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Genetic Epidemiology

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https://www.readbyqxmd.com/read/28643332/integrative-eqtl-analysis-of-tumor-and-host-omics-data-in-individuals-with-bladder-cancer
#1
Silvia Pineda, Kristel Van Steen, Núria Malats
Integrative analyses of several omics data are emerging. The data are usually generated from the same source material (i.e., tumor sample) representing one level of regulation. However, integrating different regulatory levels (i.e., blood) with those from tumor may also reveal important knowledge about the human genetic architecture. To model this multilevel structure, an integrative-expression quantitative trait loci (eQTL) analysis applying two-stage regression (2SR) was proposed. This approach first regressed tumor gene expression levels with tumor markers and the adjusted residuals from the previous model were then regressed with the germline genotypes measured in blood...
June 23, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28636232/a-genetic-stochastic-process-model-for-genome-wide-joint-analysis-of-biomarker-dynamics-and-disease-susceptibility-with-longitudinal-data
#2
Liang He, Ilya Zhbannikov, Konstantin G Arbeev, Anatoliy I Yashin, Alexander M Kulminski
Unraveling the underlying biological mechanisms or pathways behind the effects of genetic variations on complex diseases remains one of the major challenges in the post-GWAS (where GWAS is genome-wide association study) era. To further explore the relationship between genetic variations, biomarkers, and diseases for elucidating underlying pathological mechanism, a huge effort has been placed on examining pleiotropic and gene-environmental interaction effects. We propose a novel genetic stochastic process model (GSPM) that can be applied to GWAS and jointly investigate the genetic effects on longitudinally measured biomarkers and risks of diseases...
June 21, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28626864/detecting-genetic-association-through-shortest-paths-in-a-bidirected-graph
#3
Masao Ueki, Yoshinori Kawasaki, Gen Tamiya
Genome-wide association studies (GWASs) commonly use marginal association tests for each single-nucleotide polymorphism (SNP). Because these tests treat SNPs as independent, their power will be suboptimal for detecting SNPs hidden by linkage disequilibrium (LD). One way to improve power is to use a multiple regression model. However, the large number of SNPs preclude simultaneous fitting with multiple regression, and subset regression is infeasible because of an exorbitant number of candidate subsets. We therefore propose a new method for detecting hidden SNPs having significant yet weak marginal association in a multiple regression model...
June 19, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28580727/integrative-gene-set-enrichment-analysis-utilizing-isoform-specific-expression
#4
Lie Li, Xinlei Wang, Guanghua Xiao, Adi Gazdar
Gene set enrichment analysis (GSEA) aims at identifying essential pathways, or more generally, sets of biologically related genes that are involved in complex human diseases. In the past, many studies have shown that GSEA is a very useful bioinformatics tool that plays critical roles in the innovation of disease prevention and intervention strategies. Despite its tremendous success, it is striking that conclusions of GSEA drawn from isolated studies are often sparse, and different studies may lead to inconsistent and sometimes contradictory results...
June 4, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28580640/region-based-association-tests-for-sequencing-data-on-survival-traits
#5
Li-Chu Chien, Donald W Bowden, Yen-Feng Chiu
Family-based designs enriched with affected subjects and disease associated variants can increase statistical power for identifying functional rare variants. However, few rare variant analysis approaches are available for time-to-event traits in family designs and none of them applicable to the X chromosome. We developed novel pedigree-based burden and kernel association tests for time-to-event outcomes with right censoring for pedigree data, referred to FamRATS (family-based rare variant association tests for survival traits)...
June 4, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28560825/phredem-a-phred-score-informed-genotype-calling-approach-for-next-generation-sequencing-studies
#6
Peizhou Liao, Glen A Satten, Yi-Juan Hu
A fundamental challenge in analyzing next-generation sequencing (NGS) data is to determine an individual's genotype accurately, as the accuracy of the inferred genotype is essential to downstream analyses. Correctly estimating the base-calling error rate is critical to accurate genotype calls. Phred scores that accompany each call can be used to decide which calls are reliable. Some genotype callers, such as GATK and SAMtools, directly calculate the base-calling error rates from phred scores or recalibrated base quality scores...
May 31, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28480976/polygenic-scores-via-penalized-regression-on-summary-statistics
#7
Timothy Shin Heng Mak, Robert Milan Porsch, Shing Wan Choi, Xueya Zhou, Pak Chung Sham
Polygenic scores (PGS) summarize the genetic contribution of a person's genotype to a disease or phenotype. They can be used to group participants into different risk categories for diseases, and are also used as covariates in epidemiological analyses. A number of possible ways of calculating PGS have been proposed, and recently there is much interest in methods that incorporate information available in published summary statistics. As there is no inherent information on linkage disequilibrium (LD) in summary statistics, a pertinent question is how we can use LD information available elsewhere to supplement such analyses...
