Intent and Purpose

Be yourself; Everyone else is already taken.

— Oscar Wilde.

I am a high function ASD person in the late 60’s. I am a data scientist, artificial intelligence engineer, former high school science teacher etc. Needless to say, the term autism or ASD was unknown while I was growing up. The classic delay in speech (I did not start talking until I was almost 9 y.o.) and other characteristics were ascribed to some form of brain damage. Three causes were speculated: forceps delivery, German Measles at 18 months and the medication that my mother was give to keep from miscarrying (she had 6 miscarriages before me).

Today, I know that I was high risk because my father was 44 when I was born (Parental Age at Conception and the Relationship with Severity of Autism Symptoms. 2019). My childhood was not fun, because I understood enough about my situation that I was in terror for most of it. The terror caused me to work hard and I found success in a very non-social activity: mathematics and mathematics competitions. I placed in the top 3 repeatedly in both my Province and in Canadian Mathematics Competitions. That’s enough of my story.

Purpose of this Blog

Over the last few years I have became focused (the typical uber focus of an ASD person) on the microbiome to deal with family health issues. My primary focus has been on myalgic encephalomyelitis on which I have written some 1300 posts here. Out of that, I developed an analysis site using reference site and citizen science site called Microbiome Prescription. I have also became active in a Facebook group The Gut Club: Stool Test Discussion Group. This group had resulted in contact with many mothers with autistic children. Needless to say, I have both empathy for the mother and for the children (been there myself before there was support!).

This site is very open to guest posts. I do request that they be well researched with links to source studies. I hate to be ‘anti-social’ and ignoring chat-board opinions and consensus — but what do you expect from someone with ASD? 😉

As interesting notes comes across my desktop, I will explore and attempt to write up posts on what we know today.

I will start this blog by copying across some blog posts that I have done on Autism elsewhere.

Suggested watching and subscribing to:

Child: ASD, PANDA, Severe Gastro Problems

Foreword – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that 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.

Back Story

I enclosed 3 labs: Her last GI MAP, an older OAT, and recent OMBRE. 

I have done work since the OAT, obviously. 

She was diagnosed with ASD around 20 months old. Since birth severe gastro problems. Re-occurring vomiting and severe GERD. Gastro preformed her first upper scope at age 2.5. He found some food in her stomach. Gave her a gasteopresis diagnosis. At age 5, her second scoop and biopsies and her gasteopresis  DX remained. Found nothing on biopsies. Her vomiting stopped once I changed diet by 3 years old. (It was a dairy allergy causing her to vomit once I figured it out, she never vomited again) I don’t believe the GP diagnose fits her and she can’t do the emptying study so he based this dx off food in gut per two scopes. 

  • PANS/PANDAS dx at age 3.5.
  • Has not had a fever since 12 months old. 

She is non speaking 6 years old and has cried on and off in pain her whole life. We’ve believed it was her gut from day one . She had a bad smell most of her life coming from her gut.(breathe) I believe this is clostridia as she has tested high with every stool test we’ve ever ran. It got better briefly with a course of abx but came back worse. The smell is the  worse when she wakes in the morning. Her stool has always been extremely foul smelling. She has taken some form of probiotics since she was 1 year of age. I have tried to use different strains but my knowledge is limited. 

  • Severe ear infections since an infant so abx use is very high. 10 times or more. 

My next course of action after helping her gut is Lyme and coinfections testing. My research and her latest doctor have lead me there. So if you see anything hinting that way, be very helpful. It’s very expensive testing and I’m just unsure. 

Basic Analysis

The usual basics are below:

Clostridia was a specific area of concern, she is at 27.5%ile at the class level. Looking at lower levels we see some if its ‘kids’ are a problem. Three bacteria makes up 60% of the microbiome!

My immediate thought is to look at the suggestions when we hand picked these four. They so dominate the microbiome that trying to adjust the other will likely be shouting in a hurricane (i.e. no one will hear).

Then do a second round including Bifidobacterium

The results we far less than ideal (i.e. very few items over 0.5)

It is interesting that the first prescription items is Risperidone, it is prescribed for irritability caused by autism [more information, including risks]. This hints that there is a match for the bacteria causing irritability in autism. My take away from this list is simple: remove any items on the Avoid list (which includes many vitamins and probiotics “deemed healthy”).  bacillus subtilis natto (probiotics) is available is the Japanese desert food Natto (I like it, a bit of an acquire taste) with nattokinase supplement being a potential alternative. The other top items(not prescription) to take are available as supplements etc. I attach the full list.

Adding in Bifidobacterium, we see many items that encourages bifidobacterium on the avoid list.

I next did the usual consensus report (which I added to the above sets of suggestions)

The full consensus report is below. Items to TAKE of note:

One item of caution: bacillus subtilis (probiotics) is a strong avoid, one specific species is a moderate take bacillus subtilis natto (probiotics). At the gene levels they are different.

Using KEGG data

Two probiotics showed up at the top that are not available on the shelves of any US Health store: symbiopharm / symbioflor 1 and bioflorin (deu) / bioflorin. In fact, the top items are rich in European probiotics. Symbioflor-1 is available from the German Apotheke and will ship world wide (we use them) as well as bioflorin (which is expensive per capsule, so try symbioflor-1 first for the sake of your wallet!).

In terms of supplements, the following should be reviewed with your MD

  • Amylase (Enzyme) – Percentile: 1
  • beta-alanine – Percentile: 2.6
  • Glycine – Percentile: 2.8
  • L-methionine – Percentile: 3.6
  • Molybdenum – Percentile: 0.5
  • NADH – Percentile: 3.4

Remember that the basis of the KEGG data is identifying compounds that a person is low in. This is based on the hypothesis that part of the microbiome disruption is caused by rationing and impeding the operation of various bacteria. Our data is incomplete — so it is a best estimate.

Dive into Antibiotics Taken

I started the easy way — just looking at the Special Reports for your MDs. Everyone given encouraged this child’s dysbiosis.

The purpose is to give alternatives that may address medical needs while helping correct microbiome shifts.
  • Azithromycin for about two months straight at onset of PANS.  ( – 0.555 )
  • Augmentin (amoxicillin) several times for ear infections and later in life with a functional medicine doctor to address her GI MAP.   ( – 0.487 )
  • Sulfamethoxazole,  ( – 0.642 )
  • Vancomycin – increases Acidaminococcus parent
  • Cefdinir ( – 0.586 )

There are a small number of antibiotics that may help the microbiome — if antibiotics are required in the future. Discuss if any of these may be acceptable to the MD (i.e. negotiate!) for addressing his rational. Note that the general class macrolide contains both good and bad choices: bad choices (azithromycin), good choices (erythromycin).

These are computed from available literature.

Checking the Positive Benefit for Prescription items, it was very very short. the first suggestion was epinephrine (Adrenaline). This surprised me. A common pattern is too much epinephrine with autism. We need to tread carefully here because levels can be high or low in different parts of the body.

In a group of 22 autistic children aged 5 to 16 years and a group of normal controls matched for age and sex, catecholamines metabolism was investigated in plasma, platelets, and urine. This investigation was part of a research project in which several biological parameters (including serotonin) were explored simultaneously in the same children. In the autistic group, epinephrine and norepinephrine were significantly elevated in plasma, while epinephrine, norepinephrine, and dopamine were significantly lower in isolated platelets. No significant difference was found between the two groups for the urinary excretion of epinephrine, norepinephrine, dopamine, DOPAC, and MHPG. Other differences between the two groups in the statistical correlations of several biochemical parameters also suggest abnormalities of bioamine metabolism in the platelets of autistic children.

Catecholamines metabolism in infantile autism: A controlled study of 22 autistic children

Dive into the key bacteria

Above we have identified the bacteria that has taken over the gut

Questions and Answers

Q: How long do you recommend a follow up stool test after implementing some things? 

A: For most things I recommend rotation of suggestions. The purpose is to destabilize the stable dysfunctional microbiome. A typical rotation is 2 weeks. The soonest would be after 4 rotations (2 months), if things are improving then just keep going until things appear to stabilize — then do a new sample to get the next course correction.

