I recently exposed the Diversity Indices to all users on Microbiome Prescription. It is on the [Research Features] tab.

I then computed the average and also the average percentile for each symptom. I prefer to use percentile because the distribution is not a bell curve. Converting to percentiles transform it to a uniform distribution which is easier to work with for statistical tests. Percentiles are also easier for people to understand.

See this write up by CosmosId to explain these indices. I also attach the data as a CSV file for those who want to play with sorting the data in different manners. For all of the Rank, 50 is what would be expected from a general healthy population.

These Measures are Age And Lab Sensitive

Symptom Name	Shannon	Simpson	Chao	Shannon Rank	Simpson Rank	Chao Rank	Obs
Age: 0-10	1.576	0.118	8788	33.1	65.2	44.8	21
Age: 20-30	1.599	0.065	11592	32.2	49.7	52.6	57
Age: 30-40	1.579	0.06	11119	31.9	43.5	52.9	153
Age: 40-50	1.62	0.067	10433	34.8	47.1	50.5	106
Age: 50-60	1.605	0.045	11728	32.8	34.1	55.3	47
Age: 60-70	1.488	0.033	13580	28	26	60.7	22

SymptomName	Shannon	Simpson	chao	Shannon Rank	Simpson Rank	Chao Rank	observations
Age: 20-30	2.18	0.06	2360	65	49.6	15.2	38
Age: 30-40	2.116	0.06	2058	61.6	50.3	13.9	69
Age: 40-50	1.848	0.071	1724	47.8	53.9	11.7	53
Age: 50-60	1.747	0.039	2019	42.8	32.5	13.9	47
Age: 60-70	1.926	0.058	1691	52.1	43.7	11.4	75

Symptom Name	Shannon	Simpson	chao	Shannon Rank	Simpson Rank	Chao Rank	observations
Age: 0-10	2.293	0.134	19797	64.1	67.7	69.8	52
Age: 20-30	2.616	0.103	21549	74.8	63.2	69.1	31
Age: 30-40	2.816	0.083	16394	81.7	63.4	67.2	96
Age: 40-50	2.89	0.09	20275	84.8	62.2	74.1	53
Age: 50-60	3.025	0.076	21956	86.6	54	75.9	38
Age: 60-70	2.596	0.077	27740	72.4	51	72.6	72

For anyone wishing to dig further, all of the raw data is on our citizen science site for download. For example, you can compute lab specific percentiles for each symptom.