May 8, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28464407/conditional-analysis-of-multiple-quantitative-traits-based-on-marginal-gwas-summary-statistics
#8
Yangqing Deng, Wei Pan
There has been an increasing interest in joint association testing of multiple traits for possible pleiotropic effects. However, even in the presence of pleiotropy, most of the existing methods cannot distinguish direct and indirect effects of a genetic variant, say single-nucleotide polymorphism (SNP), on multiple traits, and a conditional analysis of a trait adjusting for other traits is perhaps the simplest and most common approach to addressing this question. However, without individual-level genotypic and phenotypic data but with only genome-wide association study (GWAS) summary statistics, as typical with most large-scale GWAS consortium studies, we are not aware of any existing method for such a conditional analysis...
May 2, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28464328/inferring-gene-regulatory-relationships-with-a-high-dimensional-robust-approach
#9
Yangguang Zang, Qing Zhao, Qingzhao Zhang, Yang Li, Sanguo Zhang, Shuangge Ma
Gene expression (GE) levels have important biological and clinical implications. They are regulated by copy number alterations (CNAs). Modeling the regulatory relationships between GEs and CNAs facilitates understanding disease biology and can also have values in translational medicine. The expression level of a gene can be regulated by its cis-acting as well as trans-acting CNAs, and the set of trans-acting CNAs is usually not known, which poses a high-dimensional selection and estimation problem. Most of the existing studies share a common limitation in that they cannot accommodate long-tailed distributions or contamination of GE data...
May 2, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28421636/leveraging-cell-type-specific-regulatory-regions-to-detect-snps-associated-with-tissue-factor-pathway-inhibitor-plasma-levels
#10
Jessica Dennis, Alejandra Medina-Rivera, Vinh Truong, Lina Antounians, Nora Zwingerman, Giovana Carrasco, Lisa Strug, Phil Wells, David-Alexandre Trégouët, Pierre-Emmanuel Morange, Michael D Wilson, France Gagnon
Tissue factor pathway inhibitor (TFPI) regulates the formation of intravascular blood clots, which manifest clinically as ischemic heart disease, ischemic stroke, and venous thromboembolism (VTE). TFPI plasma levels are heritable, but the genetics underlying TFPI plasma level variability are poorly understood. Herein we report the first genome-wide association scan (GWAS) of TFPI plasma levels, conducted in 251 individuals from five extended French-Canadian Families ascertained on VTE. To improve discovery, we also applied a hypothesis-driven (HD) GWAS approach that prioritized single nucleotide polymorphisms (SNPs) in (1) hemostasis pathway genes, and (2) vascular endothelial cell (EC) regulatory regions, which are among the highest expressers of TFPI...
April 18, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28393384/binomirare-a-robust-test-of-the-association-of-a-rare-variant-with-a-disease-for-pooled-analysis-and-meta-analysis-with-application-to-the-hchs-sol
#11
Tamar Sofer
Most regression-based tests of the association between a low-count variant and a binary outcome do not protect type 1 error, especially when tests are rejected based on a very low significance threshold. Noted exception is the Firth test. However, it was recently shown that in meta-analyzing multiple studies all asymptotic, regression-based tests, including the Firth, may not control type 1 error in some settings, and the Firth test may suffer a substantial loss of power. The problem is exacerbated when the case-control proportions differ between studies...
April 10, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28370330/a-combination-test-for-detection-of-gene-environment-interaction-in-cohort-studies
#12
Brandon Coombes, Saonli Basu, Matt McGue
Identifying gene-environment (G-E) interactions can contribute to a better understanding of disease etiology, which may help researchers develop disease prevention strategies and interventions. One big criticism of studying G-E interaction is the lack of power due to sample size. Studies often restrict the interaction search to the top few hundred hits from a genome-wide association study or focus on potential candidate genes. In this paper, we test interactions between a candidate gene and an environmental factor to improve power by analyzing multiple variants within a gene...
March 31, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28393390/a-novel-association-test-for-multiple-secondary-phenotypes-from-a-case-control-gwas
#13
Debashree Ray, Saonli Basu
In the past decade, many genome-wide association studies (GWASs) have been conducted to explore association of single nucleotide polymorphisms (SNPs) with complex diseases using a case-control design. These GWASs not only collect information on the disease status (primary phenotype, D) and the SNPs (genotypes, X), but also collect extensive data on several risk factors and traits. Recent literature and grant proposals point toward a trend in reusing existing large case-control data for exploring genetic associations of some additional traits (secondary phenotypes, Y) collected during the study...
July 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28393391/inclusion-of-biological-knowledge-in-a-bayesian-shrinkage-model-for-joint-estimation-of-snp-effects
#14
Miguel Pereira, John R Thompson, Christian X Weichenberger, Duncan C Thomas, Cosetta Minelli
With the aim of improving detection of novel single-nucleotide polymorphisms (SNPs) in genetic association studies, we propose a method of including prior biological information in a Bayesian shrinkage model that jointly estimates SNP effects. We assume that the SNP effects follow a normal distribution centered at zero with variance controlled by a shrinkage hyperparameter. We use biological information to define the amount of shrinkage applied on the SNP effects distribution, so that the effects of SNPs with more biological support are less shrunk toward zero, thus being more likely detected...
