Making the Mexican Diabetic: Race, Science, and the Genetics of Inequalityby Michael Montoya
This innovative ethnographic study animates the racial politics that underlie genomic research into type 2 diabetes, one of the most widespread chronic diseases and one that affects ethnic groups disproportionately. Michael J. Montoya follows blood donations from "Mexican-American" donors to laboratories that are searching out genetic contributions to diabetes. His analysis lays bare the politics and ethics of the research process, addressing the implicit contradiction of undertaking genetic research that reinscribes race’s importance even as it is being demonstrated to have little scientific validity. In placing DNA sampling, processing, data set sharing, and carefully crafted science into a broader social context, Making the Mexican Diabetic underscores the implications of geneticizing disease while illuminating the significance of type 2 diabetes research in American life.
“Timely. . . . [Montoya’s] critique that race and ethnicity are socially constructed is well taken.”
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Making the Mexican Diabetic
Race, Science, and the Genetics of Inequality
By Michael J. Montoya
UNIVERSITY OF CALIFORNIA PRESSCopyright © 2011 The Regents of the University of California
All rights reserved.
Biological or Social
Allelic Variation and the Making of Race in Single Nucleotide Polymorphism–Based Research
On a hot Chicago day, I work with Pedro, a graduate student from Texas, as he retrieves samples from the 12-by-12-foot walk-in cooler. It is a welcome retreat from the Midwest heat. Pedro's lab space is across the hall from the cooler. After shuttling a few times with Pedro as he replaces his samples and places the Styrofoam boxes onto the shelves, I notice that the shelves are loaded with such containers. Upon closer examination, I noted the inscriptions on the boxes presumably corresponding to their respective contents: "Jap 2/78," "MexAm," "Black," "Utah," "AfAm." Many of the boxes are more than ten years old. The array of nomenclature used to describe the populations mirrors the elasticity of ethnic identity in the United States over time and the general ambiguities of ethnic labeling. For example, labels for people of African ancestry change from "Black" to "African American" while other samples are labeled "MexAm," "Hispanic," or "Texas."
The lab, I soon discover, is teeming with what I will call "racial discourse." Racial discourse includes, among other things, labels on containers, abbreviations on reports, utterances from researchers, detailed and shorthand descriptions of human groups, and metalinguistic discussions about the origins of DNA samples. Racial discourse is productive and creative in Foucault's sense. That is, it is not simply "groups of signs (signifying elements referring to contents or representations)," discourse consists of "practices that systematically form the objects of which they speak." This book is a record of the processes of racial discursive formation that are produced, circulated, or consumed by the complex concatenation of people, places, and things that make up the diabetes enterprise.
On my first day at the lab, I phone Nora from the security desk, and she comes down to meet me. We wend our way through the maze of corridors and elevators to the endowed endocrinology research wing. Set off by richly grained wooden railings and distinctive wall and flooring color schemes, the wing houses the laboratories of Gary and three other scientists. Nora is a white woman in her mid-forties who started in Gary's lab as a postdoc after receiving her Ph.D. in human genetics from Yale. She was Gary's first postdoc. That was in 1982. She is now an associate professor in the departments of human genetics and medicine. Gary is a white middle-aged man who was trained in biochemistry at the University of California—San Francisco during the 1970s. He is now a professor in the departments of biochemistry and molecular biology, human genetics, and medicine.
The capital improvements of the wing are announced by gold-lettered signage that pays homage to the donor. I arrive at 11 a.m., and thirty minutes later Nora is in her first meeting of the day. A colleague from the genetics department arrived to discuss a project using "a big Mormon family" and a Hutterite data set. The scientist came to Nora to discuss typing methods, genetic markers to be used, and genotype and phenotype issues related to heritability of genes hypothesized to cause polycystic ovarian syndrome (PCOS, which is sometimes associated with diabetes) in these groups.
At 12:10 p.m., two other colleagues arrive to talk with Nora. One is an endocrinologist whose office is down the hall, a few doors away from the endowed wing, and the other is a postdoc from Nora's dry lab. Carrying over her earlier conversation, Nora asks the endocrinologist if he would genotype a PCOS polymorphism in his samples. The researcher says it will take about a week, and talk moves to another project. Nora's postdoc had been running statistical tests for the endocrinologist, who remarks that the findings suggest a racial admixture, which, as will be revealed, is a common theme among diabetes researchers. In this encounter, no specific ethnic label is used, and the talk quickly turns to results from another study.
