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المؤلفون: Megan Carey, Yildiz E. Yilmaz, William G. Pollett, Sevtap Savas, Yajun Yu, Patrick S. Parfrey, Elizabeth Dicks, Jane Green
المصدر: BMC Medicine, Vol 17, Iss 1, Pp 1-12 (2019)
BMC Medicineمصطلحات موضوعية: Male, Oncology, Time Factors, Colorectal cancer, BRAF Val600Glu mutation, lcsh:Medicine, Metastasis, Cohort Studies, Prognostic markers, 0302 clinical medicine, Cancer Survivors, 030212 general & internal medicine, Prospective cohort study, education.field_of_study, Late outcome markers, General Medicine, Middle Aged, Early outcome markers, Prognosis, Time-varying effects, Phenotype, Cohort, Female, Microsatellite Instability, Colorectal Neoplasms, Research Article, Adult, Proto-Oncogene Proteins B-raf, medicine.medical_specialty, Population, Cox model with time-varying effects, Mutation, Missense, Disease-Free Survival, Young Adult, 03 medical and health sciences, Internal medicine, medicine, Humans, education, Long-term follow-up, MSI, Aged, Proportional hazards model, business.industry, lcsh:R, Microsatellite instability, Cancer, medicine.disease, Survival Analysis, Neoplasm Recurrence, Local, business, 030217 neurology & neurosurgery, Follow-Up Studies
الوصف: Background Colorectal cancer is the third most common cancer in the world. In this study, we assessed the long-term survival characteristics and prognostic associations and potential time-varying effects of clinico-demographic variables and two molecular markers (microsatellite instability (MSI) and BRAF Val600Glu mutation) in a population-based patient cohort followed up to ~ 19 years. Methods The patient cohort included 738 incident cases diagnosed between 1999 and 2003. Cox models were used to analyze the association between the variables and a set of survival outcome measures (overall survival (OS), disease-specific survival (DSS), recurrence-free survival (RFS), metastasis-free survival (MFS), recurrence/metastasis-free survival (RMFS), and event-free survival (EFS)). Cox proportional hazard (PH) assumption was tested for all variables, and Cox models with time-varying effects were used if any departure from the PH assumption was detected. Results During the follow-up, ~ 61% patients died from any cause, ~ 26% died from colorectal cancer, and ~ 10% and ~ 20% experienced recurrences and distant metastases, respectively. Stage IV disease and post-diagnostic recurrence or metastasis were strongly linked to risk of death from colorectal cancer. If a patient had survived the first 6 years without any disease-related event (i.e., recurrence, metastasis, or death from colorectal cancer), their risks became very minimal after this time period. Distinct sets of markers were associated with different outcome measures. In some cases, the effects by variables were constant throughout the follow-up. For example, MSI-high tumor phenotype and older age at diagnosis predicted longer MFS times consistently over the follow-up. However, in some other cases, the effects of the variables varied with time. For example, adjuvant radiotherapy treatment was associated with increased risk of metastasis in patients who received this treatment after 5.5 years post-diagnosis, but not before that. Conclusions This study describes the long-term survival characteristics of a prospective cohort of colorectal cancer patients, relationships between baseline variables and a detailed set of patient outcomes over a long time, and time-varying effects of a group of variables. The results presented advance our understanding of the long-term prognostic characteristics in colorectal cancer and are expected to inspire future studies and clinical care strategies. Electronic supplementary material The online version of this article (10.1186/s12916-019-1379-5) contains supplementary material, which is available to authorized users.
