In this paper, we analyse the relation between the use of environmental data in contemporary health sciences and related conceptualisations and operationalisations of the notion of environment. We consider three case studies that exemplify a different selection of environmental data and mode of data integration in data-intensive epidemiology. We argue that the diversification of data sources, their increase in scale and scope, and the application of novel analytic tools have brought about three significant conceptual shifts. First, we discuss the EXPOsOMICS (...) project, an attempt to integrate genomic and environmental data which suggests a reframing of the boundaries between external and internal environments. Second, we explore the MEDMI platform, whose efforts to combine health, environmental and climate data instantiate a reframing and expansion of environmental exposure. Third, we illustrate how extracting epidemiological insights from extensive social data collected by the CIDACS institute yields innovative attributions of causal power to environmental factors. Identifying these shifts highlights the benefits and opportunities of new environmental data, as well as the challenges that such tools bring to understanding and fostering health. It also emphasises the constraints that data selection and accessibility pose to scientific imagination, including how researchers frame key concepts in health-related research. (shrink)

Human microbiome research makes causal connections between entire microbial communities and a wide array of traits that range from physiological diseases to psychological states. To evaluate these causal claims, we first examine a well-known single-microbe causal explanation: of Helicobacter pylori causing ulcers. This apparently straightforward causal explanation is not so simple, however. It does not achieve a key explanatory standard in microbiology, of Koch’s postulates, which rely on manipulations of single-microorganism cultures to infer causal relationships to disease. When Koch’s postulates (...) are framed by an interventionist causal framework, it is clearer what the H. pylori explanation achieves and where its explanatory strengths lie. After assessing this ‘simple’, single-microbe case, we apply the interventionist framework to two key areas of microbiome research, in which obesity and mental health states are purportedly explained by microbiomes. Despite the experimental data available, interventionist criteria for explanation show that many of the causal claims generated by microbiome research are weak or misleading. We focus on the stability, specificity and proportionality of proposed microbiome causal explanations, and evaluate how effectively these dimensions of causal explanation are achieved in some promising avenues of research. We suggest some conceptual and explanatory strategies to improve how causal claims about microbiomes are made. (shrink)

Modern medicine is often said to have originated with nineteenth century germ theory, which attributed diseases to bacterial contagions. The success of this theory is often associated with an underlying principle referred to as the “doctrine of specific etiology”. This doctrine refers to specificity at the level of disease causation or etiology. While the importance of this doctrine is frequently emphasized in the philosophical, historical, and medical literature, these sources lack a clear account of the types of specificity that it (...) involves and why exactly they matter. This paper argues that nineteenth century germ theory involves two types of specificity at the level of etiology. One type receives significant attention in the literature, but its influence on modern medicine has been misunderstood. A second type is present in this model, but it has been completely overlooked in the extant literature. My analysis clarifies how these types of specificity led to a novel conception of etiology that continues to figure in medicine today. (shrink)

This commentary focuses on the authors’ treatment of Koch’s postulates. It argues in favour of a modification of Koch’s postulates and their analysis in terms of necessary and sufficient conditions. This leads to a criticism of the authors’ treatment of the C. difficile case, and to query the need for the criteria of specificity and proportionality.

Human microbiome research makes causal connections between entire microbial communities and a wide array of traits that range from physiological diseases to psychological states. To evaluate these causal claims, we first examine a well-known single-microbe causal explanation: of Helicobacter pylori causing ulcers. This apparently straightforward causal explanation is not so simple, however. It does not achieve a key explanatory standard in microbiology, of Koch’s postulates, which rely on manipulations of single-microorganism cultures to infer causal relationships to disease. When Koch’s postulates (...) are framed by an interventionist causal framework, it is clearer what the H. pylori explanation achieves and where its explanatory strengths lie. After assessing this ‘simple’, single-microbe case, we apply the interventionist framework to two key areas of microbiome research, in which obesity and mental health states are purportedly explained by microbiomes. Despite the experimental data available, interventionist criteria for explanation show that many of the causal claims generated by microbiome research are weak or misleading. We focus on the stability, specificity and proportionality of proposed microbiome causal explanations, and evaluate how effectively these dimensions of causal explanation are achieved in some promising avenues of research. We suggest some conceptual and explanatory strategies to improve how causal claims about microbiomes are made. (shrink)

