This is a thought experiment transformed into an implementation for people to experiment with.
In doing educational reviews of a variety of samples, I came across a person whose progressed had slowed. In trying to understand why [The ME/CFS Quest for Health], I looked at metabolites level between his current sample and previous sample. To my surprise, the highest ones (highest percentile) had barely budgeted.
I looked at the prior Dec 24 sample and compare the KEGG Compounds to the current sample starting with the highest percentile ones:
While the bacteria changed, the extreme metabolites remained high but with a few reducing. There is a potential to generate suggestions based on these KEGG compounds — a little messy and definitely pushing inference into new turf.
An Idea
I asked Perplexity.ai on how to reduce a few. A typical response is shown below
On MicrobiomePrescription.com, the suggestion algorithm works solely off the bacteria that is reported by the microbiome test. This is done by using facts harvested from US National Library of Medicine studies. There are no (or likely extremely few) studies dealing with diet and metabolites.
The key phrase is reported by. We know that reporting is not standardized and often using only 16s.
Idea!
Current logic on MicrobiomePrescription.com is bacteria => suggestion impact. What if we add another approach: metabolite => normalized bacteria distribution => suggestions. We want this to have less randomness than 16s. The folks at PrecisionBiome.Eu shared 1000 shotgun results from healthy individuals with me so I could construct a normalized bacteria distribution model. From this model, I computed metabolites using data from KEGG: Kyoto Encyclopedia of Genes and Genomes and ended up with a facts table consisting of:
Metabolite
Suggestion / Modifier
Estimated Impact
The metabolite is identified by KEGG ID.
Implementation
Since the microbiome and its metabolites are very interconnected and interact with each other. I decided that looking at the top and bottom 5-10%ile (i.e. those with a percentile ranking of 90-95%ile or higher, a percentile of 10-5%ile or lower) was a reasonable approach. There is a little trust that the central limit theorem will generate reasonable results and allow metagenomics to be directly used for getting suggestions.
On the [Research Features] tab, this panel has been added:
This produces a report listing the Metabolites targeted (High and/or Low) and then Suggestions
Observation
To me, what I found very interesting is that there are a few that are very high in impact with rapid drop off. This means there are only a few critical items to add to the general bacteria-based suggestions.
Hello, I’m sorry to message you privately, but I’m reaching out for help regarding my 15-year-old daughter, who has been homebound with ME/CFS for 2.5 years since contracting COVID in 2022. I came across your story on Facebook, and I felt truly inspired by how you managed to overcome ME/CFS by working with your microbiome. We are currently trying to follow a similar path.
We’ve recently done a Biomesight 16S test for her. As expected, it showed typical deficiencies, like a lack of Lactobacillus bacteria, along with an overgrowth of sulfate-reducing bacteria (possibly SIBO). Since we’re unsure how best to approach this dysbiosis, we sought the help of a microbiome specialist through Viola Sampson in the UK. She recommended lactulose, Lactobacillus reuteri, Lactobacillus rhamnosus, Lactobacillus plantarum, Bifidobacterium breve, along with Allicin and Goulds tincture from Australia. We’re just beginning this treatment, so it’s hard to say much about progress yet. We’ve started with Lactobacillus rhamnosus, plantarum, and breve, and she’s doing well with these so far.Honestly, I’m a bit concerned about these Lactobacillus bacteria because I read somewhere that all people with ME/CFS have some degree of lactic acidosis, so I’m worried that these probiotics might produce even more lactic acid. When I brought this up with my practitioner, she wasn’t aware of it.
I also uploaded a Biomesight test of my daughter to your Microbiome Prescription page, but I noticed that your site has somewhat opposite recommendations for her microbiome, such as advising against lactulose. To be honest, I’m struggling to navigate your page, and it’s a shame because I truly want to follow the recommendations accurately. I was hoping to identify which specific antibiotics or probiotics might be the best fit for my daughter’s case, but I’m not sure how to interpret that information from your site.
Currently, my daughter is mainly dealing with POTS (Postural Orthostatic Tachycardia), histamine intolerance, chronic fatigue, anxiety and panic attacks, and digestive issues. She’s become highly sensitive to various foods and medications, and it all points towards dysautonomia. Although she’s taking many supplements, she reacts to some, like iron supplements, which I suspect might be due to certain bacteria that feed on iron. She has many vitamin deficiencies, yet we can’t supplement effectively due to these reactions. It’s so difficult to manage.
