Genetic admixture, self-reported ethnicity, self-estimated admixture, and skin pigmentation among Hispanics and Native Americans

The relationship between ethnicity and biology is of interest to anthropologists, biomedical scientists, and historians in understanding how human groups are constructed. Ethnic self-identification in recently admixed groups such as Hispanics, African Americans, and Native Americans (NA) is likely to be complex due to the heterogeneity in individual admixture proportions and social environments within these groups. This study examines the relationships between self-identified ethnicity, self-estimated admixture proportions, skin pigmentation, and genetic marker estimated admixture proportions. These measures were assessed using questionnaires, skin color measurements, and genotyping of a panel of 76 ancestry informative markers, among 170 Hispanics and NAs from New Mexico, a state known for its complex history of interactions between people of NA and European (EU) ancestry. Results reveal that NAs underestimate their degree of EU admixture, and that Hispanics underestimate their degree of NA admixture. Within Hispanics, genetic-marker estimated admixture is better predicted by forehead skin pigmentation than by self-estimated admixture. We also find that Hispanic individuals self-identified as "half-White, half Hispanic" and "Spanish" have lower levels of NA admixture than those self-identified as "Mexican" and "Mexican American." Such results highlight the interplay between culture and biology in how individuals identify and view themselves, and have implications for how ethnicity and disease risk are assessed in a medical setting.     

Genetic ancestry, self-reported race and ethnicity in African Americans and European Americans in the PCaP cohort

Background

Family history and African-American race are important risk factors for both prostate cancer (CaP) incidence and aggressiveness. When studying complex diseases such as CaP that have a heritable component, chances of finding true disease susceptibility alleles can be increased by accounting for genetic ancestry within the population investigated. Race, ethnicity and ancestry were studied in a geographically diverse cohort of men with newly diagnosed CaP.

Methods

Individual ancestry (IA) was estimated in the population-based North Carolina and Louisiana Prostate Cancer Project (PCaP), a cohort of 2,106 incident CaP cases (2063 with complete ethnicity information) comprising roughly equal numbers of research subjects reporting as Black/African American (AA) or European American/Caucasian/Caucasian American/White (EA) from North Carolina or Louisiana. Mean genome wide individual ancestry estimates of percent African, European and Asian were obtained and tested for differences by state and ethnicity (Cajun and/or Creole and Hispanic/Latino) using multivariate analysis of variance models. Principal components (PC) were compared to assess differences in genetic composition by self-reported race and ethnicity between and within states.

Results

Mean individual ancestries differed by state for self-reporting AA (p = 0.03) and EA (p = 0.001). This geographic difference attenuated for AAs who answered “no” to all ethnicity membership questions (non-ethnic research subjects; p = 0.78) but not EA research subjects, p = 0.002. Mean ancestry estimates of self-identified AA Louisiana research subjects for each ethnic group; Cajun only, Creole only and both Cajun and Creole differed significantly from self-identified non-ethnic AA Louisiana research subjects. These ethnicity differences were not seen in those who self-identified as EA.

Conclusions

Mean IA differed by race between states, elucidating a potential contributing factor to these differences in AA research participants: self-reported ethnicity. Accurately accounting for genetic admixture in this cohort is essential for future analyses of the genetic and environmental contributions to CaP.     

Race, ethnicity, and health: can genetics explain disparities?

Over the past decade, numerous studies have documented profound racial and ethnic disparities in disease in the United States. This essay examines how popular and scientific concepts of race and ethnicity converge with dominant understandings of genetics to inform the design and interpretation of research, public health policy, and medical practice. Although there is some acknowledgment in the biomedical community that racial and ethnic categories are social and not genetic, ideas about race and ethnicity that circulate in biomedicine are contradictory. Thus, in practice genetic explanations for observed differences are common both in the scientific literature and in popular media accounts of biomedical research. Such explanations naturalize racial and ethnic difference and create a conceptual barrier to developing a research program that explores the complex ways in which social inequality and experiences of racial discrimination interact with human biology to influence patterns of disease. Importantly, genetically based ideas lead to disease prevention policies that are bound to be ineffective.     

