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Christopher S Carlson

Publications and source records attributed to Christopher S Carlson.

25 records · Page 2Linked to original sources

Mapping complex disease loci in whole-genome association studies.

Identification of the genetic polymorphisms that contribute to susceptibility for common diseases such as type 2 diabetes and schizophrenia will aid in the development of diagnostics and therapeutics. Previous studies have focused on the technique of genetic linkage, but new technologies and experimental resources make whole-genome association studies more feasible. Association studies of this type have good prospects for dissecting the genetics of common disease, but they currently face a number of challenges, including problems with multiple testing and study design, definition of intermediate phenotypes and interaction between polymorphisms.

Disease↗

The effects of scale: variation in the APOA1/C3/A4/A5 gene cluster.

While there is considerable appeal to the idea of selecting a few SNPs to represent all, or much, of the DNA sequence variability in a local chromosomal region, it is also important to quantify what detail is lost in adopting such an approach. To address this issue, we compared high- and low-resolution depictions of sequence diversity for the same genomic region, the APOA1/C3/A4/A5 gene cluster on chromosome 11. First, extensive re-sequencing identified all nucleotide and sequence haplotype variation of the linked apolipoprotein genes in 72 individuals from three populations: African-Americans from Jackson, Miss., Europeans from North Karelia, Finland, and European-Americans from Rochester, Minn. We identified 124 SNPs in 17.7 kb and significant differences in variation among genes. APOC3 gene diversity was particularly distinctive at high resolution, showing large allele frequency differences ( F(ST) values >0.250) between Jackson and the other two samples, and divergent population-specific haplotype lineages. Next, we selected haplotype-tagging SNPs (htSNPs) for each gene, at a density of approximately one SNP per kb, using an algorithm suggested by Stram et al. (2003). The 17 htSNPs identified were then used to reconstruct low-resolution haplotypes, from which inferences about the structure of variation were also drawn. This comparison showed that while the htSNPs successfully tagged common haplotype variation, they also left much underlying sequence diversity undetected and failed, in some cases, to co-classify groups of closely related haplotypes. The implications of these findings for other haplotype-based descriptions of human variation are discussed.

Apolipoprotein C-III↗

Haplotype diversity across 100 candidate genes for inflammation, lipid metabolism, and blood pressure regulation in two populations.

Recent studies have suggested that a significant fraction of the human genome is contained in blocks of strong linkage disequilibrium, ranging from ~5 to >100 kb in length, and that within these blocks a few common haplotypes may account for >90% of the observed haplotypes. Furthermore, previous studies have suggested that common haplotypes in candidate genes are generally shared across populations and represent the majority of chromosomes in each population. The conclusions drawn from these preliminary studies, however, are based on an incomplete knowledge of the variation in the regions examined. To bridge this gap in knowledge, we have completely resequenced 100 candidate genes in a population of African descent and one of European descent. Although these genes have been well studied because of their medical importance, we demonstrate that a large amount of sequence variation has not yet been described. We also report that the average number of inferred haplotypes per gene, when complete data is used, is higher than in previous reports and that the number and proportion of all haplotypes represented by common haplotypes per gene is variable. Furthermore, we demonstrate that haplotypes shared between the two populations constitute only a fraction of the total number of haplotypes observed and that these shared haplotypes represent fewer of the African-descent chromosomes than was expected from previous studies. Finally, we show that restricting variation discovery to coding regions does not adequately describe all common haplotypes or the true haplotype block structure observed when all common variation is used to infer haplotypes. These data, derived from complete knowledge of genetic variation in these genes, suggest that the haplotype architecture of candidate genes across the human genome is more complex than previously suggested, with important implications for candidate gene and genomewide association studies.

Africa↗

Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium.

