Light Sensitivity Exploration

This morning I got this email:

My daughter’s light sensitivity is now so bad, she’s screaming in pain at daylight  and won’t let her flatmate put up the blinds! Of course it’s related to her autism. Now we’ve uploaded her new sample, is there anything implicated in her current dysbiosis that might lessen this?
She is tormented by this..

I believe we just have enough data to get some traction. I will first use the new Odds Ratio because it give an objective measurement of the importance of each bacteria. Second, I will use the older methodology to simply get a second opinion of which bacteria (unfortunately, this does not indicate importance of each bacteria).

There are three symptom choices related. The difference in count is a reflection of when the symptom was added (the earliest one had the highest count).

  • Neurological-Vision: photophobia (Light Sensitivity) 431 samples
  • DePaul University Fatigue Questionnaire : Abnormal sensitivity to light 259 samples
  • Other:Light sensitivity (photophobia) 5

The sample above was done using biomesight and we have 148 different bacteria using Odds that are statistically significant for increasing or reducing the odds.

The Odds of her having light sensitivity is quite high: log(Odds)=11.8,

These notes document ongoing work on this issue. The goal is both to address her request and to deepen our understanding of how the MP classic method compares to the newer Odds Ratio approach. The MP classic method has produced good results so far, and Odds Ratios may further improve them. For details on how Odds Ratios are calculated, see this related post: Odds Ratio for the Microbiome 101.

In subsequent posts I will look at two symptoms that are very often seen with light sensisitivy:

  • Multiple Chemical Sensitivity
  • Mast Cell Activation Syndrome

Comparison of “MP Classic” and Odds Ratio Algorithms

Across all symptoms, using Biomesight data, we see consistent patterns in which bacterial levels are involved. The Odds Ratio analysis focuses on more specific bacterial taxa and is therefore more targeted. For example, instead of simply indicating low Lactobacillus, the Odds Ratio can highlight a particular species such as Lactobacillus reuteri. This higher resolution enables more precise selection of probiotics.

Taxonomy RankMP ClassicOdds Ratio
Species172713541
Genus513010040
Family84636158
Order58603269
Class36631437

Overview of all Samples

The list of bacteria that DOUBLES or more the odds when present in larger amounts

BacteriaRankOdds Ratio
Salidesulfovibriogenus5.9
Salidesulfovibrio brasiliensisspecies5.9
Ethanoligenensgenus4.9
Peptoniphilus lacrimalisspecies4.3
Slackia faecicanisspecies4.2
Collinsella tanakaeispecies3.8
Finegoldia magnaspecies3.5
Viviparoideasuperfamily3.5
Architaenioglossaorder3.5
Rivulariagenus3.5
Viviparidaefamily3.5
Rivularia atraspecies3.5
Rivulariagenus3.5
Finegoldiagenus3.4
Lysobactergenus3.4
Desulfovibrio fairfieldensisspecies3.3
Aerococcaceaefamily3.3
Anaerococcusgenus3.2
Streptococcus anginosusspecies3.1
Luteolibactergenus3
Luteolibacter algaespecies3
Anaerotruncus colihominisspecies3
Odoribacter denticanisspecies3
Filifactorgenus2.8
Lactobacillus gallinarumspecies2.8
Peptoniphilus asaccharolyticusspecies2.8
Selenomonas infelixspecies2.7
Corynebacterium striatumspecies2.7
Adlercreutzia equolifaciensspecies2.6
Streptococcus anginosus groupspecies group2.6
Glutamicibacter solispecies2.6
Anaerotruncusgenus2.5
Rubritaleaceaefamily2.5
Rubritaleagenus2.5
Gardnerellagenus2.4
Oscillatorialesorder2.3
Amedibacillus dolichusspecies2.3
Amedibacillusgenus2.3
Glutamicibactergenus2.2
Anaerococcus prevotiispecies2.2
Azospirillum palatumspecies2.2
Eggerthella sinensisspecies2.2
Sphingomonas abacispecies2.2
Alcanivoraxgenus2.1
Alcanivoracaceaefamily2.1
Haploplasmagenus2.1
Haploplasma cavigenitaliumspecies2.1
Isoalcanivoraxgenus2.1
Isoalcanivorax indicusspecies2.1
Oscillatoriaceaefamily2.1
Selenomonadalesorder2.1
Nisaea nitritireducensspecies2.1
Anaerococcus tetradiusspecies2.1
Selenomonadaceaefamily2.1
Lactobacillus acidophilusspecies2.1
Anaerococcus lactolyticusspecies2.1

