Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors

Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors

Authors: Laura Almasy, Christopher I Amos, Joan E Bailey-Wilson, Rita M Cantor, Cashell E Jaquish, Maria Martinez, Rosalind J Neuman, Jane M Olson, Lyle J Palmer, Stephen S Rich, M Anne Spence and Jean W MacCluer

Description of the Framingham Heart Study data for Genetic Analysis Workshop 13

Authors: L Adrienne Cupples, Qiong Yang, Serkalem Demissie, Donna Copenhafer and Daniel Levy

Genetic Analysis Workshop 13: Simulated longitudinal data on families for a system of oligogenic traits

The Genetic Analysis Workshop 13 simulated data aimed to mimic the major features of the real Framingham Heart Study data that formed Problem 1, but under a known inheritance model and with 100 replicates, so ...

Authors: E Warwick Daw, John Morrison, Xiaojun Zhou and Duncan C Thomas

Variance components linkage analysis for adjusted systolic blood pressure in the Framingham Heart Study

We performed variance components linkage analysis in nuclear families from the Framingham Heart Study on nine phenotypes derived from systolic blood pressure (SBP). The phenotypes were the maximum and mean SBP...

Authors: Martyn C Byng, Sheila A Fisher, Cathryn M Lewis and John C Whittaker

Use of a random coefficient regression (RCR) model to estimate growth parameters

We used a random coefficient regression (RCR) model to estimate growth parameters for the time series of observed serum glucose levels in the Replicate 1 of the Genetic Analysis Workshop 13 simulated data. For...

Authors: Jonathan Corbett, Aldi Kraja, Ingrid B Borecki and Michael A Province

Linkage analysis of a derived glucose phenotype in the Genetic Analysis Workshop 13 simulated data using a variety of Haseman-Elston based regression methods

Authors: Heather J Cordell, Joanna MM Howson and David G Clayton

Quantitative trait linkage analysis of longitudinal change in body weight

One of the great strengths of the Framingham Heart Study data, provided for the Genetic Analysis Workshop 13, is the long-term survey of phenotypic data. We used this unique data to create new phenotypes repre...

Authors: Astrid Golla, Konstantin Strauch, Johannes Dietter and Max P Baur

An autosome-wide search using longitudinal data for loci linked to type 2 diabetes progression

A genome-wide screen was conducted for type 2 diabetes progression genes using measures of elevated fasting glucose levels as quantitative traits from the offspring enrolled in the Framingham Heart Study. We a...

Authors: Gyungah Jun, Yeunjoo Song, Catherine M Stein and Sudha K Iyengar

Detecting susceptibility genes in case-control studies using set association

Complex diseases are generally caused by intricate interactions of multiple genes and environmental factors. Most available linkage and association methods are developed to identify individual susceptibility g...

Authors: Sung Kim, Kui Zhang and Fengzhu Sun

Using simultaneous equation modeling for defining complex phenotypes

Interactions between multiple biological phenotypes are difficult to model. Simultaneous equation modelling (SEM), as used in econometric modelling, may prove an effective tool for this problem. Generalized li...

Authors: Terri M King

Are there mappable genes for family resemblance for the magnitude of intra-individual variation in systolic blood pressure?

The genetic regulation of variation in intra-individual fluctuations in systolic blood pressure over time is poorly understood. Analysis of the magnitude of the average fluctuation of a person's systolic blood...

Authors: Jennifer Lin, Anthony Hinrichs and Brian K Suarez

Genome-wide linkage analysis of longitudinal phenotypes using σ²_A random effects (SSARs) fitted by Gibbs sampling

The study of change in intermediate phenotypes over time is important in genetics. In this paper we explore a new approach to phenotype definition in the genetic analysis of longitudinal phenotypes. We utilize...

Authors: Lyle J Palmer, Katrina J Scurrah, Martin Tobin, Sanjay R Patel, Juan C Celedon, Paul R Burton and Scott T Weiss

Genome-wide linkage analysis of systolic blood pressure: a comparison of two approaches to phenotype definition

Problem 1 of the Genetic Analysis Workshop 13(GAW13) contains longitudinal data of cardiovascular measurements from 330 pedigrees. The longitudinal data complicates the phenotype definition because multiple me...

Authors: Susan L Slager and Stephen J Iturria

The genetics of cross-sectional and longitudinal body mass index

There has been a lack of consistency in detecting chromosomal loci that are linked to obesity-related traits. This may be due, in part, to the phenotype definition. Many studies use a one-time, single measurem...

