Individual Admixture Proportions Research Articles

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.

Comparison of Statistical Methods for Estimating Genetic Admixture in a Lung Cancer Study of African Americans and Latinos

A variety of methods are available for estimating genetic admixture proportions in populations; however, few investigators have conducted detailed comparisons using empirical data. The authors characterized admixture proportions among self-identified African Americans (n = 535) and Latinos (n = 412) living in the San Francisco Bay Area who participated in a lung cancer case-control study (1998-2003). Individual estimates of genetic ancestry based on 184 informative markers were obtained from a Bayesian approach and 2 maximum likelihood approaches and were compared using descriptive statistics, Pearson correlation coefficients, and Bland-Altman plots. Case-control differences in individual admixture proportions were assessed using 2-sample t tests and logistic regression analysis. Results indicated that Bayesian and frequentist approaches to estimating admixture provide similar estimates and inferences. No difference was observed in admixture proportions between African-American cases and controls, but Latino cases and controls significantly differed according to Amerindian and European genetic ancestry. Differences in admixture proportions between Latino cases and controls were not unexpected, since cases were more likely to have been born in the United States. Genetic admixture proportions provide a quantitative measure of ancestry differences among Latinos that can be used in analyses of genetic risk factors.

Genetic Contribution of Indigenous Yakutian Cattle to Two Hybrid Populations, Revealed by Microsatellite Variation

Indigenous Yakutian cattle's adaptation to the hardest subarctic conditions makes them a valuable genetic resource for cattle breeding in the Siberian area. Since early last century, crossbreeding between native Yakutian cattle and imported Simmental and Kholmogory breeds has been widely adopted. In this study, variations at 22 polymorphic microsatellite loci in 5 populations of Yakutian, Kholmogory, Simmental, Yakutian-Kholmogory and Yakutian-Simmental cattle were analysed to estimate the genetic contribution of Yakutian cattle to the two hybrid populations. Three statistical approaches were used: the weighted least-squares (WLS) method which considers all allele frequencies; a recently developed implementation of a Markov chain Monte Carlo (MCMC) method called likelihood-based estimation of admixture (LEA); and a model-based Bayesian admixture analysis method (STRUCTURE). At population-level admixture analyses, the estimate based on the LEA was consistent with that obtained by the WLS method. Both methods showed that the genetic contribution of the indigenous Yakutian cattle in Yakutian-Kholmogory was small (9.6% by the LEA and 14.2% by the WLS method). In the Yakutian-Simmental population, the genetic contribution of the indigenous Yakutian cattle was considerably higher (62.8% by the LEA and 56.9% by the WLS method). Individual-level admixture analyses using STRUCTURE proved to be more informative than the multidimensional scaling analysis (MDSA) based on individual-based genetic distances. Of the 9 Yakutian-Simmental animals studied, 8 showed admixed origin, whereas of the 14 studied Yakutian-Kholmogory animals only 2 showed Yakutian ancestry (>5%). The mean posterior distributions of individual admixture coefficient ( qˆ ) varied greatly among the samples in both hybrid populations. This study revealed a minor existing contribution of the Yakutian cattle in the Yakutian-Kholmogory hybrid population, but in the Yakutian-Simmental hybrid population, a major genetic contribution of the Yakutian cattle was seen. The results reflect the different crossbreeding patterns used in the development of the two hybrid populations. Additionally, molecular evidence for differences among individual admixture proportions was seen in both hybrid populations, resulting from the stochastic process in crossing over generations. (Asian-Aust. J. Anim. Sci. 2005. Vol 18, No. 5 : 613-619)

