Literature DB >> 12727138

Genetic associations: false or true?

John P A Ioannidis1.   

Abstract

Genetic association studies for multigenetic diseases are like fishing for the truth in a sea of trillions of candidate analyses. Red herrings are unavoidably common, and bias might cause serious misconceptions. However, a sizeable proportion of identified genetic associations are probably true. Meta-analysis, a rigorous, comprehensive, quantitative synthesis of all the available data, might help us to separate the true from the false.

Mesh:

Year:  2003        PMID: 12727138     DOI: 10.1016/s1471-4914(03)00030-3

Source DB:  PubMed          Journal:  Trends Mol Med        ISSN: 1471-4914            Impact factor:   11.951


  82 in total

Review 1.  "Are we there yet?": Deciding when one has demonstrated specific genetic causation in complex diseases and quantitative traits.

Authors:  Grier P Page; Varghese George; Rodney C Go; Patricia Z Page; David B Allison
Journal:  Am J Hum Genet       Date:  2003-09-17       Impact factor: 11.025

2.  The future of association studies: gene-based analysis and replication.

Authors:  Benjamin M Neale; Pak C Sham
Journal:  Am J Hum Genet       Date:  2004-07-22       Impact factor: 11.025

3.  Large scale evidence and replication: insights from rheumatology and beyond.

Authors:  J P A Ioannidis
Journal:  Ann Rheum Dis       Date:  2004-09-30       Impact factor: 19.103

4.  The prediction of disease risk in genomic medicine.

Authors:  Wayne D Hall; Katherine I Morley; Jayne C Lucke
Journal:  EMBO Rep       Date:  2004-10       Impact factor: 8.807

Review 5.  A systematic review evaluating the methodological aspects of meta-analyses of genetic association studies in cancer research.

Authors:  Stefania Boccia; Emma De Feo; Paola Gallì; Francesco Gianfagna; Rosarita Amore; Gualtiero Ricciardi
Journal:  Eur J Epidemiol       Date:  2010-09-10       Impact factor: 8.082

6.  Replication of past candidate loci for common diseases and phenotypes in 100 genome-wide association studies.

Authors:  Konstantinos C M Siontis; Nikolaos A Patsopoulos; John P A Ioannidis
Journal:  Eur J Hum Genet       Date:  2010-03-17       Impact factor: 4.246

Review 7.  Genes and human elite athletic performance.

Authors:  Daniel G Macarthur; Kathryn N North
Journal:  Hum Genet       Date:  2005-02-22       Impact factor: 4.132

8.  Molecular bias.

Authors:  John P A Ioannidis
Journal:  Eur J Epidemiol       Date:  2005       Impact factor: 8.082

9.  A fast method for computing high-significance disease association in large population-based studies.

Authors:  Gad Kimmel; Ron Shamir
Journal:  Am J Hum Genet       Date:  2006-07-24       Impact factor: 11.025

Review 10.  The integration of genomics into obstetrics and gynecology: a HuGE challenge.

Authors:  Muin J Khoury; Roberto Romero
Journal:  Am J Obstet Gynecol       Date:  2006-12       Impact factor: 8.661

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