Literature DB >> 14716719

Genetic association studies in Alzheimer's disease research: challenges and opportunities.

Steven D Edland1, Susan Slager, Matthew Farrer.   

Abstract

Genetic association studies have identified important risk factors for Alzheimer's disease and other diseases. However, the ease with which these methods can be applied and the shear number of polymorphisms in the human genome has led to a well-characterized multiple comparison problem-given the number of genetic variants being tested, it is likely that many of the positive findings reported in the literature to date will prove to be false positive findings explained simply by random fluctuation in data and type I error. The disparity of findings in initial positive reports versus subsequent negative replication studies observed in the Alzheimer's disease literature underscores this problem. The problem of a high false positive rate can be addressed in part by using statistical correction for multiple comparisons in larger and statistically more powerful samples and in meta-analyses of smaller samples. National initiatives are now being considered to address this problem by encouraging sharing of genetic material. Of equal concern in planning future initiatives are methodological issues that are the domain of the epidemiologist. In fact, it is possible that disparate findings across case-control studies reported to date may be explained in part by problems in the design, analysis and interpretation of these studies. The involvement of epidemiologists may improve the situation in this regard. For example, population stratification bias, control selection bias and prevalent case bias can be minimized by careful study design and by appropriate statistical analysis. Regarding interpretation of case-control studies, a more careful consideration of the strength of evidence for a given genetic variant may help to temper enthusiasm for, or appropriately qualify, positive findings. Epidemiologists have well-developed causal criteria for this purpose. This paper reviews the current state of case-control studies of genetic variants in Alzheimer's disease from the epidemiological perspective. The problem of multiple comparisons and a high false positive rate is reviewed. The potential for bias in case-control studies of Alzheimer's disease is reviewed by way of example. Future initiatives to promote case-control studies of genetic variants in Alzheimer's disease can only benefit from increased awareness the tools of epidemiology. Copyright 2004 John Wiley & Sons, Ltd.

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Year:  2004        PMID: 14716719     DOI: 10.1002/sim.1706

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  7 in total

1.  Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE Statement.

Authors:  Julian Little; Julian P T Higgins; John P A Ioannidis; David Moher; France Gagnon; Erik von Elm; Muin J Khoury; Barbara Cohen; George Davey-Smith; Jeremy Grimshaw; Paul Scheet; Marta Gwinn; Robin E Williamson; Guang Yong Zou; Kim Hutchings; Candice Y Johnson; Valerie Tait; Miriam Wiens; Jean Golding; Cornelia van Duijn; John McLaughlin; Andrew Paterson; George Wells; Isabel Fortier; Matthew Freedman; Maja Zecevic; Richard King; Claire Infante-Rivard; Alex Stewart; Nick Birkett
Journal:  Hum Genet       Date:  2009-02-01       Impact factor: 4.132

2.  Insulin-degrading enzyme, apolipoprotein E, and Alzheimer's disease.

Authors:  Steven D Edland
Journal:  J Mol Neurosci       Date:  2004       Impact factor: 3.444

3.  The MAX Statistic is Less Powerful for Genome Wide Association Studies Under Most Alternative Hypotheses.

Authors:  Benjamin Shifflett; Rong Huang; Steven D Edland
Journal:  Int J Stat Med Res       Date:  2017

4.  The Essentiality of Reporting Hardy-Weinberg Equilibrium Calculations in Population-Based Genetic Association Studies.

Authors:  Atefeh Namipashaki; Zahra Razaghi-Moghadam; Naser Ansari-Pour
Journal:  Cell J       Date:  2015-07-11       Impact factor: 2.479

5.  STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement.

Authors:  Julian Little; Julian P T Higgins; John P A Ioannidis; David Moher; France Gagnon; Erik von Elm; Muin J Khoury; Barbara Cohen; George Davey-Smith; Jeremy Grimshaw; Paul Scheet; Marta Gwinn; Robin E Williamson; Guang Yong Zou; Kim Hutchings; Candice Y Johnson; Valerie Tait; Miriam Wiens; Jean Golding; Cornelia van Duijn; John McLaughlin; Andrew Paterson; George Wells; Isabel Fortier; Matthew Freedman; Maja Zecevic; Richard King; Claire Infante-Rivard; Alex Stewart; Nick Birkett
Journal:  PLoS Med       Date:  2009-02-03       Impact factor: 11.069

6.  STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement.

Authors:  Julian Little; Julian P T Higgins; John P A Ioannidis; David Moher; France Gagnon; Erik von Elm; Muin J Khoury; Barbara Cohen; George Davey-Smith; Jeremy Grimshaw; Paul Scheet; Marta Gwinn; Robin E Williamson; Guang Yong Zou; Kim Hutchings; Candice Y Johnson; Valerie Tait; Miriam Wiens; Jean Golding; Cornelia van Duijn; John McLaughlin; Andrew Paterson; George Wells; Isabel Fortier; Matthew Freedman; Maja Zecevic; Richard King; Claire Infante-Rivard; Alex Stewart; Nick Birkett
Journal:  Eur J Clin Invest       Date:  2009-04       Impact factor: 4.686

Review 7.  Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE statement.

Authors:  Julian Little; Julian P T Higgins; John P A Ioannidis; David Moher; France Gagnon; Erik von Elm; Muin J Khoury; Barbara Cohen; George Davey-Smith; Jeremy Grimshaw; Paul Scheet; Marta Gwinn; Robin E Williamson; Guang Yong Zou; Kim Hutchings; Candice Y Johnson; Valerie Tait; Miriam Wiens; Jean Golding; Cornelia van Duijn; John McLaughlin; Andrew Paterson; George Wells; Isabel Fortier; Matthew Freedman; Maja Zecevic; Richard King; Claire Infante-Rivard; Alex Stewart; Nick Birkett
Journal:  Eur J Epidemiol       Date:  2009-02-03       Impact factor: 8.082

  7 in total

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