Design and Reporting Considerations for Genetic Screening Tests.

Testing asymptomatic individuals for unsuspected conditions is not new to the medical and public health communities. Protocols to develop screening tests are well established. However, the application of screening principles to inherited diseases presents unique challenges. Unlike most screening tests, the natural history and disease prevalence of most rare inherited diseases in an unselected population are unknown. It is difficult or impossible to obtain a truth set cohort for clinical validation studies. As a result, it is not possible to accurately calculate clinical positive and negative predictive values for likely pathogenic variants, which are commonly returned in genetic screening assays. In addition, many of the genetic conditions included in screening panels do not have clinical confirmatory tests. All these elements are typically required to justify the development of a screening test, according to the World Health Organization screening principles. Nevertheless, as the cost of DNA sequencing continues to fall, more individuals are opting to undergo genomic testing in the absence of a clinical indication. Despite the challenges, reasonable estimates can be deduced and used to inform test design strategies. Herein, we review basic test design principles and apply them to genetic screening.

Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits.

The growth hormone/insulin-like growth factor (IGF) axis can be manipulated in animal models to promote longevity, and IGF-related proteins including IGF-I and IGF-binding protein-3 (IGFBP-3) have also been implicated in risk of human diseases including cardiovascular diseases, diabetes, and cancer. Through genomewide association study of up to 30 884 adults of European ancestry from 21 studies, we confirmed and extended the list of previously identified loci associated with circulating IGF-I and IGFBP-3 concentrations (IGF1, IGFBP3, GCKR, TNS3, GHSR, FOXO3, ASXL2, NUBP2/IGFALS, SORCS2, and CELSR2). Significant sex interactions, which were characterized by different genotype-phenotype associations between men and women, were found only for associations of IGFBP-3 concentrations with SNPs at the loci IGFBP3 and SORCS2. Analyses of SNPs, gene expression, and protein levels suggested that interplay between IGFBP3 and genes within the NUBP2 locus (IGFALS and HAGH) may affect circulating IGF-I and IGFBP-3 concentrations. The IGF-I-decreasing allele of SNP rs934073, which is an eQTL of ASXL2, was associated with lower adiposity and higher likelihood of survival beyond 90 years. The known longevity-associated variant rs2153960 (FOXO3) was observed to be a genomewide significant SNP for IGF-I concentrations. Bioinformatics analysis suggested enrichment of putative regulatory elements among these IGF-I- and IGFBP-3-associated loci, particularly of rs646776 at CELSR2. In conclusion, this study identified several loci associated with circulating IGF-I and IGFBP-3 concentrations and provides clues to the potential role of the IGF axis in mediating effects of known (FOXO3) and novel (ASXL2) longevity-associated loci.

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome.

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.

Mosaic loss of chromosome Y is associated with common variation near TCL1A.

Mosaic loss of chromosome Y (mLOY) leading to gonosomal XY/XO commonly occurs during aging, particularly in smokers. We investigated whether mLOY was associated with non-hematological cancer in three prospective cohorts (8,679 cancer cases and 5,110 cancer-free controls) and genetic susceptibility to mLOY. Overall, mLOY was observed in 7% of men, and its prevalence increased with age (per-year odds ratio (OR) = 1.13, 95% confidence interval (CI) = 1.12-1.15; P < 2 × 10(-16)), reaching 18.7% among men over 80 years old. mLOY was associated with current smoking (OR = 2.35, 95% CI = 1.82-3.03; P = 5.55 × 10(-11)), but the association weakened with years after cessation. mLOY was not consistently associated with overall or specific cancer risk (for example, bladder, lung or prostate cancer) nor with cancer survival after diagnosis (multivariate-adjusted hazard ratio = 0.87, 95% CI = 0.73-1.04; P = 0.12). In a genome-wide association study, we observed the first example of a common susceptibility locus for genetic mosaicism, specifically mLOY, which maps to TCL1A at 14q32.13, marked by rs2887399 (OR = 1.55, 95% CI = 1.36-1.78; P = 1.37 × 10(-10)).

A Systematic Comparison of Traditional and Multigene Panel Testing for Hereditary Breast and Ovarian Cancer Genes in More Than 1000 Patients.