Symptom Name	Shannon	Simpson	Chao	Shannon Rank	Simpson Rank	Chao Rank	Obs
Asymptomatic: Minor Health Issues (a few symptoms only)	1.931	0.048	4856.983	50.7	40.5	26	58
Official Diagnosis: Ulcerative colitis	1.705	0.08	5547.478	35.2	54.7	27.5	23
Neurological: Spatial instability and disorientation	2.049	0.072	5981.804	55.2	51.8	29.5	56
Asymptomatic: No Health Issues	2.012	0.066	8924.899	53.7	45.4	29.6	188
Joint: Sudden and severe episodes of pain	2.185	0.058	6160.833	58.5	48.5	30.6	48
Neuroendocrine: Feeling like you have a high temperature	1.967	0.075	6704.373	50.9	53.8	32.6	75
Autonomic: Blurred or tunnel vision after standing	1.907	0.054	6777.784	49.9	42.1	33.2	51
Neuroendocrine Manifestations: abnormal appetite	2.012	0.06	7345.455	53.2	44.8	34.1	77
Neurological: fasciculations	1.863	0.055	8333.9	47.9	43.3	34.2	70
Onset: over 31 years since onset	1.657	0.089	7253.219	38.7	47.2	34.6	32
Neurological: Confusion	1.918	0.067	7627.785	49.4	48.4	35	93
Immune Manifestations: Diarrhea	1.936	0.075	12798.57	48.9	52.4	35	178
Neuroendocrine: Feeling like you have a low temperature	1.963	0.069	7193.583	51.5	48	35.3	60
Neurological-Vision: Blurred Vision	1.867	0.059	7616.119	46.4	44	35.4	151
Autonomic: Graying or blacking out after standing	2.037	0.058	7603.086	55.9	45.3	35.5	35
Neuroendocrine: Chills or shivers	1.813	0.083	7818.411	45.2	52.6	35.6	56
Neuroendocrine Manifestations: recurrent feelings of feverishness	1.975	0.059	8146.892	51.2	48	36.2	65
Neurological: Difficulty processing information (Understanding)	1.9	0.071	8249.883	48.3	48.1	36.3	197
Neuroendocrine Manifestations: Neuralgia	1.91	0.067	10588.14	47.2	49.6	36.4	44
Neurological-Sleep: Chaotic diurnal sleep rhythms (Erratic Sleep)	2.009	0.059	11433.45	51.6	43.4	36.5	231
Neuroendocrine: Temperature fluctuations throughout the day	1.957	0.065	7482.103	49.8	50.3	36.5	68
Neurological: Impairment of concentration	1.981	0.059	10024.12	51.6	43.8	36.8	345
Immune Manifestations: tender lymph nodes	1.981	0.057	8632.264	51.6	43.2	36.9	110
Sleep: Sleeping all day and staying awake all night	2.07	0.074	7632.563	56.3	54.3	37.1	32
Autonomic: Nausea	1.911	0.07	8689.976	48.8	51.7	37.1	85
Neurological: Short-term memory issues	2.001	0.062	8048.832	52.5	45.6	37.2	220
Neurological: Neuropathy	1.926	0.051	11019.76	48.2	41.4	37.5	71
Official Diagnosis: Metabolic Syndrome	1.748	0.067	8212.524	43.3	44.1	37.6	21
DePaul University Fatigue Questionnaire : Fever & Chills	1.728	0.102	9503.591	40.5	56.2	37.6	22
Neuroendocrine: Lack of appetite	1.946	0.064	9142.984	50.5	44.5	37.6	61
Neurological: Executive Decision Making (Difficulty making)	2.006	0.061	11185.76	52.4	44.4	37.7	289
Immune: Sensitivity to smell/food/medication/chemicals	1.979	0.067	9401.077	50	47.4	37.8	194
Immune Manifestations: Genitorinary / Nocturia – Urinary issues	2.085	0.07	7840.608	56	51.7	37.8	51
Neurological: emotional overload	2.065	0.066	8548.668	54.8	49.5	37.8	196
Neuroendocrine Manifestations: Muscle weakness	1.95	0.062	8751.741	49.6	46.2	37.9	216
General: Myalgia (pain)	2.009	0.059	13779.4	52.4	46.3	37.9	216
Onset: 2000-2010	1.949	0.064	8244.574	49.8	47.3	38	122
Neuroendocrine: Lost or gained weight without trying	1.993	0.07	8316.814	51.6	50.7	38.2	118
Immune Manifestations: new food sensitivities	1.983	0.067	9932.414	50.6	47.7	38.2	157
Onset: Gradual	2.043	0.062	13699.92	55	47.6	38.2	172
Neurological: High degree of Empathy before onset	1.975	0.07	8434.465	51	51.1	38.3	86
Comorbid-Mouth: Dry Mouth	1.856	0.055	8600.484	45.7	41.3	38.4	124
Neuroendocrine Manifestations: subnormal body temperature	1.999	0.057	12240.34	52.1	40.8	38.4	235
Neurological-Vision: Acquired or exertional dyslexia	1.911	0.076	8275.381	49.7	54.1	38.5	21
Neuroendocrine Manifestations: Dry Eye (Sicca or Sjogren Syndrome)	1.873	0.056	10422.66	45.7	42.4	38.5	136
Neurocognitive: Slowness of thought	1.958	0.061	12656.61	50.6	44.9	38.6	361
Neuroendocrine: Sweating hands	1.91	0.091	8249.438	48.2	56.6	38.7	48
Pain: Chest pain	2.124	0.069	10019.41	58.3	52.3	38.7	54
Blood Type: B Positive	1.753	0.085	8271.444	40.4	55.8	38.7	36
Neurological-Vision: inability to focus eye/vision	1.946	0.061	12655.22	49.6	42.1	38.8	224
Neurological: Difficulty reading	1.966	0.066	11904.13	50.5	45.1	39	283
Neurological-Vision: Impaired Depth Perceptions	1.917	0.093	9048.091	46.3	49.7	39	33
Asymptomatic: Live in house with person with probable microbiome dysfunction	1.954	0.057	9649.831	50.1	43.2	39	71
Neurocognitive: Absent-mindedness or forgetfulness	1.989	0.064	12091.81	51.5	45.6	39	389
Pain: Pain or aching in muscles	1.958	0.068	12992.8	49.7	51.1	39	182
Comorbid: Raynaud’s syndrome (Skin discoloration)	1.917	0.052	15270.64	48	44.7	39	33
Autonomic Manifestations: cardiac arrhythmias	1.955	0.054	9592.803	51.4	40.8	39	61
Pain: Myofascial pain	2.009	0.064	19489.55	53	47.8	39.1	89
Neuroendocrine Manifestations: Excessive adrenaline	2.027	0.064	8756.423	53.6	50.5	39.1	78
Official Diagnosis: Inflammatory Bowel Disease (IBD)	1.906	0.093	8392.806	47.6	58.5	39.2	31
Pain: Joint pain	2.003	0.066	10602.51	51.9	50.6	39.3	178
Joint: Stiffness and swelling	2.041	0.059	12655.61	53.1	43	39.3	246
Neurological-Sleep: Vivid Dreams/Nightmares	2.06	0.058	9058.67	54.6	45.4	39.3	100
Infection: Mycoplasma	2.054	0.075	11920.39	54	54	39.4	111
Neurological: Disorientation	2.102	0.077	8725.15	56.9	55	39.5	80
Comorbid-Mouth: Gingivits / Gum Disease	2.04	0.06	8021.06	55.7	47.7	39.8	67
Autonomic Manifestations: Cortisol disorders or irregularity	2.015	0.064	8834.639	51.8	47.6	39.8	97
General: Headaches	1.991	0.06	12468.8	51.2	44.8	39.9	309
Official Diagnosis: Mast Cell Dysfunction	2.012	0.06	13066.28	51.8	43.1	39.9	208
Autonomic: Dizziness or fainting	1.932	0.062	8867.455	49.6	45.5	39.9	112
Immune Manifestations: general malaise	1.962	0.061	13005.88	50.5	44.9	40	339
Comorbid: Hypothyroidism	1.982	0.061	12229.72	50.9	43.5	40	258
Autonomic Manifestations: nausea	1.862	0.067	9328.009	46.5	47.9	40.1	108
Age: 60-70	1.997	0.057	14128.26	51.2	40.1	40.2	195
Neuroendocrine Manifestations: Rapid muscular fatiguability	2.024	0.063	9405.636	53.4	46.7	40.2	165
Pain: Aching of the eyes or behind the eyes	1.954	0.058	11520.93	49.6	44.7	40.3	98
Immune Manifestations: Alcohol Intolerant	1.967	0.059	12012.28	49.9	41.8	40.5	303
Neurocognitive: Difficulty understanding things	1.942	0.071	9540.413	49.8	49.6	40.5	189
Neurological-Vision: photophobia (Light Sensitivity)	2.004	0.063	12593.74	51.2	44.7	40.5	276
Onset: less than 16 years since onset	1.954	0.057	8948.205	49.7	46.3	40.7	83
Autonomic Manifestations: irritable bowel syndrome	1.963	0.063	13226.9	50.8	44.2	40.8	378
Neurocognitive: Feeling disoriented	1.976	0.065	9168.405	50.8	49.3	40.8	126
Comorbid-Mouth: TMJ / Dysfunction of the temporomandibular joint syndrome	1.986	0.057	13336.82	50.9	40.2	40.8	223
Autonomic Manifestations: palpitations	1.876	0.064	9256.654	47	45.9	40.9	133
Infection: Human Herpesvirus 6 (HHV6)	2.056	0.068	14020.15	54.2	49.5	40.9	149
Neuroendocrine Manifestations: worsening of symptoms with stress.	1.989	0.061	10591.72	51.1	44.9	40.9	414
Autonomic Manifestations: Postural orthostatic tachycardia syndrome (POTS)	1.927	0.067	9603.289	48.8	45.2	40.9	128
Onset: less than 04 years since onset	2.034	0.073	8956.183	54.1	53.2	40.9	71
Immune Manifestations: Abdominal Pain	1.947	0.068	14265.76	49.4	46.5	41.1	326
Neurological: Word-finding problems	2.057	0.064	10858.39	53.5	46.9	41.2	289
Neurological-Audio: hypersensitivity to noise	1.958	0.064	11562.53	49.7	45.7	41.2	347
Immune Manifestations: recurrent flu-like symptoms	2.001	0.066	15145.96	51.8	48.4	41.2	124
Neuroendocrine: Alcohol intolerance	1.951	0.06	13204.94	49.6	41.8	41.3	278
Post-exertional malaise: Rapid muscular fatigability,	2.024	0.06	9815.645	52.8	44.1	41.4	169
Neurocognitive: Problems remembering things	1.99	0.065	11390.81	51.3	46.9	41.4	415
Comorbid: Constipation and Explosions (not diarrohea)	2.014	0.062	14823.47	52.2	41.9	41.5	170
Neuroendocrine Manifestations: intolerance of extremes of heat and cold	1.987	0.064	9946.112	50.9	47.3	41.5	249
Pain: Eye pain	1.978	0.046	14356.53	51	37.8	41.5	57
Neurological-Audio: Tinnitus (ringing in ear)	1.96	0.061	13969.85	49.5	44.8	41.5	392
Blood Type: A Negative	1.87	0.06	8845	47.9	42.9	41.5	24
Neurocognitive: Unable to focus vision and/or attention	2.01	0.065	12425.26	52	45.7	41.6	302
Other: Sensitivity to mold	2.043	0.067	9442.872	53.5	50.5	41.7	141
Neurocognitive: Can only focus on one thing at a time	1.981	0.06	11138.71	50.7	45	41.7	394
Neurological: Cognitive/Sensory Overload	1.988	0.067	10058.01	50.7	49.4	41.7	219
Immune Manifestations: medication sensitivities.	2.092	0.061	13364.06	55.5	44.5	41.7	142
Neurocognitive: Difficulty paying attention for a long period of time	2.002	0.064	11330.78	52	46.8	41.8	429
Immune Manifestations: hives	1.973	0.056	10904.28	50.2	38.6	41.9	46
Onset: Sudden	1.704	0.068	8797.214	39.9	47.7	41.9	70
Autonomic Manifestations: exertional dyspnea	1.771	0.061	9788.978	45.3	39.9	42	46
Comorbid: Mold Sensitivity / Exposure	2.072	0.066	9522.613	54.2	49.7	42.1	137
Sleep: Need to nap daily	1.955	0.061	9768.217	49.7	46.3	42.1	129
Neuroendocrine Manifestations: sweating episodes	2.074	0.071	13323.83	54.6	47.9	42.1	183
Post-exertional malaise: Inappropriate loss of physical and mental stamina,	2.034	0.063	9683.478	52.7	46.7	42.1	255
Autonomic Manifestations: urinary frequency dysfunction	2.023	0.07	8986.062	53.6	49.5	42.2	113
Neurocognitive: Difficulty expressing thoughts	1.996	0.074	10247.57	51.8	49.4	42.2	232
General: Fatigue	1.971	0.058	12031.46	50.6	44.5	42.3	554
Immune: Flu-like symptoms	2.032	0.067	17995.01	53.2	47.3	42.3	116
Neuroendocrine Manifestations: marked weight change	2.115	0.069	13678.23	55.3	50.2	42.3	119
Comorbid-Mouth: Bruxism – Jaw cleanching / Teeth grinding	2.005	0.062	13571.29	51.6	43.2	42.3	318
Neuroendocrine: Feeling hot or cold for no reason	1.985	0.067	10345.56	50.5	48.5	42.4	158
Autonomic: Ocassional Tachycardia (Rapid heart beat)	1.908	0.067	9478.579	48.1	49.2	42.4	121
Gender: Female	2	0.055	9736.427	51.3	43.3	42.4	372
Immune: Recurrent Sore throat	1.961	0.063	11439.67	49.5	45.9	42.5	134
Neurological-Sleep: Sleep Apnea	2.148	0.066	19898.1	58.2	52.3	42.6	103
Comorbid: Snoring (NOT Sleep Apnea	2.031	0.059	14436.91	52.7	41.6	42.6	185
Sleep: Waking up early in the morning (e.g. 3 AM)	2.057	0.062	12919.95	53.3	45	42.7	349
Neuroendocrine Manifestations: marked diurnal fluctuation	2.115	0.06	10086.79	58	45.6	42.7	24
Immune Manifestations: Mucus in the stool	2.045	0.078	14352.74	52.9	51.6	42.7	176
Neuroendocrine Manifestations: cold extremities	1.961	0.061	14395.2	49.6	45.3	42.8	267
Neuroendocrine Manifestations: loss of adaptability	1.963	0.065	22154.92	51	47.4	42.9	62
Neurological-Sleep: Night Sweats	2.071	0.065	13304.88	53.3	46.3	42.9	141
Pain: Sensitivity to pain	2.049	0.072	12457.74	53.1	51.1	42.9	181
Immune Manifestations: Bloating	1.977	0.063	13344.09	50.3	45	42.9	504
Post-exertional malaise: Difficulty reading after mild physical or mental activity	1.991	0.065	10766.63	51.2	47	42.9	192
Onset: less than 08 years since onset	2.054	0.059	9535.966	54.9	43.3	43	58
Neurological-Sleep: Insomnia	2.03	0.061	14473.17	52.3	44.6	43	339
Neuroendocrine: Cold limbs (e.g. arms, legs hands)	1.969	0.067	12977.49	50.6	46.4	43	191
Sleep: Unrefreshed sleep	1.989	0.059	12300.45	51.3	44.1	43	479
Immune Manifestations: Constipation	2.004	0.059	14280.13	52.1	43.2	43	395
General: Depression	2.11	0.067	12559.02	55.7	49.1	43	278
Official Diagnosis: Irritable Bowel Syndrome	1.999	0.065	14433.07	51.3	45	43.1	349
Comorbid: Multiple Chemical Sensitivity	2.053	0.056	12104.99	53.9	41.3	43.1	131
Neuroendocrine Manifestations: Air Hunger	1.931	0.058	9873.469	48.8	44.5	43.1	81
Sleep: Daytime drowsiness	2.018	0.065	14393.73	52.2	46.6	43.1	349
Autonomic: Shortness of breath	1.976	0.067	9794.895	50.5	47.8	43.1	124
Immune Manifestations: Thick blood / Hypercoagulation	1.99	0.061	9581.985	51.2	46.8	43.2	66
Sleep: Problems falling asleep	2.031	0.065	10621.44	52.4	47.8	43.2	221
Infection: Lyme	2.029	0.057	11234.89	52.6	46.8	43.2	71
Neurological-Sleep: Inability for deep (delta) sleep	2.097	0.071	14421.58	55.9	48.9	43.2	151
Onset: less than 02 years since onset	1.896	0.063	9318.657	46.1	46.3	43.3	67
Onset: 2010-2020	1.99	0.064	12458.24	50.4	44.7	43.4	325
Age: 10-20	2.014	0.071	9357.475	53.2	49.8	43.4	40
Autonomic Manifestations: light-headedness	1.988	0.07	10053.82	50.4	49.3	43.6	145
Sleep: Problems staying asleep	2.051	0.059	13891.49	52.9	44.1	43.7	380
Autonomic: Irregular heartbeats	2.047	0.068	14841.51	52.8	48	43.8	141
Comorbid: Histamine or Mast Cell issues	1.969	0.059	13247.94	49.7	43.5	43.8	355
Other: Sensitivity to vibrations	1.929	0.044	12403.73	47.9	37.3	43.9	52
Post-exertional malaise: Mentally tired after the slightest effort	2.018	0.063	10731.34	51.5	47.2	43.9	161
Official Diagnosis: Allergic Rhinitis (Hay Fever)	1.965	0.057	13655.98	49.7	41.6	43.9	232
Infection: Epstein-Barr virus	2.117	0.06	13402.13	55.8	45.4	44	240
Infection: Coxsackie	2.1	0.061	9782.615	57.3	47.6	44.2	39
Post-exertional malaise: Rapid cognitive fatigability,	2.055	0.061	10488.19	53.6	46.8	44.2	212
Neurocognitive: Brain Fog	1.982	0.064	12153.58	50.4	46.3	44.3	597
Comorbid: Small intestinal bacterial overgrowth (SIBO)	2.02	0.071	13923.31	51.2	52.7	44.4	191
Immune: Tender / sore lymph nodes	2.096	0.068	14842.85	53.6	46.7	44.4	111
Post-exertional malaise: Worsening of symptoms after mild mental activity	2.016	0.071	10902.02	51.9	51.4	44.4	165
General: Sinus issues with headaches	2.024	0.065	13296.41	52	46.4	44.5	124
Age: 20-30	1.974	0.07	16286.07	51.1	50.9	44.5	136
Post-exertional malaise: Next-day soreness after everyday activities	2.104	0.064	12530.68	54.4	47.2	44.5	198
Immune Manifestations: Inflammation of skin, eyes or joints	2.097	0.068	16251.55	54.8	51.1	44.6	228
Post-exertional malaise: General	2.053	0.063	13379.21	53.4	48.9	44.6	243
Neurological: Slowed speech	2.179	0.08	14630.11	57.9	49.4	44.7	108
Post-exertional malaise: Post-exertional malaise	2.072	0.06	10683.72	53.8	46.3	44.7	269
Neurological: Joint hypermobility	2.063	0.072	15030.99	53.3	48.8	44.8	167
Neurological: Seasonal Affective Disorder (SAD)	2.171	0.073	12976.18	58.7	49.8	44.9	127
Neuroendocrine Manifestations: Laboured breathing	2.003	0.077	11266.07	52.1	51.8	44.9	30
Autonomic Manifestations: delayed postural hypotension	2.091	0.08	10730.32	56.3	51.3	44.9	28
Infection: Parasite – Other	2.089	0.079	13683.44	55.4	52.2	44.9	81
Autonomic: Heart rate increase after standing	1.946	0.058	10621.93	50.4	44.6	44.9	145
