and other virus in CFS gives context, but this post, Viral Reactivation and the Microbiome gives context and cites “For EBV, viral load was significantly higher when 25(OH)D levels were low, demonstrating an inverse correlation between 25(OH)D levels and EBV load. ” [2018]. My first step would be to get 25D levels measures (likely low) and 1,25D levels (likely very high). It’s an easy issue to address with Vitamin D3 supplements (likely 20,000 IU/Day may be needed. See the following for more information
My suggestion [2016] for target level is: 90-100 ng/mL (200-250 nmol/L). (of course, to be discussed with your medical professional)
The Key Problem with Suggestions is the picking of bacteria
Suggestions are based on several main factors:
The bacteria you decide to alter (i.e. increase or decrease)
The importance of each (sometimes called weight) when there is a trade off
What substances has had any research. This is a nightmare – between contradictory results, small sample sizes, study done in the context of a specific diseases, etc. This is why I use fuzzy logic.
With the above stated, I walked thru this sample trying to first improve the bacteria selected (using my experience and statistical understanding), and then looking at the suggestions they generate.
This issue can be compounded with the depth of bacteria reported. “The disease is in the small details”. This is why more detailed and comprehensive (i.e. number of bacteria types reported) tests are a better starting point.
Contradictory Suggestions root issue
Facts in the database are based on what is specified in the study. A simple example: one study may use turmeric and a different study used curcumin. Curcumin(diferuloylmethane) is a main component of turmeric, but it also contains two other compounds demethoxycurcumin, and bisdemethoxycurcumin. In addition, volatile oils (tumerone, atlantone, and zingiberene) [Antiinflammatory Herbal Supplements, 2019]. The studies may result in a bacteria increasing in one and decreasing in the other. Both are right! It is the additional components that are significant. The worst case of “fuzziness” is with anything that has the word “diet”. Many people offering advice will deem them to be the same to simplify the facts that they need to remember; Dr. A.I. does not need to simplify — but that comes at a cost of confusion when things seem similar at a high level to the user. Another example: lactate, lactose, versus milk.
Analysis
Going to the My Profile / Health Analysis page, we see the two items that where he is at highest percentile (98%ile and 99%ile) are related and would agree with unrefreshing sleep.
Sleep Apnea
Insomnia
ADHD is high, but that seems common with ME/CFS. Dr. Jason Hawrelak Recommendations come in at the 89%ile. Going over to special studies, we see a lot of matches. The matches are not predictive — there are other factors (like DNA/SNP) before symptoms appear. They indicate simply increased risk.
The majority of probiotics are to be avoided (not unusual for ME/CFS). The top suggestion was lactobacillus casei which is an easy one to get in Japan. The well studied one is sold as Yakult. The next ones are: lactobacillus gasseri, bifidobacterium breve. With most of the probiotics being negatives, you do not want to get them in probiotic mixtures.
Most pre-biotics are to be avoided.
In terms of vitamins, we see most of the B-vitamins are suggested (this is seen in one subset of ME/CFS patients, a different subset has it as an avoid). Vitamin D is a very mild avoid — but given the EBV issue above, I would ignore it and make that judgement call based on blood tests.
This also may apply to B-vitamins — none of the B vitamins are strong avoid, so a B-Complex is fine.
I have filtered the rest of the list to only the to take, coffee is sitting high in the list which appears to agree with “I dealt with the fatigue with regular consumption of coffee/tea throughout the day“. It helps in additional ways on shifting the microbiome.
There are a few items not in the simplified list that are worth calling out:
bacillus subtilis natto (probiotics) – is in the Japanese desert food called Natto. (it is a bit of an acquired taste [I have acquired that taste] and usually found only in some Asian markets in the US). Nattokinease is an extract from it.
ME/CFS without IBS – 7 bacteria matched – We get good agreement with the above
From ME/CFS without IBS
Comparing Suggestions from Special Studies
As a result of this email (and several others received this week), I looked at Special Studies suggestions for some specific people. My expectation when I did special studies was that the suggestions would converge tighter — so some people that is true. For other people, like this person is it false. For more information read the blog post: Caution: Special Studies Suggestions
I noticed that most of the results had inulin, etc – which are to avoid above and appears to make the person worse.
