He wanted to know which has the least risk — well, I have grown to trust Perplexity.Ai to give good answers (with the sources of information linked). The FULL ANSWER IS HERE (with References).
The preferences are with 1 being the lowest risk.
Minocycline and 2. Doxycycline: These tetracyclines appear to have the lowest risk. The search results indicate that tetracyclines, particularly minocycline, have a low risk of adverse reactions. Minocycline had an adjusted odds ratio of 0.79 for community-acquired Clostridioides difficile infection (CA-CDI), while doxycycline had an adjusted odds ratio of 0.96, both lower than most other antibiotics.
Neomycin: As an aminoglycoside, neomycin is likely to have a relatively low risk. The search results mention that aminoglycosides were classified among the safest antibiotics in terms of anaphylaxis risk.
Metronidazole: While not specifically mentioned in the search results, metronidazole is generally considered to have a moderate risk profile.
Azithromycin: This macrolide antibiotic had an adjusted odds ratio of 1.31 for CA-CDI, higher than tetracyclines but lower than other antibiotics on this list.
Erythromycin: Another macrolide, erythromycin had a higher adjusted odds ratio of 1.53 for CA-CDI compared to azithromycin.
Vancomycin: While not directly compared in the search results, vancomycin is known to have potential for significant adverse reactions, including nephrotoxicity and ototoxicity.
Ampicillin: This penicillin antibiotic had one of the highest adjusted odds ratios for CA-CDI at 2.6, indicating a higher risk of adverse reactions.
As a FYI, a few decades ago, I persuaded my MD to give me Minocycline and Doxycycline by saying “Look you have no problem prescribing those to a teenager for acne — I have ME/CFS and on disability… are you saying that a teenager’s acne impacting their ability to get dates is more critical than ME/CFS? and being on disability?” I walked out with the prescriptions…..
This uses the consensus model and does the following:
Identifies the bacteria shifts reported in the literature that are seen in your microbiome sample
Computes substances that should improve those shifts
FILTER these substances using the literature of what helps the condition.
So, you have a list of things to fix the microbiome that are also known to help the condition. Many studies find that only a portion of people are helped. Our hypothesis is that the microbiome is a key factor here.
Last we give the top other suggestions (in general, they have never been tested in a clinical study — and thus we are depending on the microbiome impact)
After this, we give a list of studies used to generate the report. This should buy creditability with MD for what is being done as well as educate them.
This new suggestions report also handles multiple conditions. The example below is for someone that has both Autism and ME/CFS. It gives a good illustration of the new report intent.
This report is for Private@Annon.comand uses their reported medical conditions, microbiome sample and a fuzzy logic expert system to compute recommendations
The reported condition(s) are
Autism – Common Advice:
Omega-3 Fatty Acids: Some studies have explored omega-3 supplements (particularly those containing EPA and DHA) due to their potential neuroprotective and anti-inflammatory properties. While research results have been mixed, some parents or caregivers of individuals with ASD might consider omega-3 supplements based on the belief that they could positively impact cognitive and behavioral functions.
Probiotics: The gut-brain connection has sparked interest in the potential role of probiotics in influencing behavior and cognition. Some studies suggest that gut health might affect certain aspects of behavior in individuals with ASD. However, the use of probiotics for managing autism symptoms lacks robust scientific evidence, and their effectiveness remains unclear.
Vitamin D: Low vitamin D levels have been observed in some individuals with ASD. While research is ongoing, maintaining adequate vitamin D levels is considered important for overall health. Some parents may opt for vitamin D supplements under the guidance of a healthcare professional.
Multivitamins and Minerals: Individuals with ASD might have specific dietary habits that could lead to deficiencies in certain vitamins or minerals. Ensuring a balanced diet or supplementing with multivitamins and minerals under the guidance of a healthcare provider might be considered to address potential deficiencies.
Chronic Fatigue Syndrome – CFS,ME,Myalgic encephalomyelitis Common Advice:
Coenzyme Q10 (CoQ10): Some studies have suggested that CoQ10 supplementation might have potential benefits in reducing fatigue and improving energy levels in individuals with CFS. However, more research is needed to establish its effectiveness for CFS specifically.