Gene panels for hereditary breast and ovarian cancer risk assessment are gaining acceptance, even though the clinical utility of these panels is not yet fully defined. Technical questions remain, however, about the performance and clinical interpretation of gene panels in comparison with traditional tests. We tested 1105 individuals using a 29-gene next-generation sequencing panel and observed 100% analytical concordance with traditional and reference data on >750 comparable variants. These 750 variants included technically challenging classes of sequence and copy number variation that together represent a significant fraction (13.4%) of the pathogenic variants observed. For BRCA1 and BRCA2, we also compared variant interpretations in traditional reports to those produced using only non-proprietary resources and following criteria based on recent (2015) guidelines. We observed 99.8% net report concordance, albeit with a slightly higher variant of uncertain significance rate. In 4.5% of BRCA-negative cases, we uncovered pathogenic variants in other genes, which appear clinically relevant. Previously unseen variants requiring interpretation accumulated rapidly, even after 1000 individuals had been tested. We conclude that next-generation sequencing panel testing can provide results highly comparable to traditional testing and can uncover potentially actionable findings that may be otherwise missed. Challenges remain for the broad adoption of panel tests, some of which will be addressed by the accumulation of large public databases of annotated clinical variants.

Characterization of large structural genetic mosaicism in human autosomes.

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.

Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia.

Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P=1.22×10(-14)), 18q21.33 (BCL2, P=7.76×10(-11)), 11p15.5 (C11orf21, P=2.15×10(-10)), 4q25 (LEF1, P=4.24×10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P=2.50×10(-9)), 9p21.3 (CDKN2B-AS1, P=1.27×10(-8)), 18q21.32 (PMAIP1, P=2.51×10(-8)), 15q15.1 (BMF, P=2.71×10(-10)) and 2p22.2 (QPCT, P=1.68×10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P=2.08×10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P=5.40×10(-8)) and 5p15.33 (TERT, P=1.92×10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.

Meta-analysis identifies four new loci associated with testicular germ cell tumor.

We conducted a meta-analysis to identify new susceptibility loci for testicular germ cell tumor (TGCT). In the discovery phase, we analyzed 931 affected individuals and 1,975 controls from 3 genome-wide association studies (GWAS). We conducted replication in 6 independent sample sets comprising 3,211 affected individuals and 7,591 controls. In the combined analysis, risk of TGCT was significantly associated with markers at four previously unreported loci: 4q22.2 in HPGDS (per-allele odds ratio (OR) = 1.19, 95% confidence interval (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 that includes TEX14, RAD51C and PPM1E. These new TGCT susceptibility loci contain biologically plausible genes encoding proteins important for male germ cell development, chromosomal segregation and the DNA damage response.

Common genetic polymorphisms modify the effect of smoking on absolute risk of bladder cancer.

Bladder cancer results from the combined effects of environmental and genetic factors, smoking being the strongest risk factor. Evaluating absolute risks resulting from the joint effects of smoking and genetic factors is critical to assess the public health relevance of genetic information. Analyses included up to 3,942 cases and 5,680 controls of European background in seven studies. We tested for multiplicative and additive interactions between smoking and 12 susceptibility loci, individually and combined as a polygenic risk score (PRS). Thirty-year absolute risks and risk differences by levels of the PRS were estimated for U.S. males aged 50 years. Six of 12 variants showed significant additive gene-environment interactions, most notably NAT2 (P = 7 × 10(-4)) and UGT1A6 (P = 8 × 10(-4)). The 30-year absolute risk of bladder cancer in U.S. males was 6.2% for all current smokers. This risk ranged from 2.9% for current smokers in the lowest quartile of the PRS to 9.9% for current smokers in the upper quartile. Risk difference estimates indicated that 8,200 cases would be prevented if elimination of smoking occurred in 100,000 men in the upper PRS quartile compared with 2,000 cases prevented by a similar effort in the lowest PRS quartile (P(additive) = 1 × 10(-4)). Thus, the potential impact of eliminating smoking on the number of bladder cancer cases prevented is larger for individuals at higher than lower genetic risk. Our findings could have implications for targeted prevention strategies. However, other smoking-related diseases, as well as practical and ethical considerations, need to be considered before any recommendations could be made.

Testicular germ cell tumor susceptibility associated with the UCK2 locus on chromosome 1q23.

Genome-wide association studies (GWASs) have identified multiple common genetic variants associated with an increased risk of testicular germ cell tumors (TGCTs). A previous GWAS reported a possible TGCT susceptibility locus on chromosome 1q23 in the UCK2 gene, but failed to reach genome-wide significance following replication. We interrogated this region by conducting a meta-analysis of two independent GWASs including a total of 940 TGCT cases and 1559 controls for 122 single-nucleotide polymorphisms (SNPs) on chromosome 1q23 and followed up the most significant SNPs in an additional 2202 TGCT cases and 2386 controls from four case-control studies. We observed genome-wide significant associations for several UCK2 markers, the most significant of which was for rs3790665 (PCombined = 6.0 × 10(-9)). Additional support is provided from an independent familial study of TGCT where a significant over-transmission for rs3790665 with TGCT risk was observed (PFBAT = 2.3 × 10(-3)). Here, we provide substantial evidence for the association between UCK2 genetic variation and TGCT risk.