Twenty minutes later Nora and I are dashing through the hospital for her next meeting. A senior colleague, a pediatric endocrinologist, sought Nora's advice on his research. This colleague is new to research in general and newer still to genetics and statistics. He, too, is searching for PCOS genes, but the genotyping results of his ten subjects contained multiple errors. Of these ten, there are "five black samples" (which were referred to also as "African American"); the rest are "Caucasians." After explaining the errors and encouraging the colleague to go back and have his genotyping redone, Nora concludes the meeting. On the walk back to the lab, Nora explains that while the pediatric endocrinologist, whom I would not see or hear about again, is likely an outstanding diagnostician and thus able to make phenotypic connections that most could not, he is not familiar with the basics of research design. He had, for example, found in his workup high levels of testosterone in his female subjects and thus spent some time trying to convince Nora (unsuccessfully) that the resultant increased musculature would confer evolutionary advantage that could be an important factor in the heritability of PCOS.
Back at her office I ask about PCOS, about the Hardy-Wienberg test, about the pediatric endocrinologist and his evolutionary theories, and about admixture. On the latter point, Nora offered the following explanation:
If we were to do a collaboration with Penn [University of Pennsylvania] using Philadelphia's Italians and Chicago's eastern Europeans and Poles, they could have differences based upon geographic clines [in the United States] east to west and north to south. Maybe it would be due to migration out of Africa or selective advantages. It doesn't matter why they differ, but if you don't control for population genetics you will miss it if one heterozygote is preferentially passed on.... Africans and African Americans or black samples from Europe are most likely north-to-south clinal variations. The increased similarity in allele frequency decreases the chances of clinal differences.
Later in the day Nora has other meetings including her usual back-and-forth with Gary and responses to my queries. Most of Nora's days consist of scheduled and impromptu meetings and phone calls, e-mails, and mail from across the corridor, the campus, the country, and continents. The volume of interactions between Nora and her collaborators make the pace of life in the lab, and thus following her physically and intellectually, very challenging. I was, at first, reluctant to intrude. Yet within days the novelty of my presence wore off, and Nora no longer introduced me as the anthropologist—à la J. K. Rowling "wearing a cloak of invisibility"—whom they should all ignore.
From this first day, the complexity of racial discourse in the diabetes enterprise was evident. The admixture narrative above reveals that the racial discourse of the lab draws upon population genetics, biological anthropology, evolution, statistics, human genetics, and physiology. Yet Nora's use of Euro-American ethnic groups and three diverse groups with African ancestry suggests that additional knowledges inform the racial discourse of the diabetes enterprise as well. While Nora's explanation of admixture that first day was simplistic and general—most likely for the benefit of her audience (me)—I would soon observe the complex scientific narratives about Africans, African Americans, European blacks, and a host of other groups. In fact, as I discuss in the sections and chapters that follow, Nora and her international colleagues in the diabetes enterprise routinely practice a racial discourse that troubles any notion that scientists are isolated from the social, cultural, and historical particularities of humans in the present moment. That is, racial discourse is shot through with contemporary social and historical realities.
By examining the racial discourse in the Chicago lab, my aim is to critically evaluate the race–no-race debates by elaborating the specific ways social constructions of race and ethnicity permeate the use of populations in the diabetes enterprise. This chapter sets the stage for those that follow by arguing that (1) race is not simplistically rebiologized; (2) words that describe groups are inherited from outside the labs; and (3) the rhetoric of danger that circulates in the ethical discussions about race in science and medicine is a discursive battlefield in which contested futures of racial stratification compete with one another using as evidence narratives of past abuses of medico-scientific power. To begin this discussion, I will attend to the ways scientists use and rationalize their use of ethnically labeled groups for diabetes genetics research. The racial discourse they use will be assessed for its reiteration of biological notions of racial difference in comparison with that of forensic sciences. Then I will return to the race–no-race debates to examine the ways the debates themselves stumble upon the presumption that science and society are somehow separate.
DIABETES GENETIC EPIDEMIOLOGY: UNIQUE AND THRIFTY GENES
The racial discourse of the diabetes enterprise must be understood as a series of interlocking processes that involve production, circulation, and consumption of knowledges of and about disease, human biology, and ethnicity or race. Following scientists and blood samples through these discursive phases—the methodological and analytical strategy used for this research—is necessary to witness how racial discourse in the diabetes enterprise is constituted by social and material formations that are neither exclusively social nor bioscientific. By disaggregating these discursive phases we are able to see that the separation implied in the social/biological opposition is itself an artifice of a particular time and place, the explication of which is the aim of this book. We begin with the production of racial discourse as discerned in the Chicago laboratories of Gary and Nora.
