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	239
p < 0.001	206
p < 0.0001	184
p < 0.00001	164

Below is a walkthru that may help some people understand the statistics.

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 Phocaeicola 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
Phocaeicola	genus	9.816	10.961	9.483	8.286
Blautia	genus	9.805	8.323	7.101	7.832
Bacteroides uniformis	species	3.057	2.699	1.512	2.029
Oscillospira	genus	2.751	2.316	1.925	2.255
Parabacteroides	genus	2.604	2.627	1.714	2.007
Bacteroides cellulosilyticus	species	1.145	0.824	0.07	0.218
Clostridium	genus	2.093	1.835	1.359	1.501
Pedobacter	genus	1.134	0.986	0.545	0.647
Ruminococcus bromii	species	0.824	0.788	0.16	0.261
Bacteroides caccae	species	1.079	0.855	0.282	0.371
Akkermansia muciniphila	species	1.789	1.315	0.047	0.132
Akkermansia	genus	1.789	1.314	0.047	0.132
Blautia hansenii	species	1.093	1.033	0.713	0.786
Bifidobacterium	genus	0.627	0.965	0.133	0.061
Bilophila	genus	0.374	0.348	0.206	0.275
Bacteroides rodentium	species	0.484	0.382	0.183	0.234
Sutterella wadsworthensis	species	0.647	0.66	0.06	0.012
Bilophila wadsworthia	species	0.355	0.34	0.198	0.241
Acetivibrio	genus	0.357	0.259	0.099	0.141
Acetivibrio alkalicellulosi	species	0.343	0.25	0.094	0.134

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 %
Ethanoligenens	genus	1.35	12.4	62.9	46.6
Porphyromonas asaccharolytica	species	1.6	18.7	31.7	19.8
Mogibacterium vescum	species	1.68	21.3	29.2	17.4
Dehalobacterium	genus	1.31	8.7	49.5	37.7
Acholeplasma hippikon	species	1.49	14	33.5	22.5
Aggregatibacter	genus	0.56	15.3	14	24.8
Anaerococcus	genus	1.29	7.4	46.4	35.9
Peptoniphilus asaccharolyticus	species	1.3	7.4	44.7	34.4
Slackia faecicanis	species	1.35	8.7	38.8	28.8
Sporosarcina pasteurii	species	1.67	17.5	23.6	14.1
Finegoldia magna	species	1.29	6.7	42.4	32.9
Sporosarcina	genus	1.64	16.2	23.6	14.4
Shewanella upenei	species	1.34	7.4	33	24.7
Meiothermus	genus	1.34	7.2	31.2	23.3
Meiothermus granaticius	species	1.34	7.1	30.7	22.9
Actinobacillus pleuropneumoniae	species	0.58	10.7	10.9	18.7
Varibaculum	genus	1.53	10.8	20.6	13.4
Halanaerobium	genus	1.42	8.2	23.4	16.4
Anaerococcus vaginalis	species	1.37	7.2	25.6	18.7
Erysipelothrix inopinata	species	1.47	8.6	19.8	13.4

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
Isoalcanivorax	genus	0.002	0.25	82.4	350	88
Isoalcanivorax indicus	species	0.002	0.25	82.4	350	88
Alcanivorax	genus	0.002	0.26	81.9	359	92
Salidesulfovibrio	genus	0.002	0.3	70	371	110
Salidesulfovibrio brasiliensis	species	0.002	0.3	70	371	110
Niabella aurantiaca	species	0.002	0.33	69.1	507	169
Psychroflexus	genus	0.002	0.3	66.1	348	105
Psychroflexus gondwanensis	species	0.002	0.3	66.1	348	105
Deferribacter autotrophicus	species	0.002	0.31	64.6	360	112
Deferribacter	genus	0.002	0.31	63.7	362	114
Pelagicoccus croceus	species	0.002	0.32	61.9	368	119
Psychrobacter glacialis	species	0.002	0.38	60.9	622	235
Rickettsia marmionii Stenos et al. 2005	species	0.002	0.34	58.8	372	125
Bacillus ferrariarum	species	0.002	0.33	58.7	354	117
Segetibacter aerophilus	species	0.002	0.33	58.5	360	120
Niabella	genus	0.002	0.39	55.5	540	208
Segetibacter	genus	0.002	0.35	54.9	362	126
Actinopolyspora	genus	0.002	0.38	54.7	509	195
Lentibacillus	genus	0.002	0.38	53.8	484	185
Lentibacillus salinarum	species	0.002	0.38	52.9	468	179

