Multiple Chemical Sensitivity (MCS) – A Cause Found?

Time to Refresh What we know

A reader request with severe MCS motivated me to revisit Multiple Chemical Sensitivity (MCS) and literature on it. I am first going to recap my memory of what I know, a literature review, Last, analysis using data contributed to Microbiome Prescription – which did not find anything major beyond bacteria shifts that are statistically significant. We explore enzymes, products and substrates with no smoking guns found

There was a processing error — This post was revised

Long weekend tracing issue, made short. Some revisions to reduce running cost had a typo pointing one set of data (Substrate data for Samples) to the wrong lookup table to determine percentile. This has been corrected and the data audited to insure correctness.

I had mild MCS during one flare. It disappeared with remission.

Multiple Chemical Sensitivity (MCS) is not bronchial (breathing). There was a series of studies where the person was wearing a half-face mask breathing compressed air. Bringing a triggered close to the person (blind testing), trigger the response. My own wife lab results leaves a significant scent. She had a complete workup with Dave Berg, Hemex Lab and two weeks later she had a bad MCS reaction. About a week later, new blood work was sent. Everything was the same, except for a marker indicating very active coagulation. The marker had a short half-life around 2 hours. After she fully recovered, same test returned to normal. This hints at coagulation being part of the process.
We did find one effective treatment for shortening the duration of a MCS episode: Olestra (as in Olestra chips). This compound sucks chemicals out of tissues [2015] [2014]

– Ken Lassesen

I attended a talk today with the AAAS (I’m a member) and Memory Cells was discuss for some autoimmune conditions. It occurs to me that these are likely a factor. These cells become uber-sensitive to specific chemical compounds and have a lasting memory. In time they may die off, but not quickly.

Caution: this post is subject to revision. The findings to date are so significant that I am posting early.

The Current Literature

First a summary from a 2022 review – it covers a lot of territory… many quotes are below

Multiple Chemical Sensitivity (MCS), a condition also known as Chemical Sensitivity (CS), Chemical Intolerance (CI), Idiopathic Environmental Illness (IEI) and Toxicant Induced Loss of Tolerance (TILT), is an acquired multifactorial syndrome characterized by a recurrent set of debilitating symptoms. The symptoms of this controversial disorder are reported to be induced by environmental chemicals at doses far below those usually harmful to most persons. They involve a large spectrum of organ systems and typically disappear when the environmental chemicals are removed. However, no clear link has emerged among self-reported MCS symptoms and widely accepted objective measures of physiological dysfunction, and no clear dose-response relationship between exposure and symptom reactions has been observed. In addition, the underlying etiology and pathogenic processes of the disorder remain unknown and disputed, although biologic and psychologic hypotheses abound. It is currently debated whether MCS should be considered a clinical entity at all.

Multiple Chemical Sensitivity [2022]
  • “Not surprising, MCS is often juxtaposed to, and sometimes combined with, other diseases for which definitive diagnoses and explanations are also found wanting, including fibromyalgia (FM), Gulf War syndrome (GWS), chronic fatigue syndrome (CFS), sick building syndrome (SBS), and electromagnetic radiation exposure (ERE) [18,23,24,25,26,27,28,29,30,31,32].”
  • “An association was documented, however, between MCS and increased nasal airflow resistance, respiration rate, and heart rate.” [2021] Volatile chemicals can not only affect respiration, but can cause laryngeal symptoms which, in the extreme, can induce vocal cord dysfunction [82]. 
  • Changes in skin conductance were also seen in MCS patients but not in controls [193].
  • Compared to younger persons, those 65 years of age and older are less likely to identify themselves as chemically sensitive [88].
  • In accord with this concept, McKeown-Eyssen et al. [219] found, in a female cohort of 203 MCS cases and 162 controls, that the cases had higher levels of cytochrome P450 CYP2D6 (i.e., one of the most important enzymes involved in the metabolism of xenobiotics in the body) and n-acetyl transferase 2 (NAT2). More possible genes listed here.
  • Like the sick building syndrome [89], there is a remarkably higher prevalence in women than in men [16,18,21,90,91], with the percentage of women ranging from 60% to 88% [18,57,92,93,94]. 
Multiple Chemical Sensitivity – there may be many roads and also subsets

Microbiome and MCS

Almost every condition in the above chart has microbiome shifts associated with it. Exposure to mold also is known to cause microbiome shifts. There appears to be no published studies exploring this possibility. At this time we have 128 people (7.3%) who have annotated their samples with Multiple Chemical Sensitivity [uBiome: 55, Ombre:39, Biomesight 25] to Microbiome Prescription.A

Executing analysis by lab, we found only one taxon reported significant in two labs. Bacteroides clarus where people with MCS had 3x the count of people not reporting MCS [BiomeSight, uBiome]. The top items of significance are shown below. All of them have much higher counts in people with MCS.

