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Decoding Stool Test Results
Lihong Chen, MD, PhDNovember 3, 2018
Fecal Biomarkers, Commensal Bacteria, and Clinical Applications
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• Director of Clinical Evidence Development at Genova Diagnostics
• All data analyses are based on Genova test results
Disclosure
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• Introduce data-driven, evidence-based, interpretation of stool tests
• Pattern analysis of stool biomarkers
• It is not a literature-based interpretation of stool tests
Objective for This Presentation
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How to Use Stool Test Results?Diagnosis criteria
Case report
Pattern analysis
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Symbiosis in the Gut Depends on Multiple Factors
Lab testing is an integrated component of health assessment
Host EnvironmentalFactors
Microbiome
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Data Source for Analysis
• Calprotectin
• EPX
• sIgA
• Pancreatic elastase-1
• Fecal total fat
• Long-chain fatty acids
• Triglycerides
• Phospholipids
• Cholesterol
• Total short-chain fatty acids
• % Butyrate, acetate, and propionate
• Products of protein breakdown
• beta-glucuronidase
• Bacteroides-Prevotellagroup
• Bacteroides vulgatus
• Barnesiella spp.
• Odoribacter spp.
• Prevotella spp.
• Anaerotruncus colihominis
• Butyrivibrio crossotus
• Clostridium spp.
• Coprococcus eutactus
• Faecalibacteriumprausnitzii
• Lactobacillus spp.
• Pseudoflavonifractor spp.
• Roseburia spp.
• Ruminococcus spp.
• Veillonella spp.
• Bifidobacterium spp.
• Bifidobacterium longum
• Collinsella aerofaciens
• Desulfovibrio piger
• Escherichia coli
• Oxalobacter formigenes
• Methanobrevibactersmithii
• Fusobacterium spp.
• Akkermansia muciniphila
• All Genova GI Effects tests: August 2014 – January 2018 • Total number of tests: 173221
Fecal Biomarkers Commensal Bacteria
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• Questionnaire and lab-qualified healthy cohort
• Questionnaire-based disease cohort
– Irritable bowel syndrome (IBS)
– Inflammatory bowel disease (IBD)
– Type 2 diabetes (T2D)
– Metabolic syndrome (MS)
– Mood disorder (MD)
– Autoimmune (AI)
– Chronic fatigue (CF)
Assessment Based on Comparisons Between Healthy and Unhealthy Groups
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Algorithm-Based Comparison of Commensal Bacteria
healthy IBS
-2
0
2
4
6
8
10
12
cohorts
Healt
hy-P
att
ern
Co
nti
nu
um
healthy IBS
-4
0
4
8
12
16
20
24
cohorts
Refe
ren
ce V
ari
an
ce S
co
re
Healthy-Pattern Continuum Reference Variance Score
Unpublished data
P<0.001
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Different Aspects of the “Same” Profile
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Differential Distribution Between Healthy and IBS Cohorts
Unpublished data
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Differential Distribution Between Healthy and Chronic Fatigue Cohorts
He
alth
y-P
atte
rn C
on
tin
uu
m
Reference Variance Score
Unpublished data
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Differential Distribution Between Healthy and Autoimmune Cohorts
He
alth
y-P
atte
rn C
on
tin
uu
m
Reference Variance Score
Unpublished data
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Patient’s Result is Not Dependent on Specific Bacteria
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• Using algorithm-based profiles of selected commensal bacteria can differentiate healthy and disease cohorts
Summary 1
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Pattern Analyses with All Patients
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Testing “Everything” vs Testing “Something”
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Clustering of Patients Based on Commensal Bacteria Results
Cluster 1High Commensal Abundance
Cluster 2Low Commensal Abundance
High In:
Total fecal fat
Long-chain fatty acids
Phospholipids
Triglycerides
Total SCFAs
Butyrate %
Products of protein breakdown
Beta-glucuronidase
High In:
Calprotectin
EPX
sIgA
Cholesterol
Acetate %
Propionate %
Weighted abundance: Based on the contribution of each bacterial result in determining the clusters
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Commensal Abundance is Correlated to Inflammation/Immune Response
All statistically significant
Unpublished data
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Inflammation is Strongly Associated With Commensal Abundance
Unpublished data
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Subgroups Based on Fecal Calprotectin
Group Number
Calprotectin (mg/g)
Sample #
1 <=20 141913
2 21-40 15418
3 41-60 5603
4 61-80 2889
5 81-120 2776
6 121-200 2431
7 >200 2191
Unpublished data
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Some Commensal Bacteria are Low When Calprotectin is High
Coprococcus eutactus Pseudoflavonifractor spp.
Faecalibacterium prausnitzii2.0x107
1.5x107
1.0x107
5.0x106
0.0
Akkermansia muciniphila
Coprococcus eutactus
Unpublished data, which is in alignment with published literature.
Chen L, et al. Medicine (Baltimore). 2014;93:e51.
Lopez-Siles M, et al. Front Cell Microbiol. 2018;8:281.