A resequence analysis of genomic loci on chromosomes 1q32.1, 5p15.33, and 13q22.1 associated with pancreatic cancer risk.

OBJECTIVE: The objective of this study was to fine-map common pancreatic cancer susceptibility regions. METHODS: We conducted targeted Roche-454 resequencing across 428 kb in 3 genomic regions identified in genome-wide association studies (GWAS) of pancreatic cancer, on chromosomes 1q32.1, 5p15.33, and 13q22.1. RESULTS: An analytical pipeline for calling genotypes was developed using HapMap samples sequenced on chr5p15.33. Concordance to 1000 Genomes data for chr5p15.33 was greater than 96%. The concordance for chr1q32.1 and chr13q22.1 with pancreatic cancer GWAS data was greater than 99%. Between 9.2% and 19.0% of variants detected were not present in 1000 Genomes for the respective continental population. The majority of completely novel single-nucleotide polymorphisms (SNPs) were less common (minor allele frequency [MAF], ≤5%) or rare (MAF, ≤2%), illustrating the value of enlarging test sets for discovery of less common variants. Using the data set, we examined haplotype blocks across each region using a tag SNP analysis (r² > 0.8 for MAF of ≥5%) and determined that at least 196, 243, and 63 SNPs are required for fine-mapping chr1q32.1, chr5p15.33, and chr13q22.1, respectively, in European populations. CONCLUSIONS: We have characterized germline variation in 3 regions associated with pancreatic cancer risk and show that targeted resequencing leads to the discovery of novel variants and improves the completeness of germline sequence variants for fine-mapping GWAS susceptibility loci.

Polymorphisms in genes related to one-carbon metabolism are not related to pancreatic cancer in PanScan and PanC4.

PURPOSE: The evidence of a relation between folate intake and one-carbon metabolism (OCM) with pancreatic cancer (PanCa) is inconsistent. In this study, the association between genes and single-nucleotide polymorphisms (SNPs) related to OCM and PanCa was assessed. METHODS: Using biochemical knowledge of the OCM pathway, we identified thirty-seven genes and 834 SNPs to examine in association with PanCa. Our study included 1,408 cases and 1,463 controls nested within twelve cohorts (PanScan). The ten SNPs and five genes with lowest p values (<0.02) were followed up in 2,323 cases and 2,340 controls from eight case-control studies (PanC4) that participated in PanScan2. The correlation of SNPs with metabolite levels was assessed for 649 controls from the European Prospective Investigation into Cancer and Nutrition. RESULTS: When both stages were combined, we observed suggestive associations with PanCa for rs10887710 (MAT1A) (OR 1.13, 95 %CI 1.04-1.23), rs1552462 (SYT9) (OR 1.27, 95 %CI 1.02-1.59), and rs7074891 (CUBN) (OR 1.91, 95 %CI 1.12-3.26). After correcting for multiple comparisons, no significant associations were observed in either the first or second stage. The three suggested SNPs showed no correlations with one-carbon biomarkers. CONCLUSIONS: This is the largest genetic study to date to examine the relation between germline variations in OCM-related genes polymorphisms and the risk of PanCa. Suggestive evidence for an association between polymorphisms and PanCa was observed among the cohort-nested studies, but this did not replicate in the case-control studies. Our results do not strongly support the hypothesis that genes related to OCM play a role in pancreatic carcinogenesis.

Diabetes and risk of pancreatic cancer: a pooled analysis from the pancreatic cancer cohort consortium.

PURPOSE: Diabetes is a suspected risk factor for pancreatic cancer, but questions remain about whether it is a risk factor or a result of the disease. This study prospectively examined the association between diabetes and the risk of pancreatic adenocarcinoma in pooled data from the NCI pancreatic cancer cohort consortium (PanScan). METHODS: The pooled data included 1,621 pancreatic adenocarcinoma cases and 1,719 matched controls from twelve cohorts using a nested case-control study design. Subjects who were diagnosed with diabetes near the time (<2 years) of pancreatic cancer diagnosis were excluded from all analyses. All analyses were adjusted for age, race, gender, study, alcohol use, smoking, BMI, and family history of pancreatic cancer. RESULTS: Self-reported diabetes was associated with a forty percent increased risk of pancreatic cancer (OR = 1.40, 95 % CI: 1.07, 1.84). The association differed by duration of diabetes; risk was highest for those with a duration of 2-8 years (OR = 1.79, 95 % CI: 1.25, 2.55); there was no association for those with 9+ years of diabetes (OR = 1.02, 95 % CI: 0.68, 1.52). CONCLUSIONS: These findings provide support for a relationship between diabetes and pancreatic cancer risk. The absence of association in those with the longest duration of diabetes may reflect hypoinsulinemia and warrants further investigation.

Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia.

To identify common genetic variants that contribute to lung cancer susceptibility, we conducted a multistage genome-wide association study of lung cancer in Asian women who never smoked. We scanned 5,510 never-smoking female lung cancer cases and 4,544 controls drawn from 14 studies from mainland China, South Korea, Japan, Singapore, Taiwan and Hong Kong. We genotyped the most promising variants (associated at P < 5 × 10(-6)) in an additional 1,099 cases and 2,913 controls. We identified three new susceptibility loci at 10q25.2 (rs7086803, P = 3.54 × 10(-18)), 6q22.2 (rs9387478, P = 4.14 × 10(-10)) and 6p21.32 (rs2395185, P = 9.51 × 10(-9)). We also confirmed associations reported for loci at 5p15.33 and 3q28 and a recently reported finding at 17q24.3. We observed no evidence of association for lung cancer at 15q25 in never-smoking women in Asia, providing strong evidence that this locus is not associated with lung cancer independent of smoking.

Genome-wide association study of circulating estradiol, testosterone, and sex hormone-binding globulin in postmenopausal women.

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 ß = -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.

A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits.

Pooling genome-wide association studies (GWASs) increases power but also poses methodological challenges because studies are often heterogeneous. For example, combining GWASs of related but distinct traits can provide promising directions for the discovery of loci with small but common pleiotropic effects. Classical approaches for meta-analysis or pooled analysis, however, might not be suitable for such analysis because individual variants are likely to be associated with only a subset of the traits or might demonstrate effects in different directions. We propose a method that exhaustively explores subsets of studies for the presence of true association signals that are in either the same direction or possibly opposite directions. An efficient approximation is used for rapid evaluation of p values. We present two illustrative applications, one for a meta-analysis of separate case-control studies of six distinct cancers and another for pooled analysis of a case-control study of glioma, a class of brain tumors that contains heterogeneous subtypes. Both the applications and additional simulation studies demonstrate that the proposed methods offer improved power and more interpretable results when compared to traditional methods for the analysis of heterogeneous traits. The proposed framework has applications beyond genetic association studies.

Detectable clonal mosaicism and its relationship to aging and cancer.

In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases.

Comprehensive resequence analysis of a 123-kb region of chromosome 11q13 associated with prostate cancer.

BACKGROUND: Genome-wide association studies of prostate cancer have identified single nucleotide polymorphism (SNP) markers in a region of chromosome 11q13.3 in men of European decent. A fine-mapping analysis with tag SNPs in the cancer genetic markers of susceptibility study identified three independent loci, marked by rs10896438, rs12793759, and rs10896449. This study further annotates common and uncommon variation across this region. METHODS: A next generation resequence analysis of a 122.9-kb region of 11q13.3(68,642,755-68,765,690) was conducted in 78 unrelated individuals of European background,1 CEPH trio, and 1 YRI trio. RESULTS: In total, 644 polymorphic loci were identified by our sequence analysis. Of these,166 variants­118 SNPs and 48 insertion-deletion polymorphisms (indels)­were novel,namely not present in the 1000 Genomes or International HapMap Projects. We identified 22,25, 6, and 4 variants strongly correlated (r2 ≥ 0.8) with rs10896438, rs10896449, rs12793759,and rs11228565, respectively. HapMap SNPs were in linkage disequilibrium (r2 ≥ 0.8) with 48%, 69%, 14%, and 60% of SNPs marking bins by rs10896438, rs10896449, rs12793759, and rs11228565, respectively. CONCLUSIONS: Our next generation resequence analysis compliments publicly available datasets of European descent (HapMap, build 28 and 1000 Genome, Pilot 1, October 2010),underscoring the value of targeted resequence analysis prior to initiating functional studies based on public databases alone. Increasing the number of common variants enables investigators to better prioritize variants for functional studies designed to uncover the biological basis of the direct association(s) in the region.

Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer.

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.

Genotypic variants at 2q33 and risk of esophageal squamous cell carcinoma in China: a meta-analysis of genome-wide association studies.

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.