May 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28378447/a-genome-wide-linkage-and-association-analysis-of-imputed-insertions-and-deletions-with-cardiometabolic-phenotypes-in-mexican-americans-the-insulin-resistance-atherosclerosis-family-study
#15
Chuan Gao, Fang-Chi Hsu, Latchezar M Dimitrov, Hayrettin Okut, Yii-Der I Chen, Kent D Taylor, Jerome I Rotter, Carl D Langefeld, Donald W Bowden, Nicholette D Palmer
Insertions and deletions (INDELs) represent a significant fraction of interindividual variation in the human genome yet their contribution to phenotypes is poorly understood. To confirm the quality of imputed INDELs and investigate their roles in mediating cardiometabolic phenotypes, genome-wide association and linkage analyses were performed for 15 phenotypes with 1,273,952 imputed INDELs in 1,024 Mexican-origin Americans. Imputation quality was validated using whole exome sequencing with an average kappa of 0...
May 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28318110/on-the-association-analysis-of-genome-sequencing-data-a-spatial-clustering-approach-for-partitioning-the-entire-genome-into-nonoverlapping-windows
#16
Heide Loehlein Fier, Dmitry Prokopenko, Julian Hecker, Michael H Cho, Edwin K Silverman, Scott T Weiss, Rudolph E Tanzi, Christoph Lange
For the association analysis of whole-genome sequencing (WGS) studies, we propose an efficient and fast spatial-clustering algorithm. Compared to existing analysis approaches for WGS data, that define the tested regions either by sliding or consecutive windows of fixed sizes along variants, a meaningful grouping of nearby variants into consecutive regions has the advantage that, compared to sliding window approaches, the number of tested regions is likely to be smaller. In comparison to consecutive, fixed-window approaches, our approach is likely to group nearby variants together...
May 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28317167/semiparametric-methods-for-estimation-of-a-nonlinear-exposure-outcome-relationship-using-instrumental-variables-with-application-to-mendelian-randomization
#17
James R Staley, Stephen Burgess
Mendelian randomization, the use of genetic variants as instrumental variables (IV), can test for and estimate the causal effect of an exposure on an outcome. Most IV methods assume that the function relating the exposure to the expected value of the outcome (the exposure-outcome relationship) is linear. However, in practice, this assumption may not hold. Indeed, often the primary question of interest is to assess the shape of this relationship. We present two novel IV methods for investigating the shape of the exposure-outcome relationship: a fractional polynomial method and a piecewise linear method...
May 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28300291/are-rare-variants-really-independent
#18
Asuman Turkmen, Shili Lin
Recent advances in genotyping with high-density markers allow researchers access to genomic variants including rare ones. Linkage disequilibrium (LD) is widely used to provide insight into evolutionary history. It is also the basis for association mapping in humans and other species. Better understanding of the genomic LD structure may lead to better-informed statistical tests that can improve the power of association studies. Although rare variant associations with common diseases (RVCD) have been extensively studied recently, there is very limited understanding, and even controversial view of LD structures among rare variants and between rare and common variants...
May 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28211093/gsskat-rapid-gene-set-analysis-and-multiple-testing-correction-for-rare-variant-association-studies-using-weighted-linear-kernels
#19
Nicholas B Larson, Shannon McDonnell, Lisa Cannon Albright, Craig Teerlink, Janet Stanford, Elaine A Ostrander, William B Isaacs, Jianfeng Xu, Kathleen A Cooney, Ethan Lange, Johanna Schleutker, John D Carpten, Isaac Powell, Joan E Bailey-Wilson, Olivier Cussenot, Geraldine Cancel-Tassin, Graham G Giles, Robert J MacInnis, Christiane Maier, Alice S Whittemore, Chih-Lin Hsieh, Fredrik Wiklund, William J Catolona, William Foulkes, Diptasri Mandal, Rosalind Eeles, Zsofia Kote-Jarai, Michael J Ackerman, Timothy M Olson, Christopher J Klein, Stephen N Thibodeau, Daniel J Schaid
Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data...
May 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28198095/genetic-risk-models-influence-of-model-size-on-risk-estimates-and-precision
#20
Ying Shan, Gerard Tromp, Helena Kuivaniemi, Diane T Smelser, Shefali S Verma, Marylyn D Ritchie, James R Elmore, David J Carey, Yvette P Conley, Michael B Gorin, Daniel E Weeks
Disease risk estimation plays an important role in disease prevention. Many studies have found that the ability to predict risk improves as the number of risk single-nucleotide polymorphisms (SNPs) in the risk model increases. However, the width of the confidence interval of the risk estimate is often not considered in the evaluation of the risk model. Here, we explore how the risk and the confidence interval width change as more SNPs are added to the model in the order of decreasing effect size, using both simulated data and real data from studies of abdominal aortic aneurysms and age-related macular degeneration...
May 2017: Genetic Epidemiology
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