Finding the missing heritability of complex diseases

Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

An admixture scan in 1,484 African American women with breast cancer

African American women with breast cancer present more commonly with aggressive tumors that do not express the estrogen receptor (ER) and progesterone receptor (PR) compared with European American women. Whether this disparity is the result of inherited factors has not been established. We did an admixture-based genome-wide scan to search for risk alleles for breast cancer that are highly differentiated in frequency between African American and European American women, and may contribute to specific breast cancer phenotypes, such as ER-negative (ER-) disease. African American women with invasive breast cancer (n = 1,484) were pooled from six population-based studies and typed at approximately 1,500 ancestry-informative markers. We investigated global genetic ancestry and did a whole genome admixture scan searching for breast cancer-predisposing loci in association with disease phenotypes. We found a significant difference in ancestry between ER+PR+ and ER-PR- women, with higher European ancestry among ER+PR+ individuals, after controlling for possible confounders (odds ratios for a 0 to 1 change in European ancestry proportion, 2.84; 95% confidence interval, 1.13-7.14; P = 0.026). Women with localized tumors had higher European ancestry than women with non-localized tumors (odds ratios, 2.65; 95% confidence interval, 1.11-6.35; P = 0.029). No genome-wide statistically significant associations were observed between European or African ancestry at any specific locus and breast cancer, or in analyses stratified by ER/PR status, stage, or grade. In summary, in African American women, genetic ancestry is associated with ER/PR status and disease stage. However, we found little evidence that genetic ancestry at any one region contributes significantly to breast cancer risk or hormone receptor status.

A genome-wide association study identifies a new ovarian cancer susceptibility locus on 9p22.2

Epithelial ovarian cancer has a major heritable component, but the known susceptibility genes explain less than half the excess familial risk. We performed a genome-wide association study (GWAS) to identify common ovarian cancer susceptibility alleles. We evaluated 507,094 SNPs genotyped in 1,817 cases and 2,353 controls from the UK and approximately 2 million imputed SNPs. We genotyped the 22,790 top ranked SNPs in 4,274 cases and 4,809 controls of European ancestry from Europe, USA and Australia. We identified 12 SNPs at 9p22 associated with disease risk (P < 10(-8)). The most significant SNP (rs3814113; P = 2.5 x 10(-17)) was genotyped in a further 2,670 ovarian cancer cases and 4,668 controls, confirming its association (combined data odds ratio (OR) = 0.82, 95% confidence interval (CI) 0.79-0.86, P(trend) = 5.1 x 10(-19)). The association differs by histological subtype, being strongest for serous ovarian cancers (OR 0.77, 95% CI 0.73-0.81, P(trend) = 4.1 x 10(-21)).

Association between invasive ovarian cancer susceptibility and 11 best candidate SNPs from breast cancer genome-wide association study

Because both ovarian and breast cancer are hormone-related and are known to have some predisposition genes in common, we evaluated 11 of the most significant hits (six with confirmed associations with breast cancer) from the breast cancer genome-wide association study for association with invasive ovarian cancer. Eleven SNPs were initially genotyped in 2927 invasive ovarian cancer cases and 4143 controls from six ovarian cancer case-control studies. Genotype frequencies in cases and controls were compared using a likelihood ratio test in a logistic regression model stratified by study. Initially, three SNPs (rs2107425 in MRPL23, rs7313833 in PTHLH, rs3803662 in TNRC9) were weakly associated with ovarian cancer risk and one SNP (rs4954956 in NXPH2) was associated with serous ovarian cancer in non-Hispanic white subjects (P-trend < 0.1). These four SNPs were then genotyped in an additional 4060 cases and 6308 controls from eight independent studies. Only rs4954956 was significantly associated with ovarian cancer risk both in the replication study and in combined analyses. This association was stronger for the serous histological subtype [per minor allele odds ratio (OR) 1.07 95% CI 1.01-1.13, P-trend = 0.02 for all types of ovarian cancer and OR 1.14 95% CI 1.07-1.22, P-trend = 0.00017 for serous ovarian cancer]. In conclusion, we found that rs4954956 was associated with increased ovarian cancer risk, particularly for serous ovarian cancer. However, none of the six confirmed breast cancer susceptibility variants we tested was associated with ovarian cancer risk. Further work will be needed to identify the causal variant associated with rs4954956 or elucidate its function.

