Fungi and the microbiome finally got on my radar. Apologies to some, but there is a lot of different items on the microbiome radar screen.
“Small intestinal fungal overgrowth (SIFO)… Two recent studies showed that 26 % (24/94) and 25.3 % (38/150) of a series of patients with unexplained GI symptoms had SIFO. …. but evidence for eradication is lacking.”Small intestinal fungal overgrowth [2015]
As I did with taxa years ago, I will be writing a blog on each one reviewing the literature. If there is sufficient data at the end, I may add it as a feature to Microbiome Prescription. See also:
One of my reader’s results motivated this choice. The data from a Thorne Microbiome Test. Almost 17 out of 20 people have less of it. The person also has a Crohn’s diagnosis (with SIBO and IBS earlier).
Preventive for Fungi
The following are suggestions:
Reduce and keep your living space humidity at 50% or lower (typically done by dehumidifiers). EPA recommends 30-50% [EPA]; we set our dehumidifiers for 35%.
Ergot alkaloids are highly diverse in structure, exhibit diverse effects on animals, and are produced by diverse fungi in the phylum Ascomycota, including pathogens and mutualistic symbionts of plants. These mycotoxins are best known from the fungal family Clavicipitaceae and are named for the ergot fungi that, through millennia, have contaminated grains and caused mass poisonings, with effects ranging from dry gangrene to convulsions and death. However, they are also useful sources of pharmaceuticals for a variety of medical purposes.
“Different research found that Cordyceps militaris extract suppresses dextran sodium sulfate-induced acute colitis in BALB/c mice by suppressing disease symptoms such as body weight loss, diarrhea and gross bleeding. The extracts prevented shortening of the colon and crypt length and the epithelial damage” [2011]
“Moreover, recent studies have shown that Cordyceps pruinosa extract is a inhibitor of NF‐ κB activation and can enhance weak immune functions. Based on these facts, I hypothesize that Cordyceps pruinosa extract may thus exert its therapeutic effect on IBD by regulating NF‐κB activity and improving impaired immune functions” [2009]
Bottom Line
This is an interesting fungi with little known ill-effects and some potential good effects for IBD and colitis. Thorne does not identify the genus leaving us with more uncertainty. With no clean human adverse effects (apart from Ergotism this is specific to some members of this family only).
There are two types of ergotism. The first is characterized by muscle spasms, fever and hallucinations and the victims may appear dazed, be unable to speak, become manic, or have other forms of paralysis or tremors, and suffer from hallucinations and other distorted perceptions.[16] This is caused by serotonergic stimulation of the central nervous system by some of the alkaloids.[16] The second type of ergotism is marked by violent burning, absent peripheral pulses and shooting pain of the poorly vascularized distal organs, such as the fingers and toes,[16] and are caused by effects of ergot alkaloids on the vascular system due to vasoconstriction, sometimes leading to gangrene and loss of limbs due to severely restricted blood circulation.
Unless there are symptoms of ergotism, I would suggest ignoring it. Some genus may do good and other may do harm. We lack sufficient information and I do not advocate taking action without evidence to warrant it.
Fungi and the microbiome finally got on my radar. Apologies to some, but there is a lot of different items on the microbiome radar screen.
“Small intestinal fungal overgrowth (SIFO)… Two recent studies showed that 26 % (24/94) and 25.3 % (38/150) of a series of patients with unexplained GI symptoms had SIFO. …. but evidence for eradication is lacking.”Small intestinal fungal overgrowth [2015]
As I did with taxa years ago, I will be writing a blog on each one reviewing the literature. If there is sufficient data at the end, I may add it as a feature to Microbiome Prescription.
One of my reader’s results motivated this choice. The data from a Thorne Microbiome Test. Almost 9 out of 10 people have less of it. The person also has a Crohn’s diagnosis.
Preventive for Fungi
The following are suggestions:
Reduce and keep your living space humidity at 50% or lower (typically done by dehumidifiers). EPA recommends 30-50% [EPA]; we set our dehumidifiers for 35%.
“The black yeast E. dermatitidiswas detected in 47% of the dishwashers, primarily at the dishwasher rubber seals, at up to 106 CFU/cm2“
“Eighteen percent of all of the washed items were contaminated with fungi, irrespective of the type of material they were made from.”
“Exophiala species are common environmental fungi often associated with decaying wood and soil enriched with organic wastes….Phaeohyphomycosis caused by Exophiala species has been reported in both normal and immunosuppressed patients.” [Mycology]
E. dermatitidis is, among other species, a common colonizer of the respiratory tract of patients with CF [2018]
“predisposing factors for E. dermatitidis infections are diabetes mellitus, steroid medication, concurrent bacterial and fungal infections and nutritional deficiencies” [2018]
“Immunosuppressed and elderly patients suffer from infections with E. dermatitidis most commonly in the form of phaeohyphomycosis, keratitis or chromoblastomycosis;”[2018]
“Fatal brain infections caused by the neurotropic E. dermatitidis occurred in otherwise healthy individuals in the Asian population” [2018]
Fungi and the microbiome finally got on my radar. Apologies to some, but there is a lot of different items on the microbiome radar screen.
