Renal cell carcinoma (RCC) is the most lethal urologic cancer. Only two common susceptibility loci for RCC have been confirmed to date. To identify additional RCC common susceptibility loci, we conducted an independent genome-wide association study (GWAS). We analyzed 533 191 single nucleotide polymorphisms (SNPs) for association with RCC in 894 cases and 1516 controls of European descent recruited from MD Anderson Cancer Center in the primary scan, and validated the top 500 SNPs in silico in 3772 cases and 8505 controls of European descent involved in the only published GWAS of RCC. We identified two common variants in linkage disequilibrium, rs718314 and rs1049380 (r2 = 0.64, D ′ = 0.84), in the inositol 1,4,5-triphosphate receptor, type 2 (ITPR2) gene on 12p11.23 as novel susceptibility loci for RCC (P = 8.89 × 10−10 and P = 6.07 × 10−9, respectively, in meta-analysis) with an allelic odds ratio of 1.19 [95% confidence interval (CI): 1.13–1.26] for rs718314 and 1.18 (95% CI: 1.12–1.25) for rs1049380. It has been recently identified that rs718314 in ITPR2 is associated with waist–hip ratio (WHR) phenotype. To our knowledge, this is the first genetic locus associated with both cancer risk and WHR.

Over the past several years, genome-wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large-Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large-scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene-gene and gene-environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized.

In an analysis of 31,717 cancer cases and 26,136 cancer-free controls drawn from 13 genome-wide association studies (GWAS), we observed large chromosomal abnormalities in a subset of clones from DNA obtained from blood or buccal samples. Mosaic chromosomal abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of size >2 Mb were observed in autosomes of 517 individuals (0.89%) with abnormal cell proportions between 7% and 95%. In cancer-free individuals, the frequency increased with age; 0.23% under 50 and 1.91% between 75 and 79 (p=4.8×10−8). Mosaic abnormalities were more frequent in individuals with solid-tumors (0.97% versus 0.74% in cancer-free individuals, OR=1.25, p=0.016), with a stronger association for cases who had DNA collected prior to diagnosis or treatment (OR=1.45, p=0.0005). Detectable clonal mosaicism was common in individuals for whom DNA was collected at least one year prior to diagnosis of leukemia compared to cancer-free individuals (OR=35.4, p=3.8×10−11). These findings underscore the importance of the role and time-dependent nature of somatic events in the etiology of cancer and other late-onset diseases.

We conducted a genome-wide association study (GWAS) of breast cancer by genotyping 528,173 single nucleotide polymorphisms (SNPs) in 1,145 cases of invasive breast cancer among postmenopausal white women, and 1,142 controls. We identified a set of four SNPs in intron 2 of FGFR2, a tyrosine kinase receptor previously shown to be amplified and/or over-expressed in some breast cancers, as highly associated with breast cancer and we confirmed this association in 1,776 cases and 2,072 controls from three additional studies. In both association testing and ancestral recombination graph analysis, FGFR2 haplotypes were associated with risk of breast cancer. Across the four studies the association with all four SNPs was highly statistically significant (Ptrend for the most strongly associated SNP, rs1219648 = 1.1 × 10−10; population attributable risk = 16%). Four SNPs at other chromosomal loci most strongly associated with breast cancer in the initial GWAS were not associated with risk in the three replication studies. Our summary results from the GWAS are freely available online in a form that should speed the identification of additional loci conferring risk.

Aims

We introduce an innovative multilocus test for disease association. It is an extension of an existing score test that gains power over alternative methods by incorporating a parsimonious one-degree-of-freedom model for interaction. We use our method in applications designed to detect interactions that generate hypotheses about the functionality of prostate cancer (PRCA) susceptibility regions.

Methods

Our proposed score test is designed to gain additional power through the use of a retrospective likelihood that exploits an assumption of independence between unlinked loci in the underlying population. Its performance is validated through simulation. The method is used in conditional scans with data from stage II of the Cancer Genetic Markers of Susceptibility PRCA genome-wide association study.

