REV-ERB in GABAergic neurons controls diurnal hepatic insulin sensitivity.

Systemic insulin sensitivity shows a diurnal rhythm with a peak upon waking1,2. The molecular mechanism that underlies this temporal pattern is unclear. Here we show that the nuclear receptors REV-ERB-α and REV-ERB-ß (referred to here as 'REV-ERB') in the GABAergic (γ-aminobutyric acid-producing) neurons in the suprachiasmatic nucleus (SCN) (SCNGABA neurons) control the diurnal rhythm of insulin-mediated suppression of hepatic glucose production in mice, without affecting diurnal eating or locomotor behaviours during regular light-dark cycles. REV-ERB regulates the rhythmic expression of genes that are involved in neurotransmission in the SCN, and modulates the oscillatory firing activity of SCNGABA neurons. Chemogenetic stimulation of SCNGABA neurons at waking leads to glucose intolerance, whereas restoration of the temporal pattern of either SCNGABA neuron firing or REV-ERB expression rescues the time-dependent glucose metabolic phenotype caused by REV-ERB depletion. In individuals with diabetes, an increased level of blood glucose after waking is a defining feature of the 'extended dawn phenomenon'3,4. Patients with type 2 diabetes with the extended dawn phenomenon exhibit a differential temporal pattern of expression of REV-ERB genes compared to patients with type 2 diabetes who do not have the extended dawn phenomenon. These findings provide mechanistic insights into how the central circadian clock regulates the diurnal rhythm of hepatic insulin sensitivity, with implications for our understanding of the extended dawn phenomenon in type 2 diabetes.

Genome-wide association study identifies high-impact susceptibility loci for HCC in North America.

BACKGROUND AND AIMS: Despite the substantial impact of environmental factors, individuals with a family history of liver cancer have an increased risk for HCC. However, genetic factors have not been studied systematically by genome-wide approaches in large numbers of individuals from European descent populations (EDP). APPROACH AND RESULTS: We conducted a 2-stage genome-wide association study (GWAS) on HCC not affected by HBV infections. A total of 1872 HCC cases and 2907 controls were included in the discovery stage, and 1200 HCC cases and 1832 controls in the validation. We analyzed the discovery and validation samples separately and then conducted a meta-analysis. All analyses were conducted in the presence and absence of HCV. The liability-scale heritability was 24.4% for overall HCC. Five regions with significant ORs (95% CI) were identified for nonviral HCC: 3p22.1, MOBP , rs9842969, (0.51, [0.40-0.65]); 5p15.33, TERT , rs2242652, (0.70, (0.62-0.79]); 19q13.11, TM6SF2 , rs58542926, (1.49, [1.29-1.72]); 19p13.11 MAU2 , rs58489806, (1.53, (1.33-1.75]); and 22q13.31, PNPLA3 , rs738409, (1.66, [1.51-1.83]). One region was identified for HCV-induced HCC: 6p21.31, human leukocyte antigen DQ beta 1, rs9275224, (0.79, [0.74-0.84]). A combination of homozygous variants of PNPLA3 and TERT showing a 6.5-fold higher risk for nonviral-related HCC compared to individuals lacking these genotypes. This observation suggests that gene-gene interactions may identify individuals at elevated risk for developing HCC. CONCLUSIONS: Our GWAS highlights novel genetic susceptibility of nonviral HCC among European descent populations from North America with substantial heritability. Selected genetic influences were observed for HCV-positive HCC. Our findings indicate the importance of genetic susceptibility to HCC development.

Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk.

Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Disentangling the aetiological pathways between body mass index and site-specific cancer risk using tissue-partitioned Mendelian randomisation.