“Small intestinal fungal overgrowth (SIFO)… Two recent studies showed that 26 % (24/94) and 25.3 % (38/150) of a series of patients with unexplained GI symptoms had SIFO. …. but evidence for eradication is lacking.”
As I did with taxa years ago, I will be writing a blog on each one reviewing the literature. If there is sufficient data at the end, I may add it as a feature to Microbiome Prescription.
One of my reader’s results motivated review using Xenogene (ES) and Thorne (USA) reports that have been shared. The data from a shotgun test by Thorne had this being the highest fungi. They reported the percentile ranking of over 90%ile (i.e. 9 of 10 people who has this fungi, has less). This was their highest percentile and of concern is that this specific fungi is associated with Crohn’s disease which they have (as does 26 other people who have spared their microbiome test results).
Basic Information
Overview: The Malassezia Genus in Skin and Systemic Diseases [2012] which cites “A common characteristic of systemic infections of Malassezia yeasts in adults is the existence of a central venous catheter and total parenteral nutrition . Hematologic malignancies, cancer, and Crohn’s disease were the background of Malassezia systemic infections. ”
“the presence of Malassezia had significant consequences on the outcomes of Crohn’s disease models.” [2021]
“Pyrithione zinc kills Malassezia and all other fungi, and is highly effective against the Malassezia species actually found on scalp” [2005] – but that is a topical treatment.
Cinnamomum cassia – Best: a.k.a. Chinese cinnamon,
Rhus javanica (next): a.k.a. Chinese Sumac “Rhus javanica Linn, a traditional medicinal herb from the family Anacardiaceae, has been used in the treatment of liver diseases, cancer, parasitic infections, malaria and respiratory diseases in China, Korea and other Asian countries for centuries.” [2015]
” The mycobiota of CD patients were characterized by an expansion of Malassezia and a depletion of Saccharomyces, along with increased abundances of Candida albicans and Malassezia restricta. Malassezia was associated with the need for treatment escalation during follow-up”
“The two patients whose IBD was active at the time of initiation of treatment had complete clinical and endoscopic response after 6 and 9 months of itraconazole treatment respectively …they were able to withdraw immunosuppression and anti-TNF-α therapy during the entire itraconazole treatment course and the time to relapse in two of the Crohn’s patients was at least 10 months post-itraconazole therapy
The Montreal Heart Institute[2022] is sponsoring a clinical trail on terbinafine and itraconazole to treat Crohn’s Disease.[Website][WHO Trial Information]
Bottom Line
This attempts to summarize the current information on Malasseziaceae.
Preventive for Fungi
The following are suggestions:
Reduce and keep your living space humidity at 50% or lower (typically done by dehumidifiers). EPA recommends 30-50% [EPA]; we set our dehumidifiers for 35%.
This is a continuation of Bacteria interacting with Bacteria thread looking at proforma analysis methods and suggesting better processes. My orientation in clinical treatment. When I read a paper such as the one quote below, I roll my eyes. We know Bifidobacterium is less but how much less is needed in an individual sample is unanswered. Similarly which strains or species are shifted is unanswered.
We identified phylum- through genus-wide differences in bacterial abundance including decreased Firmicutes, increased Bacteroidetes, and decreased Bifidobacterium in the microbiome of AD participants.
I run a citizen science site where many people(2100+) have uploaded their samples (5200+ – usually 16s) and a significant number(1900+) have annotated their samples with symptoms. Walking down the same Chi2 path as I did with bacteria, we get some potentially interesting insights. I am a statistician by training and work experience.
General Approach
We look at the number of bacteria with low/high bacteria with a specific symptom (say 300 reports) and compare it to others. What others is can be one of the following:
Those reporting symptoms but not this symptoms (leaving 1600 samples)
All people without this symptoms (leaving 4900 samples).
My experience is that having significantly more samples results in higher Chi2 values despite the others including some with the symptoms. Conceptually, we may have a lower Chi2 value because of this.
For our example symptoms, Neurological-Audio: Tinnitus (ringing in ear) with 433 samples with this annotation. The table below shows the average percentile ranking.
