An evaluation of the genetic-matched pair study design using genome-wide SNP data from the European population.

Authors:
Timothy Tehua Lu, Oscar Lao, Michael Nothnagel, Olaf Junge, Sandra Freitag-Wolf, Amke Caliebe, Miroslava Balascakova, Jaume Bertranpetit, Laurence Albert Bindoff, David Comas, Gunilla Holmlund, Anastasia Kouvatsi, Milan Macek, Isabelle Mollet, Finn Nielsen, Walther Parson, Jukka Palo, Rafal Ploski, Antti Sajantila, Adriano Tagliabracci, Ulrik Gether, Thomas Werge, Fernando Rivadeneira, Albert Hofman, André Gerardus Uitterlinden, Christian Gieger, Heinz-Erich Wichmann, Andreas Ruether, Stefan Schreiber, Christian Becker, Peter Nürnberg, Matthew Roberts Nelson, Manfred Kayser, Michael Krawczak
Year of publication:
2009
Volume:
17
Issue:
7
Issn:
1018-4813
Journal title abbreviated:
EUR J HUM GENET
Journal title long:
European journal of human genetics
Impact factor:
4.580
Abstract: 
Genetic matching potentially provides a means to alleviate the effects of incomplete Mendelian randomization in population-based gene-disease association studies. We therefore evaluated the genetic-matched pair study design on the basis of genome-wide SNP data (309,790 markers; Affymetrix GeneChip Human Mapping 500K Array) from 2457 individuals, sampled at 23 different recruitment sites across Europe. Using pair-wise identity-by-state (IBS) as a matching criterion, we tried to derive a subset of markers that would allow identification of the best overall matching (BOM) partner for a given individual, based on the IBS status for the subset alone. However, our results suggest that, by following this approach, the prediction accuracy is only notably improved by the first 20 markers selected, and increases proportionally to the marker number thereafter. Furthermore, in a considerable proportion of cases (76.0%), the BOM of a given individual, based on the complete marker set, came from a different recruitment site than the individual itself. A second marker set, specifically selected for ancestry sensitivity using singular value decomposition, performed even more poorly and was no more capable of predicting the BOM than randomly chosen subsets. This leads us to conclude that, at least in Europe, the utility of the genetic-matched pair study design depends critically on the availability of comprehensive genotype information for both cases and controls.