Results

Our proposed method increases power to detect susceptibility loci in diverse settings. It identified two high-ranking, biologically interesting interactions: (1) rs748120 of NR2C2 and subregions of 8q24 that contain independent susceptibility loci specific to PRCA and (2) rs4810671 of SULF2 and both JAZF1 and HNF1B that are associated with PRCA and type 2 diabetes.

Conclusions

Our score test is a promising multilocus tool for genetic epidemiology. The results of our applications suggest functionality for poorly understood PRCA susceptibility regions. They motivate replication study.

Genome-wide and candidate-gene association studies of bladder cancer have identified 10 susceptibility loci thus far. We conducted a meta-analysis of two previously published genome-wide scans (4501 cases and 6076 controls of European background) and followed up the most significant association signals [17 single nucleotide polymorphisms (SNPs) in 10 genomic regions] in 1382 cases and 2201 controls from four studies. A combined analysis adjusted for study center, age, sex, and smoking status identified a novel susceptibility locus that mapped to a region of 18q12.3, marked by rs7238033 (P = 8.7 × 10–9; allelic odds ratio 1.20 with 95% CI: 1.13–1.28) and two highly correlated SNPs, rs10775480/rs10853535 (r2= 1.00; P = 8.9 × 10–9; allelic odds ratio 1.16 with 95% CI: 1.10–1.22). The signal localizes to the solute carrier family 14 member 1 gene, SLC14A1, a urea transporter that regulates cellular osmotic pressure. In the kidney, SLC14A1 regulates urine volume and concentration whereas in erythrocytes it determines the Kidd blood groups. Our findings suggest that genetic variation in SLC14A1 could provide new etiological insights into bladder carcinogenesis.

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.

Background

For many analytical methods the efficiency of DNA amplification varies across the genome and between samples. The most affected genome regions tend to correlate with high C + G content, however this relationship is complex and does not explain why the direction and magnitude of effects varies considerably between samples.

Results

Here, we provide evidence that sequence elements that are particularly high in C + G content can remain annealed even when aggressive melting conditions are applied. In turn, this behavior creates broader ‘Thermodynamically Ultra-Fastened’ (TUF) regions characterized by incomplete denaturation of the two DNA strands, so reducing amplification efficiency throughout these domains.

Conclusions

This model provides a mechanistic explanation for why some genome regions are particularly difficult to amplify and assay in many procedures, and importantly it also explains inter-sample variability of this behavior. That is, DNA samples of varying quality will carry more or fewer nicks and breaks, and hence their intact TUF regions will have different lengths and so be differentially affected by this amplification suppression mechanism – with ‘higher’ quality DNAs being the most vulnerable. A major practical consequence of this is that inter-region and inter-sample variability can be largely overcome by employing routine fragmentation methods (e.g. sonication or restriction enzyme digestion) prior to sample amplification.

Next Generation Sequencing represents a powerful tool for detecting genetic variation associated with human disease. Because of the high cost of this technology, it is critical that we develop efficient study designs that consider the trade-off between the number of subjects (n) and the coverage depth (μ). How we divide our resources between the two can greatly impact study success, particularly in pilot studies. We propose a strategy for selecting the optimal combination of n and μ for studies aimed at detecting rare variants and for studies aimed at detecting associations between rare or uncommon variants and disease. For detecting rare variants, we find the optimal coverage depth to be between 2 and 8 reads when using the likelihood ratio test. For association studies, we find the strategy of sequencing all available subjects to be preferable. In deriving these combinations, we provide a detailed analysis describing the distribution of depth across a genome and the depth needed to identify a minor allele in an individual. The optimal coverage depth depends on the aims of the study, and the chosen depth can have a large impact on study success.

We report a genome-wide association study in 10,286 cases and 9,135 controls of European ancestry, in the Cancer Genetic Markers of Susceptibility (CGEMS) initiative, identifying a new association with prostate cancer risk on chromosome 8q24 (rs620861, p=1.3×10-10, heterozygote OR = 1.17, 95% CI 1.10 – 1.24; homozygote OR = 1.33; 95% CI 1.21 – 1.45). This defines a new prostate locus on 8q24, Region 4, previously associated with breast cancer.