Genetic structure, self-identified race/ethnicity, and confounding in case-control association studies

We have analyzed genetic data for 326 microsatellite markers that were typed uniformly in a large multiethnic population-based sample of individuals as part of a study of the genetics of hypertension (Family Blood Pressure Program). Subjects identified themselves as belonging to one of four major racial/ethnic groups (white, African American, East Asian, and Hispanic) and were recruited from 15 different geographic locales within the United States and Taiwan. Genetic cluster analysis of the microsatellite markers produced four major clusters, which showed near-perfect correspondence with the four self-reported race/ethnicity categories. Of 3,636 subjects of varying race/ethnicity, only 5 (0.14%) showed genetic cluster membership different from their self-identified race/ethnicity. On the other hand, we detected only modest genetic differentiation between different current geographic locales within each race/ethnicity group. Thus, ancient geographic ancestry, which is highly correlated with self-identified race/ethnicity--as opposed to current residence--is the major determinant of genetic structure in the U.S. population. Implications of this genetic structure for case-control association studies are discussed.     

Characterization of mitochondrial haplogroups in a large population-based sample from the United States

Mitochondrial DNA (mtDNA) haplogroups are valuable for investigations in forensic science, molecular anthropology, and human genetics. In this study, we developed a custom panel of 61 mtDNA markers for high-throughput classification of European, African, and Native American/Asian mitochondrial haplogroup lineages. Using these mtDNA markers, we constructed a mitochondrial haplogroup classification tree and classified 18,832 participants from the National Health and Nutrition Examination Surveys (NHANES). To our knowledge, this is the largest study to date characterizing mitochondrial haplogroups in a population-based sample from the United States, and the first study characterizing mitochondrial haplogroup distributions in self-identified Mexican Americans separately from Hispanic Americans of other descent. We observed clear differences in the distribution of maternal genetic ancestry consistent with proposed admixture models for these subpopulations, underscoring the genetic heterogeneity of the United States Hispanic population. The mitochondrial haplogroup distributions in the other self-identified racial/ethnic groups within NHANES were largely comparable to previous studies. Mitochondrial haplogroup classification was highly concordant with self-identified race/ethnicity (SIRE) in non-Hispanic whites (94.8 %), but was considerably lower in admixed populations including non-Hispanic blacks (88.3 %), Mexican Americans (81.8 %), and other Hispanics (61.6 %), suggesting SIRE does not accurately reflect maternal genetic ancestry, particularly in populations with greater proportions of admixture. Thus, it is important to consider inconsistencies between SIRE and genetic ancestry when performing genetic association studies. The mitochondrial haplogroup data that we have generated, coupled with the epidemiologic variables in NHANES, is a valuable resource for future studies investigating the contribution of mtDNA variation to human health and disease.     

Anthropological insights into the use of race/ethnicity to explore genetic contributions to disparities in health

Anthropological insights into the use of race/ethnicity to explore genetic contributions to disparities in health were developed using in-depth qualitative interviews with editorial staff from nineteen genetics journals, focusing on the methodological and conceptual mechanisms required to make race/ethnicity a genetic variable. As such, these analyses explore how and why race/ethnicity comes to be used in the context of genetic research, set against the background of continuing critiques from anthropology and related human sciences that focus on the social construction, structural correlates and limited genetic validity of racial/ethnic categories. The analyses demonstrate how these critiques have failed to engage geneticists, and how geneticists use a range of essentially cultural devices to protect and separate their use of race/ethnicity as a genetic construct from its use as a societal and social science resource. Given its multidisciplinary, biosocial nature and the cultural gaze of its ethnographic methodologies, anthropology is well placed to explore the cultural separation of science and society, and of natural and social science disciplines. Anthropological insights into the use of race/ethnicity to explore disparities in health suggest that moving beyond genetic explanations of innate difference might benefit from a more even-handed critique of how both the natural and social sciences tend to essentialize selective elements of race/ethnicity. Drawing on the example of HIV/AIDS, this paper demonstrates how public health has been undermined by the use of race/ethnicity as an analytical variable, both as a cipher for innate genetic differences in susceptibility and response to treatment, and in its use to identify 'core groups' at greater risk of becoming infected and infecting others. Clearly, a tendency for biological reductionism can place many biomedical issues beyond the scope of public health interventions, while socio-cultural essentialization has tended to stigmatize 'unhealthy behaviours' and the communities where these are more prevalent.     

Ethnicity, body mass, and genome-wide data

This article combines social and genetic epidemiology to examine the influence of self-reported ethnicity on body mass index (BMI) among a sample of adolescents and young adults. We use genetic information from more than 5,000 single nucleotide polymorphisms in combination with principal components analysis to characterize population ancestry of individuals in this study. We show that non-Hispanic white and Mexican-American respondents differ significantly with respect to BMI and differ on the first principal component from the genetic data. This first component is positively associated with BMI and accounts for roughly 3% of the genetic variance in our sample. However, after controlling for this genetic measure, the observed ethnic differences in BMI remain large and statistically significant. This study demonstrates a parsimonious method to adjust for genetic differences among individual respondents that may contribute to observed differences in outcomes. In this case, adjusting for genetic background has no bearing on the influence of self-identified ethnicity.     