Q: I saw high mycoplasma on the lab’s page – is that a concern? This could explain so much as it is a main trigger for many PANS kids. Did I see that correctly? 

A-1: The literature: “Anti-Mycoplasma pneumoniae antibodies and anti-Epstein-Barr virus Nuclear Antigen antibodies were found positive in 11 (42.3%) and 5 (19.2%) patients with PANS,” [2019] This can be tested for directly and that would be the best way to answer.

A-2: Labs (and Microbiome Prescription use different criteria to determine “high”. Your child reading for  Mycoplasma was 192 / 1,000,000 bacteria or 57.2%ile. Ombre reports 70% of all samples have some mycoplasma. The level is not abnormal. The chart of values, showing your sample is below

Q: Any evidence of Lyme Disease

A: Lyme is caused by Borrelia. It is reported on Ombre/Thryve tests 0.2% of the time. None was reported in report. Conclusion, unlikely. Given the degree of dysbiosis and the known high rate of false positive with many Lyme tests when there is dysbiosis (typically caused by EBV not being fully controlled due to the dysbiosis), I would say that without a red bull-eye rash on the child — do not bother testing. The antibiotics likely to be prescribe will make your child worst.

The Lyme Disease Rash

Autistic child with sleep, lethargy issues

Foreword – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that 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 a knowledgeable medical professional before starting.

Patient Notes

My son has headache, lethargy and reduced sleep. He’s in the spectrum so there are a lot more symptoms associated with it. But these are things I am trying to figure out, help him at least have a life without pain.


As a result on my involvement with Long Covid Study – VERY early data, I built some private tools (computational intense, with good statistical understanding requires) .

The number of bacteria flagged for the closest match to the symptoms (with good sample sizes) are shown below. Each set of suggests had a lot of similarity to each hour, especially with red wine near the top of most lists. Red wine to children was historically done (especially French and Italian kids), but . . .

Symptom ObsNo Symptom ObsSymptom
83901General: Headaches32
41943Post-exertional malaise: General22
70914Neurological-Sleep: Chaotic diurnal sleep rhythms (Erratic Sleep)72
77907Autism: Official Diagnosis26

At this point, I decided not to grind thru the standard set of suggestions, instead look at the consensus data (which is attached as a download below). The list was less than usual, 180 items.

I also went over to the KEGG determined probiotics and saw some items had consensus between them for probiotics, the top agreements are below

In terms of supplements:

  • Biotin (Vitamin B-7), B-12, B-1
  • Calcium

Check the diet for food that may be high in choline (aka choline deficiency) and reduce them. See NIH page for a list.

Pro Forma Analysis

I went on to do the usual analysis:

The consensus report is attached, the suggestions appear similar but with shifting up and down on the list and a lot more items (567 vs 180 above). This video shows the process

Bottom Line

I did a VLookUp in Excel between the two lists to see the similarities and differences. There were a few difference. My usual advice is “if we don’t know the right answer, omit unless there is a strong reason to include”

CustomPro FormaModifier2
317.5262.4choline deficiency
309.3382.7rice bran
205.279.2Prescript Assist (2018 Formula)
193.6208.6vitamin b7 biotin (supplement) (vitamin B7)
164.980.4high red meat
153-13.2saccharomyces boulardii (probiotics)
152.363.6low fodmap diet
152.3159.4low protein diet
138.8-21.6low-fat diets
124.2-24.4fructo-oligosaccharides (prebiotic)
118.5-32.7vsl#3 (probiotics)
105.4-15.6red wine
105.42.4schisandra chinensis(magnolia berry or five-flavor-fruit)
98.474.7Prescript Assist (Original Formula)

Questions and Answers

One of the fundamental challenges of the microbiome is a lack of information on many interactions because studies have not been done. The site attempts to use whatever fragments of information that is available as well as the genes of the bacteria (when the data is available).

  • Question #1 PIANETA FARMA/KefiBios – I saw his Akkermansia is at a good level. Do you still recommend this probiotics?

The only known impact is on Akkermansia but that was not the basis of the suggestion. The suggestion came by looking at the amount of various compounds that he appears to be low in (using Kyoto Encyclopedia of Genes and Genomes on the bacteria he has, and the bacteria in various probiotics). Most of these compounds are not available as supplements.

Compound NameOtherNameFormula
D-AlanineD-2-Aminopropionic acid  D-Ala C3H7NO2
L-HomocysteineL-2-Amino-4-mercaptobutyric acid  Homocysteine C4H9NO2S
Aromatic aldehydeC7H6O
CDP-diacylglycerolCDP-1,2-diacylglycerol  1,2-Diacyl-sn-glycero-3-cytidine-5′-diphosphate C14H19N3O15P2R2
ThioredoxinReduced thioredoxin C10H14N4O4S2R4
N-(L-Arginino)succinate2-(Nomega-L-Arginino)succinate  L-Argininosuccinate  L-Argininosuccinic acid  L-Arginosuccinic acid C10H18N4O6
2-Dehydro-3-deoxy-6-phospho-D-gluconate6-Phospho-2-dehydro-3-deoxy-D-gluconate  2-Keto-3-deoxy-6-phosphogluconate  2-Dehydro-3-deoxy-D-gluconate 6-phosphate C6H11O9P
The above were at the 5%ile or less
  • Question #2: Prescript-AssistÂź/SBO Probiotic  –  I saw the list on your website. Sorry, I want to understand a little more detail about it. I know its soil based probiotics. I wanted to understand if it will help improve bifido .. I saw this has bacillus.
    • Answer: There is no known direct impact on bifido. If Bifidobacterium is your primary concern, excluding every other bacteria involved, then see this page. Suggestions are based on a holistic analysis, not a blinkered view.
  • Question #3: Also do you have any recommendations to help reduce the histamine level?
    • Answer:  Diamine oxidase (DAO) is the supplement commonly used to reduce the impact of histamine [study]. “Histamine is a monoamine synthesized from the amino acid histidine through a reaction catalyzed by the enzyme histidine decarboxylase (HDC)”[2018] Trying to find the bacteria involved is a bit more speculative.
Clicking on Enzymes

Searching for histidine involved enzymes, we see that he has very high levels of two:

The three greatest producers are: Erysipelatoclostridium ramosum,  [Clostridium] innocuum, Turicibacter sanguinis and Streptococcus iniae. For Erysipelatoclostridium ramosum, most items increases it ( dairy, resveratrol (grape seed/polyphenols/red wine)) but two items decreases it: xylooligosaccharide (prebiotic), bifidobacterium bifidum (probiotics). You could try hand assembling suggestions for these 4 bacteria.

The other way, using Diamine oxidase, is to go over to KEGG, it is Enzyme, none of the bacteria he has appear to produce it, nor do any of the bacteria reported from 16s samples.

  • Question #4: Choline Deficiency – Does it mean we have to give him a PC?.  You had mentioned there might be Choline in his diet. So is it more or is it deficient?, I think choline and Ammonia might be impacted because of the Antifungal regimen he is in?.
    • Answer: Choline occurs naturally in food, Background: A study on choline deficiencies found that the bacteria we targeted were shifted in the desired direction. There is a lot of literature on choline ( ) and digesting that is a job for your medical professional. My usual takeaway is  check what is normally eaten for choline content and consider reducing it a bit by changing foods (after consulting with your medical professional). No need to go to extreme measures… it is just one possible factor.
  • Question #5: Also the modifier 2 means he needs all those based on his microbiome, Is it right?
    • Answer: I do NOT know what he needs, the suggestions are strictly things that have been calculated from available data that has improved odds on shifting the microbiome towards the typical microbiome. Everything is probability and odds — nothing is definitive. In the absence of definitive knowledge, I believe that modelled data gives better suggestions than “let us try A,B,C”. For dealing with ME/CFS, the suggestions of what should help matches the literature on what helps – which increases my confidence in the model.

Bacteria to Hand-Pick for Autism with Biomesight samples

Some recent work has identified bacteria that are associated with Autism. For a summary of method, see this post. The following are the list of bacteria seen with Biomesight samples that are annotated with Autism. There are not sufficient samples yet for specific autism characteristics – so please check your uploaded samples and update the symptoms.