Performance of prediction models for BRCA mutation carriage in three racial/ethnic groups: findings from the Northern California Breast Cancer Family Registry

PURPOSE

Patients with early-onset breast and/or ovarian cancer frequently wish to know if they inherited a mutation in one of the cancer susceptibility genes, BRCA1 or BRCA2. Accurate carrier prediction models are needed to target costly testing. Two widely used models, BRCAPRO and BOADICEA, were developed using data from non-Hispanic Whites (NHW), but their accuracies have not been evaluated in other racial/ethnic populations.

METHODS

We evaluated the BRCAPRO and BOADICEA models in a population-based series of African American, Hispanic, and NHW breast cancer patients tested for BRCA1 and BRCA2 mutations. We assessed model calibration by evaluating observed versus predicted mutations and attribute diagrams, and model discrimination using areas under the receiver operating characteristic curves.

RESULTS

Both models were well-calibrated within each racial/ethnic group, with some exceptions. BOADICEA overpredicted mutations in African Americans and older NHWs, and BRCAPRO underpredicted in Hispanics. In all racial/ethnic groups, the models overpredicted in cases whose personal and family histories indicated >80% probability of carriage. The two models showed similar discrimination in each racial/ethnic group, discriminating least well in Hispanics. For example, BRCAPRO's areas under the receiver operating characteristic curves were 83% (95% confidence interval, 63-93%) for NHWs, compared with 74% (59-85%) for African Americans and 58% (45-70%) for Hispanics.

CONCLUSIONS

The poor performance of the model for Hispanics may be due to model misspecification in this racial/ethnic group. However, it may also reflect racial/ethnic differences in the distributions of personal and family histories among breast cancer cases in the Northern California population.

Tagging single-nucleotide polymorphisms in candidate oncogenes and susceptibility to ovarian cancer

Low-moderate risk alleles that are relatively common in the population may explain a significant proportion of the excess familial risk of ovarian cancer (OC) not attributed to highly penetrant genes. In this study, we evaluated the risks of OC associated with common germline variants in five oncogenes (BRAF, ERBB2, KRAS, NMI and PIK3CA) known to be involved in OC development. Thirty-four tagging SNPs in these genes were genotyped in approximately 1800 invasive OC cases and 3000 controls from population-based studies in Denmark, the United Kingdom and the United States. We found no evidence of disease association for SNPs in BRAF, KRAS, ERBB2 and PIK3CA when OC was considered as a single disease phenotype; but after stratification by histological subtype, we found borderline evidence of association for SNPs in KRAS and BRAF with mucinous OC and in ERBB2 and PIK3CA with endometrioid OC. For NMI, we identified a SNP (rs11683487) that was associated with a decreased risk of OC (unadjusted P(dominant)=0.004). We then genotyped rs11683487 in another 1097 cases and 1792 controls from an additional three case-control studies from the United States. The combined odds ratio was 0.89 (95% confidence interval (CI): 0.80-0.99) and remained statistically significant (P(dominant)=0.032). We also identified two haplotypes in ERBB2 associated with an increased OC risk (P(global)=0.034) and a haplotype in BRAF that had a protective effect (P(global)=0.005). In conclusion, these data provide borderline evidence of association for common allelic variation in the NMI with risk of epithelial OC.

No evidence of familial correlation in breast cancer metastasis

Animal experiments support the hypothesis that the metastatic potential of breast cancer is a heritable trait of the host. Our objective was to evaluate correlations in metastasis occurrence in large families with multiple cases of breast cancer. We evaluated correlation among pairs of relatives in the occurrence and timing of distant metastasis using retrospective cohort data from 743 female breast cancer patients in 242 families. We adjusted for correlation in their age at diagnosis, year of diagnosis, educational level, lymph node involvement, and estrogen receptor status. Distant metastasis occurred in 255 patients (34.3%) during mean followup of 11.7 years. None of the correlation coefficients for metastasis in blood relatives differed significantly from zero. The estimated correlation coefficient in first-degree relatives was -0.03 (95% confidence interval -0.11 to 0.06). These findings suggest that a family history of metastatic breast cancer does not contribute substantially to risk of metastasis for breast cancer patients.