Comparing genetic ancestry and self-reported race/ethnicity in a multiethnic population in New York City

Self-reported race/ethnicity is frequently used in epidemiological studies to assess an individual’s background origin. However, in admixed populations such as Hispanic, self-reported race/ethnicity may not accurately represent them genetically because they are admixed with European, African and Native American ancestry. We estimated the proportions of genetic admixture in an ethnically diverse population of 396 mothers and 188 of their children with 35 ancestry informative markers (AIMs) using the STRUCTURE version 2.2 program. The majority of the markers showed significant deviation from Hardy-Weinberg equilibrium in our study population. In mothers self-identified as Black and White, the imputed ancestry proportions were 77.6% African and 75.1% European respectively, while the racial composition among self-identified Hispanics was 29.2% European, 26.0% African, and 44.8% Native American. We also investigated the utility of AIMs by showing the improved fitness of models in paraoxanase-1 genotype-phenotype associations after incorporating AIMs; however, the improvement was moderate at best. In summary, a minimal set of 35 AIMs is sufficient to detect population stratification and estimate the proportion of individual genetic admixture; however, the utility of these markers remains questionable.     

Characterizing Race/Ethnicity and Genetic Ancestry for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort

Using genome-wide genotypes, we characterized the genetic structure of 103,006 participants in the Kaiser Permanente Northern California multi-ethnic Genetic Epidemiology Research on Adult Health and Aging Cohort and analyzed the relationship to self-reported race/ethnicity. Participants endorsed any of 23 race/ethnicity/nationality categories, which were collapsed into seven major race/ethnicity groups. By self-report the cohort is 80.8% white and 19.2% minority; 93.8% endorsed a single race/ethnicity group, while 6.2% endorsed two or more. Principal component (PC) and admixture analyses were generally consistent with prior studies. Approximately 17% of subjects had genetic ancestry from more than one continent, and 12% were genetically admixed, considering only nonadjacent geographical origins. Self-reported whites were spread on a continuum along the first two PCs, indicating extensive mixing among European nationalities. Self-identified East Asian nationalities correlated with genetic clustering, consistent with extensive endogamy. Individuals of mixed East Asian–European genetic ancestry were easily identified; we also observed a modest amount of European genetic ancestry in individuals self-identified as Filipinos. Self-reported African Americans and Latinos showed extensive European and African genetic ancestry, and Native American genetic ancestry for the latter. Among 3741 genetically identified parent–child pairs, 93% were concordant for self-reported race/ethnicity; among 2018 genetically identified full-sib pairs, 96% were concordant; the lower rate for parent–child pairs was largely due to intermarriage. The parent–child pairs revealed a trend toward increasing exogamy over time; the presence in the cohort of individuals endorsing multiple race/ethnicity categories creates interesting challenges and future opportunities for genetic epidemiologic studies.     

White ethnicity in twenty-first-century America: findings from a new national survey

The 1980s and early 1990s witnessed a great deal of research on white ethnicity. Yet since this time, few systematic empirical studies of white ethnicity have emerged. This paper uses data from a recent nationally representative survey of Americans to (re)assess white ethnicity in the twenty-first century. Three primary areas are explored: (1) the pervasiveness and salience of ethnic claims among white Americans; (2) the social and demographic characteristics of self-identified white ethnics; and (3) the impact of white ethnic identity on political opinions and racial attitudes. We find that a smaller but significant number of white Americans claim ethnicity today and that distinguishing social characteristics of white ethnics still remain. Contrary to current prevailing theoretical formulations, however, these markers of distinction do not appear to be related to political or racial attitudes in any systematic way.     

