Son and Daughter with Autism Analysis – Part 2

This is a follow up the earlier blog post: Son and Daughter with Autism Analysis from a year ago. There has been a lot of changes of the site and revisions of algorithms.

Comparing Siblings

We know from studies that members in the same family often share about 27% of the same strains. Unfortunately with 16s tests (Biomesight, Ombre), we do not get strain information just species information.

Using the new refactor citizen science symptoms (see New Special Studies on Symptoms ), we are presently surprised! We have many forecast symptoms being the same which supports the observation cited above of share taxa, likely at the strain level.

It does hint that less time with each other and a lot more time with other (ideally normal) children may have benefits to the microbiome. Some of the changes may be connected to gender:

  • About twice as many women as men experience depression [Mayo]
  • Increased inflammation is seen in the periphery in both depression and fatigue. [2019] which agrees with the daughter having a lower Anti inflammatory Bacteria Score
MeasureDaughterSon
Anti inflammatory Bacteria Score25.6%ile89%ile
Buytrate Bacteria Score95.9%ile78%ile
Histamine Producers21.8%ile15.3%
Autism From PubMed53/97 (1%ile)
Prior: 54/97 (1%ile)
73/97 (11%ile)
Prior: 53/97 (1%ile)
Forecast SymptomsOfficial Diagnosis: Depression
28 % match on 7 taxa

DePaul University Fatigue Questionnaire : Blurred Vision
25 % match on 8 taxa
Neurological-Sleep: Inability for deep (delta) sleep
23 % match on 13 taxa

Age: 10-20
17 % match on 23 taxa

DePaul University Fatigue Questionnaire : Forgetting what you are trying to say
16 % match on 31 taxa

Next looking at Percentages of Percentiles, we see significant differences. Unfortunately, we do not have gender and age reference tables, so interpretation is fuzzy.

Potential Medical Conditions Detected had nothing significant for either child. Both are at 95.6%ile on Dr. Jason Hawrelak Recommendations (they were 98.9 and 99.7%iles before) .

Detail Comparison

The thing that stands out is that the Son has a lot more Enzymes out of range (with the resulting substrates(consumers) and products also being out of range).

CriteriaDaughterSon
Lab Read Quality6.710.9
PubMed Bacteria Matches for Autism1%ile (53/97)11%ile (73/97)
Outside Range from JasonH55
Outside Range from Medivere1818
Outside Range from Metagenomics99
Outside Range from MyBioma99
Outside Range from Nirvana/CosmosId2323
Outside Range from XenoGene5151
Outside Lab Range (+/- 1.96SD)1122
Outside Box-Plot-Whiskers9876
Outside Kaltoft-Moldrup132248
Bacteria Reported By Lab842757
Bacteria Over 99%ile1311
Bacteria Over 95%ile2845
Bacteria Over 90%ile6661
Bacteria Under 10%ile66285
Bacteria Under 5%ile22214
Shannon Diversity Index3.0642.807
Simpson Diversity Index0.070.088
Chao1 Index2979124924
Rarely Seen 5%6198
Pathogens3635
Kegg Compounds Low9731001
Kegg Compounds High43162
Kegg Enzymes Low89265
Kegg Enzymes High98381
Kegg Products Low55152
Kegg Products High52209
Kegg Substrates Low46148
Kegg Substrates High58229

Looking at KEGG Derived Probiotic suggestions, the list is full of the soil based bacteria found in Prescript-Assist®/SBO Probiotic or Energybalance / ColoBiotica 28 Colon Support or General Biotics/Equilibrium. There was no probiotic above my usual threshold from the consensus, so the above seems to be worth a try.

KEGG Suggested supplements has nothing significant for the daughter, but for the son we have the following being very significant:

  • Serine
  • Threonine
  • Glutamine
  • Cysteine
  • Arginine

A complex amino-acid supplement may be worth an experiment.

As an experiment (and trying to avoid two different kid diet), I did an uber-consensus from each child’s with tons of prescription medication but only one thing above my usual 50% of highest value.

Son Compared to Prior Sample

We can see the spike in low percentile bacteria. This raises the question, has he had COVID (or a COVID vaccine) prior to the sample being done. These spikes show themselves also via Kaltoft-Moldrup and Box-Plot-Whiskers which are both sensitive to this pattern.