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المؤلفون: Patrick S. Parfrey, Michelle E. Penney, Yildiz E. Yilmaz, Sevtap Savas
المصدر: Biomarker Research, Vol 6, Iss 1, Pp 1-10 (2018)
Biomarker Researchمصطلحات موضوعية: 0301 basic medicine, Oncology, medicine.medical_specialty, Genome-wide association study, Rare single nucleotide polymorphisms, Clinical Biochemistry, Single-nucleotide polymorphism, Biology, 03 medical and health sciences, 0302 clinical medicine, Common single nucleotide polymorphisms, Internal medicine, Genetic model, Genotype, Genetic variation, medicine, SNP, Genetic association, Research, Biochemistry (medical), lcsh:RM1-950, medicine.disease, Colorectal cancer, 030104 developmental biology, lcsh:Therapeutics. Pharmacology, 030220 oncology & carcinogenesis, Molecular Medicine, Mucinous Tumor, Mucinous adenocarcinoma
الوصف: Background Colorectal cancer has significant impact on individuals and healthcare systems. Many genes have been identified to influence its pathogenesis. However, the genetic basis of mucinous tumor histology, an aggressive subtype of colorectal cancer, is currently not well-known. This study aimed to identify common and rare genetic variations that are associated with the mucinous tumor phenotype. Methods Genome-wide single nucleotide polymorphism (SNP) data was investigated in a colorectal cancer patient cohort (n = 505). Association analyses were performed for 729,373 common SNPs and 275,645 rare SNPs. Common SNP association analysis was performed using univariable and multivariable logistic regression under different genetic models. Rare-variant association analysis was performed using a multi-marker test. Results No associations reached the traditional genome-wide significance. However, promising genetic associations were identified. The identified common SNPs significantly improved the discriminatory accuracy of the model for mucinous tumor phenotype. Specifically, the area under the receiver operating characteristic curve increased from 0.703 (95% CI: 0.634–0.773) to 0.916 (95% CI: 0.873–0.960) when considering the most significant SNPs. Additionally, the rare variant analysis identified a number of genetic regions that potentially contain causal rare variants associated with the mucinous tumor phenotype. Conclusions This is the first study applying both common and rare variant analyses to identify genetic associations with mucinous tumor phenotype using a genome-wide genotype data. Our results suggested novel associations with mucinous tumors. Once confirmed, these results will not only help us understand the biological basis of mucinous histology, but may also help develop targeted treatment options for mucinous tumors. Electronic supplementary material The online version of this article (10.1186/s40364-018-0133-z) contains supplementary material, which is available to authorized users.
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المؤلفون: Yuan Wang, Yildiz E. Yilmaz, Stefan Konigorski, Candemir Cigsar
المصدر: Genetic Epidemiology
مصطلحات موضوعية: 0301 basic medicine, Epidemiology, Computer science, Datasets as Topic, Inference, Blood Pressure, Estimating equations, Machine learning, computer.software_genre, Polymorphism, Single Nucleotide, 03 medical and health sciences, time‐to‐event phenotype, Statistical inference, Humans, causal inference, Genetic Association Studies, Research Articles, Genetics (clinical), Statistical hypothesis testing, Models, Genetic, business.industry, Genetic Variation, Confounding Factors, Epidemiologic, Directed acyclic graph, Regression, Phenotype, 030104 developmental biology, Cardiovascular and Metabolic Diseases, Research Design, estimating equations, genetic association study, Causal inference, direct effect, directed acyclic graph, Regression Analysis, Graph (abstract data type), Artificial intelligence, business, computer, Software, Research Article
الوصف: In genetic association studies, it is important to distinguish direct and indirect genetic effects in order to build truly functional models. For this purpose, we consider a directed acyclic graph setting with genetic variants, primary and intermediate phenotypes, and confounding factors. In order to make valid statistical inference on direct genetic effects on the primary phenotype, it is necessary to consider all potential effects in the graph, and we propose to use the estimating equations method with robust Huber–White sandwich standard errors. We evaluate the proposed causal inference based on estimating equations (CIEE) method and compare it with traditional multiple regression methods, the structural equation modeling method, and sequential G‐estimation methods through a simulation study for the analysis of (completely observed) quantitative traits and time‐to‐event traits subject to censoring as primary phenotypes. The results show that CIEE provides valid estimators and inference by successfully removing the effect of intermediate phenotypes from the primary phenotype and is robust against measured and unmeasured confounding of the indirect effect through observed factors. All other methods except the sequential G‐estimation method for quantitative traits fail in some scenarios where their test statistics yield inflated type I errors. In the analysis of the Genetic Analysis Workshop 19 dataset, we estimate and test genetic effects on blood pressure accounting for intermediate gene expression phenotypes. The results show that CIEE can identify genetic variants that would be missed by traditional regression analyses. CIEE is computationally fast, widely applicable to different fields, and available as an R package.