Genetic Diversity and Association Studies in US Hispanic/Latino Populations: Applications in the Hispanic Community Health Study/Study of Latinos

US Hispanic/Latino individuals are diverse in genetic ancestry, culture, and environmental exposures. Here, we characterized and controlled for this diversity in genome-wide association studies (GWASs) for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We simultaneously estimated population-structure principal components (PCs) robust to familial relatedness and pairwise kinship coefficients (KCs) robust to population structure, admixture, and Hardy-Weinberg departures. The PCs revealed substantial genetic differentiation within and among six self-identified background groups (Cuban, Dominican, Puerto Rican, Mexican, and Central and South American). To control for variation among groups, we developed a multi-dimensional clustering method to define a “genetic-analysis group” variable that retains many properties of self-identified background while achieving substantially greater genetic homogeneity within groups and including participants with non-specific self-identification. In GWASs of 22 biomedical traits, we used a linear mixed model (LMM) including pairwise empirical KCs to account for familial relatedness, PCs for ancestry, and genetic-analysis groups for additional group-associated effects. Including the genetic-analysis group as a covariate accounted for significant trait variation in 8 of 22 traits, even after we fit 20 PCs. Additionally, genetic-analysis groups had significant heterogeneity of residual variance for 20 of 22 traits, and modeling this heteroscedasticity within the LMM reduced genomic inflation for 19 traits. Furthermore, fitting an LMM that utilized a genetic-analysis group rather than a self-identified background group achieved higher power to detect previously reported associations. We expect that the methods applied here will be useful in other studies with multiple ethnic groups, admixture, and relatedness.     

The use of race, ethnicity and ancestry in human genetic research

Post-Human Genome Project progress has enabled a new wave of population genetic research, and intensified controversy over the use of race/ethnicity in this work. At the same time, the development of methods for inferring genetic ancestry offers more empirical means of assigning group labels. Here, we provide a systematic analysis of the use of race/ethnicity and ancestry in current genetic research. We base our analysis on key published recommendations for the use and reporting of race/ethnicity which advise that researchers: explain why the terms/categories were used and how they were measured, carefully define them, and apply them consistently. We studied 170 population genetic research articles from high impact journals, published 2008-2009. A comparative perspective was obtained by aligning study metrics with similar research from articles published 2001-2004. Our analysis indicates a marked improvement in compliance with some of the recommendations/guidelines for the use of race/ethnicity over time, while showing that important shortfalls still remain: no article using 'race', 'ethnicity' or 'ancestry' defined or discussed the meaning of these concepts in context; a third of articles still do not provide a rationale for their use, with those using 'ancestry' being the least likely to do so. Further, no article discussed potential socio-ethical implications of the reported research. As such, there remains a clear imperative for highlighting the importance of consistent and comprehensive reporting on human populations to the genetics/genomics community globally, to generate explicit guidelines for the uses of ancestry and genetic ancestry, and importantly, to ensure that guidelines are followed.     

Integrating image data into biomedical text categorization

Categorization of biomedical articles is a central task for supporting various curation efforts. It can also form the basis for effective biomedical text mining. Automatic text classification in the biomedical domain is thus an active research area. Contests organized by the KDD Cup (2002) and the TREC Genomics track (since 2003) defined several annotation tasks that involved document classification, and provided training and test data sets. So far, these efforts focused on analyzing only the text content of documents. However, as was noted in the KDD'02 text mining contest-where figure-captions proved to be an invaluable feature for identifying documents of interest-images often provide curators with critical information. We examine the possibility of using information derived directly from image data, and of integrating it with text-based classification, for biomedical document categorization. We present a method for obtaining features from images and for using them-both alone and in combination with text-to perform the triage task introduced in the TREC Genomics track 2004. The task was to determine which documents are relevant to a given annotation task performed by the Mouse Genome Database curators. We show preliminary results, demonstrating that the method has a strong potential to enhance and complement traditional text-based categorization methods.     

Rethinking ethnicity: Identity,categorization and power

This article argues that ethnic identity is to be understood and theorized as an example of social identity in general and that externally‐located processes of social categorization are enormously influential in the production and reproduction of social identities. However, much research concerned with ethnicity, particularly social anthropological research, inspired, whether directly or indirectly, by Barth's Ethnic Groups and Boundaries, has concentrated upon internal process of group identification, at the expense of categorization. To acknowledge the necessary role of categorization in the social construction of ethnic identity is also to recognize (a) the importance of power and authority relations (domination) in that process, and (b) a distinction, which is developed in this article, between the nominal and the virtual dimensions of ethnic and other social identities. Finally, the article offers an outline of a substantive research agenda concerned with contexts of social categorization.     