Omega-3 Fatty Acids: Omega-3 supplements containing EPA and DHA have anti-inflammatory properties and may support overall health. Some individuals with CFS might consider omega-3 supplementation for potential benefits, although evidence supporting their use specifically for CFS is limited.
Probiotics: The role of probiotics in managing CFS symptoms is an area of ongoing research. Some studies suggest that probiotics might impact gut health and the immune system, which could potentially affect symptoms in some individuals with CFS. However, specific probiotic strains, dosages, and their efficacy for CFS require further investigation.
Vitamins and Minerals: Nutritional deficiencies are common in individuals with CFS, possibly due to poor dietary intake or other factors. Some individuals might have deficiencies in vitamins (such as vitamin D, B vitamins) or minerals (like magnesium or iron). Supplements might be recommended to address identified deficiencies.
Significant Bacteria Shifts
Based on the existing literature on the US National Library of Medicine and this microbiome sample, we have the following matches of bacteria shifts. There is a growing body of literature finding that the effectiveness of interventions depends on the existing microbiome. We filter by suggested interventions and this person’s specific microbiome to produce this “double validated” list..
Acidobacteriota – phylum : High 1315 Actinomycetota – phylum : Low 18 Akkermansia – genus : High 102225 Akkermansia muciniphila – species : High 6 Alcaligenaceae – family : High 25 Bacteroides ovatus – species : High 17 Bacteroides uniformis – species : High 17 Citrobacter – genus : High 20 Coprococcus – genus : Low 10 Dorea – genus : Low 182425 Eggerthella – genus : Low 5
Faecalibacterium – genus : High 92125 Oscillospiraceae – family : High 2325 Phascolarctobacterium – genus : Low 172325 Phocaeicola vulgatus – species : Low 71425 Pseudomonadaceae – family : Low 5 Pseudomonas – genus : Low 5 Ruminococcaceae – family : High 12 Staphylococcus – genus : Low 2 Sutterella – genus : High 3811192125 Sutterellaceae – family : High 422 Veillonellaceae – family : Low 16
Cross Validated Suggestions
The following improves the bacteria identified above and also is reported in the literature of helping some people with this condition. Each is link to the source study.
Reviewing substances reported to help with this condition on the US National Library of Medicine, and which will correct the above bacteria shifts. the following are recommended. Some bacteria may lack literature because none of the studied substances for the condition(s) are known to modify the bacteria.
There are many other interventions to correct the bacteria shifts seen with this person. The top 20 suggestions are listed below as the top 20 items to avoid.
A question was ask – are there significant gender differences with ME/CFS. A partial answer is possible from our citizen science data (Available here). The number of bacteria identify as statistical drops because we are reducing sample sizes. The table below shows the shifts that are seen in common with P < 0.01.
For Symptom of ME/CFS
Source
Tax_name
tax_rank
Male
Female
Male_Chi2
FeMale_Chi2
thryve
Thermodesulfobacteria
phylum
increases
increases
234.0375
138.4544
biomesight
Verrucomicrobiaceae
family
increases
increases
8.333333
7.262051
biomesight
Rhodothermaeota
phylum
increases
increases
179.2
217.3071
biomesight
Akkermansiaceae
family
increases
increases
8.718378
9.965634
biomesight
Erysipelothrix muris
species
increases
increases
9.533889
10.08333
biomesight
Akkermansia
genus
increases
increases
8.718378
9.965634
biomesight
Rhodothermales
order
increases
increases
179.2
217.3071
biomesight
Akkermansia muciniphila
species
increases
increases
8.718378
9.965634
biomesight
Erysipelothrix
genus
increases
increases
9.663289
9.663289
biomesight
Rhodothermia
class
increases
increases
179.2
217.3071
biomesight
Thermodesulfobacteria
phylum
increases
increases
281.1738
299.9112
ME/CFS With IBS
We find differences here.