Single nucleotide polymorphisms in the TP53 region and susceptibility to invasive epithelial ovarian cancer

The p53 protein is critical for multiple cellular functions including cell growth and DNA repair. We assessed whether polymorphisms in the region encoding TP53 were associated with risk of invasive ovarian cancer. The study population includes a total of 5,206 invasive ovarian cancer cases (2,829 of which were serous) and 8,790 controls from 13 case-control or nested case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Three of the studies performed independent discovery investigations involving genotyping of up to 23 single nucleotide polymorphisms (SNP) in the TP53 region. Significant findings from this discovery phase were followed up for replication in the other OCAC studies. Mixed effects logistic regression was used to generate posterior median per allele odds ratios (OR), 95% probability intervals (PI), and Bayes factors (BF) for genotype associations. Five SNPs showed significant associations with risk in one or more of the discovery investigations and were followed up by OCAC. Mixed effects analysis confirmed associations with serous invasive cancers for two correlated (r(2) = 0.62) SNPs: rs2287498 (median per allele OR, 1.30; 95% PI, 1.07-1.57) and rs12951053 (median per allele OR, 1.19; 95% PI, 1.01-1.38). Analyses of other histologic subtypes suggested similar associations with endometrioid but not with mucinous or clear cell cancers. This large study provides statistical evidence for a small increase in risk of ovarian cancer associated with common variants in the TP53 region.

Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk

Polymorphisms in genes critical to cell cycle control are outstanding candidates for association with ovarian cancer risk; numerous genes have been interrogated by multiple research groups using differing tagging single-nucleotide polymorphism (SNP) sets. To maximize information gleaned from existing genotype data, we conducted a combined analysis of five independent studies of invasive epithelial ovarian cancer. Up to 2,120 cases and 3,382 controls were genotyped in the course of two collaborations at a variety of SNPs in 11 cell cycle genes (CDKN2C, CDKN1A, CCND3, CCND1, CCND2, CDKN1B, CDK2, CDK4, RB1, CDKN2D, and CCNE1) and one gene region (CDKN2A-CDKN2B). Because of the semi-overlapping nature of the 123 assayed tagging SNPs, we performed multiple imputation based on fastPHASE using data from White non-Hispanic study participants and participants in the international HapMap Consortium and National Institute of Environmental Health Sciences SNPs Program. Logistic regression assuming a log-additive model was done on combined and imputed data. We observed strengthened signals in imputation-based analyses at several SNPs, particularly CDKN2A-CDKN2B rs3731239; CCND1 rs602652, rs3212879, rs649392, and rs3212891; CDK2 rs2069391, rs2069414, and rs17528736; and CCNE1 rs3218036. These results exemplify the utility of imputation in candidate gene studies and lend evidence to a role of cell cycle genes in ovarian cancer etiology, suggest a reduced set of SNPs to target in additional cases and controls.

Validating genetic risk associations for ovarian cancer through the international Ovarian Cancer Association Consortium

The search for genetic variants associated with ovarian cancer risk has focused on pathways including sex steroid hormones, DNA repair, and cell cycle control. The Ovarian Cancer Association Consortium (OCAC) identified 10 single-nucleotide polymorphisms (SNPs) in genes in these pathways, which had been genotyped by Consortium members and a pooled analysis of these data was conducted. Three of the 10 SNPs showed evidence of an association with ovarian cancer at P< or =0.10 in a log-additive model: rs2740574 in CYP3A4 (P=0.011), rs1805386 in LIG4 (P=0.007), and rs3218536 in XRCC2 (P=0.095). Additional genotyping in other OCAC studies was undertaken and only the variant in CYP3A4, rs2740574, continued to show an association in the replication data among homozygous carriers: OR(homozygous(hom))=2.50 (95% CI 0.54-11.57, P=0.24) with 1406 cases and 2827 controls. Overall, in the combined data the odds ratio was 2.81 among carriers of two copies of the minor allele (95% CI 1.20-6.56, P=0.017, p(het) across studies=0.42) with 1969 cases and 3491 controls. There was no association among heterozygous carriers. CYP3A4 encodes a key enzyme in oestrogen metabolism and our finding between rs2740574 and risk of ovarian cancer suggests that this pathway may be involved in ovarian carcinogenesis. Additional follow-up is warranted.

