Obesity is a leading contributor to colorectal cancer risk. We investigated whether the risk variants identified in genome-wide association studies of body mass index (BMI) and waist size are associated with colorectal cancer risk, independently of the effect of obesity phenotype due to a shared etiology. Twenty four SNPs in 15 loci (BDNF, FAIM2, FTO, GNPDA2, KCTD15, LYPLAL1, MC4R, MSRA, MTCH2, NEGR1, NRXN3, SEC16B, SH2B1, TFAP2B, and TMEM18) were genotyped in a case-control study of 2,033 colorectal cancer cases and 9,640 controls nested within the Multiethnic Cohort Study, as part of the Population Architecture using Genomics and Epidemiology (PAGE) consortium. Risk alleles for two obesity SNPs were associated with colorectal cancer risk – KCTD15 rs29941 [odds ratio (OR) for C allele = 0.90, 95% confidence interval (CI) 0.83–0.98; p = 0.01] and MC4R rs17782313 (OR for C allele = 1.12, 95% CI 1.02–1.22; p = 0.02). These associations were independent of the effect of BMI. However, none of the results remained significant after adjustment for multiple comparisons. No heterogeneity was observed across race/ethnic groups. Our findings suggest that the obesity risk variants are not likely to affect the risk of colorectal cancer substantially.
genotype-phenotype interactions; obesity; pleiotropy; prospective nested case-control studies; race/ethnicity
Peroxisome proliferator-activated receptor gamma (PPARγ) is a transcription factor important for adipogenesis and adipocyte differentiation. Data from animal studies suggest that PPARγ may be involved in breast tumorigenesis, but results from epidemiologic studies on the association between PPARγ variation and breast cancer risk have been mixed. Recent data suggest that soy isoflavones can activate PPARγ. We investigated the inter-relations of soy, PPARγ, and mammographic density (MD), a biomarker of breast cancer risk in a cross-sectional study of 2,038 women who were members of the population-based Singapore Chinese Health Study Cohort.
We assessed MD using a computer-assisted method. We used linear regression to examine the association between 26 tagging SNPs of PPARγ and their interaction with soy intake and MD. To correct for multiple testing, we calculated P-values adjusted for multiple correlated tests (PACT).
Out of the 26 tested SNPs in the PPARγ, 6 SNPs were individually shown to be statistically significantly associated with MD (PACT=0.004∼0.049). A stepwise regression procedure identified that only rs880663 was independently associated with MD which decreased by 1.89% per minor allele (PACT=0.008).This association was significantly stronger in high soy consumers as MD decreased by 3.97% per minor allele of rs880663 in high soy consumers (PACT=0.006; P for interaction with lower soy intake=0.017).
Our data support that PPARγ genetic variation may be important in determining MD, particularly in high soy consumers.
Our findings may help to identify molecular targets and lifestyle intervention for future prevention research.
PPARγ; PPARG; polymorphism; soy; mammographic density; Chinese
Regression calibration has been described as a means of correcting effects of measurement error for normally distributed dietary variables. When foods are the items of interest, true distributions of intake are often positively skewed, may contain many zeroes, and are usually not described by well-known statistical distributions. The authors considered the validity of regression calibration assumptions where data are non-Gaussian. Such data (including many zeroes) were simulated, and use of the regression calibration algorithm was evaluated. An example used data from Adventist Health Study 2 (2002–2008). In this special situation, a linear calibration model does (as usual) at least approximately correct the parameter that captures the exposure-disease association in the “disease” model. Poor fit in the calibration model does not produce biased calibrated estimates when the “disease” model is linear, and it produces little bias in a nonlinear “disease” model if the model is approximately linear. Poor fit will adversely affect statistical power, but more complex linear calibration models can help here. The authors conclude that non-Gaussian data with many zeroes do not invalidate regression calibration. Irrespective of fit, linear regression calibration in this situation at least approximately corrects bias. More complex linear calibration equations that improve fit may increase power over that of uncalibrated regressions.
