This document presents the results of statistical analysis on symptoms from viable, self-annotated Biomesight microbiome samples. The methodology for data acquisition is outlined in New Standards for Microbiome Analysis?.​

Tables have been refined to display only genus- and species-level taxa, the 20 most prominent entries per group, and associations achieving statistical significance (P < 0.01).​

The following sections provide the processed data, accompanied by guidance on interpretation and application. Counts of significant bacterial taxa are included, reflecting the application of non-standard but rigorously validated statistical approaches to extensive sample and reference populations, where statistical power derives from dataset scale.

Significance	Genus
p < 0.01	135
p < 0.001	100
p < 0.0001	83
p < 0.00001	69

Averages and Medians

I prefer medians over averages. Medians are the values where half of the people have less and half has more. If the data was a bell-curve, then the values will almost be the same… with bacteria that happens rarely. Look at Bacteroides uniformis below, we see that the average is above and the median below.

If symptom median is higher than reference median, it means there is more of this bacteria. If lower, then less. This ignores how often the bacteria is seen (we average only over reports).

tax_name	Rank	Symptom Avarage	Reference Average	Symptom Median	Reference Median
Bacteroides	genus	27.303	25.835	24.008	26.554
Bacteroides uniformis	species	3.026	2.68	1.498	2.016
Phocaeicola dorei	species	3.35	2.83	0.379	0.672
Coprococcus	genus	1.354	1.444	0.739	0.612
Bifidobacterium	genus	0.698	0.975	0.136	0.064
Bacteroides cellulosilyticus	species	0.883	0.849	0.07	0.138
Bilophila	genus	0.41	0.34	0.206	0.25
Bacteroides rodentium	species	0.416	0.387	0.179	0.221
Bilophila wadsworthia	species	0.4	0.331	0.197	0.235
Bifidobacterium longum	species	0.244	0.336	0.052	0.03
Anaerotruncus	genus	0.197	0.185	0.136	0.156
Anaerotruncus colihominis	species	0.187	0.173	0.132	0.15
Collinsella	genus	0.146	0.189	0.057	0.042
Collinsella aerofaciens	species	0.139	0.176	0.054	0.042
Anaerobranca zavarzinii	species	0.14	0.159	0.015	0.009
Anaerobranca	genus	0.14	0.159	0.015	0.009
Bifidobacterium adolescentis	species	0.281	0.305	0.013	0.007
Oxalobacter	genus	0.033	0.03	0.018	0.023
Bifidobacterium choerinum	species	0.037	0.052	0.012	0.007
Acholeplasma hippikon	species	0.051	0.042	0.006	0.01

Bacteria Incidence – How often is it reported

The common sense belief is that if a bacteria is reported more often, then the amount should be higher. This is often not true. The microbiome is a complex thing. Look at Bacteroides uniformis below, we see that the average is above and the median below

tax_name	Rank	Incidence Odds Ratio	Chi2	Symptoms %	Reference %
Aggregatibacter	genus	0.75	7.4	18.5	24.7
Prevotella bivia	species	1.29	6.6	24.4	19
Bifidobacterium scardovii	species	0.71	7.1	12.4	17.3

More or Less often based on Symptom Median All Incidence

This is a little more complex to understand. If we compute the mid point for people with the symptom, then if the bacteria was not involved then half of the reference should be above this value and half below this value. If not, it means that the symptom tends to over or under growth.

tax_name	Rank	Symptom Median	Odds Ratio	Chi2	Below	Above
Psychrobacter glacialis	species	0.002	0.37	81	584	215
Chromatium	genus	0.002	0.38	69.5	466	175
Chromatium weissei	species	0.002	0.38	69.2	465	175
Niabella	genus	0.002	0.4	65.2	500	199
Actinopolyspora	genus	0.002	0.4	64.4	482	191
Thiorhodococcus	genus	0.002	0.43	57.4	516	221
Syntrophomonas sapovorans	species	0.002	0.43	55.9	477	203
Thermodesulfovibrio thiophilus	species	0.002	0.44	52.9	480	210
Thermodesulfovibrio	genus	0.002	0.46	50.9	554	255
Oenococcus	genus	0.002	0.46	50.7	528	241
Helicobacter suncus	species	0.002	0.49	46.3	656	324
Desulfofundulus	genus	0.002	0.47	41.9	434	206
Caldithrix	genus	0.002	0.52	36.7	541	282
Desulfotomaculum defluvii	species	0.003	0.56	36.2	906	508
Viridibacillus	genus	0.002	0.52	33.7	430	222
Streptococcus infantis	species	0.003	0.56	33.2	707	396
Sporotomaculum syntrophicum	species	0.003	0.58	32.4	996	582
Alkalibacterium	genus	0.003	0.58	31.6	792	456
Hydrogenophilus	genus	0.003	0.59	31.6	994	585
Pelagicoccus	genus	0.002	0.58	30.7	750	433