Chronic Fatigue Syndrome (CFS/ME) – 52 bacteria some agreements and some disagreements
Unrefreshed Sleep — 62 bacteria matched
ME/CFS without IBS – 94 bacteria matched
I will be using this person sample to experiment with revised algorithms for Special Studies.
Probiotics
The top probiotic from KEGG data are E.Coli probiotics. Both Mutaflor and Symbioflor-2 (commercial E.Coli probiotics) are on the to take consensus list.
This was an unexpected frustration. I wait back to the algorithm and made it less conservative. By this I mean, not eliminating items where there are contradictory results from studies. This resulted in in more suggestions, some Japan specific [there are 50 items acquired in Japan on the list]
I was going to leave the algorithm with the more relaxed condition. I then did cross-validation with the consensus and found that most of the items appearing as take using the relaxed filter were on the avoid list of the consensus. Tofu, which showed up with the strict criteria, is on the consensus to take list (as in Soy).
Why do we have any disagreements? The root problem is not sufficient studies – often with contradictory results — one may be on people with diabetes and another people with asthma. Existing conditions (and in some cases severity) can result in difference response. The microbiome is not a machine but a complex society that interacts with a lot of things
The Hail Mary Exploration
I redid the consensus and included prescription items. For many people, the pharmaceuticals are way down the to take list. Herbs and probiotic having a higher positive weight often. For this person, this was not the case. What was also unusual was none of the antibiotics that are recommended in other ME/CFS analysis (and which are used for ME/CFS – i.e. cross validation) are anywhere near the top of the list. What I found listed near the top of the pharmaceuticals were:
My immediate, due diligence, suggestion is to get testing for cholesterol, hepatitis and fungal infections. Was the “EBV/Mono-type illness” perhaps hepatitis? Two of these can result in chronic fatigue. In terms of special studies, ME/CFS (three variations) were poor matches (one was the bottom of the list). Using US National Library of Medicine studies, he is at the 29%ile.
What I find interesting is that soy is a recommendation, and we find these studies..
In terms of having the typical microbiome for someone that has a ME/CFS diagnosis — he does not match. He is also at the 0%ile for hypercholesterolemia (High Cholesterol), 8%ile for GERDs (usually common for a subset of ME/CFS).
My gut feeling is that he was not sufficiently tested before the ME/CFS label was slapped on him. His microbiome is not a match. Nothing match his symptoms to the microbiome associated conditions that I have data on.
FEEDBACK FROM READER AFTER READING
Those are very interesting points. Since my initial symptoms in Korea, I was diagnosed with Gilbert’s syndrome, an excess of Bilburin. I did get my liver checked (due to slight yellowing of the eyes) out but they don’t seem to have found anything (Over a decade ago so my memory is pretty spotty.) I think over the years in college I got MRI’s and various bloodtests with obviously no real diagnosis. Even so, my life was very active over that decade. I lived in China for a few years, frequently attended the gym, also did a fair share of partying, have always had a big appetite. Minimal impairment throughout my life overall.
Since getting sick a few years ago in Japan, I got a lot of different tests, including thyroid and diabeties. If I rifle through all the different result sheets (I have quite a few), a few things of note:
Dec. 2020 I was positive for EBVVCA-IgG which my doctor told me meant that I had had EBV in fairly recent past. No treatment was suggested.
Feb.. 2020 I had slightly elevated liver enzymes (ALT, GTP) (Not surprising given my frequent social drinking in my 20s) which persisted until April 2021 and seemed to have resolved. This was explained by lowered alcohol consumption. Never received a suggestion for follow-up or differential diagnosis.
Persistently higher tryclycerides (I have gained some weight since my illness, matches with the atorvastatin suggestion!) and CRP indicating inflammation. Suggested to lose weight and exercise (The latter being somewhat problematic for me.) Back in my weight-lifting days, I drank lots of milk and overall had a high-fat/protein diet. Since I recently stopped drinking so much whole milk, I wonder if that will resolve it or not.
