Populations in north central China are at high risk for gastric cancers (GC), and altered FAS-mediated cell signaling and/or apoptosis may contribute to this risk. We examined the association of 554 single nucleotide polymorphisms (SNPs) in 53 Fas signaling-related genes using a pathway-based approach in 1758 GC cases (1126 gastric cardia adenocarcinomas (GCA) and 632 gastric noncardia adenocarcinomas (GNCA)), and 2111 controls from a genome-wide association study (GWAS) of GC in ethnic Chinese. SNP associations with risk of overall GC, GCA and GNCA were evaluated using unconditional logistic regressions controlling for age, sex and study. Gene- and pathway-based associations were tested using the adaptive rank-truncated product (ARTP) method. Statistical significance was evaluated empirically by permutation. Significant pathway-based associations were observed for Fas signaling with risk of overall GC (P = 5.5E-04) and GCA (P = 6.3E-03), but not GNCA (P = 8.1E-02). Among examined genes in the Fas signaling pathway, MAP2K4, FAF1, MAPK8, CASP10, CASP8, CFLAR, MAP2K1, CAP8AP2, PAK2 and IKBKB were associated with risk of GC (nominal P < 0.05), and FAF1 and MAPK8 were significantly associated with risk of both GCA and GNCA (nominal P < 0.05). Our examination of genetic variation in the Fas signaling pathway is consistent with an association of altered Fas signaling and/or apoptosis with risk of GC. As one of the first attempts to investigate a pathway-level association, our results suggest that these genes and the Fas signaling pathway warrant further evaluation in relation to GC risk in other populations.
Gastric cancer; gastric cardia; gastric noncardia; Fas signaling; genetic variants; GWAS; single nucleotide polymorphisms; pathway genes
We conducted imputation to the 1000 Genomes Project of four genome-wide association studies of lung cancer in populations of European ancestry (11,348 cases and 15,861 controls) and genotyped an additional 10,246 cases and 38,295 controls for follow-up. We identified large-effect genome-wide associations for squamous lung cancer with the rare variants of BRCA2-K3326X (rs11571833; odds ratio [OR]=2.47, P=4.74×10−20) and of CHEK2-I157T (rs17879961; OR=0.38 P=1.27×10−13). We also showed an association between common variation at 3q28 (TP63; rs13314271; OR=1.13, P=7.22×10−10) and lung adenocarcinoma previously only reported in Asians. These findings provide further evidence for inherited genetic susceptibility to lung cancer and its biological basis. Additionally, our analysis demonstrates that imputation can identify rare disease-causing variants having substantive effects on cancer risk from pre-existing GWAS data.
The genetic regulation of the human epigenome is not fully appreciated. Here we describe the effects of genetic variants on the DNA methylome in human lung based on methylation-quantitative trait loci (meQTL) analyses. We report 34,304 cis- and 585 trans-meQTLs, a genetic-epigenetic interaction of surprising magnitude, including a regulatory hotspot. These findings are replicated in both breast and kidney tissues and show distinct patterns: cis-meQTLs mostly localize to CpG sites outside of genes, promoters, and CpG islands (CGIs), while trans-meQTLs are over-represented in promoter CGIs. meQTL SNPs are enriched in CTCF binding sites, DNaseI hypersensitivity regions and histone marks. Importantly, 4 of the 5 established lung cancer risk loci in European ancestry are cis-meQTLs and, in aggregate, cis-meQTLs are enriched for lung cancer risk in a genome-wide analysis of 11,587 subjects. Thus, inherited genetic variation may affect lung carcinogenesis by regulating the human methylome.