I apologize for the long message, but I wanted to be as clear as possible about her situation. I’d be incredibly grateful if you could review her Microbiome Prescription and offer any insights on what stands out in her microbiome and where we might start. I’m also curious about any thoughts on the potential use of antibiotics or probiotics, as our microbiome practitioner is generally against antibiotics, though I know some people with ME/CFS have found success with a well-planned antibiotic approach.
Here, I am including the link to our microbiome analysis from Microbiome Prescription.
Analysis
First, disagreement between sites is well known and explained here: Why sites suggestions disagree on the same data. Microbiome Prescription tuned it’s advice by doing cross-validation for several conditions, for example: Cross Validation of AI Suggestions for Nonalcoholic Fatty Liver Disease. ME/CFS was the first explicit studies done. To the best of my knowledge, no other microbiome site has done cross-validations of their suggestions and been public in showing results.
Individual practitioners are hard to evaluate because they often find patterns that works for some people by trial and error. It is a rare practitioners that can provide documentation on their suggestions.
Quick boot strap
Long COVID is one condition that has a built in cross validation list of suggestions. This is on [Old Ui] / [Changing Microbiome]. POTS is not currently on the list because of insufficient studies.
This identified the following bacteria as being probable according to the published literature. The number of cross reference numbers after each item, indicate the number of studies For example Ruminococcus – genus : Low was reported in 4 studies.
The suggestions (based on microbiome shifts cross reference with substance that improved ME/CFS from studies are below. The number of cross reference numbers after each item, indicate the number of studies – as above. This leads to the best suggestions being the ones with the most cross reference. Thus:
Magnesium supplements – 6 studies
Vitamin B9 – 6 studies
Coenzyme Q10 – 6 studies
Far infrared Sauna – 4 studies — as a personal note, we purchased a small one at Costco and use it regularly as preventative.
Vitamin B1 – 3 studies
Omega-3 – 3 studies
Ribose – 3 studies
licorice – 3 studies — we usually use Spezzatina and just suck on them
carnitine Amino Acid – 3 studies
Melatonin – 3 studies
Selenium supplement – 3 studies
This is a significant list and I noticed that none of these were suggested by Viola Sampson despite published literature saying they help.
My suggestion would be to add one of these every three days, noting any changes that results. For dosages see Dosages for Supplements, start low and work up. The above will take a little over a month. All of these items can be taken continuously and together.
Probiotics
Probiotics are a popular “cure-all” which in some cases help and in other cases hurt. For example, lactobacillus probiotics often will increase brain fog.
Looking at probiotic with positive values, most are actually hard to obtain. For example Kefibios is only sold in Italy. Mutaflor in only a few countries. Of the choices, I would try Mutaflor after adding in the items above — but be warned, it may trigger severe die-off.
Top items
The list below are other things that likely have never been studied for ME/CFS but should have significant impact on the bacteria shifts.
On the other side, the following should be avoided:
Food Site
Going to https://food.microbiomeprescription.com/ and entering your login token will show the nutrients computed to help most. Iron supplements or food high in iron is at the top; for example thyme, basil, and my favorite Caterpillar, roasted ;-). Both herbs have positive recommendations.
The second one is found in cranberry (a suitable seasonal food) and raw Olive. The third one is found in maize, rye and Hard wheat, semolina. HOWEVER, none of these are recommended in the list of suggestions. I usually cross reference the two for safety.
Next Steps
I would continue with additional suggestions (1 and 2 studies) at the same pace. Two weeks after the last one was added, do another microbiome test (same firm of course) and get back to me for a follow up analysis if needed.
Postscript and Reminder
As a statistician with relevant degrees and professional memberships, I present data and statistical models for evaluation by medical professionals. I am not a licensed medical practitioner and must adhere to strict laws regarding the appearance of practicing medicine. My work focuses on academic models and scientific language, particularly statistics. I cannot provide direct medical advice or tell individuals what to take or avoid.My analyses aim to inform about items that statistically show better odds of improving the microbiome. All suggestions should be reviewed by a qualified medical professional before implementation. The information provided describes my logic and thinking and is not intended as personal medical advice. Always consult with your knowledgeable healthcare provider.