وصف الملف: application/pdf; application/msword
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المؤلفون: Sevtap Savas, Jingxiong Xu, Patrick S. Parfrey, Salem Werdyani, Wei Xu, Elizabeth Dicks, Georgia Skardasi, Yildiz E. Yilmaz, Konstantin Shestopaloff, Yajun Yu, Jane Green
المصدر: Cancer Medicine
مصطلحات موضوعية: Male, 0301 basic medicine, Score test, Cancer Research, Familial Colorectal Cancer Type X, DNA Copy Number Variations, Colorectal cancer, colorectal cancer, Bioinformatics, Disease-Free Survival, Germline, 03 medical and health sciences, 0302 clinical medicine, INDEL Mutation, Recurrence, Genetic variation, medicine, Humans, Genetic Predisposition to Disease, markers with time‐varying effects, Radiology, Nuclear Medicine and imaging, Indel, Aged, Original Research, CNVs, Proportional hazards model, business.industry, Clinical Cancer Research, Prognosis, medicine.disease, 3. Good health, 030104 developmental biology, Oncology, 030220 oncology & carcinogenesis, genetic variation, Cohort, Female, relapse‐free survival, Colorectal Neoplasms, business, early‐relapse markers
الوصف: INDELs and CNVs are structural variations that may play roles in cancer susceptibility and patient outcomes. Our objectives were a) to computationally detect and examine the genome‐wide INDEL/CNV profiles in a cohort of colorectal cancer patients, and b) to examine the associations of frequent INDELs/CNVs with relapse‐free survival time. We also identified unique variants in 13 Familial Colorectal Cancer Type X (FCCX) cases. The study cohort consisted of 495 colorectal cancer patients. QuantiSNP and PennCNV algorithms were utilized to predict the INDELs/CNVs using genome‐wide signal intensity data. Duplex PCR was used to validate predictions for 10 variants. Multivariable Cox regression models were used to test the associations of 106 common variants with relapse‐free survival time. Score test and the multivariable Cox proportional hazards models with time‐varying coefficients were applied to identify the variants with time‐varying effects on the relapse‐free survival time. A total of 3486 distinct INDELs/CNVs were identified in the patient cohort. The majority of these variants were rare (83%) and deletion variants (81%). The results of the computational predictions and duplex PCR results were highly concordant (93–100%). We identified four promising variants significantly associated with relapse‐free survival time (P
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المؤلفون: Yildiz E. Yilmaz, Patrick S. Parfrey, Sevtap Savas, Michelle E. Penney
المصدر: BMC Cancer, Vol 19, Iss 1, Pp 1-2 (2019)
مصطلحات موضوعية: 0301 basic medicine, Oncology, Cancer Research, medicine.medical_specialty, business.industry, Colorectal cancer, Microsatellite instability, Cancer, Single-nucleotide polymorphism, Genome-wide association study, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, medicine.disease, lcsh:RC254-282, Metastasis, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, 030220 oncology & carcinogenesis, Internal medicine, Genetic model, Genotype, Genetics, medicine, business
الوصف: Differentiating between cancer patients who will experience metastasis within a short time and who will be long-term survivors without metastasis is a critical aim in healthcare. The microsatellite instability (MSI)-high tumor phenotype is such a differentiator in colorectal cancer, as patients with these tumors are unlikely to experience metastasis. Our aim in this study was to determine if germline genetic variations could further differentiate colorectal cancer patients based on the long-term risk and timing of metastasis. The patient cohort consisted of 379 stage I-III Caucasian colorectal cancer patients with microsatellite stable or MSI-low tumors. We performed univariable analysis on 810,622 common single nucleotide polymorphisms (SNPs) under different genetic models. Depending on the long-term metastasis-free survival probability estimates, we applied a mixture cure model, Cox proportional hazards regression model, or log-rank test. For SNPs reaching Bonferroni-corrected significance (p
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المؤلفون: Yildiz E. Yilmaz, Manuela M. Bergmann, Tobias Pischon, Jürgen Janke, Heiner Boeing, Stefan Konigorski
