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Find video protocols related to scientific articles indexed in Pubmed.
The IRF5-TNPO3 association with systemic lupus erythematosus has two components that other autoimmune disorders variably share.
Hum. Mol. Genet.
PUBLISHED: 09-08-2014
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Exploiting genotyping, DNA sequencing, imputation and trans-ancestral mapping, we used Bayesian and frequentist approaches to model the IRF5-TNPO3 locus association, now implicated in two immunotherapies and seven autoimmune diseases. Specifically, in systemic lupus erythematosus (SLE), we resolved separate associations in the IRF5 promoter (all ancestries) and with an extended European haplotype. We captured 3230 IRF5-TNPO3 high-quality, common variants across 5 ethnicities in 8395 SLE cases and 7367 controls. The genetic effect from the IRF5 promoter can be explained by any one of four variants in 5.7 kb (P-valuemeta = 6 × 10(-49); OR = 1.38-1.97). The second genetic effect spanned an 85.5-kb, 24-variant haplotype that included the genes IRF5 and TNPO3 (P-valuesEU = 10(-27)-10(-32), OR = 1.7-1.81). Many variants at the IRF5 locus with previously assigned biological function are not members of either final credible set of potential causal variants identified herein. In addition to the known biologically functional variants, we demonstrated that the risk allele of rs4728142, a variant in the promoter among the lowest frequentist probability and highest Bayesian posterior probability, was correlated with IRF5 expression and differentially binds the transcription factor ZBTB3. Our analytical strategy provides a novel framework for future studies aimed at dissecting etiological genetic effects. Finally, both SLE elements of the statistical model appear to operate in Sjögren's syndrome and systemic sclerosis whereas only the IRF5-TNPO3 gene-spanning haplotype is associated with primary biliary cirrhosis, demonstrating the nuance of similarity and difference in autoimmune disease risk mechanisms at IRF5-TNPO3.
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SNP characteristics predict replication success in association studies.
Hum. Genet.
PUBLISHED: 07-10-2014
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Successful independent replication is the most direct approach for distinguishing real genotype-disease associations from false discoveries in genome-wide association studies (GWAS). Selecting SNPs for replication has been primarily based on P values from the discovery stage, although additional characteristics of SNPs may be used to improve replication success. We used disease-associated SNPs from more than 2,000 published GWASs to identify predictors of SNP reproducibility. SNP reproducibility was defined as a proportion of successful replications among all replication attempts. The study reporting association for the first time was considered to be discovery and all consequent studies targeting the same phenotype replications. We found that -Log(P), where P is a P value from the discovery study, is the strongest predictor of the SNP reproducibility. Other significant predictors include type of the SNP (e.g., missense vs intronic SNPs) and minor allele frequency. Features of the genes linked to the disease-associated SNP also predict SNP reproducibility. Based on empirically defined rules, we developed a reproducibility score (RS) to predict SNP reproducibility independently of -Log(P). We used data from two lung cancer GWAS studies as well as recently reported disease-associated SNPs to validate RS. Minus Log(P) outperforms RS when the very top SNPs are selected, while RS works better with relaxed selection criteria. In conclusion, we propose an empirical model to predict SNP reproducibility, which can be used to select SNPs for validation and prioritization.
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Genes with a large intronic burden show greater evolutionary conservation on the protein level.
BMC Evol. Biol.
PUBLISHED: 03-11-2014
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The existence of introns in eukaryotic genes is believed to provide an evolutionary advantage by increasing protein diversity through exon shuffling and alternative splicing. However, this eukaryotic feature is associated with the necessity of exclusion of intronic sequences, which requires considerable energy expenditure and can lead to splicing errors. The relationship between intronic burden and evolution is poorly understood. The goal of this study was to analyze the relationship between the intronic burden and the level of evolutionary conservation of the gene.
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How to get the most from microarray data: advice from reverse genomics.
BMC Genomics
PUBLISHED: 03-10-2014
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Whole-genome profiling of gene expression is a powerful tool for identifying cancer-associated genes. Genes differentially expressed between normal and tumorous tissues are usually considered to be cancer associated. We recently demonstrated that the analysis of interindividual variation in gene expression can be useful for identifying cancer associated genes. The goal of this study was to identify the best microarray data-derived predictor of known cancer associated genes.
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Immunochip analysis identifies multiple susceptibility loci for systemic sclerosis.