Implementation Strategies
Rotate bacteria inhibitors (antibiotics, herbs, probiotics) every 1-2 weeks
Some herbs/spices are compatible with probiotics (e.g., Wormwood with Bifidobacteria)
Verify dosages against reliable sources or research studies, not commercial product labels. This Dosages page may help.
Individual health conditions may make some suggestions inappropriate. Mind Mood Microbes outlines some of what her consultation service considers: A comprehensive medical assessment should consider:
Terrain-related data
Signs of low stomach acid, pancreatic function, bile production, etc.
Detailed health history
Specific symptom characteristics (e.g., type and location of bloating)
A reader messaged me about some issues she was having
Hi, could I just have a quick question? I read in the Gut Health group on Facebook that you wrote that if there is too much, for example, lactobacillus, it can cause neurological problems. I suffer from anxiety and depression and was recommended a transplant of intestinal microflora, which made the condition 100 times worse and since then I can’t get out of it and the doctors don’t know what to do with it. I’m still trying to treat dysbiosis, but now I don’t know if the problem is one of the good bacteria? Thank you very much.
yes, I have a biomesight and a GI map, there is an overgrowth of Prevotela, Streptococus, Enterobacter and Citrobacter and a little bifido and lacto. I have yellow stools after the transplant, if I don’t take probiotics. But it seems that nothing works, diet, antimicrobials, probiotics, enemas with probiotics, prebiotics, nothing helps
Initial Comments
This person is not in the US. She lives in a place where Fecal Matter Transplants is allowed for many conditions than the US (where it is only authorized for Clostridioides difficile –after everything else has failed). I view FMT as Russian roulette hoping that a silver ballet will happen to end up in the cylinder. IMHO, before a FMT is done we need at least two shotgun microbiome tests done. One for each candidate donor and one for the recipient. These need to be carefully reviewed by a third party who is very well informed on the microbiome. Only the best donor will be used. After the FMT, monthly shotgun reports of the recipient microbiome should be done for at least 6 months.
Analysis
The first step is to look at predicted symptoms, most are neurological, with the two reported symptoms sitting high up the list.
Comorbid: High Anxiety – [66.6%]
General: Depression – [64.1%]
I marked all of the items with depression and anxiety and then asked for suggestions. The top items are shown below,
The failure to understand that all probiotics are not created equal is a common problem. Often I have heard “I tried probiotics and it did not work”. That is not surprising because often they are sold with dozen of species in one bottle — “because the more species you have, the better your sales will be” from manufacturers and influencers.
You need to get specific species and ideally recently manufactured. A bottle of probiotics stored in an unrefrigerated warehouse for 12 months may have very few viable bacteria left. When they get to a retail store, they may be put into a refrigerator — but that is too late.
Where do I get the probiotics?
I prefer single species — and where I get mine?
Single species with (almost) no fillers. There are precisely three sources that I use:
Maple Life Science™: No strains yet, but shipments usually have manufactured date within 4 weeks of arrival (i.e. FRESH). Contains FOS
Bulk Probiotics: US based Newbie — but has some species not available at the other two sites. No other ingredients just the bacteria. Specifically, Lactobacillus Jensenii that has great potential for Crohn’s disease.
NOTE: none of these sell though retail outlets. This keeps their costs down and their product fresh.
Another Alternative to get Suggestions
On the old UI we have this section and we have enough studies for Depression show up.
With this sample, we have the following bacteria matches against published studies (with links to the studies).
This results in the suggestions below. Each suggestion has also been reported in studies to help depression. This means that the odds of them working is pretty good.
Treatment Suggestions for
This report is for Reader using this sample BiomeSight:2022-10-25 Self 🛑 . It uses their reported medical conditions, microbiome sample, US National Library of Medicine, and a fuzzy logic expert system to compute recommendations balancing study reliability and contraindications. These suggestions should always be reviewed by a medical professional before starting.
NOTA BENE: This is working solely from published studies. Other suggestions algorithms are available on Microbiome Prescription. The URL above may be sent to your MD if you wish to share it.
The reported condition(s) are
This person has a significant amount of bacteria known to form biofilms
Substances with a 🦠 are reported to reduce biofilms. See for studies.
