The 12th International Meeting on Human Genome Variation and Complex Genome Analysis (HGV2011: Berkeley, California, USA, 8th–10th September 2011) was a stimulating workshop where researchers from academia and industry explored the latest progress, challenges, and opportunities in genome variation research. Key themes included progress beyond GWAS, variation in human populations, use of sequence data in medical settings, large-scale sequencing data analysis, and bioinformatics approaches to large datasets.
human variation; GWAS; SNP; medical genomics
Observational studies have found an inverse association between type 2 diabetes (T2D) and prostate cancer (PCa), and genome-wide association studies have found common variants near 3 loci associated with both diseases. The authors examined whether a genetic background that favors T2D is associated with risk of advanced PCa. Data from the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium, a genome-wide association study of 2,782 advanced PCa cases and 4,458 controls, were used to evaluate whether individual single nucleotide polymorphisms or aggregations of these 36 T2D susceptibility loci are associated with PCa. Ten T2D markers near 9 loci (NOTCH2, ADCY5, JAZF1, CDKN2A/B, TCF7L2, KCNQ1, MTNR1B, FTO, and HNF1B) were nominally associated with PCa (P < 0.05); the association for single nucleotide polymorphism rs757210 at the HNF1B locus was significant when multiple comparisons were accounted for (adjusted P = 0.001). Genetic risk scores weighted by the T2D log odds ratio and multilocus kernel tests also indicated a significant relation between T2D variants and PCa risk. A mediation analysis of 9,065 PCa cases and 9,526 controls failed to produce evidence that diabetes mediates the association of the HNF1B locus with PCa risk. These data suggest a shared genetic component between T2D and PCa and add to the evidence for an interrelation between these diseases.
carcinoma; diabetes mellitus, type 2; genetic predisposition to disease; genetics; genome-wide association study; humans; polymorphism, single nucleotide; prostatic neoplasms
We conducted a meta-analysis to identify new loci for testicular germ cell tumor (TGCT) susceptibility. In the discovery phase, 931 affected individuals and 1,975 controls from three genome wide association studies (GWAS) were analyzed. Replication was conducted in six independent sample sets totaling 3,211 affected individuals and 7,591 controls. In the combined analysis, TGCT risk was significantly associated with markers at four novel loci: 4q22.2 in HPGDS (per allele odds ratio (OR) 1.19, 95%CI 1.12–1.26, P = 1.11×10−8); 7p22.3 in MAD1L1 (OR 1.21, 95%CI 1.14–1.29, P = 5.59×10−9); 16q22.3 in RFWD3 (OR 1.26, 95%CI 1.18–1.34, P = 5.15×10−12); and 17q22 (rs9905704; OR 1.27, 95%CI 1.18–1.33; P = 4.32×10−13, and rs7221274; OR 1.20, 95%CI 1.12–1.28 P = 4.04×10−9), a locus which includes TEX14, RAD51C and PPM1E. The new TGCT susceptibility loci contain biologically plausible genes encoding proteins important for male germ cell development, chromosomal segregation and DNA damage response.
Epidemiologic studies have shown consistent associations between obesity and increased thyroid cancer risk, but, to date, no studies have investigated the relationship between thyroid cancer risk and obesity-related single nucleotide polymorphisms (SNPs).
We evaluated 575 tag SNPs in 23 obesity-related gene regions in a case-control study of 341 incident papillary thyroid cancer (PTC) cases and 444 controls of European ancestry. Logistic regression models, adjusted for attained age, year of birth, and sex were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) with SNP genotypes, coded as 0, 1, and 2 and modeled continuously to calculate P-trends.
Nine out of 10 top-ranking SNPs (Ptrend<0.01) were located in the FTO (fat mass and obesity associated) gene region, while the other was located in INSR (insulin receptor). None of the associations were significant after correcting for multiple testing.
Our data do not support an important role of obesity-related genetic polymorphisms in determining the risk of PTC.