Am. J. Hum. Genet.
PUBLISHED: 01-07-2014
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In this study, 1,833 systemic sclerosis (SSc) cases and 3,466 controls were genotyped with the Immunochip array. Classical alleles, amino acid residues, and SNPs across the human leukocyte antigen (HLA) region were imputed and tested. These analyses resulted in a model composed of six polymorphic amino acid positions and seven SNPs that explained the observed significant associations in the region. In addition, a replication step comprising 4,017 SSc cases and 5,935 controls was carried out for several selected non-HLA variants, reaching a total of 5,850 cases and 9,401 controls of European ancestry. Following this strategy, we identified and validated three SSc risk loci, including DNASE1L3 at 3p14, the SCHIP1-IL12A locus at 3q25, and ATG5 at 6q21, as well as a suggested association of the TREH-DDX6 locus at 11q23. The associations of several previously reported SSc risk loci were validated and further refined, and the observed peak of association in PXK was related to DNASE1L3. Our study has increased the number of known genetic associations with SSc, provided further insight into the pleiotropic effects of shared autoimmune risk factors, and highlighted the power of dense mapping for detecting previously overlooked susceptibility loci.
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Modeling the natural history and detection of lung cancer based on smoking behavior.
PLoS ONE
PUBLISHED: 01-01-2014
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In this study, we developed a method for modeling the progression and detection of lung cancer based on the smoking behavior at an individual level. The model allows obtaining the characteristics of lung cancer in a population at the time of diagnosis. Lung cancer data from Surveillance, Epidemiology and End Results (SEER) database collected between 2004 and 2008 were used to fit the lung cancer progression and detection model. The fitted model combined with a smoking based carcinogenesis model was used to predict the distribution of age, gender, tumor size, disease stage and smoking status at diagnosis and the results were validated against independent data from the SEER database collected from 1988 to 1999. The model accurately predicted the gender distribution and median age of LC patients of diagnosis, and reasonably predicted the joint tumor size and disease stage distribution.
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A systemic sclerosis and systemic lupus erythematosus pan-meta-GWAS reveals new shared susceptibility loci.
Hum. Mol. Genet.
PUBLISHED: 06-04-2013
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Systemic sclerosis (SSc) and systemic lupus erythematosus (SLE) are two archetypal systemic autoimmune diseases which have been shown to share multiple genetic susceptibility loci. In order to gain insight into the genetic basis of these diseases, we performed a pan-meta-analysis of two genome-wide association studies (GWASs) together with a replication stage including additional SSc and SLE cohorts. This increased the sample size to a total of 21,109 (6835 cases and 14,274 controls). We selected for replication 19 SNPs from the GWAS data. We were able to validate KIAA0319L (P = 3.31 × 10(-11), OR = 1.49) as novel susceptibility loci for SSc and SLE. Furthermore, we also determined that the previously described SLE susceptibility loci PXK (P = 3.27 × 10(-11), OR = 1.20) and JAZF1 (P = 1.11 × 10(-8), OR = 1.13) are shared with SSc. Supporting these new discoveries, we observed that KIAA0319L was overexpressed in peripheral blood cells of SSc and SLE patients compared with healthy controls. With these, we add three (KIAA0319L, PXK and JAZF1) and one (KIAA0319L) new susceptibility loci for SSc and SLE, respectively, increasing significantly the knowledge of the genetic basis of autoimmunity.
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Associations between dietary intake of choline and betaine and lung cancer risk.
PLoS ONE
PUBLISHED: 02-01-2013
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Evidence from human and animal research indicates that choline metabolic pathways may be activated during a variety of diseases, including cancer. We report results of a case-control study of 2821 lung cancer cases and 2923 controls that assessed associations of choline and betaine dietary intakes with lung cancer. Using multivariable logistic regression analyses, we report a significant association between higher betaine intake and lower lung cancer risk that varied by smoking status. Specifically, no significant association was observed between betaine intake and lung cancer among never-smokers. However, higher betaine intake was significantly associated with reduced lung cancer risk among smokers, and the protective effect was more evident among current than former smokers: for former and current smokers, the ORs (95% CI) of lung cancer for individuals with highest as compared to lowest quartiles of intake were 0.70(0.55-0.88) and 0.51(0.39-0.66) respectively. Significant linear trend of higher betaine intake and lower lung cancer risk was observed among both former (p(trend)?=?0.002) and current (p(trend)<0.0001) smokers. A similar protective effect was also observed with choline intake both in overall analysis as well as among current smokers, with p-values for chi-square tests being 0.001 and 0.004 respectively, but the effect was less evident, as no linear trend was observed. Our results suggest that choline and betaine intake, especially higher betaine intake, may be protective against lung cancer through mitigating the adverse effect of smoking.
