transcriptional profiling informs target organ
phenotypic responses of agrochemicals in rats.
12 May 2020
Michael D. Cannizzo
Oak Ridge Institute for Science and Education (ORISE) Fellow
United States Environmental Protection Agency, Research Triangle Park, NC 27711.
The data presented here do not reflect EPA policy.
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Benchmark dose modeling (BMD)
The 4 Step Risk Assessment Process
Dose-Response
fs. Assessment
What are the health
problems at different
exposures?
Exposure
Assessment
How much of the pollutant
are people exposed to during
a specific time period? How
many people are exposed?
Hazard
Identification
What health problems
are caused by the
pollutant?
Risk
Characterization
What is the extra risk of
health problems in the
exposed population?
* Traditionally, a dose that
produces a predetermined
change (1-10%) in
response rate of an
adverse effect.
• Not dependent on study
design like NOAELand
LOAEL approaches.
https://www.epa.gov/risk/conducting-human-health-risk-assessmerit
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Lowest median pathway transcriptional BMD shown to be
concordant with apical BMDJ11
10000
1000
3
o
Q
Cs
5
33
Q
££3
U
Q)
O
100
10
0.1
0.1
H2B2
1 10 100 1000
Apical Potency Value with 1/2 log range
10000
Gene response coincides or precedes
adverse physical effects.
Questions:
• Can BMD modeling of gene response data
strengthen a 14 day in vivo experiment?
• Are phenotypic responses aligned with
gene expression data?
• What is the added value?
[1] http://dx.doi.org/10.22427/NTP-RR-5.
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Syngenta: 20
agrochemicolsx 5 dose
levels x 14 tissues
(ri=4/sex/group)
Rat
Daily oral gavage: 0, 200, 600, 2000, and 6000 ppm
Days: 0 2
Blood dose
Histopathology
Compare observable response to
gene expression data.
14
Blood dose
Clinical pathology
Histopathology
Gene expression (TGx)
Transcriptomics
Use gene expression data to compare
sex, dose, and chemical effects of
treatment.
Benchmark dos
Compare transcriptional
benchmark dose to apical
BMD.
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Analysis Methods
Chemical 1
Raw Gene Counts
Chemical 2
Raw Gene Counts
Use DESeq2 in
PartekFlow to get DEGs
Examine canonical
pathways in I PA
UseOneWayANOVAin
BMDExpress 2.3 to get
DEGs
Map DEGs to Reactome
pathways and take lowest
median BMDt
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Outline
Chemically similar compounds CI and C2 which disrupt electron transport chain
in plants.
Brief results on CI due to compounding limitations
• 2 dose groups available due to overt toxicity (thus no BMD modeling)
• a-2|j globulin nephropathy in kidney
C2 Results
1. Histopathology
2. Differentially expressed genes
3. Pathway analysis
4. Transcriptional BMD
CI C2
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Brief results for CI
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CI
Despite overt toxicity, dose
dependent increase in gene
response seen in males kidney.
CI eosinophilic inclusions in tubular
epithelium of kidney at 14d
Males
Females
£
0
0/4
0/4
Q.
Q.
QJ
t/1
600
4/4
0/4
O
Q
2000
4/4
0/4
CO
O
400
350
300
250
200
150
100
50
0
¦ Males
¦ Females
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Pairwise DEG comparisons show low gene overlap in kidneys across sexes.
DEG intersection for male and female kidney at 600ppm.
249 13 185
Males ^ females
DEG intersection for male and female kidney at 2000ppm.
330 26 166
Males females
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Low number of canonical pathways in common for kidneys
IL-6 Signaling
Epithelial Adherens Junction Signaling
Circadian Rhythm Signaling
Calcium Signaling
Agranulocyte Adhesion and Diapedesis
Acute Phase Response Signaling
0 0.5 1 1.5 2 2.5 3 3.5
R _ i _ . -log(p-val)
¦ Male ¦ Female &Vh^ '
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CITakeaways
• BMD modeling could not be done.
• Gene response data could be anchored to phenotypic responses.
• Added value of gene expression data
• Reinforcement of sex differences.
* Pathway data could help uncover mode of action.
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C2 Results
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C2
Inhibitory dose response
in females.
