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 , Martínez-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-Pérez A , Peterson V , Rea K , Murphy K , Makarova O , Buravkov S , Hyland NP , Stanton C , Clarke G , Gahan CGM , Dinan TG , Cryan JF ,
Summary Html Article Publication
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 ,
Summary Html Article Publication
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 , Calabrò A , De Filippo C ,
Summary Html Article Publication
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 ,
Summary Html Article Publication
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 ,
Summary Html Article Publication
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 ,
Summary Html Article Publication
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 ,
Summary Html Article Publication
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 ,
Summary Html Article Publication
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 ,
Summary Publication Publication
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 ,
Summary Publication Publication
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 ,
Summary Publication Publication
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 ,
Summary Publication Publication
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 ,
Summary Publication Publication
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 ,
Summary Publication Publication
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 ,
Summary Publication Publication
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 ,
Summary Publication Publication
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 Martínez-González AE , Andreo-Martínez P ,
Summary Publication Publication
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 , Cárdenas PA , Sandoval ME , Peña MC , Fornasini M , Flores N , Monaco MH , Berding K , Donovan SM , Kuntz T , Gilbert JA , Baldeón ME ,
Summary Publication Publication
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-Martínez P , García-Martínez N , Sánchez-Samper EP , Martínez-González AE ,
Summary Publication 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 ,
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 , Bjørklund G , Eid EM , Farid M , Mohamed SK , Wakeel KE , Chirumbolo S , Elsaeid A , Hammad DY ,
Summary Publication Publication

Recent PubMed Literature Review

This is a quick review of the latest 200 articles on PubMed, pulling out interesting items. Aug 14,2021