Depression – Depressive Disorder
Omega-3 Fatty Acids: Some studies suggest that omega-3 supplements, particularly those rich in EPA (eicosapentaenoic acid) and DHA (docosahexaenoic acid), might have modest benefits as adjuncts to traditional treatments for depression. Omega-3s are essential for brain health, and they may have some mood-stabilizing properties.
Vitamin D: Low levels of vitamin D have been associated with depression. While the exact relationship is complex and not fully understood, maintaining adequate vitamin D levels through supplements or exposure to sunlight may support overall mental health.
B Vitamins: Some B vitamins, such as B6, B9 (folate), and B12, are involved in neurotransmitter synthesis and may have a role in mood regulation. Folate deficiency, in particular, has been linked to depressive symptoms.
Probiotics: The gut-brain connection has led to studies exploring the potential impact of probiotics on mental health. Research suggests that gut health may influence mood, and some studies propose that certain probiotics might have a modest effect on reducing depressive symptoms. However, more research is needed to determine specific strains, dosages, and their impact on depression.
Significant Bacteria Shifts
Based on the existing literature on the US National Library of Medicine and this microbiome sample, we have the following matches for bacteria shifts. There is a growing body of literature finding that the effectiveness of interventions depends on the existing microbiome. We filter by documented interventions that helps some with this condition and suggestions based on this person’s specific microbiome to produce this “double validated” list.
Bacteroidaceae – family : Low 516 Bacteroides – genus : Low 13162022 Bifidobacterium longum – species : Low 710 Collinsella – genus : Low 9 Collinsella aerofaciens – species : Low 9 Escherichia – genus : Low 2512
Lactobacillus – genus : Low 5814151718192123 Parabacteroides – genus : Low 1120 Porphyromonas – genus : High 1 Prevotella – genus : High 3424 Sphingobacterium – genus : Low 13 Streptococcus – genus : Low 6
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.
There is no definitive right way to determine how to correct a dysbiosis. We just do not have enough studies. Above, you have two main approach (with some overlap of suggestions)
Working off the microbiome that are too high or too low.
We cross check probiotics suggestions using KEGG data
Working off the microbiome using only peer reviewed studies for one condition: depression.
This report should have high creditability with most medical types — because all of the evidence used to make the report is cited.
I have not been feeling so well lately (since the last 6 months). I would say that my symptoms has become worse. Earlier it has always felt as I have done some progress but the last 6 months it has been the opposite.
At the end of January I had my appendix removed. Since then I have felt even worse. Received some antibiotics while I was hospitalized. 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 3 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.
Quick Overview
I will continue with a table showing recent changes (see above for earlier values)
Criteria
3/30 2025
12/3 2024
9/2 2024
1/22 2024
2/22 2024
Lab Read Quality
7.6
9.8
9.1
7.9
9.7
GanzImmun
10
14
16
16
15
Outside Range from Lab Teletest
21
17
23
20
24
Outside Lab Range (+/- 1.96SD)
10
7
12
5
10
Outside Box-Plot-Whiskers
59
47
48
54
42
Outside Kaltoft-Moldrup
111
85
113
123
139
Bacteria Reported By Lab
718
689
600
511
666
The most striking change was the 4% increased number of bacteria. Looking at Symptom Pattern Matching, we see significant improvement with 15% with significant improvement.
Current Takes Evaluation
I have put together a video trying to describe the complexities of shifting the microbiome. My own experience during a flare was “suggestion whiplash”, the suggestions from one test became avoid on the next and became suggestions on the next test. This is not what I was expecting and caused me to question the process — until I dug deeper and did some modelling. My understanding is in this video.
What he reports taking is below. I look at the suggestions and added the weight after each.
amoxicillin: +490.3
Noni -206.1
Propolis {Bee glue} +19.5
Dandelion + 155.3
allium sativum {garlic} -214.4
Parsley + 145.3
Grapefruit seed extract +168.8
mutaflor -78.8
Takes flipping to avoids is not unexpected. It does emphasis the need to do regular tests, especially when progress slows or reverses.
Building Suggestions
Since we have symptoms we use Beginner-Symptoms since it will focus on bacteria associated with symptoms present.
