Evaluation of candidate genes in case-control studies

A statistical method to account for related subjects

Research output: Contribution to journalArticle

98 Citations (Scopus)

Abstract

Traditional case-control studies provide a powerful and efficient method for evaluation of association between candidate genes and disease. The sampling of cases from multiplex pedigrees, rather than from a catchment area, can increase the likelihood that genetic cases are selected. However, use of all the related cases without accounting for their biological relationship can increase the type I error rate of the statistical test. To overcome this problem, we present an analysis method that is used to compare genotype frequencies between cases and controls, according to a trend in proportions as the dosage of the risk allele increases. This method uses the appropriate variance to account for the correlated family data, thus maintaining the correct type I error rate. The magnitude of the association is estimated by the odds ratio, with the variance of the odds ratio also accounting for the correlated data. Our method makes efficient use of data collected from multiplex families and should prove useful for the analysis of candidate genes among families sampled for linkage studies. An application of our method, to family data from a prostate cancer study, is presented to illustrate the method's utility.

Original languageEnglish (US)
Pages (from-to)1457-1462
Number of pages6
JournalAmerican Journal of Human Genetics
Volume68
Issue number6
DOIs
StatePublished - 2001

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Case-Control Studies
Genes
Odds Ratio
Genetic Association Studies
Pedigree
Prostatic Neoplasms
Alleles
Genotype

ASJC Scopus subject areas

  • Genetics

Cite this

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abstract = "Traditional case-control studies provide a powerful and efficient method for evaluation of association between candidate genes and disease. The sampling of cases from multiplex pedigrees, rather than from a catchment area, can increase the likelihood that genetic cases are selected. However, use of all the related cases without accounting for their biological relationship can increase the type I error rate of the statistical test. To overcome this problem, we present an analysis method that is used to compare genotype frequencies between cases and controls, according to a trend in proportions as the dosage of the risk allele increases. This method uses the appropriate variance to account for the correlated family data, thus maintaining the correct type I error rate. The magnitude of the association is estimated by the odds ratio, with the variance of the odds ratio also accounting for the correlated data. Our method makes efficient use of data collected from multiplex families and should prove useful for the analysis of candidate genes among families sampled for linkage studies. An application of our method, to family data from a prostate cancer study, is presented to illustrate the method's utility.",
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