Philosophy of race meets population genetics

Towards the multileveled and processual conceptualisation of racialised individuals in biomedical research

In this paper, we discuss the processes of racialisation on the example of biomedical research. We argue that applying the concept of racialisation in biomedical research can be much more precise, informative and suitable than currently used categories, such as race and ethnicity. For this purpose, we construct a model of the different processes affecting and co-shaping the racialisation of an individual, and consider these in relation to biomedical research, particularly to studies on hypertension. We finish with a discussion on the potential application of our proposition to institutional guidelines on the use of racial categories in biomedical research.

Re-situations of scientific knowledge: a case study of a skirmish over clusters vs clines in human population genomics

We track and analyze the re-situation of scientific knowledge in the field of human population genomics ancestry studies. We understand re-situation as a process of accommodating the direct or indirect transfer of objects of knowledge from one site/situation to (one or many) other sites/situations. Our take on the concept borrows from Mary S. Morgan's work on facts traveling while expanding it to include other objects of knowledge such as models, data, software, findings, and visualizations. We structure a specific case study by tracking the re-situation of these objects between three research projects studying human population diversity reported in three articles in Science, Genome Research and PLoS Genetics between 2002 and 2005. We characterize these three engagements as a unit of analysis, a "skirmish," in order to compare: (a) the divergence of interests in how life-scientists answer similar research questions and (b) to track the challenging transformation of workflows in research laboratories as these scientific objects are re-situated individually or in bundles. Our analysis of the case study shows that an accurate understanding of re-situation requires tracking the whole bundle of objects in a project because they interact in particular key ways. The absence or dismissal of these interactions opens the door to unforeseen trade-offs, misunderstandings and misrepresentations about research design(s) and workflow(s) and what these say about the questions asked and the findings produced.

Medicine, anti-realism and ideology: Variation in medical genetics does not show that race is biologically real

Lee McIntyre’s Respecting Truth chronicles the contemporary challenges regarding the relationship amongst evidence, belief formation and ideology. The discussion in his book focusses on the ‘politicisation of knowledge’ and the purportedly growing public (and sometimes academic) tendency to choose to believe what is determined by prior ideological commitments rather than what is determined by evidence-based reasoning. In considering these issues, McIntyre posits that the claim “race is a myth” is founded on a political ideology rather than on support from scientific evidence. He contrasts this view with the argument that racially correlated biomedical outcomes for self-identified racial groups suggest that biological races are real. I explore how McIntyre’s framing of the claim “race is a myth” as fundamentally ideological results in him failing to engage with the arguments and evidence many constructionists and biological anti-realists put forward in support of their views. I also show how the biomedical evidence he thinks supports biological realism is unconvincing.

Thinking about populations and races in time

Biologists and philosophers have offered differing concepts of biological race. That is, they have offered different candidates for what a biological correlate of race might be; for example, races might be subspecies, clades, lineages, ecotypes, or genetic clusters. One thing that is striking about each of these proposals is that they all depend on a concept of population. Indeed, some authors have explicitly characterized races in terms of populations. However, including the concept of population into concepts of race raises three puzzles, all having to do with time. In this paper, I extend the causal interactionist population concept (CIPC) by introducing some simple assumptions about how to understand populations through time. These assumptions help to shed light on the three puzzles, and in the process show that if we want to understand races in terms of populations, we will need to revise our concept(s) of race.

Gould on Morton, Redux: What can the debate reveal about the limits of data?

Lewis et al. (2011) attempted to restore the reputation of Samuel George Morton, a 19th century physician who reported on the skull sizes of different folk-races. Whereas Gould (1978) claimed that Morton's conclusions were invalid because they reflected unconscious bias, Lewis et al. alleged that Morton's findings were, in fact, supported, and Gould's analysis biased. We take strong exception to Lewis et al.'s thesis that Morton was "right." We maintain that Gould was right to reject Morton's analysis as inappropriate and misleading, but wrong to believe that a more appropriate analysis was available. Lewis et al. fail to recognize that there is, given the dataset available, no appropriate way to answer any of the plausibly interesting questions about the "populations" in question (which in many cases are not populations in any biologically meaningful sense). We challenge the premise shared by both Gould and Lewis et al. that Morton's confused data can be used to draw any meaningful conclusions. This, we argue, reveals the importance of properly focusing on the questions asked, rather than more narrowly on the data gathered.

A reconsideration of the role of self-identified races in epidemiology and biomedical research

A considerable number of studies in epidemiology and biomedicine investigate the etiology of complex diseases by considering (self-identified) race as a relevant variable and focusing on the differences in risk among racial groups in the United States; they extensively draw on a genetic hypothesis--viz. the hypothesis that differences in the risk of complex diseases among racial groups are largely due to genetic differences covarying with genetic ancestry--that appears highly problematic in the light of both current biological evidence and the theory of human genome evolution. Is this reason for dismissing self-identified races? No. An alternative promising use of self-identified races exists, and ironically is suggested by those studies that investigate the etiology of complex diseases without focusing on racial differences. These studies provide a large amount of empirical evidence supporting the primacy of the contribution of non-genetic as opposed to genetic factors to the risk of complex diseases. We show that differences in race--or, better, in racial self-identification--may be critically used as proxies for differences in risk-related exposomes and epigenomes in the context of the United States. Self-identified race is what we need to capture the complexity of the effects of present and past racism on people's health and investigate risk-related external and internal exposures, gene-environment interactions, and epigenetic events. In fact patterns of racial self-identifications on one side, and patterns of risk-related exposomes and epigenomes on the other side, constantly coevolve and tend to match each other. However, there is no guarantee that using self-identified races in epidemiology and biomedical research will be beneficial all things considered: special attention must be paid at balancing positive and negative consequences.

Implications of the apportionment of human genetic diversity for the apportionment of human phenotypic diversity

Researchers in many fields have considered the meaning of two results about genetic variation for concepts of "race." First, at most genetic loci, apportionments of human genetic diversity find that worldwide populations are genetically similar. Second, when multiple genetic loci are examined, it is possible to distinguish people with ancestry from different geographical regions. These two results raise an important question about human phenotypic diversity: To what extent do populations typically differ on phenotypes determined by multiple genetic loci? It might be expected that such phenotypes follow the pattern of similarity observed at individual loci. Alternatively, because they have a multilocus genetic architecture, they might follow the pattern of greater differentiation suggested by multilocus ancestry inference. To address the question, we extend a well-known classification model of Edwards (2003) by adding a selectively neutral quantitative trait. Using the extended model, we show, in line with previous work in quantitative genetics, that regardless of how many genetic loci influence the trait, one neutral trait is approximately as informative about ancestry as a single genetic locus. The results support the relevance of single-locus genetic-diversity partitioning for predictions about phenotypic diversity.

The mind, the lab, and the field: Three kinds of populations in scientific practice

Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R. A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: the notion of "effective" population size, the work of Thomas Park on Tribolium populations, and model-based clustering algorithms such as Structure. Finally, we discuss ways to move safely between three distinct population types while avoiding confusing models and reality.