Source
Tax_name
tax_rank
Taxon
Male
Female
Male_Chi2
FeMale_Chi2
biomesight
Sutterella
genus
40544
decrease
increases
8.333333
11.25018
biomesight
Rhodothermales
order
1853224
increases
increases
139.9274
114.5716
biomesight
Dorea
genus
189330
increases
decrease
18.75
16.17875
biomesight
Rhodothermia
class
1853222
increases
increases
139.9274
114.5716
biomesight
Thermodesulfobacteria
phylum
200940
increases
increases
280.3333
187.9779
biomesight
Sutterellaceae
family
995019
decrease
increases
8.333333
11.25018
biomesight
Alcaligenaceae
family
506
decrease
increases
8.333333
9.120714
biomesight
Rhodothermaeota
phylum
1853220
increases
increases
139.9274
114.5716
ME/CFS Without IBS
We found no differences yet (given the sample size)
Source
Tax_name
tax_rank
Taxon
Male
Female
Male_Chi2
FeMale_Chi2
biomesight
Bacteroides fluxus
species
626930
increases
increases
7.355161
7.910588
biomesight
Thermodesulfobacteria
phylum
200940
increases
increases
124.4571
170.4624
Irritable Bowel Syndrome
Following up from above and noting that there is a gender bias in incidence, we find some differences
thryve
Thermodesulfobacteria
phylum
200940
increases
increases
252.8232
95.10095
biomesight
Rhodothermales
order
1853224
increases
increases
125.1467
110.6182
biomesight
Rhodothermia
class
1853222
increases
increases
125.1467
110.6182
biomesight
Thermodesulfobacteria
phylum
200940
increases
increases
314.4971
174.6182
biomesight
Rhodothermaeota
phylum
1853220
increases
increases
125.1467
110.6182
biomesight
Sharpea azabuensis
species
322505
increases
increases
16.18526
6.80625
biomesight
Sharpea
genus
519427
increases
increases
16.18526
6.80625
thryve
Mycoplasma
genus
2093
increases
decrease
12.81524
20.3229
thryve
Mycoplasmataceae
family
2092
increases
decrease
14.88581
20.3229
thryve
Phocaeicola vulgatus
species
821
increases
decrease
7.893492
17.06273
thryve
Mycoplasmatales
order
2085
increases
decrease
14.88581
26.01485
Depression
Another condition with a gender association
Source
Tax_name
tax_rank
Taxon
Male
Female
Male_Chi2
FeMale_Chi2
thryve
Thermodesulfobacteria
phylum
200940
increases
increases
227.7557
148.4336
thryve
Parabacteroides distasonis
species
823
decrease
increases
9.118356
13.46941
thryve
Eubacterium oxidoreducens
species
1732
decrease
increases
12.99507
6.76
biomesight
Rhodothermales
order
1853224
increases
increases
121.2002
91.125
biomesight
Rhodothermia
class
1853222
increases
increases
121.2002
91.125
biomesight
Thermodesulfobacteria
phylum
200940
increases
increases
223.4402
189.2431
biomesight
Rhodothermaeota
phylum
1853220
increases
increases
121.2002
91.125
thryve
Lactobacillus rogosae
species
706562
decrease
decrease
23.88368
12.12781
Symptom: Problems remembering things
This is one of the characteristics of ME/CFS, Long Covid, etc
Source
Tax_name
tax_rank
Taxon
Male
Female
Male_Chi2
FeMale_Chi2
thryve
Thermodesulfobacteria
phylum
200940
increases
increases
316.4446
120.0944
biomesight
Rhodothermales
order
1853224
increases
increases
171.7445
133.3333
biomesight
Rhodothermia
class
1853222
increases
increases
171.7445
133.3333
biomesight
Thermodesulfobacteria
phylum
200940
increases
increases
369.0078
289.0992
biomesight
Odoribacteraceae
family
1853231
increases
increases
12.79311
7.962632
biomesight
Rhodothermaeota
phylum
1853220
increases
increases
171.7445
133.3333
biomesight
Acetivibrio
genus
35829
decrease
increases
9.180865
17.49208
biomesight
Odoribacter
genus
283168
increases
increases
9.334949
12
biomesight
Acetivibrio alkalicellulosi
species
320502
decrease
increases
9.180865
19.95636
biomesight
Hathewaya histolytica
species
1498
decrease
increases
9.180865
7.262051
biomesight
Hathewaya
genus
1769729
decrease
increases
9.180865
7.262051
biomesight
[Clostridium] thermoalcaliphilum
species
29349
increases
increases
7.35
6.880909
thryve
Intestinimonas
genus
1392389
decrease
increases
16
8.552727
thryve
Intestinimonas butyriciproducens
species
1297617
decrease
increases
16.48646
9.992258
ubiome
Bacteroides sp. EBA5-17
species
447029
increases
decrease
9.055577
7.314286
Symptom: Worsening of symptoms with stress.