Note the list is specific and cannot be applied to other microbiome reports. There is a separate post for Ombre/Thryve samples.

These are bacteria that you want to reduce (with one caveat — the suggestions algorithm requires the percentile to be 50%ile or more). How to hand pick them? See below the list.

Note: you may only have a few of these. They are shown in the same sequence as seen on Microbiome Tree. The LAST item is what was found to be statistically significant.

  1. Nevskiales Sinobacteraceae Hydrocarboniphaga
  2. Gammaproteobacteria Enterobacterales Yersiniaceae
  3. Enterobacterales Yersiniaceae Serratia
  4. Yersiniaceae Serratia Serratia entomophila
  5. Enterobacterales Enterobacteriaceae Lelliottia
  6. Enterobacteriaceae Lelliottia Lelliottia amnigena
  7. Enterobacterales Enterobacteriaceae Enterobacter
  8. Enterobacteriaceae Enterobacter Enterobacter cloacae complex
  9. Enterobacter Enterobacter cloacae complex Enterobacter hormaechei
  10. Enterobacterales Enterobacteriaceae Escherichia
  11. Enterobacteriaceae Escherichia Escherichia albertii
  12. Enterobacteriaceae Escherichia Escherichia coli
  13. Rhodocyclales Zoogloeaceae Azoarcus
  14. Thiobacillaceae Thiobacillus Thiobacillus thiophilus
  15. Betaproteobacteria Burkholderiales Burkholderiaceae
  16. Burkholderiales Burkholderiaceae Limnobacter
  17. Burkholderiaceae Limnobacter Limnobacter litoralis
  18. Burkholderiales Genera incertae sedis Thiomonas Thiomonas thermosulfata
  19. Betaproteobacteria Burkholderiales Oxalobacteraceae
  20. Bacteroidia Bacteroidales Prevotellaceae
  21. Bacteroidales Prevotellaceae Prevotella
  22. Prevotellaceae Prevotella Prevotella copri
  23. Prevotellaceae Prevotella Prevotella paludivivens
  24. Prevotellaceae Prevotella Prevotella corporis
  25. Prevotellaceae Prevotella Prevotella oulorum
  26. Prevotellaceae Prevotella Prevotella veroralis
  27. Bacteroidaceae Bacteroides Bacteroides denticanum
  28. Bacteroidaceae Bacteroides Bacteroides gallinarum
  29. Bacteroidaceae Bacteroides Bacteroides caccae
  30. Bacteroidaceae Bacteroides Bacteroides graminisolvens
  31. Bacteroidaceae Bacteroides Bacteroides fragilis
  32. Peptostreptococcaceae Peptostreptococcaceae incertae sedis [Clostridium] paradoxum
  33. Eubacteriales Clostridiaceae Sarcina
  34. Clostridiaceae Sarcina Sarcina maxima
  35. Clostridiaceae Clostridium Clostridium cellulovorans
  36. Clostridiaceae Clostridium Clostridium frigoris
  37. Clostridiaceae Clostridium Clostridium chartatabidum
  38. Clostridiaceae Clostridium Clostridium nitrophenolicum
  39. Terrabacteria group Firmicutes Negativicutes
  40. Acidaminococcaceae Acidaminococcus Acidaminococcus fermentans
  41. Firmicutes Negativicutes Veillonellales
  42. Negativicutes Veillonellales Veillonellaceae
  43. Veillonellales Veillonellaceae Veillonella
  44. Veillonellaceae Veillonella Veillonella criceti
  45. Veillonellaceae Veillonella Veillonella dispar
  46. Veillonellales Veillonellaceae Megasphaera
  47. Veillonellaceae Megasphaera Megasphaera hominis
  48. Veillonellales Veillonellaceae Negativicoccus
  49. Veillonellaceae Negativicoccus Negativicoccus succinicivorans
  50. Selenomonadaceae Megamonas Megamonas funiformis
  51. Selenomonadales Selenomonadaceae Pectinatus
  52. Selenomonadaceae Pectinatus Pectinatus cerevisiiphilus
  53. Bacillales Planococcaceae Viridibacillus
  54. Bacilli Bacillales Sporolactobacillaceae
  55. Bacillales Sporolactobacillaceae Sporolactobacillus
  56. Sporolactobacillaceae Sporolactobacillus Sporolactobacillus putidus
  57. Staphylococcaceae Staphylococcus Staphylococcus pseudolugdunensis
  58. Bacillales Staphylococcaceae Salinicoccus
  59. Streptococcaceae Streptococcus Streptococcus thermophilus
  60. Streptococcaceae Streptococcus Streptococcus mutans
  61. Streptococcaceae Streptococcus Streptococcus vestibularis
  62. Cyanobacteria/Melainabacteria group Cyanobacteria Oscillatoriophycideae
  63. Cyanobacteria Oscillatoriophycideae Chroococcales
  64. Bifidobacteriaceae Bifidobacterium Bifidobacterium scardovii
  65. Bifidobacteriaceae Bifidobacterium Bifidobacterium adolescentis
  66. Bifidobacteriaceae Bifidobacterium Bifidobacterium angulatum
  67. Bifidobacteriaceae Bifidobacterium Bifidobacterium breve
  68. Bifidobacteriaceae Bifidobacterium Bifidobacterium catenulatum
  69. Bifidobacterium Bifidobacterium catenulatum Bifidobacterium catenulatum subsp. kashiwanohense
  70. Bifidobacterium catenulatum Bifidobacterium catenulatum subsp. kashiwanohense Bifidobacterium kashiwanohense PV20-2
  71. Bifidobacteriaceae Bifidobacterium Bifidobacterium cuniculi
  72. Bifidobacteriaceae Bifidobacterium Bifidobacterium indicum
  73. Bifidobacteriaceae Bifidobacterium Bifidobacterium longum
  74. Bifidobacteriaceae Bifidobacterium Bifidobacterium thermacidophilum
  75. Bifidobacteriaceae Bifidobacterium Bifidobacterium pseudocatenulatum
  76. Bifidobacteriaceae Bifidobacterium Bifidobacterium choerinum
  77. Bifidobacteriaceae Bifidobacterium Bifidobacterium gallicum
  78. Bifidobacteriales Bifidobacteriaceae Parascardovia
  79. Corynebacteriaceae Corynebacterium Corynebacterium durum

To make a selection, just check the appropriate checkboxes.

2 Samples for Autistic Child


My son is born in 2009 and diagnosed with autism in 2011. When he was 3 months old he has lot of reflux and unable to digest milk always used to throw up and we ended up using antibiotics because of mucus forming issues and at 10 months he had few words.

  • And at 18 months he got diagnosis’s of autism and was completely Non-Verbal.
  • After removing gluten and dairy from his diet at age 3.5 he started saying words
  • he also got diagnosed with Lyme and coinfections like bartonella and Babesia .
  • Now he is 11 years still having lot of issues like his weight is just 55 Lbs  he has focus issues and lot/severe OCDs and tantrums and lot of rigidity and not conversational yet ,cognitive issues cannot understand abstract concepts and has lot of echolilia and  no social skills and gets head pain all of a sudden which might be PANS will last for few minutes and will be fine again.
  • And he has lot of Gut issues like  failure to thrive even though his diet his healthy he does not gain weight at all and he has leaky gut and always have constipation issues  and poor digestion issues and picky eating and he complaints some times that his stomach hurts and some times his stomach gets very tight like gas forming. And he has brain and Gut inflammation.
  • Very recently from couple of months  he started having Acid Reflux issues after eating he will be spitting for an hour as if something is coming back from his stomach. 
    • We also noticed that when ever he eats chicken and eggs he is more constipated. We did the GI work up and everything came up normal except one thing that he does not have enzymes to digest lactose and also we make sure he is not constipated and his bowls are moving everyday with some laxative.

We have two samples for this person, while we will use the last one for suggestions, a comparison may be spark insights.

Basic Analysis

Looking at the two samples, we see that things are very different than with the ME/CFS person in this post. Instead of over representation in rare bacteria, there is over representation in common bacteria (i.e. the bacteria that most people have).

