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	223
p < 0.001	199
p < 0.0001	181
p < 0.00001	164

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 the bacterua below, we see that for some the average is above and the median below. Should one increase or decrease this bacteria?

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). IMHO using average value instead of median will often result in a worse situation for the patient

tax_name	Rank	Symptom Average	Reference Average	Symptom Median	Reference Median
Faecalibacterium prausnitzii	species	13.575	12.086	11.275	12.554
Phocaeicola dorei	species	3.484	2.854	0.395	0.746
Roseburia	genus	2.432	2.876	1.812	1.484
Lachnospira	genus	2.424	2.755	1.901	1.631
Roseburia faecis	species	0.855	1.239	0.594	0.378
Sutterella wadsworthensis	species	0.75	0.65	0.049	0.239
Coprococcus	genus	1.083	1.463	0.741	0.609
Pedobacter	genus	1.299	0.971	0.551	0.651
Blautia wexlerae	species	0.474	0.589	0.324	0.27
Anaeroplasma	genus	1.197	0.432	0.003	0.05
Dorea	genus	0.454	0.486	0.299	0.256
Parabacteroides goldsteinii	species	0.585	0.569	0.133	0.171
Thermicanus	genus	0.206	0.188	0.101	0.127
Odoribacter	genus	0.28	0.189	0.122	0.146
Bacteroides stercorirosoris	species	0.166	0.196	0.139	0.116
Collinsella aerofaciens	species	0.154	0.172	0.05	0.071
Acetivibrio alkalicellulosi	species	0.237	0.261	0.1	0.08
Acetivibrio	genus	0.246	0.27	0.105	0.085
Dorea formicigenerans	species	0.111	0.136	0.086	0.067
Anaerofilum	genus	0.23	0.273	0.109	0.092

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.

tax_name	Rank	Incidence Odds Ratio	Chi2	Symptoms %	Reference %
Lactococcus	genus	1.27	7.2	60.5	47.6
Sporotomaculum	genus	0.72	8.8	31.6	43.8
Sporotomaculum syntrophicum	species	0.73	8.5	31.3	43.2
Enterobacter hormaechei	species	0.7	6.9	18	25.8
Actinopolyspora	genus	0.58	9.9	10.6	18.2
Rothia mucilaginosa	species	0.62	8.3	11.7	18.8
Citrobacter	genus	0.65	7.1	12.5	19.2
Peptoniphilus lacrimalis	species	1.47	8.2	20.7	14.1
Chromatium	genus	0.63	7.3	11.2	17.6
Chromatium weissei	species	0.64	7.3	11.2	17.6
Anaerococcus hydrogenalis	species	1.48	6.9	16.1	10.9

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	0.27	76.7	370	99
Isoalcanivorax indicus	species	0.002	0.27	76.7	370	99
Alcanivorax	genus	0.002	0.27	76.6	380	103
Nostoc flagelliforme	species	0.002	0.25	74.8	311	78
Niabella aurantiaca	species	0.002	0.32	71.5	534	172
Pelagicoccus croceus	species	0.002	0.3	66	378	115
Psychrobacter glacialis	species	0.002	0.36	65.8	654	233
Deferribacter autotrophicus	species	0.002	0.31	65.2	378	116
Deferribacter	genus	0.002	0.31	64.6	381	118
Salidesulfovibrio	genus	0.002	0.32	63.2	386	122
Salidesulfovibrio brasiliensis	species	0.002	0.32	63.2	386	122
Actinopolyspora	genus	0.002	0.36	60.6	537	192
Niabella	genus	0.002	0.36	60.1	571	208
Rickettsia marmionii Stenos et al. 2005	species	0.002	0.33	60	394	130
Lentibacillus	genus	0.002	0.36	57.6	500	181
Psychroflexus	genus	0.002	0.32	57.5	343	111
Psychroflexus gondwanensis	species	0.002	0.32	57.5	343	111
Lentibacillus salinarum	species	0.002	0.36	57.2	485	175
Viridibacillus neidei	species	0.002	0.36	56.6	463	166
Bacillus ferrariarum	species	0.002	0.34	56.1	361	121