Dysplastic nevi (DN) is a strong risk factor for cutaneous malignant melanoma (CMM), and it frequently occurs in melanoma-prone families. To identify genetic variants for DN, we genotyped 677 tagSNPs in 38 melanoma candidate genes that are involved in pigmentation, DNA repair, cell cycle control, and melanocyte proliferation pathways in a total of 504 individuals (310 with DN, 194 without DN) from 53 melanoma-prone families (23 CDKN2A mutation positive and 30 negative). Conditional logistic regression, conditioning on families, was used to estimate the association between DN and each SNP separately, adjusted for age, sex, CMM and CDKN2A status. P-values for SNPs in the same gene were combined to yield gene-specific p-values. Two genes, CDK6 and XRCC1, were significantly associated with DN after Bonferroni correction for multiple testing (P=0.0001 and 0.00025, respectively), whereas neither gene was significantly associated with CMM. Associations for CDK6 SNPs were stronger in CDKN2A mutation positive families (rs2079147, Pinteraction=0.0033), whereas XRCC1 SNPs had similar effects in mutation-positive and negative families. The association for one of the associated SNPs in XRCC1 (rs25487) was replicated in two independent datasets (random effect meta-analysis: P<0.0001). Our findings suggest that some genetic variants may contribute to DN risk independently of their association with CMM in melanoma-prone families.
The DNA repair pathways help to maintain genomic integrity and therefore genetic variation in the pathways could affect the propensity to develop cancer. Selected germline single nucleotide polymorphisms (SNPs) in the pathways have been associated with esophageal cancer and gastric cancer (GC) but few studies have comprehensively examined the pathway genes. We aimed to investigate associations between DNA repair pathway genes and risk of esophageal squamous cell carcinoma (ESCC) and GC, using data from a genome-wide association study in a Han Chinese population where ESCC and GC are the predominant cancers. In sum, 1942 ESCC cases, 1758 GC cases and 2111 controls from the Shanxi Upper Gastrointestinal Cancer Genetics Project (discovery set) and the Linxian Nutrition Intervention Trials (replication set) were genotyped for 1675 SNPs in 170 DNA repair-related genes. Logistic regression models were applied to evaluate SNP-level associations. Gene- and pathway-level associations were determined using the resampling-based adaptive rank-truncated product approach. The DNA repair pathways overall were significantly associated with risk of ESCC (P = 6.37 × 10−
4), but not with GC (P = 0.20). The most significant gene in ESCC was CHEK2 (P = 2.00 × 10−
6) and in GC was CLK2 (P = 3.02 × 10−
4). We observed several other genes significantly associated with either ESCC (SMUG1, TDG, TP53, GTF2H3, FEN1, POLQ, HEL308, RAD54B, MPG, FANCE and BRCA1) or GC risk (MRE11A, RAD54L and POLE) (P < 0.05). We provide evidence for an association between specific genes in the DNA repair pathways and the risk of ESCC and GC. Further studies are warranted to validate these associations and to investigate underlying mechanisms.
Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate–increasing and heart rate–decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.
With recent advances in sequencing, genotyping arrays, and imputation, GWAS now aim to identify associations with rare and uncommon genetic variants. Here, we describe and evaluate a class of statistics, generalized score statistics (GSS), that can test for an association between a group of genetic variants and a phenotype. GSS are a simple weighted sum of single-variant statistics and their cross-products. We show that the majority of statistics currently used to detect associations with rare variants are equivalent to choosing a specific set of weights within this framework. We then evaluate the power of various weighting schemes as a function of variant characteristics, such as MAF, the proportion associated with the phenotype, and the direction of effect. Ultimately, we find that two classical tests are robust and powerful, but details are provided as to when other GSS may perform favorably. The software package CRaVe is available at our website (http://dceg.cancer.gov/bb/tools/crave).