Comorbid: Inflammatory bowel disease	2.096	0.078	15575.55	54.1	51.6	45	162
Immune: Chronic Sinusitis	1.969	0.056	9423.875	49.4	44.9	45	80
Neuroendocrine Manifestations: Paraesthesia (tingling burning of skin)	2.177	0.075	15722.67	57.3	52.5	45.1	129
Immune Manifestations: Hair loss	2.111	0.075	17633.89	55.2	53.5	45.1	218
Onset: 1990-2000	2.132	0.056	30905.83	56.2	46.3	45.1	42
Post-exertional malaise: Physically drained or sick after mild activity	2.092	0.063	11092.9	55.3	47.1	45.1	207
Neurological-Sleep: Prolonged Sleep	1.922	0.059	9645.784	48.1	41.6	45.2	37
Official Diagnosis: Autism	2	0.081	11715.03	50.2	52.3	45.2	207
Age: 50-60	2.013	0.049	16092.02	50.4	37	45.4	142
Official Diagnosis: Chronic Fatigue Syndrome (CFS/ME)	2.046	0.052	13112.63	52.8	40.9	45.6	528
Post-exertional malaise: Muscle fatigue after mild physical activity	2.087	0.069	12312.77	54	50.1	45.6	265
Autonomic Manifestations: Orthostatic intolerance	2.087	0.069	14092.74	54.9	49.7	45.7	164
Comorbid: Fibromyalgia	2.099	0.074	18779.22	55.9	53.2	46	107
Neurological: Myoclonic jerks or seizures	1.982	0.053	11801.6	49.9	36.9	46	50
Official Diagnosis: Depression	2.137	0.069	13752.19	57	50.9	46	99
Autonomic Manifestations: bladder dysfunction	1.947	0.064	10480.63	50.3	43.6	46.1	56
Official Diagnosis: Fibromyalgia	2.042	0.071	20205.99	53.1	50.8	46.1	73
Age: 40-50	1.989	0.073	10590.26	50.3	52.1	46.2	216
Joint: Tenderness	2.141	0.074	19366.06	56.4	51.8	46.2	173
Gender: Male	2.066	0.067	14723.23	53.5	49	46.2	507
Post-exertional malaise: Physically tired after minimum exercise	2.053	0.064	13813.96	52.7	47.5	46.2	268
Post-exertional malaise: Worsening of symptoms after mild physical activity	2.1	0.062	12504.35	54.6	46.6	46.4	282
Immune Manifestations: High Altitude Intolerance	1.997	0.067	27233.9	51.5	48	46.5	49
Official Diagnosis: High Blood Pressure (Hypertension)	2.149	0.079	24512.04	56.7	62.8	46.6	27
Comorbid: High Anxiety	2.085	0.066	16472	54.3	47.4	46.6	302
Blood Type: O Positive	2.107	0.061	14366.56	54.8	43.4	46.7	262
Autonomic: Inability to tolerate an upright position	2.119	0.074	16184.94	56.3	50.2	47	136
Official Diagnosis: Autoimmune Disease	2.217	0.069	18238.23	59.4	49.8	47.3	184
Comorbid: Methylation issues (MTHFR)	2.158	0.066	11514.35	57.8	52	47.3	113
Comorbid: Restless Leg	2.071	0.065	10681.73	54.5	48.8	47.4	93
Official Diagnosis: Mood Disorders	2.294	0.074	10430.17	62.8	57.7	47.6	54
Immune Manifestations: Inflammation (General)	2.087	0.071	16527.17	54.1	51.9	47.6	277
Onset: less than 32 years since onset	2.053	0.063	12146.14	51.7	52.7	47.6	70
Neurological: Dysautonomia	2.025	0.067	14155.11	51.8	46.9	47.8	156
Age: 30-40	2.058	0.066	11989.15	53.1	49.9	48	330
DePaul University Fatigue Questionnaire : Feeling like you have a temperature	1.938	0.074	10889.88	47.3	55.3	48.2	43
DePaul University Fatigue Questionnaire : New trouble with math	2.19	0.072	11232.03	54.9	57.6	48.4	35
DePaul University Fatigue Questionnaire : Chilled or shivery	1.931	0.071	26909.26	46.4	50.9	48.6	47
DePaul University Fatigue Questionnaire : Sweating hands	1.859	0.091	10413.74	42.2	55.8	48.9	27
Official Diagnosis: COVID19 (Long Hauler)	1.617	0.083	10288.01	33.5	54.3	48.9	203
Comorbid-Mouth: Mouth Sores	2.146	0.066	17904.74	55	45.6	48.9	70
Comorbid-Mouth: Ulcers (mouth)	1.964	0.062	11296.41	49.6	45.9	49	27
Official Diagnosis: Osteoporosis	1.888	0.054	10854.14	47.1	40.8	49	21
Immune: Viral infections with prolonged recovery periods	2.066	0.066	11620.85	53.6	48.8	49	99
Comorbid: Salicylate sensitive	1.529	0.048	10532.92	30.1	37.5	49.1	36
Comorbid: Mood Swings	1.99	0.07	11071.23	48.6	51.5	49.4	97
DePaul University Fatigue Questionnaire : Tingling feeling	1.705	0.072	14165.09	37.1	49.1	49.4	66
Blood Type: O Negative	1.945	0.077	11344.33	47.7	45.4	49.5	30
Comorbid: Electromagnetic Sensitivity (EMF)	2.224	0.065	12963.08	60.2	47.6	49.5	39
Neurological-Sleep: Sleep Reversal	2.225	0.065	10837.67	60.1	53.2	49.6	33
Neuroendocrine Manifestations: Painful menstrual periods	2.145	0.059	11232.21	57.6	45.4	49.6	57
DePaul University Fatigue Questionnaire : Impaired Memory & concentration	2.037	0.069	17173.98	51.4	49.3	49.7	298
Comorbid: Carbohydrate intolerance	1.961	0.061	12491.89	51.1	45.3	49.9	46
DePaul University Fatigue Questionnaire : Frequently get words or numbers in the wrong order	2.095	0.077	12878.05	53	54.6	49.9	56
DePaul University Fatigue Questionnaire : Chest pain	1.966	0.078	13689.93	47.9	55.4	50.3	27
Onset: 1980-1990	2.043	0.047	37107.56	53.8	36.7	50.4	32
DePaul University Fatigue Questionnaire : Poor Appetite	1.949	0.054	14012.92	48.5	43.7	50.5	37
Official Diagnosis: Attention deficit hyperactivity disorder (ADHD)	2.081	0.078	11843.49	55.1	54.8	50.5	80
Comorbid-Mouth: Periradicular periodontitis inflammatory / chronic lesion around roots of teeth	2.031	0.048	11195.24	54.4	38.9	50.6	25
DePaul University Fatigue Questionnaire : Nausea	1.856	0.074	12353	44.3	51.8	50.7	63
Physical: Eastern European	1.71	0.057	11299.21	36.8	45.9	50.8	34
DePaul University Fatigue Questionnaire : Difficulty reasoning things out	1.955	0.078	11585.79	48	52.9	50.9	79
Joint: Redness	2.274	0.072	22181.72	61.8	50	51	46
DePaul University Fatigue Questionnaire : Blurred Vision	1.766	0.062	11329.24	39.4	45.9	51	62
DePaul University Fatigue Questionnaire : Difficulty falling asleep	2.024	0.08	12073.2	50.1	53.8	51	133
DePaul University Fatigue Questionnaire : Unrefreshing Sleep, that is waking up feeling tired	2.062	0.068	16938.43	52	48.9	51.4	334
DePaul University Fatigue Questionnaire : Racing heart	1.953	0.075	22527.55	46.7	51.5	51.4	67
DePaul University Fatigue Questionnaire : Feel unsteady on feet	2.026	0.057	13562.46	50.1	37.9	51.9	41
DePaul University Fatigue Questionnaire : Fatigue	2.093	0.067	16345.97	53.2	48.8	52.1	380
DePaul University Fatigue Questionnaire : Muscle Pain (i.e., sensations of pain or aching in your muscles. This does not include weakness or pain in other areas such as joints)	1.968	0.072	20265.4	47.3	53.1	52.2	117
General: Heavy feeling in arms and legs	2.066	0.066	12763.22	53.3	48.9	52.3	104
DePaul University Fatigue Questionnaire : Upset stomach	1.839	0.07	21705.82	42.8	47.5	52.3	79
DePaul University Fatigue Questionnaire : Weight change	2.006	0.067	11665.45	50.4	50.4	52.5	60
DePaul University Fatigue Questionnaire : Pain in Multiple Joints without Swelling or Redness	1.946	0.06	15796.95	46.6	49.3	52.5	74
Autism: More Inappropriate Social Interaction	2.086	0.086	11929.54	54.1	54.1	52.6	24
Comorbid: Constipation and Diarrohea (not explosions)	1.957	0.063	12512.67	48.7	48	52.7	98
Comorbid: Sleep Apnea Diagnosis	2.054	0.059	41891.19	52.7	47.8	52.7	47
DePaul University Fatigue Questionnaire : Difficulty retaining information	2.028	0.066	18395.93	50.8	48.6	53	134
DePaul University Fatigue Questionnaire : Mood swings	2.14	0.073	12088.44	53.3	52.2	53.2	81
DePaul University Fatigue Questionnaire : Shortness of breath	2.031	0.072	12631.27	49.1	47.8	53.2	71
DePaul University Fatigue Questionnaire : Difficulty recalling information	1.98	0.067	17335.97	49	49.5	53.2	152
DePaul University Fatigue Questionnaire : Eye pain	1.881	0.051	16658.33	43.1	42.9	53.3	60
DePaul University Fatigue Questionnaire : Headaches	1.938	0.077	21075.7	46.7	51.7	53.3	97
Physical: Long term antibiotics(over 6 months)	1.953	0.082	13398.78	47.4	62.5	53.3	32
Comorbid: Migraine	2.07	0.072	18043.71	51.2	50.5	53.4	90
DePaul University Fatigue Questionnaire : Sore Throat	1.964	0.068	14178.04	48.4	45.3	53.5	57
Physical: Long term (chronic) stress	1.849	0.06	19406.05	43.2	46.1	53.5	102
DePaul University Fatigue Questionnaire : Forgetting what you are trying to say	2.039	0.069	18515.81	50.3	51.4	53.6	122
DePaul University Fatigue Questionnaire : Night sweats	2.038	0.068	12137.17	49.1	47.1	53.8	46
DePaul University Fatigue Questionnaire : Frequently loose train of thought	2.105	0.079	12781.15	53.7	57.3	53.8	107
DePaul University Fatigue Questionnaire : Difficulty following things	1.995	0.08	13048.19	49	53.9	54	89
DePaul University Fatigue Questionnaire : Depression	2.069	0.065	19883.27	52.7	49.7	54	99
DePaul University Fatigue Questionnaire : Allergies	1.921	0.059	12296.65	47.2	45.5	54	141
DePaul University Fatigue Questionnaire : Difficulty comprehending Information	1.972	0.083	12479.67	47.7	54.4	54.1	121
DePaul University Fatigue Questionnaire : Abdomen pain	1.958	0.074	22318.12	48.2	53	54.2	78
DePaul University Fatigue Questionnaire : Hot or Cold spells	1.935	0.065	23234.88	47.4	45.4	54.2	68
Blood Type: A Positive	2.167	0.078	16858.1	55.6	53	54.2	112
DePaul University Fatigue Questionnaire : Muscle weakness	1.958	0.066	12329.4	47.8	49.4	54.2	123
DePaul University Fatigue Questionnaire : Sensitivity to Alcohol	2.056	0.065	16243.8	51.6	46.2	54.3	98
DePaul University Fatigue Questionnaire : Difficulty finding the right word	2.031	0.069	17169.14	50.8	49.8	54.4	181
DePaul University Fatigue Questionnaire : Does physical activity make you feel worse	2.04	0.059	17569.78	51.4	47.2	54.5	160
Physical: Steps Per Day 2000-4000	1.898	0.057	12403.9	45.5	41.9	54.7	69
Physical: Northern European	1.847	0.062	13131.31	43.2	44.9	54.7	116
DePaul University Fatigue Questionnaire : Temperature lower than normal	2.05	0.06	13048.24	50.3	44.8	54.8	63
Comorbid: Sugars cause sleep or cognitive issues	1.988	0.071	14434.56	51.9	54.8	54.8	32
DePaul University Fatigue Questionnaire : Difficulty staying asleep	2.135	0.065	18877.49	54	48.8	54.9	141
Age: 0-10	2.083	0.116	14335.89	55.4	62.6	54.9	87
Official Diagnosis: Celiac Disease	2.036	0.08	20864.15	51.1	54.9	55	34
Condition: Acne	1.926	0.055	18545.04	47.3	45.1	55.1	80
DePaul University Fatigue Questionnaire : Walking up early in the morning (e.g. 3AM)	2.136	0.06	21152.2	54.3	47.7	55.1	102
Autism: More deficits in Language Comprehension	2.118	0.093	12237.69	55.8	60.2	55.1	35
DePaul University Fatigue Questionnaire : Confusion/disorientation	1.905	0.075	12532.17	45.7	53.7	55.1	60
DePaul University Fatigue Questionnaire : Need to nap during each day	1.869	0.065	25116.62	44.8	47.6	55.3	85
DePaul University Fatigue Questionnaire : Trouble expressing thoughts	2.048	0.079	12709.91	50.5	56	55.3	91
Autism: More Decrease in Speaking	1.956	0.089	11878.78	49.8	52.4	55.4	41
DePaul University Fatigue Questionnaire : Tense muscles	1.884	0.065	21790.03	45.6	46.9	55.5	81
DePaul University Fatigue Questionnaire : Post-exertional malaise, feeling worse after doing activities that require either physical or mental exertion	2.044	0.064	13295.65	50.9	49.3	55.5	191
Condition: Non-alcoholic Fatty Liver Disease	1.927	0.071	12291.76	48.4	49	55.7	29
DePaul University Fatigue Questionnaire : Rash	2.141	0.07	12809.34	56	49	55.9	41
Condition: Post-Traumatic Stress Disorder	2.073	0.066	13172	52.1	51.4	56.1	61
Autism: More Avoidance of Eye Contact or Poor Eye Contact	1.954	0.087	14132.08	49.9	52.4	56.2	26
Condition: ME/CFS with IBS	1.941	0.064	21176.43	47.6	46.6	56.2	146
DePaul University Fatigue Questionnaire : Absent-mindedness	2.006	0.07	19498.31	49.6	52	56.2	119
Autism: More Behavioral Disturbances	2.381	0.105	13815.91	66.7	63.9	56.3	23
Condition: ME/CFS without IBS	1.984	0.062	12510.58	49.1	45.9	56.4	89
Physical: Paleo Diet	1.768	0.038	12820.74	40.5	31.5	56.5	23
DePaul University Fatigue Questionnaire : Slowness of thought	1.941	0.07	12898.63	46.8	49.4	56.6	104
DePaul University Fatigue Questionnaire : Abnormal sensitivity to light	2.014	0.069	14154	48.9	49.3	56.7	102
Official Diagnosis: Gastroesophageal reflux disease (GERD)	2.015	0.057	19077.8	51.7	44.8	56.7	65
Autism: More Sleep Disturbances	2.136	0.084	13719.14	56.2	55.9	56.8	36
Physical: Good Air Quality	1.715	0.055	12224.21	37.6	42.9	56.8	29
DePaul University Fatigue Questionnaire : Need to have to focus on one thing at a time	1.949	0.061	13809.39	48.2	45.6	56.8	120
Physical: Steps Per Day 4000-8000	1.913	0.066	12897.58	45.5	47.1	57	60
Autism: More Repetitive Movements	2.038	0.105	12658.48	53.6	62.3	57	29
DePaul University Fatigue Questionnaire : Ringing in the Ears	1.998	0.062	20337.6	48.4	47.5	57.2	126
DePaul University Fatigue Questionnaire : Dizziness	1.983	0.066	14162.57	46.5	48.5	57.3	65
DePaul University Fatigue Questionnaire : Chemical sensitivity	2.221	0.066	14833.72	57.1	48.5	57.3	79
DePaul University Fatigue Questionnaire : Anxiety/tension	2.037	0.067	18111.31	51.4	49.2	57.5	159
Autism: More Intense Focus on One Topic	2.355	0.059	15148.77	63.7	47.7	57.5	22
Physical: Tonsils removed	2.077	0.069	13512.92	54.6	45.4	57.7	49
General: Anhedonia (inability to feel pleasure)	1.983	0.069	16245.07	47.5	54.1	57.8	27
DePaul University Fatigue Questionnaire : Poor hand to eye coodination	2.329	0.07	14096.38	57.2	52.1	58	21
Condition: Psoriasis	2.174	0.08	26532.52	56.8	54.4	58.2	33
Neuroendocrine Manifestations: Poor gut motility	1.888	0.067	19063.31	44.1	48.4	58.3	133
DePaul University Fatigue Questionnaire : Concern with driving	2.084	0.053	13892.65	53.3	43.1	58.3	40
DePaul University Fatigue Questionnaire : Easily irritated	2.077	0.07	15797.35	52.6	51.3	58.4	142
Physical: Work-Sitting	1.924	0.062	18699.64	46.1	45.2	58.5	139
Physical: Breastfed	2.17	0.049	16236.93	54.1	41.1	58.8	73
Neurocognitive: Aphantasia ( inability to visualize mental images)	1.939	0.078	14582.46	47.7	57.4	58.8	26
Official Diagnosis: Hypercholesterolemia (High Cholesterol)	2.034	0.063	13217.88	50.9	48	59.2	40
Condition: Non-Celiac Gluten Sensitivity	2.019	0.057	13551.54	50.2	44.8	59.4	78
DePaul University Fatigue Questionnaire : Slow to react	2.113	0.07	14951.93	52.7	51.2	59.4	75
Condition: Asthma	2.202	0.071	14193.31	56.9	55.2	59.5	32
Physical: Steps Per Day 8000-16000	2.18	0.063	19185.95	55.5	47.8	60.1	37
Immune Manifestations: Chronic Flatus / Flatulence / gas	2.058	0.071	22413	52.4	49.4	60.2	98
Physical: Amalgam fillings	2.108	0.055	29287.59	54.2	39.9	60.4	49
Condition: Generalized anxiety disorder	2.183	0.077	39061	57.5	54.7	60.5	45
Physical: Appendix removed	2.159	0.052	19123.71	55.6	42	60.8	28
Physical: Pets	2.122	0.068	24978.46	53.6	45.7	60.8	90
DePaul University Fatigue Questionnaire : Does physical activity make you feel better	1.909	0.07	20720.16	47.4	51.9	61.3	38
Autism: High Functioning	2.383	0.061	15824.14	66.9	46.5	61.3	42
Physical: Steps Per Day < 2000	1.998	0.056	16104.52	49.7	42.5	61.5	63
Comorbid: Panic Attacks	2.194	0.073	32169.33	57	50.3	62.3	48
Official Diagnosis: COVID19 (Fully Recovered)	2.09	0.058	15757.67	52.4	47.1	62.4	27
Condition: Osteoarthritis	1.892	0.057	14280.87	48.6	44	63.1	23
Physical: Organic Diet	2.131	0.071	26542.31	53.6	46	63.5	65
Immune Manifestations: Hyperphagia (abnormally hunger or desire to eat)	2.01	0.051	14582.67	49.9	43.5	63.7	21

