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1.
  • Sampson, Joshua N., et al. (author)
  • Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types
  • 2015
  • In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 107:12
  • Journal article (peer-reviewed)abstract
    • Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, h(l)(2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (rho = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (rho = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (rho = 0.51, SE = 0.18), and bladder and lung (rho = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
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2.
  • Machiela, Mitchell J., et al. (author)
  • Characterization of Large Structural Genetic Mosaicism in Human Autosomes
  • 2015
  • In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 96:3, s. 487-497
  • Journal article (peer-reviewed)abstract
    • 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 x 3 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.
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3.
  • Machiela, Mitchell J, et al. (author)
  • Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome
  • 2016
  • In: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 7
  • Journal article (peer-reviewed)abstract
    • 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.
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4.
  • Hollestelle, Antoinette, et al. (author)
  • No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer
  • 2016
  • In: Gynecologic Oncology. - : Elsevier BV. - 0090-8258 .- 1095-6859. ; 141:2, s. 386-401
  • Journal article (peer-reviewed)abstract
    • Objective Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3′ UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370. Methods Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers). Results We found no association with risk of ovarian cancer (OR = 0.99, 95% CI 0.94-1.04, p = 0.74) or breast cancer (OR = 0.98, 95% CI 0.94-1.01, p = 0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR = 1.09, 95% CI 0.97-1.23, p = 0.14, breast cancer HR = 1.04, 95% CI 0.97-1.12, p = 0.27; BRCA2, ovarian cancer HR = 0.89, 95% CI 0.71-1.13, p = 0.34, breast cancer HR = 1.06, 95% CI 0.94-1.19, p = 0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR = 0.94, 95% CI 0.83-1.07, p = 0.38), breast cancer (HR = 0.96, 95% CI 0.87-1.06, p = 0.38), and all other previously-reported associations. Conclusions rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.
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5.
  • Wang, Tao, et al. (author)
  • Pleiotropy of genetic variants on obesity and smoking phenotypes : Results from the Oncoarray Project of The International Lung Cancer Consortium
  • 2017
  • In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:9, s. 0185660-0185660
  • Journal article (peer-reviewed)abstract
    • Obesity and cigarette smoking are correlated through complex relationships. Common genetic causes may contribute to these correlations. In this study, we selected 241 loci potentially associated with body mass index (BMI) based on the Genetic Investigation of ANthropometric Traits (GIANT) consortium data and calculated a BMI genetic risk score (BMI-GRS) for 17,037 individuals of European descent from the Oncoarray Project of the International Lung Cancer Consortium (ILCCO). Smokers had a significantly higher BMI-GRS than never-smokers (p = 0.016 and 0.010 before and after adjustment for BMI, respectively). The BMI-GRS was also positively correlated with pack-years of smoking (p<0.001) in smokers. Based on causal network inference analyses, seven and five of 241 SNPs were classified to pleiotropic models for BMI/smoking status and BMI/pack-years, respectively. Among them, three and four SNPs associated with smoking status and pack-years (p<0.05), respectively, were followed up in the ever-smoking data of the Tobacco, Alcohol and Genetics (TAG) consortium. Among these seven candidate SNPs, one SNP (rs11030104, BDNF) achieved statistical significance after Bonferroni correction for multiple testing, and three suggestive SNPs (rs13021737, TMEM18; rs11583200, ELAVL4; and rs6990042, SGCZ) achieved a nominal statistical significance. Our results suggest that there is a common genetic component between BMI and smoking, and pleiotropy analysis can be useful to identify novel genetic loci of complex phenotypes.
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6.
  • Berndt, Sonja I., et al. (author)
  • Meta-analysis of genome-wide association studies discovers multiple loci for chronic lymphocytic leukemia
  • 2016
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
  • Journal article (peer-reviewed)abstract
    • Chronic lymphocytic leukemia (CLL) is a common lymphoid malignancy with strong heritability. To further understand the genetic susceptibility for CLL and identify common loci associated with risk, we conducted a meta-analysis of four genome-wide association studies (GWAS) composed of 3,100 cases and 7,667 controls with follow-up replication in 1,958 cases and 5,530 controls. Here we report three new loci at 3p24.1 (rs9880772, EOMES, P = 2.55 x 10(-11)), 6p25.2 (rs73718779, SERPINB6, P = 1.97 x 10(-8)) and 3q28 (rs9815073, LPP, P = 3.62 x 10(-8)), as well as a new independent SNP at the known 2q13 locus (rs9308731, BCL2L11, P = 1.00 x 10(-11)) in the combined analysis. We find suggestive evidence (P<5 x 10(-7)) for two additional new loci at 4q24 (rs10028805, BANK1, P = 7.19 x 10(-8)) and 3p22.2 (rs1274963, CSRNP1, P = 2.12 x 10(-7)). Pathway analyses of new and known CLL loci consistently show a strong role for apoptosis, providing further evidence for the importance of this biological pathway in CLL susceptibility.