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A GWAS follow-up study reveals the association of the IL12RB2 gene with systemic sclerosis in Caucasian populations.
Hum. Mol. Genet.
PUBLISHED: 11-10-2011
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A single-nucleotide polymorphism (SNP) at the IL12RB2 locus showed a suggestive association signal in a previously published genome-wide association study (GWAS) in systemic sclerosis (SSc). Aiming to reveal the possible implication of the IL12RB2 gene in SSc, we conducted a follow-up study of this locus in different Caucasian cohorts. We analyzed 10 GWAS-genotyped SNPs in the IL12RB2 region (2309 SSc patients and 5161 controls). We then selected three SNPs (rs3790567, rs3790566 and rs924080) based on their significance level in the GWAS, for follow-up in an independent European cohort comprising 3344 SSc and 3848 controls. The most-associated SNP (rs3790567) was further tested in an independent cohort comprising 597 SSc patients and 1139 controls from the USA. After conditional logistic regression analysis of the GWAS data, we selected rs3790567 [P(MH)= 1.92 × 10(-5) odds ratio (OR) = 1.19] as the genetic variant with the firmest independent association observed in the analyzed GWAS peak of association. After the first follow-up phase, only the association of rs3790567 was consistent (P(MH)= 4.84 × 10(-3) OR = 1.12). The second follow-up phase confirmed this finding (P(?2) = 2.82 × 10(-4) OR = 1.34). After performing overall pooled-analysis of all the cohorts included in the present study, the association found for the rs3790567 SNP in the IL12RB2 gene region reached GWAS-level significant association (P(MH)= 2.82 × 10(-9) OR = 1.17). Our data clearly support the IL12RB2 genetic association with SSc, and suggest a relevant role of the interleukin 12 signaling pathway in SSc pathogenesis.
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Variants in inflammation genes are implicated in risk of lung cancer in never smokers exposed to second-hand smoke.
Cancer Discov
PUBLISHED: 08-25-2011
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Lung cancer in lifetime never smokers is distinct from that in smokers, but the role of separate or overlapping carcinogenic pathways has not been explored. We therefore evaluated a comprehensive panel of 11,737 single-nucleotide polymorphisms (SNP) in inflammatory-pathway genes in a discovery phase (451 lung cancer cases, 508 controls from Texas). SNPs that were significant were evaluated in a second external population (303 cases, 311 controls from the Mayo Clinic). An intronic SNP in the ACVR1B gene, rs12809597, was replicated with significance and restricted to those reporting adult exposure to environmental tobacco smoke. Another promising candidate was an SNP in NR4A1, although the replication OR did not achieve statistical significance. ACVR1B belongs to the TGFR-? superfamily, contributing to resolution of inflammation and initiation of airway remodeling. An inflammatory microenvironment (second-hand smoking, asthma, or hay fever) is necessary for risk from these gene variants to be expressed. These findings require further replication, followed by targeted resequencing, and functional validation.
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Dietary patterns affect lung cancer risk in never smokers.
Nutr Cancer
PUBLISHED: 07-20-2011
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A number of studies suggest a role of dietary factors as risk predictors of lung cancer in never smokers. However, it is difficult to interpret the observed associations of lung cancer risk with any particular dietary item due to high correlation among different dietary items. In this study, we derived uncorrelated patterns of dietary items in the never smokers and evaluated the association of these patterns with lung cancer risk, using food frequency data from 299 never-smoker lung cancer patients and 317 controls enrolled in an ongoing case-control lung cancer study. We identified 2 major dietary patterns in never smokers: a "healthy eating" pattern including vegetables, fruits, and low-fat food items, and a "mixed dishes" pattern including most foods with positive loadings. Using multivariable regression analysis, we show that the healthy eating pattern is associated with a significant reduction of lung cancer risk among never smokers. The effect of the healthy eating pattern remained significant after adjustment for age, gender, education, caloric intake, secondhand smoke exposure, and family history of cancer. This finding, if confirmed in a prospective study, has a clear preventive significance, by promoting interventions encouraging healthier diets.