Common genetic polymorphisms may explain a portion of the heritable risk for common diseases. Within candidate genes, the number of common polymorphisms is finite, but direct assay of all existing common polymorphism is inefficient, because genotypes at many of these sites are strongly correlated. Thus, it is not necessary to assay all common variants if the patterns of allelic association between common variants can be described. We have developed an algorithm to select the maximally informative set of common single-nucleotide polymorphisms (tagSNPs) to assay in candidate-gene association studies, such that all known common polymorphisms either are directly assayed or exceed a threshold level of association with a tagSNP. The algorithm is based on the r(2) linkage disequilibrium (LD) statistic, because r(2) is directly related to statistical power to detect disease associations with unassayed sites. We show that, at a relatively stringent r(2) threshold (r2>0.8), the LD-selected tagSNPs resolve >80% of all haplotypes across a set of 100 candidate genes, regardless of recombination, and tag specific haplotypes and clades of related haplotypes in nonrecombinant regions. Thus, if the patterns of common variation are described for a candidate gene, analysis of the tagSNP set can comprehensively interrogate for main effects from common functional variation. We demonstrate that, although common variation tends to be shared between populations, tagSNPs should be selected separately for populations with different ancestries.

Algorithms↗

Additional SNPs and linkage-disequilibrium analyses are necessary for whole-genome association studies in humans.

More than 5 million single-nucleotide polymorphisms (SNPs) with minor-allele frequency greater than 10% are expected to exist in the human genome. Some of these SNPs may be associated with risk of developing common diseases. To assess the power of currently available SNPs to detect such associations, we resequenced 50 genes in two ethnic samples and measured patterns of linkage disequilibrium between the subset of SNPs reported in dbSNP and the complete set of common SNPs. Our results suggest that using all 2.7 million SNPs currently in the database would detect nearly 80% of all common SNPs in European populations but only 50% of those common in the African American population and that efficient selection of a minimal subset of SNPs for use in association studies requires measurement of allele frequency and linkage disequilibrium relationships for all SNPs in dbSNP.

Alleles↗

Cyclooxygenase 1 (COX1) polymorphisms in African-American and Caucasian populations.

Cyclooxygenases (COXs) are the primary targets of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs), and thus enzymes of major interest to pharmacology, pharmacogenetics, and epidemiology. Genetic variants that affect enzyme function, or the interaction with NSAIDs, could alter drug response. We have screened the human COX1 gene coding regions of 48 African-American and 47 Caucasian individuals using DNA sequencing. We identified 13 coding-region variants, of which seven were amino-acid substitutions, and further five intronic polymorphisms within 60bp of an exon. All nonsynonymous variants were confirmed in an independent Caucasian population (n=94 unrelated individuals). Most of the discovered polymorphisms were rare, although some variants resulting in amino-acid changes occurred at appreciable frequency in at least one population (> or =4%: R8W, P17L, L237M). We used two sequence-homology-based software programs to predict the potential impact of these polymorphisms on COX1 function. The L237M substitution was predicted as most likely to alter protein function, whereas the glycine at position 230 may be specific to COX1 function. More detailed phenotypic characterizations of these COX1 polymorphisms remain to be undertaken.

Amino Acid Substitution↗

Sequence variation in the human T-cell receptor loci.

Identifying common sequence variations known as single nucleotide polymorphisms (SNPs) in human populations is one of the current objectives of the human genome project. Nearly 3 million SNPs have been identified. Analysis of the relative allele frequency of these markers in human populations and the genetic associations between these markers, known as linkage disequilibrium, is now underway to generate a high-density genetic map. Because of the central role T cells play in immune reactivity, the T-cell receptor (TCR) loci have long been considered important candidates for common disease susceptibility within the immune system (e.g., asthma, atopy and autoimmunity). Over the past two decades, hundreds of SNPs in the TCR loci have been identified. Most studies have focused on defining SNPs in the variable gene segments which are involved in antigenic recognition. On average, the coding sequence of each TCR variable gene segment contains two SNPs, with many more found in the 5', 3' and intronic sequences of these segments. Therefore, a potentially large repertoire of functional variants exists in these loci. Association between SNPs (linkage disequilibrium) extends approximately 30 kb in the TCR loci, although a few larger regions of disequilibrium have been identified. Therefore, the SNPs found in one variable gene segment may or may not be associated with SNPs in other surrounding variable gene segments. This suggests that meaningful association studies in the TCR loci will require the analysis and typing of large marker sets to fully evaluate the role of TCR loci in common disease susceptibility in human populations.

Chromosome Mapping↗