Tax Name
Tax rank
Tinnitus Mean
Others Mean
unclassified Herbaspirillum
norank
50.3
22.6
Lacrimispora saccharolytica
species
78.1
53.1
unclassified Sutterella
norank
31.1
52.6
Collinsella tanakaei
species
60.1
43.0
Prevotella paludivivens
species
32.9
48.7
Proteus
genus
61.6
46.0
Desulfonatronovibrio
genus
54.2
38.8
Tepidimicrobium xylanilyticum
species
62.3
47.1
Prevotella oralis
species
37.7
52.5
Bifidobacterium gallicum
species
33.1
47.9
Bifidobacterium adolescentis
species
36.7
48.8
We are going to use Bifidobacterium gallicum (NCBI 78342) because of the number of samples(1400+) reporting it. What we got is below. From this we can infer odds such as:
Below 22%ile levels is a double the risk of having Tinnitus
Below 9%ile levels is four times the risk of having Tinnitus
Percentile
Expected
Obs
Chi2
1
0.79
13
190.6
9
7.11
29
74.1
10
7.9
30
68.7
22
17.38
40
37.7
31
24.49
45
24.9
36
28.44
49
23.2
47
37.13
51
9.8
49
38.71
52
8.9
50
39.5
53
9.2
51
40.29
54
9.5
52
41.08
55
9.8
53
41.87
56
10.1
54
42.66
58
12.0
55
43.45
60
14.0
56
44.24
61
14.4
62
48.98
62
9.1
63
49.77
63
9.5
64
50.56
65
11.5
68
53.72
66
8.8
69
54.51
66
7.8
71
56.09
67
7.3
72
56.88
68
7.8
73
57.67
69
8.2
75
59.25
71
9.3
78
61.62
72
7.9
79
62.41
74
10.2
86
67.94
75
5.2
91
71.89
76
2.6
93
73.47
77
2.4
96
75.84
78
1.5
99
78.21
79
0.8
Looking at a bacteria that is available as a probiotics, Bifidobacterium adolescentis (NCBI 1680) and plotting the Chi2 against the percentiles we find that the probability of having Tinnitus has a threshold around 70%ile, or in percentage terms 0.43% of the microbiome. Y axis is Chi2, X axis is the percentile of others.
Each of the above taxa are contributor to the risk of Tinnitus without any being the single cause.
We have 79 of 433 samples annotated with Tinnitus (18.2%) having Bifidobacterium adolescentis. With non Tinnitus we have 2395 out of 4800 samples (49.9%) having Bifidobacterium adolescentis suggesting that not having Bifidobacterium adolescentis is a significant risk factor for developing Tinnitus.
We have a well studied taxa as a key candidate, Bifidobacterium adolescentis. Let us look at this 2022 article, The Role of Gut Dysbiosis in the Pathophysiology of Tinnitus: A Literature Review (tinnitusjournal.com) which cites “It has been previously described that the presence of tinnitus is related to the decrease in inhibitory neurotransmitters such as GABA and an increase in excitatory neurotransmitters. Besides, the increased GABAergic inhibitory neurons and decreased excitatory responses have been successfully reported to prevent tinnitus, proving the role of neurotransmitter modulation in tinnitus.”
This suggests that an appropriate clinical trail of a Bifidobacterium adolescentis that is both human sourced and a high GABA producer should be done. Ideally with good persistence probability. A further key factor is to determine the pH value for people with tinnitus since studies have shown that the amount of GABA production is deeply influenced by the pH.
We have a lots of other taxa to investigate.
Bottom Line
Using Chi2 and percentiles of samples seem to be different sides of the same coin. The information gleamed from using this approach may often have direct clinical consequences, i.e. for Tinnitus, taking Bifidobacterium adolescentis probiotics and making diet changes to support this bacteria.
The key aspect of this post is not Tinnitus but methodology. From existing data, a lot more items with statistical significance can be extracted.
We have a small number of samples annotated with this condition. From this our candidate bacteria are shown below. Almost all of the significant ones are excess counts.
This is from a special analysis identifying bacteria that are probiotics that have association to histamines and mast cell issues using the 394 annotated samples contributed.
Some species are to be avoided. Keeping to the specified species is strongly recommended,
Tax_Name
Tax_rank
Symptom Frequency
No Symptom Frequency
Suggests
Bifidobacterium adolescentis
species
33.5
48.8
Take
Bifidobacterium pseudocatenulatum
species
8.9
7.7
Avoid
Lactococcus
genus
42.9
55.6
Take
Bifidobacterium gallicum
species
18.8
27.7
Take
Bifidobacterium kashiwanohense PV20-2
strain
10.7
20.3
Take
Bifidobacterium indicum
species
27.4
39.8
Take
Bifidobacterium
genus
83.8
94.4
Take
Bifidobacterium catenulatum subsp. kashiwanohense
subspecies
13.7
21.9
Take
Bifidobacteriaceae
family
85.3
95.4
Take
Bifidobacteriales
order
85.5
95.4
Take
Lactobacillus rogosae
species
22.8
26.6
Take
Bifidobacterium bombi
species
13.7
21.3
Take
Lactobacillaceae
family
91.1
96.7
Take
Lactobacillus iners
species
10.2
14.1
Take
Bifidobacterium subtile
species
22.6
26.8
Take
Lactobacillus
genus
83.2
89
Take
Bifidobacterium thermacidophilum
species
12.2
14.7
Take
Lactobacillales
order
97
100
Take
Lactococcus lactis
species
14
18.3
Take
In terms of bacteria patterns found, the following were found statistically significant
Bacteria are like people, they interact and are influenced. The problem is how to detect the interactions that are clinically significant and the direction of interaction without grabbing stereotypes (i.e. all Italians belong to the Mafia, Irish are lazy, Egyptians are all Islamic Terrorists, etc).
