| 1. |
- Ji, Xuemei, et al.
(författare)
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Protein-altering germline mutations implicate novel genes related to lung cancer development
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Few germline mutations are known to affect lung cancer risk. We performed analyses of rare variants from 39,146 individuals of European ancestry and investigated gene expression levels in 7,773 samples. We find a large-effect association with an ATM L2307F (rs56009889) mutation in adenocarcinoma for discovery (adjusted Odds Ratio=8.82, P=1.18x10(-15)) and replication (adjusted OR=2.93, P=2.22x10(-3)) that is more pronounced in females (adjusted OR=6.81 and 3.19 and for discovery and replication). We observe an excess loss of heterozygosity in lung tumors among ATM L2307F allele carriers. L2307F is more frequent (4%) among Ashkenazi Jewish populations. We also observe an association in discovery (adjusted OR=2.61, P=7.98x10(-22)) and replication datasets (adjusted OR=1.55, P=0.06) with a loss-of-function mutation, Q4X (rs150665432) of an uncharacterized gene, KIAA0930. Our findings implicate germline genetic variants in ATM with lung cancer susceptibility and suggest KIAA0930 as a novel candidate gene for lung cancer risk. In lung cancer, relatively few germline mutations are known to impact risk. Here the authors looked at rare variants in 39,146 individuals and find novel germline mutations associated with risk, as well as implicating ATM and a new candidate gene for lung cancer risk.
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| 2. |
- Bosse, Yohan, et al.
(författare)
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Transcriptome-wide association study reveals candidate causal genes for lung cancer
- 2020
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Ingår i: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 146:7, s. 1862-1878
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Tidskriftsartikel (refereegranskat)abstract
- We have recently completed the largest GWAS on lung cancer including 29,266 cases and 56,450 controls of European descent. The goal of our study has been to integrate the complete GWAS results with a large‐scale expression quantitative trait loci (eQTL) mapping study in human lung tissues (n = 1,038) to identify candidate causal genes for lung cancer. We performed transcriptome‐wide association study (TWAS) for lung cancer overall, by histology (adenocarcinoma, squamous cell carcinoma and small cell lung cancer) and smoking subgroups (never‐ and ever‐smokers). We performed replication analysis using lung data from the Genotype‐Tissue Expression (GTEx) project. DNA damage assays were performed in human lung fibroblasts for selected TWAS genes. As expected, the main TWAS signal for all histological subtypes and ever‐smokers was on chromosome 15q25. The gene most strongly associated with lung cancer at this locus using the TWAS approach was IREB2 (pTWAS = 1.09E−99), where lower predicted expression increased lung cancer risk. A new lung adenocarcinoma susceptibility locus was revealed on 9p13.3 and associated with higher predicted expression of AQP3 (pTWAS = 3.72E−6). Among the 45 previously described lung cancer GWAS loci, we mapped candidate target gene for 17 of them. The association AQP3‐adenocarcinoma on 9p13.3 was replicated using GTEx (pTWAS = 6.55E−5). Consistent with the effect of risk alleles on gene expression levels, IREB2 knockdown and AQP3 overproduction promote endogenous DNA damage. These findings indicate genes whose expression in lung tissue directly influences lung cancer risk.
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| 3. |
- Dai, Juncheng, et al.
(författare)
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Genome-wide association study of INDELs identified four novel susceptibility loci associated with lung cancer risk
- 2020
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Ingår i: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 146:10, s. 2855-2864
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have identified 45 susceptibility loci associated with lung ncer. Only less than SNPs, small insertions and deletions (INDELs) are the second most abundant netic polymorphisms in the human genome. INDELs are highly associated with multiple human seases, including lung cancer. However, limited studies with large-scale samples have been available to stematically evaluate the effects of INDELs on lung cancer risk. Here, we performed a large-scale meta- alysis to evaluate INDELs and their risk for lung cancer in 23,202 cases and 19,048 controls. Functional notations were performed to further explore the potential function of lung cancer risk INDELs. nditional analysis was used to clarify the relationship between INDELs and SNPs. Four new risk loci re identified in genome-wide INDEL analysis (1p13.2: rs5777156, Insertion, OR = 0.92, p = 9.10 x 10(- ; 4q28.2: rs58404727, Deletion, OR = 1.19, p = 5.25 x 10(-7); 12p13.31: rs71450133, Deletion, OR = 09, p = 8.83 x 10(-7); and 14q22.3: rs34057993, Deletion, OR = 0.90, p = 7.64 x 10(-8)). The eQTL alysis and functional annotation suggested that INDELs might affect lung cancer susceptibility by gulating the expression of target genes. After conducting conditional analysis on potential causal SNPs, e INDELs in the new loci were still nominally significant. Our findings indicate that INDELs could be tentially functional genetic variants for lung cancer risk. Further functional experiments are needed to tter understand INDEL mechanisms in carcinogenesis.
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| 4. |
- Luyapan, Jennifer, et al.