bias (epidemiology); foods; measurement error; power; regression calibration
Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have identified at least 30 distinct loci associated with small differences in risk. We conducted a GWAS in 2782 advanced PrCa cases (Gleason grade ≥ 8 or tumor stage C/D) and 4458 controls with 571 243 single nucleotide polymorphisms (SNPs). Based on in silico replication of 4679 SNPs (Stage 1, P < 0.02) in two published GWAS with 7358 PrCa cases and 6732 controls, we identified a new susceptibility locus associated with overall PrCa risk at 2q37.3 (rs2292884, P= 4.3 × 10−8). We also confirmed a locus suggested by an earlier GWAS at 12q13 (rs902774, P= 8.6 × 10−9). The estimated per-allele odds ratios for these loci (1.14 for rs2292884 and 1.17 for rs902774) did not differ between advanced and non-advanced PrCa (case-only test for heterogeneity P= 0.72 and P= 0.61, respectively). Further studies will be needed to assess whether these or other loci are differentially associated with PrCa subtypes.
Epidemiologic studies have found evidence of an inverse association between diabetes status and prostate cancer risk. We explored the hypothesis that common genetic variation may explain, in part, the inverse association between diabetes and prostate cancer.
We tested 17 diabetes risk variants for association with prostate cancer risk in a prostate cancer case-control study of 2,746 cases and 3,317 controls from five racial-ethnic groups in the Multiethnic Cohort.
After adjustment for multiple testing none of the alleles were statistically significantly associated with prostate cancer risk. Aggregate scores that sum the risk alleles were also not significantly associated with risk.
We did not find evidence of association of this set of diabetes risk alleles with prostate cancer.
Resequencing and fine-mapping of the GWAS-identified loci for diabetes and prostate cancer is necessary to understand any genetic contribution for the inverse association between these common diseases.
Genitourinary cancer; prostate; type 2 diabetes; multiethnic; epidemiology
We previously reported an association between rs2660753, a prostate cancer susceptibility polymorphism, and invasive epithelial ovarian cancer (EOC) [odds ratio (OR)=1.2, 95% confidence interval (CI)=1.0-1.4, Ptrend=0.01] that showed a stronger association with the serous histological subtype (OR=1.3, 95% CI=1.1-1.5, Ptrend=0.003).
We sought to replicate this association in 12 other studies comprising 4,482 cases and 6,894 controls of white non-Hispanic ancestry in the Ovarian Cancer Association Consortium.
No evidence for an association with all cancers or serous cancers was observed in a combined analysis of data from the replication studies (all: OR=1.0, 95% CI=0.9-1.1, Ptrend=0.61; serous: OR=1.0, 95% CI=0.9-1.1, Ptrend=0.85) or from the combined analysis of discovery and replication studies (all: OR=1.0, 95% CI=1.0-1.1, Ptrend= 0.28; serous: OR=1.1, 95% CI=1.0-1.2, Ptrend=0.11). There was no evidence for statistical heterogeneity in ORs across the studies.
Although rs2660753 is a strong a prostate cancer susceptibility polymorphism, the association with another hormonally related cancer, invasive EOC, is not supported by this replication study.
Our findings, based on a larger sample size, emphasize the importance of replicating potentially promising genetic risk associations.
chromosome 3p; SNP; ovarian cancer; risk factors
Genome-wide association studies (GWAS) have identified common variants associated with breast cancer risk among women of European and Asian ancestries. To assess the generalizability across ethnic/racial populations of a risk score derived from genotyping 12 highly replicated breast cancer GWAS hits, we performed a case-control study (2224 cases and 2827 controls) nested in the Multiethnic Cohort (MEC) study, which was initiated in 1993–1996 and consists of subjects mainly from European-American, African-American, Native Hawaiian, Japanese and Latino populations. When viewed as a summary risk score, the total number of risk alleles carried by women was significantly associated with breast cancer risk overall (OR per allele, 1.09; 95% CI, 1.06–1.12; P=2.0 × 10−10) and in all populations except African-Americans, in which no significant association was observed (OR, 1.03; 95% CI, 0.98–1.08). In aggregate, the number of risk alleles is strongly associated with breast cancer risk in all populations studied except African-Americans. These results emphasize the need for large-scale association studies of multiple racial/ethnic groups for discovery and characterization of risk alleles relevant to all populations in the United States.
breast cancer; risk markers; summary score; generalizability; diverse populations
Although the Women’s Health Initiative trial (WHI) suggested that menopausal hormone therapy (HT) does not reduce coronary heart disease mortality overall, subsequent results have suggested that there may be a benefit in younger women. The California Teachers Cohort Study (CTS) questionnaire and mortality data was used to examine whether age modified the association between HT and the relative risk of overall mortality and ischemic heart disease (IHD) deaths.