Another common symptom of ME/CFS
Source
Tax_name
tax_rank
Taxon
Male
Female
Male_Chi2
FeMale_Chi2
thryve
Thermodesulfobacteria
phylum
200940
increases
increases
282.4023
185.22
biomesight
Thermoanaerobacterales Family III. Incertae Sedis
family
543371
decrease
increases
22.00454
8.491649
biomesight
Sharpea
genus
519427
increases
increases
17.55625
12.38345
biomesight
Hathewaya
genus
1769729
decrease
increases
16.98612
11.70814
biomesight
Rhodothermales
order
1853224
increases
increases
142.9353
188.8704
biomesight
Hathewaya histolytica
species
1498
decrease
increases
16.98612
11.70814
biomesight
Sharpea azabuensis
species
322505
increases
increases
17.55625
12.97965
biomesight
Rhodothermia
class
1853222
increases
increases
142.9353
188.8704
biomesight
Thermodesulfobacteria
phylum
200940
increases
increases
352.2616
362.7038
biomesight
Acetivibrio alkalicellulosi
species
320502
decrease
increases
12.65818
8.491649
biomesight
Rhodothermaeota
phylum
1853220
increases
increases
142.9353
188.8704
biomesight
Acetivibrio
genus
35829
decrease
increases
12.65818
8.491649
Other Symptoms with Significant Gender Differences in patterns
Immune Manifestations: Abdominal Pain
Sleep: Unrefreshed sleep
Comorbid: High Anxiety
General: Fatigue
Neurological-Audio: hypersensitivity to noise
DePaul University Fatigue Questionnaire : Unrefreshing Sleep, that is waking up feeling tired
DePaul University Fatigue Questionnaire : Fatigue
Neurocognitive: Brain Fog
Neurocognitive: Problems remembering things
DePaul University Fatigue Questionnaire : Anxiety/tension
Many support groups provide lists of local MDs that are sympathetic to ME/CFS patients. Typically, they will attempt to do symptom relief, not remediate the underlying cause or do not test outside of their local standards of practice (i.e. testing for associated viral infection, Lyme or rickettsia infections) – independent of insurance coverage or the patient being will to pay.
The family was extremely fortunate to be covered by the old Microsoft Medical insurance that covered everything that the MD wanted with no deductibles; and we had a MD that was willing to learn and explore.
The Clinical and Scientific Basis of Myalgic Encephalomyelitis – Edited by Byron Hyde, M.D. Free Download eBook (PDF) This is a collection of a massive number of early research papers — most still relevant.
Goodreads: Me Cfs Books, I would exclude books not written by a MD or published before 2020.
Note that the better books are often difficult or impossible to understand due to brain fog (and sometime lack of sufficient education is specific areas)
Determine a Model and if possible, see if there is evidence that the model works
I went with two models for ME/CFS: A hypercoagulation condition (David Berg) and an “occult rickettsia like infection” (Cecile Jadin); today we could call it “post Infection Fatigue Syndrome”. Both were testable (by lab or by reaction to low risk drugs, i.e. an antibiotic often prescribed for Acne) and actionable.
Today, my thinking is that the simplest model is a persistent microbiome dysfunction. This is very testable with direct retail tests; and actionable (using Microbiome Prescription). Often the antibiotics suggestions from Microbiome Prescription mirrors the Jadin approach. The treatment plan works for her models and my microbiome model!
Going with a hypothesis that is not both testable and actionable is not recommended. Take action today incase it works! Leave speculations to researchers trying to get grant money for their special interests.
Symptoms and Bacteria appears to be strongly related
It is typical that Microbiome Prediction correctly predicts 80-100% of a person’s dominant symptoms from their microbiome. This implies that the bacteria shifts are causing the symptoms; thus correcting the bacteria shifts may reduce or eliminate symptoms.