Previous genome-wide association studies have identified two independent variants in HNF1B as susceptibility loci for prostate cancer risk. To fine-map common genetic variation in this region, we genotyped 79 single nucleotide polymorphisms (SNPs) in the 17q12 region harboring HNF1B in 10 272 prostate cancer cases and 9123 controls of European ancestry from 10 case–control studies as part of the Cancer Genetic Markers of Susceptibility (CGEMS) initiative. Ten SNPs were significantly related to prostate cancer risk at a genome-wide significance level of P < 5 × 10−8 with the most significant association with rs4430796 (P = 1.62 × 10−24). However, risk within this first locus was not entirely explained by rs4430796. Although modestly correlated (r2= 0.64), rs7405696 was also associated with risk (P = 9.35 × 10−23) even after adjustment for rs4430769 (P = 0.007). As expected, rs11649743 was related to prostate cancer risk (P = 3.54 × 10−8); however, the association within this second locus was stronger for rs4794758 (P = 4.95 × 10−10), which explained all of the risk observed with rs11649743 when both SNPs were included in the same model (P = 0.32 for rs11649743; P = 0.002 for rs4794758). Sequential conditional analyses indicated that five SNPs (rs4430796, rs7405696, rs4794758, rs1016990 and rs3094509) together comprise the best model for risk in this region. This study demonstrates a complex relationship between variants in the HNF1B region and prostate cancer risk. Further studies are needed to investigate the biological basis of the association of variants in 17q12 with prostate cancer.

Genome-wide association studies have identified prostate cancer susceptibility alleles on chromosome 11q13. As part of the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative, the region flanking the most significant marker, rs10896449, was fine mapped in 10 272 cases and 9123 controls of European origin (10 studies) using 120 common single nucleotide polymorphisms (SNPs) selected by a two-staged tagging strategy using HapMap SNPs. Single-locus analysis identified 18 SNPs below genome-wide significance (P< 10−8) with rs10896449 the most significant (P= 7.94 × 10−19). Multi-locus models that included significant SNPs sequentially identified a second association at rs12793759 [odds ratio (OR) = 1.14, P= 4.76 × 10−5, adjusted P= 0.004] that is independent of rs10896449 and remained significant after adjustment for multiple testing within the region. rs10896438, a proxy of previously reported rs12418451 (r2= 0.96), independent of both rs10896449 and rs12793759 was detected (OR = 1.07, P= 5.92 × 10−3, adjusted P= 0.054). Our observation of a recombination hotspot that separates rs10896438 from rs10896449 and rs12793759, and low linkage disequilibrium (rs10896449–rs12793759, r2= 0.17; rs10896449–rs10896438, r2= 0.10; rs12793759–rs10896438, r2= 0.12) corroborate our finding of three independent signals. By analysis of tagged SNPs across ∼123 kb using next generation sequencing of 63 controls of European origin, 1000 Genome and HapMap data, we observed multiple surrogates for the three independent signals marked by rs10896449 (n= 31), rs10896438 (n= 24) and rs12793759 (n= 8). Our results indicate that a complex architecture underlying the common variants contributing to prostate cancer risk at 11q13. We estimate that at least 63 common variants should be considered in future studies designed to investigate the biological basis of the multiple association signals.

Genome-wide association studies (GWAS) have successfully identified common genetic variants that contribute to breast cancer risk. Discovering additional variants has become difficult, as power to detect variants of weaker effect with present sample sizes is limited. An alternative approach is to look for variants associated with quantitative traits that in turn affect disease risk. As exposure to high circulating estradiol and testosterone, and low sex hormone-binding globulin (SHBG) levels is implicated in breast cancer etiology, we conducted GWAS analyses of plasma estradiol, testosterone, and SHBG to identify new susceptibility alleles. Cancer Genetic Markers of Susceptibility (CGEMS) data from the Nurses’ Health Study (NHS), and Sisters in Breast Cancer Screening data were used to carry out primary meta-analyses among ∼1600 postmenopausal women who were not taking postmenopausal hormones at blood draw. We observed a genome-wide significant association between SHBG levels and rs727428 (joint β = -0.126; joint P = 2.09×10–16), downstream of the SHBG gene. No genome-wide significant associations were observed with estradiol or testosterone levels. Among variants that were suggestively associated with estradiol (P<10–5), several were located at the CYP19A1 gene locus. Overall results were similar in secondary meta-analyses that included ∼900 NHS current postmenopausal hormone users. No variant associated with estradiol, testosterone, or SHBG at P<10–5 was associated with postmenopausal breast cancer risk among CGEMS participants. Our results suggest that the small magnitude of difference in hormone levels associated with common genetic variants is likely insufficient to detectably contribute to breast cancer risk.