المصدر: Genetic epidemiologyREFERENCES. 44(1)
مصطلحات موضوعية: Genetic Markers, 0303 health sciences, Multivariate statistics, Models, Genetic, Epidemiology, 030305 genetics & heredity, Univariate, Genetic Variation, Copula (probability theory), 03 medical and health sciences, Phenotype, Rare Diseases, Genetic marker, Covariate, Statistics, Test statistic, Humans, Computer Simulation, Genetics (clinical), Genetic Association Studies, 030304 developmental biology, Mathematics, Genetic association, Type I and type II errors, Genome-Wide Association Study
الوصف: In genetic association studies of rare variants, the low power of association tests is one of the main challenges. In this study, we propose a new single-marker association test called C-JAMP (Copula-based Joint Analysis of Multiple Phenotypes), which is based on a joint model of multiple phenotypes given genetic markers and other covariates. We evaluated its performance and compared its empirical type I error and power with existing univariate and multivariate single-marker and multi-marker rare-variant tests in extensive simulation studies. C-JAMP yielded unbiased genetic effect estimates and valid type I errors with an adjusted test statistic. When strongly dependent traits were jointly analyzed, C-JAMP had the highest power in all scenarios except when a high percentage of variants were causal with moderate/small effect sizes. When traits with weak or moderate dependence were analyzed, whether C-JAMP or competing approaches had higher power depended on the effect size. When C-JAMP was applied with a misspecified copula function, it still achieved high power in some of the scenarios considered. In a real-data application, we analyzed sequencing data using C-JAMP and performed the first genome-wide association studies of high-molecular-weight and medium-molecular-weight adiponectin plasma concentrations. C-JAMP identified 20 rare variants with p-values smaller than 10-5 , while all other tests resulted in the identification of fewer variants with higher p-values. In summary, the results indicate that C-JAMP is a powerful, flexible, and robust method for association studies, and we identified novel candidate markers for adiponectin. C-JAMP is implemented as an R package and freely available from https://cran.r-project.org/package=CJAMP.
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المؤلفون: Amit A. Negandhi, Patrick S. Parfrey, Michelle E. Penney, Yanjing He, Sevtap Savas, Yildiz E. Yilmaz
المصدر: PLoS ONE, Vol 13, Iss 2, p e0192316 (2018)
PLoS ONEمصطلحات موضوعية: 0301 basic medicine, Oncology, Threonine, Heredity, Colorectal cancer, Cancer Treatment, lcsh:Medicine, Metastasis, 0302 clinical medicine, Methionine, XRCC3, Genotype, Basic Cancer Research, Medicine and Health Sciences, Neoplasm Metastasis, lcsh:Science, Multidisciplinary, Prognosis, 3. Good health, DNA-Binding Proteins, Variable number tandem repeat, Genetic Mapping, 030220 oncology & carcinogenesis, Colorectal Neoplasms, Research Article, medicine.medical_specialty, Variant Genotypes, Polymorphism, Single Nucleotide, 03 medical and health sciences, Diagnostic Medicine, Internal medicine, medicine, Genetics, Cancer Detection and Diagnosis, Humans, Differentiated Tumors, Alleles, Colorectal Cancer, Receiver operating characteristic, business.industry, lcsh:R, Cancer, Microsatellite instability, Cancers and Neoplasms, Biology and Life Sciences, Thymidylate Synthase, medicine.disease, 030104 developmental biology, Genetic Loci, lcsh:Q, business
الوصف: Background Metastasis is a major cause of mortality in cancer. Identifying prognostic factors that distinguish patients who will experience metastasis in the short-term and those that will be free of metastasis in the long-term is of particular interest in current medical research. The objective of this study was to examine if select genetic polymorphisms can differentiate colorectal cancer patients based on timing and long-term risk of metastasis. Methods The patient cohort consisted of 402 stage I-III colorectal cancer patients with microsatellite instability (MSI)-low (MSI-L) or microsatellite stable (MSS) tumors. We applied multivariable mixture cure model, which is the proper model when