Collective effects of common SNPs and risk prediction in lung cancer.
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ABSTRACT:
SUBMITTER: Lei X
PROVIDER: S-EPMC6221896 | biostudies-literature | 2018 Dec
REPOSITORIES: biostudies-literature
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Project description:Genome-wide association studies (GWAS) have consistently identified specific lung cancer susceptibility regions. We evaluated the lung cancer-predictive performance of single-nucleotide polymorphisms (SNPs) in these regions.Lung cancer cases (N = 778) and controls (N = 1166) were genotyped for 77 SNPs located in GWAS-identified lung cancer susceptibility regions. Variable selection and model development used stepwise logistic regression and decision-tree analyses. In a subset nested in the Pittsburgh Lung Screening Study, change in area under the receiver operator characteristic curve and net reclassification improvement were used to compare predictions made by risk factor models with and without genetic variables.Variable selection and model development kept two SNPs in each of three GWAS regions, rs2736100 and rs7727912 in 5p15.33, rs805297 and rs1802127 in 6p21.33, and rs8034191 and rs12440014 in 15q25.1. The ratio of cases to controls was three times higher among subjects with a high-risk genotype in every one as opposed to none of the three GWAS regions (odds ratio, 3.14; 95% confidence interval, 2.02-4.88; adjusted for sex, age, and pack-years). Adding a three-level classified count of GWAS regions with high-risk genotypes to an age and smoking risk factor-only model improved lung cancer prediction by a small amount: area under the receiver operator characteristic curve, 0.725 versus 0.717 (p = 0.056); overall net reclassification improvement was 0.052 across low-, intermediate-, and high- 6-year lung cancer risk categories (<3.0%, 3.0%-4.9%, ? 5.0%).Specifying genotypes for SNPs in three GWAS-identified susceptibility regions improved lung cancer prediction, but probably by an extent too small to affect disease control practice.
| S-EPMC4636453 | biostudies-literature
Project description:Parkinson disease (PD) is the second most common neurodegenerative disorder in the aged population and thought to involve many genetic loci. While a number of individual single nucleotide polymorphisms (SNPs) have been linked with PD, many remain to be found and no known markers or combinations of them have a useful predictive value for sporadic PD cases. The collective effects of genome wide minor alleles of common SNPs, or the minor allele content (MAC) in an individual, have recently been shown to be linked with quantitative variations of numerous complex traits in model organisms with higher MAC more likely linked with lower fitness. Here we found that PD cases had higher MAC than matched controls. A set of 37564 SNPs with MA (MAF < 0.4) more common in cases (P < 0.05) was found to have the best predictive accuracy. A weighted risk score calculated by using this set can predict 2% of PD cases (100% specificity), which is comparable to using familial PD genes to identify familial PD cases. These results suggest a novel genetic component in PD and provide a useful genetic method to identify a small fraction of PD cases.
| S-EPMC4514478 | biostudies-literature
Project description:Optimal foraging decision is a quantitative flexible behavior, which describes the time at which animals choose to abandon a depleting food supply. The total minor allele content (MAC) in an individual has been shown to correlate with quantitative variations in complex traits. We have studied the role of MAC in the decision to leave a food lawn in recombinant inbred advanced intercross lines (RIAILs) of Caenorhabditis elegans. We found a strong link between MAC and the food lawn leaving rates (Spearman r?=?0.4, P?=?0.005). We identified 28 genes of unknown functions whose expression levels correlated with both MAC and leaving rates. When examined by RNAi experiments, 8 of 10 tested among the 28 affected leaving rates, whereas only 2 of 9 did among genes that were only associated with leaving rates but not MAC (8/10 vs 2/9, P?<?0.05). The results establish a link between MAC and the foraging behavior and identify 8 genes that may play a role in linking MAC with the quantitative nature of the trait. The method of correlations with both MAC and traits may find broad applications in high efficiency identification of target genes for other complex traits in model organisms and humans.