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
Actinopolyspora	genus	0.003	0.16	326.3	628	101
Nostoc	genus	0.003	0.33	281.5	1134	376
Flammeovirga	genus	0.003	0.35	186.1	742	261
Asticcacaulis	genus	0.003	0.42	185.9	1064	446
Flammeovirga pacifica	species	0.003	0.35	185.6	741	261
Planococcus	genus	0.003	0.32	182.4	613	194
Planococcus columbae	species	0.003	0.31	176.2	575	179
Streptococcus oralis	species	0.003	0.48	167.3	1358	652
Psychrobacter glacialis	species	0.002	0.36	164.8	654	233
Niabella aurantiaca	species	0.002	0.32	158.7	534	172
Clostridium tepidiprofundi	species	0.003	0.38	152.9	659	248
Niabella	genus	0.002	0.36	142.4	571	208
Alcanivorax	genus	0.002	0.27	142.3	380	103
Isoalcanivorax	genus	0.002	0.27	140.7	370	99
Isoalcanivorax indicus	species	0.002	0.27	140.7	370	99
Atopobium fossor	species	0.003	0.37	138.2	555	203
Lentibacillus	genus	0.002	0.36	128.3	500	181
Nostoc flagelliforme	species	0.002	0.25	127.5	311	78
Desulfitobacterium	genus	0.005	0.38	126.8	525	197
Lentibacillus salinarum	species	0.002	0.36	125.5	485	175

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	17.5	1284	800
Dethiosulfovibrio	genus	0.004	0.67	12.7	1433	961
Tetragenococcus doogicus	species	0.003	0.68	11.8	1289	875
Mycoplasmopsis	genus	0.005	0.7	10	1707	1203
Hydrocarboniphaga daqingensis	species	0.004	0.72	9	1533	1097
Tetragenococcus	genus	0.003	0.74	6.8	1270	946
Pediococcus	genus	0.004	0.75	6.6	1239	926

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
Actinopolyspora	genus	0.003	0.16	326.3	628	101
Nostoc	genus	0.003	0.33	281.5	1134	376
Flammeovirga	genus	0.003	0.35	186.1	742	261
Asticcacaulis	genus	0.003	0.42	185.9	1064	446
Flammeovirga pacifica	species	0.003	0.35	185.6	741	261
Planococcus	genus	0.003	0.32	182.4	613	194
Planococcus columbae	species	0.003	0.31	176.2	575	179
Streptococcus oralis	species	0.003	0.48	167.3	1358	652
Psychrobacter glacialis	species	0.002	0.36	164.8	654	233
Niabella aurantiaca	species	0.002	0.32	158.7	534	172
Clostridium tepidiprofundi	species	0.003	0.38	152.9	659	248
Niabella	genus	0.002	0.36	142.4	571	208
Alcanivorax	genus	0.002	0.27	142.3	380	103
Isoalcanivorax	genus	0.002	0.27	140.7	370	99
Isoalcanivorax indicus	species	0.002	0.27	140.7	370	99
Atopobium fossor	species	0.003	0.37	138.2	555	203
Lentibacillus	genus	0.002	0.36	128.3	500	181
Nostoc flagelliforme	species	0.002	0.25	127.5	311	78
Desulfitobacterium	genus	0.005	0.38	126.8	525	197
Lentibacillus salinarum	species	0.002	0.36	125.5	485	175

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

Blautia hansenii	194.64	19	0
Blautia wexlerae	147.38	8	0
Faecalibacterium prausnitzii	74.57	10	3
Enterococcus faecalis	19.48	34	44
Lactobacillus johnsonii	9.37	29	62
Streptococcus thermophilus	4.1	8	0
Escherichia coli	3.35	8	2
Segatella copri	2.83	2	4
Enterococcus faecium	2.16	10	45
Bifidobacterium breve	1.91	2	3
Heyndrickxia coagulans	1.89	7	39
Bifidobacterium longum	1.7	2	2
Bifidobacterium adolescentis	1.46	2	0
Enterococcus durans	1.4	27	30
Bifidobacterium bifidum	0.48	3	2
Bifidobacterium catenulatum	0.27	3	4
Lacticaseibacillus paracasei	0.2	5	14
Bifidobacterium animalis	0.16	1	1
Leuconostoc mesenteroides	0.09	11	26
Limosilactobacillus fermentum	0.04	9	29
Veillonella atypica	-0.03	2	4
Ligilactobacillus salivarius	-0.11	5	21
Lacticaseibacillus casei	-0.13	1	12
Lacticaseibacillus rhamnosus	-0.23	1	14
Lactiplantibacillus plantarum	-0.26	0	12
Limosilactobacillus reuteri	-0.47	24	31
Akkermansia muciniphila	-0.51	3	15
Lactobacillus acidophilus	-0.7	5	42
Lactobacillus crispatus	-0.95	1	43
Odoribacter laneus	-0.96	0	3
Bacillus subtilis	-0.99	29	55
Limosilactobacillus vaginalis	-1.33	21	70
Parabacteroides distasonis	-1.35	0	1
Bacteroides uniformis	-2.4	3	3
Lactobacillus jensenii	-2.56	6	82
Bifidobacterium pseudocatenulatum	-3.11	5	43
Lactobacillus helveticus	-5.05	35	100
Bacteroides thetaiotaomicron	-5.17	2	3
Clostridium butyricum	-5.21	0	35
Pediococcus acidilactici	-9.29	40	51
Parabacteroides goldsteinii	-9.3	0	12