People who have read my blogs over the last few decades know that I keep to direct evidence; I avoid speculation and “I figure things work this way” thinking. Microbiome tests is a key part of it. My preference is to get as much data as is affordable/reasonable. This is typically my Bacteria Reported/Cost ratio. At the moment, Thorne is the distinctive winner.

Another data source can be smart watches. I have written about this in the past, Monitoring watch for CFS and other Conditions [2021]. After two years, my watch suffered failure on the charging toggle; so time to get a new one — what I got is described below. Every year features increases on smart watches. My first watch took only a few measurements and only on the hour.

Not Prestige Watches

I could go Apple Watch ($400), Fitbit ($300), Samsung ($450) etc. and drop a few hundred dollars for a device that will likely be technologically obsolete in 2 years. Or go with a Chinese model that costs $40 and which will last 2 years or more. In many cases, the key sensors may be the same as used in the prestige models. In some cases, these Chinese watches have features not available on the prestige watches.

Accuracy/Medical Grade is NOT the purpose

I use the watch to detect differences. In general, I find the results are reasonably accurate when I compare to standalone devices.

For most people (especially those with brain fog), their memory is poor and often they do not feel there was any change based on subjective memory. Having daily history going back months allows you to get objective measurements of things that change. Hopefully, it will stop you from ceasing something that is actually helping. Remember, I am very objective evidence based.

Review of my latest watch

You can find them on Temu or Banggoods. My model is E500. Once I got mine, my wife wanted to upgrade to the same model and did.

The screens

How many steps today and hours of sleep with details below

Then Heart Rate, BP and ECG (manually done)

Some Drill Down Details

Sleep Quality is often influenced by the Microbiome

Having daily detail breakdown is sweet!

The heart rate also maps activities (such as steps) providing better understanding!

With a good summary

Blood Pressure is every 5 minutes. With the other data, if there is a spike, you have enough other measurement to evaluate the events and causes.

Oxygen Measurement is far better than a finger device!

And more details

HRV – Heart Rate Variability

With simple summary and ratings

Below is an example from a day that I was pushing myself for physical activity more than usual (some who use the term “out of shape”). Fatigue was definitely happening!

Night Sweats

At present, I do have night sweats — the temperature monitor definitely show it. They start about 3 hours after going to bed and stops when I wake. As is common for people with ME/CFS (including those that are recovered), I have below normal temperatures.

Blood Glucose Levels

This can be very good to determine how well your meals are handled by your body

Bottom Line — Concrete, Detailed Objective Data!

There is a little overhead. I usually do periodic screen captures on my phone and off load the images to my PC so I can compare what was to what is.

This study Microbial patterns in patients with histamine intolerance. Journal of physiology and pharmacology : an official journal of the Polish Physiological Society 2018 reports low Bifidobacteriaceae (NCBI:31953). The Artificial Intelligence Algorithms on Microbiome Prescription (and most medical professionals) would suggest Bifidobacterium probiotics as a possible treatment. Unfortunately, very few medical professionals outside of Poland would have read the above study!

I decided to look at the literature to see if the AI suggestions have been validated by actual studies. This is a few of the studies that I found (the ones where the title alone is sufficient):

• Combined IgE neutralization and Bifidobacterium longum supplementation reduces the allergic response in models of food allergy. [2022]
• Bifidobacterium longum IM55 and Lactobacillus plantarum IM76 alleviate allergic rhinitis in mice by restoring Th2/Treg imbalance and gut microbiota disturbance. [2019]
• Expression and Purification of Extracellular Solute-Binding Protein (ESBP) in Escherichia coli, the Extracellular Protein Derived from Bifidobacterium longum KACC 91563.[2019] ” it was demonstrated that the protein effectively alleviated food allergy symptoms via mast cell specific apoptosis, “
• Post-sensitization administration of non-digestible oligosaccharides and Bifidobacterium breve M-16V reduces allergic symptoms in mice. [2016]
• Three Novel Candidate Probiotic Strains with Prophylactic Properties in a Murine Model of Cow’s Milk Allergy [2016] One of these was Bifidobacterium longum subsp. infantis
• Extracellular vesicle-derived protein from Bifidobacterium longum alleviates food allergy through mast cell suppression.[2016]
• Longitudinal study of effects of oral dosage of Bifidobacterium bifidum G9-1 on Japanese cedar pollen-induced allergic nasal symptoms in guinea pigs. [2015]
• Bifidobacterium breve and Lactobacillus rhamnosus treatment is as effective as budesonide at reducing inflammation in a murine model for chronic asthma.[2014]
• The combination of Bifidobacterium breve with non-digestible oligosaccharides suppresses airway inflammation in a murine model for chronic asthma.[2014]
• Bifidobacterium longum lysate, a new ingredient for reactive skin. [2010]
• Effect of oral probiotics (Bifidobacterium lactis AD011 and Lactobacillus acidophilus AD031) administration on ovalbumin-induced food allergy mouse model. [2008]

Bottom Line

Bifidobacterium Longum appears to be the best researched and easily available as a single species. Different species of probiotics can cause a different response — so keep to single species probiotics and avoid probiotic mixtures as a general rule. My personal favorite source is Custom Probiotics (no financial interest), they are:

• by far the cheapest per BCFU,
• his recommended daily dosages are at therapeutic levels (80- 320 BCFU per day)
• his recommended method of taking is, IMHO, the correct way: NOT IN CAPSULES, but in a glass of water so it impacts the entire system from the mouth downwards (see 24 Years of ME/CFS with Mouth Microbiome for more information and studies)

Watch out for shooting yourself in the Microbiome!