More or Less often based on Reference Median All Incidence

This is like the above, but with a different line in the sand. Instead of the median of those with the condition, we use the median of the reference set.

tax_name	Rank	Reference Median	Odds Ratio	Chi2	Below	Above
Psychrobacter glacialis	species	0.002	0.37	141.3	584	215
Bacteroides heparinolyticus	species	0.003	0.49	114	849	412
Chromatium	genus	0.002	0.38	113.2	466	175
Chromatium weissei	species	0.002	0.38	112.6	465	175
Odoribacter denticanis	species	0.005	0.56	110.5	1455	822
Niabella	genus	0.002	0.4	109.6	500	199
Actinopolyspora	genus	0.002	0.4	107	482	191
Thiorhodococcus	genus	0.002	0.43	99	516	221
Syntrophomonas sapovorans	species	0.002	0.43	93.7	477	203
Thermodesulfovibrio	genus	0.002	0.46	91.2	554	255
Helicobacter suncus	species	0.002	0.49	89.5	656	324
Thermodesulfovibrio thiophilus	species	0.002	0.44	89.5	480	210
Oenococcus	genus	0.002	0.46	89.2	528	241
Desulfotomaculum defluvii	species	0.003	0.56	81.7	906	508
Sporotomaculum syntrophicum	species	0.003	0.58	76.8	996	582
Hydrogenophilus	genus	0.003	0.59	74.9	994	585
Desulfosporosinus	genus	0.0025	1.67	71.5	600	1004
Clostridium taeniosporum	species	0.003	0.62	70.1	1184	734
Desulfofundulus	genus	0.002	0.47	69.5	434	206
Alkalibacterium	genus	0.003	0.58	68.1	792	456

More or Less often based on Symptom Median High Incidence

Above we see that many of the top bacteria identified are sparse, that is not reported often. We then restrict them to those that occur above 50% or the time.

tax_name	Rank	Symptom Median Freq	Odds Ratio	Chi2	Below	Above
Clostridium taeniosporum	species	0.003	0.62	27.2	1184	734
Mycoplasmopsis edwardii	species	0.005	0.67	21.1	1580	1053
Dethiosulfovibrio	genus	0.004	0.67	20	1335	893
Tetragenococcus doogicus	species	0.003	0.67	18.8	1206	813
Hydrocarboniphaga daqingensis	species	0.004	0.72	13.8	1422	1022
Mycoplasmopsis	genus	0.005	0.74	12	1550	1142
Pediococcus	genus	0.004	0.75	10	1141	855
Tetragenococcus	genus	0.003	0.76	9.2	1183	899
Propionispora hippei	species	0.005	0.77	8.5	1348	1039
Propionispora	genus	0.005	0.77	8.5	1348	1039
Phocaeicola coprocola	species	0.004	0.78	7.2	1068	836
Porphyromonas canis	species	0.005	0.8	6.6	1382	1100

More or Less often based on Reference Median High Incidence

Above we see that many of the top bacteria identified are sparse, that is not reported often. We then restrict them to those that occur above 50% or the time.