  • ” Clinical trials have shown some evidence to suggest the beneficial effects of probiotics in depressive and neurodevelopmental disorders. Limited studies have discussed this subject; however, the role of the intestinal flora in the pathophysiology and treatment of mental disorders appears to be a promising field of research.” [2021]
    • Food selectivity is associated with more severe autism symptoms in toddlers with autism spectrum disorder This selectivity may reinforce the microbiome dysfunction
    • “. With accumulating evidence showing how the microorganisms modulate neural activities, more and more research is focusing on the role of the gut microbiota in mitigating ASD symptoms and the underlying mechanisms. In this review, we describe the intricate and crucial pathways via which the gut microbiota communicates with the brain, the microbiota-gut-brain axis, and summarize the specific pathways that mediate the crosstalk of the gut microbiota to the brain in ASD.”[2021]
    • Understanding Heterogeneity in Autism Spectrum Disorder: A Methodological Shift in Neuroimaging Research From Investigating Group Differences to Individual Differences [2021]
    • “provides a functional analysis of cell bioenergetics and metabolic changes in a group of Bulgarian patients with ASD. It reveals physiological abnormalities that do not allow mitochondria to adapt and meet the increased energetic requirements of the cell. ” [2021] – difference could be partially attributed to microbiome shifts
    • “Metallomic profiles of ASD patients cover, besides essential elements such as cobalt, chromium, copper, iron, manganese, molybdenum, zinc, selenium, also toxic metals burden of: aluminum, arsenic, mercury, lead, beryllium, nickel, cadmium. Performed studies indicate that children with ASD present a reduced ability of eliminating toxic metals, which leads to these metals’ accumulation and aggravation of autistic symptoms.” [2021] – some bacteria are known to reduce toxic metals, see [studies]
    • ” The results revealed that the possible underlying pathophysiology of ASD were alterations of amino acids, reactive oxidative stress, neurotransmitters, and microbiota-gut-brain axis. The potential common pathways shared by animal and human studies related to the improvement of ASD symptoms after pharmacological interventions were mammalian-microbial co-metabolite, purine metabolism, and fatty acid oxidation” [2021] – most of these items are significantly influence by the microbiome.
  • Early Motor Skills in Children With Autism Spectrum Disorders Are Marked by Less Frequent Hand and Knees Crawling
    • ” In comparison to healthy peers, children with ASD showed impairments in executive function and muscle strength. Moreover, higher muscle strength was independently associated with better executive function, but only in ASD patients. This is a first indication that the promotion of muscle strength, for example, by regular exercise, could contribute to a reduction of ASD-related executive dysfunction.” [2021]
    • Motor challenges in ASD are pervasive, clinically meaningful, and highly underrecognized, with up to 87% of the autistic population affected but only a small percentage receiving motor-focused clinical care… Findings suggest that motor difficulties in ASD are quantifiable and treatable,  ” [2021]
    • “Delays in developmental milestones, particularly in gross motor skills, are frequent and may be among the earliest indicators of differentially affected developmental processes in specific genetically defined conditions associated with ASD, as compared with those with clinical diagnoses of idiopathic ASD. ” [2021]
  • “Both paternal and maternal autoimmune diseases were associated with increased likelihood of ADHD in children. However, only paternal autoimmune diseases were related to offspring ASD risk.” [2021]
    • “In this national cohort, preterm and early term birth were associated with increased risk of ASD in boys and girls. ” [2021]
    • “Results indicate that maternal pre-pregnancy severe obesity increases risk of ASD and developmental disorders  in children and suggest high gestational-age-adjusted gestational weight gain is a risk factor for ASD in male children.” [2021]
    • “The findings showed that labor induction is associated with increased risk of ASD among children. Therefore, the findings support that clinical use of oxytocin during labor has a significant negative impact on the long-term mental health of children.” [2021]
    • “Children with predominant white matter injury, related to insults in the late second or early third trimester, had the highest prevalence of autism (40%). Children who had sustained a middle cerebral artery infarction had the highest prevalence of ADHD (62%).” [2021]
    • “Neonatal jaundice, depends on its severity, seems to be one of the possible biological factors associated with subsequent development of and the severity of ASD. ” [2021]
  • “Results indicated that youth with ASD had greater Reactivity severity and also greater positive change in Reactivity than non-ASD peers. Furthermore, differences between youth with and without ASD in the relationship between Reactivity and Dysphoria suggest a distinct profile of emotion dysregulation in ASD” [2021]
  • “The results demonstrate a positive association between comprehensive treatment models and better prognosis in childhood, especially regarding symptoms, and language. However, most extant research involves small, non-randomized studies, preventing definitive conclusions from being drawn. Clearly, the outcomes of children with ASD are still far from normal, especially with respect to adaptive functioning, and the four mediating variables pertaining to treatment elements can affect their gains, including approach, implementer, intensity, and total treatment hours.” [2021]
  • ” A review of the literature on whether hyperbaric oxygen therapy (HBOT) as a therapy significantly affects the symptoms of ASD does not confirm its effectiveness.” [2021]
  • ” the adults with ASD were approximately 2.6 times more likely to be diagnosed with early-onset Alzheimer’s disease and related dementias compared to the general population.” [2021]
  • Autistic people are more likely to be transgender, which means having a gender identity different to one’s sex assigned at birth. [2021]
  • Decreased risk for substance use disorders in individuals with high-functioning autism spectrum disorder [2021]
  • ” This study suggested that acupuncture could effectively treat ASD” [2021]
  • “Our results further support a hypothesized causal link with ASD that is specific to postnatal exposures to traffic-related pollution.” [2021]

Technical DNA/SNP Stuff

Autoimmune Encephalitis with Autism, COVID, CFS/ME etc

A reader asked “Autoimmune Encephalitis in kids and therapeutic Treatment agents 🙏“. I am aware that the reader deals with a child with autism, so my focus will be in that direction.

Autoimmune encephalitis is a collection of related conditions in which the body’s immune system attacks the brain, causing inflammation. The immune system produces substances called antibodies that mistakenly attack brain cells.

Brain Institute

Those with CFS/ME knows that ME stands for myalgic encephalomyelitis which leads to the question — what is the difference?

Acute disseminated encephalomyelitis (ADEM) accounts for around 10% of all known cases of encephalitis.  ADEM usually affects children and begins after a childhood rash (exanthema), other viral infections or immunizations. There is usually a latent period of days to two to three weeks before symptoms emerge. The illness has been poorly understood and a variety of terminologies used to describe it, these including post-viral, post-infectious or para-infectious.

Acute disseminated encephalomyelitis (ADEM) | The Encephalitis Society

The key words are poorly understood and there is no definitive test to tell them apart. There was a proposal in 2016, A clinical approach to diagnosis of autoimmune encephalitis – autism is not mentioned in this proposal or its appendix. We do see from this article that there are multiple sub-categories.

The Diagnosis and Treatment of Autoimmune Encephalitis (nih.gov) [2016]

This article lists the following infection associated: HSV, CMV, VZV, JE, Enterovirus, HHV6, HHV7, Neuroborreliosis (Lyme disease), WNV (West Nile), Syphilis, Cryptococcus, Aspergillus fumigatus, Mucor , Tuberculosis, , Listeria, Streptococcus, Toxoplasmosis. Bold items are items associated to CFS/ME. To these, we need to add COVID.