there is a substantial group of patients who remain free of metastasis in the long-term, to 26 polymorphisms. Time-dependent receiver operator characteristic (ROC) curve analysis was performed to determine the change in discriminatory accuracy of the models when the significant SNPs were included. Results After adjusting for significant baseline characteristics, two polymorphisms were significantly associated with time-to-metastasis: TT and TC genotypes of the XRCC3 Thr241Met (p = 0.042) and the 3R/3R genotype of TYMS 5’-UTR variable number tandem repeat (VNTR) (p = 0.009) were associated with decreased time-to-metastasis. ROC curves showed that the discriminatory accuracy of the model is increased slightly when these polymorphisms were added to the significant baseline characteristics. Conclusions Our results indicate XRCC3 Thr241Met and TYMS 5’-UTR VNTR polymorphisms are associated with time-to-metastasis, and may have potential biological roles in expediting the metastatic process. Once replicated, these associations could contribute to the development of precision medicine for colorectal cancer patients.
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المؤلفون: Stefan Konigorski, Tobias Pischon, Yildiz E. Yilmaz
المصدر: PLoS ONE, Vol 12, Iss 5, p e0178504 (2017)
PLoS ONEمصطلحات موضوعية: 0301 basic medicine, Genetic Markers, Heredity, Quantitative Trait Loci, Test Statistics, Gene Identification and Analysis, Normal Distribution, lcsh:Medicine, Blood Pressure, Computational biology, Biology, Quantitative trait locus, Linear Regression Analysis, Research and Analysis Methods, Polymorphism, Single Nucleotide, Vascular Medicine, Statistical power, 03 medical and health sciences, Mathematical and Statistical Techniques, Linear regression, Genetics, Medicine and Health Sciences, Humans, Statistical Methods, lcsh:Science, Statistical hypothesis testing, Genetic association, Multidisciplinary, Quantitative Traits, Simulation and Modeling, lcsh:R, Biology and Life Sciences, Probability Theory, Probability Distribution, Phenotypes, 030104 developmental biology, Cardiovascular and Metabolic Diseases, 13. Climate action, Genetic marker, Sample size determination, Genetic Loci, Physical Sciences, Regression Analysis, lcsh:Q, Mathematics, Statistics (Mathematics), Type I and type II errors, Research Article
الوصف: In genetic association studies of rare variants, low statistical power and potential violations of established estimator properties are among the main challenges of association tests. Multi-marker tests (MMTs) have been proposed to target these challenges, but any comparison with single-marker tests (SMTs) has to consider that their aim is to identify causal genomic regions instead of variants. Valid power comparisons have been performed for the analysis of binary traits indicating that MMTs have higher power, but there is a lack of conclusive studies for quantitative traits. The aim of our study was therefore to fairly compare SMTs and MMTs in their empirical power to identify the same causal loci associated with a quantitative trait. The results of extensive simulation studies indicate that previous results for binary traits cannot be generalized. First, we show that for the analysis of quantitative traits, conventional estimation methods and test statistics of single-marker approaches have valid properties yielding association tests with valid type I error, even when investigating singletons or doubletons. Furthermore, SMTs lead to more powerful association tests for identifying causal genes than MMTs when the effect sizes of causal variants are large, and less powerful tests when causal variants have small effect sizes. For moderate effect sizes, whether SMTs or MMTs have higher power depends on the sample size and percentage of causal SNVs. For a more complete picture, we also compare the power in studies of quantitative and binary traits, and the power to identify causal genes with the power to identify causal rare variants. In a genetic association analysis of systolic blood pressure in the Genetic Analysis Workshop 19 data, SMTs yielded smaller p-values compared to MMTs for most of the investigated blood pressure genes, and were least influenced by the definition of gene regions.
