Celeste Leigh Pearce

Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease

Association studies offer a potentially powerful approach to identify genetic variants that influence susceptibility to common disease, but are plagued by the impression that they are not consistently reproducible. In principle, the inconsistency may be due to false positive studies, false negative studies or true variability in association among different populations. The critical question is whether false positives overwhelmingly explain the inconsistency. We analyzed 301 published studies covering 25 different reported associations. There was a large excess of studies replicating the first positive reports, inconsistent with the hypothesis of no true positive associations (P < 10−14). This excess of replications could not be reasonably explained by publication bias and was concentrated among 11 of the 25 associations. For 8 of these 11 associations, pooled analysis of follow-up studies yielded statistically significant replication of the first report, with modest estimated genetic effects. Thus, a sizable fraction (but under half) of reported associations have strong evidence of replication; for these, false negative, underpowered studies probably contribute to inconsistent replication. We conclude that there are probably many common variants in the human genome with modest but real effects on common disease risk, and that studies using large samples will convincingly identify such variants.

Modeling and E-M Estimation of Haplotype-Specific Relative Risks from Genotype Data for a Case-Control Study of Unrelated Individuals

The US National Cancer Institute has recently sponsored the formation of a Cohort Consortium (http://2002.cancer.gov/scpgenes.htm) to facilitate the pooling of data on very large numbers of people, concerning the effects of genes and environment on cancer incidence. One likely goal of these efforts will be generate a large population-based case-control series for which a number of candidate genes will be investigated using SNP haplotype as well as genotype analysis. The goal of this paper is to outline the issues involved in choosing a method of estimating haplotype-specific risk estimates for such data that is technically appropriate and yet attractive to epidemiologists who are already comfortable with odds ratios and logistic regression. Our interest is to develop and evaluate extensions of methods, based on haplotype imputation, that have been recently described (Schaid et al., Am J Hum Genet, 2002, and Zaykin et al., Hum Hered, 2002) as providing score tests of the null hypothesis of no effect of SNP haplotypes upon risk, which may be used for more complex tasks, such as providing confidence intervals, and tests of equivalence of haplotype-specific risks in two or more separate populations. In order to do so we (1) develop a cohort approach towards odds ratio analysis by expanding the E-M algorithm to provide maximum likelihood estimates of haplotype-specific odds ratios as well as genotype frequencies; (2) show how to correct the cohort approach, to give essentially unbiased estimates for population-based or nested case-control studies by incorporating the probability of selection as a case or control into the likelihood, based on a simplified model of case and control selection, and (3) finally, in an example data set (CYP17 and breast cancer, from the Multiethnic Cohort Study) we compare likelihood-based confidence interval estimates from the two methods with each other, and with the use of the single-imputation approach of Zaykin et al. applied under both null and alternative hypotheses. We conclude that so long as haplotypes are well predicted by SNP genotypes (we use the R2h criteria of Stram et al. [1]) the differences between the three methods are very small and in particular that the single imputation method may be expected to work extremely well.

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 ∼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 × 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, Ptrend = 5.1 × 10−19). The association differs by histological subtype, being strongest for serous ovarian cancers (OR 0.77, 95% CI 0.73–0.81, Ptrend = 4.1 × 10−21).

Prevention of cancers of the breast, endometrium and ovary

A central epidemiological feature of cancers of the breast, endometrium and ovary is the sharp slowing down in their rate of increase with age around the time of menopause. The incidence of these tumors by the age of 70 years would be between fourfold and eightfold increased if the rapid increase with age seen in young women continued into old age. These phenomena can be explained by the different effects of ovarian hormones on cell division rates in the relevant tissues. Models of these effects provide a plausible explanation of most of the known epidemiology of each of the cancers, including the increase in breast cancer risk from menopausal estrogen–progestin therapy. Some recent epidemiological findings in endometrial and ovarian cancer suggest new avenues for possible chemoprevention of these cancers.

Tubal ligation and risk of ovarian cancer subtypes: a pooled analysis of case-control studies

BACKGROUND Tubal ligation is a protective factor for ovarian cancer, but it is unknown whether this protection extends to all invasive histological subtypes or borderline tumors. We undertook an international collaborative study to examine the association between tubal ligation and ovarian cancer subtypes. METHODS We pooled primary data from 13 population-based case-control studies, including 10,157 patients with ovarian cancer (7942 invasive; 2215 borderline) and 13,904 control women. Invasive cases were analysed by histological type, grade and stage, and borderline cases were analysed by histological type. Pooled odds ratios were estimated using conditional logistic regression to match on site, race/ethnicity and age categories, and to adjust for age, oral contraceptive use duration and number of full-term births. RESULTS Tubal ligation was associated with significantly reduced risks of invasive serous (OR, 0.81; 95% CI, 0.74-0.89; P < 0.001), endometrioid (OR, 0.48; 95% CI, 0.40-0.59; P < 0.001), clear cell (OR, 0.52; 95% CI, 0.40-0.67; P < 0.001) and mucinous (OR, 0.68; 95% CI, 0.52-0.89; P = 0.005) cancers. The magnitude of risk reduction was significantly greater for invasive endometrioid (P < 0.0001) and clear cell (P = 0.0018) than for serous cancer. No significant associations were found with borderline serous or mucinous tumours. CONCLUSIONS We found that the protective effects of tubal ligation on ovarian cancer risk were subtype-specific. These findings provide insights into distinct aetiologies of ovarian cancer subtypes and mechanisms underlying the protective effects of tubal ligation.