Recent genome-wide association studies have identified independent susceptibility loci for prostate cancer (CaP) that could influence risk through interaction with other, possibly undetected, susceptibility loci. We explored evidence of interaction between pairs of 13 known susceptibility loci and single nucleotide polymorphisms (SNPs) across the genome to generate hypotheses about the functionality of CaP susceptibility regions. We used data from Cancer Genetic Markers of Susceptibility: Stage I included 523,841 SNPs in 1175 cases and 1100 controls; Stage II included 27,383 SNPs in an additional 3941 cases and 3964 controls. Power calculations assessed the magnitude of interactions our study is likely to detect. Logistic regression was used with alternative methods that exploit constraints of gene-gene independence between unlinked loci to increase power. Our empirical evaluation demonstrated that an empirical Bayes (EB) technique is powerful and robust to possible violation of the independence assumption. Our EB analysis identified several noteworthy interacting SNP pairs, although none reached genome-wide significance. We highlight a Stage II interaction between the major CaP susceptibility locus in the subregion of 8q24 that contains POU5F1B and an intronic SNP in the transcription factor EPAS1, which has potentially important functional implications for 8q24. Another noteworthy result involves interaction of a known CaP susceptibility marker near the prostate protease genes KLK2 and KLK3 with an intronic SNP in PRXX2. Overall, the interactions we have identified merit follow-up study, particularly the EPAS1 interaction which has implications not only in CaP but also in other epithelial cancers that are associated with the 8q24 locus.

Objective

The arylamine N-acetyltransferase 2 (NAT2) slow acetylation phenotype is an established risk factor for urinary bladder cancer. We previously reported on this risk association using NAT2 phenotypic categories inferred from NAT2 haplotypes based on 7 single nucleotide polymorphisms (SNPs) in a study in Spain. In a subsequent genome-wide scan, we have identified a single common tag SNP (rs1495741) located in the 3′ end of NAT2 that is also associated with bladder cancer risk. The aim of this report is to evaluate the agreement between the common tag SNP and the 7-SNP NAT2 inferred phenotype.

Methods

The agreement between the 7-SNP NAT2 inferred phenotype and the tag SNP, rs1495741, was initially assessed in 2,174 subjects from the Spanish Bladder Cancer Study (SBCS), and confirmed in a subset of subjects from the Main and Vermont component the New England Bladder Cancer Study (NEBCS). We also investigated the association of rs1495741 genotypes with NAT2 catalytic activity in cryopreserved hepatocytes from 154 individuals of European background.

Results

We observed very strong agreement between rs1495741 and the 7-SNP inferred NAT2 phenotype: sensitivity and specificity for the NAT2 slow phenotype was 99% and 95%, respectively. Our findings were replicated in an independent population from the United States. Estimates for the association between NAT2 slow phenotype and bladder cancer risk in the SBCS and its interaction with cigarette smoking were comparable for the 7-SNP inferred NAT2 phenotype and rs1495741. In addition, rs1495741 genotypes were strongly related to NAT2 activity measured in hepatocytes (P<0.0001).

Conclusion

A novel NAT2 tag SNP (rs1495741) predicts with high accuracy the 7- SNP inferred NAT2 phenotype, and thus can be used as a sole marker in pharmacogenetic or epidemiological studies of populations of European background. These findings illustrate the utility of tag SNPs, often employed in genome-wide association studies (GWAS), to identify novel phenotypic markers. Further studies are required to determine the functional implications of this novel SNP and the structure and evolution of the haplotype on which it resides.