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
Methylobacillus glycogenes	species	0.003	0.4	215.7	1186	478
Methylobacillus	genus	0.003	0.42	201.4	1185	496
Streptococcus oralis	species	0.003	0.47	177.9	1355	632
Erysipelothrix muris	species	0.015	0.53	167.1	2060	1096
Desulfotomaculum	genus	0.004	0.49	156.3	1370	678
Erysipelothrix	genus	0.015	0.55	148	2061	1143
Niabella aurantiaca	species	0.002	0.33	145.2	507	169
Psychrobacter glacialis	species	0.002	0.38	144.7	622	235
Alcanivorax	genus	0.002	0.26	142.5	359	92
Isoalcanivorax	genus	0.002	0.25	141.6	350	88
Isoalcanivorax indicus	species	0.002	0.25	141.6	350	88
Caloramator fervidus	species	0.045	0.58	131	2131	1235
Salidesulfovibrio	genus	0.002	0.3	126.8	371	110
Salidesulfovibrio brasiliensis	species	0.002	0.3	126.8	371	110
Porphyromonas	genus	0.012	0.58	125.1	1974	1145
Niabella	genus	0.002	0.39	124.6	540	208
Actinopolyspora	genus	0.002	0.38	119.5	509	195
Psychroflexus	genus	0.002	0.3	117.4	348	105
Psychroflexus gondwanensis	species	0.002	0.3	117.4	348	105
Deferribacter autotrophicus	species	0.002	0.31	116.8	360	112

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	0.6	21.7	1272	762
Dethiosulfovibrio	genus	0.004	0.65	15.5	1446	943
Tetragenococcus doogicus	species	0.003	0.66	14.9	1290	845
Hydrocarboniphaga daqingensis	species	0.004	0.7	11.3	1531	1065
Mycoplasmopsis	genus	0.005	0.72	9.6	1681	1206
Pediococcus	genus	0.004	0.72	8.6	1222	885
Tetragenococcus	genus	0.003	0.74	7.6	1268	938
Carboxydocella ferrireducens	species	0.004	0.75	6.8	1215	912

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.

Methylobacillus glycogenes	species	0.003	0.4	215.7	1186	478
Methylobacillus	genus	0.003	0.42	201.4	1185	496
Streptococcus oralis	species	0.003	0.47	177.9	1355	632
Erysipelothrix muris	species	0.015	0.53	167.1	2060	1096
Desulfotomaculum	genus	0.004	0.49	156.3	1370	678
Erysipelothrix	genus	0.015	0.55	148	2061	1143
Niabella aurantiaca	species	0.002	0.33	145.2	507	169
Psychrobacter glacialis	species	0.002	0.38	144.7	622	235
Alcanivorax	genus	0.002	0.26	142.5	359	92
Isoalcanivorax	genus	0.002	0.25	141.6	350	88
Isoalcanivorax indicus	species	0.002	0.25	141.6	350	88
Caloramator fervidus	species	0.045	0.58	131	2131	1235
Salidesulfovibrio	genus	0.002	0.3	126.8	371	110
Salidesulfovibrio brasiliensis	species	0.002	0.3	126.8	371	110
Porphyromonas	genus	0.012	0.58	125.1	1974	1145
Niabella	genus	0.002	0.39	124.6	540	208
Actinopolyspora	genus	0.002	0.38	119.5	509	195
Psychroflexus	genus	0.002	0.3	117.4	348	105
Psychroflexus gondwanensis	species	0.002	0.3	117.4	348	105
Deferribacter autotrophicus	species	0.002	0.31	116.8	360	112

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
Bifidobacterium breve	6.33	1	0
Bacteroides thetaiotaomicron	6.22	1	0
Bifidobacterium longum	6.14	1	0
Bifidobacterium adolescentis	4.79	1	0
Bacteroides uniformis	4.21	1	0
Lactobacillus helveticus	3.61	3	10
Enterococcus faecalis	2.88	8	8
Pediococcus acidilactici	2.43	3	7
Bifidobacterium bifidum	1.71	1	0
Bifidobacterium catenulatum	1.07	1	0
Bifidobacterium animalis	0.71	1	0
Segatella copri	0.53	1	0
Bacillus subtilis	0.29	2	6
Veillonella atypica	0.09	1	0
Heyndrickxia coagulans	0.06	1	2
Limosilactobacillus fermentum	-0.01	1	2
Bacillus	-0.01	0	1
Pediococcus	-0.01	0	1
Leuconostoc mesenteroides	-0.01	0	1
Ligilactobacillus salivarius	-0.02	1	3
Lacticaseibacillus rhamnosus	-0.02	0	1
Lactiplantibacillus pentosus	-0.02	0	1
Lactiplantibacillus plantarum	-0.02	0	1
Bacillus subtilis group	-0.02	0	1
Lacticaseibacillus casei	-0.03	0	2
Enterococcus faecium	-0.04	1	5
Lacticaseibacillus paracasei	-0.05	0	3
Bifidobacterium pseudocatenulatum	-0.05	0	4
Lactobacillus crispatus	-0.06	1	4
Clostridium butyricum	-0.06	0	1
Lactobacillus acidophilus	-0.1	1	6
Enterococcus durans	-0.13	1	4
Limosilactobacillus vaginalis	-0.18	0	7
Bacillus amyloliquefaciens group	-0.19	0	8
Lactobacillus johnsonii	-0.21	2	7
Limosilactobacillus reuteri	-0.24	1	5
Odoribacter laneus	-0.34	0	1
Lactobacillus jensenii	-0.43	1	11
Parabacteroides goldsteinii	-5.4	0	3
Akkermansia muciniphila	-11.49	0	6
Parabacteroides distasonis	-14.94	0	1
Blautia wexlerae	-15.49	0	1
Blautia hansenii	-18.32	0	3