Looking at the Consensus report we see the top 3 antibiotics are all ones associated with CFS
The other items is interesting and would suggest Whole Milk (high Fat) (Yogurt) from A2 cows, I do not know if that is easily available in his country. I happen (as a recovered ME/CFS person) to have some to my daily morning porridge.
The suggestions above do not fit typical patterns that I have seen. I went back and did “just give me suggestions” in case the bacteria filtering by symptoms caused some odd twist. Results were similar as shown below.
One More Analysis
I looked at the prior Dec 24 sample and compare the KEGG Compounds to the current sample starting with the highest percentile ones:
While the bacteria changed, the extreme metabolites remained high but with a few reducing. There is a potential to generate suggestions based on these KEGG compounds — a little messy and definitely pushing inference into new turf.
I have decided to build an adjacent Suggestions Agent using metabolites ONLY. The microbiome is a very complex system and there is a possibility that the metabolites approach may work better. Stay tune!
Reconciliation of Recent Diet and Suggestions
During my own recovery, I had “whip-lash” between suggestions from one test until the next test. One test results had to take, the next result was the same items on the avoid list. This “pendulum” swinging back and forth may be happening here. My own response was to be “less religious” in keeping to the suggestions (i.e. “moderate compliance”) and retest after 6 weeks doing suggestions. The pendulum swing dampened down and lead to a full remission (with patience).
The 300 grams of fiber (Rye, Oats) should be reduced. If you can get a willing MD, then you may wish to rotate to a different antibiotic because of the risk of antibiotic resistance occurring.
And thus have the ability to compute the theoretical differences.
We also have these collections of studies which we can use by flipping things to be negative cognitive function:
Cognitive Function
Intelligence:Comprehension, Cognitive Ability
This resulted in 71 bacteria.
Results
For Sugar we had agreement between reported shift and cognitive issues for the following:
Bacillota
Bacteroides
Coprococcus
Desulfovibrio
Dorea
Escherichia coli
Faecalibacterium prausnitzii
Lachnospiraceae
Ruminococcus
Streptococcus
For Fat we had agreement between reported shift and cognitive issues for the following:
Bacillota
Bacteroidaceae
Bacteroides
Clostridium
Coprococcus
Coriobacteriaceae
Dorea
Faecalibacterium prausnitzii
Oscillospira
Phascolarctobacterium
Porphyromonadaceae
Ruminococcaceae
Ruminococcus
With Fat we had significantly more contrary shifts than with Sugar.
Bottom Line
Both High Fat and High Sugar in isolation appear to impact cognitive function. High Fat has the appearance of having less impact in isolation than high sugar. The following shifts seem to be common with these:
A few days ago I posted the results for Bacteria Association (with graphics). I did some operations Research black magic in transforming the data. This black magic is a key part of a patent application that has been filed.
Over the last decade, I have been focused on understanding the statistics of the microbiome bacteria. My multiple degrees are in Probability and Statistics, hence the desire to build mathematical models for the microbiome bacteria.
One of my key observations is that “one model does not fit all taxa“. One observation is very consistent: no bacteria fits the gaussian (normal or bell curves) rendering the use of mean and standard deviation not only suspect, but naively dumb.
This post exhibits the challenges. We take 1000 Shotgun samples of healthy people using 10 million reads and look for associations by doing classic linear regression. We apply a variety of monotonic increasing transformations to the percentage/counts and see where we get the most relationships with R2 > 0.25.
First Pass Analysis
I decided to see how well “common textbox solutions” would do compared to my “Black Magic” monotonic increasing transformation. If people want to suggest other monotonic increasing transformations, I am very willing to run other transformations on this dataset and add it to this report.
Method
“Black Magic”
Using Percentage / Count
Using Log(Count)
Number of R2 > 0.25
15,183
1,764
9,616
Number with higher R2
1,356
7,167
Number with lower R2
408 [13,827]
2,449 [8016]
Numer of items with R2 > 0.25
The [ ] is the sum of not found and lower R2.We see that the “Black Magic” clearly found more statistically significant relationships. Taken in isolation, “Black Magic” also found more relationships with a higher R2. The Log(Count) items with a higher value are worth some extra analysis.
