Medicine Studies

, Volume 3, Issue 4, pp 249–262 | Cite as

EnviroGenomarkers: The Interplay Between Mechanisms and Difference Making in Establishing Causal Claims

Article

Abstract

According to Russo and Williamson (Int Stud Philos Sci 21(2):157–170, 2007, Hist Philos Life Sci 33:389–396, 2011a, Philos Sci 1(1):47–69, 2011b), in order to establish a causal claim of the form, ‘C is a cause of E’, one typically needs evidence that there is an underlying mechanism between C and E as well as evidence that C makes a difference to E. This thesis has been used to argue that hierarchies of evidence, as championed by evidence-based movements, tend to give primacy to evidence of difference making over evidence of mechanisms and are flawed because the two sorts of evidence are required and they should be treated on a par. An alternative approach gives primacy to evidence of mechanism over evidence of difference making. In this paper, we argue that this alternative approach is equally flawed, again because both sorts of evidence need to be treated on a par. As an illustration of this parity, we explain how scientists working in the ‘EnviroGenomarkers’ project constantly make use of the two evidential components in a dynamic and intertwined way. We argue that such an interplay is needed not only for causal assessment but also for policy purposes.

Keywords

Causality Disease causation Public health policy Mechanisms Russo–Williamson thesis Biomarkers 