(författare)
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A new efficient method to detect genetic interactions for lung cancer GWAS
- 2020
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Ingår i: BMC Medical Genomics. - : Springer Science and Business Media LLC. - 1755-8794. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Genome-wide association studies (GWAS) have proven successful in predicting genetic risk of disease using single-locus models; however, identifying single nucleotide polymorphism (SNP) interactions at the genome-wide scale is limited due to computational and statistical challenges. We addressed the computational burden encountered when detecting SNP interactions for survival analysis, such as age of disease-onset. To confront this problem, we developed a novel algorithm, called the Efficient Survival Multifactor Dimensionality Reduction (ES-MDR) method, which used Martingale Residuals as the outcome parameter to estimate survival outcomes, and implemented the Quantitative Multifactor Dimensionality Reduction method to identify significant interactions associated with age of disease-onset. Methods: To demonstrate efficacy, we evaluated this method on two simulation data sets to estimate the type I error rate and power. Simulations showed that ES-MDR identified interactions using less computational workload and allowed for adjustment of covariates. We applied ES-MDR on the OncoArray-TRICL Consortium data with 14,935 cases and 12,787 controls for lung cancer (SNPs = 108,254) to search over all two-way interactions to identify genetic interactions associated with lung cancer age-of-onset. We tested the best model in an independent data set from the OncoArray-TRICL data. Results: Our experiment on the OncoArray-TRICL data identified many one-way and two-way models with a single-base deletion in the noncoding region of BRCA1 (HR 1.24, P = 3.15 × 10–15), as the top marker to predict age of lung cancer onset. Conclusions: From the results of our extensive simulations and analysis of a large GWAS study, we demonstrated that our method is an efficient algorithm that identified genetic interactions to include in our models to predict survival outcomes.
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| 5. |
- Ostrom, Quinn T., et al.
(författare)
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Glioma risk associated with extent of estimated European genetic ancestry in African Americans and Hispanics
- 2020
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Ingår i: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 146:3, s. 739-748
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Tidskriftsartikel (refereegranskat)abstract
- Glioma incidence is highest in non-Hispanic Whites, and to date, glioma genome-wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case-Control Study and GliomaSE Case-Control Study previously estimated to have <80% EA, or self-identify as non-White. We estimated global and local ancestry using fastStructure and RFMix, respectively, using 1,000 genomes project reference populations. Within groups with >= 40% AA (AFR(>= 0.4)), and >= 15% NAA (AMR(>= 0.15)), genome-wide association between local EA and glioma was evaluated using logistic regression conditioned on global EA for all gliomas. We identified two regions (7q21.11, p = 6.36 x 10(-4); 11p11.12, p = 7.0 x 10-4) associated with increased EA, and one associated with decreased EA (20p12.13, p = 0.0026) in AFR(>= 0.4). In addition, we identified a peak at rs1620291 (p = 4.36 x 10(-6)) in 7q21.3. Among AMR(>= 0.15), we found an association between increased EA in one region (12q24.21, p = 8.38 x 10(-4)), and decreased EA in two regions (8q24.21, p = 0. 0010; 20q13.33, p = 6.36 x 10(-4)). No other significant associations were identified. This analysis identified an association between glioma and two regions previously identified in EA populations (8q24.21, 20q13.33) and four novel regions (7q21.11, 11p11.12, 12q24.21 and 20p12.13). The identifications of novel association with EA suggest regions to target for future genetic association studies. What's new? Glioma is rare in non-White populations, and most glioma genome-wide association studies have included only primarily European ancestry populations. Here, the authors assess whether variation in European ancestry is associated with glioma risk in populations with a combination of European, African and Native American ancestry. Based on African American and Hispanic cases from two large glioma case-control studies, this analysis shows that increased European ancestry in admixed populations may be associated with increased glioma risk. The associations between glioma and two chromosomal regions previously identified in European ancestry populations, and four novel regions, may guide future studies.
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| 6. |
- Wang, Yuzhuo, et al.
(författare)
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Association Analysis of Driver Gene-Related Genetic Variants Identified Novel Lung Cancer Susceptibility Loci with 20,871 Lung Cancer Cases and 15,971 Controls
- 2020
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 29:7, s. 1423-1429
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Tidskriftsartikel (refereegranskat)abstract
- Background: A substantial proportion of cancer driver genes (CDG) are also cancer predisposition genes. However, the associations between genetic variants in lung CDGs and the susceptibility to lung cancer have rarely been investigated.Methods: We selected expression-related single-nucleotide polymorphisms (eSNP) and nonsynonymous variants of lung CDGs, and tested their associations with lung cancer risk in two large-scale genome-wide association studies (20,871 cases and 15,971 controls of European descent). Conditional and joint association analysis was performed to identify independent risk variants. The associations of independent risk variants with somatic alterations in lung CDGs or recurrently altered pathways were investigated using data from The Cancer Genome Atlas (TCGA) project.Results: We identified seven independent SNPs in five lung CDGs that were consistently associated with lung cancer risk in discovery (P < 0.001) and validation (P < 0.05) stages. Among these loci, rs78062588 in TPM3 (1q21.3) was a new lung cancer susceptibility locus (OR = 0.86, P = 1.65 x 10(-6)). Subgroup analysis by histologic types further identified nine lung CDGs. Analysis of somatic alterations found that in lung adenocarcinomas, rs78062588[C] allele (TPM3 in 1q21.3) was associated with elevated somatic copy number of TPM3 (OR = 1.16, P = 0.02). In lung adenocarcinomas, rs1611182 (HLA-A in 6p22.1) was associated with truncation mutations of the transcriptional misregulation in cancer pathway (OR = 0.66, P = 1.76 x 10(-3)).Conclusions: Genetic variants can regulate functions of lung CDGs and influence lung cancer susceptibility. Impact: Our findings might help unravel biological mechanisms underlying lung cancer susceptibility.
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| 7. |
- Yang, Tianzhong, et al.
(författare)
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Incorporating multiple sets of eQTL weights into gene-by-environment interaction analysis identifies novel susceptibility loci for pancreatic cancer
- 2020
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Ingår i: Genetic Epidemiology. - : Wiley-Blackwell. - 0741-0395 .- 1098-2272. ; 44:8, s. 880-892
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Tidskriftsartikel (refereegranskat)abstract
- It is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene-by-environment interaction (G x E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data-adaptive G x E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case-Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome-wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking-related pancreatic cancer susceptibility genes,TRIP10andKDM3A, were identified. The aGEw test is implemented in an R package aGE.
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