SourceprobabilityTax_Nametax_rankwith MCSwithout
BiomeSightP < 0.001Anaerotruncusgenus33561834683
BiomeSightP < 0.001Anaerotruncus colihominisspecies32081743683
BiomeSightP < 0.001Bacteroides intestinalisspecies289802430396
ThryveP < 0.001Prevotella maculosaspecies273995733404
Average Counts out of a million

These have been added to the [Research] tab, as shown below.

Looking at KEGG Enzymes we have the strongest candidates below. Looking for any enzyme that is significant for 2 or more labs, we had only one: D-lyxose aldose-ketose-isomerase (Biomesight and Thryve).

7alpha-hydroxysteroid:NAD+ 7-oxidoreductase1.1.1.159BiomeSight1468124794.01657
acetyl-CoA:glycerone phosphate C-acetyltransferase2.3.1.245BiomeSight49551274443.56701
acetyl-CoA:heparan-alpha-D-glucosaminide N-acetyltransferase2.3.1.78BiomeSight2690993944.02671
alginate beta-D-mannuronate—uronate lyase4.2.2.3BiomeSight2693394724.02681
CTP:phosphoglutamine cytidylyltransferase2.7.7.103BiomeSight27471131563.97702
L-alanine:glyoxylate aminotransferase2.6.1.44uBiome1608320293.40309
NAD+:glycine ADP-D-ribosyltransferase (sulfide-adding)
phosphoenolpyruvate:glycerone phosphotransferase2.7.1.121BiomeSight68289418083.60702
sn-glycerol-1-phosphate:NAD(P)+ 2-oxidoreductase1.1.1.261BiomeSight29070114403.55700
Probability of being random is P < 0.001

Dropping by Lab and using Percentiles Only

Trying a different approach aggregating all of the data and using percentile ranking. This masks most of the differences between labs and gives us large sample size, We have a very actionable item: increase Bifidobacterium by taking Bifidobacterium probiotics.

Alistipes indistinctusspecies61.761
Anaerobutyricum halliispecies39.841
Oscillospiraceae incertae sedisnorank63.141
Butyricimonas faecihominisspecies61.243
Collinsella aerofaciensspecies39.183
Phascolarctobacterium succinatutensspecies37.352
Bacteria where Percentile Average above 60%ile or below 40%ile

KEGG Enzymes

Applying this to KEGG Enzymes, we have just one of concern that is high: EC3.2.1.46  galactosylceramidase, and a big 39 that are low indicating a deficiency of enzymes is likely