From a collection of samples, we pull all samples that report both bacteria. We take these numbers and drop them into a tool like Excel. Chart the data and try to do a linear regression. This is often pro-forma in research papers because that is rote learning.
A Uniform Way
This is almost the same, except we do not use the actual numbers, but the percentile rankings. This produce stronger regressions values Using the percentile transform the data to a uniform distribution. R2 increased by 10 fold but really a long away from significance.
You can almost see signs of a trend in the middle of lots of noise.
A Non-parametric Way
We use classic Chi2. The process is simple
For bacteria A we determine the percentage with a value of 100 or higher, say 5%
For bacteria B we determine the percentage with a value of 1000 or higher, say 5%
We filter the samples to those with bacteria A being higher than 100
If there are no interactions than we expect 5% of bacteria B to be 1000 or more.
If we find that 30% of bacteria B is more than 1000, then it appears that high Levels of A results in higher levels of B
From the above we can compute a statistics,Chi2, and thus the statistical significance. In this case, very very significant.
This means that we isolate the impact of high values and low values which the earlier methods did not do, We do not know how the middle value interact but for clinical issues, it is abnormally high and abnormally low values that are of interest.
Implementation
The first question is to pick the high and low threshold values. People can pick arbitrary values and try them. I have my own preference a patent pending algorithm to produce ranges.
The number of calculations to be done were done in the following datasets with 5%ile and above, and 95%ile and above. The bigger the sample, the better sensitivity and more interactions likely to be discovered.
All: 5,191,562 possible pairs on 5189 samples –> 1,270,000+ Interactions found
Biomesight: 1,717,410 possible pairs on 2534 samples –> 275,000+ Interactions found
Ombre: 1,743,720 possible pairs on 1540 samples –> 220,000+ Interactions found
uBiome: 132,860 possible pairs on 791 samples –> 4,700+ Interactions found
For each pair of taxa we have 4 scenarios (Low versus Low, Low vs High, High vs High, High vs Low) Or about 32 million queries retrieving data sets and performing calculations. The bigger the sample size, the more items that are likely to be identified. For thresholds, we use a patent pending algorithm that appears to yield good results (shown above). The alternative would be to enumerate percentages and find the ones that work best (so 100 x 100 x 32 million = 320,000,000,000 queries).
Illustration of the code is below.
Select Sum(Case when c1.Percentile < 19.274700171330668
/* 577309 Low Percentile Threshold*/
then 1 else 0 End) Obs, /*Low Count that is filtered sample */
Count(1) Cnt, /*Filtered sample Count*/
cast(Count(1) * 19.274700171330668/100 as float) [Expected Value]
from UserCounts c1 Join Usercounts c2
on C1.sampleId=c2.sampleId
And C1.taxon=204516
And C2.Taxon=577309
Join Users U on C1.SampleId=SequenceId
Where c2.Percentile < 12.890741292051205 /* 577309 Low Percentile Threshold*/
Group by C1.Taxon,C2.Taxon
dependent
independent
Label
Obs
Direction
Expected
Chi2
%
204516
577309
L,L
158
>
79
98.5
200%
204516
577309
L,H
204
<
238
6
86%
204516
577309
H,L
138
<
202
39.5
68%
204516
577309
H,H
724
>
609
43.1
119%
Phocaeicola massiliensis
Paraprevotella
Example of results with counts
There is a question of using Chi2 or using the percentage increased or decreased.
Example:
High Paraprevotella, we get more high count and less low count of Phocaeicola massiliensis. In other words Phocaeicola massiliensis numbers increase as a result (i.e. median likely moved up).
Low Example: Paraprevotella, we get less high count and more low count of Phocaeicola massiliensis. In other words Phocaeicola massiliensis numbers decrease as a result (i.e. median likely moved up).
Looking at doing linear regression, we do not see the relationship.
Chi2 Low
Chi2 High
Number of Interaction Found
6
50
1427931
50
150
301973
150
250
35584
250
350
7966
350
450
3172
450
550
1303
550
649
695
950
1050
610
650
750
505
750
850
483
851
950
376
1051
1150
349
1250
1350
223
1150
1250
218
1350
1450
213
1551
1650
158
1450
1549
153
1651
1750
141
1850
1949
138
1751
1847
126
1950
2050
98
2050
2150
83
2150
2249
68
2252
2348
64
2350
2449
56
2451
2548
33
2551
2650
31
2951
3043
28
2753
2845
27
2659
2741
27
3057
3150
26
3153
3242
23
3253
3348
20
2856
2949
19
3862
3948
18
3365
3450
16
4057
4141
14
3470
3548
12
3752
3842
12
3555
3625
9
3652
3749
8
3956
4046
8
4162
4248
6
4278
4329
3
4867
4905
3
5763
5782
2
4373
4423
2
5102
5139
2
4771
4771
1
5189
5189
1
4737
4737
1
If you use your own limits, this can be used to determine if the limits are better or not.
