A reader asked on Inherited Factors for ME/CFS:

Which of your posts gives the clearest explanation of how someone might begin addressing one or more possible contributors to ME/CFS? What is the most practical “how-to” guide for following the steps that led to your remission?

I understand that remission may not be possible for everyone. Still, people may want to know what I tried so they can decide whether any of those steps are appropriate for them.

I would answer this in two parts.

First, I will describe what contributed to my original recovery. Much of that approach may be difficult or impossible for many people to duplicate today because of cost, insurance limitations, and the way medical care is commonly delivered.

Second, I will describe a more practical approach that attempts to follow the same general reasoning as closely as possible.

My Original Recovery

When I was first diagnosed with ME/CFS, around 2000, I was in an unusually fortunate situation:

• I received disability pay for one year.
• My employer-covered medical plan paid 100% of costs, including out-of-network care, prescriptions, and dental care.
• My physician could spend as much time with me as needed, bill for that time, and be reimbursed without major administrative barriers.

At that time, two sets of papers had been published reporting remission rates of roughly 80% to 90% using different approaches. My physician and I decided to pursue both approaches at the same time.

The plan included:

• Extensive coagulation testing through a specialist laboratory. This included testing for inherited clotting-related factors, followed by treatment based on the results.
  • Lovenox, a low-molecular-weight heparin anticoagulant. At the time, it cost approximately $500 per month.
  • Piracetam, a compound in the racetam family, which I imported from the Czech Republic.
  • Turmeric.
• The Dr. Cecil Jadin protocol.
  • A monthly rotation of different antibiotics.

Many of the antibiotics caused a strong die-off reaction, often described as a Herxheimer or “herx” reaction. After the reaction settled down, we added substances intended to improve penetration or effectiveness, such as bromelain.

Over several months, this approach worked for me. However, because genetic factors appeared to be involved, I did not regard it as a permanent cure. I considered it a remission.

I also came to believe that stress was an important trigger for my symptoms. As a result, I made significant lifestyle changes. In particular, I changed the kind of work I did and developed a much lower tolerance for persistently stressful work environments or managers. If a job became harmful to my health, I made it a priority to leave rather than remain in that situation.

Later Relapses

My later relapses did not always appear to have the same immediate trigger. Stress was one trigger. A flu vaccination seemed to be another in at least one instance.

There was, however, one important difference from my earlier illness: I developed gastrointestinal symptoms.

That led me back to the research literature. I found a 1999 paper describing shifts in bacterial populations associated with ME/CFS. When I reviewed the antibiotics used in my earlier treatment, I realized that they may also have corrected most of the bacterial shifts described in that paper.

Jadin’s protocol described the issue as an “occult infection,” meaning an underlying infection or infection-like process that can produce symptoms similar to those caused by the original infection. That idea helped clarify my thinking.

My interpretation was that the initial infection may have caused shifts in the gut microbiome. Even after the original infection resolved, those bacterial shifts may not have returned to a healthy baseline. In other words, some continuing symptoms may have been driven less by the original pathogen and more by the lasting changes it caused in the gut ecosystem.

That realization led me into microbiome research.

A More Practical Starting Approach

For people who want to explore this line of thinking, I would suggest a practical, lower-cost approach centered on microbiome testing and data-guided interventions.

1. Obtain a microbiome test from Biomesight. The discount code is Micro. Use of the code provides a contribution toward the costs of maintaining the site.
2. I prefer Biomesight primarily because we have the largest number of uploads from that testing service. A larger comparable dataset makes it easier to identify bacterial patterns that may be relevant.
3. Transfer your Biomesight data to Microbiome Prescription.
4. Log in to Microbiome Prescription, enter your symptoms, and review the suggestions it generates.
5. You should also receive an Odds Ratio list of suggested interventions within about a day. I would start with those suggestions for approximately two weeks.
6. If you see no meaningful improvement after two weeks, consider switching to the symptom-based suggestions generated by the site.