In 2000, after several years of work, the main cluster of collaborator-informants with whom I work announced in the journal Nature Genetics the discovery of a polygene that confers susceptibility to type 2 diabetes. A polygene is an inherited set of genetic material from multiple chromosomes that together influence a phenotype. The report is significant for several reasons. First, it is the culmination of years of collaborative work across national, institutional, and disciplinary boundaries. Researchers from an array of disciplines and from state, corporate, and academic settings on three continents contributed to its production. Equally important is that the researchers reported having found a combination of genetic material that confers susceptibility to type 2 diabetes. As such, it was the first published report of a genetic association with disease susceptibility for a multigene disease with a rich environmental etiology. The report was so significant that it was accompanied by two commentaries, one on the methodological complexity of the report and the other a critique of the general merit of looking for genetic causes for diseases such as type 2 diabetes, which is well known to have environmental causes. The latter editorial reflects an open debate within diabetes sciences about the cost-benefit ratio of researching the genetics of complex diseases in light of the methodological complexity and immense uncertainty that the findings will result in any beneficial outcomes. The polygene finding is anthropologically interesting because the different bits of genetic material are thought to be variably found in different ethnoracial groups, which forms an important basis for the ways racial and ethnic admixture figures in diabetes science. Some diabetes scientists debate the appropriateness of using race and ethnicity at all by arguing that doing so detracts from closer scrutiny of gene locus-phenotype-trait interactions as opposed to noninteractive models. The stakes of these debates will become clearer as we examine the complex methodological approach used by researchers within the diabetes enterprise.
Genetic analysis is generally considered to be the process of drawing inferences from genetic data. The genetic analysis used by diabetes genetic epidemiology researchers is a statistical, computer-assisted, highly codified, and abstracted practice whereby the quantitative distribution of genetic variation is used to infer ways that known genetic material affects a phenotype. It is also used to hunt for genes or genetic material that affect a phenotypic group, such as diabetics, or for diabetes-specific genetic material in particular ethnic or racial populations. The selection of particular populations for genetic analysis is the subject of this discussion.
The process of diabetes genetic analysis, which I will unpack below, involves increasingly finer grained localization of genetic material. Imagine the levels of analysis as follows: humanity, subpopulation, diabetic versus nondiabetic, genetic material, specific bits of genetic material, combinations of specific bits of genetic material. It is complicated because researchers are looking for code within code. Whereas some diseases are caused by single genes that are always present in affected persons—that is, they follow standard Mendelian inheritance patterns—most common diseases do not follow this standard. The genetic contributions to common diseases remains elusive because they are thought to involve multiple genes or multiple variants of genes that, compared with those found in the general population, are believed to put an individual at increased risk. Complicating things further are the heterogeneous factors external to the physical body that significantly affect who gets sick and who does not. This makes complex disease gene research exponentially more complicated than research into monogenetic conditions. Because genetic analysis is principally concerned with interpreting genetic information, the practice of analysis occurs after samples have been collected and the genetic information has been extracted.
While the process is not entirely linear, it is useful to distinguish between sampling, genotyping, analysis, physiological research, drug target studies, and translational studies. Table 1 outlines the process in linear form from sampling to developing therapies. For each research practice, there are numerous steps, methods, techniques, histories, and controversies. Because diabetes genetic epidemiology is a collaborative venture requiring the participation of scientists involved in any number of areas of research, the controversies are largely glossed over until a problem arises.
The acquisition and use of population DNA is the first requirement for this kind of science. It is the raw material from which the genetic data are derived. When queried, scientists say that the rationale for the use of ethnically and racially classified populations in diabetes research has little to do with the population per se. When asked why the South Texas Mexicana/o group was used, for example, one scientist remarked, "We're not going to learn everything we need to know about the genetics of type 2 diabetes from our studies of Mexican Americans, but it's a useful population in which to work." Other scientists report the reasons are public health concerns. When asked why low-income Mexican Americans were sampled in a randomized way, another scientist explained, "That's where the highest rates of diabetes are ... and lower-income Mexican Americans have a higher rate than the suburbanites. It's a huge public health problem." Other reasons for the use of Mexican Americans are more pragmatically oriented to collecting samples. One geneticist remarked, "We were looking for a county in which the population was small enough that we could legitimately go in and characterize the whole county."
Excerpted from Making the Mexican Diabetic by Michael J. Montoya. Copyright © 2011 The Regents of the University of California. Excerpted by permission of UNIVERSITY OF CALIFORNIA PRESS.
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Meet the Author
Michael J. Montoya is Associate Professor of Anthropology, Chicano/Latino Studies&Public Health at the University of California, Irvine.
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