On the other end, the bacteria that reduces the odds when present in higher amounts are:

Propionibacterialesorder0.1
Dyadobactergenus0.3
Herbaspirillum magnetovibriospecies0.3
Calditrichiaclass0.4
Calditrichalesorder0.4
Calditrichaceaefamily0.4
Caldithrixgenus0.4
Calditrichotaphylum0.4
Desulfitobacteriaceaefamily0.4
Bifidobacterium adolescentisspecies0.4
Bifidobacterium longumspecies0.4

In terms of probiotics, we see some quick observations: good and bad.

  • Two Lactobacillus probiotics significantly increases the odds — i.e. AVOID, especially yogurts!
  • Two Bifidobacterium species (and the genus as a whole) significantly decreases the odds — TAKE A LARGER DOSAGE.

Looking at this specific sample

We found no lactobacillus at all, and Bifidobacterium adolescentis is too low. Bifidobacterium longum was found but the amount was significant for reducing the risk.

Getting best probiotics via modelling

This is done using the Correlation Coefficient between bacteria from the R2 site (using the lab specific numbers). We focused solely on the bacteria that increased the odds significantly, and then compute the probiotics (based on only the species what Biomesight reports) that will shift them in the right direction.

Tax_nameImpact
Pediococcus acidilactici4.28
Bacillus amyloliquefaciens group3.89
Limosilactobacillus vaginalis2.95
Bifidobacterium2.5
Enterococcus faecalis1.73
Bifidobacterium pseudocatenulatum1.6
Leuconostoc mesenteroides1.6
Heyndrickxia coagulans (bacillus coagulans)1.53
Bifidobacterium longum1.49
Clostridium butyricum1.46
Lacticaseibacillus paracasei1.35
Lactococcus lactis1.33
Bifidobacterium breve1.28
Lactobacillus helveticus1.27
Enterococcus faecium1.24
Bacillus subtilis group1.16
Lactiplantibacillus plantarum1.08
Bifidobacterium bifidum0.96
Bifidobacterium adolescentis0.84

Taking these same bacteria using the odds ratios and our usual suggestions engine, we get the following as the top suggestions.

ModifierNetTakeAvoid
Slow digestible carbohydrates. {Low Glycemic}375216
dietary fiber294516
Fiber, total dietary243814
fruit223412
fruit/legume fibre203212
(2->1)-beta-D-fructofuranan {Inulin}20233
High-fibre diet {Whole food diet}193213
oligosaccharides {oligosaccharides}19266
whole-grain diet18257
Lactobacillus plantarum {L. plantarum}172912
bifidobacterium15161
wheat12142

The Avoids. I noticed that Bofutsushosan is an avoid. This is a promoter of Akkermansia — which was on our avoid probiotics list. There appears to be reasonable consistency although we are using two different sources and mechanism to get these suggestions.

ModifierNetTakeAvoid
high-fat diets-8311
Ganoderma sichuanense {Reishi Mushroom}-516
Pulvis ledebouriellae compositae {Bofutsushosan}-405
2-aminoacetic acid {glycine}-404
Bacteriophages LH01,T4D,LL12,LL5 {PreforPro}-404
laminaria hyperborea {Cuvie}-404
low protein diet-416
D-glucose {Glucose}-416
Ferrum {Iron Supplements}-415
Ulmus rubra {slippery elm}-426
Honey {Honey }-426

Going Old School Suggestions

This is done the usual way but we temporarily clear all of the symptoms and then just marked this single symptom. We are wanting to focus solely on this one horrible symptom.