Often I have encounter people frustrated over their inability to increase bifidobacterium or Lactobacillus. When they disclose what they are also taking — it becomes apparent why!

Going to Details about Bifidobacterium: NCBI 1678 we see what increases or decrease it. You may wish to consider reducing or eliminating these items.

General Substance	Specific Substance	Effect
Herb or Spice	ascophyllum nodosum (sea weed)	Studies report Decreases in consensus
Herb or Spice	berberine	Studies report Decreases in consensus
Herb or Spice	Curcumin	Studies report Decreases in consensus
Herb or Spice	galla chinensis (herb)	Studies report Decreases in consensus
Herb or Spice	garlic (allium sativum)	Studies report Decreases in consensus

General Substance	Specific Substance	Effect
Amino Acid and similar	Leonurine	Studies report Decreases in consensus
Amino Acid and similar	melatonin supplement	Studies report Decreases in consensus

General Substance	Specific Substance	Effect
Diet Style	animal-based diet	Studies report Decreases in consensus
Diet Style	gluten-free diet	Studies report Decreases in consensus
Diet Style	high beef diet	Studies report Decreases in consensus
Diet Style	high-fat diets	Studies report Decreases in consensus
Diet Style	high-protein diet	Studies report Decreases in consensus
Diet Style	high-saturated fat diet	Studies report Decreases in consensus
Diet Style	lacto-ovo-vegetarian diet	Studies report Decreases in consensus
Diet Style	low carbohydrate diet	Studies report Decreases in consensus
Diet Style	low fodmap diet	Studies report Decreases in consensus
Diet Style	low-fat diets	Studies report Decreases in consensus
Diet Style	magnesium-deficient diet	Studies report Decreases in consensus

General Substance	Specific Substance	Effect
Vitamins, Minerals and similar	Ferric citrate	Studies report Decreases in consensus
Vitamins, Minerals and similar	fluorine (i.e. tooth paste)	Studies report Decreases in consensus
Vitamins, Minerals and similar	folic acid,(supplement Vitamin B9)	Studies report Decreases in consensus
Vitamins, Minerals and similar	pyridoxine hydrochloride (vitamin B6)	Studies report Decreases in consensus
Vitamins, Minerals and similar	retinoic acid,(Vitamin A derivative)	Studies report Decreases in consensus
Vitamins, Minerals and similar	thiamine hydrochloride (vitamin B1)	Studies report Decreases in consensus
Vitamins, Minerals and similar	Vitamin B-12	Studies report Decreases in consensus
Vitamins, Minerals and similar	vitamin b3 (niacin)	Studies report Decreases in consensus
Vitamins, Minerals and similar	vitamin b7 biotin (supplement) (vitamin B7)	Studies report Decreases in consensus
Vitamins, Minerals and similar	Vitamin C (ascorbic acid)	Studies report Decreases in

The beef/protein diet are high in B-vitamins – thus very logical that both groups decreases.

A reader email me informing me that Microba no longer supplies 4 files, just one — Species. So no Phylum, Family or Genus information. I have modified the upload to handle just having one file available for whatever usefulness is possible.

A Long Time Pain

Microba does not provide data with the official NCBI Taxon numbers (which is what drives Microbiome Prescription AI). This means having to do name match over 3,635,527 different names on the NCBI database. Unfortunately, we still do not find matches, a few examples:

• Pauljensenia MIC9711
• QAMI01 MIC9451
• Ruminiclostridium_C sp000435295
• UBA1191 MIC6579
• UBA1191 MIC9444

Getting more information usually result in this from Google:

I have written them in the past hoping they would be more willing to cooperate. No luck.

What is Available

When you look at the microbiome tree, you will see values only for species. Everything else is 0. It is impossible to accurately estimate genus etc from species alone.

Prior, we would see something like this:

And you will get nothing from Dr. Jason Hawrelak Recommendations. Only one species is in it.

On the positive side, you will still get reasonably accurate KEGG based data (since that is based on species).

“Just Give Me Suggestions” will still work to some extent. Other suggestions can be tricky. The AI will work to the extent of the data available (which is greatly reduced compared to Thorne, Ombre or Biomesight).

Bottom Line

For those people in Australia, I would suggest moving over to BiomeSight, you will likely get six times more data at a lower cost.

A reader wrote:

How does having Ehrlichia and Rickettsia in high values in the sample correspond to having these Lyme coinfections systemically? These are fairly common to see in the sample but my values are very high 96 and 99%.

From a reader

What is he talking about?

Ehrlichia is a genus of Rickettsiales bacteria that are transmitted to vertebrates by ticks. These bacteria cause the disease ehrlichiosis, which is considered zoonotic, because the main reservoirs for the disease are animals… Originally called Rickettsia ruminantium, and is currently named Ehrlichia ruminantium. [Wikipeadia]

Rickettsia is the name of a single genus, …Many new strains or species of Rickettsia are described each year… Some Rickettsia species are pathogens of medical and veterinary interest, but many Rickettsia are non-pathogenic to vertebrates, including humans[Wikipedia]

He mentions they are common to see, let us look at the upload stats. From Ehrlichia: NCBI 943

And looking at Rickettsia: NCBI 780

The microbiome raises Yellow Flags only

For both of the above, the species or strains you have may be non-pathogenic (or even you are not susceptible to them). There are two steps that should be considered:

• Do you have any symptoms for either condition?
  • See Ehrlichiosis
  • See Rickettsiosis
• If you have symptoms — then take the microbiome results to your MD quickly and ask for further testing (the above pages enumerates the appropriate tests)
• If you do not have any symptoms, then for your next regular appointment, mention this — your MD may or may not do tests. Typically some symptoms is needed to justify the testing cost to insurance.

Is the Microbiome a Leading or Trailing Indicator?

A leading indicator is one that has the microbiome shifting before the diagnosis is usually done. This could be viewed as the microbiome shift feeding the condition. A trailing indicator means that the condition develop and then the microbiome changes.

We so not know the answer. I tend to favor it being a leading indicator, thus, when the shifts are towards a known condition then you can take action and either slow the progression or prevent it. Since the main mechanism (diet change) is extremely safe and usually very affordable — it appears to be rational.

Back Story

My history is:

• currently 56 years old
• CFS started at age 32 after a bad cold
• I’ve had bloating and burping since hospitalized as a child for a lump on my throat. I received antibiotics at this time
• I went into 80% remission for about 6 years from age 50-56. I don’t know what did it but I was on a low FODMAPS diet and started using hydrogen peroxide as a mouth rinse

• Symptoms
  • in addition to the bloating and burping I have the following symptoms
  • fatigue
  • sometimes a numb feeling in parts of my hands and feet
  • orthostatic intolerance (although I did the tilt table test and tested negative)
  • halitosis
  • tinnitus
  • a strange feeling in my head
  • shortness of breath

I took inulin before my remission and my symptoms intensified immensely (especially burping and fatigue and shortness of breath)

I had a culture of my upper duodenum done in 2013 and it showed 10000CFU/ml of rothia, prevotella melaninogenica and streptococci viridins. A recent Bristle Health oral biome test showed the prevotella melaninogenica in the 90th percentile

Analysis

I was not surprised about getting ME/CFS after a cold. Cold virus include COVID which can cause Long COVID — a sibling of ME/CFS. The wrong cold virus combined with other catalysts can send someone down that path.

First, I look at the distribution of percentiles. A normal/typical microbiome should have the same count (percentage) in each of the 10%ile. As is often seen with ME/CFS and Long COVID, we have a major overrepresentation of the 0-9%ile — 4x the count of most other groups.

Percentile	Genus	Species
0 – 9	62	89
10 – 19	14	22
20 – 29	15	22
30 – 39	16	16
40 – 49	15	19
50 – 59	20	25
60 – 69	10	14
70 – 79	18	22
80 – 89	20	17
90 – 99	21	35

I interpret this as a host, “a mafia”, of odd bacteria that cross support each other and pumps disrupting metabolites (chemicals) into the body. Thus it is not a bacteria(person) that causes the problems but a big gang of bacteria.

There was not a strong bacteria that predominate this shift, Phocaeicola massiliensis was the only candidate. Looking at Potential Medical Conditions Detected, there were no significant matches (not surprising with an abundance of low percentile bacteria).

Bacteria deemed unhealthy is a pretty long list.

Looking at Dr. Jason Hawrelak Recommendations, we see several that are usually low percentiles that are too too low. These include: Bifidobacterium, Lactobacillus, Methanobrevibacter, Roseburia and Faecalibacterium prausnitzii.

Taxonomy	Rank	Low	High	Your Value	Status
Bacteroidia	class	0	35	37.564	Not Ideal
Akkermansia	genus	1	3	3.225	Not Ideal
Bacteroides	genus	0	20	29.183	Not Ideal
Bifidobacterium	genus	2.5	5	0.015	Not Ideal
Blautia	genus	5	10	6.53	Ideal
Desulfovibrio	genus	0	0.25	0.149	Ideal
Eubacterium	genus	0	15	0.006	Ideal
Lactobacillus	genus	0.01	1	0.002	Not Ideal
Methanobrevibacter	genus	0.0001	0.02	0	Not Ideal
Roseburia	genus	5	10	1.154	Not Ideal
Ruminococcus	genus	0	15	3.9	Ideal
Proteobacteria	phylum	0	4	3.09	Ideal
Bilophila wadsworthia	species	0	0.25	0.575	Not Ideal
Escherichia coli	species	0	0.01	0.006	Ideal
Faecalibacterium prausnitzii	species	10	15	5.159	Not Ideal

Looking at some of the conditions we see a marginally better match for Long COVID than for ME/CFS! Not sufficient to ascribe to a cold virus as the onset cause, but interesting.

• Long COVID   (62 %ile) 16 of 204
• Chronic Fatigue Syndrome   (60 %ile) 4 of 64

Going over to our special studies, we see Long COVID is the best match

Bristle Health Results

This is the first time that I have seen this report. It is a mouth test from BristleHealth.com (good name, better then ToothBrushHealth!). I have pointed out the importance of the mouth in prior posts: A mouth full – for better or worst [2014] and Your mouth can trigger flares[2017].

It provides information on selected strains by role:

As an exercise to understand the “end-to-end” process (literally), I have created the table below. Since the data is by species we have an issue of different tests reporting different species. For more details see The taxonomy nightmare before Christmas… The * indicate that there was no match at the strain level, so we use the genus as a proxy.

First thing to remember is that bacteria is pH sensitive so the quantity in each location is expected to be very different.