Before I moved recently I had been going to a cfs clinic which conducted sleep studies (of which I have had several over the years, indicating that I do not have sleep apnea, although that was my thought for years.) and did some other tests indicating I had high stress/inflammation. He gave me vitamins, CoQ10 (which I ordered myself) and anti-depressants for sleep. (Interesting I score high for Depression (47%) but up until the last few years I had a very active lifestyle, I don’t think depression fits my physical symptoms at all. I’ve always been very social and generally on the adventurous side. Still am, just don’t have the physical stamina I used to. I requested a prescription for Piracetam (all of the -tams were recently regulated in Japan) and he refused.
I haven’t gone back there since as I felt like the approach he had was very symptoms based and surface level. Reading your recovery stories, I pretty much ruled out getting any kind of prescription anti-biotics or being able to utilize those out here. I don’t know how the legal system works here in Japan, but my own and other anecdotal experience tells me that doctors here don’t enjoy doing things off-label, it’s an extremely by-the-book conservative approach to medicine. Fortunately, if you have a specific, known medical problem, you can get extremely professional and competent care here.
It is very interesting that I do not fit in the ME/CFS microbiome profile. An infection with Hepatitis or a fungus at some point could fit, especially given that I’ve spent time in a variety of different environments. I think I could easily get tested for Hepatitis here, it will just have to wait until next month (Currently very busy as a **** .) As far as fungus goes, usually I hear about “Candida,” any suggestions of what kind of fungus I should perhaps be looking out for would be helpful.
I will have to think about how I will go about getting tested for fungal infections here, it is somewhat difficult to explain my issues to doctors and get them to take it seriously. Definitely a good idea to also pursue a potential alternative diagnosis though, the data certainly doesn’t rule it out.
You have given me a lot to think about, thanks again for all of your consideration!
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 appears to 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.
I use modelling and various mathematical technique to estimate forecasts when there is no hard data available.
I have been in dialog with a microbiome testing firm on incorporating my suggestions engine into their site. One of their requests was to provide more information on foods. Of course, if there are no studies than how can you make suggestions?
It is possible to model likely impact of foods by looking at what is in them. That information is available from:
So the process using existing pubmed studies to identify the constituents of the food that impacts certain bacteria and then aggregate these constituents to get a modelled benefit from the food.
The results are two tables (depending on which decomposition approach is used).
This is on the Changes Tab
This lists only things that are entirely one way or the other.
Appears to Cross Validate
I did some of the other suggestions methods, built a consensus report and then looked for Almonds on the same sample and found agreement. Same with Barley, Basil, and Buckwheat. Some suggestions from the second list have disagreements (not unexpected).
I would suggest that that you see how it works for your samples between these two approaches.
For your amusement, the second list is LONG (typically 800+ items) and for those that drink wine, may be amusing to scan..
Other Labs
This has been added to the define suggestions page. Both buttons open the suggestions in new windows so it is easy to switch back and forth.
If you have already uploaded a sample, a link has been added there.
Special Studies are a conceptual thought experiment. The logic is simple, identify the bacteria that are have major statistical significance from the reference. Then use these bacteria with the weight that each has being the z-score to generate suggestions.
The first reviews that I did using them had good results and agreement with my preferred trio to build consensus, namely:
This last week I have gotten several emails from people who got counter-indicated suggestions. I have verified that for their samples, it produces contrary suggestions.
Digging into the mathematics and fuzzy logic being used, I see several possible failure points that I want to slowly investigate. The top failure points are:
Using the z-score for the weight to give for each desired shifts. A different formula may resolve it. Two candidate formula are:
z-score * incidence of bacteria being seen
z-score * function(bacteria count) — with many possible functions
The z-score cut off is too low, I am using 5.0 at present, it may need to be raised to a higher value.
The criteria for picking a bacteria to include may not be specific enough, so a lot of bacteria that are fine are included. This can result in excessive noise in the suggestions
The data available for suggestions at the species levels that we are working are insufficient (and in some cases, may not exist). A lot of the species flagged are rarely seen in studies showing changes.
Bottom Line
Use the suggestions generated with great caution. If they compliment the suggestions from the three preferred consensus methods listed above — good. If they contradict, keep to the original consensus method — I have been getting consistent report that they work. The special studies suggestions are getting inconsistent results.