References

  1. Bechtel, W., A. Abrahamsen. 2005. Explanation: A mechanist alternative. Studies in the History and Philosophy of the Biological and Biomedical Sciences 36:421–441.CrossRefGoogle Scholar
  2. Boniolo, G., R. Faraldo, A. Saggion. 2011. Explicating the notion of ‘causation’: The role of extensive quantities. In: Causality in the sciences, eds. P. Illari, F. Russo, J. Williamson, 502–525. Oxford: Oxford University Press.CrossRefGoogle Scholar
  3. Broadbent, A. 2011. Inferring causation in epidemiology: Mechanisms, black boxes, and contrasts. In Causality in the sciences, eds. P. Illari, F. Russo, J. Williamson, 45–69. Oxford: Oxford University Press.CrossRefGoogle Scholar
  4. Brownson, R.C., E.A. Baker, T.L. Leet, K.N. Gillespie. 2003. Evidence-based public health. New York: Oxford University Press.Google Scholar
  5. Brownson, R.C., J.G. Gurney, G.H. Land. 1999. Evidence-based decision making in public health. Journal of Public Health Management Practice 5(5):86–97.Google Scholar
  6. Campaner, R. 2011. Understanding mechanisms in the health sciences. Theoretical Medicine and Bioethics 32:5–17.CrossRefGoogle Scholar
  7. Casini, L., P.M. Illari, F. Russo, J. Williamson. 2011. Models for prediction, explanation and control: recursive Bayesian networks. Theoria 26(1), 5–33.Google Scholar
  8. Chadeau-Hyam, M., T.J. Athersuch, H.C. Keun, M.D. Iorio, T.M. Ebbels, M. Jenab, C. Sacerdote, S.J. Bruce, E. Holmes, P. Vineis. 2011. Meeting-in-the-middle using metabolic profiling—A strategy for the identification of intermediate biomarkers in cohort studies. Biomarkers 16(1):83–88.CrossRefGoogle Scholar
  9. Clarke, B. 2011. Causality in medicine with particular reference to the viral causation of cancers. PhD thesis, Department of Science and Technology Studies, University College London, London.Google Scholar
  10. Darby, G., J. Williamson. 2011. Imaging technology and the philosophy of causality. Philosophy & Technology 24(2):115–136.CrossRefGoogle Scholar
  11. Dowe, P. 1992. Wesley Salmon’s process theory of causality and the conserved quantity theory. Philosophy of Science 59(2):195–216.CrossRefGoogle Scholar
  12. Dowe P. (2000) Causality and explanation: Review of Salmon. British Journal for the Philosophy of Science 51:165–174CrossRefGoogle Scholar
  13. Galea, S., M. Riddle, G.A. Kaplan. 2010. Causal thinking and complex system approaches in epidemiology. International Journal of Epidemiology 39:97–106.CrossRefGoogle Scholar
  14. Gillies, D.A. 2011. The Russo–Williamson thesis and the question of whether smoking causes heart disease. In Causality in the sciences eds. P. Illari, F. Russo, J. Williamson, 110–125. Oxford: Oxford University PressCrossRefGoogle Scholar
  15. Glennan, S. 2002. Rethinking mechanistic explanation. Philosophy of Science 69(Supplement):S342–S353.CrossRefGoogle Scholar
  16. Glymour, C., P.W. Cheng. 1998. Causal mechanism and probability: A normative approach. In Rational models of cognition, eds. M. Oaksford, N. Chater. Oxford: Oxford University Press.Google Scholar
  17. Hall, N. 2004. Two concepts of causation. In: Causation and counterfactuals eds. J. Collins, N. Hall, L. Paul, 225–276. Cambridge MA, London: MIT Press.Google Scholar
  18. Hill, B. 1965. The environment of disease: Association or causation? Proceedings of the Royal Society of Medicine 58:295–300.Google Scholar
  19. Howick, J. 2011. Exposing the vanities—and a qualified defence—of mechanistic evidence in clinical decision-making. Philosophy of Science 78(5):926–940. Proceedings of the Biennial PSA 2010.Google Scholar
  20. Illari, P.M. 2011a. Disambiguating the Russo–Williamson thesis. International Studies in the Philosophy of Science 25(2):139–157.CrossRefGoogle Scholar
  21. Illari P.M. (2011b) Why theories of causality need Production: An information transmission account. Philosophy & Technology 24(2):95–114.CrossRefGoogle Scholar
  22. Illari P.M., J. Williamson. 2012. What is a mechanism? Thinking about mechanisms accross the sciences. European Journal for Philosophy of Science 2(1):119–135.CrossRefGoogle Scholar
  23. Killoran, A., M.P. Kelly ed. 2010. Evidence-based public health. Effectiveness and efficiency. New York: Oxford University Press.Google Scholar
  24. Machamer, P., L. Darden, C. Craver. 2000. Thinking about mechanisms. Philosophy of Science 67:1–25.CrossRefGoogle Scholar
  25. Rappaport, S.M., Smith, M.T. 2010. Environment and disease risks. Science 330:460–461.Google Scholar
  26. Reichenbach, H. 1956. The direction of time, 1971 edition. Berkeley, Los Angeles: University of California Press.Google Scholar
  27. Russell, B. 1913. On the notion of cause. Proceedings of the Aristotelian Society 13:1–26.Google Scholar
  28. Russell, B. 1948. Human knowledge. London: George Allen & Unwin.Google Scholar
  29. Russo, F. 2009. Causality and causal modelling in the social sciences. Measuring variations. Methodos Series. New York: Springer.Google Scholar
  30. Russo, F. 2011. Causal webs in epidemiology. Paradigmi XXXIX(1):67–98.Google Scholar
  31. Russo, F. 2012. Public health policy, evidence, and causation. Lessons from the studies on obesity. Medicine, Health Care, and Philosophy 15(2):141–151.CrossRefGoogle Scholar
  32. Russo, F., J. Williamson. 2007. Interpreting causality in the health sciences. International Studies in the Philosophy of Science 21(2):157–170.CrossRefGoogle Scholar
  33. Russo, F., J. Williamson. 2011a. Epistemic causality in medicine. History and Philosophy of the Life Sciences 33:389–396.Google Scholar
  34. Russo, F., J. Williamson. 2011b. Generic versus single-case causality: The case of autopsy. European Journal for Philosophy of Science 1(1):47–69.CrossRefGoogle Scholar
  35. Salmon, W.C. 1984. Scientific explanation and the causal structure of the world. Princeton, NJ: Princeton University Press.Google Scholar
  36. Salmon, W.C. 1997. Causality and explanation: A reply to two critiques. Philosophy of Science 64(3):461–477.CrossRefGoogle Scholar
  37. Scarff, K.L., K.S. Ung, H. Nandurkar, P.J. Crack, C.H. Bird, P.I. Bird. 2004. Targeted disruption of spi3/serpinb6 does not result in developmental or growth defects, leukocyte dysfunction, or susceptibility to stroke. Molecular and Cellular Biology 24(9):4075–4082.CrossRefGoogle Scholar
  38. Steel, D. 2007. Across the boundaries, extrapolation in biology and social science. Oxford: Oxford University Press.Google Scholar
  39. Thomas, D.C. 2006. High-volume “-omics” technologies and the future of molecular epidemiology. Epidemiology 17(5):490–491.CrossRefGoogle Scholar
  40. Vineis, P., M. Chadeau-Hyam. 2011. Integrating biomarkers into molecular epidemiological studies. Current Opinion in Oncology 23(1):100–105.CrossRefGoogle Scholar
  41. Vineis, P., Khan, A.E., Vlaanderen, J., Vermeulen, R. 2009. The impact of new research technologies on our understanding of environmental causes of disease: the concept of clinical vulnerability. Environmental Health 8(54)Google Scholar
  42. Vineis, P., Perera, F. 2007. Molecular epidemiology and biomarkers in etiologic cancer research: The new in light of the old. Cancer Epidemiology, Biomarkers & Prevention 16(10):1954–1965.CrossRefGoogle Scholar
  43. Weber, E. 2007. Conceptual tools for causal analysis in the social sciences. In Causality and probability in the sciences, eds. F. Russo, J. Williamson, 197–213. London: College Publications.Google Scholar
  44. Weber, E. 2009. How probabilistic causation can account for the use of mechanistic evidence. International Studies in the Philosophy of Science 23(3):277–295.CrossRefGoogle Scholar
  45. Williamson, J. 2005. Bayesian nets and causality: Philosophical and computational foundations. Oxford: Oxford University Press.Google Scholar
  46. Williamson, J. 2009. Probabilistic theories. In The Oxford handbook of causation, eds. H. Beebee, C. Hitchcock, P. Menzies, 185–212. Oxford: Oxford University Press.CrossRefGoogle Scholar
  47. Williamson, J. 2011. Mechanistic theories of causality. Philosophy Compass 6(6):421–447.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Center Leo ApostelVrije UniversiteitBrusselBelgium
  2. 2.Centre for ReasoningUniversity of KentKent,UK
  3. 3.Department of PhilosophyUniversity of KentKent,UK

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