Zhou L, et al. Inflamm Bowel Dis. 2018;24:1926-1940.
Quevrain E, et al. Gut. 2016;65:415-425.
Morgan XC, et al. Genome Biology. 2015;16:67.
Berry D, et al. Best Pract Res Clin Gastroenterol. 2013;27:47-58.
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Some Commensal Bacteria are High/No Change When Calprotectin is High
Fusobacterium spp.
Bifidobacterium longumBifidobacterium spp.
Escherichia coli
Unpublished data, which is in alignment with published literature.
Azimi T, et al. APMIS. 2018;126:275-283.
Kabeerdose J, et al. Indian J Med Res. 2015;142:23-32.
Shaw KA, et al. Genome Medicine. 2016;8:75.
Allen-Vercoe E, et al. Immunol Lett. 2016;162: 54-61.
Kedia S, et al. J Gastroenterol. 2016;51:660-671.
Morgan XC, et al. Genome Biology. 2015;16:67.
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H2 consumers behave differently
H2S is Pro-inflammatory
CH4 is anti-inflammatory
Desulfovibrio piger
Methanobrevibacter smithiiUnpublished data, which is in alignment with published literature.
Ghavami SB, et al. Microb Pathog. 2018;17:285-289.
Kurada S, et al. Aliment Pharmacol Ther. 2015;41:329-341.
Pimentel M, et al. Dig Dis Sci. 2003;48:86-92.
Carbonero F, et al. Nat Rev. 2012;9:504-518.
Boros M, et al. Crit Care Med. 2012;40:1269-1278.
Beaumont M, et al. Free Radic Biol Med. 2016;93:155-164.
Yao CK, et al. Aliment Pharmacol Ther. 2016;43:181-196.
Blachier F, et al. Amino Acids. 2010;39:335-347.
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Gut Inflammation (Immune Response) Associated Dysbiosis Score
Inflammation Associated Dysbiosis Score
Inflammation Associated Dysbiosis Score
Inflammation Associated Dysbiosis Score
All statistically significantUnpublished data
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IAD Score Increases Only In the IBD Cohort
*
IBD: Inflammatory bowel disease
IBS: Irritable bowel syndrome
CF: Chronic Fatigue
AI: Autoimmune
MD: Mood Disorder
MS: Metabolic Syndrome
Unpublished data
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• Specific commensal profiles are associated with host responses such as inflammation.
Summary 2
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Multiple Layers of Analysis
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Story About Fecal Short-Chain Fatty Acids
Cook SI, Sellin JH. Aliment Pharmacol Ther. 1998;12:499-507.
Here is where we measure!
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Distribution of Fecal SCFAs Test Results
Group Total SCFAs (mmol/g)
1 <1
2 1 – 4.9
3 5 – 9.9
4 10 – 14.9
5 15 – 19.9
6 20 – 24.9
7 25 – 29.9
8 30 – 39.9
9 40 – 49.9
10 50 – 59.9
11 60 – 69.9
12 70 – 79.9
13 >=80
Unpublished data
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Fecal SCFAs and Stool Conditions
Stool Condition
Additional Reading:
Gargari G, et al. Environ Microbiol. 2018;20:3201-3213. Ruppin H, et al. Gastroenterology. 1980;78:1500-1507.
Clausen MR, et al. Gastroenterology. 1991;6:1497-1504. Treem WR, et al. J Pediatr Gastroenterol Nutr. 1996;23:280-288.
Binder HJ, et al. J Clin Gastroenterol. 2005;39:S53-58 . Binder HJ. Annu Rev Physiol. 2010;72:297-313.
Unpublished data
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SCFA, Stool Condition, & Fecal Calprotectin
SCFA <1mmol/g SCFA >80mmol/g
All
Unpublished data
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SCFA, Stool Condition, & Fecal EPXAll
SCFA <1mmol/gSCFA >80mmol/g
Unpublished data
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SCFA, Stool Condition, & Fecal sIgA
SCFA <1mmol/g
All
SCFA >80mmol/g
Unpublished data
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SCFA, Stool Condition, & Weighted Abundance (Bacteria)
All
SCFA <1mmol/g SCFA >80mmol/g
Unpublished data
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• To properly interpret test results, we need to look at a pattern from different angles and dig deeper
Summary 3
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There are Many Animals in the Room
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Grouping of Commensal Bacteria Based on Factor Analysis
Group 1 Group 2 Group 3 Group 4 Group 5
Methanobrevibacter smithii Bacteroides vulgatus Bifidobacterium spp. Escherichia coli Butyrivibrio crossotus
Oxalobacter formigenes Ruminococcus spp. Bifidobacterium longum Fusobacterium spp. Prevotella spp.
Odoribacter spp. Faecalibacterium prausnitzii Veillonella spp. Lactobacillus spp. Desulfovibrio piger
Barnesiella spp. Bacteroides-Prevotella group Roseburia spp.Bacteroides-Prevotellagroup
Collinsella aerobaciens Pseudoflavonitractor spp.