Factors other than selected genetic polymorphisms may be responsible for the observed associations between obesity and increased PTC risk.
single nucleotide polymorphisms; case-control study; obesity; body mass index; thyroid neoplasms
There has been a long-standing controversy in epidemiology with regard to an appropriate risk scale for testing interactions between genes (G) and environmental exposure (E ). Although interaction tests based on the logistic model—which approximates the multiplicative risk for rare diseases—have been more widely applied because of its convenience in statistical modeling, interactions under additive risk models have been regarded as closer to true biologic interactions and more useful in intervention-related decision-making processes in public health. It has been well known that exploiting a natural assumption of G-E independence for the underlying population can dramatically increase statistical power for detecting multiplicative interactions in case-control studies. However, the implication of the independence assumption for tests for additive interaction has not been previously investigated. In this article, the authors develop a likelihood ratio test for detecting additive interactions for case-control studies that incorporates the G-E independence assumption. Numerical investigation of power suggests that incorporation of the independence assumption can enhance the efficiency of the test for additive interaction by 2- to 2.5-fold. The authors illustrate their method by applying it to data from a bladder cancer study.
additive risk model; case-control studies; gene-environment independence; gene-environment interaction; multiplicative risk model
Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10−8). More than 70 prostate cancer susceptibility loci, explaining ~30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.
Pulmonary inflammation may contribute to lung cancer etiology. We conducted a broad evaluation of the association of single nucleotide polymorphisms (SNPs) in innate immunity and inflammation pathways with lung cancer risk, and conducted comparisons with a lung cancer genome wide association study (GWAS).
We included 378 lung cancer cases and 450 controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. An Illumina GoldenGate oligonucleotide pool assay was used to genotype 1,429 SNPs. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for each SNP, and p-values for trend were calculated. For statistically significant SNPs (p-trend<0.05), we replicated our results with genotyped or imputed SNPs in the GWAS, and adjusted p-values for multiple testing.
In our PLCO analysis, we observed a significant association between 81 SNPs located in 44 genes and lung cancer (p-trend<0.05). Of these 81 SNPS, there was evidence for confirmation in the GWAS for 10 SNPs. However, after adjusting for multiple comparisons, the only SNP that remained significantly associated with lung cancer in the replication phase was rs4648127 (NFKB1; multiple testing adjusted p-trend=0.02). The CT/TT genotype of NFKB1 was associated with reduced odds of lung cancer in the PLCO study (OR=0.56; 95% CI 0.37–0.86) and the GWAS (OR=0.79; 95% CI 0.69–0.90).
We found a significant association between a variant in the NFKB1 gene and lung cancer risk. Our findings add to evidence implicating inflammation and immunity in lung cancer etiology.
lung cancer; genetics; inflammation; immunity; epidemiology
There is growing evidence linking genetic variations to non–Hodgkin lymphoma (NHL) etiology. To complement ongoing agnostic approaches for identifying susceptibility genes, we evaluated 488 candidate gene regions and their relation to risk for NHL and NHL subtypes.
We genotyped 6,679 tag single nucleotide polymorphisms (SNPs) in 947 cases and 826 population-based controls from a multicenter U.S. case–control study. Gene-level summary of associations were obtained by computing the minimum P value (“minP test”) on the basis of 10,000 permutations. We used logistic regression to evaluate the association between genotypes and haplotypes with NHL. For NHL subtypes, we conducted polytomous multivariate unconditional logistic regression (adjusted for sex, race, age). We calculated P-trends under the codominant model for each SNP.
Fourteen gene regions were associated with NHL (P < 0.01). The most significant SNP associated with NHL maps to the SYK gene (rs2991216, P-trend = 0.00005). The three most significant gene regions were on chromosome 6p21.3 (RING1/RXRB; AIF1; BAT4). Accordingly, SNPs in RING1/RXRB (rs2855429), AIF1 (rs2857597), and BAT4 (rs3115667) were associated with NHL (P-trends ≤ 0.0002) and both diffuse large B-cell and follicular lymphomas (P-trends < 0.05).