rare variants; score test; GWAS; association test
In China, esophageal cancer is the fourth leading cause of cancer death where essentially all cases are histologically esophageal squamous cell carcinoma (ESCC), in contrast to esophageal adenocarcinoma in the West. Globally, ESCC is 2.4 times more common among men than women and recently it has been suggested that sex hormones may be associated with the risk of ESCC. We examined the association between genetic variants in sex hormone metabolic genes and ESCC risk in a population from north central China with high-incidence rates. A total of 1026 ESCC cases and 1452 controls were genotyped for 797 unique tag single-nucleotide polymorphisms (SNPs) in 51 sex hormone metabolic genes. SNP-, gene- and pathway-based associations with ESCC risk were evaluated using unconditional logistic regression adjusted for age, sex and geographical location and the adaptive rank truncated product (ARTP) method. Statistical significance was determined through use of permutation for pathway- and gene-based associations. No associations were observed for the overall sex hormone metabolic pathway (P = 0.14) or subpathways (androgen synthesis: P = 0.30, estrogen synthesis: P = 0.15 and estrogen removal: P = 0.19) with risk of ESCC. However, six individual genes (including SULT2B1, CYP1B1, CYP3A7, CYP3A5, SHBG and CYP11A1) were significantly associated with ESCC risk (P < 0.05). Our examination of genetic variation in the sex hormone metabolic pathway is consistent with a potential association with risk of ESCC. These positive findings warrant further evaluation in relation to ESCC risk and replication in other populations.
Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotype.
CHRNA5; CHRNA3; CHRNB4; meta-analysis; nicotine; smoke
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.
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.
Recent studies have shown an association between cigarettes per day (CPD) and a nonsynonymous single-nucleotide polymorphism in CHRNA5, rs16969968.
To determine whether the association between rs16969968 and smoking is modified by age at onset of regular smoking.
Available genetic studies containing measures of CPD and the genotype of rs16969968 or its proxy.
Uniform statistical analysis scripts were run locally. Starting with 94 050 ever-smokers from 43 studies, we extracted the heavy smokers (CPD >20) and light smokers (CPD ≤10) with age-at-onset information, reducing the sample size to 33 348. Each study was stratified into early-onset smokers (age at onset ≤16 years) and late-onset smokers (age at onset >16 years), and a logistic regression of heavy vs light smoking with the rs16969968 genotype was computed for each stratum. Meta-analysis was performed within each age-at-onset stratum.
Individuals with 1 risk allele at rs16969968 who were early-onset smokers were significantly more likely to be heavy smokers in adulthood (odds ratio [OR]=1.45; 95% CI, 1.36–1.55; n=13 843) than were carriers of the risk allele who were late-onset smokers (OR = 1.27; 95% CI, 1.21–1.33, n = 19 505) (P = .01).
These results highlight an increased genetic vulnerability to smoking in early-onset smokers.
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.
Cutaneous malignant melanoma (CMM) is an etiologically heterogeneous disease with genetic, environmental (sun exposure) and host (pigmentation/nevi) factors, and their interactions contributing to risk. Genetic variants in DNA repair genes may be particularly important since their altered function in response to sun exposure-related DNA damage maybe related to risk for CMM. However, systematic evaluations of genetic variants in DNA repair genes are limited, particularly in high-risk families.
We comprehensively analyzed DNA repair gene polymorphisms and CMM risk in melanoma-prone families with/without CDKN2A mutations. A total of 586 individuals (183 CMM) from 53 families (23 CDKN2A (+), 30 CDKN2A (−)) were genotyped for 2964 tagSNPs in 131 DNA repair genes. Conditional logistic regression, conditioning on families, was used to estimate trend p-values, odds ratios and 95% confidence intervals for the association between CMM and each SNP separately, adjusted for age and sex. P-values for SNPs in the same gene were combined to yield gene specific p-values. Two genes, POLN and PRKDC, were significantly associated with melanoma after Bonferroni correction for multiple testing (p=0.0003 and 0.00035, respectively). DCLRE1B showed suggestive association (p=0.0006). 28~56% of genotyped SNPs in these genes had single SNP p<0.05. The most significant SNPs in POLN and PRKDC had similar effects in CDKN2A (+) and CDKN2A (−) families. Our finding suggests that polymorphisms in DNA repair genes, POLN and PRKDC, were associated with increased melanoma risk in melanoma families with and without CDKN2A mutations.
