RESUMEN
A general question for linkage disequilibrium-based association studies is how power to detect an association is compromised when tag SNPs are chosen from data in one population sample and then deployed in another sample. Specifically, it is important to know how well tags picked from the HapMap DNA samples capture the variation in other samples. To address this, we collected dense data uniformly across the four HapMap population samples and eleven other population samples. We picked tag SNPs using genotype data we collected in the HapMap samples and then evaluated the effective coverage of these tags in comparison to the entire set of common variants observed in the other samples. We simulated case-control association studies in the non-HapMap samples under a disease model of modest risk, and we observed little loss in power. These results demonstrate that the HapMap DNA samples can be used to select tags for genome-wide association studies in many samples around the world.
Asunto(s)
Mapeo Cromosómico/métodos , Genética de Población/métodos , Polimorfismo de Nucleótido Simple , Lugares Marcados de Secuencia , Neoplasias de la Mama/etnología , Neoplasias de la Mama/genética , Estudios de Casos y Controles , Estudios de Cohortes , Simulación por Computador , Femenino , Variación Genética , Genoma Humano , Proyecto Genoma Humano , Humanos , Desequilibrio de Ligamiento , Masculino , Neoplasias de la Próstata/etnología , Neoplasias de la Próstata/genéticaRESUMEN
BACKGROUND: The PROGINS allele of the progesterone receptor (PGR) gene has been associated with an increased risk of ovarian cancer and a decreased risk of breast cancer. We set out to refine the association between common variation at the PGR gene locus and these two diseases. METHODS: We characterized the haplotype structure of the PGR gene by genotyping 54 single-nucleotide polymorphisms (SNPs) in 349 women. We then selected a subset of 17 haplotype-tagging SNPs that captured variation across the locus and typed them in 267 ovarian cancer case patients and 397 control subjects from two case-control studies and in 1715 breast cancer case patients and 2505 control subjects from a cohort study. RESULTS: The PGR locus was characterized by four blocks of strong linkage disequilibrium. Two SNPs in block 4 were associated with an increased risk of ovarian cancer among homozygous carriers as compared with noncarriers: rs1042838 (PROGINS allele; odds ratio [OR] = 3.23, 95% confidence interval [CI] = 1.19 to 8.75, P = .022) and rs608995 (minor allele; OR = 3.10, 95% CI = 1.63 to 5.89, P<.001). The PROGINS allele was observed on a subset of chromosomes carrying the minor allele at rs608995, and its association with ovarian cancer was fully explained by its association with rs608995. In addition, rs608995 fell on two common haplotypes (4-D and 4-E), whose association with ovarian cancer was the same as that of rs608995. These same two haplotypes were associated with a non-statistically significantly reduced risk of breast cancer. CONCLUSIONS: Variation in PGR was associated with ovarian cancer risk, although the strongest result was not with the PROGINS allele. Instead, any causal allele(s) are likely in or downstream of block 4 and carried on haplotypes 4-D and 4-E. There was some evidence that the same variation was associated with a reduced risk of breast cancer, but the association was not statistically significant.