Polymorphism in the IL18 gene and epithelial ovarian cancer in non-Hispanic white women

Over 22,000 cases of ovarian cancer were diagnosed in 2007 in the United States, but only a fraction of them can be attributed to mutations in highly penetrant genes such as BRCA1. To determine whether low-penetrance genetic variants contribute to ovarian cancer risk, we genotyped 1,536 single nucleotide polymorphisms (SNP) in several candidate gene pathways in 848 epithelial ovarian cancer cases and 798 controls in the North Carolina Ovarian Cancer Study (NCO) using a customized Illumina array. The inflammation gene interleukin-18 (IL18) showed the strongest evidence for association with epithelial ovarian cancer in a gene-by-gene analysis (P = 0.002) with a <25% chance of being a false-positive finding (q value = 0.240). Using a multivariate model search algorithm over 11 IL18 tagging SNPs, we found that the association was best modeled by rs1834481. Further, this SNP uniquely tagged a significantly associated IL18 haplotype and there was an increased risk of epithelial ovarian cancer per rs1834481 allele (odds ratio, 1.24; 95% confidence interval, 1.06-1.45). In a replication stage, 12 independent studies from the Ovarian Cancer Association Consortium (OCAC) genotyped rs1834481 in an additional 5,877 cases and 7,791 controls. The fixed effects estimate per rs1834481 allele was null (odds ratio, 0.99; 95% confidence interval, 0.94-1.05) when data from the 12 OCAC studies were combined. The effect estimate remained unchanged with the addition of the initial North Carolina Ovarian Cancer Study data. This analysis shows the importance of consortia, like the OCAC, in either confirming or refuting the validity of putative findings in studies with smaller sample sizes. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3567-72).

Family history of breast cancer and all-cause mortality after breast cancer diagnosis in the Breast Cancer Family Registry

Although having a family history of breast cancer is a well established breast cancer risk factor, it is not known whether it influences mortality after breast cancer diagnosis. We studied 4,153 women with first primary incident invasive breast cancer diagnosed between 1991 and 2000, and enrolled in the Breast Cancer Family Registry through population-based sampling in Northern California, USA; Ontario, Canada; and Melbourne and Sydney, Australia. Cases were oversampled for younger age at diagnosis and/or family history of breast cancer. Carriers of germline mutations in BRCA1 or BRCA2 were excluded. Cases and their relatives completed structured questionnaires assessing breast cancer risk factors and family history of cancer. Cases were followed for a median of 6.5 years, during which 725 deaths occurred. Cox proportional hazards regression was used to evaluate associations between family history of breast cancer at the time of diagnosis and risk of all-cause mortality after breast cancer diagnosis, adjusting for established prognostic factors. The hazard ratios for all-cause mortality were 0.98 (95% confidence interval [CI] = 0.84-1.15) for having at least one first- or second-degree relative with breast cancer, and 0.85 (95% CI = 0.70-1.02) for having at least one first-degree relative with breast cancer, compared with having no such family history. Estimates did not vary appreciably when stratified by case or tumor characteristics. In conclusion, family history of breast cancer is not associated with all-cause mortality after breast cancer diagnosis for women without a known germline mutation in BRCA1 or BRCA2. Therefore, clinical management should not depend on family history of breast cancer.

