S G Buxbaum | PubMed Health

PubMed2001

A quantitative-trait analysis of human plasma-dopamine beta-hydroxylase activity: evidence for a major functional polymorphism at the DBH locus.

Dopamine-beta-hydroxylase (D beta H) catalyzes the conversion of dopamine to norepinephrine and is released from sympathetic neurons into the circulation. Plasma-D beta H activity varies widely between individuals, and a subgroup of the population has very low activity levels. Mounting evidence suggests that the DBH structural gene is itself the major quantitative-trait locus (QTL) for plasma-D beta H activity, and a single unidentified polymorphism may account for a majority of the variation in activity levels. Through use of both sequencing-based mutational analysis of extreme phenotypes and genotype/phenotype correlations in samples from African American, European American (EA), and Japanese populations, we have identified a novel polymorphism (--1021C-->T), in the 5' flanking region of the DBH gene, that accounts for 35%--52% of the variation in plasma-D beta H activity in these populations. In EAs, homozygosity at the T allele predicted the very low D beta H-activity trait, and activity values in heterozygotes formed an intermediate distribution, indicating codominant inheritance. Our findings demonstrate that --1021C-->T is a major genetic marker for plasma-D beta H activity and provide new tools for investigation of the role of both D beta H and the DBH gene in human disease.

Amino Acid Substitution↗

PubMed2001

Predicting quantitative trait levels by modeling SNP interaction.

Predicting phenotype from genotype is difficult when the phenotype is affected by a gene with numerous weakly penetrant alleles that differ only in the pattern of their single nucleotide polymorphisms (SNPs). While it is probable that SNP interactions affect phenotype, to our knowledge no one has determined the most effective way of evaluating whether SNPs interact and of modeling the interaction. Therefore, to explore this issue, we investigate here three methods of modeling SNP interaction using data from Genetic Analysis Workshop 12. Since major gene 5 (MG5) has sequence information and explains 37% of the variation in quantitative trait 5 (Q5), we focus on using SNPs within MG5 to predict Q5 among individuals who married into the pedigree. As a preliminary screening step, we reduced the number of SNPs from 269 to 34 based on their association with Q5. In our first models we assumed that SNPs affected Q5 in a simple additive manner. These models explained 34% and 15% of the variation in Q5 in women and men, respectively. Our second model was a linear model, which used individual SNPs and simple interaction terms as predictors. These models explained 36% and 16% of the variation in Q5 levels for women and men, respectively. Our last model was a "hit"-based model which was motivated by the hypothesis that disequilibrium between SNPs may reflect the fact that SNPs affect phenotype by acting in concert with other SNPs within their "disequilibrium set." Thus, the number of hits within the disequilibrium sets were used as predictors. These models explained 35% and 19% of the variation in Q5 for women and men, respectively. Our results suggest that phenotype can be predicted from complex patterns of weakly penetrant SNPs using relatively simple models. We concluded that SNP interaction either was not included in the simulation model, or had only a weak impact on Q5 levels.

Female↗