Aspirin, Nonaspirin Nonsteroidal Anti-inflammatory Drug, and Acetaminophen Use and Risk of Invasive Epithelial Ovarian Cancer: A Pooled Analysis in the Ovarian Cancer Association Consortium

BACKGROUND Regular aspirin use is associated with reduced risk of several malignancies. Epidemiologic studies analyzing aspirin, nonaspirin nonsteroidal anti-inflammatory drug (NSAID), and acetaminophen use and ovarian cancer risk have been inconclusive. METHODS We analyzed pooled data from 12 population-based case-control studies of ovarian cancer, including 7776 case patients and 11843 control subjects accrued between 1992 and 2007. Odds ratios (ORs) for associations of medication use with invasive epithelial ovarian cancer were estimated in individual studies using logistic regression and combined using random effects meta-analysis. Associations between frequency, dose, and duration of analgesic use and risk of ovarian cancer were also assessed. All statistical tests were two-sided. RESULTS Aspirin use was associated with a reduced risk of ovarian cancer (OR = 0.91; 95% confidence interval [CI] = 0.84 to 0.99). Results were similar but not statistically significant for nonaspirin NSAIDs, and there was no association with acetaminophen. In seven studies with frequency data, the reduced risk was strongest among daily aspirin users (OR = 0.80; 95% CI = 0.67 to 0.96). In three studies with dose information, the reduced risk was strongest among users of low dose (<100 mg) aspirin (OR = 0.66; 95% CI = 0.53 to 0.83), whereas for nonaspirin NSAIDs, the reduced risk was strongest for high dose (≥500 mg) usage (OR = 0.76; 95% CI = 0.64 to 0.91). CONCLUSIONS Aspirin use was associated with a reduced risk of ovarian cancer, especially among daily users of low-dose aspirin. These findings suggest that the same aspirin regimen proven to protect against cardiovascular events and several cancers could reduce the risk of ovarian cancer 20% to 34% depending on frequency and dose of use.

Obesity and risk of ovarian cancer subtypes: evidence from the Ovarian Cancer Association Consortium

Whilst previous studies have reported that higher BMI increases a womans risk of developing ovarian cancer, associations for the different histological subtypes have not been well defined. As the prevalence of obesity has increased dramatically, and classification of ovarian histology has improved in the last decade, we sought to examine the association in a pooled analysis of recent studies participating in the Ovarian Cancer Association Consortium. We evaluated the association between BMI (recent, maximum and in young adulthood) and ovarian cancer risk using original data from 15 case-control studies (13 548 cases and 17 913 controls). We combined study-specific adjusted odds ratios (ORs) using a random-effects model. We further examined the associations by histological subtype, menopausal status and post-menopausal hormone use. High BMI (all time-points) was associated with increased risk. This was most pronounced for borderline serous (recent BMI: pooled OR=1.24 per 5 kg/m(2); 95% CI 1.18-1.30), invasive endometrioid (1.17; 1.11-1.23) and invasive mucinous (1.19; 1.06-1.32) tumours. There was no association with serous invasive cancer overall (0.98; 0.94-1.02), but increased risks for low-grade serous invasive tumours (1.13, 1.03-1.25) and in pre-menopausal women (1.11; 1.04-1.18). Among post-menopausal women, the associations did not differ between hormone replacement therapy users and non-users. Whilst obesity appears to increase risk of the less common histological subtypes of ovarian cancer, it does not increase risk of high-grade invasive serous cancers, and reducing BMI is therefore unlikely to prevent the majority of ovarian cancer deaths. Other modifiable factors must be identified to control this disease.

Increased ovarian cancer risk associated with menopausal estrogen therapy is reduced by adding a progestin

It has become increasingly clear that use of menopausal hormone therapy (HT) is associated with an increased risk of ovarian cancer; however, the effects by type of formulation and duration of use are less clear. A systematic review of the HT and ovarian cancer literature was conducted to identify population‐based case‐control studies, cohort studies, and randomized trials that examined effects by formulation of HT (estrogen‐alone [ET] and estrogen plus progestin [EPT]) and duration of use.

Systematic Evaluation of Genetic Variation at the Androgen Receptor Locus and Risk of Prostate Cancer in a Multiethnic Cohort Study

Repeat length of the CAG microsatellite polymorphism in exon 1 of the androgen receptor (AR) gene has been associated with risk of prostate cancer in humans. This association has been the focus of >20 primary epidemiological publications and multiple review articles, but a consistent and reproducible association has yet to be confirmed. We systematically addressed possible causes of false-negative and false-positive association in >4,000 individuals from a multiethnic, prospective cohort study of prostate cancer, comprehensively studying genetic variation by microsatellite genotyping, direct resequencing of exons in advanced cancer cases, and haplotype analysis across the 180-kb AR genomic locus. These data failed to confirm that common genetic variation in the AR gene locus influences risk of prostate cancer. A systematic approach that assesses both coding and noncoding genetic variation in large and diverse patient samples can help clarify hypotheses about association between genetic variants and disease.

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.