Literature DB >> 11308071

Family-based association studies.

H Zhao1.   

Abstract

Over the past decade, attention has turned from positional cloning of Mendelian disease genes to the dissection of complex diseases. Both theoretical and empirical studies have shown that traditional linkage studies may be inferior in power compared to studies that directly utilize allele status. Case-control association studies, as an alternative, are subject to bias due to population stratification. As a compromise between linkage studies and case-control studies, family-based association designs have received great attention recently due to their potentially higher power to identify complex disease genes and their robustness in the presence of population substructure. In this review, we first describe the basic family-based association design involving one affected offspring with its two parents, all genotyped for a biallelic genetic marker. Extensions of the original transmission disequilibrium tests to multiallelic markers, families with multiple siblings, families with incomplete parental genotypes, and general pedigree structures are discussed. Further developments of statistical methods to study quantitative traits, to analyse genes on the X chromosome, to incorporate multiple tightly linked markers, to identify imprinting genes, and to detect gene-environment interactions are also reviewed. Finally, we discuss the implications of the completion of the Human Genome Project and the identification of hundreds of thousands of genetic polymorphisms on employing family-based association designs to search for complex disease genes.

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Year:  2000        PMID: 11308071     DOI: 10.1177/096228020000900604

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  8 in total

1.  Power calculations for a general class of family-based association tests: dichotomous traits.

Authors:  Christoph Lange; Nan M Laird
Journal:  Am J Hum Genet       Date:  2002-08-12       Impact factor: 11.025

2.  Using the noninformative families in family-based association tests: a powerful new testing strategy.

Authors:  Christoph Lange; Dawn DeMeo; Edwin K Silverman; Scott T Weiss; Nan M Laird
Journal:  Am J Hum Genet       Date:  2003-09-18       Impact factor: 11.025

3.  Semiparametric Bayesian modeling of random genetic effects in family-based association studies.

Authors:  Li Zhang; Bhramar Mukherjee; Bo Hu; Victor Moreno; Kathleen A Cooney
Journal:  Stat Med       Date:  2009-01-15       Impact factor: 2.373

4.  Association of TMEM106B gene polymorphism with age at onset in granulin mutation carriers and plasma granulin protein levels.

Authors:  Carlos Cruchaga; Caroline Graff; Huei-Hsin Chiang; Jun Wang; Anthony L Hinrichs; Noah Spiegel; Sarah Bertelsen; Kevin Mayo; Joanne B Norton; John C Morris; Alison Goate
Journal:  Arch Neurol       Date:  2011-01-10

Review 5.  Analysis of genetically complex epilepsies.

Authors:  Ruth Ottman
Journal:  Epilepsia       Date:  2005       Impact factor: 5.864

6.  Linkage and association of myocilin (MYOC) polymorphisms with high myopia in a Chinese population.

Authors:  Wing Chun Tang; Shea Ping Yip; Ka Kin Lo; Po Wah Ng; Pik Shan Choi; Sau Yin Lee; Maurice K H Yap
Journal:  Mol Vis       Date:  2007-04-04       Impact factor: 2.367

7.  Family-based versus unrelated case-control designs for genetic associations.

Authors:  Evangelos Evangelou; Thomas A Trikalinos; Georgia Salanti; John P A Ioannidis
Journal:  PLoS Genet       Date:  2006-06-26       Impact factor: 5.917

8.  Family-based exome-wide association study of childhood acute lymphoblastic leukemia among Hispanics confirms role of ARID5B in susceptibility.

Authors:  Natalie P Archer; Virginia Perez-Andreu; Ulrik Stoltze; Michael E Scheurer; Anna V Wilkinson; Ting-Nien Lin; Maoxiang Qian; Charnise Goodings; Michael D Swartz; Nalini Ranjit; Karen R Rabin; Erin C Peckham-Gregory; Sharon E Plon; Pedro A de Alarcon; Ryan C Zabriskie; Federico Antillon-Klussmann; Cesar R Najera; Jun J Yang; Philip J Lupo
Journal:  PLoS One       Date:  2017-08-17       Impact factor: 3.240

  8 in total

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