Authors: Lisa Strug, Lei Sun and Mary Corey

Empirically derived phenotypic subgroups – qualitative and quantitative trait analyses

The Framingham Heart Study has contributed a great deal to advances in medicine. Most of the phenotypes investigated have been univariate traits (quantitative or qualitative). The aims of this study are to der...

Authors: Marsha A Wilcox, Diego F Wyszynski, Carolien I Panhuysen, Qianli Ma, Agustin Yip, John Farrell and Lindsay A Farrer

Power of maximum HLOD tests to detect linkage to obesity genes

We investigate the power of heterogeneity LOD test to detect linkage when a trait is determined by several major genes using Genetic Analysis Workshop 13 simulated data. We consider three traits, two of which ...

Authors: Yun Joo Yoo, Yanling Huo, Yuming Ning, Derek Gordon, Stephen Finch and Nancy R Mendell

Comparison of longitudinal variance components and regression-based approaches for linkage detection on chromosome 17 for systolic blood pressure

We compare two methods to detect genetic linkage by using serial observations of systolic blood pressure in pedigree data from the Framingham Heart Study focusing on chromosome 17. The first method is a varian...

Authors: Mariza de Andrade and Curtis Olswold

Analysis of gene × environment interactions in sibships using mixed models

Gene × environment models are widely used to assess genetic and environmental risks and their association with a phenotype of interest for many complex diseases. Mixed generalized linear models were used to as...

Authors: Jill S Barnholtz-Sloan, Laila M Poisson, Steven W Coon, Gary A Chase and Benjamin A Rybicki

Multilevel modeling for the analysis of longitudinal blood pressure data in the Framingham Heart Study pedigrees

The data arising from a longitudinal familial study have a complex correlation structure that cannot be modeled using classical methods for the analysis of familial data at a single time point.

Authors: Laurent Briollais, Anjela Tzontcheva and Shelley Bull

Comparison of the linkage results of two phenotypic constructs from longitudinal data in the Framingham Heart Study: analyses on data measured at three time points and on the average of three measurements

Family studies are often conducted in a cross-sectional manner without long-term follow-up data. The relative contribution of a gene to a specific trait could change over the lifetime. The Framingham Heart Stu...

Authors: Rong Cheng, Naeun Park, Susan E Hodge and Suh-Hang Hank Juo

Segregation and linkage analysis for longitudinal measurements of a quantitative trait

We present a method for using slopes and intercepts from a linear regression of a quantitative trait as outcomes in segregation and linkage analyses. We apply the method to the analysis of longitudinal systoli...

Authors: Conway Gee, John L Morrison, Duncan C Thomas and W James Gauderman

Longitudinal variance-components analysis of the Framingham Heart Study data

The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of t...

Authors: Stuart Macgregor, Sara A Knott, Ian White and Peter M Visscher

Comparison of Haseman-Elston regression analyses using single, summary, and longitudinal measures of systolic blood pressure

To compare different strategies for linkage analyses of longitudinal quantitative trait measures, we applied the "revisited" Haseman-Elston (RHE) regression model (the cross product of centered sib-pair trait ...

Authors: Lucia Mirea, Shelley B Bull and James Stafford

Genetic linkage analysis of longitudinal hypertension phenotypes using three summary measures

Longitudinal data often have multiple (repeated) measures recorded along a time trajectory. For example, the two cohorts from the Framingham Heart Study (GAW13 Problem 1) contain 21 and 5 repeated measures for...

Authors: Shaoqi Rao, Lin Li, Xia Li, Kathy L Moser, Zheng Guo, Gongqing Shen, Ruth Cannata, Erich Zirzow, Eric J Topol and Qing Wang

Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling

This paper describes an analysis of systolic blood pressure (SBP) in the Genetic Analysis Workshop 13 (GAW13) simulated data. The main aim was to assess evidence for both general and specific genetic effects o...

Authors: Katrina J Scurrah, Martin D Tobin and Paul R Burton

Linkage analysis of cross-sectional and longitudinally derived phenotypic measures to identify loci influencing blood pressure

The design of appropriate strategies to analyze and interpret linkage results for complex human diseases constitutes a challenge. Parameters such as power, definition of phenotype, and replicability have to be...

Authors: Neil Shephard, Milena Falcaro, Eleftheria Zeggini, Philip Chapman, Anne Hinks, Anne Barton, Jane Worthington, Andrew Pickles and Sally John

Linkage analysis of longitudinal data

We propose a statistical model for linkage analysis of the longitudinal data. The proposed model is a mixed model based on the new Haseman and Elston model and allows several random effects. Specifically, the ...