Our results suggest potential importance for SYK on chromosome 9 with NHL etiology. Our results further implicate 6p21.3 gene variants, supporting the need for full characterization of this chromosomal region in relation to lymphomagenesis.
Gene variants on chromosome 9 may represent a new region of interesting for NHL etiology. The independence of the reported variants in 6p21.3 from implicated variants (TNF/HLA) supports the need to confirm causal variants in this region
To test the hypothesis that genetic variations in DNA repair genes may modify the association between occupational exposure to solvents and the risk of non-Hodgkin lymphoma (NHL).
A population-based case-control study was conducted in Connecticut women including 518 histologically confirmed incident NHL cases and 597 controls. Unconditional logistic regression models were used to estimate odds ratios (OR) and effect modification from the 30 SNPs in 16 DNA repair genes of the association between solvent exposure and risk of NHL overall and subtypes.
SNPs in MGMT (rs12917) and NBS1 (rs1805794) significantly modified the association between exposure to chlorinated solvents and NHL risk (Pforinteraction = 0.0003 and 0.0048 respectively). After stratified by major NHL histological subtypes, MGMT (rs12917) modified the association between chlorinated solvents and risk of diffuse large B-cell lymphoma (Pforinteraction = 0.0027) and follicular lymphoma (Pforinteraction = 0.0024). A significant interaction was also observed between occupational exposure to benzene and BRCA2 (rs144848) for NHL overall (Pforinteraction = 0.0042).
Our study results suggest that genetic variations in DNA repair genes modify the association between occupational exposure to solvents and risk of NHL.
Non-Hodgkin Lymphoma; Occupational Exposure; Solvents; Single Nucleotide Polymorphism; DNA Repair Genes
Previous studies have examined the association between ABO blood group and ovarian cancer risk, with inconclusive results.
In 8 studies participating in the Ovarian Cancer Association Consortium (OCAC), we determined ABO blood groups and diplotypes by genotyping 3 SNPs in the ABO locus. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in each study using logistic regression; individual study results were combined using random effects meta-analysis.
Compared to blood group O, the A blood group was associated with a modestly increased ovarian cancer risk: (OR: 1.09; 95% CI: 1.01–1.18; p=0.03). In diplotype analysis, the AO, but not the AA diplotype was associated with increased risk (AO: OR: 1.11; 95% CI: 1.01–1.22; p=0.03; AA: OR: 1.03; 95% CI: 0.87–1.21; p=0.76). Neither AB nor the B blood groups were associated with risk. Results were similar across ovarian cancer histologic subtypes.
Consistent with most previous reports, the A blood type was associated modestly with increased ovarian cancer risk in this large analysis of multiple studies of ovarian cancer. Future studies investigating potential biologic mechanisms are warranted.
ovarian cancer; ABO blood group; Ovarian Cancer Association Consortium (OCAC); genetic epidemiology
There is increasing interest in adding common genetic variants
identified through genome wide association studies (GWAS) to breast cancer
risk prediction models. First results from such models showed modest
benefits in terms of risk discrimination. Heterogeneity of breast cancer as
defined by hormone-receptor status has not been considered in this context.
In this study we investigated the predictive capacity of 32 GWAS-detected
common variants for breast cancer risk, alone and in combination with
classical risk factors, and for tumors with different hormone receptor
Material and Methods
Within the Breast and Prostate Cancer Cohort Consortium (BPC3), we
analyzed 6009 invasive breast cancer cases and 7827 matched controls of
European ancestry, with data on classical breast cancer risk factors and 32
common gene variants identified through GWAS. Discriminatory ability with
respect to breast cancer of specific hormone receptor-status was assessed
with the age- and cohort-adjusted concordance statistic
(AUROCa). Absolute risk scores were
calculated with external reference data. Integrated discrimination
improvement (IDI) was used to measure improvements in risk prediction.