Percentage or Count
This is the typical naïve approach used by people who rote-learn statistics. We found only 10% of those we got via “Black Magic”. Many relationship were very similar, they tend to be for bacteria with low rates of detection (i.e. occurs in < 25% of samples) and low amounts of bacteria. To translate, very few distinct values in these subsets.
Other has significant differences
A chart comparing results.
Log(Count)
Using a log(values) is a common statistical trick dealing with non-gaussian (normal/bell curve) data to get semi-normal data. For R2 that were higher than “Black Magic” we have:
Mean Difference: 0.23
StdDev Difference: 0.09
Maximum Difference: 0.43
We have a sample of the greatest difference below, and note that the sample size was relatively small. The top line has R2 of 0.999. This suggests that we may need to exclude taxa that has less than N distinct values (a possible follow up post)
Restricting to samples where we have 300 or more (incidence of detection: 30%). In this case Log(Count) with higher R2 exceed those with lower R2 compared to “Black Magic”
Method
“Black Magic”
Using Percentage / Count
Using Log(Count)
Number of R2 > 0.25
10,733
702
8,121
Number with higher R2
494
6130
Number with lower R2
208 [10239]
1991 [4603]
Bottom Line
Log(Count) produces acceptable results while failing to detect 20% of those detected by “Black Magic”. The ideal solution would be to do both methods and take the highest R2 from each regression. I await other suggestions for monotonic increasing transforms to try. It is very clear that using counts / percentage is a poor statistical choice.
There is a follow up post suggested based on the density/sparseness of different values. Having too few distinct values appears to over-fit and produce suspect/false higher R2.
Methane may be reduced by up to 98% by eating a small amount of Red Seaweed. Bromoform in red seaweed inhibits a key enzyme used by microbes to produce methane gas. It is commonly found in red seaweed Asparagopsis taxiformis(Recommended reading)
Asparagopsis is one of the most popular types of limu.[4] in the cuisine of Hawaii, it is principally a condiment.[5] It is known as Limu kohu in the Hawaiian language, meaning “pleasing seaweed”.[6]Limu kohu has a bitter taste, somewhat reminiscent of iodine,[7] and is a traditional ingredient inpoke.
In reviewing the literature on different types of seaweeds, most studies found that they reduced methane. Consumption of common seaweeds supplements or foods are a viable approach. The levels of Bromoform may not be as high, but may be enough to cause changes while generally considered safe to consume..
There are no studies on using seaweed with SIBO that could be located.
L-lactic acid (L-lactate, (S)-lactic acid, or (+)-lactic acid):
This is the form produced in human metabolism, especially during anaerobic glycolysis (when oxygen is limited, such as during intense exercise or tissue hypoperfusion).
L-lactate is the predominant form found in human blood and tissues.
D-lactic acid (D-lactate, (R)-lactic acid, or (−)-lactic acid):
This form is produced mainly by certain bacteria during carbohydrate fermentation, including some gut bacteria.
Humans produce very little D-lactate, but it can accumulate in specific conditions, such as short bowel syndrome, where bacterial overgrowth leads to increased D-lactate production and absorption. Typically this form often manifest itself as Brain Fog.
Lactic acidosis refers to the accumulation of lactic acid in the body, leading to a decrease in blood pH. It is classified based on the underlying cause:
Type A Lactic Acidosis:
Caused by tissue hypoperfusion and hypoxia (lack of oxygen), leading to increased anaerobic metabolism and L-lactate production.
Common in shock (septic, cardiogenic, hypovolemic), severe hypoxemia, or cardiac arrest.
This is the most serious and common form.
Type B Lactic Acidosis:
Occurs without obvious tissue hypoxia or hypoperfusion.
Subdivided into:
Type B1: Associated with underlying diseases (e.g., liver failure, cancer, diabetes).
Type B2: Caused by drugs or toxins (e.g., metformin, antiretrovirals).
Type B3: Due to inborn errors of metabolism or microbiome dysbiosis.
Can also result from intense exercise, seizures, or certain metabolic conditions.
D-Lactic Acidosis:
A rare form caused by excess D-lactate, typically in patients with short bowel syndrome or after certain intestinal surgeries.