Genome-wide association studies have identified susceptibility loci for esophageal squamous cell carcinoma (ESCC). We conducted a meta-analysis of all single-nucleotide polymorphisms (SNPs) that showed nominally significant P-values in two previously published genome-wide scans that included a total of 2961 ESCC cases and 3400 controls. The meta-analysis revealed five SNPs at 2q33 with P< 5 × 10−8, and the strongest signal was rs13016963, with a combined odds ratio (95% confidence interval) of 1.29 (1.19–1.40) and P= 7.63 × 10−10. An imputation analysis of 4304 SNPs at 2q33 suggested a single association signal, and the strongest imputed SNP associations were similar to those from the genotyped SNPs. We conducted an ancestral recombination graph analysis with 53 SNPs to identify one or more haplotypes that harbor the variants directly responsible for the detected association signal. This showed that the five SNPs exist in a single haplotype along with 45 imputed SNPs in strong linkage disequilibrium, and the strongest candidate was rs10201587, one of the genotyped SNPs. Our meta-analysis found genome-wide significant SNPs at 2q33 that map to the CASP8/ALS2CR12/TRAK2 gene region. Variants in CASP8 have been extensively studied across a spectrum of cancers with mixed results. The locus we identified appears to be distinct from the widely studied rs3834129 and rs1045485 SNPs in CASP8. Future studies of esophageal and other cancers should focus on comprehensive sequencing of this 2q33 locus and functional analysis of rs13016963 and rs10201587 and other strongly correlated variants.
Accumulating evidence suggests that alterations in immune function may be important in the etiology of papillary thyroid cancer (PTC). To identify genetic markers in immune-related pathways, we evaluated 3,985 tag single nucleotide polymorphisms (SNPs) in 230 candidate gene regions (adhesion-extravasation-migration, arachidonic acid metabolism/eicosanoid signaling, complement and coagulation cascade, cytokine signaling, innate pathogen detection and antimicrobials, leukocyte signaling, TNF/NF-kB pathway or other) in a case-control study of 344 PTC cases and 452 controls. We used logistic regression models to estimate odds ratios (OR) and calculate one degree of freedom P values of linear trend (PSNP-trend) for the association between genotype (common homozygous, heterozygous, variant homozygous) and risk of PTC. To correct for multiple comparisons, we applied the false discovery rate method (FDR). Gene region- and pathway-level associations (PRegion and PPathway) were assessed by combining individual PSNP-trend values using the adaptive rank truncated product method. Two SNPs (rs6115, rs6112) in the SERPINA5 gene were significantly associated with risk of PTC (PSNP-FDR/PSNP-trend = 0.02/6×10−6 and PSNP-FDR/PSNP-trend = 0.04/2×10−5, respectively). These associations were independent of a history of autoimmune thyroiditis (OR = 6.4; 95% confidence interval: 3.0–13.4). At the gene region level, SERPINA5 was suggestively associated with risk of PTC (PRegion-FDR/PRegion = 0.07/0.0003). Overall, the complement and coagulation cascade pathway was the most significant pathway (PPathway = 0.02) associated with PTC risk largely due to the strong effect of SERPINA5. Our results require replication but suggest that the SERPINA5 gene, which codes for the protein C inhibitor involved in many biological processes including inflammation, may be a new susceptibility locus for PTC.
Hormonal differences are hypothesized to contribute to the approximately ≥2-fold higher thyroid cancer incidence rates among women compared with men worldwide. Although thyroid cancer cells express estrogen receptors and estrogen has a proliferative effect on papillary thyroid cancer (PTC) cells in vitro, epidemiologic studies have not found clear associations between thyroid cancer and female hormonal factors. We hypothesized that polymorphic variation in hormone pathway genes is associated with the risk of developing papillary thyroid cancer.
