Exclusion of angiotensinogen gene in molecular basis of human hypertension: Sibpair linkage and association analyses in Australian anglo-caucasians

Linkage with essential hypertension has been claimed for a microsatellite marker near the angiotensinogen gene (AGT; chromosome 1q42), as has association for the AGT variants M235T, G(-6)A and A(-20)C. To more rigorously evaluate AGT as a candidate gene for hypertension we performed sibpair analysis with multiple microsatellite markers surrounding this locus and using more sophisticated analysis programs. We also performed an association study of the AGT variants in unrelated subjects with a strong family history (two affected parents). For the linkage study, single and multiplex polymerase chain reaction (PCRs) and automated genescan analysis were conducted on DNA from 175 Australian Anglo-Celtic Caucasian hypertensives for the following markers: D1S2880-(2.1 cM)-D1S213-(2.8 cM)-D1S251-(6.5 cM)-AGT-(2.0 cM) -D1S235. Statistical evaluation of genotype data by nonparametric methods resulted in the following scores: Single-point analysis - SPLINK, P > 0.18; APM method, P > 0.25; ASPEX, MLOD < 0.28; SIB-PAIR, P > 0. 24; Multipoint analysis - MAPMAKER/SIBS, MLOD < 0.24; GENEHUNTER, P > 0.35. Exclusion scores of Lod -4.1 to -5.1 were obtained for these markers using MAPMAKER/SIBS for a lambda(s) of 1.6. The association study of G(-6)A, A(-20)C and M235T variants in 111 hypertensives with strong family history and 190 normotensives with no family history showed significant linkage disequilibrium between particular haplotypes, but we could find no association with hypertension. The present study therefore excludes AGT in the etiology of hypertension, at least in the population of Australian Anglo-Celtic Caucasians studied.

Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering

The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. The family nests as particular cases several important asymmetric distributions like the Generalized Hyperbolic distribution. The Generalized Hyperbolic distribution in turn nests many other well known distributions such as the Normal Inverse Gaussian. In a multivariate setting, an extension of the standard location and scale mixture concept is proposed into a so called multiple scaled framework which has the advantage of allowing different tail and skewness behaviours in each dimension with arbitrary correlation between dimensions. Estimation of the parameters is provided via an EM algorithm and extended to cover the case of mixtures of such multiple scaled distributions for application to clustering. Assessments on simulated and real data confirm the gain in degrees of freedom and flexibility in modelling data of varying tail behaviour and directional shape.