Participants from the CTS were 71,237 postmenopausal women (mean age = 63, range 36 to 94 years) followed prospectively for mortality and other outcomes from 1995–1996 through 2004.
Age at baseline was a much more important modifier of HT effects than age at start of therapy. Risks for all-cause mortality (n=8,399) were lower for younger current HT users at baseline than for never users (for women ≤60 years: HR=0.54, 95% CI=0.46–0.62). These risk reductions greatly diminished, in a roughly linear fashion, with increasing baseline age (for women 85–94 years HR=0.94, 95% CI=0.81–1.10 for all-cause mortality). Similar results were seen for IHD deaths (n=1,464). No additional significant modifying effects of age at first use, duration of use, or formulation were apparent.
These results provide evidence that reduced risks of mortality associated with HT use are observed among younger users but not for older postmenopausal women even those starting therapy close to their time of menopause.
Overall mortality; heart disease; menopausal hormone therapy; risk; survival; age
Genome-wide association studies (GWAS) in populations of European ancestry have identified several loci that confer an increased risk of colorectal cancer (CRC).
We studied the generalizability of the associations with 11 risk variants for CRC on 8q23 (rs16892766), 8q24 (rs6983267), 9p24 (rs719725), 10p14 (rs10795668), 11q23 (rs3802842), 14q22 (rs4444235), 15q13 (rs4779584), 16q22 (rs9929218), 18q21 (rs4939827), 19q13 (rs10411210) and 20p12 (rs961253) in a multiethnic sample of 2,472 CRC cases, 839 adenoma cases and 4,466 controls comprised of European American, African American, Native Hawaiian, Japanese American and Latino men and women. Because findings for CRC and adenoma were similar, we combined both groups in the analyses.
We confirmed the associations with an increased risk of CRC/adenoma for the 8q24, 11q23 and 15q13 loci in European Americans, and observed significant associations between the 8q24 and 20p12 loci with CRC/adenoma risk in African Americans. Moreover, we found statistically significant cumulative effects of risk alleles on CRC/adenoma risk in all populations (odds ratio (OR) per allele = 1.07–1.09, p≤0.039) except in Japanese Americans (OR=1.01, p=0.52). We found heterogeneity in the associations by tumor subsite, age of CRC/adenoma onset, sex, body mass index (BMI) and smoking status for some of the variants.
These results provide evidence that the known variants are in aggregate significantly associated with CRC/adenoma risk in multiple populations except Japanese Americans, and the influences may differ across groups defined by clinicopathological characteristics for some variants.
These results underline the importance of studying the epidemiologic architecture of these genetic effects in large and diverse populations.
Colorectal Cancer; Genetic Susceptibility; Cancer in minority; Underserved populations; Multiethnic Cohort
There is extensive evidence that increases in blood and tissue concentrations of steroid hormones and of insulin-like growth factor I (IGF-I) are associated with breast cancer risk. However, studies of common variation in genes involved in steroid hormone and IGF-I metabolism have yet to provide convincing evidence that such variants predict breast cancer risk. The Breast and Prostate Cancer Cohort Consortium (BPC3) is a collaboration of large US and European cohorts. We genotyped 1416 tagging single nucleotide polymorphisms (SNPs) in 37 steroid hormone metabolism genes and 24 IGF-I pathway genes in 6292 cases of breast cancer and 8135 controls, mostly Caucasian, postmenopausal women from the BPC3. We also imputed 3921 additional SNPs in the regions of interest. None of the SNPs tested was significantly associated with breast cancer risk, after correction for multiple comparisons. The results remained null when cases and controls were stratified by age at diagnosis/recruitment, advanced or nonadvanced disease, body mass index, with or without in situ cases; or restricted to Caucasians. Among 770 estrogen receptor-negative cases, an SNP located 3′ of growth hormone receptor (GHR) was marginally associated with increased risk after correction for multiple testing (Ptrend = 1.5 × 10−4). We found no significant overall associations between breast cancer and common germline variation in 61 genes involved in steroid hormone and IGF-I metabolism in this large, comprehensive study. Although previous studies have shown that variations in these genes can influence endogenous hormone levels, the magnitude of the effect of single SNPs does not appear to be sufficient to alter breast cancer risk.