Slight increase in DEGs
response in males.
C2 observable effects at 14d
to
O
400
300
g 200
100
0
I
I
200
Male
600 2000
Kidney
Female
6000 200
Dose (ppm)
600 2000
Adrenals
6000
Males
Females
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Sex differences apparent in adrenals and kidneys, but
adrenals have more DEGs in common than kidneys.
DEG intersection for male and female adrenals at 2000ppm
DEG intersection for male and female kidney at 2000ppm
330 26 166
Males females
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FXR/RXR Activation
Acute Phase Response Signaling
LXR/RXR Activation
IL-12 Signaling and Production in Macrophages
Production of Nitric Oxide and Reactive Oxygen Species in Macrophages
IL-22 Signaling
Role of JAKfamily kinases in IL-6-type Cytokine Signaling
IL-17A Signaling in Gastric Cells
Apelin Liver Signaling Pathway
Type II Diabetes Mellitus Signaling
Antioxidant Action of Vitamin C
RAR Activation
IL-1 Signaling
Extrinsic Prothrombin Activation Pathway
CDK5 Signaling
HIFlT± Signaling
Mitochondrial L-carnitine Shuttle Pathway
Protein Kinase A Signaling
Coagulation System
ErbB Signaling
Glucocorticoid Receptor Signaling
Intrinsic Prothrombin Activation Pathway
Hepatic Fibrosis / Hepatic Stellate Cell Activation
2000ppm was selected for pathway analysis
because it is proximal to phenotypic responses
seen at 6000ppm.
Adrenals Pathways 2000ppm
1. Over 2x the significant
canonical pathways in
common as kidneys.
2. Top 3 pathways have
robust p-values.
-log(p-value)
I Males ¦ Females
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C2
450
400
350
I* 300
u5
250
~ 200
0
(ft
Q 150
100
50
0
Median Pathway BMD Accumulation shows transcriptional BMD is
within 5-fold of apical BMD.
Male Adrenal
BMDt: 51.6
BMDa/BMDt: 1.3
;F BMDa: 114
-M BMDa: 69.2
Female Adrenal
BMDt: 22.8
BMDa/BMDt: 5
o o
• Male Adrenal
• Female Adrenal
° Male Kidney
*
° Female Kidney
o o
«•
O O O O
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1. BMDt values for kidney were also within 5-fold of adrenal apical BMD
2. All BMDt values were more sensitive than lowest adrenal apical BMD,
suggesting transcriptional BMDs are more health protective.
3. Female kidney DEGs also mapped to the citric acid cycle and respiratory
electron transport. Pathway related to chemical intrinsic properties.
Adrenals BMDtl calculated using
phenotypic response data
Significant Median BMDt using BMDExpress 2.3 Pathway Analysis
(Reactome)
Male mg/kg/day
69.2
Female mg/kg/day
114
Organ
Kidney
Adrenals
Male mg/kg/day
63.7
(Extracellular matrix organization)
51.6
(Extracellular matrix organization)
Female mg/kg/day
43.5
(The citric acid (TCA) cycle and
respiratory electron transport)
22.8
(Metabolism)
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Conclusion
ci
• Transcriptional response could be anchored to observable effects.
• Due to toxicity of higher doses, BMD modeling could not be done.
• Added value of gene expression data
• Reinforcement of sex differences.
• Pathway data could help uncover mode of action.
* Transcriptional response aligned with observable response.
* Lowest median BMDt within tenfold of apical, potentially more health protective
* Added value of gene expression data
• Reinforcement of sex differences.
• More protective BMDt.
• Lowest median pathway in female kidney supported intrinsic property of the chemical.
• Pathway data could help uncover mode of action.
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Future Work
Analyze the remainder of the chemicals
Look into upstream regulators
Try to develop gene response signatures for each chemical
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Acknowledgements
Leah Wehmas, USEPA, RTP, NC
Susan Hester, USEPA, RTP, NC
Kathryn Bailey, Syngenta Crop Protection, RTP, NC
David Cowie, Syngenta Jeaiott's Hill International Research Centre, UK
Richard Currie, Syngenta Jeaiott's Hill International Research Centre, UK
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Questions?
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