BACKGROUND: Body mass index (BMI) is known to influence the risk of various site-specific cancers, however, dissecting which subcomponents of this heterogenous risk factor are predominantly responsible for driving disease effects has proven difficult to establish. We have leveraged tissue-specific gene expression to separate the effects of distinct phenotypes underlying BMI on the risk of seven site-specific cancers. METHODS: SNP-exposure estimates were weighted in a multivariable Mendelian randomisation analysis by their evidence for colocalization with subcutaneous adipose- and brain-tissue-derived gene expression using a recently developed methodology. RESULTS: Our results provide evidence that brain-tissue-derived BMI variants are predominantly responsible for driving the genetically predicted effect of BMI on lung cancer (OR: 1.17; 95% CI: 1.01-1.36; P = 0.03). Similar findings were identified when analysing cigarettes per day as an outcome (Beta = 0.44; 95% CI: 0.26-0.61; P = 1.62 × 10-6), highlighting a possible shared aetiology or mediator effect between brain-tissue BMI, smoking and lung cancer. Our results additionally suggest that adipose-tissue-derived BMI variants may predominantly drive the effect of BMI and increased risk for endometrial cancer (OR: 1.71; 95% CI: 1.07-2.74; P = 0.02), highlighting a putatively important role in the aetiology of endometrial cancer. CONCLUSIONS: The study provides valuable insight into the divergent underlying pathways between BMI and the risk of site-specific cancers.

An international genome-wide meta-analysis of primary biliary cholangitis: Novel risk loci and candidate drugs.

BACKGROUNDS & AIMS: Primary biliary cholangitis (PBC) is a chronic liver disease in which autoimmune destruction of the small intrahepatic bile ducts eventually leads to cirrhosis. Many patients have inadequate response to licensed medications, motivating the search for novel therapies. Previous genome-wide association studies (GWAS) and meta-analyses (GWMA) of PBC have identified numerous risk loci for this condition, providing insight into its aetiology. We undertook the largest GWMA of PBC to date, aiming to identify additional risk loci and prioritise candidate genes for in silico drug efficacy screening. METHODS: We combined new and existing genotype data for 10,516 cases and 20,772 controls from 5 European and 2 East Asian cohorts. RESULTS: We identified 56 genome-wide significant loci (20 novel) including 46 in European, 13 in Asian, and 41 in combined cohorts; and a 57th genome-wide significant locus (also novel) in conditional analysis of the European cohorts. Candidate genes at newly identified loci include FCRL3, INAVA, PRDM1, IRF7, CCR6, CD226, and IL12RB1, which each play key roles in immunity. Pathway analysis reiterated the likely importance of pattern recognition receptor and TNF signalling, JAK-STAT signalling, and differentiation of T helper (TH)1 and TH17 cells in the pathogenesis of this disease. Drug efficacy screening identified several medications predicted to be therapeutic in PBC, some of which are well-established in the treatment of other autoimmune disorders. CONCLUSIONS: This study has identified additional risk loci for PBC, provided a hierarchy of agents that could be trialled in this condition, and emphasised the value of genetic and genomic approaches to drug discovery in complex disorders. LAY SUMMARY: Primary biliary cholangitis (PBC) is a chronic liver disease that eventually leads to cirrhosis. In this study, we analysed genetic information from 10,516 people with PBC and 20,772 healthy individuals recruited in Canada, China, Italy, Japan, the UK, or the USA. We identified several genetic regions associated with PBC. Each of these regions contains several genes. For each region, we used diverse sources of evidence to help us choose the gene most likely to be involved in causing PBC. We used these 'candidate genes' to help us identify medications that are currently used for treatment of other conditions, which might also be useful for treatment of PBC.

Genome-wide association study of familial lung cancer.

To identify genetic variation associated with lung cancer risk, we performed a genome-wide association analysis of 685 lung cancer cases that had a family history of two or more first or second degree relatives compared with 744 controls without lung cancer that were genotyped on an Illumina Human OmniExpressExome-8v1 array. To ensure robust results, we further evaluated these findings using data from six additional studies that were assembled through the Transdisciplinary Research on Cancer of the Lung Consortium comprising 1993 familial cases and 33 690 controls. We performed a meta-analysis after imputation of all variants using the 1000 Genomes Project Phase 1 (version 3 release date September 2013). Analyses were conducted for 9 327 222 SNPs integrating data from the two sources. A novel variant on chromosome 4p15.31 near the LCORL gene and an imputed rare variant intergenic between CDKN2A and IFNA8 on chromosome 9p21.3 were identified at a genome-wide level of significance for squamous cell carcinomas. Additionally, associations of CHRNA3 and CHRNA5 on chromosome 15q25.1 in sporadic lung cancer were confirmed at a genome-wide level of significance in familial lung cancer. Previously identified variants in or near CHRNA2, BRCA2, CYP2A6 for overall lung cancer, TERT, SECISPB2L and RTEL1 for adenocarcinoma and RAD52 and MHC for squamous carcinoma were significantly associated with lung cancer.