A special study with a z-score below 6.6 is very suspect and should be ignored.
A reader contacted me over a new post on Biomesight – How to reduce brain fog. He was concerned over the content (knowing that I have often researched and posted on brain fog), so I am doing this post to provide some clarity on brain fog. (Bad pun: Remove some fog from brain fog)
What is Brain Fog?
The term brain fog is a vague term that has been defined in the literature as a combination of the following more accurate (and measurable by tests) conditions. A better term is executive dysfunction [2015] or Cognitive Fatigue [2014]. The literature goes back to at least 1989. I know from personal experience, I have taken them from professional psychologist, and other in the family has too.
Some people will perform badly on all tests, other will perform poorly on certain tests only.
IMHO, if you do not have the majority of the above, the term may be misapplied.
For different diseases, what constitues brain fog can vary, for example:
The clinical picture typically affects visuo-spatial immediate memory (g = − 0.55, p = 0.007), reading speed (g = − 0.82, p = 0.0001) and graphics gesture (g = − 0.59, p = 0.0001). Analysis also revealed difficulties in several processes inherent in episodic verbal memory (storage, retrieval, recognition) and visual memory (recovery) and a low efficiency in attentional abilities.
Many of the above have distinct microbiome signatures and thus the hope of getting a universal microbiome signature for brain fog is an ideological belief. This appears to be confirmed in the analysis from Special Studies … Brain fog strongest z-score is just 5.2. This is lowest significance level of 26 items evaluated, the next lowest is General Fatigue. IMHO, there may be no true significance, the z-scores numbers were not adjusted for False discovery rate and incidence of reporting.
Most people will agree that there is no magic cause or microbiome signature for general fatigue — it could be an issue with iron levels, excessive lactic acid (impairment in clearing it), blood circulation issues, respiratory issues etc.
Brain fog could be described as mental fatigue and thus the same wide variety of issues can be involved. For ME/CFS, the dominant causes for brain fog, according to the literature are mentioned in some of my prior posts:
My first concern is simple, the belief of there being a common microbiome pattern is very questionable. There are likely patterns, for example, a microbiome pattern that results in higher d-lactic acid production; a pattern that results in lower d-lactic acid production; a pattern that inhibits one of the many steps in the coagulation cascade; a pattern that overloads one of the many steps in the coagulation cascade; a pattern that causes vascular constriction; a pattern that cause inflammation; a pattern that inhibits the absorption of iron…and on and on. There is not a single pattern that applies to all.
When a statement like this is made “Unsurprisingly, high ethanol producers in the gut based on research findings (separate from what we are seeing from the Biomesight dataset) is associated with brain fog.” I would expect links to these research papers to be included for the reader to follow up. Ethanol is drinking alcohol, booze – which has me very curious about the links and especially if they are seen with many of the conditions cited above.
How does special studies compared to Biomesight post
The table below shows no agreement between my special studies and their findings. We used different statistical process, but finding not a single agreement should be a red flag on relying on the data. While I have a smaller sample (approximately 1/3), the data processing to get the microbiome data was identical.
Bacteria
BiomeSight Post
Special Studies Z-Score
Escherichia coli (species)
5.3
Lactiplantibacillus pentosus (species)
5.1
Shuttleworthia (genus)
5.1
Escherichia (genus)
4.5
Veillonella (genus)
4.4
Veillonella dispar (species)
4.4
Staphylococcus pseudolugdunensis (species)
4.2
Clostridium cellulovorans (species)
4.1
Class Deltaproteobacteria
X
Species Bacteroides uniformis
X
Species Bacteroides cellulosilyticus
X
Species Phascolarctobacterium faecium
X
Genus Bacteroides
X
Species Anaerotruncus colihominis
X
Species Faecalibacterium prausnitzii
X
Genus Prevotella
X
Bottom Line
I do not believe that we can aggregate all microbiome samples reporting brain fog into a single set and find a universal pattern to address a priori. The numbers from Special Study: Neurocognitive: Brain Fog were the weakest of all special studies and, based on some other recent work in progressed, results may be adversely affected by sampling bias, sample quality, and false detection rate.
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