tax_name	Rank	Reference Median Freq	Odds Ratio	Chi2	Below	Above
Psychrobacter glacialis	species	0.002	0.37	141.3	584	215
Bacteroides heparinolyticus	species	0.003	0.49	114	849	412
Chromatium	genus	0.002	0.38	113.2	466	175
Chromatium weissei	species	0.002	0.38	112.6	465	175
Odoribacter denticanis	species	0.005	0.56	110.5	1455	822
Niabella	genus	0.002	0.4	109.6	500	199
Actinopolyspora	genus	0.002	0.4	107	482	191
Thiorhodococcus	genus	0.002	0.43	99	516	221
Syntrophomonas sapovorans	species	0.002	0.43	93.7	477	203
Thermodesulfovibrio	genus	0.002	0.46	91.2	554	255
Helicobacter suncus	species	0.002	0.49	89.5	656	324
Thermodesulfovibrio thiophilus	species	0.002	0.44	89.5	480	210
Oenococcus	genus	0.002	0.46	89.2	528	241
Desulfotomaculum defluvii	species	0.003	0.56	81.7	906	508
Sporotomaculum syntrophicum	species	0.003	0.58	76.8	996	582
Hydrogenophilus	genus	0.003	0.59	74.9	994	585
Desulfosporosinus	genus	0.0025	1.67	71.5	600	1004
Clostridium taeniosporum	species	0.003	0.62	70.1	1184	734
Desulfofundulus	genus	0.002	0.47	69.5	434	206
Alkalibacterium	genus	0.003	0.58	68.1	792	456

Summary

A large number of bacterial taxa exhibit shifts with P < 0.01 in association with this condition. The subsequent challenge is determining how to modulate these taxa, since the volume of candidates exceeds what most individuals can practically consider. Moreover, for many of the taxa identified, there is no published evidence in the U.S. National Library of Medicine describing how to alter their abundance.

A deep optimization model, such as the one implemented on the Microbiome Taxa R2 site, can be used to inform probiotic selection. This model provides coverage for each identified taxon and infers which probiotics are most likely to shift their levels. Its output may then be integrated with more conventional recommendations derived from literature indexed in the U.S. National Library of Medicine where such evidence exists, with the two recommendation sets reconciled by giving priority to probiotic-based suggestions.

Development of a dedicated database based on Biomesight samples is in progress. The current model uses data contributed by PrecisionBiome, and datasets generated with differing laboratory processing pipelines cannot be safely combined, as discussed in The taxonomy nightmare before Christmas…. Once the Biomesight-specific database is complete, an option for generating (offline-only) personalized suggestions will be added to the Microbiome Prescription website.

Probiotics Suggestions

The following are based on a simplified algorithm using R2 data for Biomesight. These are tentative numbers subject to future refinements. Bacteria listed are only for probiotics detected with Biomesight tests. Probiotics include some that are available only in some countries and some that are pending approval for retail sale.

• Good Count: Number of bacteria expected to shift in desired direction
• Bad Count: Number of bacteria expected to shift in wrong direction
• Impact: Estimator of impact based on Chi-2, Slope and R2 vectors

Probiotic Species	Impact	Good Count	Bad Count
Segatella copri	11.24	1	0
Lactobacillus helveticus	10.17	2	2
Bifidobacterium breve	6.17	1	0
Bifidobacterium longum	5.98	1	0
Bifidobacterium adolescentis	4.67	1	0
Bifidobacterium bifidum	1.67	1	0
Bifidobacterium catenulatum	1.04	1	0
Blautia wexlerae	0.71	1	0
Bifidobacterium animalis	0.7	1	0
Enterococcus faecalis	0.17	2	3
Limosilactobacillus reuteri	0.14	3	0
Enterococcus durans	0.11	5	1
Lactobacillus johnsonii	0.11	3	0
Lactococcus lactis	0.09	1	0
Limosilactobacillus vaginalis	0.03	3	1
Bifidobacterium pseudocatenulatum	0.02	2	1
Escherichia coli	0.02	1	0
Lacticaseibacillus rhamnosus	0.02	1	0
Enterococcus faecium	0.01	1	1
Akkermansia muciniphila	-0.01	0	1
Ligilactobacillus salivarius	-0.01	0	1
Bacillus subtilis	-0.02	4	3
Lactobacillus jensenii	-0.02	2	2
Lactobacillus crispatus	-0.03	1	3
Pediococcus acidilactici	-1.09	2	3
Bacteroides uniformis	-32.26	0	1
Bacteroides thetaiotaomicron	-33.35	0	1