Beta-microseminoprotein (MSP) is one of the three most abundantly secreted proteins of the prostate, and has been suggested as a biomarker for prostate cancer risk. A common variant, rs10993994, in the 5’ region of the gene which encodes MSP (MSMB), has recently been identified as a risk factor for prostate cancer.
We examined the association between rs10993994 genotype and MSP levels in a sample of 500 prostate cancer-free men from four racial/ethnic populations in the Multiethnic Cohort (European Americans, African Americans, Latinos, and Japanese Americans). Generalized linear models were used to estimate the association between rs10993994 genotype and MSP levels.
We observed robust associations between rs10994994 genotype and MSP levels in each racial/ethnic population (all P<10−8) with carriers of the C allele having lower geometric mean MSP levels (ng/mL) (CC/CT/TT genotypes: European Americans, 28.8/20.9/10.0; African Americans, 29.0/21.9/10.9; Latinos, 29.2/17.1/8.3; and Japanese Americans 25.8/16.4/6.7). We estimated the variant accounts for 30–50% of the variation in MSP levels in each population. We also observed significant differences in MSP levels between populations (P=3.5×10−6), with MSP levels observed to be highest in African Americans and lowest in Japanese Americans.
Rs10993994 genotype is strongly associated with plasma MSP levels in multiple racial/ethnic populations.
This supports the hypothesis that rs10993994 may be the biologically functional allele.
MSMB; beta-microseminoprotein; prostate; genetic; multiethnic
The insulin-like growth factor (IGF) pathway has been implicated in prostate development and carcinogenesis. We conducted a comprehensive analysis, utilizing a resequencing and tagging single-nucleotide polymorphism (SNP) approach, between common genetic variation in the IGF1, IGF binding protein (BP) 1, and IGFBP3 genes with IGF-I and IGFBP-3 blood levels, and prostate cancer (PCa) risk, among Caucasians in the NCI Breast and Prostate Cancer Cohort Consortium. We genotyped 14 IGF1 SNPs and 16 IGFBP1/IGFBP3 SNPs to capture common [minor allele frequency (MAF) ≥ 5%] variation among Caucasians. For each SNP, we assessed the geometric mean difference in IGF blood levels (N = 5684) across genotypes and the association with PCa risk (6012 PCa cases/6641 controls). We present two-sided statistical tests and correct for multiple comparisons. A non-synonymous IGFBP3 SNP in exon 1, rs2854746 (Gly32Ala), was associated with IGFBP-3 blood levels (Padj = 8.8 × 10−43) after adjusting for the previously established IGFBP3 promoter polymorphism A-202C (rs2854744); IGFBP-3 blood levels were 6.3% higher for each minor allele. For IGF1 SNP rs4764695, the risk estimates among heterozygotes was 1.01 (99% CI: 0.90–1.14) and 1.20 (99% CI: 1.06–1.37) for variant homozygotes with overall PCa risk. The corrected allelic P-value was 8.7 × 10−3. IGF-I levels were significantly associated with PCa risk (Ptrend = 0.02) with a 21% increase of PCa risk when compared with the highest quartile to the lowest quartile. We have identified SNPs significantly associated with IGFBP-3 blood levels, but none of these alter PCa risk; however, a novel IGF1 SNP, not associated with IGF-I blood levels, shows preliminary evidence for association with PCa risk among Caucasians.
