Literature DB >> 10486333

Joint multipoint linkage analysis of multivariate qualitative and quantitative traits. I. Likelihood formulation and simulation results.

J T Williams1, P Van Eerdewegh, L Almasy, J Blangero.   

Abstract

We describe a variance-components method for multipoint linkage analysis that allows joint consideration of a discrete trait and a correlated continuous biological marker (e.g., a disease precursor or associated risk factor) in pedigrees of arbitrary size and complexity. The continuous trait is assumed to be multivariate normally distributed within pedigrees, and the discrete trait is modeled by a threshold process acting on an underlying multivariate normal liability distribution. The liability is allowed to be correlated with the quantitative trait, and the liability and quantitative phenotype may each include covariate effects. Bivariate discrete-continuous observations will be common, but the method easily accommodates qualitative and quantitative phenotypes that are themselves multivariate. Formal likelihood-based tests are described for coincident linkage (i.e., linkage of the traits to distinct quantitative-trait loci [QTLs] that happen to be linked) and pleiotropy (i.e., the same QTL influences both discrete-trait status and the correlated continuous phenotype). The properties of the method are demonstrated by use of simulated data from Genetic Analysis Workshop 10. In a companion paper, the method is applied to data from the Collaborative Study on the Genetics of Alcoholism, in a bivariate linkage analysis of alcoholism diagnoses and P300 amplitude of event-related brain potentials.

Mesh:

Year:  1999        PMID: 10486333      PMCID: PMC1288247          DOI: 10.1086/302570

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  61 in total

1.  An empirical test of the significance of an observed quantitative trait locus effect that preserves additive genetic variation.

Authors:  S J Iturria; J T Williams; L Almasy; T D Dyer; J Blangero
Journal:  Genet Epidemiol       Date:  1999       Impact factor: 2.135

2.  A multivariate method for detecting genetic linkage, with application to a pedigree with an adverse lipoprotein phenotype.

Authors:  C I Amos; R C Elston; G E Bonney; B J Keats; G S Berenson
Journal:  Am J Hum Genet       Date:  1990-08       Impact factor: 11.025

3.  Solution of multiple trait animal models with missing data on some traits.

Authors:  V Ducrocq; B Besbes
Journal:  J Anim Breed Genet       Date:  1993-01-12       Impact factor: 2.380

4.  Linkage of multilocus components of variance to polymorphic markers.

Authors:  H K Tiwari; R C Elston
Journal:  Ann Hum Genet       Date:  1997-05       Impact factor: 1.670

5.  Combined linkage and segregation analysis using regressive models.

Authors:  G E Bonney; G M Lathrop; J M Lalouel
Journal:  Am J Hum Genet       Date:  1988-07       Impact factor: 11.025

6.  Multifactorial qualitative traits: genetic analysis and prediction of recurrence risks.

Authors:  N R Mendell; R C Elston
Journal:  Biometrics       Date:  1974-03       Impact factor: 2.571

7.  Statistical genetic approaches to human adaptability.

Authors:  J Blangero
Journal:  Hum Biol       Date:  1993-12       Impact factor: 0.553

8.  Event-related brain potentials in boys at risk for alcoholism.

Authors:  H Begleiter; B Porjesz; B Bihari; B Kissin
Journal:  Science       Date:  1984-09-28       Impact factor: 47.728

9.  Use of robust variance components models to analyse triglyceride data in families.

Authors:  T H Beaty; S G Self; K Y Liang; M A Connolly; G A Chase; P O Kwiterovich
Journal:  Ann Hum Genet       Date:  1985-10       Impact factor: 1.670

10.  Study of the genetic transmission of hypercholesterolemia and hypertriglyceridemia in a 195 member kindred.

Authors:  R C Elston; K K Namboodiri; C J Glueck; R Fallat; R Tsang; V Leuba
Journal:  Ann Hum Genet       Date:  1975-07       Impact factor: 1.670

View more
  84 in total

1.  Enhanced efficiency of quantitative trait loci mapping analysis based on multivariate complexes of quantitative traits.

