1. Environmental Health 2013 Boston, USA 3-6 March 2013 1
The connectivity paradigm
to cumulative risk assessment
metabolite
formation
GI tract – portal vein GI tract – portal vein
L L
i i
v v
e e
r r
H H
e e
a a
r r
t t
B B
r r
a a
i i
n n
M M
u u
s s
c c
l l
e e
s s
S S
k k
i i
n n
K K
i i
d d
n n
e e
y y
s s
A A
d d
i i
p p
o o
s s
e e
B B
o o
n n
e e
s s
B B
r r
e e
a a
s s
t t
Uterus - gonads Uterus - gonads
A L V A L V
r u e r u e
t n n t n n
e g o e g o
r s u r s u
Denis A. Sarigiannis
i s i s
a a
l b l b
l l
b o b o
l o l o
o d o d
o o
d d
Spyros Karakitsios
Alberto Gotti
Environmental Engineering Laboratory (EnvE-Lab)
Department of Chemical Engineering, Aristotle University of Thessaloniki - 54124, Greece
Graziella Cimino-Reale
National Cancer Institute, Italy

2. What’s the exposome?
Environmental Health 2013 Boston, USA 3-6 March 2013 2
• The record of all exposures, both internal and
external, an individual receives over his or her
lifetime, from conception onward. These
exposures range from chemicals in the
environment to the body’s response to infection or
psychological stress
(C. Wild, IARC, 2005)
• It is important to keep an unbiased (agnostic)
stance to coupling chemical exposure to health
status
S M Rappaport, M T Smith Science 2010;330:460-461
Is this enough?

3. Advancing exposome –
The integrative approach
Environmental Health 2013 Boston, USA 3-6 March 2013 3
“Systems Biology” Approach
metabolite
formation
GI tract – portal vein GI tract – portal vein
Liver Liver
Heart Heart
Brain Brain
Muscles Muscles
Skin Skin
Kidneys Kidneys
Adipose Adipose
Bones Bones
Breast Breast
Uterus - gonads Uterus - gonads
Arterial blood Lungs Venous blood Arterial blood Lungs Venous blood
cell organ organism
“Physiome” Approach
Aim: How?
To draw the maximum benefit from the exposure • advanced –omics technologies (A)
information related to the currently evermore • systems biology (B)
enhanced biomonitoring data • physiology-based biokinetic modeling (C)

4. Coupled EWAS-GWAS Methodology
The HEALS paradigm
Environmental Health 2013 Boston, USA 3-6 March 2013 4

5. (A) Integrated Multi-layer computational
Approach
Environmental Health 2013 Boston, USA 3-6 March 2013 5
Characterization of exposure Aggregate and cumulative
Probabilistic exposure
factors exposure models
Toxicological analysis
Biologically effective dose- Biomarkers of exposure
Dose-effect models
early biological effects effects
Omics (expression profiles)
Individual profiles
-Life styles Biomarkers of individual
Individual response
-Polymorphisms susceptibility
Population studies Molecular dosimetry Assessment of Risk Factors

6. Environmental exposure:
in-/outdoor/personal
Environmental Health 2013 Boston, USA 3-6 March 2013 6

7. (A) Expressomics for the Exposome
Environmental Health 2013 Boston, USA 3-6 March 2013 7
Environment and Health
Experimental Design Signature of chemicals in products
Implementation of Risk Assessment
Tissues RNA
Mice, Rats, Humans Biomarkers and
B
Systems Toxicology
I
O Models
I
N
F
O Integrated approach
Whole Genome Discovery Systems R with
(32.000 genes) M Proteomics/Metabonomics
A
T
I Genes Modulation
C Genes Classification
Gene Identification
S Genes Pathway
Validation by Quantitative PCR Statistical Evaluation

8. (A) Transcriptomics responses
to chemical mixtures
Environmental Health 2013 Boston, USA 3-6 March 2013 8
Signal transduction
Protein metabolism
Protein biosynthesis
mRNA transcription
Electron transport
Cell surface receptomediated signaling
10ug/l
100ng/l 0 50 100 150 200 250 300 0 50 100 150 200 250 300
10ng/l Mix A Mix B