Bacteria	Bristle	Percentile
Actinomyces dentalis	1.8	90	*
Actinomyces graevenitzii	1.9	90	*
Actinomyces odontolyticus	0.4	90	*
Atopobium parvulum	6.8	69	*
Atopobium sp	8	69	*
Campylobacter concisus	5.2	98	*
Campylobacter gracilis	5.1	98	*
Candida albicans	1.8
Candida dubliniensis	1.5
Candida glabrata	2.2
Candida sp	1.1
Capnocytophaga granulosa	7.3
Capnocytophaga sputigena	0.19		*
Capnocytophaga sp	0.18		*
Corynebacterium matruchotii	8.3	86	*
Dialister micraerophilus	0.4	94	*
Eikenella corrodens	2.6
Enterobacter cloacae	2.5
Fusobacterium nucleatum	1.9	19
Fusobacterium sp	0.3	92
Gemella haemolysans	1.8	48	*
Gemella morbillorum	0.12	48	*
Granulicatella adiacens (30%)	4.8	15
Haemophilus haemolyticus	4.8
Haemophilus parainfluenzae	7.2
Haemophilus pittmaniae	0.79
Helicobacter pylori	2.3	61	*
Lactobacillus fermentum	3.5	5	*
Leptotrichia trevisanii	0.99
Megasphera micronuciformis	8.5	24	*
Neisseria elongata	0.15		*
Neisseria flavescens	2.1
Neisseria mucosa	3
Neisseria subflava	1
Oribacterium sp	0.098	26
Porphyromonas sp	2	100
Porphyromonas catoniae	0.27	100	*
Prevotella sp	10	73
Prevotella fusca	2.2	73	*
Prevotella histolica	9.5	73	*
Prevotella loescheii	1.6	1
Prevotella melaninogenica	9	73	*
Prevotella pallens	0.1	73	*
Prevotella salivae	8.8	73	*
Prevotella tannerae	0.56	73	*
Prevotella veroalis	7.5	73	*
Propionibacterium acidifaciens	2.1
Rothia aeria	0.8
Rothia mucilaginosa	5.2
Selenomonas noxia	4.4	72	*
Solobacterium moorei	0.3	89
Stomatobaculum longum	0.18
Streptococcus constellatus	2.7	48	*
Streptococcus infantis	7.9	48	*
Streptococcus intermedius	1.9	0
Streptococcus mitis	7.8	48	*
Streptococcus oralis	7.2	1
Streptococcus parasanguinis	1.3	49
Streptococcus peroris	1.6	48	*
Streptococcus salivarius	5	48	*
Streptococcus sanguinis	2	48	*
Streptococcus tigurinus	8.7	48	*
Tannerella sp	0.88
Treponema sp	0.73
Veillonella atypica	8.5	18
Veillonella dispar	7.5	18	*
Veillonella sp	2.7	18	*

I noticed something interesting with strains that were in both samples.

• Solobacterium moorei in both. It occurs only is 14% of Biomesight samples.
• Streptococcus parasanguinis in both. It occurs only is 59% of Biomesight samples.
• Streptococcus oralis in both. It occurs only is 53% of Biomesight samples.
• Streptococcus intermedius in both. It occurs only is 13% of Biomesight samples.
• Prevotella loescheii in both. It occurs only is 15% of Biomesight samples.
• Granulicatella adiacens in both. It occurs only is 30% of Biomesight samples.
• Fusobacterium nucleatum in both. It occurs only is 11% of Biomesight samples.

My subjective conclusion is that this strongly supports the hypothesis that the mouth microbiome feeds the microbiome of the rest of the digestive track. We have 4 rare strains in the above list of 7 where only 1 would be expected to be below 14% (1 in 7).

We can get suggestions for the mouth approximately by using this feature and entering by the genus items above 7 for high, 9 for very high or below 3 for low, below 1 for very low.

All Bacteria [Genus] Reported

720 Bacteria

Suggestions include (for mouth) are below. This is an experiment to see how suggestions for the “other end” compares! Values below 0.4 are usually low significance.

There are some subjective issues in entering the contents and getting suggestions. For suggestions, doing parent and/or children can be debated many ways. Some species are low of a genus and others are high… do you mark the genus high, low or normal? It is unclear if the bacteria listed are pure bad or just bad in excess. That is, should anything not zero be deemed too high or only those over 7. Things are not sufficiently cleared from this report. If I get more requests to do analysis of Bristol Health reports, I will invest more time and add a custom manual entry page. I will need to research every single species to know the appropriate handling.

Below is for purposes of illustration only

Avoids include: xylan (prebiotic), lactobacillus plantarum (probiotics), berberine, Cacao, d-ribose

Microbiome Suggestions

The adage “No man can server two master” is good to keep in mind in this scenario.

I did the usual “Just Give Me Suggestions” path since there was nothing that stood out that could require special handling. “Just Give Me Suggestions” obtains 4 sets of suggestions using different logic to try to derive the best suggestions. I will start by taking the above list and see how they rank in terms of the microbiome.

Modifier (Alt Names on Hover)	Mouth Confidence	BiomeSight Confidence
🕮  inulin (prebiotic)	1  📏	-27
walnuts	0.863  📏	6
whole grain diet	0.588	-14
🕮  lactobacillus reuteri (probiotics)	0.471  📏	34
rare meat	0.392	5.6
refined wheat breads	0.392	126
triphala	0.392  📏	-10
Slippery Elm	0.392	49.8

As expected, with my two masters preamble, we have disagreements. All of the mouth items came in as weak suggestions against BiomeSight suggestions (range: -460 to 465), so doing them will likely not have significant impact on the other end’s microbiome.

Back to Microbiome Suggestions, we have in decreasing priority (excluding antibiotics):

• mastic gum (prebiotic)
• lauric acid(fatty acid in coconut oil,in palm kernel oil,)
• garlic (allium sativum)
• N-Acetyl Cysteine (NAC),
• whole-grain barley
• lactobacillus kefiri (NOT KEFIR) – only available in Italy to the best of my knowledge
• rosmarinus officinalis (rosemary)
• Hesperidin (polyphenol)
• thiamine hydrochloride (vitamin B1)
• Vitamin B-12
• ibuprofen
• Arbutin (polyphenol)
• brown rice
• luteolin (flavonoid)
• cinnamon (oil. spice)
• raffinose(sugar beet)
• Nicotine (Nicotine patches?) See this story of a person recovering from using nicotine patches
• vitamin b7 biotin (supplement) (vitamin B7)

And on the to avoid

• ketogenic diet
• berberine
• stevia
• xylan (prebiotic) (as with the mouth)
• mediterranean diet

Looking at Diet Styles, only two are strong indicated, both avoids (listed above).

Food Site

The food site takes the nutrients found and assists in building a food menu plan.

👍	100	Cystine
👍	94.17	Naringin
👍	92.19	Thiamin
👍	90.83	Hesperetin
👍	88.99	Caffeine
👍	86.67	Vitamin B-12
👍	84.71	Vitamin C

For the top one, a nutrient unfamiliar to most people, we see this list to choose from. We See Barley on it. It Barley is a problem, then almond, peanut or pistachio are good alternatives. For Peanuts, I actually did some posts in the ME/CFS context.

• Peanut Butter – a complex food? [2013]
• Peanuts – A recommended part of diet [2015]
• Nuts and Seeds for CFS? [2017]

mg per 100 grams	Food
533600	Pistachio
374500	Almond
358000	Peanut
243500	Fennel
218200	Paprika
200000	Barley

Similarly, Naringin points to Grapefruit (just about the only choice) with rosmarinus officinalis (rosemary) being a vert diminished next choice.

Thiamin is an easy to find vitamin — Vitamin B1

Hesperetin is in Lime, Blond Orange, Lemon and Grapefruit (AGAIN Grapefruit!)

Questions

Q: What testing method is BristleHealth using?

A: “Shotgun microbiome test examples: Bristle (oral microbiome).” [src] Biomesight is using 16s which provides less data. Thorne uses shotgun testing and thus would be a better match.

Q: On cfsremission and/or cort johnsons blog you discussed the importance of breaking down biofilms with things like nac as well as rotating herbs, probiotics and antibiotics. Is that a layer that should be added onto the items selected by microbiomeprescription (I plan to reread those posts before starting).

A: Yes, I have posted about biofilm in the past: Combating an Infection Defense Mechanism: Biofilms [2014] and Probiotic Biofilm Breakers[2016]. It is not a simple matter “Biofilms provide survival sites for both beneficial and opportunistic pathogenic bacteria, by providing protection as above and increasing the potential of the bacteria to survive and evolve” [2013]. It impacts antibiotic resistance [2020]. In other words, we have yin-yang. If you are intending to aggressively reduce bacteria known to use biofilms, especially with antibiotics, then it is a wise choice. In most cases, I would not do it by default. For example, Akkermansia muciniphila and Lactobacillus rhamnosus GG both form biofilms [2020].

Q: What can you suggest to deal with Halitosis (Bad Breath)

A: The bacteria involved are nicely listed in your report.

We will again use All Bacteria [Genus] Reported but deem all of the above to be high (0-5), very high (5+).

In the resulting list we see many items that can be used as teas (which would likely impact the mouth bacteria): triphala, oregano (origanum vulgare, oil) . Items that can be chewed in the mouth: mastic gum .

• I personally use the hard tablets of clostridium butyricum Miyarisan which I allow to dissolve in the mouth

On the avoid: alcoholic beverages (rarely an option with ME/CFS), gluten-free diet, aspartame (sweetener).

The same approach may be done for other mouth bacteria that you wish to eliminate, you should cross check that none of the substance are strong avoid for the “other end”.

More Readings:

• Editorial: Association between oral microbiota dysbiosis and the development of systemic conditions [2023] ” there may be a bidirectional relationship between the oral microbiota and systemic diseases. “
• “The detrimental effects of oral microorganisms are not confined to the oral cavity, they can also contribute to systemic disorders, such as type 2 diabetes mellitus, cardiovascular disease, and inflammatory bowel disease (IBD) (Hajishengallis and Chavakis, 2021). “
• “In the article by Chen et al. the influence of periodontal pathogen infection on gut mycobiome was explored. The authors demonstrated the first evidence of gut fungal dysbiosis with periodontal pathogen administration. “
• The Role of the Oral Microbiota Related to Periodontal Diseases in Anxiety, Mood and Trauma- and Stress-Related Disorders [2021]
• Roles of oral microbiota and oral-gut microbial transmission in hypertension [2023]
• Oral Microbiota: A Major Player in the Diagnosis of Systemic Diseases [2021]

Bottom Line

This person’s microbiome matches the pattern usually seen with ME/CFS and Long COVID. The suggestions are also in general keeping with what has been reported to reduce symptoms. The B-Vitamins are well established. Some other citations, Brain “fog,” inflammation and obesity: key aspects of neuropsychiatric disorders improved by luteolin [2015], Modulation of antigen-induced chronic fatigue in mouse model of water immersion stress by naringin, a polyphenolic antioxidant [2009]

The oral microbiome impacting the entire flow (including SIBO) seems to be well illustrated with this data. The bacteria strains from the Bristle Health report appear to be those known to cause issues in the mouth (and most are not reported on by other tests). This implies that the ideal pair of tests to deal with systemic health issue is likely Bristle Health and Thorne.

Allergies are often tossed into a big box of “all allergies are the same”. I have learnt from studies that often different items are clustered together to avoid needing to learn and detail with the details. I know people that have very specific allergies — i.e. to birch but not grass or other tree pollens. Most MDs will toss such people in the seasonal allergic rhinitis bucket; treating them proforma.

This appears borne out by some studies:

• ” A delayed correlation between the birch pollen concentration and the symptom scores was seen up to two days after the pollen measurement. For grass pollen this effect lasted up to three days after the pollen measurement.”[2023]
• “the most effective treatments for allergic rhinitis were in order as follows: sublingual immunotherapy_dust mite, subcutaneous immunotherapy_dust mite, sublingual immunotherapy_ grass mix plus pollen extract, placebo, and pharmacotherapy. ” [2023] – note that placebo was more effective that traditional medicine!

