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)

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)

Causation has multiple distinct meanings in genetics. One reason for this is meaning slippage between two concepts of the gene: Mendelian and molecular. Another reason is that a variety of genetic methods address different kinds of causal relationships. Some genetic studies address causes of traits in individuals, which can only be assessed when single genes follow predictable inheritance patterns that reliably cause a trait. A second sense concerns the causes of trait differences within a population. Whereas some single genes can (...) be said to cause population-level differences, most often these claims concern the effects of many genes. Polygenic traits can be understood using heritability estimates, which estimate the relative influences of genetic and environmental differences to trait differences within a population. Attempts to understand the molecular mechanisms underlying polygenic traits have been developed, although causal inference based on these results remains controversial. Genetic variation has also recently been leveraged as a randomizing factor to identify environmental causes of trait differences. This technique—Mendelian randomization—offers some solutions to traditional epidemiological challenges, although it is limited to the study of environments with known genetic influences. (shrink)

We are less optimistic than Madole & Harden that family-based genome-wide association studies (GWASs) will lead to significant second-generation causal knowledge. Despite bearing some similarities, family-based GWASs and randomised controlled trials (RCTs) are not identical. Most RCTs assess a relatively homogenous causal stimulus as a treatment, whereas GWASs assess highly heterogeneous causal stimuli. Thus, GWAS results will not translate so easily into second-generation causal knowledge.

When explaining the causes of human behavior, genes are often given a special status. They are thought to relate to an intrinsic human 'essence', and essentialist biases have been shown to skew the way in which causation is assessed. Causal reasoning in general is subject to other pre-existing biases, including beliefs about normativity and morality. In this synthesis we show how factors which influence causal reasoning can be mapped to a framework of genetic essentialism, which reveals both the shared and (...) unique factors underpinning biases in causal reasoning and genetic essentialism. This comparison identifies overlooked areas of research which could provide fruitful investigation, such as whether normative assessments of behaviors influence the way that genetic causes are ascribed or endorsed. We also outline the importance of distinguishing reasoning processes regarding genetic causal influences on one's self versus others, as different cognitive processes and biases are likely to be at play. (shrink)