Lessons from chimpanzee-based research on human disease: the implications of genetic differences

Assertions that the use of chimpanzees to investigate human diseases is valid scientifically are frequently based on a reported 98-99% genetic similarity between the species. Critical analyses of the relevance of chimpanzee studies to human biology, however, indicate that this genetic similarity does not result in sufficient physiological similarity for the chimpanzee to constitute a good model for research, and furthermore, that chimpanzee data do not translate well to progress in clinical practice for humans. Leading examples include the minimal citations of chimpanzee research that is relevant to human medicine, the highly different pathology of HIV/AIDS and hepatitis C virus infection in the two species, the lack of correlation in the efficacy of vaccines and treatments between chimpanzees and humans, and the fact that chimpanzees are not useful for research on human cancer. The major molecular differences underlying these inter-species phenotypic disparities have been revealed by comparative genomics and molecular biology - there are key differences in all aspects of gene expression and protein function, from chromosome and chromatin structure to post-translational modification. The collective effects of these differences are striking, extensive and widespread, and they show that the superficial similarity between human and chimpanzee genetic sequences is of little consequence for biomedical research. The extrapolation of biomedical data from the chimpanzee to the human is therefore highly unreliable, and the use of the chimpanzee must be considered of little value, particularly given the breadth and potential of alternative methods of enquiry that are currently available to science.     

Genetic databases and pharmacogenetics: introduction

Since the inception of the Human Genome Project, human genetics has frequently been conducted through big science projects, combining academic, state and industrial methods, interests and resources. The legitimacy of such projects has been linked to national prestige and images of the nation, the purity of scientific endeavour, the entrepreneurial spirit, medical progress and the public health. A key complication in these discourses is that large-scale genetic research has yet to show major results when considered in terms of the objectives used to legitimate investment and social support for these projects. The main area showing promise at present is the developing field of pharmacogenetics, which is now attracting major industry and government investment. Sociological, ethical and philosophical study of human genetic sample-based research and pharmacogenetics has developed in parallel with inquiry in the biological and biomedical sciences. This paper introduces a symposium on the ethical and social aspects of this field of biomedical research.     

Advantages and limitations of nonhuman primates as animal models in genetic research on complex diseases

Abstract: The genetic similarity between humans and nonhuman primates makes nonhuman primates uniquely suited as models for genetic research on complex physiological and behavioral phenotypes. By comparison with human subjects, nonhuman primates, like other animal models, have several advantages for these types of studies: 1) constant environmental conditions can be maintained over long periods of time, greatly increasing the power to detect genetic effects; 2) different environmental conditions can be imposed sequentially on individuals to characterize genotype-environment interactions; 3) complex pedigrees that are much more powerful for genetic analysis than typically available human pedigrees can be generated; 4) genetic hypotheses can be tested prospectively by selective matings; and 5) essential invasive and terminal experiments can be conducted. Limitations of genetic research with nonhuman primates include cost and availability. However, the ability to manipulate both genetic and environmental factors in captive primate populations indicates the promise of genetic research with these important animal models for illuminating complex disease processes. The utility of nonhuman primates for biomedical research on human health problems is illustrated by examples concerning the use of baboons in studies of osteoporosis, alcohol metabolism, and lipoproteins.     

Molecular mechanistic associations of human diseases

Background  

The study of relationships between human diseases provides new possibilities for biomedical research. Recent achievements on human genetic diseases have stimulated interest to derive methods to identify disease associations in order to gain further insight into the network of human diseases and to predict disease genes.     

Genome of the apes.

The Human Genome Project has generated both the information and technological infrastructure needed to accelerate genetic comparisons between humans and the African great apes (chimpanzees and gorillas). Sequence and chromosomal organization differences between these highly related genomes will provide clues to the genetic basis for recently evolved, specifically human traits such as bipedal gait and advanced cognitive function. Recent studies comparing the primate genomes have the potential to affect many aspects of human biomedical research and could benefit primate conservation efforts.     

Convergence of human pluripotent stem cell,organoid, and genome editing technologies

The last decade has seen many exciting technological breakthroughs that greatly expanded the toolboxes for biological and biomedical research, yet few have had more impact than induced pluripotent stem cells and modern-day genome editing. These technologies are providing unprecedented opportunities to improve physiological relevance of experimental models, further our understanding of developmental processes, and develop novel therapies. One of the research areas that benefit greatly from these technological advances is the three-dimensional human organoid culture systems that resemble human tissues morphologically and physiologically. Here we summarize the development of human pluripotent stem cells and their differentiation through organoid formation. We further discuss how genetic modifications, genome editing in particular, were applied to answer basic biological and biomedical questions using organoid cultures of both somatic and pluripotent stem cell origins. Finally, we discuss the potential challenges of applying human pluripotent stem cell and organoid technologies for safety and efficiency evaluation of emerging genome editing tools.