Evidence of a major gene effect for angiotensinogen among Nigerians

Segregation Analysis Using the Unified Model

Segregation analysis is a basic tool in human genetics. It is a statistical method to determine if a trait, continuous or binary, has a transmission pattern in pedigrees that is consistent with Mendelian segregation. Major locus segregation is combined together with multifactorial/polygenic inheritance in the unified model. Segregation analysis as a procedure to identify the presence of segregation at a major Mendelian locus, with/without multifactorial inheritance, is introduced in this chapter. It is illustrated with the program SEGREG in the Statistical Analysis for Genetic Epidemiology (S.A.G.E.) package, which can use either regressive models or the finite polygenic mixed model to incorporate the multifactorial/polygenic component.

Segregation analysis using the unified model

Segregation analysis is a basic tool in human genetics. It is a statistical method to determine if a trait, continuous or binary, has a transmission pattern in pedigrees that is consistent with Mendelian segregation. Major locus segregation is combined together with multifactorial/polygenic inheritance in the unified model. Segregation analysis as a procedure to identify the presence of segregation at a major Mendelian locus, with/without multifactorial inheritance, is introduced in this chapter. It is illustrated with the program SEGREG in the Statistical Analysis for Genetic Epidemiology (S.A.G.E.) package, which can use either regressive models or the finite polygenic mixed model to incorporate the multifactorial/polygenic component.

Mixture models of serum iron measures in population screening for hemochromatosis and iron overload

Homozygosity for the C282Y mutation of the hemochromatosis gene on chromosome 6p (HFE) is a common genetic trait that increases susceptibility to iron overload. The authors describe and apply methodology developed for the analysis of phenotypic and genotypic data from 46,136 non-Hispanic Caucasians, a subset of the multi-ethnic cohort enrolled in the Hemochromatosis and Iron Overload Screening (HEIRS) Study. For analysis of the distribution of transferrin saturation (TS), mixtures of normal distributions were considered and the expectation-maximization (EM) algorithm was applied for parameter estimation. Maximized log-likelihoods were compared, and significance was assessed by resampling. Sensitivity, specificity, and predictive values from the modeled subpopulations were compared with the actual observed genotypes for C282Y and H63D mutations in the HFE gene. A strong association between HFE genotype and TS subpopulations was found in these data collected from different geographic regions, confirming the external validity of the statistical approach when applied to population-based data. It was concluded that mixture modeling of phenotypic data may provide a clinical guide for screening with gender-specific thresholds to identify potential samples for genetic testing.

Angiotensin I-converting enzyme polymorphisms, ACE level and blood pressure among Nigerians, Jamaicans and African-Americans

The genes in the renin-angiotensin system are important physiologic candidates in studies of the genetic susceptibility to hypertension. Limited information has been available in most studies on the extent of variation in the candidate loci or the modifying effects of different environmental settings. We consequently genotyped 13 polymorphisms at the angiotensin I-converting enzyme (ACE) locus at an average distance of 2 kb in 2776 family members from Nigeria, Jamaica and an African-American community in the US. Allele and haplotype frequencies were similar in the three populations, with modest evidence of European admixture in the US. Two markers were consistently associated with ACE level in the three samples and the proportion of variance accounted for by ACE8 was similar in the three groups. No evidence of consistent association of single markers was noted with blood pressure across the three population samples, however. Likewise, in a haplotype-based analysis, despite significant associations within each population, the findings were not replicated consistently across all three samples. We did observe, however, that the overtransmitted haplotypes among hypertensives were drawn from a single clade, suggesting that susceptibility may cluster in patterns not captured directly by our markers.

Mixture distribution analysis of phenotypic markers reflecting HFE gene mutations

The goal of this study was to determine whether statistical modeling of population data for a phenotypic marker could reflect a major locus gene defect. Identifying mutations in the HFE gene makes it possible to assess the association between transferrin saturation (TS) subpopulations and HFE mutations. Data were analyzed from 27 895 white patients who attended a health appraisal clinic and who had TS and common mutations of HFE determined. Mixture distribution modeling of TS was performed, and the proportion of HFE mutations in TS subpopulations was assessed on a probability basis. Three subpopulations of TS were identified, consistent with Hardy-Weinberg conditions for major locus effects. For men, 72% of the subpopulation with the highest mean TS had HFE gene mutations; they were primarily homozygotes or compound heterozygotes. Seventy-three percent of the subpopulation with moderate mean TS also had HFE gene mutations; they were predominantly simple heterozygotes. Sixty-seven percent of the subpopulation with the lowest mean TS were wild-type homozygotes. Similar results were observed for women. These results suggest that statistical modeling of population clinical laboratory test data can reveal the influence of a major locus gene defect and perhaps can be applied to other aspects of body metabolism than iron.

Linkage and association analysis of angiotensin I-converting enzyme (ACE)-gene polymorphisms with ACE concentration and blood pressure

Considerable effort has been expended to determine whether the gene for angiotensin I-converting enzyme (ACE) confers susceptibility to cardiovascular disease. In this study, we genotyped 13 polymorphisms in the ACE gene in 1,343 Nigerians from 332 families. To localize the genetic effect, we first performed linkage and association analysis of all the markers with ACE concentration. In multipoint variance-component analysis, this region was strongly linked to ACE concentration (maximum LOD score 7.5). Likewise, most of the polymorphisms in the ACE gene were significantly associated with ACE (P<.0013). The two most highly associated polymorphisms, ACE4 and ACE8, accounted for 6% and 19% of the variance in ACE, respectively. A two-locus additive model with an additive x additive interaction of these polymorphisms explained most of the ACE variation associated with this region. We next analyzed the relationship between these two polymorphisms (ACE4 and ACE8) and blood pressure (BP). Although no evidence of linkage was detected, significant association was found for both systolic and diastolic BP when a two-locus additive model developed for ACE concentration was used. Further analyses demonstrated that an epistasis model provided the best fit to the BP variation. In conclusion, we found that the two polymorphisms explaining the greatest variation in ACE concentration are significantly associated with BP, through interaction, in this African population sample. Our study also demonstrates that greater statistical power can be anticipated with association analysis versus linkage, when markers in strong linkage disequilibrium with a trait locus have been identified. Furthermore, allelic interaction may play an important role in the dissection of complex traits such as BP.