Admixture analysis of a rural population of the state of Guerrero, Mexico

We studied 156 individuals of Native American descent from the city of Tlapa in the state of Guerrero in western Mexico. Most individuals' ethnicity was either Nahua, Mixtec, or Tlapanec, but self-identified Mestizos and individuals of mixed ethnicities were also included in the sample. We typed 24 autosomal, one Y-chromosome, and four mitochondrial ancestry-informative markers (AIMs) to estimate group and individual admixture proportions, and determine whether the admixture process involved directional gene flow between parental groups. When genetically defined (GD) Mestizos were excluded from the analysis, Native American ancestry represented approximately 98% of the population's gene pool, while European and West African ancestry represented approximately 1% each. Maternally inherited markers also showed an exceptionally high Native American contribution (98.5%), as did the paternally inherited marker, DYS199 (90.7%). We did not detect genetic structure in this population using these AIMs, which appears consistent with the homogeneity of the sample in terms of admixture proportions. The addition of GD Mestizos to the sample did not produce a considerable change in admixture estimates, but it had a major effect on population structure. These results show that the population of Tlapa in Guerrero, Mexico, has experienced little admixture with Europeans and/or West Africans. They also show that the impact of a small number of admixed individuals on an otherwise homogeneous population might have profound implications on subsequent ancestry/phenotype analysis and mapping strategies. We suggest that heterogeneity is a major characteristic of Mexican populations and, as a consequence, should not be disregarded when designing epidemiological studies of Mexican and Mexican American populations.

Control of Confounding of Genetic Associations in Stratified Populations

To control for hidden population stratification in genetic-association studies, statistical methods that use marker genotype data to infer population structure have been proposed as a possible alternative to family-based designs. In principle, it is possible to infer population structure from associations between marker loci and from associations of markers with the trait, even when no information about the demographic background of the population is available. In a model in which the total population is formed by admixture between two or more subpopulations, confounding can be estimated and controlled. Current implementations of this approach have limitations, the most serious of which is that they do not allow for uncertainty in estimations of individual admixture proportions or for lack of identifiability of subpopulations in the model. We describe methods that overcome these limitations by a combination of Bayesian and classical approaches, and we demonstrate the methods by using data from three admixed populations--African American, African Caribbean, and Hispanic American--in which there is extreme confounding of trait-genotype associations because the trait under study (skin pigmentation) varies with admixture proportions. In these data sets, as many as one-third of marker loci show crude associations with the trait. Control for confounding by population stratification eliminates these associations, except at loci that are linked to candidate genes for the trait. With only 32 markers informative for ancestry, the efficiency of the analysis is 70%. These methods can deal with both confounding and selection bias in genetic-association studies, making family-based designs unnecessary.

Relationship of prevalence of non-insulin-dependent diabetes mellitus to Amerindian admixture in the Mexican Americans of San Antonio, Texas.

A genetic and epidemiological survey of non-insulin-dependent diabetes mellitus (NIDDM) was conducted among the Mexican Americans residing in three socioeconomically distinct areas of San Antonio, Texas: a low socioeconomic (SES) traditional area (barrio), a middle SES, ethnically balanced area (transitional), and a high SES, predominantly Anglo area (suburb). Seventeen polymorphic markers were used to relate the prevalences of NIDDM with the extent of Amerindian ancestry of 1,237 Mexican Americans of these three residential areas. While only the RH and haptoglobin loci showed evidence of association with NIDDM, an admixture analysis of the combined allele frequency data revealed a pattern of decreasing NIDDM prevalence with increasing socioeconomic status (as approximated by neighborhood of residence) and a parallel decrease in Amerindian ancestry. The rank-order correlation between NIDDM prevalence and Amerindian admixture is 0.943 (P less than .001) for the crude prevalence rate and 0.829 (P less than .02) for the age-adjusted rate. Nested gene diversity analysis revealed that the heterogeneity of allele frequencies is more pronounced when individuals were classified by their NIDDM disease status as compared to the classification by neighborhood. Estimation of Amerindian ancestry of each individual did not reveal any significant change in the shape of the distributions of individual admixture proportions in diabetics as compared to the controls. Nevertheless, the results suggest that genetic factors partially explain the differences in NIDDM prevalence observed between the Mexican American and Anglo populations in the southwestern United States.