It is well-known that population substructure may lead to confounding in case-control association studies. Here, we examined genetic structure in a large racially and ethnically diverse sample consisting of 5 ethnic groups of the Multiethnic Cohort study (African Americans, Japanese Americans, Latinos, European Americans and Native Hawaiians) using 2,509 SNPs distributed across the genome. Principal component analysis on 6,213 study participants, 18 Native Americans and 11 HapMap III populations revealed 4 important principal components (PCs): the first two separated Asians, Europeans and Africans, and the third and fourth corresponded to Native American and Native Hawaiian (Polynesian) ancestry, respectively. Individual ethnic composition derived from self-reported parental information matched well to genetic ancestry for Japanese and European Americans. STRUCTURE-estimated individual ancestral proportions for African Americans and Latinos are consistent with previous reports. We quantified the East Asian (mean 27%), European (mean 27%) and Polynesian (mean 46%) ancestral proportions for the first time, to our knowledge, for Native Hawaiians. Simulations based on realistic settings of case-control studies nested in the Multiethnic Cohort found that the effect of population stratification was modest and readily corrected by adjusting for race/ethnicity or by adjusting for top PCs derived from all SNPs or from ancestry informative markers; the power of these approaches was similar when averaged across causal variants simulated based on allele frequencies of the 2,509 genotyped markers. The bias may be large in case-only analysis of gene by gene interactions but it can be corrected by top PCs derived from all SNPs.
AIMs; African American; Native Hawaiian; Latino; admixture; principal component analysis
A low meat diet and regular non-steroidal anti-inflammatory drugs (NSAIDs) have been associated with decreased mortality among colorectal cancer (CRC) patients. Here we investigated the association between pre-diagnosis usual meat consumption and CRC-specific mortality, and whether meat consumption modifies the previously noted association between NSAID use and CRC-specific mortality among women in the California Teachers Study (CTS) cohort. Women joining CTS in 1995–1996 without prior CRC diagnosis, diagnosed with incident CRC during follow-up through December 2007, were eligible for inclusion. Meat intake (frequency and serving size) and NSAID use (aspirin or ibuprofen use) were ascertained via self-administered questionnaires before diagnosis. Vital status and cause of death were determined by linkage with mortality files. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HR) for death and 95% confidence intervals (CI). Pre-diagnosis meat consumption was not associated with CRC-specific mortality among 704 CRC patients (and 201 CRC-specific deaths), comparing patients in the lowest consumption tertile (0–5.4 medium-size servings/week) to those with higher consumption. Regular NSAID use (1–3 times/week, 4–6 times/week, daily) vs. none was associated with decreased CRC-specific mortality among patients in the lowest meat consumption tertile (HR=0.22, 95% CI 0.06–0.82), but not among patients in the higher meat intake tertiles. The previously observed mortality risk reduction among female CRC patients associated with regular NSAID use was restricted to patients who reported low meat intake before diagnosis. These findings have implications for CRC survivorship and tertiary CRC prevention.
Epithelial ovarian cancer (EOC) is the leading cause of death from gynecological malignancy in the developed world accounting for 4 percent of deaths from cancer in women1. We performed a three-phase genome-wide association study of EOC survival in 8,951 EOC cases with available survival time data, and a parallel association analysis of EOC susceptibility. Two SNPs at 19p13.11, rs8170 and rs2363956, showed evidence of association with survival (overall P=5×10−4 and 6×10−4), but did not replicate in phase 3. However, the same two SNPs demonstrated genome-wide significance for risk of serous EOC (P=3×10−9 and 4×10−11 respectively). Expression analysis of candidate genes at this locus in ovarian tumors supported a role for the BRCA1 interacting gene C19orf62, also known as MERIT40, which contains rs8170, in EOC development.
Non-steroidal anti-inflammatory drug (NSAID) use has been associated with decreased colorectal cancer (CRC) risk. However, NSAID effects on clinical outcomes after CRC diagnosis are not well-defined. We investigated the association of pre-diagnosis NSAID use and mortality after CRC diagnosis among women in the California Teachers Study (CTS) cohort.
Women under 85 years participating in the CTS, without prior CRC diagnosis at baseline (1995-1996), and diagnosed with CRC during follow-up through December 2005, were eligible for analysis of the association of pre-diagnosis NSAID use and mortality. NSAID use (including aspirin, and ibuprofen) was collected through a self-administered questionnaire. Cancer occurrence was identified through California Cancer Registry linkage. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HR) for death and 95% confidence intervals (CI).