The Odds Ratio approach has received encouraging reports from several people, including some health professionals. Individual responses vary greatly, however, so it is important to introduce changes carefully, track symptoms, and involve an appropriately qualified clinician when considering prescription medicines, anticoagulants, or antibiotics.

Summary

In my experience, two areas appear to be the most promising paths to investigate:

• Deep coagulation testing, especially where there is reason to suspect clotting-related or inherited factors.
  • 23andMe is an option: its Hereditary Thrombophilia Genetic Health Risk report covers the two common inherited clot-risk variants—Factor V Leiden in F5 and prothrombin G20210A in F2. Not complete but better than no information.
• Microbiome testing and targeted efforts to correct unfavorable bacterial patterns.

For many people, microbiome testing may be the more accessible starting point. It is often less expensive, less confrontational, and more practical than trying to obtain extensive specialist testing or persuade clinicians to pursue less conventional treatment pathways.

One probiotic of note: Mutaflor — it is one of those bacteria found deficient in the 1999 study. My own experience is that it can cause a significant herx; on the plus side, if things are a little off, I will often use it as a preventative and take for 1-2 weeks.

This is not a promise of remission, and it should not replace individualized medical care. But it is the closest practical version of the path that led me from severe illness toward remission.

A reader forwarded me a link to this new study

which included this nice diagram

This is actually OLD news

I covered this in a post from almost a decade ago, The Heart and Blood of the CFS Patient. This post cited studies from 2008. It also included this chart that bears great similarity to the above.

In new publications on ME/CFS, I too often seen results that were known and published in the past. Too often the prior studies were not cited — indicating that the researcher failed to do due diligence (or just search this site!!).

We have one factor that likely comes from DNA.

Inherited Coagulation Defects

This is another DNA variation that is over represented with ME/CFS and has been known for over a quarter century.

• Thick Blood, Clots dimension of CFS etc

• Hemex Protocol and Dave Berg
  • Dave Berg – CFS Radio Program 1999-08-29
  • Dave Berg Talk #4
  • Townhall with David Berg #3
  • Transcript of Townhall with Dave Berg, Hemex Labs, (#1)
  • Transcript of Townhall with Dave Berg, Hemex Labs (#2)

Addressing this was part of the plan that resulted in my remission.

Some more recent studies:

A notable 2024 plasma-proteomics study analyzed platelet-poor plasma from 15 people with ME/CFS and 10 non–SARS-CoV-2-infected controls. It found 24 proteins increased and 21 decreased in ME/CFS. Among the altered proteins were thrombospondin-1, platelet factor 4, and protein S—findings the authors interpreted as consistent with disrupted platelet/coagulation regulation and endothelial dysfunction. Complement proteins, including C9, were also lower. Its small sample size means this is hypothesis-generating rather than a confirmed biomarker panel.

Data-independent LC-MS/MS analysis of ME/CFS plasma reveals a dysregulated coagulation system, endothelial dysfunction, downregulation of complement machinery

A 2023 review in Blood Reviews concluded that multiple ME/CFS studies report platelet hyperactivation, anomalous clot formation, a more procoagulant phenotype, and endothelial dysfunction. It proposes impaired capillary-level exchange and tissue hypoperfusion as one possible connection to fatigue, cognitive symptoms, and exertional intolerance.

Cardiovascular and haematological pathology in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS): A role for viruses

The “microclot” literature—especially studies using fluorescence methods, thromboelastography, and platelet imaging—has reported larger fibrinogen/amyloid-containing fibrinaloid deposits, platelet hyperactivation, and hypercoagulability in ME/CFS samples versus controls. These aggregates are hypothesized to be relatively resistant to normal fibrinolysis. However, assay standardization, replication by independent groups, and proof of clinical relevance remain important gaps

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: the biology of a neglected disease

Iron Levels — why females get ME/CFS more often?

This is more uncertain because ferritin has a complex interaction.

A 2023 Japanese study of people with Long COVID found those who went on to meet ME/CFS criteria had higher ferritin than both Long-COVID participants without ME/CFS and people without fatigue: median 193.0 µg/L versus 98.2 and 86.7 µg/L, respectively. The difference was particularly apparent in women, and ferritin correlated with fatigue severity measures.