CriteriaCurrent SampleOld Sample
Lab Read Quality10.94.4
Outside Range from JasonH44
Outside Range from Medivere1717
Outside Range from Metagenomics1010
Outside Range from MyBioma1313
Outside Range from Nirvana/CosmosId2727
Outside Range from XenoGene4949
Outside Lab Range (+/- 1.96SD)2222
Outside Box-Plot-Whiskers76100
Outside Kaltoft-Moldrup24889
Bacteria Reported By Lab757708
Bacteria Over 90%ile6182
Bacteria Under 10%ile28526
Shannon Diversity Index2.8072.451
Simpson Diversity Index0.0880.15
Chao1 Index2492419183
Lab: Thryve
Pathogens3530
Condition Est. Over 90%ile20
Kegg Compounds Low10011048
Kegg Compounds High162132
Kegg Enzymes Low265115
Kegg Enzymes High381296
Kegg Products Low15274
Kegg Products High209191
Kegg Substrates Low14869
Kegg Substrates High229212
Anti inflammatory Bacteria Score89.2%ile83.2%ile
Buytrate Bacteria Score77.9%ile90.2%ile
Histamine Producers15.3%ile38.2%ile
Histamine dropping is usually a good sign

From this weekend update of special studies, we can get a count of bacteria shifts strongly associated to symptoms.

  • Old Sample: 32 taxa
  • Latest Sample: 60 taxa

Daughter Compared to Prior Sample

First the numbers which are usually similar to the prior sample.

CriteriaCurrent SampleOld Sample
Lab Read Quality6.73.1
Outside Range from JasonH66
Outside Range from Medivere1919
Outside Range from Metagenomics77
Outside Range from MyBioma1212
Outside Range from Nirvana/CosmosId2626
Outside Range from XenoGene4747
Outside Lab Range (+/- 1.96SD)1161
Outside Box-Plot-Whiskers98203
Outside Kaltoft-Moldrup132134
Bacteria Reported By Lab842852
Bacteria Over 90%ile66202
Bacteria Under 10%ile6610
Shannon Diversity Index3.0643.411
Simpson Diversity Index0.070.028
Chao1 Index2979135210
Lab: Thryve
Pathogens3635
Condition Est. Over 90%ile00
Kegg Compounds Low9731027
Kegg Compounds High4380
Kegg Enzymes Low8944
Kegg Enzymes High98171
Kegg Products Low5529
Kegg Products High5286
Kegg Substrates Low4626
Kegg Substrates High58111
Anti inflammatory Bacteria Score25.5%ile28%ile
Buytrate Bacteria Score95.9%ile74.5%ile
Histamine Producers21.7%ile28.7%ile

From this weekend update of special studies, we can get a count of bacteria shifts strongly associated to symptoms.

  • Old Sample 53
  • Latest Sample: 39

Out of curiosity, I compared the symptom associated outliers. We found 3 are matches (of these 39) and one not matches for the taxa reported for each. That is close to the expected percentage of the same strains for people in the same house.

Bacteria NameDaughterSon
  NegativicutesToo HighToo High
  AcidobacteriiaToo LowToo Low
  Bacteroides eggerthiiToo HighToo Low
  PropionibacterialesToo LowToo Low

Going Forward

Autism has challenges because of its complex nature. This is compounded by a low number of samples to work from for Citizen Science analysis. The shifts reported from PubMed have a high pattern match with people who do not have autism.

I am going to try building a consensus for each by doing two itemsL

  • “Just give Me Suggestions”
  • Doing PubMed Autism on [Changing Microbiome]
  • [All Bacteria identified by special studies]

The rationale is that the last one identify the bacteria that appears to be symptom causing in many people. We have a very poor match from what we do have a match for. This is not surprising because autism is a very wide spectrum.

We then see six sets of suggestion

Son

When I look at the details we have over 150 items with 6 recommended take (i.e. everyone agrees)

The probiotics that have no known adverse risk for any bacteria is below. The high value is 510.

Daughter

When I look at the details we have just 15 items with 6 recommended take (i.e. everyone agrees)

The probiotics that have no known adverse risk for any bacteria are low in computed benefit, so I would ignore them.