0 – 910177
10 – 19109912
20 – 2969813
30 – 391018710
40 – 49129612
50 – 591215918
60 – 69107812
70 – 7910161016
80 – 8925392238
90 – 991031494064
Std Dev29.3144.0010.6517.61
  • Looking at “Potential Medical Conditions Detected” for both samples we see a very long list of candidate conditions for both samples
  • For “Bacteria deemed Unhealthy”, again we have some long lists
  • For “Dr. Jason Hawrelak Recommendations”, we have the earlier sample at 75%ile and the latest sample at 98.8%ile, i.e. “no issues”
  • AI Computer Probiotics.
  • AI Computed supplements at 10% level: Neither sample had any.

There is the appearance of improvement between the sample. This may be solely due to the changes due to age (18 months between samples), or moving further away from microbiome disruptive events of the past.

Going Forward

We need to go with some caution because the child microbiome is different than an adult’s and most of the data we are using are from adults.

I am going to build the consensus in a slightly different way than usual:

  •  Use JasonH (15 Criteria) – 6 bacteria picked
  •  Standard Lab Ranges (+/- 2 Std Dev) â€“ 17 bacteria picked
  •  Box Plot Whisker â€“ 59 bacteria picked
  •  Kaltoft-Moltrup Normal Ranges â€“ 92 bacteria picked
  •  Percentile in top or bottom  10 % – 160 bacteria picked
  • Canned Autism using U.S. Nation Library of Medicine Data – 8 bacteria picked
  • Using Experimental Page using Official Diagnosis Autism only – 9 bacteria picked

Looking at Consensus Items

I scanned the top items and picked items that I suspect will be acceptable, easy to obtain and reasonable cost:

Take / Add to regime

There were some interesting AVOIDS (very different than ME/CFS people)

Avoid / Remove or Reduce use of

Seeing lactulose as a very strong to be avoid agrees so much with no tolerance for milk. I checked the antibiotics positive/negative benefit and was actually surprise to see on the positive impact many of the antibiotics used for ME/CFS and Lyme: fluoroquinolone (antibiotic)s, tetracycline (antibiotic)s, minocycline (antibiotic)s with the best one being vancomycin (antibiotic). This was interesting because “Vancomycin is used to treat colitis (inflammation of the intestine caused by certain bacteria) that may occur after antibiotic treatment.”[MedlinePlus]

Questions And Answers

  1. Do you mean your current recommendations is not to use any probiotics or use only Lactobacillus salivarius strain of probiotics ?
    1. Only a very small number of probiotics appear to have a positive impact, less than 18. The other 39 came out with a negative effect. You need to read the labels carefully.
  2. I also for the earlier sample you mentioned the PDF use of prescript assist soil based probiotic and also lactobacillus bulgaricus (probiotics) and lactobacillus kefiri . I have not used these so now do you think using them might be helpful based on the analysis 
    1. Those are on the recommended list, so YES
  3. And based on your analysis what is most pathogenic bacteria that I need to address from the sample which is problematic such that I research and see how to reduce it?
    1. Unlike most people, this child has a huge amount of Lactobacillus bacteria, he has 98% more than anyone else in the database. Clicking on the link above (and those below) are the worst offenders where his levels are higher than 95% of peoples
    2. [Ruminococcus] gnavusActinomycesBacillusDoreaErysipelatoclostridium ramosumShigella (especially Shigella dysenteriae),Streptococcus pyogenesStreptococcus sanguinis
    3. In the video, I will show how you can find suggestions EXPLICIT for these.
  4. What key strains of good bacteria do you think is missing for weight gain or in general ?
    1. Every good strain becomes bad if there are too many of them, for example Lactobacillus above. The microbiome should be viewed as “Yin/Yang” and not good and bad. I really do not have a clean answer for that question.
  5. Which Lactobacillus strains does he have has 95% which I need to avoid further is it Lactobacillus Reutri and Lactobacillus Johnson and Lactobacillus planetarium are those the ones which I need to avoid completely to give or any other list?
    1. ALL Lactobacillus are similar with only small changes between them. They are a family. As with human families, they cross support each other. You want to lower all of the Lactobacillus, ideally have no lactobacillus probiotics.
  6. Currently I started using sauerkraut , thinking he needs more Lactobacillus strains and I read sauerkraut has lot of different good strains. Would it be still okay to use it?
    1. He DOES NOT need more Lactobacillus strains — he needs a lot less!
    2. In my humble opinion NO. Two main reasons:
      1. You have no idea of which bacteria are in. Commercial versions usually do not list the
        species. On the few that do, it is very questionable if the label is correct.
        ” the species of lactic acid bacteria present in sauerkraut fermentations are more diverse than previously reported and include Leuconostoc citreum, Leuconostoc argentinum, Lactobacillus paraplantarum, Lactobacillus coryniformis, and Weissella sp.” [2007]
        For Weissella, he is at 90%ile — too high. He does not need more
  7. Do I need to do anything to reduce Lactobacillus strains that are high?
    1. There is no studies that target explicit strains.
    2. melatonin supplement, B-vitamins reduce it too.
    3. A word of caution here. Are you going to target just one item of concern in several dozens by focusing on this item (with the potential cost of many other things becoming worst); or work from suggestions that are targeted to improve the microbiome as a whole?

In response to question #3, I did a hand picked of all of those over 95%ile on the Health Summary with the results shown below

In response to quest 5-7, the Lactobacillus tree. Note that of 65,000 Lactobacillus bacteria — less than 1,400 ( 2%) had the species identified. We do not know the species that he is high in.

A short list of Suggestions

To be discussed with family MD before starting

Items to AVOID (You may wish to read the full list

One of the easiest modern ways to do it, is to download this data as a CSV and save on your smart phone when shopping.

REMINDER: The items indicate odds/confidence in shifting the microbiome is the intended direction. It is NOT how effective it is. Each item in the take likely improves your odds of improving when taken; keep taking items the avoid list — continuing likely increase the odds of not changing.


Experimental: Picking Autism Bacteria via Symptoms

As a result of some work with BiomeSight, I ended up rethinking how to handle the symptoms to bacteria process. I had been thinking linearly in terms of building regression. I got some traction with that, but was definitely unhappy because once multiple symptoms are added the regression faded out.

A novel approach is simple, take all of the people with the same set of symptoms and create a composite of their microbiomes. In this composite identify outliers and then see where those outliers match the sample that you are looking at. Take those that match and create a Hand Picked Bacteria set and then generate suggestions from those.

So simple, just pick the symptoms and then see the bacteria identified. But you must first enter the symptoms for the person!

This is located on the “Research Features” tab

You will see the list of all of the symptoms you entered for the sample, they are listed in descending order of the number of samples sharing the same symptoms.

Experimental: Picking Bacteria via Symptoms – YouTube

Pick the first one and click add to list

The list show is for only those that include Autism

Adding another example, reduces the choices.

You can keep adding as many as you wish (you do not need to add)

When you are ready (or just interested in seeing the bacteria picked), click the green button

You will get a short or long list of bacteria. If a long list, you may wish to go for stronger relationships.

Increasing to Expected, caused a major drop in the numbers

Having more is not always better. I reduced it to just Autism, and the list was much fewer than when I had multiple symptoms. Note that the list will be different for different people and different samples

For Autism alone

Examples for some autistic children

Bottom Line

The key thing to remember is that the symptom is NOT caused by a specific set of bacteria but by different combinations of bacteria acting in similar ways. This approach attempt to capture the probable combinations for a symptom set.

Second Example for Long COVID

This was mainly done to show that we can get strong relationships.

For WEAK relationship
For Strong relationships

For Very Strong — nothing was listed.

ASD Child Analysis with OATS

Information from the reader is below

My son has ASD, with speech delay and melting down behavior, anything related gut-brain axis will be helpful. I gave 1 small spoon of custom prebiotics d- lactate free last night, he woke up crying and screaming xx but this morning I saw improvement eye contact soooo much better xx he is low on bifidobacterium and high on d-lactate.

Editor Comment: As a FYI, this was also what I dealt with as a child – Ken

Round #1: OATS Results

With the new feature of using OATS results to pick probiotics, I wanted to start with that data before looking at the microbiome. They are two separate ways of doing analysis with some overlap, but they are not the same — and getting identical results is not expected. The story of blind men descripting an elephant applies.