| S-EPMC4652280 | biostudies-literature
Project description:BackgroundEmerging evidence suggests that single nucleotide polymorphisms (SNPs) in microRNA-coding genes may participate in the pathogenesis of lung cancer by altering the expression of tumor-related microRNAs. Several studies were investigated in recent years to evaluate the association between hsa-miR-196a2 rs11614913 polymorphism and increased/decreased lung cancer risk. In the present study, we performed a meta-analysis to systematically summarize the possible association.Methodology/principal findingsWe performed a meta-analysis of 4 case-control studies that included 2219 lung-cancer cases and 2232 cancer-free controls. We evaluated the strength of the association using odds ratios (ORs) with 95% confidence intervals (CIs). In the overall analysis, it was found that the rs11614913 polymorphism significantly elevated the risk of lung cancer (CC versus (vs.) TT OR?=?1.26, 95% CI 1.07-1.49, P?=?0.007; CC/CT vs. TT: OR?=?1.13, 95% CI 0.98-1.29, P?=?0.007; C vs. T: OR?=?1.12, 95% CI 1.03-1.22, P?=?0.008). In the subgroup analysis by ethnicity, statistically significantly increased cancer risk was found among Asians (CC vs. TT: OR?=?1.30, 95% CI 1.10-1.54, P?=?0.003; CT vs. TT: OR?=?1.16, 95% CI 1.01-1.34, P?=?0.039; CC vs. CT/TT: OR?=?1.21, 95% CI 1.04-1.41, P?=?0.012; C vs. T: OR?=?1.14, 95% CI 1.05-1.25, P?=?0.002). For Europeans, a significant association with lung cancer risk was found in recessive model (CC vs. CT/TT: OR?=?0.63, 95% CI 0.40-0.98, P?=?0.040). No publication bias was found in this study.Conclusions/significanceOur meta-analysis suggests that the rs11614913 polymorphism is significant associated with the increased risk of lung cancer, especially in Asians. Besides, the C allele of rs11614913 polymorphism may contribute to increased lung cancer risk.
| S-EPMC3625214 | biostudies-literature
Project description:To understand the funtion of Colorectal cancer GWAS results, we perform a comprehensive analysis using biofeatures of HCT116 colon cancer cell line and got a list of risk-asscociated SNP. Risk-associated SNP are likely exerting their effects through promoters or enhancer. In order to understand the importance of the genes with risk-associated SNP in their promoters and enhancers' putatively targeted genes, we did a comparison of these genes between HCT116 colon cancer cell and normal colon and try to understand their function Two biological replicates of HCT116 were compared to the data of two normal colon samples already deposited in GEO (GSM1010974 and GSM1010942).
2014-10-01 | E-GEOD-52429 | biostudies-arrayexpress
Project description:To understand the funtion of Colorectal cancer GWAS results, we perform a comprehensive analysis using biofeatures of HCT116 colon cancer cell line and got a list of risk-asscociated SNP. Risk-associated SNP are likely exerting their effects through promoters or enhancer. In order to understand the importance of the genes with risk-associated SNP in their promoters and enhancers' putatively targeted genes, we did a comparison of these genes between HCT116 colon cancer cell and normal colon and try to understand their function
2014-10-01 | GSE52429 | GEO
Project description:For African American or Hispanic women, the extent to which clinical breast cancer risk prediction models are improved by including information on susceptibility single nucleotide polymorphisms (SNPs) is unknown, even though these women comprise increasing proportions of the US population and represent a large proportion of the world's population. We studied 7539 African American and 3363 Hispanic women from the Women's Health Initiative. The age-adjusted 5-year risks from the BCRAT and IBIS risk prediction models were measured and combined with a risk score based on >70 independent susceptibility SNPs. Logistic regression, adjusting for age group, was used to estimate risk associations with log-transformed age-adjusted 5-year risks. Discrimination was measured by the odds ratio (OR) per standard deviation (SD) and the area under the receiver operator curve (AUC). When considered alone, the ORs for African American women were 1.28 for BCRAT, and 1.04 for IBIS. When combined with the SNP risk score (OR 1.23), the corresponding ORs were 1.39 and 1.22. For Hispanic women the corresponding ORs were 1.25 for BCRAT, and 1.15 for IBIS. When combined with the SNP risk score (OR 1.39), the corresponding ORs were 1.48 and 1.42. There was no evidence that any of the combined models were not well calibrated. Including information on known breast cancer susceptibility loci provides approximately 10 and 19% improvement in risk prediction using BCRAT for African Americans and Hispanics, respectively. The corresponding figures for IBIS are approximately 18 and 26%, respectively.