Autism Specific

“Diagnosing autoimmune encephalitis sooner can increase the effectiveness of curative treatments-such as immune therapy or immune modulatory therapy-that may prevent the long-term consequence of being misdiagnosed with autism spectrum disorder. Glutamate therapy primarily normalizes glutamate neurotransmission and can be a new add-on intervention alongside antipsychotics for treating autoimmune autism.”

Autism Associated With Anti-NMDAR Encephalitis: Glutamate-Related Therapy [2019]

Drilling down in this direction we find:

There are a lot more, but the reader’s concern was treatment.

Treatment Options

We have what really amounts to be a symptom ” “, which can be associated with many causes — for example: infections. For those the treatment should be specific for the infection.

For some of the conditions cited above, we have really just one set of suggestions which may be worth considering (after consulting with your medical professional). This is specific for autism, but may be applicable to ME/CFS and Long Haul Covid.

Glutamate supplementation or blockers. See this article Glutamate – The Autism Community in Action (TACA) (tacanow.org). Note that Urine Amino Analysis: (i.e. OATS) and blood tests are deemed unreliable. An old school approach is to insure a stable regular diet and then try supplementation that increases glutamate for 1-2 weeks and then try supplementation that reduces glutamate for 1-2 weeks [see above page]. This will likely provide insight to the nature of the imbalance of glutamate.

Supplements to reduce IL-17

The interleukin 17 (IL-17) family, a subset of cytokines plays crucial roles in both acute and chronic inflammatory responses. Its intended role is against pathogens — but if it is stuck on then it becomes harmful. This can sometime happen with mis-identification of chemical signals. For details on the members of this subset, see Kyoto Encyclopedia of Genes and Genomes.

It appears to be a significant player for Autism, Interleukin-17 in Chronic Inflammatory Neurological Diseases [2020]

A reader has asked about items that are known to reduce it. The following comes from a search of PubMed

  • There are a variety of prescription IL-17 inhibitors (ixekizumab, secukinumab, bimekizumab, netakimab, brodalumab) covered in this review [2021]
  • An engineered Lactobacillus salivarius  is described here [2017]
  • Lactobacillus plantarum (LP) IS-10506 “The IL-4 and IL-17 levels were significantly lower in the probiotic than the placebo group.” [2020]
  • Luteolin decreases levels [2021] (available as a supplement)
  • ” The combination of L. acidophilus, vitamin B, and curcumin effectively downregulated Th17 cells and the related cytokine IL-17, thereby maintained the Treg population, ” [2020]
  • Lactobacillus plantarum “pre-treatment with food-borne Lpb. plantarum significantly reduce pro-inflammatory cytokines IL-17F and IL-23 levels in inflamed NCM460 cells.” [2020]
  • Lactobacillus casei Shirota (Yakult, the beverage) ” LcS significantly reduced plasma monocyte chemotactic protein-1 and, on subgroup analysis, plasma interleukin-1β (alcoholic cirrhosis), interleukin-17a and macrophage inflammatory protein-1β (non-alcoholic cirrhosis), compared with placebo.” [2020]
  • The Role of Flavonoids in Inhibiting Th17 Responses in Inflammatory Arthritis [2018] provide a lot of details (including some unusual herbs and spices). Items more commonly available include:
    • Apples –  Procyanidins B1, B2, and C1
    • Grape Seed Extract — Proanthocyanidins
    • Licorice — (Glycyrrhiza glabra) I can strongly attest that it does wonders for inflammation (We use spezzatina )
    • Blueberry, Raspberry, black rice, and black soybean – Anthocyanins
  • Berberine “attenuating the Th17 response triggered by the B cell-activating factor” [2018]
  • Astragalus “Downregulating Interleukin-17 Expression via Wnt Pathway'[2020]
  • Curcumin (Turmeric) – “Curcumin mediates attenuation of pro-inflammatory interferon γ and interleukin 17 cytokine responses in psoriatic disease” [2020]

More items (with references) is listed here, this was a quick summary – that is a deeper review.