We evaluated the association between PTC and 1151 tag single nucleotide polymorphisms (SNPs) in 58 candidate gene regions involved in sex hormone synthesis and metabolism, gonadotropins, and prolactin in a case-control study of 344 PTC cases and 452 controls, frequency matched on age and sex. Odds ratios and p-values for the linear trend for the association between each SNP genotype and PTC risk were estimated using unconditional logistic regression. SNPs in the same gene region or pathway were aggregated using adaptive rank-truncated product methods to obtain gene region-specific or pathway-specific p-values. To account for multiple comparisons, we applied the false discovery rate method.
Seven SNPs had p-values for linear trend <0.01, including four in the CYP19A1 gene, but none of the SNPs remained significant after correction for multiple comparisons. Results were similar when restricting the dataset to women. p-values for examined gene regions and for all genes combined were ≥0.09.
Based on these results, SNPs in selected hormone pathway genes do not appear to be strongly related to PTC risk. This observation is in accord with the lack of consistent associations between hormonal factors and PTC risk in epidemiologic studies.
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.
Cancer is an important cause of morbidity in the elderly, and many medical conditions and treatments influence cancer risk. The Surveillance, Epidemiology, and End Results (SEER)-Medicare database can be used to conduct population-based case-control studies that elucidate the etiology of cancer among the US elderly. SEER-Medicare links data on malignancies ascertained through SEER cancer registries to claims from Medicare, the US government insurance program for people over age 65 years. Under one approach described herein, elderly cancer cases are ascertained from SEER data (1987–2005). Matched controls are selected from a 5% random sample of Medicare beneficiaries. Risk factors of interest, including medical conditions and procedures, are identified by using linked Medicare claims. Strengths of this design include the ready availability of data, representative sampling from the US elderly population, and large sample size (e.g., under one scenario: 1,176,950 cases, including 221,389 prostate cancers, 185,853 lung cancers, 138,041 breast cancers, and 124,442 colorectal cancers; and 100,000 control subjects). Limitations reflect challenges in exposure assessment related to Medicare claims: restricted range of evaluable risk factors, short time before diagnosis/selection for ascertainment, and inaccuracies in claims. With awareness of limitations, investigators have in SEER-Medicare data a valuable resource for epidemiologic research on cancer etiology.
aged; case-control studies; data collection; epidemiologic methods; Medicare; neoplasms; risk factors; SEER Program
DNA damage is an important mechanism in carcinogenesis, so genes related to maintaining genomic integrity may influence papillary thyroid cancer (PTC) risk. Candidate gene studies targeting some of these genes have identified only a few polymorphisms associated with risk of PTC. Here, we expanded the scope of previous candidate studies by increasing the number and coverage of genes related to maintenance of genomic integrity. We evaluated 5077 tag single-nucleotide polymorphisms (SNPs) from 340 candidate gene regions hypothesized to be involved in DNA repair, epigenetics, tumor suppression, apoptosis, telomere function and cell cycle control and signaling pathways in a case–control study of 344 PTC cases and 452 matched controls. We estimated odds ratios for associations of single SNPs with PTC risk and combined P values for SNPs in the same gene region or pathway to obtain gene region-specific or pathway-specific P values using adaptive rank-truncated product methods. Nine SNPs had P values <0.0005, three of which were in HDAC4 and were inversely related to PTC risk. After multiple comparisons adjustment, no SNPs remained associated with PTC risk. Seven gene regions were associated with PTC risk at P < 0.01, including HUS1, ALKBH3, HDAC4, BAK1, FAF1_CDKN2C, DACT3 and FZD6. Our results suggest a possible role of genes involved in maintenance of genomic integrity in relation to risk of PTC.