Genetic variation on the Y chromosome has not been convincingly implicated in prostate cancer risk. To comprehensively analyze the role of inherited Y chromosome variation in prostate cancer risk in individuals of European ancestry, we genotyped 34 binary Y chromosome markers in 3,995 prostate cancer cases and 3,815 control subjects drawn from four studies. In this set, we identified nominally significant association between a rare haplogroup, E1b1b1c, and prostate cancer in stage I (P = 0.012, OR = 0.51; 95% confidence interval 0.30–0.87). Population substructure of E1b1b1c carriers suggested Ashkenazi Jewish ancestry, prompting a replication phase in individuals of both European and Ashkenazi Jewish ancestry. The association was not significant for prostate cancer overall in studies of either Ashkenazi Jewish (1,686 cases and 1,597 control subjects) or European (686 cases and 734 control subjects) ancestry (Pmeta = 0.078), but a meta-analysis of stage I and II studies revealed a nominally significant association with prostate cancer risk (Pmeta = 0.010, OR = 0.77; 95% confidence interval 0.62–0.94). Comparing haplogroup frequencies between studies, we noted strong similarities between those conducted in the US and France, in which the majority of men carried R1 haplogroups, resembling Northwestern European populations. On the other hand, Finns had a remarkably different haplogroup distribution with a preponderance of N1c and I1 haplogroups. In summary, our results suggest that inherited Y chromosome variation plays a limited role in prostate cancer etiology in European populations but warrant follow-up in additional large and well characterized studies of multiple ethnic backgrounds.

Electronic supplementary material

The online version of this article (doi:10.1007/s00439-012-1139-5) contains supplementary material, which is available to authorized users.

Pathway analysis of genome-wide association studies (GWAS) offer a unique opportunity to collectively evaluate genetic variants with effects that are too small to be detected individually. We applied a pathway analysis to a bladder cancer GWAS containing data from 3,532 cases and 5,120 controls of European background (n = 5 studies). Thirteen hundred and ninety-nine pathways were drawn from five publicly available resources (Biocarta, Kegg, NCI-PID, HumanCyc, and Reactome), and we constructed 22 additional candidate pathways previously hypothesized to be related to bladder cancer. In total, 1421 pathways, 5647 genes and ∼90,000 SNPs were included in our study. Logistic regression model adjusting for age, sex, study, DNA source, and smoking status was used to assess the marginal trend effect of SNPs on bladder cancer risk. Two complementary pathway-based methods (gene-set enrichment analysis [GSEA], and adapted rank-truncated product [ARTP]) were used to assess the enrichment of association signals within each pathway. Eighteen pathways were detected by either GSEA or ARTP at P≤0.01. To minimize false positives, we used the I2 statistic to identify SNPs displaying heterogeneous effects across the five studies. After removing these SNPs, seven pathways (‘Aromatic amine metabolism’ [PGSEA = 0.0100, PARTP = 0.0020], ‘NAD biosynthesis’ [PGSEA = 0.0018, PARTP = 0.0086], ‘NAD salvage’ [PARTP = 0.0068], ‘Clathrin derived vesicle budding’ [PARTP = 0.0018], ‘Lysosome vesicle biogenesis’ [PGSEA = 0.0023, PARTP<0.00012], ’Retrograde neurotrophin signaling’ [PGSEA = 0.00840], and ‘Mitotic metaphase/anaphase transition’ [PGSEA = 0.0040]) remained. These pathways seem to belong to three fundamental cellular processes (metabolic detoxification, mitosis, and clathrin-mediated vesicles). Identification of the aromatic amine metabolism pathway provides support for the ability of this approach to identify pathways with established relevance to bladder carcinogenesis.

We conducted a two-stage genome-wide association study of renal cell carcinoma (RCC) in 3,772 cases and 8,505 controls of European background from 11 studies, and followed up 6 SNPs in three replication studies of 2,198 cases and 4,918 controls. Two loci on the regions of 2p21 and 11q13.3 were associated with RCC susceptibility below genome-wide significance. Two correlated variants (r2 = 0.99 in controls), rs11894252 (P = 1.8×10−8) and rs7579899 (P = 2.3×10−9), map to EPAS1 on 2p21, which encodes hypoxia-inducible- factor-2 alpha, a transcription factor previously implicated in RCC. The second locus, rs7105934, at 11q13, contains no characterized genes (P = 7.8×10−14). In addition, we observed a promising association on 12q24.31 for rs4765623 which maps to the scavenger receptor class B, member 1 (SCARB1) gene (P = 2.6×10−8). Our study reports novel genomic regions associated with RCC risk that may lead to new etiological insights.