To avoid:

  • Lactobacillus rhamnosus GG (LGG) ATCC 53103 “upregulated the expression of IL-17” [2020]
  • “We confirm that food intake increases IL-17 expression in the mouse ileum and human blood. e. Thus, IL-17 is a gut-produced factor that is controlled by diet and modulates food intake by acting in the hypothalamus. Our findings provide the first evidence of a cytokine that is acutely regulated by food intake and plays a role in the regulation of eating.” [2020]

Bottom Line

The last citation points to the microbiome as a very significant factor for the levels of IL-17. At present, we do not know which bacteria play a role (many bacteria cannot be cultured, which limits our knowledge of what they do).

Modelling Candidate Bacteria

We have a list of items that reduces IL-17. We also find many of these items in our database. Thus if we look at the bacteria that are reduced by these food, we may be able to generate a candidate list of bacteria of concern.

The result is this list of significant bacteria

  • Clostridiaceae (family)
  • Enterobacteriaceae (family)
  • Staphylococcaceae (family)
  • Streptococcaceae (family)
  • Clostridium (genus)
  • Enterobacter (genus)
  • Enterococcus (genus)
  • Escherichia (genus)
  • Kluyvera (genus)
  • Pseudomonas (genus)
  • Staphylococcus (genus)
  • Streptococcus (genus)
  • Enterococcus faecalis (species)
  • Escherichia coli (species)
  • Pseudomonas aeruginosa (species)
  • Pseudomonas aeruginosa group (species)
  • Staphylococcus aureus (species)
  • Streptococcus mutans (species)

The strongest hint is for Staphylococcus aureus (species) which leads to this article:

So we have a full cycle… items shown to reduce IL-17 also are items that reduce a list of bacteria. Checking those bacteria, we find that they are associated with high IL-17 levels.

Consequence: In asking for suggestions – you may wish to go to hand-pick bacteria and select any of those listed above.

I have a longer list by genus below that are also suspect (from strongest hint to weaker).

  1. Escherichia (genus)
  2. Pseudomonas (genus)
  3. Staphylococcus (genus)
  4. Kluyvera (genus)
  5. Streptococcus (genus)
  6. Enterobacter (genus)
  7. Clostridium (genus)
  8. Enterococcus (genus)
  9. Citrobacter (genus)
  10. Dorea (genus)
  11. Eubacterium (genus)
  12. Raoultella (genus)
  13. Shigella (genus)
  14. Bacillus (genus)
  15. Fenollaria (genus)
  16. Intestinimonas (genus)
  17. Caloramator (genus)
  18. Oscillibacter (genus)
  19. Gracilibacter (genus)
  20. Coprobacter (genus)
  21. Slackia (genus)
  22. Helicobacter (genus)
  23. Coprococcus (genus)
  24. Cronobacter (genus)
  25. Prevotella (genus)
  26. Anaerobutyricum (genus)
  27. Parasporobacterium (genus)
  28. Anaerobium (genus)
  29. Anaerotignum (genus)
  30. Fusicatenibacter (genus)
  31. Hespellia (genus)
  32. Faecalicatena (genus)
  33. Tyzzerella (genus)

Fecal Matter Transplant in Autism

I have written posts on this for ME/CFS, listed below — but a reader asked me specific for Autism. On Pubmed there was a number of studies on Autism and FMT, hence this article.

Autism Specific

Together, these findings suggest that MTT is safe and well-tolerated in children with ASD ages 7–16 years. MTT led to significant improvements in both GI- and ASD-related symptoms, and the improvements were sustained at least 8 weeks after treatment. Coincident with these clinical improvements, both microbiota and phage from the donors appear to have engrafted, at least partially, in the recipients. This shifted gut microbiota of children with ASD toward that of neurotypical children is consistent with the hypothesis that gut microbiota may be at least partially responsible for GI and ASD symptoms. 

Microbiota transfer therapy alters gut ecosystem and improves gastrointestinal and autism symptoms: an open-label study.[2017]

Bottom Line

The largest studies are from China with 73 patients. One of the typical problem with small studies is bias in the selection of candidates as well as reporting averages. With the China study we get 61.6% improvement; this agrees with “most improvements” (i.e. over 50%) from other studies.

The selection of the donor is critical. For example, if the child is low in Akkermansia muciniphila, the donor should be high (i.e. above the median at least, ideally at the 75%ile or more). A 16s microbiome profile should be done on the child and candidate samples before proceeding. “Bottled off-the shelf FMTs” will likely have poorer success rates.

This is not a cure, it is an improvement. The greatest benefit may occur in children with gastrointestinal symptoms (speculation ).