Authors:  A B Korol; Y I Ronin; A M Itskovich; J Peng; E Nevo
Journal:  Genetics       Date:  2001-04       Impact factor: 4.562

2.  Genetics of event-related brain potentials in response to a semantic priming paradigm in families with a history of alcoholism.

Authors:  L Almasy; B Porjesz; J Blangero; A Goate; H J Edenberg; D B Chorlian; S Kuperman; S J O'Connor; J Rohrbaugh; L O Bauer; T Foroud; J P Rice; T Reich; H Begleiter
Journal:  Am J Hum Genet       Date:  2000-12-01       Impact factor: 11.025

3.  A genomewide linkage scan for quantitative-trait loci for obesity phenotypes.

Authors:  Hong-Wen Deng; Hongyi Deng; Yong-Jun Liu; Yao-Zhong Liu; Fu-Hua Xu; Hui Shen; Theresa Conway; Jin-Long Li; Qing-Yang Huang; K M Davies; Robert R Recker
Journal:  Am J Hum Genet       Date:  2002-03-28       Impact factor: 11.025

Review 4.  Searching for the mountains of the moon: genome scans for atherosclerosis.

Authors:  Michael A Province
Journal:  Curr Atheroscler Rep       Date:  2002-05       Impact factor: 5.113

5.  Human plasma lipidome is pleiotropically associated with cardiovascular risk factors and death.

Authors:  Claire Bellis; Hemant Kulkarni; Manju Mamtani; Jack W Kent; Gerard Wong; Jacquelyn M Weir; Christopher K Barlow; Vincent Diego; Marcio Almeida; Thomas D Dyer; Harald H H Göring; Laura Almasy; Michael C Mahaney; Anthony G Comuzzie; Sarah Williams-Blangero; Peter J Meikle; John Blangero; Joanne E Curran
Journal:  Circ Cardiovasc Genet       Date:  2014-11-02

6.  Genetic factors influence serological measures of common infections.

Authors:  Rohina Rubicz; Charles T Leach; Ellen Kraig; Nikhil V Dhurandhar; Ravindranath Duggirala; John Blangero; Robert Yolken; Harald H H Göring
Journal:  Hum Hered       Date:  2011-10-11       Impact factor: 0.444

Review 7.  How pleiotropic genetics of the musculoskeletal system can inform genomics and phenomics of aging.

Authors:  David Karasik
Journal:  Age (Dordr)       Date:  2010-07-02

8.  Bone Strength Estimated by Micro-Finite Element Analysis (µFEA) Is Heritable and Shares Genetic Predisposition With Areal BMD: The Framingham Study.

Authors:  David Karasik; Serkalem Demissie; Darlene Lu; Kerry E Broe; Steven K Boyd; Ching-Ti Liu; Yi-Hsiang Hsu; Mary L Bouxsein; Douglas P Kiel
Journal:  J Bone Miner Res       Date:  2017-07-19       Impact factor: 6.741

9.  Susceptibility loci for adiposity phenotypes on 8p, 9p, and 16q in American Samoa and Samoa.

Authors:  Karolina Aberg; Feng Dai; Guangyun Sun; Ember D Keighley; Subba R Indugula; Sarah T Roberts; Qi Zhang; Diane Smelser; Satupaitea Viali; John Tuitele; Li Jin; Ranjan Deka; Daniel E Weeks; Stephen T McGarvey
Journal:  Obesity (Silver Spring)       Date:  2008-12-18       Impact factor: 5.002

10.  Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies.

Authors:  Anderson M Winkler; Peter Kochunov; John Blangero; Laura Almasy; Karl Zilles; Peter T Fox; Ravindranath Duggirala; David C Glahn
Journal:  Neuroimage       Date:  2009-12-16       Impact factor: 6.556

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.