In general, I will look only at items flagged with H and a single item that was Low. I included the OATS number after each for reference.

  • Yeast and Fungal Markers
    • Items that are low are ignored (all are related to Aspergillus). Taking Aspergillus oryzae NK (strong wakamoto w) is an obvious correction, if desired.
    • High items are:
      • Arabinose (7)
      • Carboxycitric (8) – C7H8O9 — no matches
  • Bacterial Markers
    • 4-Hydroxybenzoic (12)
  • Oxalate Metabolites
    • Oxalic (21)
  • Glycolytic Cycle Metabolites
    • Lactic (22)
  • Mitochondrial Markers – Krebs Cycle Metabolites
    • Succinic (24)
  • Pyrimidine Metabolites – Folate Metabolism
    • Uracil (41)
  • Ketone and Fatty Acid Oxidation
    • 3-Hydroxybutyric (43)
    • Methylsuccinic (46)
  • Nutritional Markers
    • Pantothenic (B5) (52)
    • Glutaric (53)
    • Ascorbic (54) LOW
  • Indicators of Detoxification
    • Pyroglutamic (58)
    • 2-Hydroxybutyric (59) – C4H8O3 – no match
    • 2-Hydroxyhippuric (61) – C9H9NO4 – no match

Not every item was a match. Often for chemical formula there may be multiple matches… but no clear match (it may have the same formula, but how the atoms are connected are different).

So, with so many items, the issue of aggregation or consensus arises. I added a consolidation option to the site (you MUST be logged in to use it). It aggregates every computation request until you clear the current aggregation.

The Green buttons are just added.

The results are shown below. The results show no clear probiotic to take when all of the above OATS results are used. If you prioritize a couple of OATS results, you may be a clearer result. On the positive side, every probiotic listed had a higher times-suggested than times not-suggested. Clostridium butyricum would be my first pick because it has the greatest positive difference and easily available.

Round #2: KEGG Suggested Probiotics

This approach does not use OATS results, rather looks for under-production of various KEGG compounds compared to other samples and looks for probiotics that produces those compounds. Note: Above we were focuses on over-production. Nothing was suggested.

I also checked KEGG AI Computed Supplements — nothing was listed.

Round #3: KEGG versus OATS

This is a bit of an lemons to watermelon comparison, but I expect someone will do it. So let us look at the results. I have added an OATS column to make life easier. We are focused on PERCENTILE. Remember that OATS reported high levels of all of these but one (OATS#54 – which there is no data on).

Remember — labs do NOT report all bacteria, nor do we know the efficiency — thus these are very rough estimates. Both Lactic Acid and Uracil are in strong agreement with OATS.

For the two items in agreement, I return to the Round 1, clear existing aggregation and try these two alone.

The results were equally not clear. The reason appears that some bacteria both consumes and produces some chemicals (often depending on the availability of other compounds). To be sure, I am refreshing my data from KEGG in the next week (I do not expect any changes … but I wish to be sure).

Round #4

Alas, we do not have KEGG provide clean, clear suggestions. That does happen with some people/samples. So we continue onwards.

Dr. Jason Hawrelak Guidance

There are a number of undesired levels:

Bacteria NameAnalysis
  BacteroidiaToo High
  BifidobacteriumToo Low
  Escherichia coliToo High
  Faecalibacterium prausnitziiToo Low
  LactobacillusToo Low
  MethanobrevibacterToo Low
  ProteobacteriaToo High
  RoseburiaToo Low

The suggestions are below:

Kaltoft-Moltrup Range Guidance

This methods looks at the sample values that are really out of expected range when compared to 2400+ other samples. This is one of the longest list that I have seen.

Bacteria NameAnalysis
  AcetivibrioToo High
  AnaerostipesToo Low
  Bacteroides fragilisToo High
  Bacteroides uniformisToo Low
  Candidatus PhytoplasmaToo Low
  Candidatus Phytoplasma prunorumToo Low
  CatonellaToo Low
  Catonella morbiToo Low
  Dorea formicigeneransToo Low
  DysgonomonadaceaeToo High
  DysgonomonasToo High
  Dysgonomonas wimpennyiToo Low
  OscillospiraceaeToo High
  Pectinatus cerevisiiphilusToo Low
  PeptostreptococcaceaeToo Low
  Phocaeicola vulgatusToo Low
  Pseudobutyrivibrio xylanivoransToo Low
  RoseburiaToo Low

Looking at the suggestions for this, and comparing to the above, I was delighted/shocked that there was a great overlap with the suggestions from Jason’s guidance — despite no shared bacteria in the picked list. This gives me confidence that these two lists feel good.

NOTE:  vitamin b3 (niacin) was a strong avoid

Using US Library of Medicine Autism Profile

Autism covers a wide spectrum of symptoms and causes. In general, I deprioritize this approach unless there is poor results from other approaches, but I am curious:

Settings Used

The result is still a longer list of selected bacteria than above.

Bacteria NameAnalysis
  AcidaminococcaceaeToo Low
  ActinobacillusToo High
  AkkermansiaToo High
  Akkermansia muciniphilaToo High
  Bacteroides fragilisToo High
  BlautiaToo Low
  CorynebacteriumToo Low
  DialisterToo High
  DoreaToo Low
  EnterobacterToo High
  EnterobacteriaceaeToo High
  ErysipelotrichaceaeToo Low
  EscherichiaToo High
  HaemophilusToo High
  Haemophilus parainfluenzaeToo High
  LachnospiraceaeToo Low
  LactobacillaceaeToo Low
  MegasphaeraToo High
  OscillospiraToo High
  ParabacteroidesToo High
  Phocaeicola vulgatusToo Low
  PrevotellaToo High
  PrevotellaceaeToo High
  RoseburiaToo Low
  RuminococcaceaeToo High
  RuminococcusToo High
  SarcinaToo Low
  StaphylococcusToo Low
  StreptococcusToo High
  VeillonellaToo High
  VeillonellaceaeToo High

Unlike above, we actually have many to avoid with high values

Putting it all together

We have three rounds of suggestions, so should use the consensus report to combine them into one set.

The consensus report can often have items not seen in any of the above suggestions appear in the safest takes. Why? In the suggests, we attempt to balance. The Safest takes does not attempt to balance but find absolutes!

Some kid friendly take away are:

  • Xylitol Chewing Gum (for a child, an easy approach)
  • Regular porridge with walnuts, barley, inulin with some cinnamon and whole milk.

Looking at custom prebiotics d- lactate free species we find:

  • L. Rhamnosus – on Safest Take
  • L. Salivarius – on Safest Take
  • B. Lactis – on Safest Take
  • B. Bifidum – on Safest Take
  • B. Infantis – on Some Risk / Avoids
  • B. Longum – on Some Risk / Avoids – but strain BB536 is on Likely Safe Takes

So, it should likely be continued — when the bottle is finished, you may wish to switch to single strains.

Remember, this is an educational post showing how to use resources on Microbiome Prescription and not intended to be medical advice in any way. Before making any changes, the changes should be reviewed by your knowledgeable medical professional. The above is based on novel artificial intelligence algorithms and approaches; as well as theoretical constructs.

Picking Probiotics from OATS results

In a series of past posts, I walked thru the many pages of a OATS looking at each line:

A reader of that page presented me with a challenging question: “Which probiotic would reduce ….. ?” I checked the US National Library of Medicine studies — nothing. I am a lateral thinker (read Edward de Bono since I was a teenager) and it occurred to me that, theoretically, we can use data from KEGG: Kyoto Encyclopedia of Genes and Genomes because they have the gene sequence of many probiotics and thus their enzymes. Enzymes are mini-factories that consumes some metabolites and produces other metabolites. There are 5200+ different compounds reported on KEGG.

Since I have all of the data in a friendly (to me) datastore, it was just a matter of constructing a few complex queries and creating some web pages. The result was this page: Probiotics to Change KEGG Compounds

In the video below, I walk thru how we use OATS result and this page. Other test results can be used. OATS happened to be inspiration for this feature.