A family history of pancreatic cancer has consistently been associated with increased risk of pancreatic cancer. However, uncertainty remains about the strength of this association. Results from previous studies suggest a family history of select cancers (i.e. ovarian, breast, and colorectal) could also be associated, although not as strongly, with increased risk of pancreatic cancer. We examined the association between a family history of five types of cancer (pancreas, prostate, ovarian, breast, and colorectal) and risk of pancreatic cancer using data from a collaborative nested case-control study conducted by the Pancreatic Cancer Cohort Consortium. Cases and controls were from cohort studies from the United States, Europe, and China, and a case-control study from the Mayo Clinic. Analyses of family history of pancreatic cancer included 1,183 cases and 1,205 controls. A family history of pancreatic cancer in a parent, sibling, or child was associated with increased risk of pancreatic cancer (multivariate-adjusted OR = 1.76, 95% CI 1.19–2.61). A family history of prostate cancer was also associated with increased risk (OR = 1.45, 95% CI 1.12–1.89). There were no statistically significant associations with a family history of ovarian cancer (OR = 0.82, 95% CI 0.52–1.31), breast cancer (OR = 1.21, 95% CI 0.97–1.51), or colorectal cancer (OR = 1.17, 95% CI 0.93–1.47). Our results confirm a moderate sized association between a family history of pancreatic cancer and risk of pancreatic cancer and also provide evidence for an association with a family history of prostate cancer worth further study.

Genome-wide scans of nucleotide variation in human subjects are providing an increasing number of replicated associations with complex disease traits. Most of the variants detected have small effects and, collectively, they account for a small fraction of the total genetic variance. Very large sample sizes are required to identify and validate findings. In this situation, even small sources of systematic or random error can cause spurious results or obscure real effects. The need for careful attention to data quality has been appreciated for some time in this field, and a number of strategies for quality control and quality assurance (QC/QA) have been developed. Here we extend these methods and describe a system of QC/QA for genotypic data in genome-wide association studies. This system includes some new approaches that (1) combine analysis of allelic probe intensities and called genotypes to distinguish gender misidentification from sex chromosome aberrations, (2) detect autosomal chromosome aberrations that may affect genotype calling accuracy, (3) infer DNA sample quality from relatedness and allelic intensities, (4) use duplicate concordance to infer SNP quality, (5) detect genotyping artifacts from dependence of Hardy-Weinberg equilibrium (HWE) test p-values on allelic frequency, and (6) demonstrate sensitivity of principal components analysis (PCA) to SNP selection. The methods are illustrated with examples from the ‘Gene Environment Association Studies’ (GENEVA) program. The results suggest several recommendations for QC/QA in the design and execution of genome-wide association studies.

Retinol is one of the most biologically active forms of vitamin A and is hypothesized to influence a wide range of human diseases including asthma, cardiovascular disease, infectious diseases and cancer. We conducted a genome-wide association study of 5006 Caucasian individuals drawn from two cohorts of men: the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. We identified two independent single-nucleotide polymorphisms associated with circulating retinol levels, which are located near the transthyretin (TTR) and retinol binding protein 4 (RBP4) genes which encode major carrier proteins of retinol: rs1667255 (P =2.30× 10−17) and rs10882272 (P =6.04× 10−12). We replicated the association with rs10882272 in RBP4 in independent samples from the Nurses’ Health Study and the Invecchiare in Chianti Study (InCHIANTI) that included 3792 women and 504 men (P =9.49× 10−5), but found no association for retinol with rs1667255 in TTR among women, thus suggesting evidence for gender dimorphism (P-interaction=1.31× 10−5). Discovery of common genetic variants associated with serum retinol levels may provide further insight into the contribution of retinol and other vitamin A compounds to the development of cancer and other complex diseases.

