Decoding Stool Test Results

Lihong Chen, MD, PhDNovember 3, 2018

Fecal Biomarkers, Commensal Bacteria, and Clinical Applications

• Director of Clinical Evidence Development at Genova Diagnostics

• All data analyses are based on Genova test results

Disclosure

• 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

How to Use Stool Test Results?Diagnosis criteria

Case report

Pattern analysis

Symbiosis in the Gut Depends on Multiple Factors

Lab testing is an integrated component of health assessment

Host EnvironmentalFactors

Microbiome

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

• 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

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Unpublished data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

Different Aspects of the “Same” Profile

Differential Distribution Between Healthy and IBS Cohorts

Unpublished data

Differential Distribution Between Healthy and Chronic Fatigue Cohorts

He

alth

y-P

atte

rn C

on

tin

uu

m

Reference Variance Score

Unpublished data

Differential Distribution Between Healthy and Autoimmune Cohorts

He

alth

y-P

atte

rn C

on

tin

uu

m

Reference Variance Score

Unpublished data

Patient’s Result is Not Dependent on Specific Bacteria

• Using algorithm-based profiles of selected commensal bacteria can differentiate healthy and disease cohorts

Summary 1

Pattern Analyses with All Patients

Testing “Everything” vs Testing “Something”

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

Commensal Abundance is Correlated to Inflammation/Immune Response

All statistically significant

Unpublished data

Inflammation is Strongly Associated With Commensal Abundance

Unpublished data

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

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.

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.

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.

Gut Inflammation (Immune Response) Associated Dysbiosis Score

Inflammation Associated Dysbiosis Score

Inflammation Associated Dysbiosis Score

Inflammation Associated Dysbiosis Score

All statistically significantUnpublished data

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

• Specific commensal profiles are associated with host responses such as inflammation.

Summary 2

Multiple Layers of Analysis

Story About Fecal Short-Chain Fatty Acids

Cook SI, Sellin JH. Aliment Pharmacol Ther. 1998;12:499-507.

Here is where we measure!

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

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

SCFA, Stool Condition, & Fecal Calprotectin

SCFA <1mmol/g SCFA >80mmol/g

All

Unpublished data

SCFA, Stool Condition, & Fecal EPXAll

SCFA <1mmol/gSCFA >80mmol/g

Unpublished data

SCFA, Stool Condition, & Fecal sIgA

SCFA <1mmol/g

All

SCFA >80mmol/g

Unpublished data

SCFA, Stool Condition, & Weighted Abundance (Bacteria)

All

SCFA <1mmol/g SCFA >80mmol/g

Unpublished data

• To properly interpret test results, we need to look at a pattern from different angles and dig deeper

Summary 3

There are Many Animals in the Room

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

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

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

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

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

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

Pattern Analysis is Essential for Understanding Interactions of Multiple Factors

Host EnvironmentalFactors

Microbiome

Future

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

Questions?

Thank you!