We found a small but steady increase in discriminatory ability with
increasing numbers of genetic variants included in the model (difference in
AUROCa going from 2.7 to 4%). Discriminatory ability
for all models varied strongly by hormone receptor status
Discussion and Conclusion
Adding information on common polymorphisms provides small but
statistically significant improvements in the quality of breast cancer risk
prediction models. We consistently observed better performance for receptor
positive cases, but the gain in discriminatory quality is not sufficient for
breast cancer; risk prediction; genetic factors; hormone receptor status
We conducted a genome-wide association study of gastric cancer (GC) and esophageal squamous cell carcinoma (ESCC) in ethnic Chinese subjects in which we genotyped 551,152 single nucleotide polymorphisms (SNPs). We report a combined analysis of 2,240 GC cases, 2,115 ESCC cases, and 3,302 controls drawn from five studies. In logistic regression models adjusted for age, sex, and study, multiple variants at 10q23 had genome-wide significance for GC and ESCC independently. A notable signal was rs2274223, a nonsynonymous SNP located in PLCE1, for GC (P=8.40×1010; per allele odds ratio (OR) = 1.31) and ESCC (P=3.85×10−9; OR = 1.34). The association with GC differed by anatomic subsite. For tumors located in the cardia the association was stronger (P=4.19 × 10−15; OR= 1.57) and for those located in the noncardia stomach it was absent (P=0.44; OR=1.05). Our findings at 10q23 could provide insight into the high incidence rates of both cancers in China.
We report a new model to project the predictive performance of polygenic models based on the number and distribution of effect sizes for the underlying susceptibility alleles and the size of the training dataset. Using estimates of effect-size distribution and heritability derived from current studies, we project that while 45% of the variance of height has been attributed to common tagging Single Nucleotide Polymorphisms (SNP), a model trained on one million people may only explain 33.4% of variance of the trait. Current studies can identify 3.0%, 1.1%, and 7.0%, of the populations who are at two-fold or higher than average risk for Type 2 diabetes, coronary artery disease and prostate cancer, respectively. Tripling of sample sizes could elevate the percentages to 18.8%, 6.1%, and 12.2%, respectively. The utility of future polygenic models will depend on achievable sample sizes, underlying genetic architecture and information on other risk-factors, including family history.
Endometrial cancer is the most common malignancy of the female genital tract in developed countries. To identify genetic variants associated with endometrial cancer risk, we undertook a genome-wide association study involving 1,265 endometrial cancer cases from Australia and the UK and 5,190 controls from the Wellcome Trust Case Control Consortium. Genotype frequencies in cases and controls were compared for 519,655 SNPs. Forty-seven SNPs that showed evidence of association with endometrial cancer in stage 1 were genotyped in 3,957 additional cases and 6,886 controls. We identified an endometrial cancer susceptibility locus close to HNF1B on chromosome 17q (SNP rs4430796: P=7.1×10−10), that is also associated with risk of prostate cancer and is inversely associated with type 2 diabetes.
Copy number variants (CNV) can be called from SNP-arrays; however, few studies have attempted to combine both CNV and SNP calls to test for association with complex diseases. Even when SNPs are located within CNVs, two separate association analyses are necessary, to compare the distribution of bi-allelic genotypes in cases and controls (referred to as SNP-only strategy) and the number of copies of a region (referred to as CNV-only strategy). However, when disease susceptibility is actually associated with allele specific copy-number states, the two strategies may not yield comparable results, raising a series of questions about the optimal analytical approach. We performed simulations of the performance of association testing under different scenarios that varied genotype frequencies and inheritance models. We show that the SNP-only strategy lacks power under most scenarios when the SNP is located within a CNV; frequently it is excluded from analysis as it does not pass quality control metrics either because of an increased rate of missing calls or a departure from fitness for Hardy-Weinberg proportion. The CNV-only strategy also lacks power because the association testing depends on the allele which copy number varies. The combined strategy performs well in most of the scenarios. Hence, we advocate the use of this combined strategy when testing for association with SNPs located within CNVs.