| S-EPMC4661211 | biostudies-literature
Project description:BackgroundTP53 encodes a tumor suppressor protein containing cell cycle arrest, apoptosis, senescence, DNA repair, or changes in metabolism. The effect of TP53 inactivation is well-known, and genetically determined smaller variations in TP53 activity are related to cancer. Lung cancer causes the highest rates of morbidity and mortality in the world. Epidemiology studies have assessed the association of TP53 single nucleotide polymorphisms with lung cancer.MethodsWe systematically examined the association of five htSNPs (haplotype-tagging single nucleotide polymorphism) (rs12951053, rs1042522, rs8079544, rs12602273 and rs8064946) across the entire TP53 locus and interaction between genes TP53 and PPP1R13L and CD3EAP and smoking-duration related to lung cancer risk in this Chinese study including 544 cases and 550 controls.ResultsNo significant associations were observed in analysis of alleles and genotypes with co-dominant, dominant, recessive, and log-additive models after adjustment for smoking status. Haplotype analysis showed that haplotype9 (rs12951053A-rs1042522C-rs8079544C-rs12602273G-rs8064946C) [OR (95% CI) = 0.13 (0.03-0.59), p = 0.0079] was associated with decreased risk of lung cancer after adjusted for smoking-duration. The analysis of smoking-duration within TP53 haplotypes showed that there were more carriers of haplotype1 (AGCCG), 2 (CCCGC) and 4 (CCCCG) in smoking-subgroup of >20 (years) (all p < 0.05). MDR testing analysis identified two significant models (both p < 0.0010) of gene-gene-environment interaction in relation to lung cancer risk in whole study group.ConclusionThe present results provide novel evidence that the haplotype of TP53 htSNPs and interaction between genetic variation in TP53 and CD3EAP and smoking-duration may associate with lung cancer risk, and provide additional evidence of association between TP53 htSNP haplotypes and long-term smoking-related behavior.
| S-EPMC9133261 | biostudies-literature
Project description:BackgroundAlthough BRCA1 and BRCA2 mutations account for only ∼27% of the familial aggregation of ovarian cancer (OvC), no OvC risk prediction model currently exists that considers the effects of BRCA1, BRCA2 and other familial factors. Therefore, a currently unresolved problem in clinical genetics is how to counsel women with family history of OvC but no identifiable BRCA1/2 mutations.MethodsWe used data from 1548 patients with OvC and their relatives from a population-based study, with known BRCA1/2 mutation status, to investigate OvC genetic susceptibility models, using segregation analysis methods.ResultsThe most parsimonious model included the effects of BRCA1/2 mutations, and the residual familial aggregation was accounted for by a polygenic component (SD 1.43, 95% CI 1.10 to 1.86), reflecting the multiplicative effects of a large number of genes with small contributions to the familial risk. We estimated that 1 in 630 individuals carries a BRCA1 mutation and 1 in 195 carries a BRCA2 mutation. We extended this model to incorporate the explicit effects of 17 common alleles that are associated with OvC risk. Based on our models, assuming all of the susceptibility genes could be identified we estimate that the half of the female population at highest genetic risk will account for 92% of all OvCs.ConclusionsThe resulting model can be used to obtain the risk of developing OvC on the basis of BRCA1/2, explicit family history and common alleles. This is the first model that accounts for all OvC familial aggregation and would be useful in the OvC genetic counselling process.
| S-EPMC4501173 | biostudies-literature
Project description:We generated a blood-derived transcriptional signature that discriminates patients with lung cancer from non-affected smokers. When applied to blood samples from one of the largest prospective population-based cancer studies (the European Prospective Investigation into Cancer and Nutrition), this signature accurately predicted the occurrence of lung cancer in smokers within two years before the onset of clinical symptoms. Such a blood test could be used as a screening tool to enable early diagnosis of lung cancer at a curable stage. All samples were taken from smokers. EPIC cases were taken from the EPIC trial (a large prospective epidemiological trial in Europe, and are incident cases), Cosmos and BC cases are prevalent cases from a Cologne, Germany based epidemiological trial.
2010-02-28 | E-GEOD-12771 | biostudies-arrayexpress