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In genetic epidemiological studies informative families are often oversampled to increase the power of a study. For a proband-family design, where relatives of probands are sampled, we derive the score statistic to test for clustering of binary and quantitative traits within families due to genetic factors. The derived score statistic is robust to ascertainment scheme. We considered correlation due to unspecified genetic effects and/or due to sharing alleles identical by descent (IBD) at observed marker locations in a candidate region. A simulation study was carried out to study the distribution of the statistic under the null hypothesis in small data-sets. To illustrate the score statistic, data from 33 families with type 2 diabetes mellitus (DM2) were analyzed. In addition to the binary outcome DM2 we also analyzed the quantitative outcome, body mass index (BMI). For both traits familial aggregation was highly significant. For DM2, also including IBD sharing at marker D3S3681 as a cause of correlation gave an even more significant result, which suggests the presence of a trait gene linked to this marker. We conclude that for the proband-family design the score statistic is a powerful and robust tool for detecting clustering of outcomes.

Original publication

DOI

10.1046/j.1529-8817.2005.00177.x

Type

Journal article

Journal

Annals of human genetics

Publication Date

07/2005

Volume

69

Pages

373 - 381

Addresses

Department of Epidemiology and Biostatistics, Erasmus MC, Rotterdam, The Netherlands.

Keywords

Humans, Diabetes Mellitus, Type 2, Body Mass Index, Chi-Square Distribution, Genetics, Medical, Alleles, Models, Genetic, Research Design, Computer Simulation, Female, Male