[] ATP:cellobiose 6-phosphotransferase34.664
[] phosphate:oxaloacetate carboxy-lyase (adding phosphate, phosphoenolpyruvate-forming)35.2122
[] 6-sulfo-alpha-D-quinovosyl diacylglycerol 6-sulfo-D-quinovohydrolase36.161
[] nicotinate:cytochrome 6-oxidoreductase (hydroxylating)36.763
[] N-succinyl-LL-2,6-diaminoheptanedioate amidohydrolase37.9122
[] protein-Npi-phospho-L-histidine:sucrose Npi-phosphotransferase38122
[] 4-(gamma-L-glutamylamino)butanal:NAD(P)+ oxidoreductase38.163
[] formate:[oxidized hydrogenase] oxidoreductase38.3121
[] protein-Npi-phospho-L-histidine:2-O-alpha-mannopyranosyl-D-glycerate Npi-phosphotransferase38.494
[] pyridoxine:NADP+ 4-oxidoreductase38.498
[] S-adenosyl-L-methionine:16S rRNA (guanine1207-N2)-methyltransferase38.5120
[] S-adenosyl-L-methionine:23S rRNA (guanine2069-N7)-methyltransferase38.6121
[] N-benzoylamino-acid amidohydrolase38.763
[] UDP-alpha-D-glucose:alpha-D-galactose-1-phosphate uridylyltransferase38.7122
[] ADP-alpha-D-glucose:alpha-D-glucose-1-phosphate 4-alpha-D-glucosyltransferase (configuration-retaining)38.9121
[] D-fructose-6-phosphate D-erythrose-4-phosphate-lyase (adding phosphate; acetyl-phosphate-forming)39122
[] D-xylulose-5-phosphate D-glyceraldehyde-3-phosphate-lyase (adding phosphate; acetyl-phosphate-forming)39122
[] alpha-maltose-6′-phosphate 6-phosphoglucohydrolase39122
[] xylitol:NAD+ 2-oxidoreductase (D-xylulose-forming)39.183
[] D-aspartate:[beta-GlcNAc-(1->4)-Mur2Ac(oyl-L-Ala-gamma-D-Glu-L-Lys-D-Ala-D-Ala)]n ligase (ADP-forming)39.2122
[] D-tagatose 1,6-bisphosphate D-glyceraldehyde-3-phosphate-lyase (glycerone-phosphate-forming)39.2122
[] cobalt-precorrin 5A acylhydrolase39.2122
[] (2S,3S)-2,3-dihydro-2,3-dihydroxybenzoate:NAD+ oxidoreductase39.273
[] D-galactose-6-phosphate aldose-ketose-isomerase39.3115
[] ATP:D-ribulose-5-phosphate 1-phosphotransferase39.462
[] protein-Npi-phospho-L-histidine:maltose Npi-phosphotransferase39.4122
[] protein-Npi-phospho-L-histidine:lactose Npi-phosphotransferase39.4118
[] beta-L-arabinofuranoside non-reducing end beta-L-arabinofuranosidase39.472
[] 3-dehydro-L-gulonate:NAD(P)+ 2-oxidoreductase39.572
[] 6-phospho-beta-D-galactoside 6-phosphogalactohydrolase39.5117
[] amino-acid racemase39.7108
[] oligosaccharide 6-alpha-glucohydrolase39.7122
[] uronate:NAD+ 1-oxidoreductase39.761
[] 5-oxo-L-proline amidohydrolase (ATP-hydrolysing)39.7120
[] protein-Npi-phospho-L-histidine:D-mannose Npi-phosphotransferase39.8122
[] glycerol hydro-lyase (3-hydroxypropanal-forming)39.864
[] Carboxypeptidase Taq39.9122
[] ATP:(S)-4,5-dihydroxypentane-2,3-dione 5-phosphotransferase39.972
[] D-galactosyl-N-acylsphingosine galactohydrolase63.365
Enzymes where Percentile Average above 60%ile or below 40%ile

Compound Produced

This is reflected in compound produced. With D-Galactose being the only high – matching enzyme [] D-galactosyl-N-acylsphingosine galactohydrolase above,

22336Reduced hydrogenase38.3121
1113D-Galactose 6-phosphate39.2118
615Protein histidine39.6122
1097D-Tagatose 6-phosphate39.8115

Compounds Consumed

As above for production and for bacteria, we have just one item with a high percentile and many with a low percentile.

Hydrogen selenide39.9122
Reduced riboflavin39.850
Protein N(pi)-phospho-L-histidine39.6122
[SoxY protein]-S-disulfanyl-L-cysteine39.643
alpha-D-Galactose 1-phosphate39.4122
D-Galactose 6-phosphate39.3115
D-Xylulose 5-phosphate39.1122
Oxidized hydrogenase38.3121
Hexadecenoyl-[acyl-carrier protein]37.247
Protein lysine37.1120

Bottom Line

The is no obvious imbalance between compounds produced and consumed. Thus the best path is to use the bacteria identified at the start. A quick select has been added to the menus.

  • There are a few things that could be factors, for example D-Galactaro-1,4-lactone is 33.3%ile for consumption and 39.9%ile for production. Unfortunately, the microbiome is not a closed system and whether any surplus accumulates would be too speculative.
Example of the MCS pick page for a person with MCS.

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