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Cigarette smoking is not a risk factor for systemic sclerosis.
Arthritis Rheum.
PUBLISHED: 06-08-2011
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To investigate the association of cigarette smoking with susceptibility to systemic sclerosis (SSc) in a large, well-defined patient population.
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Identification of novel genetic markers associated with clinical phenotypes of systemic sclerosis through a genome-wide association strategy.
PLoS Genet.
PUBLISHED: 05-25-2011
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The aim of this study was to determine, through a genome-wide association study (GWAS), the genetic components contributing to different clinical sub-phenotypes of systemic sclerosis (SSc). We considered limited (lcSSc) and diffuse (dcSSc) cutaneous involvement, and the relationships with presence of the SSc-specific auto-antibodies, anti-centromere (ACA), and anti-topoisomerase I (ATA). Four GWAS cohorts, comprising 2,296 SSc patients and 5,171 healthy controls, were meta-analyzed looking for associations in the selected subgroups. Eighteen polymorphisms were further tested in nine independent cohorts comprising an additional 3,175 SSc patients and 4,971 controls. Conditional analysis for associated SNPs in the HLA region was performed to explore their independent association in antibody subgroups. Overall analysis showed that non-HLA polymorphism rs11642873 in IRF8 gene to be associated at GWAS level with lcSSc (P?=?2.32×10(-12), OR?=?0.75). Also, rs12540874 in GRB10 gene (P?=?1.27 × 10(-6), OR?=?1.15) and rs11047102 in SOX5 gene (P?=?1.39×10(-7), OR?=?1.36) showed a suggestive association with lcSSc and ACA subgroups respectively. In the HLA region, we observed highly associated allelic combinations in the HLA-DQB1 locus with ACA (P?=?1.79×10(-61), OR?=?2.48), in the HLA-DPA1/B1 loci with ATA (P?=?4.57×10(-76), OR?=?8.84), and in NOTCH4 with ACA P?=?8.84×10(-21), OR?=?0.55) and ATA (P?=?1.14×10(-8), OR?=?0.54). We have identified three new non-HLA genes (IRF8, GRB10, and SOX5) associated with SSc clinical and auto-antibody subgroups. Within the HLA region, HLA-DQB1, HLA-DPA1/B1, and NOTCH4 associations with SSc are likely confined to specific auto-antibodies. These data emphasize the differential genetic components of subphenotypes of SSc.
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Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria.
BMC Med Res Methodol
PUBLISHED: 05-11-2011
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Volunteering participants in disease studies tend to be healthier than the general population partially due to specific enrollment criteria. Using modeling to accurately predict outcomes of cohort studies enrolling volunteers requires adjusting for the bias introduced in this way. Here we propose a new method to account for the effect of a specific form of healthy volunteer bias resulting from imposing disease status-related eligibility criteria, on disease-specific mortality, by explicitly modeling the length of the time interval between the moment when the subject becomes ineligible for the study, and the outcome.
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A smoking-based carcinogenesis model for lung cancer risk prediction.
Int. J. Cancer
PUBLISHED: 03-29-2011
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Lung cancer is the leading cancer killer for both men and women worldwide. Over 80% of lung cancers are attributed to smoking. In this analysis, the authors propose to use a two-stage clonal expansion (TSCE) model to predict an individuals lung cancer risk based on gender and smoking history. The TSCE model is traditionally fitted to prospective cohort data. Here, the authors describe a new method that allows for the reconstruction of cohort data from the combination of risk factor data obtained from a case-control study, and tabled incidence/mortality rate data, and discuss alternative approaches. The method is applied to fit a TSCE model based on smoking. The fitted model is validated against independent data from the control arm of a lung cancer chemoprevention trial, CARET, where it accurately predicted the number of lung cancer deaths observed.
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Association of smoking with tumor size at diagnosis in non-small cell lung cancer.
