Mechanistic and topological explanations in medicine: the case of medical genetics and network medicine

Abstract

Medical explanations have often been thought on the model of biological ones and are frequently defined as mechanistic explanations of a biological dysfunction. In this paper, I argue that topological explanations, which have been described in ecology or in cognitive sciences, can also be found in medicine and I discuss the relationships between mechanistic and topological explanations in medicine, through the example of network medicine and medical genetics. Network medicine is a recent discipline that relies on the analysis of various disease networks (including diseasegene networks) in order to find organizing principles in disease explanation. My aim is to show how topological explanations in network medicine can help solving the conceptual issues that pure mechanistic explanations of the genetics of disease are currently facing, namely the crisis of the concept of genetic disease, the progressive geneticization of diseases and the dissolution of the distinction between monogenic and polygenic diseases. However, I will also argue that topological explanations should not be considered as independent and radically different from mechanistic explanations for at least two reasons. First, in network medicine, topological explanations depend on and use mechanistic information. Second, they leave out some missing gaps in disease explanation that require, in turn, the development of new mechanistic explanations. Finally, I will insist on the specific contribution of topological explanations in medicine: they push us to develop an explanation of disease in general, instead of focusing on single explanations of individual diseases. This last point may have major consequences for biomedical research.

General theory of topological explanations and explanatory asymmetry

“…If we take these lessons, a clearer path emerges when it comes to the solution of the asymmetry problem in topological explanations, namely, the counterfactual dependence is a structural feature of explanations that is available in both causal and noncausal explanations. Given that many philosophers argue that topological explanations are non-causal, because their explanans does not cite any causes, but rather mathematical properties of network topology [1,[26][27][28][29][30][31][32], then appealing to causation or causal facts is not an option for solving the asymmetry problem in topological explanations. A better way to approach the problem is to inquire whether the counterfactual dependence in topological explanations can account for explanatory asymmetry.…”

Phenomenological physiotherapy: extending the concept of bodily intentionality

“…Western medicine’s theoretical framework builds on the mechanistic physiology paradigm (Darrason 2018; Edwards 1998; Leder 1990; Savransky and Rosengarten 2016). Correspondingly, in Western countries, physiotherapists understand the body primarily as a physicochemical system of tissues and substances interconnected by causal relationships (Nicholls and Gibson 2010; Shaw and Connelly 2013).…”

Are topological explanations really free of mechanisms?

“…Nevertheless, the existence and prominence of non-mechanistic explanations in biology have long been recognized (Woodward 2013). Recent years see a surge of philosophical discussions on non-mechanistic explanations in various biosciences, including but not exclusive to ecology (Huneman 2010), evolutionary biology (Baker 2009;Huneman 2018b), neuroscience (Kostić 2018b), systems biology (Green et al 2018), immunology (Jones 2014) and network medicine (Darrason 2018). In these discussions, different types of non-mechanistic explanation have been identified, for example, dynamical model explanation (Ross 2015), minimal model explanation (Batterman and Rice 2014) and optimality explanation (Rice 2015).…”