Human enzymes cannot efficiently metabolize D-lactate, so it can accumulate and cause neurological symptoms (encephalopathy)
In Home Treatment Options for Normal Acidosis
The common approaches include:
Vitamin B1 or Thiamine : A deficiency of this vitamin can cause lactic acid issues
Water / hydration: Goal is to urinate out the excessive lactic acid
Stop any medication associated, to do this do google search or use perplexity.ai naming your medication or supplement and asking if lactic acidosis can be cause by it. Example below
Treatment Options for d-Lactic Acidosis
“Symptoms typically present after the ingestion of high-carbohydrate feedings. Neurologic symptoms include altered mental status, slurred speech, and ataxia, with patients often appearing drunk. Onset of neurologic symptoms is accompanied by metabolic acidosis and elevation of plasma D-lactate concentration. “
“Treatment includes correcting the acidosis and decreasing substrate for D-lactate such as carbohydrates in meals. In addition, antibiotics can be used to clear colonic flora.”
“Oral antibiotics that are poorly absorbed are most effectively used locally in the gut—these include clindamycin, vancomycin, neomycin, and kanamycin”
“There have been reports as described above regarding probiotics being implicated as a causative agent in a few cases of D-la”
Bottom line for d-Lactic Acidosis
Reduce or eliminate carbohydrates
Antibiotics
Avoid probiotics
Get a detailed microbiome report (ideally shotgun) to identify candidate bacteria and then alter diet appropriately.
See what encourage it here. MAKE SURE TO EXCLUDE everything that could contain d-lactic producing probiotics (i.e. ANY probiotics, i.e. Yogurt). Items that modifies Veillonella are there.
I’d love some additional help, please. I’ve done two BiomeSight.com tests. I followed the suggestions after the first test and my microbiome has changed and some of my symptoms are improving. However, I couldn’t tolerate any of the bifidobacterium strains I tried, all of them caused very painful long-lasting migraines. Despite taking them for a combined 6wks (3 different strains for 2wks each), my bifidobacterium levels look unchanged. The suggestions do say that ‘No Probiotics without some adverse risks could not be identified.’ so maybe it’s better I just avoid them altogether for now?
I was diagnosed with ME/CFS 16yrs ago, after EBV 22yrs ago.
I caught Covid-19 in 2023.
I was diagnosed with chronic migraines in 2024 – they have increased in severity and occurrence over the last 5yrs, since the Covid-19 vaccines, though I can’t be sure it’s related.
My primary symptoms are: fatigue, pem, migraines, brain fog, ibs, acne, and hair loss.
I give my permission to use the above information anonymously for a blog post.
Analysis
I smiled when I saw ” ‘No Probiotics without some adverse risks could not be identified” and “I couldn’t tolerate any of the bifidobacterium strains I tried“. It seems that the expert system are making good (probable) suggestions. Suggestions are based on odds and not guaranteed.
Pass 1 – Based on Reported Symptoms
When there are many symptoms, my usual path is to get symptoms entered and then get suggestions focused on the bacteria likely associated to those symptoms. This is a targeted approach.
This person had entered any symptoms for their latest sample, and did for the sample from 7 months prior. 4-9 months between samples is what I advocate (balancing costs and time to change the microbiome).
I usually check all of the types of suggestions (I have no ideological position against using any of the types)
Then on the resulting page we see 12 bacteria that are the most likely causes. 2 low and 10 high. Suggestions are computed using five(5) different algorithms and then we use Monte Carlo Model to improve the odds of making good choices. Why different algorithms — simple, microbiome tests are fuzzy in their identification and many different criteria for selecting bacteria are advocated in the literature.
We go to the Consensus Suggestions and sort by Take Count — to get what all agrees about.
Looking at positive 5’s only:
Vitamins
Vitamin B2
Vitamin B1
Zinc
Amino Acid
Melatonin
Carnitine
Glutamine
Taurien
Antibiotic (Only 5’s)
loperamide hydrochloride Loperamide is most commonly used to treat acute and chronic diarrhea, including traveler’s diarrhea and diarrhea associated with inflammatory bowel disease (IBD).
florfenicol. Florfenicol is effective against a wide range of bacterial pathogens in animals, including both Gram-positive and Gram-negative bacteria. It is commonly used to treat respiratory infections, gastrointestinal infections, urinary tract infections, and other bacterial infections in livestock and companion animals
AtorvastatinAtorvastatin belongs to a class of medications known as statins, which work by inhibiting HMG-CoA reductase, an enzyme involved in cholesterol synthesis. By reducing cholesterol production in the liver, atorvastatin helps lower total cholesterol, LDL cholesterol (often referred to as “bad” cholesterol), and triglyceride levels.
