, Volume 35, Issue 1, pp 175–190 | Cite as

Information Channels and Biomarkers of Disease

  • Phyllis Illari
  • Federica Russo


Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson (Med Stud, 2012) address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has examined Ned Hall’s distinction between two concepts of causality: production and dependence (Hall in Causation and counterfactuals. MIT Press, Cambridge, pp 225–276, 2004). In another recent paper, Illari (Philos Technol, p 20, 2011b) examined the relatively under-explored production approach to causality, arguing that at least one job of an account of causal production is to illuminate our inferential practices concerning causal linking. Illari argued that an informational account solves existing problems with traditional accounts. This paper follows up this previous work by investigating the nature of the causal links established in biomarkers research. We argue that traditional accounts of productive causality are unable to provide a sensible account of the nature of the causal link in biomarkers research, while an informational account is very promising.


Causality Information Biomarkers Exposomics Productive causality Causality as production Biomarkers of disease Exposome 



We are deeply indebted to Paolo Vineis and collaborators on the EXPOsOMICS project at Imperial for discussions on these issues. We gratefully acknowledge the financial support of the FWO-Flanders (F. Russo has been a ‘Pegasus Marie Curie Fellow’ during the academic year 2012–2013) and the AHRC (P. Illari has been working on the project ‘Understanding information quality standards and their challenges’ at the University of Hertfordshire, 2011–2013). We also thank audiences at the Fifth Workshop on the Philosophy of Information, University of Hertfordshire 2013; the “Causality and Mechanisms” workshop of the Egenis group, University of Exeter 2013; the Causality and Experimentation in the Sciences Conference, Sorbonne, Paris, 2013; and the European Philosophy of Science Association, Helsinki, 2013, especially Erik Weber, and one anonymous referee, for useful comments. Remaining errors are, of course, our own.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.UCLLondonUK
  2. 2.Dipartimento di Studi UmanisticiUniversità degli Studi di FerraraFerraraItaly

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