Lung Cancer
PUBLISHED: 02-22-2011
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Tumor size at diagnosis (TSD) indirectly reflects tumor growth rate. The relationship between TSD and smoking is poorly understood. The aim of the study was to determine the relationship between smoking and TSD. We reviewed 1712 newly diagnosed and previously untreated non-small cell lung cancer (NSCLC) patients electronic medical records and collected tumor characteristics. Demographic and epidemiologic characteristics were derived from questionnaires administered during personal interviews. Univariate and multivariate linear regression models were used to evaluate the relationship between TSD and smoking controlling for demographic and clinical factors. We also investigated the relationship between the rs1051730 SNP in an intron of the CHRNA3 gene (the polymorphism most significantly associated with lung cancer risk and smoking behavior) and TSD. We found a strong dose dependent relationship between TSD and smoking. Current smokers had largest and never smokers smallest TSD with former smokers having intermediate TSD. In the multivariate linear regression model, smoking status (never, former, and current), histological type (adenocarcinoma versus SqCC), and gender were significant predictors of TSD. Smoking duration and intensity may explain the gender effect in predicting TSD. We found that the variant allele of rs1051730 in CHRNA3 gene was associated with larger TSD of squamous cell carcinoma. In the multivariate linear regression model, both rs1051730 and smoking were significant predictors for the size of squamous carcinomas. We conclude that smoking is positively associated with lung tumor size at the moment of diagnosis.
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Modeling the mortality reduction due to computed tomography screening for lung cancer.
Cancer
PUBLISHED: 01-10-2011
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The efficacy of computed tomography (CT) screening for lung cancer remains controversial because results from the National Lung Screening Trial are not yet available. In this study, the authors used data from a single-arm CT screening trial to estimate the mortality reduction using a modeling-based approach to construct a control comparison arm.
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Assessment of lung-cancer mortality reduction from CT Screening.
Lung Cancer
PUBLISHED: 09-28-2010
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CT screening has been shown to increase lung cancer curability and we now assess the corresponding reduction in lung cancer mortality.
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Prioritizing genes associated with prostate cancer development.
BMC Cancer
PUBLISHED: 03-25-2010
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The genetic control of prostate cancer development is poorly understood. Large numbers of gene-expression datasets on different aspects of prostate tumorigenesis are available. We used these data to identify and prioritize candidate genes associated with the development of prostate cancer and bone metastases. Our working hypothesis was that combining meta-analyses on different but overlapping steps of prostate tumorigenesis will improve identification of genes associated with prostate cancer development.
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Genome-wide association study of systemic sclerosis identifies CD247 as a new susceptibility locus.
Nat. Genet.
PUBLISHED: 01-04-2010
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Systemic sclerosis (SSc) is an autoimmune disease characterized by fibrosis of the skin and internal organs that leads to profound disability and premature death. To identify new SSc susceptibility loci, we conducted the first genome-wide association study in a population of European ancestry including a total of 2,296 individuals with SSc and 5,171 controls. Analysis of 279,621 autosomal SNPs followed by replication testing in an independent case-control set of European ancestry (2,753 individuals with SSc (cases) and 4,569 controls) identified a new susceptibility locus for systemic sclerosis at CD247 (1q22-23, rs2056626, P = 2.09 x 10(-7) in the discovery samples, P = 3.39 x 10(-9) in the combined analysis). Additionally, we confirm and firmly establish the role of the MHC (P = 2.31 x 10(-18)), IRF5 (P = 1.86 x 10(-13)) and STAT4 (P = 3.37 x 10(-9)) gene regions as SSc genetic risk factors.
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Candidate pathways and genes for prostate cancer: a meta-analysis of gene expression data.
BMC Med Genomics
PUBLISHED: 08-04-2009
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The genetic mechanisms of prostate tumorigenesis remain poorly understood, but with the advent of gene expression array capabilities, we can now produce a large amount of data that can be used to explore the molecular and genetic mechanisms of prostate tumorigenesis.
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GWAS meets microarray: are the results of genome-wide association studies and gene-expression profiling consistent? Prostate cancer as an example.
PLoS ONE
PUBLISHED: 05-11-2009
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Genome-wide association studies (GWASs) and global profiling of gene expression (microarrays) are two major technological breakthroughs that allow hypothesis-free identification of candidate genes associated with tumorigenesis. It is not obvious whether there is a consistency between the candidate genes identified by GWAS (GWAS genes) and those identified by profiling gene expression (microarray genes).
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Estimation of the effects of smoking and DNA repair capacity on coefficients of a carcinogenesis model for lung cancer.