This is a follow up on the prior post below. The reader’s comments are “I am feeling much better but still very fatigued and lately been quite achey. The recommendations have changed significantly except for whole grain barley.”
Let us first do the simple numbers. A lot of values are the same (typical) but many of them show improvement. 🙂 indicate significant reduction is out of range values See Technical Note: Lab Quality Versus Bacteria Reported We would expect a 15% drop from lower lab quality, the drops shown are well below that).
Criteria
Current Sample
Old Sample
Eubiosis Index
62.8% 🙂
59%
Lab Read Quality
4.3
8.4
Outside Range from JasonH
8
8
Outside Range from Medivere
20
20
Outside Range from Metagenomics
10
10
Outside Range from MyBioma
8
8
Outside Range from Nirvana/CosmosId
18
18
Outside Range from XenoGene
42
42
Outside Lab Range (+/- 1.96SD)
9 🙂
16
Outside Box-Plot-Whiskers
38 🙂
98
Outside Kaltoft-Moldrup
56 🙂
139
Bacteria Reported By Lab
494
752
Bacteria Over 90%ile
20 🙂
82
Bacteria Under 10%ile
66 🙂
232
Shannon Diversity Index
1.465
1.701
Simpson Diversity Index
0.035
0.028
Chao1 Index
7474
17093
Shannon Diversity Percentile
28.5
61.4
Simpson Diversity Percentile
30.2
21.5
Chao1 Percentile
28.9
87.7
Lab: BiomeSight
Pathogens
18 🙂
39
Condition Est. Over 90%ile
4
4
Kegg Compounds Low
969 :-)
1242
Kegg Compounds High
5 🙂
23
Kegg Enzymes Low
272
284
Kegg Enzymes High
17 🙂
75
P or P Chi2
.9999245
.999999999
Health Analysis Comparisons
I have not created an automatic compare yet (on to do list). Many values were similar, some interesting ones with improvements are below. Jason Hawrelak Criteria got worse, but I have deep reservations on using his criteria on Biomesight tests (he based them on a very different test method).
Current
Prior
General Health Predictors: Flagged Bacteria
8 🙂
10
Anti inflammatory Bacteria Score
14.4%ile 🙂
13.3 %ile
Lactate (controls many bad bacteria)
33.1 %ile 🙂
20 %ile
L-Lactic Acid (controls many bad bacteria)
47.1 %ile :-)
25.2 %ile
NADH (Typically low with ME/CFS)
26.5 %ile :-)
13.7 %ile
Hydrogen peroxide (controls many bad bacteria)
17.3 %ile 🙂
5.8 %ile
D-Lactic Acid (Associated with brain fog)
6.5 %ile 🙂
7.9 %ile
Potential Medical Conditions Detected
2 🙂
7
Bacteria deemed Unhealthy
7 🙂
22
Jason Hawrelak Criteria
56.4 %ile
75.8 %ile
Going Forward
A review of the Health Analysis was done above, with the two items: Mood Disorders and COVID-19 (a proxy for ME/CFS IMHO). A secondary review of all the items on [Changing Microbiome]/[US National Library of Medicine Studies] for high items not flagged. Nothing added.
Doing what is becoming a regular pattern: “Just give me suggestions” and then using given symptoms under Special Studies using these items:
Note: items like age and gender are omitted as well as any other symptoms that we do not have sufficient data.
First the filtered PDF suggestions. The list is much longer than usual:
And the to avoid list is more typical.
Let us go over to viewing the consensus for the latest microbiome sample to get some suggestions.
The highest suggested value/priority was 485 (so 240 for cutoff), lowest value was -574 ( so-287 for cutoff)
So in summary, shift a diet to low sugar, gluten free with moderation in meat (no guidance on chicken or fish). If your MD is willing, I would suggest reviewing Cecile Jadin approach with antibiotics and rotate with those suggested above. IMHO Continuous on a single antibiotic is more likely to complicate the microbiome.
Postscript – and Reminder
I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”. I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.
I cannot tell people what they should take or not take. I can inform people items that have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.
The answers above describe my logic and thinking and is not intended to give advice to this person or any one. Always review with your knowledgeable medical professional.