Next Project
Many taxa shifts have nothing in the literature affecting the taxa for use in a clinical context. Identifying taxa with a strong interaction that we can affect should allow us to indirectly influence the target taxa. Yes, gets complex but with modern computer power, very possible to do.
I would say some small subjective improvements since last time, but no major changes. Reminder: I have a friendly MD in terms of antibiotics.
Metronidazole was on top in the last samples, I did it back then.
Comment: Metronidazole is no longer at the top but dropped down to 16% of the highest value. It appears to have done its magic in reducing the bacteria pointing to it as a tool..
Base Analysis
When people have multiple samples, I like to do side-by-side comparisons, especially when someone has been doing some of the suggestions suggested. The suggestions are computed and may not always work. Expert Systems and AI are not perfect; they typically do better than a person with only a few years of experience that has training in the discipline (better consistency, remember more facts, etc). How are we doing objectively?
Scores
We see two positive shifts in the latest sample: Increase of Anti inflammatory Bacteria Score and decrease of Histamine Producers.
Sample
2021-11-18
2022-05-20
2023-06-22
2023-09-04
Anti inflammatory Bacteria Score
54%ile
43%ile
63%ile
87%ile 🥰
Butyrate Bacteria Score
57%ile
56%ile
57%ile
54%ile
Histamine Producers
78%ile
82%ile
81%ile
67%ile 🥰
Percentages of Percentiles
We see a lot of bouncing around between samples. The middle two images matches the typical pattern seen with ME/CFS and Long COVID. Those shifts have faded over the last 3 months with a different pattern appearing indicating a different dialect of gut dysfunction.
Multi-Vector Comparison
The main numbers are below. The take away, less bacteria that are in the high percentile range (at 95%ile, 10 -> 28 -> 23 -> 8). The numbers bounce around with the middle two being similar and the other two also similar. There are no really clear shift in these measures.
Criteria
11/18/2021
5/20/2022
6/22/2023
9/4/2023
Lab Read Quality
8.1
5.5
4.7
7.2
Outside Range from JasonH
6
6
9
9
Outside Range from Medivere
16
16
15
15
Outside Range from Metagenomics
8
8
7
7
Outside Range from MyBioma
5
5
6
6
Outside Range from Nirvana/CosmosId
20
20
23
23
Outside Range from XenoGene
29
29
35
35
Outside Lab Range (+/- 1.96SD)
7
6
17
3
Outside Box-Plot-Whiskers
36
69
54
38
Outside Kaltoft-Moldrup
93
48
47
88
Bacteria Reported By Lab
652
508
542
558
Bacteria Over 99%ile
7
4
6
2
Bacteria Over 95%ile
10
28
23
8
Bacteria Over 90%ile
29
42
36
22
Bacteria Under 10%ile
208
41
50
175
Bacteria Under 5%ile
180
19
8
157
Shannon Diversity Index
1.853
1.826
1.272
1.556
Simpson Diversity Index
0.056
0.038
0.087
0.09
Rarely Seen 1%
2
2
7
1
Rarely Seen 5%
14
5
21
8
Pathogens
41
24
29
36
From Special Studies
The top match was the same on all of the samples, with an increase when there was actually COVID.
Criteria
11/18/2021
5/20/2022
6/22/2023
9/4/2023
COVID19 (Long Hauler)
28%ile
33%ile
41%ile
28%ile
Next one:
15%ile
26%ile
20%ile
13%ile
The “next one” dropping implies some reduction of dysbiosis
Health Analysis
Using Dr. Jason Hawrelak Recommendations, there are many items on the edge of being in range with some items of interest (I strike out those that are unlikely to be of great concern):
Faecalibacterium prausnitzii at 27% of the microbiome or 96%ile
Faecalibacterium prausnitzii at 27% of the microbiome or 96%ile
I would suggest a test for candida to be safe. The data suggests a risk. If confirmed, candida would contribute significantly to gut dysbiosis [The interplay between gut bacteria and the yeast Candida albicans[2021]). I did a “back-flip” check of the top prescription items, and all of them reduces Candida (studies cited below).
Addendum – Predicted Symptoms
This was just added to the site today as a further refactor based on New Special Studies on Symptoms data. These are from [My Profile Tab]
Criteria
11/18/2021
5/20/2022
6/22/2023
9/4/2023
Forecast Major Symptoms
Neurological: Cognitive/Sensory Overload 40 % match on 25 taxa
DePaul University Fatigue Questionnaire : Racing heart 38 % match on 13 taxa
DePaul University Fatigue Questionnaire : Difficulty falling asleep 37 % match on 27 taxa
DePaul University Fatigue Questionnaire : Difficulty finding the right word 35 % match on 20 taxa
Autonomic Manifestations: urinary frequency dysfunction 66 % match on 6 taxa Immune Manifestations: Bloating 37 % match on 45 taxa
Neurological-Audio: hypersensitivity to noise 35 % match on 28 taxa
None
Neurological-Sleep: Chaotic diurnal sleep rhythms (Erratic Sleep) 50 % match on 18 taxa
Neurological: Spatial instability and disorientation 37 % match on 16 taxa
This can be helpful for judging possible severity (and potential improvement of some symptoms), for example: Neurological: Cognitive/Sensory Overload. See [Special Studies] tab.