The literature has consistently reported no association between low to moderate alcohol consumption and pancreatic cancer; however, a few studies have shown that high levels of intake may increase risk. Most single studies have limited power to detect associations even in the highest alcohol intake categories or to examine associations by alcohol type. We analyzed these associations using 1,530 pancreatic cancer cases and 1,530 controls from the Pancreatic Cancer Cohort Consortium (PanScan) nested case–control study. Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated using unconditional logistic regression, adjusting for potential confounders. We observed no significant overall association between total alcohol (ethanol) intake and pancreatic cancer risk (OR = 1.38, 95% CI = 0.86–2.23, for 60 or more g/day vs. >0 to <5 g/day). A statistically significant increase in risk was observed among men consuming 45 or more grams of alcohol from liquor per day (OR = 2.23, 95% CI = 1.02–4.87, compared to 0 g/day of alcohol from liquor, P-trend = 0.12), but not among women (OR = 1.35, 95% CI = 0.63–2.87, for 30 or more g/day of alcohol from liquor, compared to none). No associations were noted for wine or beer intake. Overall, no significant increase in risk was observed, but a small effect among heavy drinkers cannot be ruled out.

Background

A recent ovarian cancer genome-wide association study (GWAS) identified a locus on 9p22 associated with reduced ovarian cancer risk. The single nucleotide polymorphism (SNP) markers localize to the BNC2 gene, which has been associated with ovarian development.

Methods

We analyzed the association of 9p22 SNPs with transvaginal ultrasound (TVU) screening results and CA-125 blood levels from participants without ovarian cancer in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO); 1,106 women with adequate ultrasound screening results and available genotyping information were included in the study.

Results

We observed a significantly increased risk of abnormal suspicious TVU results for seven SNPs on 9p22, with odds ratios between 1.68 (95% CI: 1.04–2.72) for rs4961501 and 2.10 (95% CI: 1.31–3.38) for rs12379183. Associations were restricted to abnormal suspicious findings at the first TVU screen. We did not observe an association between 9p22 SNPs and CA-125 levels.

Conclusions

Our findings suggest that 9p22 SNPs, which were found to be associated with decreased risk of ovarian cancer in a recent GWAS, are associated with sonographically detectable ovarian abnormalities. Our results corroborate the relevance of the 9p22 locus for ovarian biology. Further studies are required to understand the complex relationship between screening abnormalities and ovarian carcinogenesis and to evaluate whether this locus can influence the risk stratification of ovarian cancer screening.

Background

Subjects with non-O ABO blood group alleles have increased risk of pancreatic cancer. Glycosyltransferase activity is greater for the A1 versus A2 variant, while O01 and O02 variants are nonfunctioning. We hypothesized: (1) A1 allele would confer greater risk than A2 allele, (2) protective effect of the O allele would be equivalent for O01 and O02 variants, (3) secretor phenotype would modify the association with risk.

Methods

We determined ABO variants and secretor phenotype from single nucleotide polymorphisms in ABO and FUT2 genes in 1533 cases and 1582 controls from 12 prospective cohort studies. Adjusted odds ratios (ORs) for pancreatic cancer were calculated using logistic regression.

Results

An increased risk was observed in participants with A1, but not A2 alleles. Compared to subjects with genotype O/O, genotypes A2/O, A2/A1, A1/O, and A1/A1 had ORs of 0.96 (95% confidence interval [CI], 0.72–1.26), 1.46 (95%CI, 0.98–2.17), 1.48 (95%CI, 1.23–1.78), and 1.71 (95%CI, 1.18–2.47). Risk was similar for O01 and O02 variant O alleles. Compared to O01/O01, the ORs for each additional allele of O02, A1, and A2 were 1.00 (95%CI, 0.87–1.14), 1.38 (95%CI, 1.20–1.58), and 0.96 (95%CI, 0.77–1.20); P-value, O01 versus O02=0.94, A1 versus A2=0.004. Secretor phenotype was not an effect modifier (P-interaction=0.63).

Conclusions

Among participants in a large prospective cohort consortium, ABO allele subtypes corresponding to increased glycosyltransferase activity were associated with increased pancreatic cancer risk.

Impact

These data support the hypothesis that ABO glycosyltransferase activity influences pancreatic cancer risk, rather than actions of other nearby genes on chromosome 9q34.