Recent studies have identified common genetic variants that are unequivocally associated with central adiposity, BMI, and/or fasting plasma glucose among individuals of European descent. Our objective was to evaluate these associations in a population of Asian-Indians. We examined 16 single-nucleotide polymorphisms (SNPs) from loci previously linked to waist circumference, BMI, or fasting glucose in 1,129 Asian-Indians from New Delhi and Trivandrum. Trained medical staff measured waist circumference, height, and weight. Fasting plasma glucose was measured from collected blood specimens. Genotype–phenotype associations were evaluated using linear regression, with adjustments for age, gender, religion, and study region. For gene–environment interaction tests, total physical activity (PA) during the past 7 days was assessed by the International Physical Activity Questionnaire (IPAQ). The T allele at the FTO rs3751812 locus was associated with increased waist circumference (per allele effect of +1.58 cm, Ptrend = 0.0015) after Bonferroni adjustment for multiple testing (Padj = 0.04). We also found a nominally statistically significant FTO–PA interaction (Pinteraction = 0.008). Among participants with <81 metabolic equivalent (MET)-h/wk of PA, the rs3751812 variant was associated with increased waist size (+2.68 cm; 95% confidence interval (CI) = 1.24, 4.12), but not among those with 212+ MET-h/wk (−1.79 cm; 95% CI = −4.17, 0.58). No other variant had statistically significant associations, although statistical power was modest. In conclusion, we confirmed that an FTO variant associated with central adiposity in European populations is associated with central adiposity among Asian-Indians and corroborated prior reports indicating that high PA attenuates FTO-related genetic susceptibility to adiposity.
The risk of glioma has consistently been shown to be increased two-fold in relatives of patients with primary brain tumors (PBT). A recent genome-wide linkage study of glioma families provided evidence for a disease locus on 17q12-21.32, with the possibility of four additional risk loci at 6p22.3, 12p13.33-12.1, 17q22-23.2, and 18q23.
To identify the underlying genetic variants responsible for the linkage signals, we compared the genotype frequencies of 5,122 SNPs mapping to these five regions in 88 glioma cases with and 1,100 cases without a family history of PBT (discovery study). An additional series of 84 familial and 903 non-familial cases were used to replicate associations.
In the discovery study, 12 SNPs showed significant associations with family history of PBT (P < 0.001). In the replication study, two of the 12 SNPs were confirmed: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.031) and 17q12-21.32 SPOP rs650461 (P = 0.025). In the combined analysis of discovery and replication studies, the strongest associations were attained at four SNPs: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.0001), SOX5 rs7305773 (P = 0.0001) and STKY1 rs2418087 (P = 0.0003), and 17q12-21.32 SPOP rs6504618 (P = 0.0006). Further, a significant gene-dosage effect was found for increased risk of family history of PBT with these four SNPs in the combined data set (Ptrend < 1.0 ×10−8).
The results support the linkage finding that some loci in the 12p13.33-12.1 and 17q12-q21.32 may contribute to gliomagenesis and suggest potential target genes underscoring linkage signals.
Association; Polymorphisms; Glioma; Family history of primary brain tumor; Linkage analysis
Recent evidence suggests a link between constitutional telomere length (TL) and cancer risk. Previous studies have suggested that longer telomeres were associated with an increased risk of melanoma and larger size and number of nevi. The goal of this study was to examine whether TL modified the risk of melanoma in melanoma-prone families with and without CDKN2A germline mutations.
Materials and Methods
We measured TL in blood DNA in 119 cutaneous malignant melanoma (CMM) cases and 208 unaffected individuals. We also genotyped 13 tagging SNPs in TERT.