Utility of Serum Ferritin for Predicting Myalgic Encephalomyelitis/Chronic Fatigue Syndrome in Patients with Long COVID

Other Factors

The landmark DecodeME genome-wide association study compared 15,579 people with ME/CFS against 259,909 controls of European ancestry. Its initial 2025 results identified eight genome-wide significant genomic regions. The implicated biology clustered mainly around immune response to infection and nervous-system pathways.

Possible genetic clues to ME/chronic fatigue syndrome identified in massive study

Bottom Line

I view ME/CFS as a heterogeneous condition in which impaired oxygen delivery, oxygen utilization, or microcirculatory blood flow may contribute to a state of functional tissue hypoxia—meaning tissues may not receive or effectively use enough oxygen even when routine oxygen-saturation measurements appear normal.

In this model, a person may have pre-existing vulnerabilities that leave them relatively close to a physiological threshold. These vulnerabilities could include genetic predisposition, immune dysregulation, autonomic dysfunction, endothelial or microvascular abnormalities, mitochondrial or metabolic limitations, nutrient deficiencies, chronic inflammation, or prior infectious exposures. A triggering event—commonly an acute infection, but potentially another major physiological stressor—then pushes the system beyond its capacity to recover normally.

Once that threshold is crossed, the consequences may extend far beyond the initial trigger. Reduced perfusion or impaired cellular energy production could activate stress responses involving the autonomic nervous system, immune signaling, coagulation, oxidative stress, redox balance, metabolism, sleep regulation, and neuroinflammation. These systems interact with one another. For example, impaired tissue perfusion may worsen metabolic stress; metabolic stress may intensify inflammatory and autonomic signaling; and inflammation or vascular dysfunction may further impair blood flow and oxygen availability.

This could create a set of self-reinforcing feedback loops rather than one isolated defect. It may also help explain why people with ME/CFS can have normal results on many standard resting tests while developing profound symptoms after relatively minor physical, cognitive, or orthostatic exertion. Post-exertional malaise could reflect a delayed failure of recovery systems after demand exceeds an already limited physiological reserve.

Under this framework, correcting a contributor to hypoxia—such as iron deficiency, sleep-disordered breathing, low blood volume, impaired autonomic compensation, inflammation, or vascular dysfunction—may still meaningfully reduce symptoms. But it may be insufficient by itself to produce full recovery once downstream processes have become established. Recovery may require interrupting several interacting loops and allowing time for vascular, immune, metabolic, neurologic, and autonomic regulation to normalize.

This is a conceptual model rather than an established unified explanation for all ME/CFS. ME/CFS is likely biologically diverse: tissue hypoxia may be central in some people, secondary in others, and less important in still others.

I got an interesting request

I wonder if you would be willing to write a blog post looking at my recent test results in comparison to last year? Confirmed diagnosis of ME/CFS. UK NHS only helps with pacing advice.

• First BiomeSight test: 2025-04-17

Following this, 3 self-directed cycles of antibiotics, probiotics, prebiotics, and diet changes based on MicrobiomePrescription results. First 2 cycles increased my baseline and reduced symptoms dramatically, third cycle set me back slightly. Overall very positive.

Unfortunately then was hospitalised later in 2025 with a perforated and infected gallbladder, sepsis. They rotated through quite a few different harsh antibiotics trying to find one which worked. Then in December 2025 went in for surgery to remove the gallbladder, more antibiotics.

• Second BiomeSight test: 2026-03-16

My baseline now is worse again, many symptoms returned. I am loathe to use more antibiotics while some of my bacteria are so low (Akkermansia at 0.006) even though my positive scores are dominated by antibiotic suggestions. Would like to focus on probiotics, prebiotics, herbs, supplements, diet changes for now.

Any insight would be most appreciated.

Confirming the Worst

Going over to the symptom compare tool, we see that you are now worse than a year ago. 140 of 141 symptom forecasts are significantly worse! Seeing number this much worse is unusual but consistent with his events and perception.