Int. J. Cancer
PUBLISHED: 01-07-2009
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Numerous prospective and retrospective studies have clearly demonstrated a dose-related increased lung cancer risk associated with cigarette smoking, with evidence also for a genetic component to risk. In this study, using the two-stage clonal expansion stochastic model framework, for the first time we investigated the roles of both genetic susceptibility and smoking history in the initiation, clonal expansion, and malignant transformation processes in lung carcinogenesis, integrating information collected by a case-control study and a large-scale prospective cohort study. Our results show that individuals with suboptimal DNA repair capacity have enhanced transition rates of key events in carcinogenesis.
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Building a statistical model for predicting cancer genes.
PLoS ONE
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More than 400 cancer genes have been identified in the human genome. The list is not yet complete. Statistical models predicting cancer genes may help with identification of novel cancer gene candidates. We used known prostate cancer (PCa) genes (identified through KnowledgeNet) as a training set to build a binary logistic regression model identifying PCa genes. Internal and external validation of the model was conducted using a validation set (also from KnowledgeNet), permutations, and external data on genes with recurrent prostate tumor mutations. We evaluated a set of 33 gene characteristics as predictors. Sixteen of the original 33 predictors were significant in the model. We found that a typical PCa gene is a prostate-specific transcription factor, kinase, or phosphatase with high interindividual variance of the expression level in adjacent normal prostate tissue and differential expression between normal prostate tissue and primary tumor. PCa genes are likely to have an antiapoptotic effect and to play a role in cell proliferation, angiogenesis, and cell adhesion. Their proteins are likely to be ubiquitinated or sumoylated but not acetylated. A number of novel PCa candidates have been proposed. Functional annotations of novel candidates identified antiapoptosis, regulation of cell proliferation, positive regulation of kinase activity, positive regulation of transferase activity, angiogenesis, positive regulation of cell division, and cell adhesion as top functions. We provide the list of the top 200 predicted PCa genes, which can be used as candidates for experimental validation. The model may be modified to predict genes for other cancer sites.
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Genome-wide association study reveals novel genetic determinants of DNA repair capacity in lung cancer.
Cancer Res.
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Suboptimal cellular DNA repair capacity (DRC) has been shown to be associated with enhanced cancer risk, but genetic variants affecting the DRC phenotype have not been comprehensively investigated. In this study, with the available DRC phenotype data, we analyzed correlations between the DRC phenotype and genotypes detected by the Illumina 317K platform in 1,774 individuals of European ancestry from a Texas lung cancer genome-wide association study. The discovery phase was followed by a replication in an independent set of 1,374 cases and controls of European ancestry. We applied a generalized linear model with single nucleotide polymorphisms as predictors and DRC (a continuous variable) as the outcome. Covariates of age, sex, pack-years of smoking, DRC assay-related variables, and case-control status of the study participants were adjusted in the model. We validated that reduced DRC was associated with an increased risk of lung cancer in both independent datasets. Several suggestive loci that contributed to the DRC phenotype were defined in ERCC2/XPD, PHACTR2, and DUSP1. In summary, we determined that DRC is an independent risk factor for lung cancer, and we defined several genetic loci contributing to DRC phenotype.
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Chapter 11: Rice-MD Anderson lung cancer model.
Risk Anal.
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The Rice-MD Anderson group uses a two-stage clonal expansion (TSCE) model of lung cancer mortality calibrated to a combination of MD Anderson case-control data on smoking histories and lung cancer mortality/incidence rate data collected from prospective cohorts in order to predict risk of lung cancer. This model is used to simulate lung cancer mortality in the U.S. population under the three scenarios of CISNET lung groups smoking base case project in order to estimate the effect of tobacco control policy on lung cancer mortality rates. Simulation results show that tobacco control policies have achieved 35% of the reduction in lung cancer mortality that would have resulted from cessation of all smoking in 1965.
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Beyond comparing means: the usefulness of analyzing interindividual variation in gene expression for identifying genes associated with cancer development.
