Genetic testing for long-QT syndrome: distinguishing pathogenic mutations from benign variants.

BACKGROUND: Genetic testing for long-QT syndrome (LQTS) has diagnostic, prognostic, and therapeutic implications. Hundreds of causative mutations in 12 known LQTS-susceptibility genes have been identified. Genetic testing that includes the 3 most commonly mutated genes is available clinically. Distinguishing pathogenic mutations from innocuous rare variants is critical to the interpretation of test results. We sought to quantify the value of mutation type and gene/protein region in determining the probability of pathogenicity for mutations. METHODS AND RESULTS: Type, frequency, and location of mutations across KCNQ1 (LQT1), KCNH2 (LQT2), and SCN5A (LQT3) were compared between 388 unrelated "definite" (clinical diagnostic score >or=4 and/or QTc >or=480 ms) cases of LQTS and >1300 healthy controls for each gene. From these data, estimated predictive values (percent of mutations found in definite cases that would cause LQTS) were determined according to mutation type and location. Mutations were 10 times more common in cases than controls (0.58 per case versus 0.06 per control). Missense mutations were the most common, accounting for 78%, 67%, and 89% of mutations in KCNQ1, KCNH2, and SCN5A in cases and >95% in controls. Nonmissense mutations have an estimated predictive value >99% regardless of location. In contrast, location appears to be critical for characterizing missense mutations. Relative frequency of missense mutations between cases and controls ranged from approximately 1:1 in the SCN5A interdomain linker to infinity in the pore, transmembrane, and linker in KCNH2. These correspond to estimated predictive values ranging from 0% in the interdomain linker of SCN5A to 100% in the transmembrane/linker/pore regions of KCNH2. The estimated predictive value is also high in the linker, pore, transmembrane, and C terminus of KCNQ1 and the transmembrane/linker of SCN5A. CONCLUSIONS: Distinguishing pathogenic mutations from rare variants is of critical importance in the interpretation of genetic testing in LQTS. Mutation type, mutation location, and ethnic-specific BACKGROUND: should be viewed as variants of uncertain significance and prompt further investigation to clarify the likelihood of disease causation. However, mutations in regions such as the transmembrane, linker, and pore of KCNQ1 and KCNH2 may be defined confidently as high-probability LQTS-causing mutations. These findings will have implications for other genetic disorders involving mutational analysis.

The structure of common genetic variation in United States populations.

The common-variant/common-disease model predicts that most risk alleles underlying complex health-related traits are common and, therefore, old and found in multiple populations, rather than being rare or population specific. Accordingly, there is widespread interest in assessing the population structure of common alleles. However, such assessments have been confounded by analysis of data sets with bias toward ascertainment of common alleles (e.g., HapMap and Perlegen) or in which a relatively small number of genes and/or populations were sampled. The aim of this study was to examine the structure of common variation ascertained in major U.S. populations, by resequencing the exons and flanking regions of 3,873 genes in 154 chromosomes from European, Latino/Hispanic, Asian, and African Americans generated by the Genaissance Resequencing Project. The frequency distributions of private and common single-nucleotide polymorphisms (SNPs) were measured, and the extent to which common SNPs were shared across populations was analyzed using several different estimators of population structure. Most SNPs that were common in one population were present in multiple populations, but SNPs common in one population were frequently not common in other populations. Moreover, SNPs that were common in two or more populations often differed significantly in frequency from one population to another, particularly in comparisons of African Americans versus other U.S. populations. These findings indicate that, even if the bulk of alleles underlying complex health-related traits are common SNPs, geographic ancestry might well be an important predictor of whether a person carries a risk allele.

Genetic variability and evolution of two pharmacologically important classes of genes.

We have studied the human genetic variability of single nucleotide polymorphisms (SNPs) and haplotypes in two pharmaceutically important classes of genes that might be expected to experience different evolutionary pressures: antigen presentation and processing (APP) and nuclear hormone receptor (NHR) genes. We compared the variation pattern in these two classes of genes with 5119 reference (REF) genes. We assessed this variability by sequencing and discovering SNPs in 5'-upstream, 5'-untranslated region (5'UTR), exon, intron, 3'UTR and 3'-downstream regions of all these genes in 79 unrelated humans from diverse ethnic backgrounds, one chimpanzee (Pan troglodytes) and a gorilla (Gorilla gorilla). SNP density and nucleotide diversity were higher in the APP genes than the REF genes. Relative to the REF genes, APP SNP density was significantly higher in the coding and 3'UTR regions. Higher variation in the coding region of the APP genes was due specifically to having more non-synonymous changes, which suggests that natural selection may be acting to promote change or diversity in these proteins. In contrast, the NHR genes showed lower SNP density and diversity relative to REF genes. The NHR genes consistently showed lower nucleotide diversity in all the genomic regions except in the 3'downstream region. SNP frequency data on the non-synonymous SNPs also suggested that the coding region in the NHR genes is conserved to a higher degree than the coding region in the REF genes. Significantly lower SNP density was observed in the 5'-upstream and 5'UTR regions of the NHR genes, perhaps reflecting selective conservation of these regions. Heterozygosity in the APP genes was significantly higher than in the NHR genes in each of the three species tested. Moreover, between species there were more fixed differences in the APP genes than in the NHR genes. Substantial variability exists in these two classes of genes. It is important to consider this interindividual variability pattern while developing drugs that act on such targets.

DNA variability of human genes.

We have investigated the level of DNA-based variation (both SNPs and haplotypes) for several thousand human genes. In addition, we have characterized how this variation is distributed in a number of biologically and clinically important ways. First, we have determined how SNPs are distributed within human genes: where they occur relative to various functional regions; levels of variability of human SNPs; pattern of the molecular sequence of SNPs; and how these compare with the corresponding sequence of a chimpanzee. Second, we have determined how these aspects of SNP distribution vary among four human population samples. All genes were sequenced on DNA obtained from 82 unrelated individuals: 20 African-Americans, 20 East Asians, 21 European-Americans, 18 Hispanic-Latinos and three Native Americans. In particular, we looked at patterns of SNP and haplotype sharing among the four larger population samples. Third, we have determined the patterns of linkage disequilibrium among SNPs, which also determines the haplotype variability of each gene. These characteristics also vary substantially among populations. A deeper understanding of these aspects of human genetic variation will be of vital importance when trying to identify the genetic contribution to complex phenotypes such as aging.