The role of environmental heterogeneity in meta-analysis of gene-environment interactions with quantitative traits.

abstract：:The aim of this paper is to develop a functional-mixed effects modeling (FMEM) framework for the joint analysis of high-dimensional imaging data in a large number of locations (called voxels) of a three-dimensional volume with a set of genetic markers and clinical covariates. Our FMEM is extremely useful for efficient...

journal_title：Genetic epidemiology

authors： Lin JA,Zhu H,Mihye A,Sun W,Ibrahim JG,Alzheimer's Neuroimaging Initiative.

更新日期：2014-12-01 00:00:00

abstract：:The linkage between electronic health records (EHRs) and genotype data makes it plausible to study the genetic susceptibility of a wide range of disease phenotypes. Despite that EHR-derived phenotype data are subjected to misclassification, it has been shown useful for discovering susceptible genes, particularly in th...

journal_title：Genetic epidemiology

authors： Wang L,Damrauer SM,Zhang H,Zhang AX,Xiao R,Moore JH,Chen J

更新日期：2017-12-01 00:00:00

abstract：:Testing association between a genetic marker and multiple-dependent traits is a challenging task when both binary and quantitative traits are involved. The inverted regression model is a convenient method, in which the traits are treated as predictors although the genetic marker is an ordinal response. It is known tha...

journal_title：Genetic epidemiology

authors： Yan T,Li Q,Li Y,Li Z,Zheng G

更新日期：2013-09-01 00:00:00

abstract：:Increased adiposity has repeatedly been identified as a major risk factor for a variety of chronic diseases. However, the question still remains whether the amount of adipose tissue itself is genetically mediated. To address this question, a segregation analysis, using maximum likelihood techniques as implemented in t...

journal_title：Genetic epidemiology

authors： Comuzzie AG,Blangero J,Mahaney MC,Mitchell BD,Hixson JE,Samollow PB,Stern MP,MacCluer JW

更新日期：1995-01-01 00:00:00

abstract：:Genetic studies are continuing to generate volumes and variety of data that can be used to examine the genetic effects. Often the effect of a genetic variant varies by nongenetic measures, what is traditionally defined as gene-environment interaction (G×E). If the G×E term is neglected, estimates of the main effects c...

journal_title：Genetic epidemiology

authors： Lobach I

更新日期：2018-12-01 00:00:00

abstract：:We develop a Bayesian multi-SNP Markov chain Monte Carlo approach that allows published functional significance scores to objectively inform single nucleotide polymorphism (SNP) prior effect sizes in expression quantitative trait locus (eQTL) studies. We developed the Normal Gamma prior to allow the inclusion of funct...

journal_title：Genetic epidemiology

authors： Boggis EM,Milo M,Walters K

更新日期：2016-05-01 00:00:00

abstract：:This paper summarizes the analyses by participants in the insulin-dependent diabetes mellitus (IDDM) component of Genetic Analysis Workshop 5 (GAW5). The data were obtained from 94 families with two or more IDDM sibs. Topics treated in the Workshop analysis included the following: methods for detecting associations an...

journal_title：Genetic epidemiology

authors： Spielman RS,Baur MP,Clerget-Darpoux F

更新日期：1989-01-01 00:00:00

abstract：:Different maximum likelihood approaches were used to explore the role of candidate genes in the variability of quantitative trait Q1 while accounting for the effects of age, Q2, and Q3. Segregation analysis, under the class D regressive model, provides evidence for a Mendelian gene effect on the adjusted trait Q1. Res...

journal_title：Genetic epidemiology

authors： Martinez M,Abel L,Demenais F

更新日期：1995-01-01 00:00:00

abstract：:Due to the drop in sequencing cost, the number of sequenced genomes is increasing rapidly. To improve power of rare-variant tests, these sequenced samples could be used as external control samples in addition to control samples from the study itself. However, when using external controls, possible batch effects due to...

journal_title：Genetic epidemiology

authors： Lee S,Kim S,Fuchsberger C

更新日期：2017-11-01 00:00:00

abstract：:Meta-analyses of genetic association studies are usually performed using a single polymorphism at a time, even though in many cases the individual studies report results from partially overlapping sets of polymorphisms. We present here a multipoint (or multilocus) method for multivariate meta-analysis of published pop...

