Literature DB >> 11479836

Optimized group sequential study designs for tests of genetic linkage and association in complex diseases.

I R König1, H Schäfer, H H Müller, A Ziegler.   

Abstract

The study of genetic linkage or association in complex traits requires large sample sizes, as the expected effect sizes are small and extremely low significance levels need to be adopted. One possible way to reduce the numbers of phenotypings and genotypings is the use of a sequential study design. Here, average sample sizes are decreased by conducting interim analyses with the possibility to stop the investigation early if the result is significant. We applied optimized group sequential study designs to the analysis of genetic linkage (one-sided mean test) and association (two-sided transmission/disequilibrium test). For designs with two and three stages at overall significance levels of.05 and.0001 and a power of.8, we calculated necessary sample sizes, time points, and critical boundaries for interim and final analyses. Monte Carlo simulation analyses were performed to confirm the validity of the asymptotic approximation. Furthermore, we calculated average sample sizes required under the null and alternative hypotheses in the different study designs. It was shown that the application of a group sequential design led to a maximal increase in sample size of 8% under the null hypothesis, compared with the fixed-sample design. This was contrasted by savings of up to 20% in average sample sizes under the alternative hypothesis, depending on the applied design. These savings affect the amounts of genotyping and phenotyping required for a study and therefore lead to a significant decrease in cost and time.

Mesh:

Year:  2001        PMID: 11479836      PMCID: PMC1235488          DOI: 10.1086/323250

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  21 in total

1.  On the total expected study cost in two-stage genome-wide search designs for linkage analysis using the mean test for affected sib pairs.

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Journal:  Genet Epidemiol       Date:  2001-04       Impact factor: 2.135

2.  Two-stage global search designs for linkage analysis I: use of the mean statistic for affected sib pairs.

Authors:  X Guo; R C Elston
Journal:  Genet Epidemiol       Date:  2000-02       Impact factor: 2.135

Review 3.  Optimum study designs.

Authors:  C Gu; D C Rao
Journal:  Adv Genet       Date:  2001       Impact factor: 1.944

Review 4.  Significance levels in genome scans.

Authors:  G Thomson
Journal:  Adv Genet       Date:  2001       Impact factor: 1.944

5.  A single, sequential, genome-wide test to identify simultaneously all promising areas in a linkage scan.

Authors:  M A Province
Journal:  Genet Epidemiol       Date:  2000-12       Impact factor: 2.135

6.  Sequential tests for the detection of linkage.

Authors:  N E MORTON
Journal:  Am J Hum Genet       Date:  1955-09       Impact factor: 11.025

7.  Linkage strategies for genetically complex traits. II. The power of affected relative pairs.

Authors:  N Risch
Journal:  Am J Hum Genet       Date:  1990-02       Impact factor: 11.025

8.  Candidate genes in psychiatry: an epidemiological perspective.

Authors:  R R Crowe
Journal:  Am J Med Genet       Date:  1993-07-15

9.  A multiple testing procedure for clinical trials.

Authors:  P C O'Brien; T R Fleming
Journal:  Biometrics       Date:  1979-09       Impact factor: 2.571

10.  Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM).

Authors:  R S Spielman; R E McGinnis; W J Ewens
Journal:  Am J Hum Genet       Date:  1993-03       Impact factor: 11.025

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  2 in total

1.  Optimum two-stage designs in case-control association studies using false discovery rate.

Authors:  Aya Kuchiba; Noriko Y Tanaka; Yasuo Ohashi
Journal:  J Hum Genet       Date:  2006-09-27       Impact factor: 3.172

2.  The association study of calmodulin 1 gene polymorphisms with susceptibility to adolescent idiopathic scoliosis.

Authors:  Yu Zhang; Zuchao Gu; Guixing Qiu
Journal:  Biomed Res Int       Date:  2014-01-16       Impact factor: 3.411

  2 in total

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