Among 621 CRC cases identified, 64% reported no pre-diagnosis regular NSAID use, 17% reported use 1-6 days/week, and 20% reported daily use; duration of NSAID use < 5 years was reported by 17% and ≥5 years reported by 18%. Regular pre-diagnosis NSAID use (1-3 days/week, 4-6 days/week, daily) vs. none was associated with improved overall survival (OS) (HR=0.71, 95% CI 0.53-0.95) and CRC-specific survival (CRC-SS) (HR=0.58, 95% CI 0.40-0.84) after adjustment for clinically relevant factors. Pre-diagnosis NSAID use ≥5 years (versus none) was associated with improved OS (HR=0.55, 95% CI 0.37-0.84) and CRC-SS (HR=0.40, 95% CI 0.23-0.71) in adjusted analyses.
When used regularly or over a prolonged duration prior to CRC diagnosis, NSAIDs are associated with decreased mortality among female CRC cases.
Colon cancer; colorectal cancer; non-steroidal anti-inflammatory drugs; NSAIDs; rectal cancer; survival
It has been recently hypothesized that many of the signals detected in genome-wide association studies (GWAS) to T2D and other diseases, despite being observed to common variants, might in fact result from causal mutations that are rare. One prediction of this hypothesis is that the allelic associations should be population-specific, as the causal mutations arose after the migrations that established different populations around the world. We selected 19 common variants found to be reproducibly associated to T2D risk in European populations and studied them in a large multiethnic case-control study (6,142 cases and 7,403 controls) among men and women from 5 racial/ethnic groups (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In analysis pooled across ethnic groups, the allelic associations were in the same direction as the original report for all 19 variants, and 14 of the 19 were significantly associated with risk. In summing the number of risk alleles for each individual, the per-allele associations were highly statistically significant (P<10−4) and similar in all populations (odds ratios 1.09–1.12) except in Japanese Americans the estimated effect per allele was larger than in the other populations (1.20; Phet = 3.8×10−4). We did not observe ethnic differences in the distribution of risk that would explain the increased prevalence of type 2 diabetes in these groups as compared to European Americans. The consistency of allelic associations in diverse racial/ethnic groups is not predicted under the hypothesis of Goldstein regarding “synthetic associations” of rare mutations in T2D.
Single rare causal alleles and/or collections of multiple rare alleles have been suggested to create “synthetic associations” with common variants in genome-wide association studies (GWAS). This model predicts that associations with common variants will not be consistent across populations. In this study, we examined 19 T2D variants for association with T2D risk in 6,142 cases and 7,403 controls from five racial/ethnic populations in the Multiethnic Cohort (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In racial/ethnic pooled analysis, all 19 variants were associated with T2D risk in the same direction as previous reports in Europeans, and the sum total of risk variants was significantly associated with T2D risk in each racial/ethnic group. The consistent associations across populations do not support the Goldstein hypothesis that rare causal alleles underlie GWAS signals. We also did not find evidence that these markers underlie racial/ethnic disparities in T2D prevalence. Large-scale GWAS and sequencing studies in these populations are necessary in order to both improve the current set of markers at these risk loci and identify new risk variants for T2D that may be difficult, or impossible, to detect in European populations.