Complex organisms thwart the simple rectilinear causality paradigm of “necessary and sufficient,” with its experimental strategy of “knock down and overexpress.” This Essay organizes the eccentricities of biology into four categories that call for new mathematical approaches; recaps for the biologist the philosopher's recent refinements to the causation concept and the mathematician's computational tools that handle some but not all of the biological eccentricities; and describes overlooked insights that make causal properties of physical hierarchies such as emergence and downward causation (...) straightforward. Reviewing and extrapolating from similar situations in physics, it is suggested that new mathematical tools for causation analysis incorporating feedback, signal cancellation, nonlinear dependencies, physical hierarchies, and fixed constraints rather than instigative changes will reveal unconventional biological behaviors. These include “eigenisms,” organisms that are limited to quantized states; trajectories that steer a system such as an evolving species toward optimal states; and medical control via distributed “sheets” rather than single control points. (shrink)

. Early microbiome research found numerous associations between microbial community patterns and host physiological states. These findings hinted at community-level explanations. “Top-down” experiments, working with whole communities, strengthened these explanatory expectations. Now, “bottom-up” mechanism-seeking approaches are dissecting communities to focus on specific microbes carrying out particular biochemical activities. To understand the interplay between methodological and explanatory scales, we examine claims of “dysbiosis,” when host illness is proposed as the consequence of a community state. Our analysis concludes with general observations about (...) how methodologies relate to explanations, and the implications for microbiome research. (shrink)

Complex organisms thwart the simple rectilinear causality paradigm of “necessary and sufficient,” with its experimental strategy of “knock down and overexpress.” This Essay organizes the eccentricities of biology into four categories that call for new mathematical approaches; recaps for the biologist the philosopher's recent refinements to the causation concept and the mathematician's computational tools that handle some but not all of the biological eccentricities; and describes overlooked insights that make causal properties of physical hierarchies such as emergence and downward causation (...) straightforward. Reviewing and extrapolating from similar situations in physics, it is suggested that new mathematical tools for causation analysis incorporating feedback, signal cancellation, nonlinear dependencies, physical hierarchies, and fixed constraints rather than instigative changes will reveal unconventional biological behaviors. These include “eigenisms,” organisms that are limited to quantized states; trajectories that steer a system such as an evolving species toward optimal states; and medical control via distributed “sheets” rather than single control points. (shrink)

The dual role of microbial communities as either beneficial/functional or harmful/pathogenic involves two issues concerning causality in physiology and medicine, etiology of disease, and the notion of function in biology. Causal explanation formulated by the germ theory of disease and the Koch postulates connects the existence of a specifically identified microbe to disease by the isolation and identification of a pathogen from an organism with the disease and the successful infection of a healthy individual. Similarly, microbiome research in medicine centers (...) on taxonomic composition in correlation with physiological conditions and germ-free mice experimentations to establish causal connections. However, because the microbiome is an ecological community, it lacks the specificity of identification assumed in the germ theory. Furthermore, the ecological aspects within and between microbiomes such as background conditions, microbial interactions, and interdependence, are treated as confounding. Looking at ecological studies, the causal explanations are less specific regarding complex systems with their processes of interactions. This article makes the following two points: One is that microbiome causality in the host should be understood similarly to the microbiome causality in an ecosystem. The second is that if considering a microbiome’s causality in the host as an ecosystem, its etiological explanation needs to be revisited to include a heterogeneous and mutual notion of interactions. Finally, according to the second point, the notion of function in ecology with its relevant notion of causality should be considered accordingly. (shrink)

Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how (...) invariance could be qualified for such variables. (shrink)