Genome-wide interaction study of smoking behavior and non-small cell lung cancer risk in Caucasian population.

Non-small cell lung cancer is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between single nucleotide polymorphisms (SNPs) and smoking status (never- versus ever-smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13336 non-small cell lung cancer cases. Candidate SNPs with P-value <0.001 were further analyzed using a standard case-control interaction analysis including 13970 controls. The significant SNPs with P-value <3.5 × 10-5 (correcting for multiple tests) from the case-control analysis in the discovery stage were further validated using an independent replication dataset comprising 5377 controls and 3054 non-small cell lung cancer cases. We further stratified the analysis by histological subtypes. Two novel SNPs, rs6441286 and rs17723637, were identified for overall lung cancer risk. The interaction odds ratio and meta-analysis P-value for these two SNPs were 1.24 with 6.96 × 10-7 and 1.37 with 3.49 × 10-7, respectively. In addition, interaction of smoking with rs4751674 was identified in squamous cell lung carcinoma with an odds ratio of 0.58 and P-value of 8.12 × 10-7. This study is by far the largest genome-wide SNP-smoking interaction analysis reported for lung cancer. The three identified novel SNPs provide potential candidate biomarkers for lung cancer risk screening and intervention. The results from our study reinforce that gene-smoking interactions play important roles in the etiology of lung cancer and account for part of the missing heritability of this disease.

Novel genetic variants in the P38MAPK pathway gene ZAK and susceptibility to lung cancer.

The P38MAPK pathway participates in regulating cell cycle, inflammation, development, cell death, cell differentiation, and tumorigenesis. Genetic variants of some genes in the P38MAPK pathway are reportedly associated with lung cancer risk. To substantiate this finding, we used six genome-wide association studies (GWASs) to comprehensively investigate the associations of 14 904 single nucleotide polymorphisms (SNPs) in 108 genes of this pathway with lung cancer risk. We identified six significant lung cancer risk-associated SNPs in two genes (CSNK2B and ZAK) after correction for multiple comparisons by a false discovery rate (FDR) <0.20. After removal of three CSNK2B SNPs that are located in the same locus previously reported by GWAS, we performed the LD analysis and found that rs3769201 and rs7604288 were in high LD. We then chose two independent representative SNPs of rs3769201 and rs722864 in ZAK for further analysis. We also expanded the analysis by including these two SNPs from additional GWAS datasets of Harvard University (984 cases and 970 controls) and deCODE (1319 cases and 26 380 controls). The overall effects of these two SNPs were assessed using all eight GWAS datasets (OR = 0.92, 95%CI = 0.89-0.95, and P = 1.03 × 10-5 for rs3769201; OR = 0.91, 95%CI = 0.88-0.95, and P = 2.03 × 10-6 for rs722864). Finally, we performed an expression quantitative trait loci (eQTL) analysis and found that these two SNPs were significantly associated with ZAK mRNA expression levels in lymphoblastoid cell lines. In conclusion, the ZAK rs3769201 and rs722864 may be functional susceptibility loci for lung cancer risk.

Functional variants in DCAF4 associated with lung cancer risk in European populations.

Cullin-RING ubiquitin ligases (CRLs) responsible for substrate specificity of ubiquitination play a key role in cell-cycle control and DNA damage response. In this study, we assessed associations between 16 599 SNPs in 115 CRL genes and lung cancer risk by using summary data of six published genome-wide association studies (GWASs) of 12 160 cases and 16 838 cases of European ancestry. As a result, we identified three independent SNPs in DCAF4 (rs117781739, rs12587742 and rs2240980) associated with lung cancer risk (odds ratio = 0.91, 1.09 and 1.09, respectively; 95% confidence interval = 0.88-0.95, 1.05-1.14 and 1.05-1.13, respectively; and P = 3.99 × 10-6, 4.97 × 10-5 and 1.44 × 10-5, respectively) after multiple comparison correction by a false discovery rate <0.05. Since SNP rs12587742 is located within the promoter region and one CpG island of DCAF4, we further performed in silico functional analyses and found that the rs12587742 variant A allele was associated with an increased mRNA expression (P = 2.20 × 10-16, 1.79 × 10-13 and 0.001 in blood cells, normal lung tissues and tumor tissues of lung squamous carcinoma, respectively) and a decreased methylation status (P = 2.48 × 10-9 and 0.032 in adipose and lung tumor tissues, respectively). Moreover, evidence from differential expression analyses further supported an oncogenic effect of DCAF4 on lung cancer, with higher mRNA levels in both lung squamous carcinoma and adenocarcinoma (P = 4.48 × 10-11 and 1.22 × 10-9, respectively) than in adjacent normal tissues. Taken together, our results suggest that rs12587742 is associated with an increased lung cancer risk, possibly by up-regulating mRNA expression and decreasing methylation status of DCAF4.