Going Forward

My last two post has been evaluating the alternative path — instead of attacking the bacteria causing symptoms, push the person to a statistically significant healthy microbiome. The following links may be worth a reading:

• Another ME/CFS Microbiome Update – Review of a sample
• A new sample and two roads to walk – Review of a sample
• Good vs Bad Bacteria Dogmatic Beliefs – background
• Turning Fixing the Microbiome Upside Down! – background

This approach matches “I am loathe to use more antibiotics” because antibiotics typically are on the avoid lists with the healthy approach and high on the to take list attacking symptoms. It is sitting on the Simple UI page.

Basic Results:

• 52 bacteria were identified — every single one was too high.
• I have broken suggestions into classes below. In general, I have kept them to items with an impact of at least 1.
  • Items listed are order by largest impact first.

Herbs

The top herbs are below. I was delighted {Bofutsushosan} was listed because it is well known increases Akkermansia which he is concerned about.

Food

Flavonoids

Vitamins

Common and OTC Supplements

Probiotics x PubMed

This list is done using PubMed studies.

Probiotics x R2 Model

I prefer the R2 Model because we have a lot more data to use than with PubMed. On the flip side, this does not have clinical studies supporting the choices.

The top probiotic Bacillus thuringiensis suitable for human consumption may be a challenge. Most retail products are formulated to control caterpillars, worms, or mosquito larvae in gardens and standing water, not for ingestion or probiotic use.

Non-Human Retail options

• Home Depot sells Monterey B.T. Bacillus Thuringiensis Pint Concentrate as an online retail product.
• Wilco Farm Stores / Farm Store lists Bonide Bt Bacillus Thuringiensis as a garden pest-control product.
• DoMyOwn sells a dedicated Bt category and says it’s available through their store rather than big-box shelves.
• FBN lists Bt ingredient-based products, including Bacillus thuringiensis subspecies tenebrionis.
• DIY Pest Control lists Bt products and notes common trade names like Thuricide and Mosquito Dunks.

Summary

I look forward to see how well this alternative approach performs. It does not focus on the bacteria associated with his 141 symptoms — instead, we focus on shifting to a healthy microbiome profile (with very high statistical significance, p < 0.0001,) I would suggest retesting every 3-4 months to track progress.

Questions And Answers

Q: It’s interesting to see how some Odds Ratio based suggestions match with the Consensus Suggestions, and some vary wildly.

• A: Suggestions are based on bacteria target and available literature. Literature is sparse and often without replication of results
  • The safest path would be to start with items that are in agreement.

Q: I had one question with regard to whole milk, dairy, and lactose. The Odds Ratio analysis suggested these were positives – this makes my life a lot easier as I was using milk to help ferment and increase the CFU of the probiotics I used last year and hoped to again, and I eat a fair amount of dairy in general (I mostly eat a vegetarian diet with occasional fish, and dairy helps with my protein intake).

However when I ran the Consensus Suggestions earlier this week I got scores of -294.9 for bovine milk products, -120 for whole cow milk, and -158.6 for lactose.

• A: I favor the Odds Ratio. On this point as you have no issues with dairy, keep to your current usage.

Q: Does this mean I likely need to make a choice between the Consensus Suggestions route (which I followed last year) and the new Odds Ratio route?

• A: No, you could start doing a consensus of the consensus and odds ratio. Then add in items that disagree. I would suggest using an ratio evaluation:
  • Consensus: -120 with min of -960, so -(120/960) = -12.5%
  • Odds Ratio: 4 with max of 8, so 4/8 =50%
  • Thus odds ratio would win

Postscript – and Reminder

Other posts dealing with ME/CFS or Long COVID.

I am not a licensed medical professional, and the laws where I live prohibit any activity that could be interpreted as practicing medicine or giving personal medical advice. My work is limited to academic and analytical models, and I restrict myself to the language of science and statistics rather than clinical recommendations.

