Dataset Information

Gene-centric genomewide association study via entropy.

ABSTRACT: Genes are the functional units in most organisms. Compared to genetic variants located outside genes, genic variants are more likely to affect disease risk. The development of the human HapMap project provides an unprecedented opportunity for genetic association studies at the genomewide level for elucidating disease etiology. Currently, most association studies at the single-nucleotide polymorphism (SNP) or the haplotype level rely on the linkage information between SNP markers and disease variants, with which association findings are difficult to replicate. Moreover, variants in genes might not be sufficiently covered by currently available methods. In this article, we present a gene-centric approach via entropy statistics for a genomewide association study to identify disease genes. The new entropy-based approach considers genic variants within one gene simultaneously and is developed on the basis of a joint genotype distribution among genetic variants for an association test. A grouping algorithm based on a penalized entropy measure is proposed to reduce the dimension of the test statistic. Type I error rates and power of the entropy test are evaluated through extensive simulation studies. The results indicate that the entropy test has stable power under different disease models with a reasonable sample size. Compared to single SNP-based analysis, the gene-centric approach has greater power, especially when there is more than one disease variant in a gene. As the genomewide genic SNPs become available, our entropy-based gene-centric approach would provide a robust and computationally efficient way for gene-based genomewide association study.

SUBMITTER: Cui Y

PROVIDER: S-EPMC2390640 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

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Gene-centric genomewide association study via entropy.

Cui Yuehua Y Kang Guolian G Sun Kelian K Qian Minping M Romero Roberto R Fu Wenjiang W

Genetics 20080505 1

Genes are the functional units in most organisms. Compared to genetic variants located outside genes, genic variants are more likely to affect disease risk. The development of the human HapMap project provides an unprecedented opportunity for genetic association studies at the genomewide level for elucidating disease etiology. Currently, most association studies at the single-nucleotide polymorphism (SNP) or the haplotype level rely on the linkage information between SNP markers and disease vari ...[more]

PMID: 18458106

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Project description:We investigated genetic determinants of single-dose simvastatin pharmacokinetics in a prospective study of 170 subjects and a retrospective cohort of 59 healthy volunteers. In a microarray-based genomewide association study with the prospective data, the SLCO1B1 c.521T>C (p.Val174Ala, rs4149056) single nucleotide variation showed the strongest, genomewide significant association with the area under the plasma simvastatin acid concentration-time curve (AUC; P = 6.0 × 10-10 ). Meta-analysis with the retrospective cohort strengthened the association (P = 1.6 × 10-17 ). In a stepwise linear regression candidate gene analysis among all 229 participants, SLCO1B1 c.521T>C (P = 1.9 × 10-13 ) and CYP3A4 c.664T>C (p.Ser222Pro, rs55785340, CYP3A4*2, P = 0.023) were associated with increased simvastatin acid AUC. Moreover, the SLCO1B1 c.463C>A (p.Pro155Thr, rs11045819, P = 7.2 × 10-6 ) and c.1929A>C (p.Leu643Phe, rs34671512, P = 5.3 × 10-4 ) variants associated with decreased simvastatin acid AUC. Based on these results and the literature, we classified the volunteers into genotype-predicted OATP1B1 and CYP3A4 phenotype groups. Compared with the normal OATP1B1 function group, simvastatin acid AUC was 273% larger in the poor (90% confidence interval (CI), 137%, 488%; P = 3.1 × 10-6 ), 40% larger in the decreased (90% CI, 8%, 83%; P = 0.036), and 67% smaller in the highly increased function group (90% CI, 46%, 80%; P = 2.4 × 10-4 ). Intermediate CYP3A4 metabolizers (i.e., heterozygous carriers of either CYP3A4*2 or CYP3A4*22 (rs35599367)), had 87% (90% CI, 39%, 152%, P = 6.4 × 10-4 ) larger simvastatin acid AUC than normal metabolizers. These data suggest that in addition to no function SLCO1B1 variants, increased function SLCO1B1 variants and reduced function CYP3A4 variants may affect the pharmacokinetics, efficacy, and safety of simvastatin. Care is warranted if simvastatin is prescribed to patients carrying decreased function SLCO1B1 or CYP3A4 alleles.

Project description:BACKGROUND: The high-throughput genotyping chips have contributed greatly to genome-wide association (GWA) studies to identify novel disease susceptibility single nucleotide polymorphisms (SNPs). The high-density chips are designed using two different SNP selection approaches, the direct gene-centric approach, and the indirect quasi-random SNPs or linkage disequilibrium (LD)-based tagSNPs approaches. Although all these approaches can provide high genome coverage and ascertain variants in genes, it is not clear to which extent these approaches could capture the common genic variants. It is also important to characterize and compare the differences between these approaches. METHODOLOGY/PRINCIPAL FINDINGS: In our study, by using both the Phase II HapMap data and the disease variants extracted from OMIM, a gene-centric evaluation was first performed to evaluate the ability of the approaches in capturing the disease variants in Caucasian population. Then the distribution patterns of SNPs were also characterized in genic regions, evolutionarily conserved introns and nongenic regions, ontologies and pathways. The results show that, no mater which SNP selection approach is used, the current high-density SNP chips provide very high coverage in genic regions and can capture most of known common disease variants under HapMap frame. The results also show that the differences between the direct and the indirect approaches are relatively small. Both have similar SNP distribution patterns in these gene-centric characteristics. CONCLUSIONS/SIGNIFICANCE: This study suggests that the indirect approaches not only have the advantage of high coverage but also are useful for studies focusing on various functional SNPs either in genes or in the conserved regions that the direct approach supports. The study and the annotation of characteristics will be helpful for designing and analyzing GWA studies that aim to identify genetic risk factors involved in common diseases, especially variants in genes and conserved regions.

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Gene-centric genomewide association study via entropy.

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Gene-centric genomewide association study via entropy.

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