Ancestry inference using principal component analysis and spatial analysis: a distance-based analysis to account for population substructure.

BACKGROUND: Accurate inference of genetic ancestry is of fundamental interest to many biomedical, forensic, and anthropological research areas. Genetic ancestry memberships may relate to genetic disease risks. In a genome association study, failing to account for differences in genetic ancestry between cases and controls may also lead to false-positive results. Although a number of strategies for inferring and taking into account the confounding effects of genetic ancestry are available, applying them to large studies (tens thousands samples) is challenging. The goal of this study is to develop an approach for inferring genetic ancestry of samples with unknown ancestry among closely related populations and to provide accurate estimates of ancestry for application to large-scale studies. METHODS: In this study we developed a novel distance-based approach, Ancestry Inference using Principal component analysis and Spatial analysis (AIPS) that incorporates an Inverse Distance Weighted (IDW) interpolation method from spatial analysis to assign individuals to population memberships. RESULTS: We demonstrate the benefits of AIPS in analyzing population substructure, specifically related to the four most commonly used tools EIGENSTRAT, STRUCTURE, fastSTRUCTURE, and ADMIXTURE using genotype data from various intra-European panels and European-Americans. While the aforementioned commonly used tools performed poorly in inferring ancestry from a large number of subpopulations, AIPS accurately distinguished variations between and within subpopulations. CONCLUSIONS: Our results show that AIPS can be applied to large-scale data sets to discriminate the modest variability among intra-continental populations as well as for characterizing inter-continental variation. The method we developed will protect against spurious associations when mapping the genetic basis of a disease. Our approach is more accurate and computationally efficient method for inferring genetic ancestry in the large-scale genetic studies.

Identification of shared and unique susceptibility pathways among cancers of the lung, breast, and prostate from genome-wide association studies and tissue-specific protein interactions.

Results from genome-wide association studies (GWAS) have indicated that strong single-gene effects are the exception, not the rule, for most diseases. We assessed the joint effects of germline genetic variations through a pathway-based approach that considers the tissue-specific contexts of GWAS findings. From GWAS meta-analyses of lung cancer (12 160 cases/16 838 controls), breast cancer (15 748 cases/18 084 controls) and prostate cancer (14 160 cases/12 724 controls) in individuals of European ancestry, we determined the tissue-specific interaction networks of proteins expressed from genes that are likely to be affected by disease-associated variants. Reactome pathways exhibiting enrichment of proteins from each network were compared across the cancers. Our results show that pathways associated with all three cancers tend to be broad cellular processes required for growth and survival. Significant examples include the nerve growth factor (P = 7.86 × 10(-33)), epidermal growth factor (P = 1.18 × 10(-31)) and fibroblast growth factor (P = 2.47 × 10(-31)) signaling pathways. However, within these shared pathways, the genes that influence risk largely differ by cancer. Pathways found to be unique for a single cancer focus on more specific cellular functions, such as interleukin signaling in lung cancer (P = 1.69 × 10(-15)), apoptosis initiation by Bad in breast cancer (P = 3.14 × 10(-9)) and cellular responses to hypoxia in prostate cancer (P = 2.14 × 10(-9)). We present the largest comparative cross-cancer pathway analysis of GWAS to date. Our approach can also be applied to the study of inherited mechanisms underlying risk across multiple diseases in general.

Susceptibility loci of CNOT6 in the general mRNA degradation pathway and lung cancer risk-A re-analysis of eight GWASs.

