Admixed populations such as African Americans and Hispanic Americans present both challenges and opportunities in genetic epidemiologic research. Because of variation in admixture levels among individuals, case-control association studies may be subject to stratification bias. On the other hand, admixed populations also present special opportunities both for examining the role of genetic and environmental factors for observed racial/ethnic differences, and for possibly mapping alleles that contribute to such differences. Here we examined the distribution and relationship of individual admixture (IA) estimates with BMI and three measures of blood pressure in two admixed populations in the NHLBI Family Blood Pressure Program (FBPP): African Americans and Mexican Americans. For the African Americans, we observed modest but significant differences in average African IA among four recruitment sites. We observed a slight excess of African IA among hypertensives compared to normotensives, and a positive (non-significant) regression of African IA on blood pressure in untreated participants. Within Mexican Americans, we found no difference in average IA between hypertensives and normotensives, but a positive (marginally significant) regression of African IA on diastolic blood pressure. We also observed a significant positive regression of Caucasian IA (and negative regression of Native American IA) on BMI. Our results are suggestive of genetic differences between Africans and non-Africans that influence blood pressure, but such effects are likely to be modest compared to environmental ones. Excess obesity among Native Americans compared to whites is not consistent with a simple genetic explanation.

OBJECTIVE:To determine if the relationship between abdominal visceral fat (AVF) and measures of adiposity are different between Black and White subjects and to develop valid field prediction models that accurately identify those individuals with AVF levels associated with high risk for chronic disease. DESIGN: Cross-sectional measurements obtained from 91 Black men, 137 Black women, 227 White men, and 237 White women subjects, ages 17-65 y, who were participants in the HERITAGE Family Study, both at baseline and following 20 weeks of endurance training. MEASURMENTS: AVF, abdominal subcutaneous fat (ASF), abdominal total fat (ATF), and sagittal diameter (SagD) were measured by computed tomography (CT). Body density was determined by hydrostatic weighing and was used to estimate relative body fat. Arm, waist (WC), and hip circumferences and skinfold thickness measures were taken, and BMI was calculated from weight (kg) and height (m 2 ). Since CT abdominal fat variables were skewed, a natural log transformation (Ln) was used to produce a normal distribution. The General Linear Model (GLM) procedure was used to test the relationship between AVF and two different groups of variablesFCT and anthropometric. RESULTS: The AVF of White men and women was significantly higher than that of Black men and women, independent of BMI, WHR, WC, and age, and was greater for men than for women. The CT model showed that the combination of SagD, Ln (ASF), age, and race accounted for 84 and 75% of the variance in AVF in men and women, respectively. The anthropometric model provided two valid generalized field AVF prediction equations. The Field-I equation, which included BMI, WHR, age and race, had an r 2 of 0.78 and 0.73 for men and women, respectively. The Field-II equation, which included BMI (women only), WC, age, and race, had an r 2 of 0.78 and 0.72 for men and women, respectively. The field model equations became less accurate as the estimated AVF increased. CONCLUSIONS: (1) At the same age and level of adiposity, Black men and women have less AVF than White men and women. These differences are greater in men than in women. (2) The field regression equations can be generalized to the diverse group of adults studied, both in an untrained and trained state. However, their accuracy decreases with increasing levels of AVF.

Background Several consortia have pursued genome-wide association studies for identifying novel genetic loci for blood pressure (BP), lipids, hypertension, etc. They demonstrated the power of collaborative research through meta-analysis of study-specific results. Methods and Results The Gene-Lifestyle Interactions Working Group was formed to facilitate the first large, concerted, multi-ancestry study to systematically evaluate gene-lifestyle interactions. In Stage 1, genome-wide interaction analysis is carried out in 53 cohorts with a total of 149,684 individuals from multiple ancestries. In Stage 2 involving an additional 71 cohorts with 460,791 individuals from multiple ancestries, focused analysis is carried out for a subset of the most promising variants from Stage 1. In all, the study involves up to 610,475 individuals. Current focus is on cardiovascular traits including blood pressure and lipids, and lifestyle factors including smoking, alcohol, education (as a surrogate for socio-economic status), physical activity, psychosocial variables, and sleep. The total sample sizes vary among projects due to missing data. Large scale gene-lifestyle or more generally gene-environment interaction (G×E) meta-analysis studies can be cumbersome and challenging. This paper describes the design and some of the approaches pursued in the interaction projects. Conclusions The Gene-Lifestyle Interactions Working Group provides an excellent framework for understanding the lifestyle context of genetic effects and to identify novel trait loci through analysis of interactions. An important and novel feature of our study is that the gene-lifestyle interaction (G×E) results may improve our knowledge about the underlying mechanisms for novel as well as already known trait loci.

Human genetic linkage maps are based on rates of recombination across the genome. These rates in humans vary by the sex of the parent from whom alleles are inherited, by chromosomal position, and by genomic features, such as GC content and repeat density. We have examined--for the first time, to our knowledge--racial/ethnic differences in genetic maps of humans. We constructed genetic maps based on 353 microsatellite markers in four racial/ethnic groups: whites, African Americans, Mexican Americans, and East Asians (Chinese and Japanese). These maps were generated using 9,291 subjects from 2,900 nuclear families who participated in the National Heart, Lung, and Blood Institute-funded Family Blood Pressure Program, the largest sample used for map construction to date. Although the maps for the different groups are generally similar, we did find regional and genomewide differences across ethnic groups, including a longer genomewide map for African Americans than for other populations. Some of this variation was explained by genotyping artifacts--namely, null alleles (i.e., alleles with null phenotypes) at a number of loci--and by ethnic differences in null-allele frequencies. In particular, null alleles appear to be the likely explanation for the excess map length in African Americans. We also found that nonrandom missing data biases map results. However, we found regions on chromosome 8p and telomeric segments with significant ethnic differences and a suggestive interval on chromosome 12q that were not due to genotype artifacts. The difference on chromosome 8p is likely due to a polymorphic inversion in the region. The results of our investigation have implications for inferences of possible genetic influences on human recombination as well as for future linkage studies, especially those involving populations of nonwhite ethnicity.

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