I cannot tell anyone what they should or should not take. Instead, I can present information about items that, based on numerical and statistical analysis, appear to have better odds of improving microbiome-related measures. I am a trained, experienced statistician with appropriate degrees and professional affiliations, and my role is to interpret data—not to treat patients.

All information I provide is for educational and informational purposes only and is not a substitute for professional medical advice, diagnosis, or treatment. Any ideas, rankings, or “suggestions” derived from my analyses must be reviewed and approved by your qualified medical professional before you decide to act on them.

The answers and explanations I provide describe my reasoning and methodology. They are not intended as medical advice for you or for anyone else, and they do not create a doctor–patient or provider–patient relationship. Always consult a knowledgeable licensed healthcare professional before starting, changing, or stopping any treatment, supplement, or health-related regimen.

This is part of this continuing saga with this person. Prior posts and the labs shown below. Repairing the microbiome is not a single test, take a pill, and you are done. It may be like a long journey by sail through the fjords of Norway: a lot of course corrections!

• The ME/CFS Quest for Health [May 2025]
• Ongoing ME/CFS Journey [Jan 2025]
• ME/CFS Continues Improvement + Lab Read Quality Issues [Feb 2024]
• Rosacea, Circulation and mild CFS [Dec 2021]
• Update on ME/CFS Person [Sep 2023]
• Follow up Microbiome Analysis from a prior post [Apr 2022]

Person’s Summary

I would say that there is no improvement since the last test. So this is still applicable:

I have not been feeling so well lately (since the last year). I would say that my symptoms has become worse. Earlier it has always felt as I have done some progress but the last 18 months it has been the opposite. Earlier I got rid of my muscle and joint pain but it has come back and I have much bigger issues with my red nose and my body feels very stressed.

Also feel very bloated.

• A summary of my biggest issues:
• Get the red nose (some form of rosacea).
• Feel fatigued (both physically and mentally).
• Feeling stressed.
• Brain fog.
• Bloated.
• Lots of gas – I fart and burps a lot.
• Issues with allergies
• Muscle and joint pain

For the last 4-5 years I’ve been eating large amounts of rye and oats.

• Around 150-200 gram of rye bread every day.
• Around 70 gram of oats every day.

Been eating low fat, low protein and high carb (specially from rye, oats, apple juice and potatoes) because this diet seem to reduce my symptoms. As soon as I start to eat high meat and high fat my symptoms get worse.

In this analysis, I am going to look at:

• Changes since the last sample
• Review a new approach that is being incorporated
• Looking at suggestions and the difference between the new approach and the traditional approach

At the end, I suggest following the new approach with the motivation that the traditional approach has appeared to have stalled. The microbiome adapts to antibiotics and diet changes; rotation to alternatives often seems to be needed to keep destabilizing the microbiome dysbiosis.

Changes Between Samples

Going to Old UI/Multiple Samples we compare symptom matching values. We see that just 1 of 42 showed improvement.

Looking at the new Odds Ratio data, we see the number of bacteria identified as critical in different samples below / Odds Estimate. I am not clear on the meaning and significance…

• Odds Estimate: The higher the number, the more likely that the person is healthy
• Number of Bacteria: Not reliable because different bacteria contribute differently to health.

• 2026-03-06: 59 / 1632
• 2025-11-17: 36 / 1588
• 2025-03-30: 20 / 1671
• 2024-12-03: 21 / 1561
• 2024-09-02: 36 / 1611
• 2024-01-22: 58 / 1586
• 2023-09-12: 38 / 678
• 2023-02-22: 52 / 1707
• 2022-08-11: 30 / 886
• 2022-03-25: 24 / 1037
• 2021-12-03: 15 / 1287
• 2021-08-31: 49 / 757

My general reading is that from 2021-2024 there was improvement and now the person is in a new stable healthier state but with still dysbiosis. I am hoping that the switch to an alternative view of solving his health may result in further improvement. In other words, rotation of approaches.

Another View on the Same Issue

In my recent post, Turning Fixing the Microbiome Upside Down!, I introduced a different way to think about repairing the microbiome. A human–society analogy might make it clearer.