We found that longer telomeres were associated with an increased risk of CMM (adjusted OR = 2.81, 95% CI = 1.02–7.72, P = 0.04). The association of longer TL with CMM risk was seen in CDKN2A- cases but not in CDKN2A+ cases. Among CMM cases, the presence of solar injury was associated with shorter telomeres (P = 0.002). One SNP in TERT, rs2735940, was significantly associated with TL (P = 0.002) after Bonferroni correction.
Our findings suggest that TL regulation could be variable by CDKN2A mutation status, sun exposure, and pigmentation phenotype. Therefore, TL measurement alone may not be a good marker for predicting CMM risk.
The epidermal growth factor receptor (EGFR) signaling pathway regulates cell proliferation, differentiation, and survival, and is frequently dysregulated in esophageal and gastric cancers. Few studies have comprehensively examined the association between germline genetic variants in the EGFR pathway and risk of esophageal and gastric cancers. Based on a genome-wide association study in a Han Chinese population, we examined 3443 SNPs in 127 genes in the EGFR pathway for 1942 esophageal squamous cell carcinomas (ESCCs), 1758 gastric cancers (GCs), and 2111 controls. SNP-level analyses were conducted using logistic regression models. We applied the resampling-based adaptive rank truncated product approach to determine the gene- and pathway-level associations. The EGFR pathway was significantly associated with GC risk (P = 2.16×10−3). Gene-level analyses found 10 genes to be associated with GC, including FYN, MAPK8, MAP2K4, GNAI3, MAP2K1, TLN1, PRLR, PLCG2, RPS6KB2, and PIK3R3 (P<0.05). For ESCC, we did not observe a significant pathway-level association (P = 0.72), but gene-level analyses suggested associations between GNAI3, CHRNE, PAK4, WASL, and ITCH, and ESCC (P<0.05). Our data suggest an association between specific genes in the EGFR signaling pathway and risk of GC and ESCC. Further studies are warranted to validate these associations and to investigate underlying mechanisms.
Epithelial ovarian cancer (EOC) has a heritable component that remains to be fully characterized. Most identified common susceptibility variants lie in non-protein-coding sequences. We hypothesized that variants in the 3′ untranslated region at putative microRNA (miRNA) binding sites represent functional targets that influence EOC susceptibility. Here, we evaluate the association between 767 miRNA binding site single nucleotide polymorphisms (miRSNPs) and EOC risk in 18,174 EOC cases and 26,134 controls from 43 studies genotyped through the Collaborative Oncological Gene-environment Study. We identify several miRSNPs associated with invasive serous EOC risk (OR=1.12, P=10−8) mapping to an inversion polymorphism at 17q21.31. Additional genotyping of non-miRSNPs at 17q21.31 reveals stronger signals outside the inversion (P=10−10). Variation at 17q21.31 associates with neurological diseases, and our collaboration is the first to report an association with EOC susceptibility. An integrated molecular analysis in this region provides evidence for ARHGAP27 and PLEKHM1 as candidate EOC susceptibility genes.
We show how to use reports of cancer in family members to discover additional genetic associations or confirm previous findings in genome-wide association (GWA) studies conducted in case-control, cohort, or cross-sectional studies. Our novel family-history-based approach allows economical association studies for multiple cancers, without genotyping of relatives (as required in family studies), follow-up of participants (as required in cohort studies), or oversampling of specific cancer cases, (as required in case-control studies). We empirically evaluate the performance of the proposed family-history-based approach in studying associations with prostate and ovarian cancers, using data from GWA studies previously conducted within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. The family-history-based method may be particularly useful for investigating genetic susceptibility to rare diseases, for which accruing cases may be very difficult, by using disease information from non-genotyped relatives of participants in multiple case-control and cohort studies designed primarily for other purposes.