2021 – 40% matches
2022- 24% matches
6/22/23 – 16% matches
9/4/2023 – 4% matches
Going Forward
COVID has had quite an impact on this microbiome. I am going to just go with the “Just Give Me Suggestions” option with the addition of what matched his diagnosis:
To explain a bit more. First I click the button below
And then click I could click the consensus report to see what the top items are:
Which are shown below.
In this case, I want to add Irritable Bowel Syndrome suggestions (on the Changing Microbiome Tab)
Instead of the usual 4 packages of suggestions, we have 5
When we look at the consensus report we see the same items there, but the values have increased.
The intent is put a little bias on the numbers towards specific conditions of greatest concern.
PDF Suggestions
I tend to favor the PDF suggestions because it simplifies things for many readers. Also the PDF gives a good list of citations (never complete) used to make the citations to persuade MDs to see that the suggestions are based on studies — a lot of studies.
The PDF suggestions are below (using the consensus view is another option for those more technically orientated). I clip from the PDF to keep the blog simpler for the typical reader.
This is a little longer list than usual, so I went to the consensus report to get priority data. Top value was 618, so 309 is the 50% threshold.
Minor note: quercetin with resveratrol is an avoid, quercetin is a take. resveratrol by itself is a negative (-113). At times, you need to look at the technical details/consensus to clarify things; the data we are using is incomplete and sparse…. If clearly contradictory suggestions appear, then don’t do them (thing an abundance of caution).
Because he has an antibiotic friendly MD, the following are the TOP antibiotics with notes:
“Since gentamicin has minimal gastrointestinal absorption,…it has applications in several clinical scenarios, such as bacterial septicemia, meningitis, urinary tract infections, gastrointestinal tract (including peritonitis), and soft tissue infection,” NIH StatPearls
“The FDA-Approved indications include acute infective exacerbation of chronic bronchitis, otitis media in pediatrics only, travelers diarrhea for treatment and prophylaxis, urinary tract infections, shigellosis, pneumocystis jirovecii, pneumonia/pneumocystis carinii pneumonia (PJP/PCP), and toxoplasmosis, both as prophylaxis and treatment. ” NIH StatPearlls
CFS Antibiotics are also above the threshold. Since the prior sample had a strong Long COVID or ME/CFS Profile, I would be inclined to include one of those below in the antibiotic rotation. The microbiome cannot make a diagnosis of most things, with most ME/CFS microbiomes there is a particular pattern which you had in your last sample but which has disappeared from your current sample which looks more like your first sample. I read this as recovering from ME/CFS…. in likely a fragile state since relapse is very common with ME/CFS.
My own experience is that it is better to overcure ME/CFS and when there are signs of recovery…. no backflips of joy or running marathons; keep doing slow walks that becomes a bit further each week for 6-12 months. Your microbiome is fragile and can quickly slip back.
I prefer to use the strategy of going for prescription items that are both suggested from the microbiome and been shown to help with one or more of the diagnosis conditions. This usually encounter low resistance from physicians — they are clueless for the microbiome, but very accepting of published studies. An antibiotic that is used as a prophylaxis usually encounter little resistance.
KEGG Suggestions
This is done by using information from the bacteria found with some fudge factors. I am in discussion with some Ph.D. candidates to build this concept directly from the FASTQ files and will hopefully have this as an added feature next year.
The KEGG probiotics is the usual pattern for ME/CFS and Long COVID with the top one being the usual, with the top reasonably available ones for other families shown below. I usually like to compare the values with those from consensus to minimum risk (i.e. two thumbs up, we do; mixed, we skipped)
The suggestions should be thought as influencers. The human population is often a good analogy or parable for the microbiome population. Each influencer shifts the population in the desired direction. Based on Cecile Jadin’s work and several studies, I am a firm believer in short duration (1-2 weeks) of each influencers. Just as with human influencers, people stop listening if the same person just keeps droning on and on. If a different person starts speaking, you get persuaded more. If a mob start to shout, yet a different human behavior will occur. In terms of the microbiome, “stop listening” means mutations that are resistant to the item will start to increase. Items line vitamins and minerals can be taken continuously; items that are likely to have bacteria resistance developed should be taken for a week and then another item replace it.
Herbs and spices: cinnamon, ginger, black cumin, thyme, rosemary, quercetin (suggests just before each antibiotic with a few days of overlap because it has potential synergistic activity with antibiotics [2020], [2016],[2018] )
Remember our goal is to destabilize a stable microbiome dysfunction.