Imagine your city is struggling with homelessness, vagrancy, and petty crime. The usual response—especially in the U.S.—is to send in the police. Round up those panhandling on the streets! In microbiome terms, that’s like identifying “bad bacteria” and launching an attack.

But there’s another approach: offer housing, mental health care, and job training. You don’t punish people—you help them heal and reintegrate.

Traditionally, Microbiome Prescription has focused on detecting problematic bacteria and trying to suppress or adjust them. The challenge is that most people have many interconnected symptoms. Research often shows that substance X improves one symptom but worsens another. You end up chasing symptoms—fixing one only to see another emerge or intensify.

A more holistic alternative, which has only recently become possible, is to guide the person’s microbiome toward a naturally healthy state instead. See this post: Mathematically Derived Healthy Microbiome.

Recently I asked the head of a microbiome testing company, what statistical evidence do you have for what is a healthy or desired microbiome profile. How do you obtain the importance of each bacteria? He knew that using means and standard deviation were invalid because of the high skew with the data. His response was requesting his staff to remedy this situation, looking at odds-ratio as a starting point.

---

Evaluation

I am a modeler, not a medical professional. Modelers try putting together mathematics using available data and use that to generate predictions. Once the predictions are made, they are evaluated against any available facts.

Above we have some observations from the person, the model does not know this information — so we can evaluate predictions against this data.

Been eating low fat, low protein and high carb (specially from rye, oats, apple juice and potatoes) because this diet seem to reduce my symptoms. As soon as I start to eat high meat and high fat my symptoms get worse.

Comparing Suggestions

	Health	Symptoms	Novice
Rye	-0.11	-183.5	-352.3
Oats	0.15	-179.2	-742.6
Apple	2.34	-385.1	-351.5
Potato	1.32	-1102.7	-1418.5
High Meat	2.2	155.9	763
Raw Meat	-2.78	105.5	21.2
High Fat Diet	-.79	154.4	-246.1
high-saturated fat diet	-.35	96	-291.1
low-fat diet	0.86	195.9	378.4
Range of Values	-6.82 to 5.43	-2075 to 1359	-2296 to 1461
Best to Take	Catechol {Catecholamines}	restricted-fiber diet {low fiber diet}	restricted-fiber diet {low fiber diet}

Each of the above depends heavily on the bacteria selected and the threshold used. It is interesting to see that the new “Make Healthy” is a clear winner against his observations.

What is particularly interesting with the “Make Healthy” is that values were computed for 1,632 substances. Looking at the list os suggestions, we do not have a mass of antibiotics seen on the other lists. We are not focused on reducing bad bacteria, rather on improving the good bacteria, and letting those address the bad bacteria. The top items are below.

• Bromelain
• N-acetylneuraminic acid {Sialic acid} : a bioactive sugar involved in cell signaling, glycoproteins, glycolipids, and is abundant in the brain; it is linked to cognitive function, memory, and immune function in general mechanistic descriptions
• 1,2-dithiolane-3-pentanoic acid {a-Lipoic acid (ALA)}
• pediococcus acidilactici {P acidilactici}
• lactobacillus paragasseri {L. Paragasseri}
• Rubus fruticosus {Blackberry}
• Eutrema japonicum {wasabi}
• Cucurbita pepo {Pumpkin}
• Alkalihalobacillus clausii {Bacillus clausii }
• Faecalibacterium prausnitzii {Faecalibacterium prausnitzii}
• Capra hircus milk {Goat milk}
• 1,4-linked ß-D-xylopyranosyl {arabinoxylan}
• Gamma-Aminobutyric Acid {GABA}
• Ulmus rubra {slippery elm}
• Musa acuminata {Banana}

My impression is that this is a much friendlier set of suggestions. In fact, the bottom of the list (to avoid) are pages of antibiotics and prescription drugs.

Probiotics Exploration

There are two ways of getting probiotics:

• Using published studies on their impact. In general, each study describes one or two bacteria impacted. This results in low data
• Using the R2 Associations: This is a modelling of their impact with hundreds of bacteria impact estimated.