وصف الملف: application/pdf
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المؤلفون: Stefan Konigorski, Yildiz E. Yilmaz, Tobias Pischon
المصدر: BMC Proceedings
Europe PubMed Centralمصطلحات موضوعية: 0301 basic medicine, Genetics, Whole genome sequencing, Copula (linguistics), Univariate, Statistical model, General Medicine, Computational biology, Biology, Genetic analysis, General Biochemistry, Genetics and Molecular Biology, Genetic association analysis, 03 medical and health sciences, Proceedings, 030104 developmental biology, Cardiovascular and Metabolic Diseases, Gene, Genetic association
الوصف: Recent work on genetic association studies suggests that much of the heritable variation in complex traits is unexplained, which indicates a need for using more biologically meaningful modeling approaches and appropriate statistical methods. In this study, we propose a biological framework and a corresponding statistical model incorporating multilevel biological measures, and illustrate it in the analysis of the real data provided by the Genetic Analysis Workshop (GAW) 19, which contains whole genome sequence (WGS), gene expression (GE), and blood pressure (BP) data. We investigate the direct effect of single-nucleotide variants (SNVs) on BP and GE, while considering the non-directional dependence between BP and GE, by using copula functions to jointly model BP and GE conditional on SNVs. We implement the method for analysis on a genome-wide scale, and illustrate it within an association analysis of 68,727 SNVs on chromosome 19 that lie in or around genes with available GE measures. Although there is no indication for inflated type I errors under the proposed method, our results show that the association tests have smaller p values than tests under univariate models for common and rare variants using single-variant tests and gene-based multimarker tests. Hence, considering multilevel biological measures and modeling the dependence structure between these measures by using a plausible graphical approach may lead to more informative findings than standard univariate tests of common variants and well-recognized gene-based rare variant tests.
وصف الملف: application/pdf
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2384e874845f84d5b16297f83ba9ca3a
http://edoc.mdc-berlin.de/16217/1/16217oa.pdf -
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المؤلفون: Shelley B. Bull, Stefan Konigorski, Yildiz E. Yilmaz
المصدر: BMC Proceedings
مصطلحات موضوعية: Censored regression model, 0303 health sciences, business.industry, Univariate, Pedigree chart, General Medicine, Bivariate analysis, Bioinformatics, 01 natural sciences, General Biochemistry, Genetics and Molecular Biology, Copula (probability theory), Correlation, 010104 statistics & probability, 03 medical and health sciences, Blood pressure, Proceedings, Joint probability distribution, Medicine, cardiovascular diseases, 0101 mathematics, business, 030304 developmental biology, circulatory and respiratory physiology
الوصف: We conduct genetic association analysis in the subset of unrelated individuals from the San Antonio Family Studies pedigrees, applying a two-stage approach to take account of the dependence between systolic and diastolic blood pressure (SBP and DBP). In the first stage, we adjust blood pressure for the effects of age, sex, smoking, and use of antihypertensive medication based on a novel modification of censored regression. In the second stage, we model the bivariate distribution of the adjusted SBP and DBP phenotypes by a copula function with interpretable SBP-DBP correlation parameters. This allows us to identify genetic variants associated with each of the adjusted blood pressures, as well as variants that explain the association between the two phenotypes. Within this framework, we define a pleiotropic variant as one that reduces the SBP-DBP correlation. Our results for whole genome sequence variants in the gene ULK4 on chromosome 3 suggest that inference obtained from a copula model can be more informative than findings from the SBP-specific and DBP-specific univariate models alone.
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