Before/Donor/After FMT for Autism

A user of my site that is active consulting on autism microbiome manipulation obtained permissions for me to do an analysis of one of his patients going through FMT. All of the microbiome testing was done via Biomesight (including the donor). This is specific type of data that I have been pleading to see if we can make predictive models of what could occur with FMT.


I did analysis at the Species, Genus, Family, Order and Class level trying many many approaches. This summarize my key findings.

The second sample was done one month after the FMT. Patient was very good for a couple of days, then “the war started”. New more severe autism symptoms appeared.

Do NOT expect it to reduce overgrowths!

Looking at the lowest numbers of the recipient prior and the donor, we found that the post-FMT numbers had a clear pattern.

  • At the Class level, 97% was higher than the lowest of the two, 58% was higher than the highest
  • At the Order level, 96% was higher than the lowest of the two, 56% was higher than the highest
  • At the Family level, 95% was higher than the lowest of the two, 61% was higher than the highest
  • At the Genus level, 91% was higher than the lowest of the two, 51% was higher than the highest
  • At the Species level, 94% was higher than the lowest of the two, 47% was higher than the highest

This was shocking — 50% of the bacteria will be higher than either the donor’s or recipient’s levels. Many people will assume that the levels will magically average the two levels. The reality seen here is that only 50% of the time will the new level be between these two levels and 50%of the time it will be higher than either. This is unlikely to be a preferred outcome.

Unexpected Disappearances

There were several items where both the recipient and the donor had bacteria, they were gone in the post-FMT sample! This was not expected, of special interest is that Lactobacillus was wiped out.

  • Order: Puniceicoccales
  • Family: Clostridiales Family XVI. Incertae Sedis
  • Family: Lactobacillaceae
  • Family: Puniceicoccaceae
  • Genus: Alkalibacterium
  • Genus: Butyricimonas
  • Genus: Carboxydocella
  • Genus: Catonella
  • Genus: Lactobacillus
  • Genus: Macrococcus
  • Genus: Pelagicoccus
  • Genus: Turicibacter
  • Species: lingnae
  • Species: Streptococcus oralis
  • Species: Veillonella parvula
  • Species: Streptococcus pseudopneumoniae
  • Species: Carboxydocella ferrireducens
  • Species: Sutterella wadsworthensis
  • Species: Catonella morbi

Many New Kids showed up!

These are bacteria not seen in the recipient prior nor the donor sample

  • Class Level: Acidobacteria, Calditrichae,Chitinophagia,Flavobacteriia,Ktedonobacteria,
  • Order Level: Acidobacteriales, Calditrichales, Caulobacterales, Chitinophagales, Chroococcales, Desulfobacterales, Flavobacteriales, Kiloniellales, Nostocales, Oscillatoriales, Rhodocyclales, Rickettsiales, Streptosporangiales, Synechococcales, Syntrophobacterales, Thermogemmatisporales,
  • Family Level: Acetobacteraceae, Acidobacteriaceae, Anaplasmataceae, Calditrichaceae, Caulobacteraceae, Chitinophagaceae, Chroococcaceae, Clostridiales Family XII. Incertae Sedis, Cyanobacteriaceae, Cytophagaceae, Desulfobacteraceae, Dysgonamonadaceae, Flavobacteriaceae, Fusobacteriaceae, Hymenobacteraceae, Kiloniellaceae, Listeriaceae, Nostocaceae, Oceanospirillaceae, Oscillatoriaceae, Oxalobacteraceae, Prevotellaceae, Pseudanabaenaceae, Rhodanobacteraceae, Rhodocyclaceae, Rickettsiaceae, Rivulariaceae, Streptosporangiaceae, Synechococcaceae, Syntrophobacteraceae, Thermogemmatisporaceae, Thiotrichaceae, Verrucomicrobiaceae,
  • Genus Level: Acholeplasma, Acidaminobacter, Aminobacterium, Ammonifex, Anoxybacillus, Asticcacaulis, Bilophila, Caldithrix, Calothrix, Catenibacterium, Chroococcus, Cyanobacterium, Desulfofrigus, Desulfosporosinus, Dokdonella, Dysgonomonas, Edaphobacter, Ehrlichia, Emticicia, Escherichia, Fusibacter, Fusobacterium, Gillisia, Haemophilus, Insolitispirillum, Kushneria, Listeria, Luteibacter, Lysinibacillus, Marinospirillum, Microbacterium, Neisseria, Niastella, Novispirillum, Oleomonas, Olivibacter, Oscillatoria, Parapedobacter, Paraprevotella, Pelotomaculum, Pontibacter, Ralstonia, Rickettsia, Roseomonas, Sarcina, Sebaldella, Skermanella, Tepidanaerobacter, Tepidimicrobium, Thalassospira, Thermoanaerobacter, Thermogemmatispora, Thiothrix,
  • I will skip the species level…

Bottom line is that the microbiome has become much more diverse

Recent FMT aspects

FMT destabilizes the microbiome, there are “strain riots” in the guts. We can see this with all of the “New Kids” showing up because the existing occupants are busy dealing with each other. This can be seen by the post microbiome having a lot more taxonomical items (550 vs 374 before – a 47% increase), The microbiome, over time, will downsize and stabilize with a new normal. During this period, you want to entrench your desired items by feeding it the right things and avoiding the wrong thing.

Personally, I would suggest a new sample every 6 weeks to monitor the stabilization.

Is FMT Worth the Risk?

FMT is effectively an organ transplant. Like organ transplants, there are significant risks of rejection and no way to undo it once it happens. From correspondence with many people who have tried it for ME/CFS, my feelings are that it is not a magic bullet. It is closer to playing Russian roulette, but with 5 of the 6 bullet chambers have bullets in them.

I just spent 90 minutes zooming to the consultant involved with this autistic child. We both agreed that FMT for autistic children is not a wise course. The consultant is scratching their head on what to help this child recover from this situation.

Some prior posts on FMT

Analysis of a 6 yo ASD

Description: boy is almost 6, has big belly, low muscle tone, sensitivity issues, ADHD and very functional ASD.


Using US National Library of Medicine (PubMed)

Since we have two defined conditions specified, I apply PubMed literature to the sample. This information is not predictive because there are many subgroup for both conditions. The information gives us more probable candidates of the bacteria involved.

Ordering them by highest percentile, we see Generalized anxiety disorder at 76%ile which is a likely match for sensitive issues. Two other high matches of interest are:

I also checked Naive Predicted Symptoms From Citizen Science 2.0 and there was no additional really significant matches (Comorbid: Panic Attacks, Immune: Sensitivity to smell/food/medication/chemicals ) with the possible exception of Condition: Non-Celiac Gluten Sensitivity. This last one is fuzzy because a child’s microbiome is very different from an adult (and most of our data is adult), however doing a gluten free trial for 2 weeks is an easy way to test this. If issues improved, then keep gluten free for 6 months and then retest the microbiome.

Outliers (abnormal values)

Going to My Biome View(Taxon Hierarchy View) spotted some items of concern:

  • Burkholderiales is 10% of the microbiome, almost one of the highest values seen.
    • Could not find any studies of this with autism or ADHD, but looking at its components
    • Alcaligenaceae
      • “we demonstrate that increased levels of Alcaligenaceae in intestinal biopsy samples from AUT-GI children result from the presence of high levels of members of the genus Sutterella.” [2012]
      • ” children with ASD still had unique bacterial biomarkers, such as Alcaligenaceae, Enterobacteriaceae, and Clostridium” [2019]
    • Sutterellaceae (see above)
      • “almost all the identified Sutterellaceae and Enterobacteriaceae were the highest in AD.” [2013]
  • Prevotella copri is 6%
    • Associated to both autism and obesity [2021]
    • Prevotellaceae is almost exclusively this strain.
  • Blautia coccoides is 6%
    • Several studies found Blautia being lower in autism [2019] [2016] so this being high implies not being in the typical subset.

As this is a child (and most of the data on Microbiome Prescription is for adults), I consulted A Systematic Review of the Microbiome in Children With Neurodevelopmental Disorders [2019] where I read “Prevotellaceae, Lactobacillaceae, and Mogibacteraceae resulted as being the 3 key families discriminating samples from children with ASD from samples from HCs. “, so let us check the other two in our sample:

  • Lactobacillaceae is low (agrees with the above study)
  • Mogibacteraceae is not reported on any of the common 16s tests.

