In reviewing many papers with the microbiome I noticed that often the researchers restrict their examinations to the taxa that is reported in all samples. I suspect this is due to a lack of sufficient statistical training and/or not understanding the natures of the microbiome.

Recently I came across these papers that uses an approach that I often have used, working off relative frequency of detection a.k.a. prevalence.

• A predictive index for health status using species-level gut microbiome profiling [2020]
• Gut Microbiome Wellness Index 2 for Enhanced Health Status Prediction from Gut Microbiome Taxonomic Profiles [2023]
• GMWI-webtool: a user-friendly browser application for assessing health through metagenomic gut microbiome profiling [2023]

This post is going to use samples available at Microbiome Prescription Citizen Science site. We are going to restrict to one lab source and divide the data into two groups based on their self-declare symptoms and diagnosis.

• Patients with Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) declared [Obs: 271]
• Patients without Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) declared and other status declared (for example: “Asymptomatic” [Obs:569]

Naive First Pass

We are going to take the average count for each group ignoring no values reported. We are going to restrict it to taxa where we have at least 30 non-zero values [1,564 taxa]. We found some 77 taxa with a t-score over 2.81 (p < 0.005)

taxa name	taxa rank	Shift	T_score
Prevotella copri	species	low in ME/CFS	-5.27
Prevotella	genus	low in ME/CFS	-4.52
Sporolactobacillaceae	family	low in ME/CFS	-4.2
Sporolactobacillus putidus	species	low in ME/CFS	-4.19
Sporolactobacillus	genus	low in ME/CFS	-4.19
Prevotellaceae	family	low in ME/CFS	-4.1
Firmicutes	phylum	high in ME/CFS	3.94
Blautia	genus	high in ME/CFS	3.91
Cetobacterium ceti	species	high in ME/CFS	3.89
Cetobacterium	genus	high in ME/CFS	3.84

Deeming Not Reported to be Zero

In this case we have 78 taxa with a t-score over 2.81 with slight changes of t-scores.

taxa name	taxa rank	Shift	T_score
Prevotella copri	species	low in ME/CFS	-5.31
Sporolactobacillaceae	family	low in ME/CFS	-4.63
Sporolactobacillus putidus	species	low in ME/CFS	-4.62
Sporolactobacillus	genus	low in ME/CFS	-4.62
Prevotella	genus	low in ME/CFS	-4.5
Prevotella oulorum	species	low in ME/CFS	-4.35
Prevotellaceae	family	low in ME/CFS	-4.08
Bifidobacterium gallicum	species	low in ME/CFS	-3.97
Firmicutes	phylum	high in ME/CFS	3.94
Blautia	genus	high in ME/CFS	3.91

Prevalence

We followed the same process as above and limited things to a Chi-2 probability of < 0.005 (as used above) We ended up with 65 taxa.

Comparing these two lists, we found only 6 taxa in common

• Bifidobacterium angulatum
• Propionigenium modestum
• Pseudomonas viridiflava
• Cetobacterium ceti
• Cetobacterium
• Propionigenium

The next result is that we have 78+65 – 6 = 137 statistically significant bacteria with p < 0.005.

Bottom Line

There are at least two different statistical ways of determining significance. IMHO, the prevalence approach is likely to be a superior tool for diagnosis purposes because it is possible to compute the probability of a match to the above patterns despite some bacteria not being reported.

The full list of bacteria is listed here.