Literature DB >> 17110744

Genetic association studies of complex neurological diseases.

P M Abou-Sleiman1, M G Hanna, N W Wood.   

Abstract

Genetic association studies offer a powerful approach to identify the multiple variants of small effect that modulate susceptibility to common, complex disease. They, however, have a poor reputation, mainly because of the consistent lack of replication of all but a few. Thousands of genetic studies have been carried out on multifactorial diseases in the past 30 years, yielding only about 50 variants that can be considered to be true positives. Although the positive studies show proof of principle, the multitude of negative studies indicate fundamental problems in the design and execution of association studies. Here, we discuss some of the more pertinent study design and data analysis issues which can affect the outcome of genetic association studies.

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Year:  2006        PMID: 17110744      PMCID: PMC2077426          DOI: 10.1136/jnnp.2005.082024

Source DB:  PubMed          Journal:  J Neurol Neurosurg Psychiatry        ISSN: 0022-3050            Impact factor:   10.154


  16 in total

1.  Use of unlinked genetic markers to detect population stratification in association studies.

Authors:  J K Pritchard; N A Rosenberg
Journal:  Am J Hum Genet       Date:  1999-07       Impact factor: 11.025

Review 2.  Population stratification and spurious allelic association.

Authors:  Lon R Cardon; Lyle J Palmer
Journal:  Lancet       Date:  2003-02-15       Impact factor: 79.321

Review 3.  Genetic associations in large versus small studies: an empirical assessment.

Authors:  John P A Ioannidis; Thomas A Trikalinos; Evangelia E Ntzani; Despina G Contopoulos-Ioannidis
Journal:  Lancet       Date:  2003-02-15       Impact factor: 79.321

4.  Studying parents and grandparents to assess genetic contributions to early-onset disease.

Authors:  Clarice R Weinberg
Journal:  Am J Hum Genet       Date:  2003-01-17       Impact factor: 11.025

5.  Genome scans and candidate gene approaches in the study of common diseases and variable drug responses.

Authors:  David B Goldstein; Kourosh R Ahmadi; Mike E Weale; Nicholas W Wood
Journal:  Trends Genet       Date:  2003-11       Impact factor: 11.639

6.  Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits.

Authors:  S Purcell; S S Cherny; P C Sham
Journal:  Bioinformatics       Date:  2003-01       Impact factor: 6.937

7.  Assessing the impact of population stratification on genetic association studies.

Authors:  Matthew L Freedman; David Reich; Kathryn L Penney; Gavin J McDonald; Andre A Mignault; Nick Patterson; Stacey B Gabriel; Eric J Topol; Jordan W Smoller; Carlos N Pato; Michele T Pato; Tracey L Petryshen; Laurence N Kolonel; Eric S Lander; Pamela Sklar; Brian Henderson; Joel N Hirschhorn; David Altshuler
Journal:  Nat Genet       Date:  2004-03-28       Impact factor: 38.330

8.  The future of genetic studies of complex human diseases.

Authors:  N Risch; K Merikangas
Journal:  Science       Date:  1996-09-13       Impact factor: 47.728

9.  Genotype relative risks: methods for design and analysis of candidate-gene association studies.

Authors:  D J Schaid; S S Sommer
Journal:  Am J Hum Genet       Date:  1993-11       Impact factor: 11.025

Review 10.  Haplotype blocks and linkage disequilibrium in the human genome.

Authors:  Jeffrey D Wall; Jonathan K Pritchard
Journal:  Nat Rev Genet       Date:  2003-08       Impact factor: 53.242

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  3 in total

1.  Distinguishing true from false positives in genomic studies: p values.

Authors:  Linda Broer; Christina M Lill; Maaike Schuur; Najaf Amin; Johannes T Roehr; Lars Bertram; John P A Ioannidis; Cornelia M van Duijn
Journal:  Eur J Epidemiol       Date:  2013-02-01       Impact factor: 8.082

2.  Genetic Architecture of Depression: Where Do We Stand Now?

Authors:  Pinar Unal-Aydin; Orkun Aydin; Ayla Arslan
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

3.  Biallelic and Triallelic 5-Hydroxytyramine Transporter Gene-Linked Polymorphic Region (5- HTTLPR) Polymorphisms and Their Relationship with Lifelong Premature Ejaculation: A Case-Control Study in a Chinese Population.

Authors:  Yuanyuan Huang; Xiansheng Zhang; Jingjing Gao; Dongdong Tang; Pan Gao; Chao Li; Weiqun Liu; Chaozhao Liang
Journal:  Med Sci Monit       Date:  2016-06-17
  3 in total

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