The new Healthy Algorithm includes R2 recommendations

We got the following suggestions

We will explore how different algorithms evaluate these.

Bacteria	Healthy With R2	Healthy With Studies	Symptoms With Studies	Novice with Studies
Streptococcus thermophilus	1988	-1 to 4	-132 to -139	-132 to -139
Enterococcus faecalis	1291	.6	-579	-579
Bifidobacterium infantis	1124	-2	76	76
Bifidobacterium breve	377	1	213	213
Bifidobacterium longum	365	1	-1423	-1423
Bacillus thuringiensis	96	n/a	n/a	n/a
Pichia kudriavzevii	38	n/a	n/a	n/a
Acidipropionibacterium acidipropionici	22	n/a	n/a	n/a
Aspergillus oryzae	15	.1 – 3	-192 to 8	-192 to 8
Lactobacillus acidophilus	4	0	-574	-574

Keeping to the “When in disagreement, leave it out” a.k.a. Minimal Risk a.k.a. “Do not harm”, we have

• Top choice is Bifidobacterium breve
• Reasonable choice is Bifidobacterium infantis

Alternatively, Streptococcus thermophilus high value, cheap, and easy availability — it is a good candidate to try a 2-4 week experiment.

Personally, I would be tempted to try the following pattern (starting at a low dosage and increasing):

• 3 weeks of Streptococcus thermophilus (up to 10 BCFU)
• 2 weeks of Bifidobacterium breve (up to 20 BCFU)
• 2 weeks of Bifidobacterium infantis (up to 20 BCFU)

Bottom Line

My personal choice would be to go with the “Healthy Algorithm” for the following reasons:

• The traditional approach has appeared to stall, time for a change
• It is heavily based on very statistical significance over the entire scope of bacteria involved (i.e. dense data) but it has not been validated by clinical studies.
• I have always been unhappy about clinical studies because the data is:
  • Messy (typically in the context of one or another medical condition)
  • Small sample sizes
  • Low resolution to bacteria

I am also curious to see how well the “Healthy Algorithm” performs.

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.

My academic training is in Operations Research with a large dosage of lateral thinking (Edward de Bono).

A classic story is below:

One famous story of operations research success during the war involved an analysis of Allied bombers returning from bombing missions over Europe. The military analyzed the location of shrapnel damage and bullet holes in returning bombers, to identify where to place additional armor on aircraft. Operations researchers were brought in at the last minute to do a “confirmatory” analysis, but they recommended that additional armor be placed on bombers everywhere except the places with damage or bullet holes! The operations researchers realized that analyzing damage to returning bombers involved a sampling error. It was the bombers that did not return that needed extra protection—and they needed it in the most vulnerable places (the places not damaged on the returning bombers).

In the past, most medical work has focused on bacterial shifts statistically linked to individual symptoms. Think of the “bullet holes” problem: the literature usually looks at one symptom at a time, while real patients often present with dozens.

Recently, I started using odds ratios instead. Most people know odds ratios from smoking and cancer risk, but they can be applied broadly—for example, the odds of working at Microsoft if you graduated from a particular university.

Using about 5,500 samples and roughly 350 symptoms, I built odds tables and then tested those odds ratios against a reference set of healthy individuals. To my surprise, sample after sample showed the highest odds for being asymptomatic, far more often than I expected.

On reflection, this implies we now have a well-defined, statistically grounded model of a healthy (asymptomatic) microbiome. That was the “lightbulb” moment.

Instead of hunting for individual “holes” and trying to patch them, we should look at all the shifts away from this asymptomatic model. Once those shifts and their contributions (odds ratios) are identified, we can use published research to determine what is most likely to normalize the microbiome. A long list of symptoms (bullet holes) stops being the target; the real target becomes making the microbiome asymptomatic.

Some past links:

• Significance Ordered list of Bacteria Associated with Autism using Odds Ratio
• Mathematically Derived Healthy Microbiome
• Generalized Odds Ratio to predict Symptoms from microbiome reports
• Open Access Odds Tables

A walk through on applying the above methodology pattern.