Follicular lymphoma (FL) has variable progression and survival, and improved identification of patients at high risk for progression would aid in identifying patients most likely to benefit from alternative therapy. In a sample of 244 FL cases identified during a population-based case-control study of non-Hodgkin lymphoma (NHL), we examined 6,679 tag SNPs in 488 gene regions for associations with overall FL survival. Over a median follow-up of 89 months with 65 deaths in this preliminary study, we identified 5 gene regions (BMP7, GALNT12, DUSP2, GADD45B, and ADAM17) that were associated with overall survival from FL. Results did not meet the criteria for statistical significance after adjustment for multiple hypothesis testing. These results, which support a role for host factors in determining the variable progression of FL, serve as an initial examination that can inform future studies of genetic variation and FL survival. However, they require replication in independent populations, as well as assessment in rituximab-treated patients.
follicular lymphoma; genetic variation; survival; tag SNP; case-control study
Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case–control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10−6, 1.6 × 10−5, 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10−5), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H.
pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer.
We examined host genetic factors to identify those more common in individuals whose human papillomavirus (HPV) infections were most likely to persist and progress to cervical intraepithelial neoplasia grade 3 (CIN3) and cancer.
We genotyped 92 single-nucleotide polymorphisms (SNPs) from 49 candidate immune response and DNA repair genes obtained from 469 women with CIN3 or cancer, 390 women with persistent HPV infections (median duration, 25 months), and 452 random control subjects from the 10,049-woman Guanacaste Costa Rica Natural History Study. We calculated odds ratios and 95% confidence intervals (CIs) for the association of SNP and haplotypes in women with CIN3 or cancer and HPV persistence, compared with random control subjects.
A SNP in the Fanconi anemia complementation group A gene (FANCA) (G501S) was associated with increased risk of CIN3 or cancer. The AG and GG genotypes had a 1.3-fold (95% CI, 0.95–1.8-fold) and 1.7-fold (95% CI, 1.1–2.6-fold) increased risk for CIN3 or cancer, respectively (Ptrend = .008; referent, AA). The FANCA haplotype that included G501S also conferred increased risk of CIN3 or cancer, as did a different haplotype that included 2 other FANCA SNPs (G809A and T266A). A SNP in the innate immune gene IRF3 (S427T) was associated with increased risk for HPV persistence (Ptrend = .009).
Our results require replication but support the role of FANCA variants in cervical cancer susceptibility and of IRF3 in HPV persistence.
Relationships are unclear between polymorphisms in genes involved in metabolism and detoxification of various chemicals and papillary thyroid cancer (PTC) risk as well as their potential modification by alcohol or tobacco intake. We evaluated associations between 1647 tagging single nucleotide polymorphisms (SNPs) in 132 candidate genes/regions involved in metabolism of exogenous and endogenous compounds (Phase I/II, oxidative stress, and metal binding pathways) and PTC risk in 344 PTC cases and 452 controls. For 15 selected regions and their respective SNPs, we also assessed interaction with alcohol and tobacco use. Logistic regression models were used to evaluate the main effect of SNPs (Ptrend) and interaction with alcohol/tobacco intake. Gene- and pathway-level associations and interactions (Pgene interaction) were evaluated by combining Ptrend values using the adaptive rank-truncated product method. While we found associations between PTC risk and nine SNPs (Ptrend≤0.01) and seven genes/regions (Pregion<0.05), none remained significant after correction for the false discovery rate. We found a significant interaction between UGT2B7 and NAT1 genes and alcohol intake (Pgene interaction=0.01 and 0.02 respectively) and between the CYP26B1 gene and tobacco intake (Pgene interaction=0.02). Our results are suggestive of interaction between the genetic polymorphisms in several detoxification genes and alcohol or tobacco intake on risk of PTC. Larger studies with improved exposure assessment should address potential modification of PTC risk by alcohol and tobacco intake to confirm or refute our findings.