The goal of this exercise is see if there are any new options or approaches for addressing this issue.

Environment May Be a Factor

Some of my university professors refused to believe that allergic rhinitis existed. They were born and raised in a part of the middle east and never encountered people with it before moving to North America. This saying from the prophet recorded by Salamah b. al-Akwa, implies that allergies may have been unknown in that part of the world:

“When a man sneezed beside the prophet (May peace be upon him), he said to him : Allah have mercy on you, but when he sneezed again, he said : The man has a cold in the head.“

This seen in the following charts: (A) Unspecified rhinitis; (B) allergic rhinitis; (C) non‐allergic rhinitis.

• “A family history of allergic rhinitis, asthma, or atopic dermatitis increases a patient’s risk of being diagnosed with allergic rhinitis. People in the United States are commonly sensitized to grass, dust mites, and ragweed allergens.” [2023]
• “Asthmatic patients from Madrid(urban) have a worse clinical evolution than those from Ciudad Real (rural)because of higher levels of urban pollution,” Clinical impact and immunological alterations in asthmatic patients allergic to grass pollen subjected to high urban pollution in Madrid [2022]
• “Subjects with persistent rhinitis and asthma had higher levels of total IgE at baseline and after 10 years, and exhaled nitric oxide and eosinophil cationic protein at baseline compared with those that remained healthy. ” [2023]
  • Exhaled nitric oxide implies a breath test and thus we have 1135 bacteria the produces this chemical, hence a potential overgrowth as a contributing factor.
  • Eosinophil cationic protein in also in the gastro-intestinal tract[2011]

Treatment Trends

Things here gets a little complex…

B cells are key players in the mechanisms underlying allergic sensitization, allergic reactions, and tolerance to allergens. Allergen-specific immune responses are initiated when peptide:MHCII complexes on dendritic cells are recognized by antigen-specific receptors on T cells followed by interactions between costimulatory molecules on the surfaces of B and T cells. In the presence of IL-4, such T-B cell interactions result in clonal expansion and isotype class-switching to IgE in B cells, which will further differentiate into either memory B cells or PCs. Allergic reactions are then triggered upon cross-linking of IgE-FcɛRI complexes on basophils and mast cells, leading to cell degranulation and the release of pro-inflammatory mediators.Mechanisms underlying effective allergen-specific immunotherapy (AIT) involve the induction of Tregs and the secretion of blocking IgG4 antibodies, which together mediate the onset and maintenance of immune tolerance towards non-hazardous environmental antigens. 

B Cell Functions in the Development of Type I Allergy and Induction of Immune Tolerance [2022]

• Oralair, a biologic, has grown in use in Europe (approved in 2008 from 8% to 29% by 2012 [2015]) and is approved in the USA (2013) Link to FDA documents. It is prescription with a base cost of $5 or more per tablet — hence, antihistamines are more likely to be recommended in the US due to cost, not effectivity.
• Similar items are also available, (2800 BAU grass SLIT-T) [Relative to placebo, grass AIT treatment improved total combined scores by 20% 2011], Grazax [The active group demonstrated a 31% reduction in median rhinoconjunctivitis symptom [2011]], MK-7243. There are not cures, rather reduces severity for a percentage of people.

“The only treatment available to treat grass allergy is immunotherapy treatment. This is when you are exposed to small but increasing doses of allergens over a long period of time to help stop your allergic reaction. It takes a long time to work and needs to be prescribed by an allergy specialist.” Australian Department of Health

Treatment via Microbiome

For grass allergy we have the following available retail with studies which boils down to 2 probiotic species worth considering.

Lactobacillus casei Shirota	Yakult	Oral delivery of Lactobacillus casei Shirota modifies allergen-induced immune responses in allergic rhinitis. [“ Volunteers treated with LcS showed a significant reduction in levels of antigen-induced IL-5, IL-6 and IFN-gamma production compared with volunteers supplemented with placebo. Meanwhile, levels of specific IgG increased and IgE decreased in the probiotic group.”]
Lactobacillus rhamnosus GG	Culturelle®	Effect of Lactobacillus rhamnosus GG and vitamin D supplementation on the immunologic effectiveness of grass-specific sublingual immunotherapy in children with allergy. [“Reduction in the symptom-medication score and improvement in lung function as well as a significant increase in the percentage of ….in all the groups were observed compared with control group”]
Lactobacillus rhamnosus GR-1	RepHresh™ Pro-B™ Probiotic	Development and pilot evaluation of a novel probiotic mixture for the management of seasonal allergic rhinitis. [“provided few clinical benefits.”]
Mutaflor (Escherichia coli strain Nissle 1917)	Mutaflor (Canada, Australia, Findland, Germany)	Tolerability and clinical outcome of coseasonal treatment with Escherichia coli strain Nissle 1917 in grass pollen-allergic subjects. [“not sufficient to achieve clinical efficacy in grass pollen”]

Non-Strain probiotic candidates:

• Bifidobacterium longum [2023], lowers IgE (see below)
• Lacticaseibacillus paracasei [2023] ” 2 billion CFU/day for 3 months ameliorated sneezing”

And this delightful title “Role of Probiotics in Patients with Allergic Rhinitis: A Systematic Review of Systematic Reviews” [2022] found no hard evidence for any specific probiotics.

Bottom Line for Probiotics: It seems that they need to be taken well in advance of allergy season with sufficiently large dosages.

Explorations

I took the list of 1135 bacteria that produces nitric oxide and then looked at the 40 bacteria reported on National Library of Medicine Citations for Allergic Rhinitis (Hay Fever). I was disappointed not to find many matches. What I found were matches for:

• Bacteroides (NCBI:816 )
• Clostridium (NCBI:1485 )
• Acidaminococcus intestini (NCBI:187327 )

Next, I went to samples that are annotated with Official Diagnosis: Allergic Rhinitis (Hay Fever) – about 200 samples, and then cross apply them to the above 1135 bacteria. There are no strong statistical significance found.

Tax_name	Average	Samples
Haemophilus parainfluenzae	56.1	41

Tax_name	Average	Samples
Pelosinus fermentans	60.1	22
Limosilactobacillus fermentum a.k.a. Lactobacillus fermentum	57.7	34
Veillonella atypica	52.9	22
Veillonella dispar	52.7	49

How to do this experiment

• Go to your samples
• Look at Microbiome Tree

• Search for the items above
• Hand pick (if you have any matches)

This exploration failed to produce any significant finding or insights. 🙁

Exploring Immunoglobulin (IgE etc)

As a starting point, Immediate Hypersensitivity Reactions [2023] is of special interest for those who have reactions within 24 hours. “Antibodies including IgE, IgM, and IgG mediate them… Allergic rhinitis is another atopic disease where histamine and leukotrienes are responsible for rhinorrhea, sneezing, and nasal obstruction. ” Typically only IgE is involved. IgE increase in response to grass pollen exposure and are responsible for the allergic symptoms.

• “Patients with pollen allergy but not control donors have a population of circulating allergen-specific B cells with the phenotype and functional properties of adaptive memory B-cell responses. These cells could provide precursors for allergen-specific IgE production upon allergen re-exposure.” [2015] – which implies repeat exposure may increase severity.
• Omalizumab: reduced significant clinical exacerbation within 24 weeks [2023]

FYI On Other Allergies

Mast Cells Issues can be moderated by some Bifidobacterium bacteria (Click for studies).

Bottom Line

Symptom relief via antihistamines or DAO for a subset for immediate response, or months of preparation for allergy season by probiotics and biologics.

DAO levels were lower in AR patients compared with the controls. The DAO level did not significantly correlate with the severity of AR according to the Allergic Rhinitis and its Impact on Asthma (ARIA) score, though it was lower in patients with persistent or moderate to severe symptoms. The total IgE, eosinophil percentage, and SNOT-22 score all had an inverse relationship with DAO.

Predictive Value of the Serum Diamine Oxidase Level in the Diagnosis of Seasonal Allergic Rhinitis [2022]”

Avoidance of Grass Pollen

This is really what the Asthma and Allergy Foundation of America strongly advocates.

Above memory B-cell responses were cited in research which I translate that repeated exposure will make it worse, hence one approach is aggressive avoidance.

• Wearing a N95 or better mask when outside from the start of pollen season onwards. In some cases a full face mask may be better. When you arrive home, do a complete change of clothes as soon as possible (ideally outside) and take a shower.
• Aggressively reduce pollen in your living place (i.e. pollen leaking into the house via windows and open doors)

Our Approach

This household’s solution for grass allergy has been HEPA air filters oversized for the room size. For example, this $90 unit is rated for 183 sq ft. We would use it for 90 sq ft only — the size of a small bathroom (8′ x 10′). A 10x more expensive unit (Austin HEALTHMATE PLUS ) is rated for 1500 sq ft, so we will use it to cover only 750 sq feet. This means that a 2,000 sq ft house would need at least three operating. Note that this intentional oversizing is to reduce the time to remove grass pollen that comes in.

Time to Reduce Pollen from opening a door

The Austin does 400 cubic feet per minute and we can assume that for one complete room exchange that the pollen level will drop by 50%. It will not remove all in one room exchange. You remove 400 cf in a minute and shoves the clean air back into the room — diluting the air that is there. A little calculus finds that after one cycle, we are down 50% only.

Sample Calculation: 750 sq ft x 8 ft ceiling = 6000 cu feet … thus 15 minutes for one exchange with a 400 cfm unit (i.e. the Austin). If we go with manufacture specifications of 1500 sq feet, than 30 minutes to remove half of the pollen.

PPM, or pollen per cubic meter.

Consider a High Grass level at 340. After one room exchange, it would be 170 (still high), after two room exchanges it would be at 85 (still high), after three exchanges down to 43 – moderate, and at 4 exchanges we are at 20 — into the low range at last. In short, after opening a door for a short while, it may take 2 hours for the pollen level to get reduced to acceptable levels.

Conclusion: Keep the doors open for the least amount of time possible. Consider adding automatic door closers to all doors. Windows should not be open and they should be tight seals. A furnace that brings air in from the outside as part of normal operation should have HEPA filters installed on the intake.

We went one step further, we added to our house an air pump that takes air thru a HEPA filter and creates a positive air pressure in the house. This is one way to address leaky doors and windows — instead of pollen leaking in, the positive pressure pushes it away. We originally installed it to address wild fire smoke (works nicely), but this pollen season it has made a noticeable difference.

If you look at my 2018 post “What is the best diet in your opinion?” [repost in 2022], you will find a logic that is simple: your microbiome adapts over generations to the food available. When food choices quickly, issues arise in the microbiome. One known issues:

• “Gut Microbiota: An Important Link between Western Diet and Chronic Diseases” [2019]
• “Effect of ultra-processed diet on gut microbiota and thus its role in neurodegenerative diseases” [2020]

The other day I spotted a non-alcoholic Imperial Pale Ale at Costco and picked up a dozen. During the summer when I am working outside, I like having a cold one when I come inside. Health Canada in 2023 updated their guidance to restrict alcohol use to 2 standard drinks or less per week  with discussion about putting health labels (like tobacco labels) on all drinks. This product tastes like a good IPA, but has no significant alcohol — likely close to the common beer that my ancestors had for breakfast, lunch and dinner.

The light went on! Up until around 1900, beer and ales were common daily drinks –including for children. The reason was simple, water was often deadly due to bacteria in it. Clean drinking water was scarce or unreliable. Milk was fine. Coffee and Tea was fine. Water was not. The beer was not the typical 8% alcohol often seen in American Beers, but 2% or less.

This leads to the speculation that removing regular gluten exposure during childhood — via weak beers and plain-old-school porridge (oats, barley etc.) is the cause of the exploding gluten sensitivity!