PURPOSE: mRNA degradation is an important regulatory step for controlling gene expression and cell functions. Genetic abnormalities involved in mRNA degradation genes were found to be associated with cancer risks. Therefore, we systematically investigated the roles of genetic variants in the general mRNA degradation pathway in lung cancer risk. EXPERIMENTAL DESIGN: Meta-analyses were conducted using summary data from six lung cancer genome-wide association studies (GWASs) from the Transdisciplinary Research in Cancer of the Lung and additional two GWASs from Harvard University and deCODE in the International Lung Cancer Consortium. Expression quantitative trait loci analysis (eQTL) was used for in silico functional validation of the identified significant susceptibility loci. RESULTS: This pathway-based analysis included 6816 single nucleotide polymorphisms (SNP) in 68 genes in 14 463 lung cancer cases and 44 188 controls. In the single-locus analysis, we found that 20 SNPs were associated with lung cancer risk with a false discovery rate threshold of <0.05. Among the 11 newly identified SNPs in CNOT6, which were in high linkage disequilibrium, the rs2453176 with a RegulomDB score "1f" was chosen as the tagSNP for further analysis. We found that the rs2453176 T allele was significantly associated with lung cancer risk (odds ratio = 1.11, 95% confidence interval = 1.04-1.18) in the eight GWASs. In the eQTL analysis, we found that levels of CNOT6 mRNA expression were significantly correlated with the rs2453176 T allele, which provided additional biological basis for the observed positive association. CONCLUSION: The CNOT6 rs2453176 SNP may be a new functional susceptible locus for lung cancer risk. © 2016 Wiley Periodicals, Inc.

Pathway-analysis of published genome-wide association studies of lung cancer: A potential role for the CYP4F3 locus.

The fatty acids (FAs) metabolism is suggested to play a pivotal role in the development of lung cancer, and we explored that by conducting a pathway-based analysis. We performed a meta-analysis of published datasets of six genome wide association studies (GWASs) from the Transdisciplinary Research in Cancer of the Lung (TRICL) consortium, which included 12 160 cases with lung cancer and 16 838 cancer-free controls. A total of 30 722 single-nucleotide polymorphisms (SNPs) from 317 genes relevant to FA metabolic pathways were identified. An additional dataset from the Harvard Lung Cancer Study with 984 cases and 970 healthy controls was also added to the final meta-analysis. In the initial meta-analysis, 26 of 28 SNPs that passed false discovery rate multiple tests were mapped to the CYP4F3 gene. Among the 26 top ranked hits was a proxy SNP, CYP4F3 rs4646904 (P = 8.65 × 10-6 , FDR = 0.018), which is suggested to change splicing pattern/efficiency and to be associated with gene expression levels. However, after adding data of rs4646904 from the Harvard GWAS, the significance in the combined analysis was reduced to P = 3.52 × 10-3 [odds ratio (OR) = 1.07, 95% confidence interval (95%CI) = 1.03-1.12]. Interestingly, the small Harvard dataset also pointed to the same direction of the association in subgroups of smokers (OR = 1.07) and contributed to a combined OR of 1.13 (95% CI = 1.06-1.20, P = 6.70 × 10-5 ). The results suggest that a potentially functional SNP in CYP4F3 (rs4646904) may contribute to the etiology of lung cancer, especially in smokers. Additional mechanistic studies are warranted to unravel the potential biological significance of the finding.

FastPop: a rapid principal component derived method to infer intercontinental ancestry using genetic data.

BACKGROUND: Identifying subpopulations within a study and inferring intercontinental ancestry of the samples are important steps in genome wide association studies. Two software packages are widely used in analysis of substructure: Structure and Eigenstrat. Structure assigns each individual to a population by using a Bayesian method with multiple tuning parameters. It requires considerable computational time when dealing with thousands of samples and lacks the ability to create scores that could be used as covariates. Eigenstrat uses a principal component analysis method to model all sources of sampling variation. However, it does not readily provide information directly relevant to ancestral origin; the eigenvectors generated by Eigenstrat are sample specific and thus cannot be generalized to other individuals. RESULTS: We developed FastPop, an efficient R package that fills the gap between Structure and Eigenstrat. It can: 1, generate PCA scores that identify ancestral origins and can be used for multiple studies; 2, infer ancestry information for data arising from two or more intercontinental origins. We demonstrate the use of FastPop using 2318 SNP markers selected from the genome based on high variability among European, Asian and West African (African) populations. We conducted an analysis of 505 Hapmap samples with European, African or Asian ancestry along with 19661 additional samples of unknown ancestry. The results from FastPop are highly consistent with those obtained by Structure across the 19661 samples we studied. The correlations of the results between FastPop and Structure are 0.99, 0.97 and 0.99 for European, African and Asian ancestry scores, respectively. Compared with Structure, FastPop is more efficient as it finished ancestry inference for 19661 samples in 16 min compared with 21-24 h required by Structure. FastPop also provided scores based on SNP weights so the scores of reference population can be applied to other studies provided the same set of markers are used. We also present application of the method for studying four continental populations (European, Asian, African, and Native American). CONCLUSIONS: We developed an algorithm that can infer ancestries on data involving two or more intercontinental origins. It is efficient for analyzing large datasets. Additionally the PCA derived scores can be applied to multiple data sets to ensure the same ancestry analysis is applied to all studies.