It is interesting that Lactobacillus dominate with just one Bifidobacterium. I would carefully try these, one at a time, starting with a low dosage and increases, then change every 1-2 week to the next (keeping notes!!!), My preferred source of probiotics are listed here.
Pass 2 – Based on PubMed
I view this method as less accurate but the suggestions are ideal for discussion with a MD if antibiotics or other prescription items are suggested. It is available as the last item.
Rather than detailing items, I attached the report below
I’ll give this new round of suggestions a go, and then I’ll do another test.
I don’t have a willing GP (or vet, lol) to prescribe antibiotics but it’s very interesting that statins suggested – high cholesterol runs in my family and a lot of them are on statins.
The cholesterol issues are often DNA related… and DNA also impacts the microbiome. DNA is hard to change, the microbiome is easier.
From Perplexity: High cholesterol levels can indeed be influenced by genetic factors, with both common and rare gene variants playing significant roles in LDL cholesterol regulation. Here’s a breakdown of the genetic mechanisms involved:
Key Genes Affecting Cholesterol
LDLR (LDL Receptor) Mutations in this gene (chromosome 19) disrupt LDL cholesterol clearance, causing familial hypercholesterolemia (FH). This autosomal dominant condition leads to lifelong elevated LDL levels (200–300% higher in heterozygotes) due to defective receptor production or function126.
APOB (Apolipoprotein B) Mutations in APOB impair LDL binding to receptors, reducing clearance. For example, the APOB variant causing “familial ligand-defective apoB-100” increases LDL by 200–300%17.
PCSK9 Gain-of-function mutations in this gene degrade LDL receptors excessively, raising LDL levels. Conversely, loss-of-function variants (e.g., in 2% of African Americans) lower LDL by 30% and protect against heart disease168.
E4 carriers have ~5% higher LDL due to rapid lipoprotein clearance and LDLR downregulation.
E2 carriers have ~5% lower LDL but risk familial dysbetalipoproteinemia13.
Inherited Disorders
Familial Hypercholesterolemia (FH): Caused by mutations in LDLR, APOB, or PCSK9. Affects ~1/250 people, leading to LDL >190 mg/dL and premature atherosclerosis if untreated146.
Familial Hypobetalipoproteinemia: APOB mutations reduce LDL production, resulting in very low cholesterol levels13.
Autosomal Recessive Hypercholesterolemia: Rare ARH mutations cause LDL receptor dysfunction, leading to severe cholesterol elevation1.
Polygenic Influences
Most hypercholesterolemia cases involve interactions between multiple common variants (e.g., APOE, NPC1L1) and lifestyle factors. These variants individually exert small effects but collectively contribute to cholesterol variability137.
While genetics set baseline risks, diet and exercise remain critical for management, especially in individuals with predisposing variants368. Genetic testing is recommended for suspected FH to guide early intervention
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.
Microbiome Prescription has a rich collection of annotated samples from different labs (uBiome, Ombre, Biomesight). The samples are annotated with self declared symptoms from a list of 548 different symptoms/diagnosis. 328 symptoms had statistically significant associations.
Biomesight: 4169 samples
Ombre: 1514 samples
uBiome: 795 samples
There are several possibility of associations to these symptoms, including:
Bacteria Association
Enzyme Association
Metabolite Association which we can decompose into
Production
Substrate (Consumers)
Net Metabolite (Production – Consumer)
For each of these 5 vectors, we use these three statistical methods and set out criteria to p < 0.005:
Fisher’s exact test on prevalence of bacteria
Mann Whitney Wilcoxon Test
t-Test on Means
We used KEGG.JP data as a poor man method of compute metabolites.
Below we have counts of the associations found. It is clear that bacteria associations are weaker(fewer) than Enzymes by a factor of 4-10. With metabolites, the net metabolite appears a poorer estimator than either producers or substrates.
As would be expected, large population, we find more associations as the population increases.
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