Association study of prostate cancer susceptibility variants with risks of invasive ovarian, breast, and colorectal cancer

Several prostate cancer susceptibility loci have recently been identified by genome-wide association studies. These loci are candidates for susceptibility to other epithelial cancers. The aim of this study was to test these tag single nucleotide polymorphisms (SNP) for association with invasive ovarian, colorectal, and breast cancer. Twelve prostate cancer-associated tag SNPs were genotyped in ovarian (2,087 cases/3,491 controls), colorectal (2,148 cases/2,265 controls) and breast (first set, 4,339 cases/4,552 controls; second set, 3,800 cases/3,995 controls) case-control studies. The primary test of association was a comparison of genotype frequencies between cases and controls, and a test for trend stratified by study where appropriate. Genotype-specific odds ratios (OR) were estimated by logistic regression. SNP rs2660753 (chromosome 3p12) showed evidence of association with ovarian cancer [per minor allele OR, 1.19; 95% confidence interval (95% CI), 1.04-1.37; P(trend) = 0.012]. This association was stronger for the serous histologic subtype (OR, 1.29; 95% CI, 1.09-1.53; P = 0.003). SNP rs7931342 (chromosome 11q13) showed some evidence of association with breast cancer (per minor allele OR, 0.95; 95% CI, 0.91-0.99; P(trend) = 0.028). This association was somewhat stronger for estrogen receptor-positive tumors (OR, 0.92; 95% CI, 0.87-0.98; P = 0.011). None of these tag SNPs were associated with risk of colorectal cancer. In conclusion, loci associated with risk of prostate cancer may also be associated with ovarian and breast cancer susceptibility. However, the effects are modest and warrant replication in larger studies.

Performance of BRCA1/2 mutation prediction models in Asian Americans

PURPOSE

There are established differences in breast cancer epidemiology between Asian and white individuals, but little is known about hereditary breast cancer in Asian populations. Although increasing numbers of Asian individuals are clinically tested for BRCA1/2 mutations, it is not known whether computer models that predict mutations work accurately in Asian individuals. We compared the performance in Asian and white individuals of two widely used BRCA1/2 mutation prediction models, BRCAPRO and Myriad II.

PATIENTS AND METHODS

We evaluated BRCAPRO and Myriad II in 200 Asian individuals and a matched control group of 200 white individuals who were tested for BRCA1/2 mutations at four cancer genetics clinics, by comparing numbers of observed versus predicted mutation carriers and by evaluating area under the receiver operating characteristic curve (AUC) for each model.

RESULTS

BRCAPRO and Myriad II accurately predicted the number of white BRCA1/2 mutation carriers (25 observed v 24 predicted by BRCAPRO; 25 predicted by Myriad II, P > or = .69), but underpredicted Asian carriers by two-fold (49 observed v 25 predicted by BRCAPRO; 26 predicted by Myriad II; P < or = 3 x 10(-7)). For BRCAPRO, this racial difference reflects substantial underprediction of Asian BRCA2 mutation carriers (26 observed v 4 predicted; P = 1 x 10(-30)); for Myriad II, separate mutation predictions were not available. For both models, AUCs were nonsignificantly lower in Asian than white individuals, suggesting less accurate discrimination between Asian carriers and noncarriers.

CONCLUSION

Both BRCAPRO and Myriad II underestimated the proportion of BRCA1/2 mutation carriers, and discriminated carriers from noncarriers less well, in Asian compared with white individuals.

Multiple loci with different cancer specificities within the 8q24 gene desert

Recent studies based on genome-wide association, linkage, and admixture scan analysis have reported associations of various genetic variants in 8q24 with susceptibility to breast, prostate, and colorectal cancer. This locus lies within a 1.18-Mb region that contains no known genes but is bounded at its centromeric end by FAM84B and at its telomeric end by c-MYC, two candidate cancer susceptibility genes. To investigate the associations of specific loci within 8q24 with specific cancers, we genotyped the nine previously reported cancer-associated single-nucleotide polymorphisms across the region in four case-control sets of prostate (1854 case subjects and 1894 control subjects), breast (2270 case subjects and 2280 control subjects), colorectal (2299 case subjects and 2284 control subjects), and ovarian (1975 case subjects and 3411 control subjects) cancer. Five different haplotype blocks within this gene desert were specifically associated with risks of different cancers. One block was solely associated with risk of breast cancer, three others were associated solely with the risk of prostate cancer, and a fifth was associated with the risk of prostate, colorectal, and ovarian cancer, but not breast cancer. We conclude that there are at least five separate functional variants in this region.