Authors: Young Ju Suh, Taesung Park and Soo Yeon Cheong

Power of linkage analysis using traits generated from simulated longitudinal data of the Framingham Heart Study

The Framingham Heart Study is a very successful longitudinal research for cardiovascular diseases. The completion of a 10-cM genome scan in Framingham families provided an opportunity to evaluate linkage using...

Authors: Dai Wang, Xiaohui Li, Ying-Chao Lin, Kai Yang, Xiuqing Guo and Huiying Yang

Genetic analyses of longitudinal phenotype data: a comparison of univariate methods and a multivariate approach

We explored three approaches to heritability and linkage analyses of longitudinal total cholesterol levels (CHOL) in the Genetic Analysis Workshop 13 simulated data without knowing the answers. The first two w...

Authors: Qiong Yang, Irmarie Chazaro, Jing Cui, Chao-Yu Guo, Serkalem Demissie, Martin Larson, Larry D Atwood, L Adrienne Cupples and Anita L DeStefano

Consistency of linkage results across exams and methods in the Framingham Heart Study

The repeated measures in the Framingham Heart Study in the Genetic Analysis Workshop 13 data set allow us to test for consistency of linkage results within a study across time. We compared regression-based lin...

Authors: Larry D Atwood, Nancy L Heard-Costa, L Adrienne Cupples and Daniel Levy

Age-Stratified QTL Genome Scan Analyses for Anthropometric Measures

With the availability of longitudinal data, age-specific (stratified) or age-adjusted genetic analyses have the potential to localize different putative trait influencing loci. If age does not influence the lo...

Authors: Stephanie R Beck, W Mark Brown, Adrienne H Williams, June Pierce, Stephen S Rich and Carl D Langefeld

Age-stratified heritability estimation in the Framingham Heart Study families

The Framingham Heart Study provides a unique source of longitudinal family data related to CVD risk factors. Age-stratified heritability estimates were obtained over three age groups (31–49 years, 50–60 years,...

Authors: W Mark Brown, Stephanie R Beck, Ethan M Lange, Cralen C Davis, Christine M Kay, Carl D Langefeld and Stephen S Rich

Sibling recurrence risk ratio analysis of the metabolic syndrome and its components over time

The purpose of this study was to estimate both cross-sectional sibling recurrence risk ratio (λ _s ) and lifetime λ _s for the metabolic s...

Authors: Wei J Chen, Pi-Hua Liu, Yen-Yi Ho, Kuo-Liong Chien, Min-Tzu Lo, Wei-Liang Shih, Yu-Chun Yen and Wen-Chung Lee

Strategy and model building in the fourth dimension: a null model for genotype × age interaction as a Gaussian stationary stochastic process

Using univariate and multivariate variance components linkage analysis methods, we studied possible genotype × age interaction in cardiovascular phenotypes related to the aging process from the Framingham Hear...

Authors: Vincent P Diego, Laura Almasy, Thomas D Dyer, Júlia MP Soler and John Blangero

Genome-wide linkage analysis using cross-sectional and longitudinal traits for body mass index in a subsample of the Framingham Heart Study

To evaluate linkage evidence for body mass index (BMI) using both cross-sectional and longitudinal data, we performed genome-wide multipoint linkage analyses on subjects who had complete data at four selected ...

Authors: Xiaohui Li, Dai Wang, Kai Yang, Xiuqing Guo, Ying-chao Lin, Carlos G Samayoa and Huiying Yang

Comparison of year-of-exam- and age-matched estimates of heritability in the Framingham Heart Study data

Several different approaches can be used to examine generational and temporal trends in family studies. The measurement of offspring and parents can be made over a short period of time with parents and offspri...

Authors: Rasika A Mathias, Marie-Hélène Roy-Gagnon, Cristina M Justice, George J Papanicolaou, Yu Ti Fan, Elizabeth W Pugh and Alexander F Wilson

Lack of reproducibility of linkage results in serially measured blood pressure data

Using the longitudinal Framingham Heart Study data on blood pressure, we analyzed the reproducibility of linkage measures from serial cross-sectional surveys of a defined population by performing genome-wide m...

Authors: Sanjay R Patel, Juan C Celedon, Scott T Weiss and Lyle J Palmer

Stability of exploratory multivariate data modeling in longitudinal data

Exploratory data-driven multivariate analysis provides a means of investigating underlying structure in complex data. To explore the stability of multivariate data modeling, we have applied a common method of ...