journal_title：Genetic epidemiology

authors： Bagos PG,Liakopoulos TD

更新日期：2010-11-01 00:00:00

abstract：:Over the past few years at least 13 transmission/disequilibrium test (TDT)-based tests have been developed for quantitative (Q) traits for the assessment of association or linkage in the presence of the other. A total of six of these QTDT methods were used to analyze log10IgE in the Collaborative Study on the Genetics...

journal_title：Genetic epidemiology

authors： Page GP,Wilcox MA,Occhiuto J,Adak S,Neuberg D,Bajorunaite R,George V

更新日期：2001-01-01 00:00:00

abstract：:Cancer has predominant environmental and somatic causes but the assessment of hereditary (genetic) causes is difficult, except for highly penetrant single-gene causes. Family studies are only partially informative in this regard because family members share diet and life-styles. Twin studies have been classically used...

journal_title：Genetic epidemiology

authors： Hemminki K,Lönnstedt I,Vaittinen P,Lichtenstein P

更新日期：2001-01-01 00:00:00

abstract：:We performed multivariate genetic analyses of cardiovascular risk factors from two sets of data on US and Australian female twins. Similar models for body mass index (BMI), serum low density (LDL) and high density (HDL) lipoproteins, including age as a covariate, were fitted successfully to both groups. These suggeste...

journal_title：Genetic epidemiology

authors： Duffy DL,O'Connell DL,Heller RF,Martin NG

更新日期：1993-01-01 00:00:00

abstract：:Most complex traits such as cancer and coronary heart diseases are attributed either to heritable factors or to environmental factors or to both. Dissecting the genetic and environmental etiology of complex traits thus requires an interdisciplinary research strategy. Genetic studies generally involve families and inve...

journal_title：Genetic epidemiology

authors： Zhao LP,Hsu L,Davidov O,Potter J,Elston RC,Prentice RL

更新日期：1997-01-01 00:00:00

abstract：:Grade of membership analysis (GoM) may have particular relevance for genetic epidemiology. The method can flexibly relate genetic markers, clinical features, and environmental exposures to possible subtypes of disease termed pure types even when population allele frequencies and penetrance functions are not known. Hen...

journal_title：Genetic epidemiology

authors： Corder EH,Woodbury MA

更新日期：1993-01-01 00:00:00

abstract：:alpha 1-antitrypsin (alpha 1 AT) deficiency is variably associated with the development of pulmonary emphysema. To gain insight into the process which begins the Z point mutation at the Protease Inhibitor (Pi) locus and results in the variable development of emphysema, three quantitative phenotypes, including total al...

journal_title：Genetic epidemiology

authors： Silverman EK,Province MA,Campbell EJ,Pierce JA,Rao DC

更新日期：1990-01-01 00:00:00

abstract：:We have conducted a study of renal sodium and potassium reabsorption in 205 pairs of twins on freely chosen diets; 89 of the subjects were studied on more than one occasion. Renal tubular sodium and potassium handling, as measured by the fractional excretions FENa and FEK, show repeatable differences between individua...

journal_title：Genetic epidemiology

authors： Whitfield JB,Martin NG

更新日期：1985-01-01 00:00:00

abstract：:Alcohol dependence often is a familial disorder and has a genetic component. Research in causative factors of alcoholism is coordinated by a multi-center program, COGA [The Collaborative Study on the Genetics of Alcoholism, Begleiter et al., 1995]. We analyzed a subset of the COGA family sample, 84 pedigrees of Caucas...

journal_title：Genetic epidemiology

authors： Windemuth C,Hahn A,Strauch K,Baur MP,Wienker TF

更新日期：1999-01-01 00:00:00

abstract：:This paper presents a projection regression model (PRM) to assess the relationship between a multivariate phenotype and a set of covariates, such as a genetic marker, age, and gender. In the existing literature, a standard statistical approach to this problem is to fit a multivariate linear model to the multivariate p...

journal_title：Genetic epidemiology

authors： Lin JA,Zhu H,Knickmeyer R,Styner M,Gilmore J,Ibrahim JG

更新日期：2012-09-01 00:00:00

abstract：:Three characteristics of genetic epidemiology that distinguish it from its parent disciplines are a focus on population-based research, a focus on the joint effects of genes and the environment, and the incorporation of the underlying biology of the disease into its conceptual models. These principles are illustrated ...