Consortium analysis of 7 candidate SNPs for ovarian cancer

The Ovarian Cancer Association Consortium selected 7 candidate single nucleotide polymorphisms (SNPs), for which there is evidence from previous studies of an association with variation in ovarian cancer or breast cancer risks. The SNPs selected for analysis were F31I (rs2273535) in AURKA, N372H (rs144848) in BRCA2, rs2854344 in intron 17 of RB1, rs2811712 5' flanking CDKN2A, rs523349 in the 3' UTR of SRD5A2, D302H (rs1045485) in CASP8 and L10P (rs1982073) in TGFB1. Fourteen studies genotyped 4,624 invasive epithelial ovarian cancer cases and 8,113 controls of white non-Hispanic origin. A marginally significant association was found for RB1 when all studies were included [ordinal odds ratio (OR) 0.88 (95% confidence interval (CI) 0.79-1.00) p = 0.041 and dominant OR 0.87 (95% CI 0.76-0.98) p = 0.025]; when the studies that originally suggested an association were excluded, the result was suggestive although no longer statistically significant (ordinal OR 0.92, 95% CI 0.79-1.06). This SNP has also been shown to have an association with decreased risk in breast cancer. There was a suggestion of an association for AURKA, when one study that caused significant study heterogeneity was excluded [ordinal OR 1.10 (95% CI 1.01-1.20) p = 0.027; dominant OR 1.12 (95% CI 1.01-1.24) p = 0.03]. The other 5 SNPs in BRCA2, CDKN2A, SRD5A2, CASP8 and TGFB1 showed no association with ovarian cancer risk; given the large sample size, these results can also be considered to be informative. These null results for SNPs identified from relatively large initial studies shows the importance of replicating associations by a consortium approach.

Effects of common germ-line genetic variation in cell cycle genes on ovarian cancer survival

PURPOSE

Somatic alterations have been shown to correlate with ovarian cancer prognosis and survival, but less is known about the effects on survival of common inherited genetic variation. Of particular interest are genes involved in cell cycle pathways, which regulate cell division and could plausibly influence clinical characteristics of multiple tumors types.

EXPERIMENTAL DESIGN

We examined associations between common germ-line genetic variation in 14 genes involved in cell cycle pathway (CCND1, CCND2, CCND3, CCNE1, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CDKN2D, CDK2, CDK4, CDK6, and RB1) and survival among women with invasive ovarian cancer participating in a multicenter case-control study from United Kingdom, Denmark, and United States. DNAs from up to 1,499 women were genotyped for 97 single-nucleotide polymorphisms that tagged the known common variants (minor allele frequency > or = 0.05) in these genes. The genotypes of each polymorphism were tested for association with survival by Cox regression analysis.

RESULTS

A nominally statistically significant association between genotype and ovarian cancer survival was observed for polymorphisms in CCND2 and CCNE1. The per-allele hazard ratios (95% confidence intervals) were 1.16 (1.03-1.31; P = 0.02) for rs3217933, 1.14 (1.02-1.27; P = 0.024) for rs3217901, and 0.85 (0.73-1.00; P = 0.043) for rs3217862 in CCND2 and 1.39 (1.04-1.85; P = 0.033) for rs3218038 in CCNE1. However, these were not significant after adjusting for multiple hypothesis tests.

CONCLUSION

It is unlikely that common variants in cell cycle pathways examined above associated with moderate effect in survival after diagnosis of ovarian cancer. Much larger studies will be needed to exclude common variants with small effects.