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7.
  • Brenner, Darren R, et al. (author)
  • Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia
  • 2015
  • In: Carcinogenesis. - : Oxford University Press. - 0143-3334 .- 1460-2180. ; 36:11, s. 1314-1326
  • Journal article (peer-reviewed)abstract
    • Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10−8) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10−7) and MTMR2 at 11q21 (rs10501831, P = 3.1×10−6) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10−7) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10−4 for KCNIP4, represented by rs9799795) and AC (P = 2.16×10−4 for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range.
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8.
  • Carreras-Torres, Robert, et al. (author)
  • Obesity, metabolic factors and risk of different histological types of lung cancer : a Mendelian randomization study
  • 2017
  • In: PLOS ONE. - : Public library science. - 1932-6203. ; 12:6
  • Journal article (peer-reviewed)abstract
    • Background: Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. Methods and findings: We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95% CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m(2)]), but not for adenocarcinoma (OR [95% CI] = 0.93 [0.79-1.08]) (P-heterogeneity = 4.3x10(-3)). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10(-3)), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95% CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95% CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. Conclusions: Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.
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9.
  • Dai, Juncheng, et al. (author)
  • Systematic analyses of regulatory variants in DNase I hypersensitive sites identified two novel lung cancer susceptibility loci
  • 2019
  • In: Carcinogenesis. - : Oxford University Press (OUP). - 0143-3334 .- 1460-2180. ; 40:3, s. 432-440
  • Journal article (peer-reviewed)abstract
    • DNase I hypersensitive sites (DHS) are abundant in regulatory elements, such as promoter, enhancer and transcription factor binding sites. Many studies have revealed that disease-associated variants were concentrated in DHS-related regions. However, limited studies are available on the roles of DHS-related variants in lung cancer. In this study, we performed a large-scale case-control study with 20 871 lung cancer cases and 15 971 controls to evaluate the associations between regulatory genetic variants in DHS and lung cancer susceptibility. The expression quantitative trait loci (eQTL) analysis and pathway-enrichment analysis were performed to identify the possible target genes and pathways. In addition, we performed motif-based analysis to explore the lung-cancer-related motifs using sequence kernel association test. Two novel variants, rs186332 in 20q13.3 (C>T, odds ratio [OR] = 1.17, 95% confidence interval [95% CI]: 1.10-1.24, P = 8.45 × 10-7) and rs4839323 in 1p13.2 (T>C, OR = 0.92, 95% CI: 0.89-0.95, P = 1.02 × 10-6) showed significant association with lung cancer risk. The eQTL analysis suggested that these two SNPs might regulate the expression of MRGBP and SLC16A1, respectively. What's more, the expression of both MRGBP and SLC16A1 was aberrantly elevated in lung tumor tissues. The motif-based analysis identified 10 motifs related to the risk of lung cancer (P < 1.71 × 10-4). Our findings suggested that variants in DHS might modify lung cancer susceptibility through regulating the expression of surrounding genes. This study provided us a deeper insight into the roles of DHS-related genetic variants for lung cancer.
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10.
  • Ferreiro-Iglesias, Aida, et al. (author)
  • Fine mapping of MHC region in lung cancer highlights independent susceptibility loci by ethnicity
  • 2018
  • In: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 9
  • Journal article (peer-reviewed)abstract
    • Lung cancer has several genetic associations identified within the major histocompatibility complex (MHC); although the basis for these associations remains elusive. Here, we analyze MHC genetic variation among 26,044 lung cancer patients and 20,836 controls densely genotyped across the MHC, using the Illumina Illumina OncoArray or Illumina 660W SNP microarray. We impute sequence variation in classical HLA genes, fine-map MHC associations for lung cancer risk with major histologies and compare results between ethnicities. Independent and novel associations within HLA genes are identified in Europeans including amino acids in the HLA-B*0801 peptide binding groove and an independent HLA-DQB1*06 loci group. In Asians, associations are driven by two independent HLA allele sets that both increase risk in HLA-DQB1*0401 and HLA-DRB1*0701; the latter better represented by the amino acid Ala-104. These results implicate several HLA-tumor peptide interactions as the major MHC factor modulating lung cancer susceptibility.
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