Authors: Haydar Sengul and M Michael Barmada

Bootstrap calibration of TRANSMIT for informative missingness of parental genotype data

Informative missingness of parental genotype data occurs when the genotype of a parent influences the probability of the parent's genotype data being observed. Informative missingness can occur in a number of ...

Authors: Andrew S Allen, Julianne S Collins, Paul J Rathouz, Craig L Selander and Glen A Satten

An examination of the genotyping error detection function of SIMWALK2

This investigation was undertaken to assess the sensitivity and specificity of the genotyping error detection function of the computer program SIMWALK2. We chose to examine chromosome 22, which had 7 microsate...

Authors: Michael D Badzioch, Hawkins B DeFrance and Gail P Jarvik

Pedigree and genotype errors in the Framingham Heart Study

The pedigree and genotype data from the Framingham Heart Study were examined for errors. Errors in 21 of 329 pedigrees were detected with the program PREST, and of these the errors in 16 pedigrees were resolve...

Authors: Gerry Brush and Laura Almasy

Imputation methods for missing data for polygenic models

Methods to handle missing data have been an area of statistical research for many years. Little has been done within the context of pedigree analysis. In this paper we present two methods for imputing missing ...

Authors: Brooke Fridley, Kari Rabe and Mariza de Andrade

Multiple imputation methods for longitudinal blood pressure measurements from the Framingham Heart Study

Missing data are a great concern in longitudinal studies, because few subjects will have complete data and missingness could be an indicator of an adverse outcome. Analyses that exclude potentially informative...

Authors: Terri Kang, Peter Kraft, W James Gauderman and Duncan Thomas

Comparison of missing data approaches in linkage analysis

Observational cohort studies have been little used in linkage analyses due to their general lack of large, disease-specific pedigrees. Nevertheless, the longitudinal nature of such studies makes them potential...

Authors: Chao Xing, Fredrick R Schumacher, David V Conti and John S Witte

Interaction of gender and body mass index (BMI) reveals evidence of linkage for hypertension in the Framingham Heart Study

Genetic heterogeneity and complex biologic mechanisms of blood pressure regulation pose significant challenges to the identification of susceptibility loci influencing hypertension. Previous linkage studies ha...

Authors: Denise Daley, Shannon R Edwards, Yeunjoo Song, Dan Baechle, Sobha Puppala, JH Schick, Jane M Olson and Katrina AB Goddard

Comparison of significance level at the true location using two linkage approaches: LODPAL and GENEFINDER

We compare two new software packages for linkage analysis, LODPAL and GENEFINDER. Both allow for covariate adjustment. Replicates 1 to 3 of Genetic Analysis Workshop 13 simulated data sets were used for the an...

Authors: Fang-Chi Hsu, Jacqueline B Hetmanski, Lan Li, Diane Markakis, Kevin Jacobs and Yin Yao Shugart

Genome-wide scan on plasma triglyceride and high density lipoprotein cholesterol levels, accounting for the effects of correlated quantitative phenotypes

Plasma triglyceride and high density lipoprotein cholesterol levels are inversely correlated and both are genetically related. Two correlated traits may be influenced both by shared and unshared genes. The pow...

Authors: Jing-Ping Lin

Transmission ratio distortion in families from the Framingham Heart Study

One implicit assumption in most linkage analysis is that live-born siblings unselected for a phenotype do not share alleles greater than the Mendelian expectation at any particular locus. However, since most f...

Authors: Andrew D Paterson, Lei Sun and Xiao-Qing Liu

Susceptibility scoring in family-based association testing

Family-based association testing is an important part of genetic epidemiology. Tests are available to include multiple siblings, unaffected offspring, and to adjust for environmental covariates. We explore a s...

Authors: Laila M Poisson, Benjamin A Rybicki, Steven W Coon, Jill S Barnholtz-Sloan and Gary A Chase

Adjusting for covariates on a slippery slope: linkage analysis of change over time

We analyzed the Genetic Analysis Workshop 13 (GAW13) simulated data to contrast and compare different methods for the genetic linkage analysis of hypertension and change in blood pressure over time. We also ex...

Authors: Evadnie Rampersaud, Andrew Allen, Yi-Ju Li, Yujun Shao, Meredyth Bass, Carol Haynes, Allison Ashley-Koch, Eden R Martin, Silke Schmidt and Elizabeth R Hauser