Questions and Answers
While there has not been significant changes in many of the vectors between this sample and the prior sample from a few months earlier, there has been two significant objective changes:
Significant improvement of Anti inflammatory Bacteria Score (higher) and Histamine Producers (Lower).
The lost of the ME/CFS – Long COVID spike in the 0-9%ile
Q: Do you/should I use the colored list now instead of the consensus list?
Either are fine, the color list (from PDF) is what I tend to use in post because it is easier for new readers to understand (and automatically sent on new uploads). The consensus page is more complex but allows people to apply their own logic and priorities.
Q: “Quercetin (suggests just before each antibiotic with a few days of overlap because it has potential synergistic activity with antibiotics”
Q: I just did Mutaflor for 8 days and felt really tired all the time (but in the end I also got a flu/cold, so maybe that was the reason and not mutaflor). Nevertheless, if it was a herx reaction, I wonder if I should have taken it for longer until the reaction disappeared? (I stopped it 4 days ago.) Not sure if this question even makes sense.
My personal choice would be to keep taking it for at least a week (perhaps 2). Remember that the traditional pattern for a herx is feeling bad for X hours and then things get better. The duration of the feeling bad usually decrease from day to day. Catching a cold makes interpretation challenging.
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 can compute items to take, those computations do not provide information on rotations etc.
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.
Recently I did a much more rigorous implementation of the Kaltoft-Moldrup ranges as part of a periodic review and refactor. Today, I tested a hypothesis that those ranges may be good for detecting the taxa (bacteria) associated with a self-reporting symptom. The results exceeded expectations.
The methodology is simple to understand. Suppose we have 1000 samples. The KM lower limit is 5%ile and upper limit is 85%ile across the entire population.
For those with brain fog as a symptom we found that instead of the expected 5% of 1000 (i.e. 50), we only have just 5 samples in this range. That is a dramatic (and statistically significant shift).
On the other end, we do not have our expected 150 (100%-85% * 1000) but 300 sample in this range.
We can conclude that those with less than the 5%ile is associated with brain fog as well as those with more than 85%ile.
Most of the time we will find just one shift being significant. At times, both can be — i.e. values cascaded away from the range is both directions.
I have determined the taxa/bacteria for a stack of symptoms using P < 0.01. Because different labs identifies taxa information (see Nightmare ). This is why there is often no replication of (or contrary) results in many published studies. I created a table that is lab specific for each taxa.
Overview Page
This shows the number of bacteria found significant for each symptom. “All” usually will have more because it has more samples to use and thus can detect lesser associations better.
The following are permissible extracts (200 words per article). Click [more] to read more…
How the microbiome changes our idea of what it means to be human
YOU may, quite reasonably, think you are an individual of the species Homo sapiens. Once you have finished reading what follows, you will hopefully have been convinced that there is far more to us than that. Trillions of other organisms live on (and, more notably, in) your body. As you will see in the reports that follow, their impact on you is such that you will probably never think about yourself in the same way again. Your microbes change who you are and what it means to be you. With knowledge of this facet of ourselves growing rapidly, exploring it has never been more relevant.
Until recently, scientists believed that there were three discrete parts of our nature that reflected solid aspects of an individual self: the immune system, the genome and the brain. “None of these pillars of the traditional definitions of the self – immunity, genome integrity, the central nervous system – are free of microbial impact,” says Thomas Bosch at Kiel University in Germany.
The microbes that colonise us, collectively known as the microbiome, challenge the concept of a discrete self. These include bacteria, viruses and fungi, although the bacteria are the best-studied. [more]
The best way to care for your microbiome to keep it healthy as you age
Your gut microbiome is a vital support system for mental and physical health, supplying the body with all-important nutrients and helping tune the immune system.
As we get older, the balance of microbes in our gut changes. There are declines in beneficial types, such as the anti-inflammatory Faecalibacterium, and an increase in species that lead to more inflammation, which is implicated in multiple age-related conditions, including heart disease, cancer and cognitive decline. Many studies, with participants ranging from an isolated rural population in India to a wealthy semi-urban community in Italy, show striking similarities in the microbiome signatures of old age. One key finding is that people who have no significant health concerns in older age have an abundance of distinct beneficial microbes that are lost when there is a shift to physiological decline.
It isn’t clear whether the microbiomes of healthy older people are driving their vitality or are a result of the way they live, but an astonishing study in mice by John Cryan at University College Cork, Ireland, and his colleagues found that transplanting gut microbiota from young animals to elderly ones reversed age-associated impairments in brain function. [more]
Can probiotics and supplements really improve your gut microbiome?
If you have a condition like irritable bowel syndrome (IBS), a finnicky gut or just want to keep your microbiome in top condition, you might be tempted by products and treatments that offer a microbial tune-up. But what really works? Here are the main tools to engineer a better gut.
Probiotics
Probiotics are microbes that may help to restore healthy gut microbiota. If they also improve your mood, they are called psychobiotics. You can typically get them from eating naturally fermented foods like yogurt that contain beneficial bacteria, such as Lactobacillus or Bifidobacterium.