J Bioinform Comput Biol
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Identifying genes associated with cancer development is typically accomplished by comparing mean expression values in normal and tumor tissues, which identifies differentially expressed (DE) genes. Interindividual variation (IV) in gene expression is indirectly included in DE gene identification because given the same absolute differences in means, genes with lower variance tend to have lower p-values. We explored the direct use of IV in gene expression to identify candidate genes associated with cancer development. We focused on prostate (PCa) and lung (LC) cancers and compared IV in the expression level of genes shown to be cancer related with that in all other genes in the human genome. Compared with all those other genes, cancer-related genes tended to have greater IV in normal tissues and a greater increase in IV during the transition from normal to tumorous tissue. Genes without significantly different mean expression values between tumor and normal tissues but with greater IV in tumor than in normal tissue (note: the DE-based approach completely ignores those genes) had stronger associations with clinically important features like Gleason score in PCa or tumor histology in LC than all other genes were. Our results suggest that analyzing IV in gene expression level is useful in identifying novel candidate genes associated with cancer development.
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Derived SNP alleles are used more frequently than ancestral alleles as risk-associated variants in common human diseases.
J Bioinform Comput Biol
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Evolutionary aspects of the genetic architecture of common human diseases remain enigmatic. The results of more than 200 genome-wide association studies published to date were compiled in a catalog (). We used cataloged data to determine whether derived (mutant) alleles are associated with higher risk of human disease more frequently than ancestral alleles. We placed all allelic variants into ten categories of population frequency (0%-100%) in 10% increments. We then analyzed the relationship between allelic frequency, evolutionary status of the polymorphic site (ancestral versus derived), and disease risk status (risk versus protection). Given the same population frequency, derived alleles are more likely to be risk associated than ancestral alleles, as are rarer alleles. The common interpretation of this association is that negative selection prevents fixation of the risk variants. However, disease stratification as early or late onset suggests that weak selection against risk-associated alleles is unlikely a major factor shaping genetic architecture of common diseases. Our results clearly suggest that the duration of existence of an allele in a population is more important. Alleles existing longer tend to show weaker linkage disequilibrium with neighboring alleles, including the causal alleles, and are less likely to tag a SNP-disease association.
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Structural analysis of methyl 6-O-benzyl-2-deoxy-2-dimethylmaleimido-?-D-allopyranoside by X-ray crystallography, NMR, and QM calculations: hydrogen bonding and comparison of density functionals.
Carbohydr. Res.
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The crystal structure of methyl 6-O-benzyl-2-deoxy-2-dimethylmaleimido-?-D-allopyranoside was solved in order to gain insight into the hydrogen bond features which can be determining features in the glycosylation regioselectivity observed for this compound. An intramolecular hydrogen bond between the hydroxyl H(O)3 and a carbonyl oxygen from the dimethylmaleoyl (DMM) group was observed. This was in agreement with previous NMR temperature shift determinations and molecular modeling. The determination has also found an intermolecular hydrogen bond between the second hydroxyl H(O)4 and the other carbonyl oxygen (generated by symmetry) from DMM. The crystal structure was optimized by five different functionals, namely the hybrid methods B3LYP, M06-2X, B3PW91, and PBE0, and the pure functional PBE, and the optimized geometries were compared with the crystal geometry and with MM3. An excellent coincidence of the geometries was found with the five quantum methods, with minor details deviating from this coincidence. PBE tends to yield larger bond distances, whereas M06-2X fails slightly to match the exocyclic torsion angles for the sugar moiety. In any case, the differences are small, implying that any of these functionals can accurately emulate the geometries of a complex carbohydrate derivative like this one.
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IRF5 polymorphism predicts prognosis in patients with systemic sclerosis.
Ann. Rheum. Dis.
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The first genome-wide association study (GWAS) of systemic sclerosis (SSc) demonstrated three non-major histocompatibility complex (MHC) susceptibility loci. The goal of this study was to investigate the impact of these gene variants on survival and severity of interstitial lung disease (ILD) in SSc.
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Impact of reduced tobacco smoking on lung cancer mortality in the United States during 1975-2000.
J. Natl. Cancer Inst.
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Considerable effort has been expended on tobacco control strategies in the United States since the mid-1950s. However, we have little quantitative information on how changes in smoking behaviors have impacted lung cancer mortality. We quantified the cumulative impact of changes in smoking behaviors that started in the mid-1950s on lung cancer mortality in the United States over the period 1975-2000.
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Initial medical attention on patients with early-stage non-small cell lung cancer.
PLoS ONE
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Detection of early stage non-small cell lung cancer (NSCLC) is commonly believed to be incidental. Understanding the reasons that caused initial detection of these patients is important for early diagnosis. However, these reasons are not well studied.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.