Association between single-nucleotide polymorphisms in hormone metabolism and DNA repair genes and epithelial ovarian cancer: results from two Australian studies and an additional validation set

Although some high-risk ovarian cancer genes have been identified, it is likely that common low penetrance alleles exist that confer some increase in ovarian cancer risk. We have genotyped nine putative functional single-nucleotide polymorphisms (SNP) in genes involved in steroid hormone synthesis (SRD5A2, CYP19A1, HSB17B1, and HSD17B4) and DNA repair (XRCC2, XRCC3, BRCA2, and RAD52) using two Australian ovarian cancer case-control studies, comprising a total of 1,466 cases and 1,821 controls of Caucasian origin. Genotype frequencies in cases and controls were compared using logistic regression. The only SNP we found to be associated with ovarian cancer risk in both of these two studies was SRD5A2 V89L (rs523349), which showed a significant trend of increasing risk per rare allele (P = 0.00002). We then genotyped another SNP in this gene (rs632148; r(2) = 0.945 with V89L) in an attempt to validate this finding in an independent set of 1,479 cases and 2,452 controls from United Kingdom, United States, and Denmark. There was no association between rs632148 and ovarian cancer risk in the validation samples, and overall, there was no significant heterogeneity between the results of the five studies. Further analyses of SNPs in this gene are therefore warranted to determine whether SRD5A2 plays a role in ovarian cancer predisposition.

Comparison of admixture and association mapping in admixed families

The family-based admixture mapping test (AMT) identifies disease-related genes using family data from admixed individuals with the disease of interest (cases). The cases' genotypes at a set of markers are used to infer their DNA ancestry as it varies in blocks along the chromosomes. The test compares the cases' inferred ancestries to those expected from their family histories. Deviation between observed and expected ancestries in a region suggests the presence of a disease gene. We use a likelihood-based development of the AMT to compare it with the transmission disequilibrium test (TDT) as applied to admixed populations. The two tests have a common framework but differ significantly when the disease locus is untyped. The TDT infers disease-locus genotypes using the markers with which it is in linkage disequilibrium (LD). In contrast, the AMT infers disease locus ancestries using those of its linked markers. Thus, TDT power depends on LD between disease and marker loci, while AMT power depends on the lengths of the ancestry blocks containing the disease locus. We compare the power of the two tests when applied to cases with descent from two ancestral populations. The AMT outperforms the TDT when case marker ancestries are correctly specified and LD between disease and marker loci is less than one-third its maximal value (Delta' < 1/3). However, the TDT performs better in the presence of uncertain marker ancestries, even for weak LD between disease and marker loci (Delta' = 0.1). These findings have implications for the design of studies using admixed populations.

Progesterone receptor variation and risk of ovarian cancer is limited to the invasive endometrioid subtype: results from the Ovarian Cancer Association Consortium pooled analysis

There is evidence that progesterone plays a role in the aetiology of invasive epithelial ovarian cancer. Therefore, genes involved in pathways that regulate progesterone may be candidates for susceptibility to this disease. Previous studies have suggested that genetic variants in the progesterone receptor gene (PGR) may be associated with ovarian cancer risk, although results have been inconsistent. We have established an international consortium to pool resources and data from many ovarian cancer case–control studies in an effort to identify variants that influence risk. In this study, three PGR single nucleotide polymorphisms (SNPs), for which previous data have suggested they affect ovarian cancer risk, were examined. These were +331 C/T (rs10895068), PROGINS (rs1042838), and a 3′ variant (rs608995). A total of 4788 ovarian cancer cases and 7614 controls from 12 case–control studies were included in this analysis. Unconditional logistic regression was used to model the association between each SNP and ovarian cancer risk and two-sided P-values are reported. Overall, risk of ovarian cancer was not associated with any of the three variants studied. However, in histopathological subtype analyses, we found a statistically significant association between risk of endometrioid ovarian cancer and the PROGINS allele (n=651, OR=1.17, 95% CI=1.01–1.36, P=0.036). We also observed borderline evidence of an association between risk of endometrioid ovarian cancer and the +331C/T variant (n=725 cases; OR=0.80, 95% CI 0.62–1.04, P=0.100). These data suggest that while these three variants in the PGR are not associated with ovarian cancer overall, the PROGINS variant may play a modest role in risk of endometrioid ovarian cancer.