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Original Paper

Free Access

Robust Age at Onset Linkage Analysis in Nuclear Families

Callegaro A. · van Houwelingen J.C. · Houwing-Duistermaat J.J.

Author affiliations

Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, University of Leiden, Leiden, The Netherlands

Corresponding Author

Andrea Callegaro

Department of Medical Statistics and Bioinformatics

Leiden University Medical Center, S-5-P, PO Box 9600

NL–2300 RC Leiden (The Netherlands)

Tel. +31 71 526 9718, Fax +31 71 526 8280, E-Mail a.callegaro@lumc.nl

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Hum Hered 2010;69:80–90

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Objective: Standard methods for linkage analysis ignore the phenotype of the parents when they are not genotyped. However, this information can be useful for gene mapping. In this paper we propose methods for age at onset genetic linkage analysis in sibling pairs, taking into account parental age at onset. Methods:Two new score statistics are derived, one from an additive gamma frailty model and one from a log-normal frailty model. The score statistics are classical non-parametric linkage (NPL) statistics weighted by a function of the age at onset of the four family members. The weight depends on information from registries (age-specific incidences) and family studies (sib-sib and father-mother correlation). Results:In order to investigate how age at onset of sibs and their parents affect the information for linkage analysis the weight functions were studied for rare and common disease models, realistic models for breast cancer and human lifespan. We studied the performance of the weighted NPL methods by simulations. As illustration, the score statistics were applied to the GAW12 data. The results show that it is useful to include parental age at onset information in genetic linkage analysis.

© 2009 S. Karger AG, Basel


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Article / Publication Details

First-Page Preview
Abstract of Original Paper

Received: April 01, 2009
Accepted: July 13, 2009
Published online: December 04, 2009
Issue release date: January 2010

Number of Print Pages: 11
Number of Figures: 6
Number of Tables: 2

ISSN: 0001-5652 (Print)
eISSN: 1423-0062 (Online)

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