Coprococcus eutactus Desulfovibrio piger (-)
Akkermansia muciniphila Roseburia spp.
Clostridium spp. Anaerotruncus colihominis
Desulfovibrio piger
Pseudoflavonitractor spp.
Based on the analysis results, we generated weighted abundance for each group
Unpublished data
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Short Medical History:• 60 y/o female with longstanding GI issues
• Diagnosed with celiac disease in the past
• Has been on gluten-free diet for years
• After a recent stool test, bacterial overgrowth was suspected; antibiotics were given to the patient but the treatment exacerbated the GI symptoms
Case Study #1
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Case Study #1: Commensal Groups & Inflammation
1 2 3 4
0
10
20
30
40
Group 5 quartile
Fecal calp
rote
cti
n (
ug
/g)
calprotectin
1 2 3 4
0
10
20
30
40
Group 4 quartile
Fecal calp
rote
cti
n (
ug
/g)
calprotectin
1 2 3 4
0
10
20
30
40
Group 3 quartile
Fecal calp
rote
cti
n (
ug
/g)
calprotectin
1 2 3 4
0
10
20
30
40
Group 2 quartile
Fecal calp
rote
cti
n (
ug
/g)
calprotectin
1 2 3 4
0
10
20
30
40
Group 1 quartile
Fecal calp
rote
cti
n (
ug
/g)
calprotectin
1 2 3 4
0.0
0.5
1.0
1.5
2.0
Group 5 quartile
Fecal E
PX
(u
g/g
)
EPX
1 2 3 4
0.0
0.5
1.0
1.5
2.0
Group 4 quartile
Fecal calp
rote
cti
n (
ug
/g)
EPX
1 2 3 4
0.0
0.5
1.0
1.5
2.0
Group 3 quartile
Fecal E
PX
(u
g/g
)
EPX
1 2 3 4
0.0
0.5
1.0
1.5
2.0
Group 2 quartile
Fecal E
PX
(u
g/g
)
EPX
1 2 3 4
0.0
0.5
1.0
1.5
2.0
Group 1 quartile
Fecal E
PX
(u
g/g
)
EPX
1 2 3 4
0
200
400
600
800
Group 5 quartile
Fecal sIg
A (
mcg
/g)
sIgA
1 2 3 4
0
200
400
600
800
Group 4 quartile
Fecal sIg
A (
mcg
/g)
sIgA
1 2 3 4
0
200
400
600
800
Group 3 quartile
Fecal sIg
A (
mcg
/g)
sIgA
1 2 3 4
0
200
400
600
800
Group 2 quartile
Fecal sIg
A (
mcg
/g)
sIgA
1 2 3 4
0
200
400
600
800
Group 1 quartile
Fecal sIg
A (
mcg
/g)
sIgA
Calprotectin
EPX
sIgA
Group 1 Group 2 Group 3 Group 4 Group 5
Patient result L H L H L H L H L H
Group-specific weighted abundance
Unpublished data
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Short Medical History:• 47 y/o female with chronic fatigue, constipation, adult-onset acne
• Diet is mainly paleo diet with high protein, high fat, low carb, and mostly gluten-free
• She took probiotics intermittently
• A recent stool test indicated low fecal SCFA
• Given the patient had a relatively high total abundance of commensal bacteria in the test, it was not clear if both prebiotics and probiotics were needed
Case Study #2
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Case 2 – Commensal Groups and SCFA
Unpublished data
Patientresult L H L H L H L H L H
1 2 3 4
0
20
40
60
80
Group 5 quartile
Fecal to
tal S
CFA
(u
mo
l/g
)
total SCFA
1 2 3 4
0
20
40
60
80
Group 4 quartile
Fecal to
tal S
CFA
(u
mo
l/g
)
total SCFA
1 2 3 4
0
20
40
60
80
Group 3 quartile
Fecal to
tal S
CFA
(u
mo
l/g
)
total SCFA
1 2 3 4
0
20
40
60
80
Group 2 quartile
Fecal to
tal S
CFA
(u
mo
l/g
)
total SCFAsGroup 2 Group 3 Group 4 Group 5
1 2 3 4
0
20
40
60
80
Group 1 quartile
tota
l S
CFA
(u
mo
l/g
)
total SCFAsGroup 1
SCFA
Group-specific weighted abundance
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Different Bacterial Groups Have Different Weight on Fecal Total SCFA
Group 2 Group 4
L H L H
G4l+G2l-h 250 G4h+G2l-h 250
Unpublished data
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Pattern Analysis is Essential for Understanding Interactions of Multiple Factors
Host EnvironmentalFactors
Microbiome
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Future
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Acknowledgement
Medical Affairs
Doreen Saltiel, MD, FACC
Michael Chapman, ND
Patricia Devers, DO
Betsy Redmond, PhD
Christine Stubbe, ND
Laboratory
Amy PeaceBrewer, PhD
Robert David, PhD
Genova Diagnostics Generativity Solutions Group, LLCJason C. Allaire, PhD
Care-Safe, LLCMark Peucker, MS
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Questions?
Thank you!