Where do we go from here?

I am going to get suggestions in several different ways:

The goal is to identify items common across all of them. There is no definitive best approach. The first one is very focused on specific bacteria that is both associated with autism and abnormal in the sample. The others are more generic approach which include more bacteria families.

Hand picked bacteria
Kaltoft-Moltrup unfiltered
Kaltoft-Moltrup filtered by Autism (PubMed studies)

We have the commonality shown below (i.e. items are on all three approaches). remember there is no definitive best approach. I have done the three that I am most inclined to and then we intersect the results to get a consensus from the approaches.

Bottom Line

This child microbiome fits the general pattern for autism in children according to the literature. It is my belief that issues will improve with microbiome manipulation. Yesterday, I has a long conversation with someone in Europe that consults on Autistic children using their microbiome and Microbiome Prescription. He reports consistent improvement with his clients.

Usual advice: Please review with your medical professional before making any changes. The suggestions come from a mathematical model and not clinical experience. The suggestions above applies to this person with their unique microbiome. Get a microbiome done and follow the pattern of analysis above to get what is appropriate to your child.

Reading list for Autism and the Microbiome

I thought it would be good to share what is currently used in the system.

Autism   Dysbiotic Gut Microbiota and Dysregulation of Cytokine Profile in Children and Teens With Autism Spectrum Disorder.
Frontiers in neuroscience (Front Neurosci ) Vol: 15 Issue Pages: 635925
Pub: 2021 Epub: 2021 Feb 10 Authors Cao X , Liu K , Liu J , Liu YW , Xu L , Wang H , Zhu Y , Wang P , Li Z , Wen J , Shen C , Li M , Nie Z , Kong XJ ,
Summary Html Article Publication
Autism   [Correlation between gut microbiota and behavior symptoms in children with autism spectrum disorder].
Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics (Zhongguo Dang Dai Er Ke Za Zhi ) Vol: 21 Issue 7 Pages: 663-669
Pub: 2019 Jul Epub: Authors Zhao RH , Zheng PY , Liu SM , Tang YC , Li EY , Sun ZY , Jiang MM ,
Summary Html Article
Autism   Gut Microbiota Dysbiosis Associated With Altered Production of Short Chain Fatty Acids in Children With Neurodevelopmental Disorders.
Frontiers in cellular and infection microbiology (Front Cell Infect Microbiol ) Vol: 10 Issue Pages: 223
Pub: 2020 Epub: 2020 May 19 Authors Bojovic K , Ignjatovic ÐI , Sokovic Bajic S , Vojnovic Milutinovic D , Tomic M , Golic N , Tolinacki M ,
Summary Html Article Publication
Autism   Autism spectrum disorder is associated with gut microbiota disorder in children.
BMC pediatrics (BMC Pediatr ) Vol: 19 Issue 1 Pages: 516
Pub: 2019 Dec 27 Epub: 2019 Dec 27 Authors Sun H , You Z , Jia L , Wang F ,
Summary Html Article Publication
Autism   Autism spectrum disorder is associated with gut microbiota disorder in children.
BMC pediatrics (BMC Pediatr ) Vol: 19 Issue 1 Pages: 516
Pub: 2019 Dec 27 Epub: 2019 Dec 27 Authors Sun H , You Z , Jia L , Wang F ,
Summary Html Article Publication
Autism   Characterization of Intestinal Microbiota and Probiotics Treatment in Children With Autism Spectrum Disorders in China.
Frontiers in neurology (Front Neurol ) Vol: 10 Issue Pages: 1084
Pub: 2019 Epub: 2019 Nov 5 Authors Niu M , Li Q , Zhang J , Wen F , Dang W , Duan G , Li H , Ruan W , Yang P , Guan C , Tian H , Gao X , Zhang S , Yuan F , Han Y ,
Summary Html Article Publication
Autism   Association Between Gut Microbiota and Autism Spectrum Disorder: A Systematic Review and Meta-Analysis.
Frontiers in psychiatry (Front Psychiatry ) Vol: 10 Issue Pages: 473
Pub: 2019 Epub: 2019 Jul 17 Authors Xu M , Xu X , Li J , Li F ,
Summary Html Article Publication
Autism   Altered Gut Microbiota in Chinese Children With Autism Spectrum Disorders.
Frontiers in cellular and infection microbiology (Front Cell Infect Microbiol ) Vol: 9 Issue Pages: 40
Pub: 2019 Epub: 2019 Mar 6 Authors Ma B , Liang J , Dai M , Wang J , Luo J , Zhang Z , Jing J ,
Summary Html Article Publication
Autism   Altered composition and function of intestinal microbiota in autism spectrum disorders: a systematic review.
Translational psychiatry (Transl Psychiatry ) Vol: 9 Issue 1 Pages: 43
Pub: 2019 Jan 29 Epub: 2019 Jan 29 Authors Liu F , Li J , Wu F , Zheng H , Peng Q , Zhou H ,
Summary Html Article Publication
Autism   Altered gut microbiota and short chain fatty acids in Chinese children with autism spectrum disorder.
Scientific reports (Sci Rep ) Vol: 9 Issue 1 Pages: 287
Pub: 2019 Jan 22 Epub: 2019 Jan 22 Authors Liu S , Li E , Sun Z , Fu D , Duan G , Jiang M , Yu Y , Mei L , Yang P , Tang Y , Zheng P ,
Summary Html Article Publication
Autism   The valproic acid rat model of autism presents with gut bacterial dysbiosis similar to that in human autism.
Molecular autism (Mol Autism ) Vol: 9 Issue Pages: 61
Pub: 2018 Epub: 2018 Dec 10 Authors Liu F , Horton-Sparks K , Hull V , Li RW , MartĂ­nez-Cerdeño V ,
Summary Html Article Publication
Autism   Analysis of gut microbiota profiles and microbe-disease associations in children with autism spectrum disorders in China.
Scientific reports (Sci Rep ) Vol: 8 Issue 1 Pages: 13981
Pub: 2018 Sep 18 Epub: 2018 Sep 18 Authors Zhang M , Ma W , Zhang J , He Y , Wang J ,
Summary Html Article Publication
Autism   Analysis of gut microbiota profiles and microbe-disease associations in children with autism spectrum disorders in China.
Scientific reports (Sci Rep ) Vol: 8 Issue 1 Pages: 13981
Pub: 2018 Sep 18 Epub: 2018 Sep 18 Authors Zhang M , Ma W , Zhang J , He Y , Wang J ,
Summary Html Article Publication
Autism   Microbiota-related Changes in Bile Acid & Tryptophan Metabolism are Associated with Gastrointestinal Dysfunction in a Mouse Model of Autism.
EBioMedicine (EBioMedicine ) Vol: 24 Issue Pages: 166-178
Pub: 2017 Oct Epub: 2017 Sep 21 Authors Golubeva AV , Joyce SA , Moloney G , Burokas A , Sherwin E , Arboleya S , Flynn I , Khochanskiy D , Moya-PĂ©rez A , Peterson V , Rea K , Murphy K , Makarova O , Buravkov S , Hyland NP , Stanton C , Clarke G , Gahan CGM , Dinan TG , Cryan JF ,
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Autism   Distinct Microbiome-Neuroimmune Signatures Correlate With Functional Abdominal Pain in Children With Autism Spectrum Disorder.
Cellular and molecular gastroenterology and hepatology (Cell Mol Gastroenterol Hepatol ) Vol: 3 Issue 2 Pages: 218-230
Pub: 2017 Mar Epub: 2016 Dec 11 Authors Luna RA , Oezguen N , Balderas M , Venkatachalam A , Runge JK , Versalovic J , Veenstra-VanderWeele J , Anderson GM , Savidge T , Williams KC ,
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Autism   New evidences on the altered gut microbiota in autism spectrum disorders.
Microbiome (Microbiome ) Vol: 5 Issue 1 Pages: 24
Pub: 2017 Feb 22 Epub: 2017 Feb 22 Authors Strati F , Cavalieri D , Albanese D , De Felice C , Donati C , Hayek J , Jousson O , Leoncini S , Renzi D , CalabrĂČ A , De Filippo C ,
