Conceptions of Race and Ethnicity Used in Gene-Environment Interaction Studies

This qualitative, ethnographic project addresses a "Grand Challenge" for the future of genomic research and a NHGRI ELSI Research Program priority area: the analysis of the impact of genomics on concepts of race, ethnicity, and individual and group identity. The goals of the project are: (a) to describe how race and ethnicity are conceptualized by genetic epidemiologists in gene-environment interaction (GEI) studies of complex diseases; (b) to examine how those conceptions specifically and concretely impact GEI study design and actual, implemented study procedures, and (c) to analyze the consequences of the uses of race and ethnicity in GEI studies for societal understandings of race and ethnicity and individual and group differences. The controversies over the role of race and ethnicity in genomic research, documented variations in the use of race and ethnicity, and the influence that scientific findings have on societal beliefs and future research all indicate the importance of studying how genome scientists themselves conceptualize and use race and ethnicity in study design and implementation. Genetic epidemiologists conducting GEI research on the etiology of coronary heart disease (CHD), type 2 diabetes, and cancer comprise an important professional community in which to examine these questions. CHD, diabetes, and cancer are widely recognized to have genetic, behavioral, and social determinants, making a GEI approach an increasingly used modality to investigate the racial and ethnic disparities that characterize these diseases. Genetic epidemiologists frequently provide important leadership in GEI studies because of their disciplinary expertise in population-based approaches, the evaluation of multiple disease determinants, and the use of race and ethnicity. To date, no study has investigated these questions comprehensively among this professional community. Therefore, the specific aims of this study are: (1) to describe how genetic epidemiologists involved in federally-funded GEI studies of CHD, diabetes, and cancer etiology conceptualize race and ethnicity and understand their significance in GEI research; (2) to analyze how these conceptions of race and ethnicity influence the design and planned methods of GEI studies; and (3) to analyze how conceptions of race and ethnicity affect actual, implemented recruitment, data collection, analysis, and interpretation procedures, and the design of future studies. These data will be obtained from longitudinal, in-depth interviews with genetic epidemiologists, analyses of GEI study documents, and ethnographic observation of scientific conferences and ongoing GEI studies. Systematic qualitative data analysis procedures will be used to achieve the study aims. The long-term objectives of this project are: to anticipate and analyze how conceptions of race and ethnicity used in GEI research influence societal understandings of race, ethnicity, and individual and group identity; and to identify how policies and practices regarding the conceptualization, measurement, and interpretation of race and ethnicity in genomic research might be elaborated in ways that render them more meaningful or robust. PUBLIC HEALTH RELEVANCE: This project will yield new knowledge useful for improving the conceptualization of and methodological practices associated with race and ethnicity, particularly in the context of GEI research, a major emerging trend in genome science. Findings from this project can help inform how practices regarding the measurement and use of race and ethnicity might be standardized in ways that make them more meaningful and robust, and under what kinds of conditions genome scientists might find such standardization less than useful. This project will therefore provide important information both for considering the ethical and societal impact of genomic research on concepts of individual and group identity, and of race and ethnicity, and for shaping future measures and methods used in genomic and gene-environment interaction research on health disparities.