Polymorphisms of the centrosomal gene (FGFR1OP) and lung cancer risk: a meta-analysis of 14,463 cases and 44,188 controls.

Centrosome abnormalities are often observed in premalignant lesions and in situ tumors and have been associated with aneuploidy and tumor development. We investigated the associations of 9354 single-nucleotide polymorphisms (SNPs) in 106 centrosomal genes with lung cancer risk by first using the summary data from six published genome-wide association studies (GWASs) of the Transdisciplinary Research in Cancer of the Lung (TRICL) (12,160 cases and 16 838 controls) and then conducted in silico replication in two additional independent lung cancer GWASs of Harvard University (984 cases and 970 controls) and deCODE (1319 cases and 26,380 controls). A total of 44 significant SNPs with false discovery rate (FDR) ≤ 0.05 were mapped to one novel gene FGFR1OP and two previously reported genes (TUBB and BRCA2). After combined the results from TRICL with those from Harvard and deCODE, the most significant association (P combined = 8.032 × 10(-6)) was with rs151606 within FGFR1OP. The rs151606 T>G was associated with an increased risk of lung cancer [odds ratio (OR) = 1.10, 95% confidence interval (95% CI) = 1.05-1.14]. Another significant tagSNP rs12212247 T>C (P combined = 9.589 × 10(-6)) was associated with a decreased risk of lung cancer (OR = 0.93, 95% CI = 0.90-0.96). Further in silico functional analyzes revealed that rs151606 might affect transcriptional regulation and result in decreased FGFR1OP expression (P trend = 0.022). The findings shed some new light on the role of centrosome abnormalities in the susceptibility to lung carcinogenesis.

Telomere structure and maintenance gene variants and risk of five cancer types.

Telomeres cap chromosome ends, protecting them from degradation, double-strand breaks, and end-to-end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset-based meta-analyses of 204,993 directly-measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene-level p value cutoffs ≤3.08 × 10-5 ). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere-related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.

Functional characterization of RAD52 as a lung cancer susceptibility gene in the 12p13.33 locus.

Recent genome-wide association studies have identified variations in the recombination repair gene, RAD52, that are associated with increased lung cancer risk, and particularly with the development of lung squamous cell carcinomas (LUSC). As LUSC development is strongly associated with smoking, DNA repair is increased in the lung tissues of smokers, presumably because of ongoing DNA damage from exposure to tobacco smoke. A key player in the DNA damage response, RAD52 plays a role in DNA strand exchange and annealing during homologous recombination (HR) in mammalian cells. In this study, we discovered two cis-expression quantitative trait loci (eQTL) SNPs in the RAD52 gene that are associated with its expression and are also associated with LUSC risk. In addition, we report that amplification of the genomic region 12p13.33, which contains the RAD52 gene, is significantly associated with the development of LUSC in the TCGA database and that somatic overexpression of RAD52 was confirmed to be significant in LUSC tumors from our own patient cohort. Consistent with these genetic findings, we demonstrate that blockade of Rad52 slows cell growth and induces senescence in mouse bronchial epithelial cells. In contrast, overexpression of Rad52 leads to an increased rate of cell proliferation. We show that depletion of Rad52 in mouse lung tumor cells alters cell cycle distribution and increases DNA damage accumulation associated with increased tumor cell death. Our genetic and functional data implicate RAD52 as a significant determinant of risk in the development of LUSC.