While lung cancer is largely caused by tobacco smoking, inherited genetic factors play a role in its etiology. Genome-wide association studies (GWAS) in Europeans have robustly demonstrated only three polymorphic variations influencing lung cancer risk. Tumor heterogeneity may have hampered the detection of association signal when all lung cancer subtypes were analyzed together. In a GWAS of 5,355 European smoking lung cancer cases and 4,344 smoking controls, we conducted a pathway-based analysis in lung cancer histologic subtypes with 19,082 SNPs mapping to 917 genes in the HuGE-defined “inflammation” pathway. We identified a susceptibility locus for squamous cell lung carcinoma (SQ) at 12p13.33 (RAD52, rs6489769), and replicated the association in three independent samples totaling 3,359 SQ cases and 9,100 controls (odds ratio=1.20, Pcombined=2.3×10−8).
The combination of pathway-based approaches and information on disease specific subtypes can improve the identification of cancer susceptibility loci in heterogeneous diseases.
Lung cancer; histology; squamous cell carcinoma; pathway analysis; RAD52
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.
An important follow-up step after genetic markers are found to be associated with a disease outcome is a more detailed analysis investigating how the implicated gene or chromosomal region and an established environment risk factor interact to influence the disease risk. The standard approach to this study of gene–environment interaction considers one genetic marker at a time and therefore could misrepresent and underestimate the genetic contribution to the joint effect when one or more functional loci, some of which might not be genotyped, exist in the region and interact with the environment risk factor in a complex way. We develop a more global approach based on a Bayesian model that uses a latent genetic profile variable to capture all of the genetic variation in the entire targeted region and allows the environment effect to vary across different genetic profile categories. We also propose a resampling-based test derived from the developed Bayesian model for the detection of gene–environment interaction. Using data collected in the Environment and Genetics in Lung Cancer Etiology (EAGLE) study, we apply the Bayesian model to evaluate the joint effect of smoking intensity and genetic variants in the 15q25.1 region, which contains a cluster of nicotinic acetylcholine receptor genes and has been shown to be associated with both lung cancer and smoking behavior. We find evidence for gene–environment interaction (P-value = 0.016), with the smoking effect appearing to be stronger in subjects with a genetic profile associated with a higher lung cancer risk; the conventional test of gene–environment interaction based on the single-marker approach is far from significant.
Many common diseases result from a complex interplay of genetic and environmental risk factors. It is important to study the potential genetic and environmental risk factors jointly in order to achieve a better understanding of the mechanisms underlying disease development. The standard single-marker approach that studies the environmental risk factor and one genetic marker at a time could misrepresent the gene–environment interaction, as the single genetic marker might not be an appropriate surrogate for the underlying genetic functioning polymorphisms. We propose a method to look at gene–environment interaction at the gene/region level by integrating information observed on multiple genetic markers within the selected gene/region with measures of environmental exposure. Using data collected in the Environment and Genetics in Lung Cancer Etiology (EAGLE) study, we apply the proposed model to evaluate the joint effect of smoking intensity and genetic variants in the 15q25.1 region and find evidence for gene–environment interaction (P-value = 0.016), with the smoking effect varying according to a subject's genetic profile.
The presence of pancreatic cancer (PC) in melanoma-prone families has been consistently associated with an increased frequency of CDKN2A mutations, the major high-risk susceptibility gene identified for melanoma. However, the precise relationship between CDKN2A, melanoma and PC remains unknown. We evaluated a recently identified PC susceptibility gene PALB2 using both sequencing and tagging to determine whether PALB2 might explain part of the relationship between CDKN2A, melanoma, and PC. No disease-related mutations were identified from sequencing PALB2 in multiple pancreatic cancer patients or other mutation carrier relatives of PC patients from the eight melanoma-prone families with CDKN2A mutations and PC. In addition, no significant associations were observed between 11 PALB2 tagging SNPs and melanoma risk in 23 melanoma-prone families with CDKN2A mutations or the subset of 11 families with PC or PC-related CDKN2A mutations. The results suggested that PALB2 does not explain the relationship between CDKN2A, melanoma, and pancreatic cancer in these melanoma-prone families.
CDKN2A; PALB2; familial melanoma; pancreatic cancer; germline mutation