Accounting for genetic heterogeneity in homozygosity mapping: Application to Mendelian susceptibility to mycobacterial disease

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Date

2011-08

Authors

Grant, Audrey V.
Dupuis, Stephanie Boisson
Herquelot, Eleonore
de Beaucoudrey, Ludovic
Santos, Orchidee Filipe
Nolan, Daniel K.
Feinberg, Jacqueline
Boland, Anne
Al-Muhsen, Saleh
Sanal, Özden

Journal Title

Journal ISSN

Volume Title

Publisher

Bmj Publishing Group

Abstract

Introduction Genome-wide homozygosity mapping is a powerful method for locating rare recessive Mendelian mutations. However, statistical power decreases dramatically in the presence of genetic heterogeneity. Methods The authors applied an empirical approach to test for linkage accounting for genetic heterogeneity by calculating the sum of positive per-family multipoint LOD scores (S) across all positions, and obtaining corresponding empirical p values (EmpP) through permutations. Results The statistical power of the approach was found to be consistently higher than the classical heterogeneity LOD by simulations. Among 21 first-cousin matings with a single affected child, for five families linked to a locus of interest and 16 families to other loci, S/EmpP achieved a power of 40% versus 28% for heterogeneity LOD at an alpha level of 0.001. The mean size of peak linkage regions was markedly higher for true loci than false positive regions. The S/EmpP approach was applied to a sample of 17 consanguineous families with Mendelian susceptibility to mycobacterial disease, leading to the identification of two mutations in IL12RB1 and TYK2 from the largest of six linkage regions at p<10(-3). Conclusions The S/EmpP approach is a flexible and powerful approach that can be applied to linkage analysis of families with suspected Mendelian disorders.

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Keywords

Genetics & heredity, Sequencing-based discovery, Deficiency, Immunity, Mutation, Reveals

Citation

Grant, A. V. vd. (2011). "Accounting for genetic heterogeneity in homozygosity mapping: Application to Mendelian susceptibility to mycobacterial disease". Journal of Medical Genetics, 48(8), 567-571.