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Autism   Ketogenic diet modifies the gut microbiota in a murine model of autism spectrum disorder.
Molecular autism (Mol Autism ) Vol: 7 Issue 1 Pages: 37
Pub: 2016 Epub: 2016 Sep 1 Authors Newell C , Bomhof MR , Reimer RA , Hittel DS , Rho JM , Shearer J ,
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Autism   Comparison of Fecal Microbiota in Children with Autism Spectrum Disorders and Neurotypical Siblings in the Simons Simplex Collection.
PloS one (PLoS One ) Vol: 10 Issue 10 Pages: e0137725
Pub: 2015 Epub: 2015 Oct 1 Authors Son JS , Zheng LJ , Rowehl LM , Tian X , Zhang Y , Zhu W , Litcher-Kelly L , Gadow KD , Gathungu G , Robertson CE , Ir D , Frank DN , Li E ,
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Autism   Increased abundance of Sutterella spp. and Ruminococcus torques in feces of children with autism spectrum disorder.
Molecular autism (Mol Autism ) Vol: 4 Issue 1 Pages: 42
Pub: 2013 Nov 4 Epub: 2013 Nov 4 Authors Wang L , Christophersen CT , Sorich MJ , Gerber JP , Angley MT , Conlon MA ,
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Autism   Fecal microbiota and metabolome of children with autism and pervasive developmental disorder not otherwise specified.
PloS one (PLoS One ) Vol: 8 Issue 10 Pages: e76993
Pub: 2013 Epub: 2013 Oct 9 Authors De Angelis M , Piccolo M , Vannini L , Siragusa S , De Giacomo A , Serrazzanetti DI , Cristofori F , Guerzoni ME , Gobbetti M , Francavilla R ,
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Autism   Reduced incidence of Prevotella and other fermenters in intestinal microflora of autistic children.
PloS one (PLoS One ) Vol: 8 Issue 7 Pages: e68322
Pub: 2013 Epub: 2013 Jul 3 Authors Kang DW , Park JG , Ilhan ZE , Wallstrom G , Labaer J , Adams JB , Krajmalnik-Brown R ,
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Autism   Gut Microbial Dysbiosis in Indian Children with Autism Spectrum Disorders.
Microbial ecology (Microb Ecol ) Vol: 76 Issue 4 Pages: 1102-1114
Pub: 2018 Nov Epub: 2018 Mar 21 Authors Pulikkan J , Maji A , Dhakan DB , Saxena R , Mohan B , Anto MM , Agarwal N , Grace T , Sharma VK ,
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Autism   Differences in fecal microbial metabolites and microbiota of children with autism spectrum disorders.
Anaerobe (Anaerobe ) Vol: 49 Issue Pages: 121-131
Pub: 2018 Feb Epub: 2017 Dec 22 Authors Kang DW , Ilhan ZE , Isern NG , Hoyt DW , Howsmon DP , Shaffer M , Lozupone CA , Hahn J , Adams JB , Krajmalnik-Brown R ,
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Autism   Disturbance of trace element and gut microbiota profiles as indicators of autism spectrum disorder: A pilot study of Chinese children.
Environmental research (Environ Res ) Vol: 171 Issue Pages: 501-509
Pub: 2019 Apr Epub: 2019 Feb 5 Authors Zhai Q , Cen S , Jiang J , Zhao J , Zhang H , Chen W ,
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Autism   Changes in the Gut Microbiota of Children with Autism Spectrum Disorder.
Autism research : official journal of the International Society for Autism Research (Autism Res ) Vol: 13 Issue 9 Pages: 1614-1625
Pub: 2020 Sep Epub: 2020 Aug 24 Authors Zou R , Xu F , Wang Y , Duan M , Guo M , Zhang Q , Zhao H , Zheng H ,
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Autism   Study of the gut Microbiome Profile in Children with Autism Spectrum Disorder: a Single Tertiary Hospital Experience.
Journal of molecular neuroscience : MN (J Mol Neurosci ) Vol: 70 Issue 6 Pages: 887-896
Pub: 2020 Jun Epub: 2020 Feb 15 Authors Ahmed SA , Elhefnawy AM , Azouz HG , Roshdy YS , Ashry MH , Ibrahim AE , Meheissen MA ,
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Autism   Identifying psychiatric disorder-associated gut microbiota using microbiota-related gene set enrichment analysis.
Briefings in bioinformatics (Brief Bioinform ) Vol: Issue Pages:
Pub: 2019 Apr 5 Epub: 2019 Apr 5 Authors Cheng S , Han B , Ding M , Wen Y , Ma M , Zhang L , Qi X , Cheng B , Li P , Kafle OP , Liang X , Liu L , Du Y , Zhao Y , Zhang F ,
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Autism   The Gut Microbiota and Autism Spectrum Disorders
Frontiers in Cellular Neuroscience (Front Cell Neurosci ) Vol: 11 Issue Pages: 120
Pub: 2017 Apr 28 Epub: 2017 Apr 28 Authors Li Q , Han Y , Dy AB , Hagerman RJ ,
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Autism   Intestinal Dysbiosis and Yeast Isolation in Stool of Subjects with Autism Spectrum Disorders.
Mycopathologia (Mycopathologia ) Vol: 182 Issue 3-4 Pages: 349-363
Pub: 2017 Apr Epub: 2016 Sep 21 Authors Iovene MR , Bombace F , Maresca R , Sapone A , Iardino P , Picardi A , Marotta R , Schiraldi C , Siniscalco D , Serra N , de Magistris L , Bravaccio C ,
Summary Publication Publication
Autism   Can we reduce autism-related gastrointestinal and behavior problems by gut microbiota based dietary modulation? A review.
Nutritional neuroscience (Nutr Neurosci ) Vol: Issue Pages: 1-12
Pub: 2019 Jun 19 Epub: 2019 Jun 19 Authors Nogay NH , Nahikian-Nelms M ,
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Autism   The Role of Gut Microbiota in Gastrointestinal Symptoms of Children with ASD.
Medicina (Kaunas, Lithuania) (Medicina (Kaunas) ) Vol: 55 Issue 8 Pages:
Pub: 2019 Jul 26 Epub: 2019 Jul 26 Authors MartĂ­nez-GonzĂĄlez AE , Andreo-MartĂ­nez P ,
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Autism   Analysis of gut microbiome, nutrition and immune status in autism spectrum disorder: a case-control study in Ecuador.
Gut microbes (Gut Microbes ) Vol: Issue Pages: 1-12
Pub: 2019 Sep 18 Epub: 2019 Sep 18 Authors Zurita MF , CĂĄrdenas PA , Sandoval ME , Peña MC , Fornasini M , Flores N , Monaco MH , Berding K , Donovan SM , Kuntz T , Gilbert JA , BaldeĂłn ME ,
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Autism   An approach to gut microbiota profile in children with autism spectrum disorder.
Environmental microbiology reports (Environ Microbiol Rep ) Vol: Issue Pages:
Pub: 2019 Nov 11 Epub: 2019 Nov 11 Authors Andreo-MartĂ­nez P , GarcĂ­a-MartĂ­nez N , SĂĄnchez-Samper EP , MartĂ­nez-GonzĂĄlez AE ,
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Autism   [Correlation between gut microbiota and behavior symptoms in children with autism spectrum disorder].
Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics (Zhongguo Dang Dai Er Ke Za Zhi ) Vol: 21 Issue 7 Pages: 663-669
Pub: 2019 Jul Epub: Authors Zhao RH , Zheng PY , Liu SM , Tang YC , Li EY , Sun ZY , Jiang MM ,
Autism   Impact of Clostridium Bacteria in Children with Autism Spectrum Disorder and Their Anthropometric Measurements.
Journal of molecular neuroscience : MN (J Mol Neurosci ) Vol: Issue Pages:
Pub: 2020 Mar 4 Epub: 2020 Mar 4 Authors Kandeel WA , Meguid NA , BjĂžrklund G , Eid EM , Farid M , Mohamed SK , Wakeel KE , Chirumbolo S , Elsaeid A , Hammad DY ,
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