Clicking on this one symptom, we then get 10 bacteria associated

And also suggestions. I note some agreements between the methods:

  • Avoids: Honey, Ganoderma sichuanense {Reishi Mushroom},laminaria hyperborea {Cuvie}, etc
  • Takes: whole-grain diet, oligosaccharides
  • Disagreement: Bifidobacterium Longum – this gets interesting because the Odds Ratio indicate that the amount of Bifidobacterium Longum present was sufficient to reduce the odds to below 1.0

Summary

I generally favor a consensus of recommendations as the safest course. In this case, my impression is that using Odds Ratios leads to better identification of the bacteria involved (10 versus 24 for this sample), with the added benefit of indicating the relative importance of each bacterium. With Odds Ratios, the thresholds for being too high or too low are symptom-specific, rather than some magical universal cutoff that applies to all conditions.

Believing that there is one magic reference range for any bacteria is simply naive and ignoring the data.

I need to do some more refining of the code as well as enhancement to handle multiple symptoms concurrently; in time, this will be added to the sight.

Using Odds Ratio is now available on the site. The video below shows how to access it.

Technical Notes

Doing a low level comparison between the “classic forecast method” and the “Odds Ratio method I generated the table below. The Odds Ratio identified bacteria at a much more at a finer level (species) and most people would interpret that as being more targeted and likely better outcomes.

MeasureClassicOdds Ratio
Bacteria Considered115148
Bacteria in common2020
Species857
Genus2251
Family3321
Order2310
Class143

This also implies that only Genus and Species should be considered with Odds Ratio. Statistically this is preferred to reduce the amount of double counting.

Revisiting Suggestions using only Genus and Species with Odds Ratio

The R2 Probiotics are similar. Most probiotics are more challenging to obtain — see this page for known sources. The avoids are:

  • Lactobacillus johnsonii
  • Akkermansia muciniphila
  • Bacillus subtilis

Note: Pediococcus acidilactici and L.Plantarum (positive) mixtures is likely the easiest to obtain.

Tax_nameImpactPossible Source
Pediococcus acidilactici4.28Imagilin / NutriLots
Bacillus amyloliquefaciens group3.1only in big mixtures 🙁
Limosilactobacillus vaginalis1.79n/a
Bifidobacterium pseudocatenulatum1.6only in big mixtures 🙁
Leuconostoc mesenteroides1.6Bulk Probiotics / Leuconostoc Mesenteroides Probiotic Powder
Clostridium butyricum1.46Many sources
Lacticaseibacillus paracasei1.35danactive drink and many others
Lactococcus lactis1.33Bulk Probiotics / Lactococcus Lactis Probiotic Powder 
Bifidobacterium1.04

The To Take List

ModifierNetTakeAvoid
Slow digestible carbohydrates. {Low Glycemic}344712
dietary fiber294011
Fiber, total dietary233511
fruit203010
oligosaccharides {oligosaccharides}20244
High-fibre diet {Whole food diet}192910
fruit/legume fibre19289
whole-grain diet18245
(2->1)-beta-D-fructofuranan {Inulin}17181
bifidobacterium12120
Lactobacillus plantarum {L. plantarum}112211
wheat11121
3,3′,4′,5,7-pentahydroxyflavone {Quercetin}10111
Bovine Milk Products {Dairy}9134
Human milk oligosaccharides (prebiotic, Holigos, Stachyose)9101
polyphenols8124

The To Avoid List

high-fat diets-617
Honey {Honey }-516
Pulvis ledebouriellae compositae {Bofutsushosan}-405
2-aminoacetic acid {glycine}-404
laminaria hyperborea {Cuvie}-404
Vaccinium myrtillus {Bilberry}-404
D-glucose {Glucose}-416
Sodium Chloride {Salt}-415
Ferrum {Iron Supplements}-415
Ulmus rubra {slippery elm}-426
2-Amino-5-(carbamoylamino)pentanoic acid {Citrulline}-303
Lactotransferrin {Lactoferrin}-303
Sus domesticus {Pork}-303
Ganoderma sichuanense {Reishi Mushroom}-314
low protein diet-313
Theobroma cacao {Cacao}-325

Leave a Reply