journal_title：Genetic epidemiology

authors： Thomas DC

更新日期：2000-12-01 00:00:00

abstract：:The purpose of the current study was to utilize the Genetic Analysis Workshop 12 simulated data to evaluate fine-mapping strategies for quantitative traits. We approached the analysis as if it was a follow-up to a genome scan that had identified two regions of interest and used the provided 1-cM density microsatellite...

journal_title：Genetic epidemiology

authors： Heard-Costa NL,Demissie S,DeStefano AL,Knowlton BA,Maher NE,Myers RH,Volcjak JS,Wilk JB,Cupples LA

更新日期：2001-01-01 00:00:00

abstract：:Various statistical methods have been proposed to evaluate associations between measured genetic variants and disease, including some using family designs. For breast cancer and rare variants, we applied a modified segregation analysis method that uses the population cancer incidence and population-based case families...

journal_title：Genetic epidemiology

authors： Cui JS,Spurdle AB,Southey MC,Dite GS,Venter DJ,McCredie MR,Giles GG,Chenevix-Trench G,Hopper JL

更新日期：2003-04-01 00:00:00

abstract：:A key aim for current genome-wide association studies (GWAS) is to interrogate the full spectrum of genetic variation underlying human traits, including rare variants, across populations. Deep whole-genome sequencing is the gold standard to fully capture genetic variation, but remains prohibitively expensive for large...

journal_title：Genetic epidemiology

authors： Quick C,Anugu P,Musani S,Weiss ST,Burchard EG,White MJ,Keys KL,Cucca F,Sidore C,Boehnke M,Fuchsberger C

更新日期：2020-09-01 00:00:00

abstract：:The etiology of complex traits likely involves the effects of genetic and environmental factors, along with complicated interaction effects between them. Consequently, there has been interest in applying genetic association tests of complex traits that account for potential modification of the genetic effect in the pr...

journal_title：Genetic epidemiology

authors： Broadaway KA,Duncan R,Conneely KN,Almli LM,Bradley B,Ressler KJ,Epstein MP

更新日期：2015-07-01 00:00:00

abstract：:We contrast the pooling of multiple data sets with the compound HLOD (HLOD-C) and the posterior probability of linkage (PPL), two approaches that have been shown to have more power in the presence of genetic heterogeneity. We also propose and evaluate several multipoint extensions. ...

journal_title：Genetic epidemiology

authors： Van Eerdewegh P,Dowd M,Dupuis J,Falls K,Hayward B,Santangelo SL

更新日期：2001-01-01 00:00:00

abstract：:Mantel statistics provide an additional step to standard approaches in the analysis of gene expression and covariate data, allow the calculation of standard statistics such as correlation, partial correlation, and regression coefficients, and, with permutation tests, provide P values for these statistics to relate the...

journal_title：Genetic epidemiology

authors： Shannon WD,Watson MA,Perry A,Rich K

更新日期：2002-06-01 00:00:00

abstract：:Logistic regression is the primary analysis tool for binary traits in genome-wide association studies (GWAS). Multinomial regression extends logistic regression to multiple categories. However, many phenotypes more naturally take ordered, discrete values. Examples include (a) subtypes defined from multiple sources of ...

journal_title：Genetic epidemiology

authors： German CA,Sinsheimer JS,Klimentidis YC,Zhou H,Zhou JJ

更新日期：2020-04-01 00:00:00

abstract：: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...

journal_title：Genetic epidemiology

authors： Coombes B,Basu S,McGue M

更新日期：2017-07-01 00:00:00

abstract：:We set out to apply conventional analytic methods to a GAW data set of nuclear families with an oligogenic disease that has a population prevalence of 0.023. We chose methods generally applied to disorders with at least one major gene. Our approaches included: 1) complex segregation analysis under two models of ascert...

journal_title：Genetic epidemiology

authors： Falk CT,Ashley A,Lamb N,Sherman SL

更新日期：1995-01-01 00:00:00

abstract：:We used variance-components analysis to investigate the additive genetic effects regulating some of the phenotypes included in the GAW11 data set. Variance-components models were fitted using Gibbs sampling methods in BUGS v 0.6. Linkage analyses for both multivariate normal (MvN) traits and right censored survival ti...

journal_title：Genetic epidemiology

authors： Palmer LJ,Tiller KJ,Burton PR

更新日期：1999-01-01 00:00:00