  • Their values are low: 16/31 out of a high value of 301

Bottom Line

The failure to find significant matching patterns is a bit of a frustration to me. What we did find had very good agree for the son with 150+ items having each of the size suggestion set agreeing for the take. For the daughter, it was not as strong: 15 for 6 sets being in agreement, and 50 with 5 sets being in agreement.

Questions

  1. I assume higher anti-inflammatory score is better – Daughter was 25% and Son was 89%
  2. Deep Sleep with Son – 23% match that he has deep sleep issues is pretty strong?
    • Does not jump out, but indicates that microbiome is playing a role.
  3. Son – lot more missed enzymes – what is that do you believe and probiotics help with that?
    • I avoid the word “believe”. A rational assumption is that disruption of enzymes compare to others impacts how the cells (including brain cells) react.
  4. Spike in low percentage bacteria – likely long Covid for Son means he has less good bacteria now?
    • I avoid the words “good” or “bad” bacteria. Any bacteria far enough from typical values become bad; disruption to the microbiome and the body. Theses spikes are typically seen (pattern matching) with two conditions: Long COVID and ME/CFS. A common symptom of these two issues are cognitive issues – for example: memory, ability to learn, etc.
  5. Histamine – Higher percentage is worse correct?  Daughter was 21% and son was 15% 
  6. Higher Butryate percentage is better?  95% daughter / 78% son

The Journey Begins with your microbiome

Thanks for joining me!

This is a companion site to the analysis site at: 

https://microbiomeprescription.com/

The intent of this site to assist people with health issues that are, or could be, microbiome connected. There are MANY conditions known to have the severity being a function of the microbiome dysfunction, including Autism, Alzheimer’s, Anxiety and Depression. See this list of studies from the US National Library of Medicine. Individual symptoms like brain fog, anxiety and depression have strong statistical association to the microbiome. A few of them are listed here.

The base rule of the site is to avoid speculation, keep to facts from published studies and to facts from statistical analysis(with the source data available for those wish to replicate the results). Internet hearsay is avoid like the plague it is.

Open data and Open source are our mottos!

Continue reading “The Journey Begins with your microbiome” →Posted on  by lassesenEdit

Biomesight #4 Sample: IBS and COVID

We have a varied history with some storms blowing us off courses. Here’s a list of the tests and prior blog posts:

His comments are short:

  • I would say some small subjective improvements since last time, but no major changes. Reminder: I have a friendly MD in terms of antibiotics.
  • Metronidazole was on top in the last samples, I did it back then.
    • Comment: Metronidazole is no longer at the top but dropped down to 16% of the highest value. It appears to have done its magic in reducing the bacteria pointing to it as a tool..

Base Analysis

When people have multiple samples, I like to do side-by-side comparisons, especially when someone has been doing some of the suggestions suggested. The suggestions are computed and may not always work. Expert Systems and AI are not perfect; they typically do better than a person with only a few years of experience that has training in the discipline (better consistency, remember more facts, etc). How are we doing objectively?

Scores

We see two positive shifts in the latest sample: Increase of Anti inflammatory Bacteria Score and decrease of Histamine Producers.

Percentages of Percentiles

We see a lot of bouncing around between samples. The middle two images matches the typical pattern seen with ME/CFS and Long COVID. Those shifts have faded over the last 3 months with a different pattern appearing indicating a different dialect of gut dysfunction.

Multi-Vector Comparison

The main numbers are below. The take away, less bacteria that are in the high percentile range (at 95%ile, 10 -> 28 -> 23 -> 8). The numbers bounce around with the middle two being similar and the other two also similar. There are no really clear shift in these measures.

Criteria11/18/20215/20/20226/22/20239/4/2023
Lab Read Quality8.15.54.77.2
Outside Range from JasonH6699
Outside Range from Medivere16161515
Outside Range from Metagenomics8877
Outside Range from MyBioma5566
Outside Range from Nirvana/CosmosId20202323
Outside Range from XenoGene29293535
Outside Lab Range (+/- 1.96SD)76173
Outside Box-Plot-Whiskers36695438
Outside Kaltoft-Moldrup93484788
Bacteria Reported By Lab652508542558
Bacteria Over 99%ile7462
Bacteria Over 95%ile1028238
Bacteria Over 90%ile29423622
Bacteria Under 10%ile2084150175
Bacteria Under 5%ile180198157
Shannon Diversity Index1.8531.8261.2721.556
Simpson Diversity Index0.0560.0380.0870.09
Rarely Seen 1%2271
Rarely Seen 5%145218
Pathogens41242936

From Special Studies

The top match was the same on all of the samples, with an increase when there was actually COVID.