Genome-wide association studies have identified multiple common alleles associated with prostate cancer risk in populations of European ancestry. Testing these variants in other populations is needed to assess the generalizability of the associations, and may guide fine-mapping efforts. We examined 13 of these risk variants in a multiethnic sample of 2,768 incident prostate cancer cases and 2,359 controls from the Multiethnic Cohort (MEC; African Americans, European Americans, Latinos, Japanese Americans and Native Hawaiians). We estimated ethnic-specific and pooled odds ratios and tested for ethnic heterogeneity of effects using logistic regression. In ethnic-pooled analyses, 12 of the 13 variants were positively associated with risk, with statistically significant associations (p<0.05) noted with 6 variants (odds ratio, 95% confidence interval): JAZF1, rs10486567, 1.23(1.12–1.35); Xp11.2, rs5945572, 1.31(1.13–1.51); HNF1B, rs4430796, 1.15(1.06–1.25); MSMB, rs10993994, 1.13(1.04–1.23); 11q13.2, rs7931342, 1.13(1.03–1.23); 3p12.1, rs2660753, 1.11(1.01–1.21); SLC22A3, rs9364554, 1.10(1.00–1.21); CTBP2, rs12769019, 1.11(0.99–1.25); HNF1B, rs11649743, 1.10(0.99–1.22); EHBP1, rs721048, 1.08(0.94–1.25); KLK2/3, rs2735839, 1.06(0.97–1.16); 17q24.3, rs1859962, 1.04(0.96–1.13); and LMTK2, rs6465657, 0.99(0.89–1.09). Significant ethnic heterogeneity of effects was noted for 4 variants (EHBP1, phet = 3.9×10−3; 11q13, phet = 0.023; HNF1B (rs4430796), phet = 0.026; and KLK2/3, phet = 2.0×10−3). Although power was limited in some ethnic/racial groups due to variation in sample size and allele frequencies, these findings suggest that a large fraction of prostate cancer variants identified in populations of European ancestry are global markers of risk. For many of these regions, fine-mapping in non-European samples may help localize causal alleles and better determine their contribution to prostate cancer risk in the population.
Genitourinary Cancers; Prostate; Risk Assessment; Epidemiology; Cancer in minority and underserved populations; Genetics of Risk; Outcome, and Prevention; MEC
Because of the high cost of commercial genotyping chip technologies, many investigations have used a two-stage design for genome-wide association studies, using part of the sample for an initial discovery of “promising” SNPs at a less stringent significance level and the remainder in a joint analysis of just these SNPs using custom genotyping. Typical cost savings of about 50% are possible with this design to obtain comparable levels of overall type I error and power by using about half the sample for stage I and carrying about 0.1% of SNPs forward to the second stage, the optimal design depending primarily upon the ratio of costs per genotype for stages I and II. However, with the rapidly declining costs of the commercial panels, the generally low observed ORs of current studies, and many studies aiming to test multiple hypotheses and multiple endpoints, many investigators are abandoning the two-stage design in favor of simply genotyping all available subjects using a standard high-density panel. Concern is sometimes raised about the absence of a “replication” panel in this approach, as required by some high-profile journals, but it must be appreciated that the two-stage design is not a discovery/replication design but simply a more efficient design for discovery using a joint analysis of the data from both stages. Once a subset of highly-significant associations has been discovered, a truly independent “exact replication” study is needed in a similar population of the same promising SNPs using similar methods. This can then be followed by (1) “generalizability” studies to assess the full scope of replicated associations across different races, different endpoints, different interactions, etc.; (2) fine-mapping or re-sequencing to try to identify the causal variant; and (3) experimental studies of the biological function of these genes. Multistage sampling designs may be more useful at this stage, say for selecting subsets of subjects for deep re-sequencing of regions identified in the GWAS.
multistage sampling; genetic associations; replication; re-sequencing; DNA pooling; gene-environment interactions
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.
IGF2R has been proposed to be a tumor suppressor gene given its antagonist role on cellular growth and evidence of loss of heterozygosity in several cancers, including breast cancer. To investigate whether inherited differences in potentially functional IGF2R variants influence the risk of breast cancer, we sequenced 46 exons of IGF2R to identify novel missense single-nucleotide polymorphisms (SNP) and tested 12 missense SNPs for their associations with breast cancer risk among 1,614 breast cancer cases and 1,960 controls from the Multiethnic Cohort. None of these missense SNPs were significantly associated with breast cancer risk. Our findings provide no evidence that missense SNPs in IGF2R influence breast cancer susceptibility.
