Literature DB >> 15716906

Genome-wide association studies for common diseases and complex traits.

Joel N Hirschhorn1, Mark J Daly.   

Abstract

Genetic factors strongly affect susceptibility to common diseases and also influence disease-related quantitative traits. Identifying the relevant genes has been difficult, in part because each causal gene only makes a small contribution to overall heritability. Genetic association studies offer a potentially powerful approach for mapping causal genes with modest effects, but are limited because only a small number of genes can be studied at a time. Genome-wide association studies will soon become possible, and could open new frontiers in our understanding and treatment of disease. However, the execution and analysis of such studies will require great care.

Mesh:

Year:  2005        PMID: 15716906     DOI: 10.1038/nrg1521

Source DB:  PubMed          Journal:  Nat Rev Genet        ISSN: 1471-0056            Impact factor:   53.242


  944 in total

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Authors:  Shizhong Xu; Theodore Garland
Journal:  Genetics       Date:  2017-08-03       Impact factor: 4.562

2.  Mapping genes that predict treatment outcome in admixed populations.

Authors:  T M Baye; R A Wilke
Journal:  Pharmacogenomics J       Date:  2010-10-05       Impact factor: 3.550

Review 3.  Genome-wide association studies of chronic kidney disease: what have we learned?

Authors:  Conall M O'Seaghdha; Caroline S Fox
Journal:  Nat Rev Nephrol       Date:  2011-12-06       Impact factor: 28.314

4.  Family-based association tests using genotype data with uncertainty.

Authors:  Zhaoxia Yu
Journal:  Biostatistics       Date:  2011-12-08       Impact factor: 5.899

Review 5.  "Higher order" addiction molecular genetics: convergent data from genome-wide association in humans and mice.

Authors:  George R Uhl; Tomas Drgon; Catherine Johnson; Oluwatosin O Fatusin; Qing-Rong Liu; Carlo Contoreggi; Chuan-Yun Li; Kari Buck; John Crabbe
Journal:  Biochem Pharmacol       Date:  2007-07-25       Impact factor: 5.858

Review 6.  Genetic profiling and individualized assessment of fracture risk.

Authors:  Tuan V Nguyen; John A Eisman
Journal:  Nat Rev Endocrinol       Date:  2013-02-05       Impact factor: 43.330

7.  Estimation of heritability for nine common cancers using data from genome-wide association studies in Chinese population.

Authors:  Juncheng Dai; Wei Shen; Wanqing Wen; Jiang Chang; Tongmin Wang; Haitao Chen; Guangfu Jin; Hongxia Ma; Chen Wu; Lian Li; Fengju Song; YiXin Zeng; Yue Jiang; Jiaping Chen; Cheng Wang; Meng Zhu; Wen Zhou; Jiangbo Du; Yongbing Xiang; Xiao-Ou Shu; Zhibin Hu; Weiping Zhou; Kexin Chen; Jianfeng Xu; Weihua Jia; Dongxin Lin; Wei Zheng; Hongbing Shen
Journal:  Int J Cancer       Date:  2016-10-11       Impact factor: 7.396

Review 8.  Chemical genomics for studying parasite gene function and interaction.

Authors:  Jian Li; Jing Yuan; Ken Chih-Chien Cheng; James Inglese; Xin-zhuan Su
Journal:  Trends Parasitol       Date:  2013-11-09

9.  Testing gene-gene interactions in genome wide association studies.

Authors:  Jie Kate Hu; Xianlong Wang; Pei Wang
Journal:  Genet Epidemiol       Date:  2014-01-15       Impact factor: 2.135

Review 10.  The emerging molecular architecture of schizophrenia, polygenic risk scores and the clinical implications for GxE research.

Authors:  Conrad Iyegbe; Desmond Campbell; Amy Butler; Olesya Ajnakina; Pak Sham
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2014-01-17       Impact factor: 4.328

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