This paper responds to recent criticisms of the idea that true causal claims, satisfying a minimal “interventionist” criterion for causation, can differ in the extent to which they satisfy other conditions—called stability and proportionality—that are relevant to their use in explanatory theorizing. It reformulates the notion of proportionality so as to avoid problems with previous formulations. It also introduces the notion of conditional independence or irrelevance, which I claim is central to understanding the respects and the extent to which upper (...) level explanations can be “autonomous”. (shrink)

This paper attempts to elucidate three characteristics of causal relationships that are important in biological contexts. Stability has to do with whether a causal relationship continues to hold under changes in background conditions. Proportionality has to do with whether changes in the state of the cause “line up” in the right way with changes in the state of the effect and with whether the cause and effect are characterized in a way that contains irrelevant detail. Specificity is connected both to (...) David Lewis’ notion of “influence” and also with the extent to which a causal relation approximates to the ideal of one cause–one effect. Interrelations among these notions and their possible biological significance are also discussed. (shrink)

A wide range of gene knockout experiments shows that functional stability is an important feature of biological systems. On this backdrop, we present an argument for higher‐level causation based on counterfactual dependence. Furthermore, we sketch a metaphysical picture providing resources to explain the metaphysical nature of functional stability, higher‐level causation, and the relevant notion of levels. Our account aims to clarify the role empirical results and philosophical assumptions should play in debates about reductionism and higher‐level causation. It thereby contributes to (...) the development of a philosophical foundation for systems biology. †To contact the authors, please write to: CSMN/IFIKK, University of Oslo, Box 1020 Blindern, N‐0315, Oslo, Norway; e‐mail: [email protected] , [email protected]. (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)

Heritability estimates obtained from genome-wide association studies are much lower than those of traditional quantitative methods. This phenomenon has been called the “missing heritability problem.” By analyzing and comparing GWAS and traditional quantitative methods, we first show that the estimates obtained from the latter involve some terms other than additive genetic variance, while the estimates from the former do not. Second, GWAS, when used to estimate heritability, do not take into account additive epigenetic factors transmitted across generations, while traditional quantitative (...) methods do. Given these two points we show that the missing heritability problem can largely be dissolved. (shrink)

Genome-wide association studies of human complex traits have provided us with new estimates of heritability. These estimates foreground the question of genetic causation. After having presen...

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)

Synthetic biology research is often described in terms of programming cells through the introduction of synthetic genes. Genetic material is seemingly attributed with a high level of causal responsibility. We discuss genetic causation in synthetic biology and distinguish three gene concepts differing in their assumptions of genetic control. We argue that synthetic biology generally employs a difference-making approach to establishing genetic causes, and that this approach does not commit to a specific notion of genetic program or genetic control. Still, we (...) suggest that a strong program concept of genetic material can be used as a successful heuristic in certain areas of synthetic biology. Its application requires control of causal context, and may stand in need of a modular decomposition of the target system. We relate different modularity concepts to the discussion of genetic causation and point to possible advantages of and important limitations to seeking modularity in synthetic biology systems. (shrink)

The paper argues for a pragmatic account of genetic explanation. This is to say that when a disease or other trait is termed genetic, the reasons for singling out genes as causes over other, also necessary, genetic and nongenetic conditions are not wholly theoretical but include pragmatic dimensions. Whether the explanation is the presence of a trait in an individual or differences in a trait among individuals, genetic explanations are context-dependent in three ways: they are relative to a causal background (...) of genetic and nongenetic factors; they are relative to a population; and they are relative to the present state of knowledge. Criteria like causal priority, nonstandardness, and causal efficacy that purport to distinguish objectively between genetic causes and nongenetic conditions either incorporate pragmatic elements or fail for other reasons. When the pragmatic dimensions of genetic explanations are recognized, we come to understand the current phenomenon of geneticization to be a reflection of increased technological capacities to manipulate genes in the laboratory, and potentially the clinic, rather than theoretical progress in understanding how diseases and other traits arise. This calls into question the value of the search for theoretical definitions of designations like genetic disease or genetic susceptibility as directives for action. (shrink)