Criteria11/18/20215/20/20226/22/20239/4/2023
COVID19 (Long Hauler)28%ile33%ile41%ile28%ile
Next one:15%ile26%ile20%ile13%ile

The “next one” dropping implies some reduction of dysbiosis

Health Analysis

Using Dr. Jason Hawrelak Recommendations, there are many items on the edge of being in range with some items of interest (I strike out those that are unlikely to be of great concern):

  • Faecalibacterium prausnitzii at 27% of the microbiome or 96%ile
  • Akkermansia — 0.009 % of the microbiome or 35%ile
  • Bifidobacterium 0.016 % of the microbiome or 16%ile
  • Bacteroides – 27% of microbiome, or 64%ile

Additionally, two indicate increased risk of Candida (new feature just added)

  • Phocaeicola dorei at 10% of the microbiome or 91%ile
  • Faecalibacterium prausnitzii at 27% of the microbiome or 96%ile

I would suggest a test for candida to be safe. The data suggests a risk. If confirmed, candida would contribute significantly to gut dysbiosis [The interplay between gut bacteria and the yeast Candida albicans[2021]). I did a “back-flip” check of the top prescription items, and all of them reduces Candida (studies cited below).

Addendum – Predicted Symptoms

This was just added to the site today as a further refactor based on New Special Studies on Symptoms data. These are from [My Profile Tab]

Criteria11/18/20215/20/20226/22/20239/4/2023
Forecast Major SymptomsNeurological: Cognitive/Sensory Overload
40 % match on 25 taxa

DePaul University Fatigue Questionnaire : Racing heart
38 % match on 13 taxa

DePaul University Fatigue Questionnaire : Difficulty falling asleep
37 % match on 27 taxa

DePaul University Fatigue Questionnaire : Difficulty finding the right word
35 % match on 20 taxa
Autonomic Manifestations: urinary frequency dysfunction
66 % match on 6 taxa
Immune Manifestations: Bloating
37 % match on 45 taxa

Neurological-Audio: hypersensitivity to noise
35 % match on 28 taxa
NoneNeurological-Sleep: Chaotic diurnal sleep rhythms (Erratic Sleep)
50 % match on 18 taxa

Neurological: Spatial instability and disorientation
37 % match on 16 taxa

This can be helpful for judging possible severity (and potential improvement of some symptoms), for example: Neurological: Cognitive/Sensory Overload. See [Special Studies] tab.

  • 2021 – 40% matches
  • 2022- 24% matches
  • 6/22/23 – 16% matches
  • 9/4/2023 – 4% matches

Going Forward

COVID has had quite an impact on this microbiome. I am going to just go with the “Just Give Me Suggestions” option with the addition of what matched his diagnosis:

  • Irritable Bowel Syndrome  (68 %ile) 7 of 68

To explain a bit more. First I click the button below

And then click I could click the consensus report to see what the top items are:

Which are shown below.

In this case, I want to add Irritable Bowel Syndrome suggestions (on the Changing Microbiome Tab)

Instead of the usual 4 packages of suggestions, we have 5

When we look at the consensus report we see the same items there, but the values have increased.

The intent is put a little bias on the numbers towards specific conditions of greatest concern.

PDF Suggestions

I tend to favor the PDF suggestions because it simplifies things for many readers. Also the PDF gives a good list of citations (never complete) used to make the citations to persuade MDs to see that the suggestions are based on studies — a lot of studies.

The PDF suggestions are below (using the consensus view is another option for those more technically orientated). I clip from the PDF to keep the blog simpler for the typical reader.

This is a little longer list than usual, so I went to the consensus report to get priority data. Top value was 618, so 309 is the 50% threshold.

These appear to be of low influence with the exception of l.bulgaricus:

Minor note: quercetin with resveratrol is an avoid, quercetin is a take. resveratrol by itself is a negative (-113). At times, you need to look at the technical details/consensus to clarify things; the data we are using is incomplete and sparse…. If clearly contradictory suggestions appear, then don’t do them (thing an abundance of caution).