It is very likely that gluten sensitivity is connected to diet changes – most of our wheat was breed for specific things, like yield per acre — those changes may contribute too. It is impossible to find clear evidence — but blaming drinking water is an amusing suggestion!

SIBO or Small Intestinal Bacterial Overgrowth was first proposed as a medical condition in 1970. The first use of breath tests for it was around 1974. The key things to remember is that this condition was the naming of a collection of symptoms. The name reflected the speculation on the general cause without any specifics. Over the years, this condition has been broken down in 6 general subsets depending on the results of breath test (and a potential 7th, if the symptoms are there but no positive breath test results).

Assuming that it is a bacteria overgrowth — which bacteria is overgrown? The breath test does not provide evidence on which specific bacteria a person has.

Based on Kyoto Encyclopedia of Genes and Genomes, we see many suspect bacteria. Worse still, it may not be a single species overgrowth but several.

• Hydrogen Levels (H2) – 595 species
• Methane Levels (CH4) – 622 species
• hydrogen sulfide (H2S) – 3817 species

The clinical practice is often applying a simple logic “If it is an overgrowth, we just toss the appropriate antibiotic at it and it is solved!”. Experience has shown that some are generally effective, i.e.

• Rifaximin was 78% effective [2023]
• Amoxicillin (500 mg 3 times a day per, during the first month), followed by ciprofloxacin (500 mg twice a day per, during the second month) and metronidazole (500 mg 3 times a day per, during the third month) about 56% effective [2023]

With effective usually being defined as symptom improvement not remission. Reporting adverse reaction is poorly done.

The reality that using herbs, oil of.. , tinctures, etc. have the same problem as antibiotics. With the evidence above there is not way to determine which ones will be effective for the individual.

There is a recognized and accepted way to better determine the bacteria involved: Small Intestine Aspirate. This is a quasi-surgical procedure to take a sample from the Small Intestine.

The gotcha is the handling of the sample, the treating physician or the lab may do one of several possible things:

• Just report the quantity (confirming an overgrowth) — most common
• Classic culturing of the sample — which will report on the culturable bacteria (most are NOT culturable)
• 16s testing of the sample – better resolution
• Shotgun testing of the sample — best resolution

Cost issues can be complicated by insurance companies not covering the costs in most situations.

The Downstream Proposal

Whatever is in the small bowel or intestine eventually makes it way thru the entire system and ends up in a stool. The amount will likely differ because of passages through multiple environments.

The motivation for this post was a reader telling me that his hydrogen sulfide levels have become a problem. His latest sample had a significant amount of them. This suggests that 16s sampling can be helpful for detecting the species involved and thus treatment suggestions based on the bacteria that appear to be in overgrowth (by virtue of the breath test elements).

The video below takes you through the process.

A Walkthru

Note that the top antibiotics suggested from Microbiome Prescription are those used for treating SIBO.

Suggested Readings

Many older articles have stale information, the following are very recent publications.

• Small-bowel aspiration during upper esophagogastroduodenoscopy: Rao technique [2021]
• Unravelling the controversy with small intestinal bacterial overgrowth [2023]
• Evaluation of small intestinal bacterial overgrowth [2023] “SIBO was conventionally defined as a total bacterial count >100,000 colony forming units (CFU) per mL on quantitative culture of upper gut aspirate. The threshold for the diagnosis of SIBO has been reduced to >1000 CFU per mL of aspirate recently.” That is 100x decrease of the amount need to get the diagnosis!
• Association between Gut Dysbiosis and the Occurrence of SIBO, LIBO, SIFO and IMO [2023] “The subject literature is extensive but of limited quality.”
• Diagnosis by Microbial Culture, Breath Tests and Urinary Excretion Tests, and Treatments of Small Intestinal Bacterial Overgrowth [2023]
• Understanding Our Tests: Hydrogen-Methane Breath Testing to Diagnose Small Intestinal Bacterial Overgrowth [2023]

The Ask

I’ve been reading the cfsremission.com site for a few years now and respect and appreciate your work very much! Today I received results from my first test with Biomesight and have uploaded to microbiomeprescription.com, however I’m struggling to know where to go from here.

It looks like I have high F. prausnitzii which goes against some of the CFS research. I can also see zero E. coli (I think) and low bifidobacteria/lactobacillus, but not sure there are strep/staph/klebsiella/other pathogens which I was expecting to see, owing to my issues with histamine/bloating, am I correct?

I’m reluctant to go ahead with taking herbal antimicrobials as I’m not sure exactly what I should be trying to kill off. The suggestions that come up mostly seem to be fibres/prebiotics which I haven’t typically responded well to in the past (worsened bloating and oily skin).

My backstory:

My issues started with the persistent abdominal bloating and sneezing/nasal congestion about 5 years ago. The bloating never goes away, and now I’ve progressed into a state of moderate but unrelenting fatigue, muscle pain and inflammatory issues (dry eyes, etc.), made worse by COVID and then the Pfizer jab last year which pushed my ’steady state’ in terms of energy to a lower level than it ever has been. I know that the root cause of this all is my gut. For example, I can eat regular yoghurt and the next day I will wake up with a back ache, 50% more tiredness and very sneezy. I did test positive for SIBO around 3 years ago but multiple rounds of rifaximin did nothing to help, neither did herbal antimicrobials. The bloating seems to be inflammatory/mast cell related rather than actual gas.

Symptoms:

• – Crushing fatigue/muscle weakness/PEM (do not have a CFS diagnosis but the symptoms fit)
• – General inflammation/muscle pain
• – Freezing cold hands/feet all the time
• – Sneezing/nasal congestion/itchy throat especially after histamine containing foods
• – Persistant abdominal bloating which never goes away 
• – Brain fog
• – Acne/very oily skin
• – Dry eyes

For other analysis of the microbiome of people with ME/CFS, see this index.

First Questions Researched

Low Faecalibacterium prausnitzii is seen in several studies for ME/CFS. This person’s level is at a huge 23.7% of the microbiome — the 93%ile. However, for ME/CFS sibling (Long COVID) we have two studies reporting high levels for Long COVID (with 4 reporting Low) and three for COVID being high and one being low. In other words — atypical levels are to be expected. Note that he had COVID and then the Pfizer jab – so Long COVID is likely a better diagnosis than ME/CFS (at this point). The two tend to merge over time.

Usual Analysis Approach

The percentile x percentage breakdown shows the typical pattern for ME/CFS and Long COVID: Over representation on the low percentiles and under representation of the high percentiles.

Percentile	Genus	Species
0 – 9	21	22
10 – 19	22	25
20 – 29	18	22
30 – 39	17	18
40 – 49	9	19
50 – 59	16	23
60 – 69	12	14
70 – 79	10	16
80 – 89	9	7
90 – 99	5	9

The likely causes suggested are: Faecalibacterium prausnitzii, Phocaeicola coprocola and Bacteroides stercoris. The top one was already flagged by the reader.

Going over to Dr. Jason Hawrelak Recommendations, we see a lot out of range.

Taxonomy	Rank	Low	High	Your Value	Status
Bacteroidia	class	0	35	37.029	Not Ideal
Akkermansia	genus	1	3	0.003	Not Ideal
Bacteroides	genus	0	20	33.827	Not Ideal
Bifidobacterium	genus	2.5	5	0.349	Not Ideal
Blautia	genus	5	10	4.049	Not Ideal
Desulfovibrio	genus	0	0.25	0.002	Ideal
Eubacterium	genus	0	15	0	Ideal
Lactobacillus	genus	0.01	1	0.002	Not Ideal
Methanobrevibacter	genus	0.0001	0.02	0	Not Ideal
Roseburia	genus	5	10	2.658	Not Ideal
Ruminococcus	genus	0	15	8.32	Ideal
Proteobacteria	phylum	0	4	3.705	Ideal
Bilophila wadsworthia	species	0	0.25	0.265	Not Ideal
Escherichia coli	species	0	0.01	0	Ideal
Faecalibacterium prausnitzii	species	10	15	23.71	Not Ideal
Overall Percentile Ranking	56.5%

Looking at PubMed matches we see that he is somewhere between these two siblings

• Long COVID   (45 %ile) 10 of 204
• COVID-19   (18 %ile) 3 of 118
• Chronic Fatigue Syndrome   (66 %ile) 4 of 64

Going Forward

He wrote “For example, I can eat regular yoghurt and the next day I will wake up with a back ache, 50% more tiredness and very sneezy. ” Most yogurt contains large amount lactobacillus acidophilus (probiotics) which is high on his to avoid list. In general lactobacillus should be avoided with brain fog because many species produces d-lactic acid (See my 2019 post Reminder of D-Lactic acidosis and ME/CFS – which contains the name of bacteria that may contribute to the issue). If you cannot find a yogurt free of these bacteria, you may wish to give yogurt up. I would suggest the following probiotics as likely being good choices:

• bifidobacterium longum bb536 – available in many products
• bifidobacterium breve
• bifidobacterium infantis

He wrote ” multiple rounds of rifaximin did nothing to help, neither did herbal antimicrobials.” Well, that antibiotic is a negative, and like the lactobacillus yogurt above is likely to contribute to the microbiome issues. He did not specify the herbs that he tried.

-75.8

rifaximin (antibiotic)s

Typical herbs used for SIBO [Src] are below. Having no results (or negative results) is not surprising.

• Allicin – positive
• Oregano – positive
• Neem – negative
• Berberine –  negative
• Peppermint – negative

The top herbs suggested

• anise
• eugenol (from clove oil, nutmeg, cinnamon, basil,bay leaf.)
• oregano (origanum vulgare, oil)
• chamomile (chamaemelum nobile)
• tulsi
• garlic (allium sativum)

He wrote “The suggestions that come up mostly seem to be fibres/prebiotics which I haven’t typically responded well to in the past (worsened bloating and oily skin).’ We see that almost all of the prebiotics are below 100 priority (item #170), so they would not make it into my preferred list (I prefer to keep to the to 100 or less). 25% of these are actually below a -200 priority. We also see low fiber diet is high priority. So his experience and the computations are in agreement

Other Items

In terms of common antibiotics for ME/CFS, near the top we see metronidazole (see this 2017 post) and erythromycin (See Azithromycin in Chronic Fatigue Syndrome (CFS), an analysis of clinical data [2006], where 58% improved). If you can persuade your MD to prescribe.

Supplements of note: Taxifolin (See 2021 post dealing with histamine), glutamine (The Role of Glutamine in the Aetiology of the Chronic Fatigue Syndrome [2011] ). Nothing in the flavonoids, polyphenols list stand out. In terms of prefer sugars: chitosan,(sugar),sucralose, raffinose(sugar beet) – most sugars are marginal or negatives. In terms of Vitamins: Iron and magnesium.

Bottom Line

In my years of reviewing literature on ME/CFS, the typical results are similar to the Azithromycin study above: it works for X% of the people and has no or negative effect for the rest. It is my hypothesis/belief that the microbiome determines if a substance works or not.

Above, you see my preferred approach — look at the top 5-10% of suggestions and then cross reference the literature to see which are known to help some. The alternative of working from studies (without reviewing the microbiome) has failed to produce consistent positive results over the decades that it has been tried. The other key item is to look at the bottom 20% of suggestions and eliminate as many of them that you can.

For “Just give me suggestions”, I prefer the priority to be over 150 if possible for takes, and below 0 for avoids.

Remember this is a multiple path journey. Keep on the suggestions for 6-12 weeks and then retest. The suggestions may shift a bit with each course correction.

Postscript – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.

The answers above describe my logic and thinking and is not intended to give advice to this person or any one. Always review with your knowledgeable medical professional.