But as an adult, these microbes are unlikely to colonise your intestines. To the extent that they are helpful, their benefit comes while they are passing through. Such probiotics stimulate immune cells in the gut to reduce inflammation, increase mucus production and deter pathogens by producing lactic acid. But as mere visitors, they need daily top-ups.
Probiotic supplements have been used (with mixed success) for more than a century to help with the gut conditions of Crohn’s disease, colitis and IBS. They have also been shown to help with weight loss in people who are overweight and are increasingly being used for other conditions… [more]
Secrets of a long and healthy life reside in your gut microbiome
WHY do we age? As youngsters, we seem invincible. We climb trees, frolic in the dirt and blithely share alarming quantities of mucus. At college, we can thrive on a diet of ramen and beer, party all night and still sit an exam the next day. But in our 30s, we start to wind down. It becomes harder to maintain muscle tone and avoid illness. Our joints start to ache and our memory begins to dim. And it is mostly downhill from there.
People have long attempted to stop or reverse this process. But fountains of youth and secrets of immortality remain firmly in the realms of fiction. Our bodies wear out, even if we no longer do the back-breaking physical labour our ancestors did. And the world seems determined to grind us down with a plethora of disease-causing microbes. To help fend off these pathogens, our bodies recruit other microbes, vast numbers of which reside in our intestines, where we feed them in exchange for their services. But, as we age, this gut microbiota becomes less effective at fighting diseases too. [more]
Where does your gut microbiome really come from – and does it matter?
Imagine a remote island, recently formed by volcanic activity, in the middle of the ocean. At first, it is lifeless, but a growing variety of plants take hold, providing food for pioneering animal species, until eventually there is a diverse and flourishing ecosystem.
This is a useful way to think about how our gut ecosystems develop. “Your microbiome goes on a journey,” says Alan Walker at the University of Aberdeen, UK. “When you’re born, some bugs get in and then, when you start eating solid foods, other bugs replace them. There’s a dynamic process where your microbiome changes until you get to mid-to-late childhood. Then, through adult life, you’ve got a reasonably stable microbial community.”
Does a C-section affect a baby’s microbiome?
The first individuals that colonise an island can have long-lasting influences on its ecosystem, an idea known as the founder effect. Until recently, the thinking went that if the founder bacteria in a baby’s gut were unusual – because the baby was born by Caesarean section, for instance – this might disrupt their bacterial ecosystems. This idea has led some parents to take radical steps to get their children’s microbiomes back on the right track. [more]
What is the role of the microbiome in diseases like chronic fatigue
ONE of the most compelling discoveries about the gut microbiome is its influence on the immune system. Between 70 and 80 per cent of immune cells are in the gut, where they are constantly communicating with microbes. This crosstalk helps fight disease, strengthen immune responses and regulate inflammation, our body’s first line of defence against infection. Controlling inflammation is critical, as too much damages cells and helps drive chronic illness.
It is no surprise, then, that a growing body of evidence implicates the gut microbiome in various chronic diseases, from arthritis to Alzheimer’s. It is still early days, and most of these findings only point to associations. But they raise the possibility that gut microbes may contribute to, or even cause, some of our most intractable conditions, an idea that has already inspired new treatments.
It is now well established that gut microbiomes in people with conditions like multiple sclerosis, type 1 and type 2 diabetes, Parkinson’s disease and even asthma differ significantly from those of people without an underlying illness. Two papers published earlier this year showed that people with chronic fatigue syndrome – also known as myalgic encephalomyelitis, or ME/CFS – have less of a gut bacterium called Faecalibacterium prausnitzii [more]
How your microbiome is shaped by your friends, family, lovers and pets
“I jokingly say that your dating app profile should include your microbiome profile,” says Brett Finlay at the University of British Columbia in Canada.
The strongest evidence comes from work published in January by Mireia Valles-Colomer at the University of Trento, Italy, and her colleagues, who conducted the largest study to date of how our gut microbiomes are shaped by the people around us. They analysed DNA in the faeces of more than 7000 people from households around the world, including rural parts of Africa and South America and cities in the US, Europe and China, to find out which bacterial strains were in their guts and what proportion they shared with others. [more]
—————– from older issues ———————-
Your gut microbiome is linked to your fitness and biological age
The diversity of microbes in the gut could affect a person’s fitness and their biological age. Better understanding this may one day lead to probiotics that alter the gut’s microbial make-up to promote health.
Zsolt Radak at the Hungarian University of Sports Science and his colleagues studied 80 amateur rowers, aged 38 to 84, who participated in the 2019 World Rowing Masters Regatta in Velence, Hungary.
The rowers, whose training regimens ranged from practising every day to once a week, each provided a stool sample to identify the bacteria in their guts. The researchers also took blood samples to gauge the participants’ biological ages – a measure based on DNA markers, rather than the number of years someone has been alive.
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