Because he has an antibiotic friendly MD, the following are the TOP antibiotics with notes:

CFS Antibiotics are also above the threshold. Since the prior sample had a strong Long COVID or ME/CFS Profile, I would be inclined to include one of those below in the antibiotic rotation. The microbiome cannot make a diagnosis of most things, with most ME/CFS microbiomes there is a particular pattern which you had in your last sample but which has disappeared from your current sample which looks more like your first sample. I read this as recovering from ME/CFS….  in likely a fragile state since relapse is very common with ME/CFS.

My own experience is that it is better to overcure ME/CFS and when there are signs of recovery…. no backflips of joy or running marathons; keep doing slow walks that becomes a bit further each week for 6-12 months. Your microbiome is fragile and can quickly slip back.

I prefer to use the strategy of going for prescription items that are both suggested from the microbiome and been shown to help with one or more of the diagnosis conditions. This usually encounter low resistance from physicians — they are clueless for the microbiome, but very accepting of published studies. An antibiotic that is used as a prophylaxis usually encounter little resistance.

KEGG Suggestions

This is done by using information from the bacteria found with some fudge factors. I am in discussion with some Ph.D. candidates to build this concept directly from the FASTQ files and will hopefully have this as an added feature next year.

The KEGG probiotics is the usual pattern for ME/CFS and Long COVID with the top one being the usual, with the top reasonably available ones for other families shown below. I usually like to compare the values with those from consensus to minimum risk (i.e. two thumbs up, we do; mixed, we skipped)

KEGG Supplements

From the list, we will look only at those with a z-score (statistical significance) over 2. After each we put the consensus value (if it is listed)

Only two items are with high confidence.

How to Proceed Suggestions

The suggestions should be thought as influencers. The human population is often a good analogy or parable for the microbiome population. Each influencer shifts the population in the desired direction. Based on Cecile Jadin’s work and several studies, I am a firm believer in short duration (1-2 weeks) of each influencers. Just as with human influencers, people stop listening if the same person just keeps droning on and on. If a different person starts speaking, you get persuaded more. If a mob start to shout, yet a different human behavior will occur. In terms of the microbiome, “stop listening” means mutations that are resistant to the item will start to increase. Items line vitamins and minerals can be taken continuously; items that are likely to have bacteria resistance developed should be taken for a week and then another item replace it.

The items to rotate:

  • Antibiotics listed above
  • Probiotics: lactobacillus salivarius and lactobacillus bulgaricus
  • Herbs and spices: cinnamon, ginger, black cumin, thyme, rosemary, quercetin (suggests just before each antibiotic with a few days of overlap because it has potential synergistic activity with antibiotics [2020], [2016],[2018] )

Remember our goal is to destabilize a stable microbiome dysfunction.

Questions and Answers

While there has not been significant changes in many of the vectors between this sample and the prior sample from a few months earlier, there has been two significant objective changes:

  • Significant improvement of Anti inflammatory Bacteria Score (higher) and Histamine Producers (Lower).
  • The lost of the ME/CFS – Long COVID spike in the 0-9%ile

Q: Do you/should I use the colored list now instead of the consensus list?

  • Either are fine, the color list (from PDF) is what I tend to use in post because it is easier for new readers to understand (and automatically sent on new uploads). The consensus page is more complex but allows people to apply their own logic and priorities.

Q: “Quercetin (suggests just before each antibiotic with a few days of overlap because it has potential synergistic activity with antibiotics”

Q: I just did Mutaflor for 8 days and felt really tired all the time (but in the end I also got a flu/cold, so maybe that was the reason and not mutaflor). Nevertheless, if it was a herx reaction, I wonder if I should have taken it for longer until the reaction disappeared? (I stopped it 4 days ago.) Not sure if this question even makes sense.

  • My personal choice would be to keep taking it for at least a week (perhaps 2). Remember that the traditional pattern for a herx is feeling bad for X hours and then things get better. The duration of the feeling bad usually decrease from day to day. Catching a cold makes interpretation challenging.

Postscript – and Reminder

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

I can compute items to take, those computations do not provide information on rotations etc.

I cannot tell people what they should take or not take. I can inform people items that have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.

The answers above describe my logic and thinking and is not intended to give advice to this person or any one. Always review with your knowledgeable medical professional.

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