Among men of European ancestry, diabetics have a lower risk of prostate cancer than do nondiabetics. The biologic basis of this association is unknown. The authors have examined whether the association is robust across populations in a population-based prospective study. The analysis included 5,941 prostate cancer cases identified over a 12-year period (1993–2005) among 86,303 European-American, African-American, Latino, Japanese-American, and Native Hawaiian men from the Multiethnic Cohort. The association between diabetes and prostate-specific antigen (PSA) levels (n = 2,874) and PSA screening frequencies (n = 46,970) was also examined. Diabetics had significantly lower risk of prostate cancer than did nondiabetics (relative risk = 0.81, 95% confidence interval (CI): 0.74, 0.87; P < 0.001), with relative risks ranging from 0.65 (95% CI: 0.50, 0.84; P = 0.001) among European Americans to 0.89 (95% CI: 0.77, 1.03; P = 0.13) among African Americans. Mean PSA levels were significantly lower in diabetics than in nondiabetics (mean PSA levels, 1.07 and 1.28, respectively; P = 0.003) as were PSA screening frequencies (44.7% vs. 48.6%; P < 0.001); however, this difference could explain only a small portion (∼20%) of the inverse association between these diseases. Diabetes is a protective factor for prostate cancer across populations, suggesting shared risk factors that influence a common mechanism.
cohort studies; diabetes mellitus, type 2; ethnology; prostate-specific antigen; prostatic neoplasms
To evaluate the reproducibility and validity of the food-frequency questionnaire (FFQ) used in the California Teachers Study (CTS) cohort and to use this data to quantify the effects of correcting nutrient-breast cancer relative risks for measurement error.
195 CTS cohort members participated in a 10-month dietary validation study that included four 24-hour dietary recalls and pre- and post-study FFQs. Shrout-Fleiss intraclass correlations for reproducibility were computed. Under several standard assumptions concerning the correlations of errors in the FFQs and 24-hour recalls, we calculated energy-adjusted deattenuated Pearson correlations for validity and tested for differences in validity according to a number of demographic and other risk factors. For each nutrient, we compared ot performance of the FFQ versus the 24-hour recalls, estimating the number of days of recalls that give equivalent information about true intake as does a single FFQ.. Finally, the effects of adjustment for measurement error on risk estimates were evaluated in 44,423 postmenopausal cohort members, 1,544 of whom developed breast cancer during seven years of follow-up. Relative risks (RR) and confidence intervals (CI) were calculated using Cox proportional hazards with and without correction for measurement error.
Reproducibility correlations for the nutrients ranged from 0.60 to 0.87. With a few exceptions, validity correlations were reasonably high (range: 0.55–0.85), including r=0.74 for alcohol. Performance of the FFQ differed by age for percent of calories from fat and by body mass index and hormone therapy use for alcohol consumption. For most nutrients examined, our FFQ is comparable to two to six recalls for each subject in capturing true intake. In the measurement error-adjusted risk analyses, corrected RRs were within 13% of uncorrected values for all nutrients examined except for linoleic acid. For alcohol consumption the corrected RR (per 20g/1000kcal/d) was 1.36 (95% CI: 1.03–1.51) compared to the uncorrected estimate of 1.25 (95% CI: 1.10–1.42).
The FFQ dietary assessment used in the CTS is reproducible and valid for all nutrients except the unsaturated fatty acids. Correcting relative risk estimates for measurement error resulted in relatively small changes in the associations between the majority of nutrients and the risk of postmenopausal breast cancer.
dietary assessment; reproducibility; validity; calibration; breast cancer; alcohol
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 sub-type (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 were associated with ovarian cancer risk. Further work will be needed to identify the causal variant associated with rs4954956 or elucidate its function.
We propose a modification of the well-known Armitage trend test to address the problems associated with hidden population structure and hidden relatedness in genome-wide case-control association studies.
The new test adopts beneficial traits from three existing testing strategies: the principal components, mixed model, and genomic control while avoiding some of their disadvantageous characteristics, such as the tendency of the principal components method to over-correct in certain situations or the failure of the genomic control approach to reorder the adjusted tests based on their degree of alignment with the underlying hidden structure. The new procedure is based on Gauss-Markov estimators derived from a straightforward linear model with an imposed variance structure proportional to an empirical relatedness matrix. Lastly, conceptual and analytical similarities to and distinctions from other approaches are emphasized throughout.
Our simulations show that the power performance of the proposed test is quite promising compared to the considered competing strategies. The power gains are especially large when small differential differences between cases and controls are present; a likely scenario when public controls are used in multiple studies.
The proposed modified approach attains high power more consistently than that of the existing commonly implemented tests. Its performance improvement is most apparent when small but detectable systematic differences between cases and controls exist.