9. (A) Transcriptomics responses
to chemical mixtures
Environmental Health 2013 Boston, USA 3-6 March 2013 9
Protein
modification
Protein
metabolism
Protein
biosynthesis
mRNA
transcription…
mRNA
transcription
Hematopoiesis
Cytokine and
chemokine…
Cell proliferation
and differentiation
10ug/l
0 20 40 60 80 100 0 20 40 60 80 100
100ng/l
10ng/l Mix A Mix B

10. (B) Metabolic profiling and
systems biology integration
Environmental Health 2013 Boston, USA 3-6 March 2013 10
Diet, behavior
Exposome Health outcomes
Genetics
Epigenetics

11. (C) Internal dosimetry models
Environmental Health 2013 Boston, USA 3-6 March 2013 11
metabolite
formation
Physiology Based PharmacoKinetic (PBPK) models are GI tract – portal vein GI tract – portal vein
modeling tools that describe the mechanisms of
absorption, distribution, metabolism and elimination (ADME)
of chemicals in the body resulting from acute and/or chronic Liver Liver
exposure regimes
Heart Heart
dCij Brain Brain
Vi Qi (CAj CVij ) Metabij E limij Absorpij Pr Bindingij
dt
Muscles Muscles
PBPK models serve three main purposes: Skin Skin
- internal dose – Biologically Effective Dose (BED) Kidneys Kidneys
assessment - for refined exposure characterization (I)
Adipose Adipose
- the capability to derive an exposure conversion factor
(ECF)/advanced exposure reconstruction for Bones Bones
biomonitoring data assimilation (II)
Breast Breast
- the capability to derive Biomonitoring Equivalents Uterus - gonads Uterus - gonads
(BEs) - link to BED for direct comparison to
legislative/toxicological thresholds (III)
Arterial Lungs Venous Arterial Lungs Venous
blood blood blood blood

12. Coupling biokinetics and metabolism regulation
Environmental Health 2013 Boston, USA 3-6 March 2013 12

13. (C) (I) External and internal exposure
intra-day variability
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14.0 0.14
Benzene exposure (μg/m3)
NNK exposure (ng/m3)
12.0 Formaldehyde exposure (μg/m3) 0.12
Benzene toxic metabolites (μg/L)
NNK metabolites (ng/L)
10.0 0.1
DPX (μM∙105)
Internal exposure
External exposure
8.0 0.08
6.0 0.06
4.0 0.04
2.0 0.02
0.0 0
0 4 8 12 16 20 24 28 32 36 40 44
Time (h)

14. (C) (II) Exposure reconstruction from
HBM data
Environmental Health 2013 Boston, USA 3-6 March 2013 14
Distribution of exposures
consistent with HBM data
Potential exposure
estimation Improved
sampling
Optimization
algorithm
Comparison with biomarker data
En
PBTK model run B*n
with E*n input
E3 Small proportion
B*3 of rejected model
E2
simulations
E1 B*2
PBTK model run B*1
with E*1 input
Exposure model
Companion data
 INTERA Biomarker
(Exposure
 TAGS data
related)
 ProTEGE

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19. Conclusions
Environmental Health 2013 Boston, USA 3-6 March 2013 19
• Advancing risk assessment from a “hazard based” to an
“exposure based” process is made easier by exposomics
• Key for the development of the exposome is the exploitation
of biomonitoring data, in combination to advanced PBPK
models for relating exposure biomarkers to actual exposure
scenarios
• Omics technologies hold a key role for understanding the
intermediate pathways between exposure and disease,
especially in the case of exposure to mixtures or latency
• Advanced computational tools are needed for understanding
the interaction between environmental, exposure and
biological responses.
• PBPK and systems biology modeling is the connecting layer
for incorporating the above dynamics within a continuous
frame