Information channels and biomarkers of disease

1. Information channels and
biomarkers of disease
Phyllis Illari and Federica Russo

2. Overview
Why ‘exposomics’?
A good case in the CitS / SPSP spirit
In search of a concept of linking
The failure of traditional production accounts
Revisiting the causal literature in the light of new challenges
Where to look next for a concept of linking
The prospects of an informational approach
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3. Why exposomics? 3

4. Environmental
exposure and disease
Traditional epidemiology
Establish correlation between
environmental factors and
classes of disease
Molecular epidemiology
Measurement at molecular
level
Identify biomarkers of
exposure, of early clinical
changes, of disease
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5. Finding the missing link
Environmental factors ➯disease
Chemicals in water / air ⤳
biomarkers of exposure ⤳
biomarkers of clinical changes ⤳
disease
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6. From GWAS to EWAS
The limits of genomics
An expanded notion of exposure
Internal and external exposure – the EXPOSOME
Better understanding of disease mechanisms
the MISSING LINK:how environmental exposure and
disease are connected
Go down to the molecular level
Better prediction and health policy planning
Earlier and more accurate prediction
Identification of areas for public health intervention
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7. Goals
Looking for biomarkers of the process of evolution of the disease
The meeting-in-the-middle methodology: matching key evolution stages
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Come to understand how environmental exposure is linked to the disease
We know a lot about the system, but a lot is still unknown
We seek many small causes, with small effects, and large interaction effects
We expect widely different factors to be causes,
including e.g. social and chemical factors
Use of new omics technologies allows a comprehensive approach,
but generates vast amounts of data
Challenges
Upshot
Exposomicslooks for tiny, difficult-to-find causal links in the middle of a mess

8. What is this linking?

9. What we want
Nail down
what linkingisand
how we reason about it
Tension: general but not vacuous
A thin and versatile metaphysics – and broadly realist
A widely applicable, general metaphysics – and informative
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10. Where to find linking?
Accounts of difference-making
Probabilistic, counterfactual, manipulationist, …
Establish thatC causes E
Accounts of production
Processes, mechanisms, CPD, …
Establish howC causes E
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11. TRADITIONAL ACCOUNTS OF
PRODUCTION FAIL
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12. Physical processes
Tied to description of processes in physics,
only one type of linking
Mechanisms
Give organization of parts and their interactions,
course-grained linking
Capacities, Powers, Dispositions
Give modal properties of some parts of mechanisms,
not linking
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14. Purely physical
quantity
Physical processes
Tied to description of
processes in physics,
only one type of linking
Mechanisms
Give organization of parts and
their interactions,
course-grained linking
Capacities, Powers, Dispositions
Give modal properties of some
parts of mechanisms,
not linking

15. Processes
Discriminate between causal and non-causal physical
processes
Salmon-Dowe
Exchange of conserved quantities
Billiard balls colliding
Boniolo et al
Exchange between extensive quantities
Electric heating making environment hotter
Tied to description of processes in physics,
only one type of linking
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16. Physical processes
Tied to description of
processes in physics, only
one type of linking
Mechanisms
Give organization of parts
and their
interactions, course-
grained linking
Capacities, Powers, Dispositions
Give modal properties of some
parts of mechanisms,
not linking

17. Mechanisms
Illari& Williamson proposed consensus:
“Entities and activities organised in such a way of being
responsible for a phenomenon”
Key elements of mechanistic explanation:
Identification of the phenomenon
Identification of entities and activities involved
Identification of the organisation
Give organization of parts and their interactions,
course-grained linking
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18. Physical processes
Tied to description of
processes in physics, only
one type of linking
Mechanisms
Give organization of parts and
their interactions,
course-grained linking
Capacities, Powers, Dispositio
ns
Give modal properties of
parts of
mechanisms, not
linking

19. Capacities, Powers, Dispositions
Cartwright & Pemberton, Mumford &Anjum, Bird
Cope with (scientific) situations lacking
universal, exceptionless laws
Hang on to realist intuitions
CPDs are properties of a particular thing or system
Things-with-capacities licence specific capacity claim
Modal character of capacities
Give properties of some parts of mechanisms,
not linking
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20. Recap
Traditional accounts of production seek:
Realism: what is causality?
Science-first: what does science say causality is?
Exposomics requires something:
Fine-grained
Very general to apply in multiple cases and to link profoundly
inhomogeneous causal factors
Something that can exist and potentially be found in such a
mess of interaction
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21. How to trace such linking?

22. THE PROSPECTS OF AN
INFORMATIONAL APPROACH
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23. Picking up signal
While classical statistical models to analyzing -omics data serve the
purpose of identifying signals and separating them
from noise, little has been done in chronic diseases to model
time into the exposure-biomarker-disease continuum. Recently,
SandroGalea has proposed to generalise mathematical approaches
initially designed to study infectious disease to chronic diseases
epidemiology. In that setting, biomarkers should not be assessed
synchronically, as usually done, but diachronically and even ideally
their full evolution along time should be considered.
[Vineis and Chadeau-Hyam 2011]
From these two parallel analyses [statistical analyses], we obtained
lists of putative markers of (i) the disease outcome, and (ii)
exposure. These were compared in a second step in order to
identify possible intersecting signals, therefore defining
potential intermediate biomarkers.
[Chadeau-Hyam et al 201]
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24. Why information
Gives a way of describing reality, of any kind.
Information transmission can be tracked, measured, described precisely.
See e.g.: biological information
A thin secret connexion
In line with Anscombian pluralism
Guides interpretation of multiple data sources
Helps with knowledge construction, conceptualisation of link,
of picking up signal
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25. Informational thinking helps with
knowledge construction
Information is like a branch floating down a river
Scientific study of processes, mechanisms, CPDs
Define the banks, find the currents, intercept position
of branch, …
The river is there, but we shape the banks
We try to track the tree down to the wood
factory, where it can be processed
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26. Mechanisms as information channels
Reconcile informational approach to successful
existing work on mechanisms
Mechanisms give course-grained linking
They help track linking
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27. Why informational thinking helps:
the inhomogeneity argument
⁇Plausible links
Social ⤳ Biological
Big ⤳ Small
(and viceversa)
☝Exposomics
Environmental exposure (B)
⤳ molecular changes (s)
‼ Restore homogeneity:
biological measurements
⁇Problem isn’t solved
Choose exact level,
links hard to interpret
Reinterpret micro links
at macro level
☝Information flowing via
biomarkers:
Interpretation of
many pieces of puzzle
Reconstruction of
information flow
Biomarkers analyses +
statistics + biological theory
+ …
⁇Plausible links
Not via homogeneity
But via reconstruction of
continuous linking
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28. WHAT LINKING IS NOT
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29. Avoid category mistakes
Why not counterfactuals?
Isn’t causation counterfactual dependence?
Counterfactuals help with reasoning
Counterfactual dependence helps establish
difference-making, not production
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30. SUM UP AND CONCLUDE
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31. Why exposomics?
An emerging, interesting, challenging
area of research driving change
Modelling disease evolution
Conceptualisation of exposure
A field to test the possibility of philosophy
to help with conceptual engineering
Do traditional accounts help with new challenges?
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32. Why information
Referenced in scientific practice
Picking up signal
More than an entity in our ontology
A thin secret connexion
A way of thinking
Knowledge construction and data interpretation
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33. Why information for exposomics?
Exposomics forces us to reconsider
existing approaches to causality:
shows the importance of understanding causal linking…
…while showing that existing accounts of productionhelp track linking
Information as an answer is
Real and referenced in scientific practice,
General and fine-grained enough,
Helps with tracking linking, by reconstructing the flow of signaling
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