An evaluation of the genetic-matched pair study design using genome-wide SNP data from the European population.
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.
Lu
Timothy Tehua
TT
Institut für Medizinische Informatik und Statistik, Christian-Albrechts-Universität Kiel, Kiel, Germany.
Lao
Oscar
O
Nothnagel
Michael
M
Junge
Olaf
O
Freitag-Wolf
Sandra
S
Caliebe
Amke
A
Balascakova
Miroslava
M
Bertranpetit
Jaume
J
Bindoff
Laurence Albert
LA
Comas
David
D
Holmlund
Gunilla
G
Kouvatsi
Anastasia
A
Macek
Milan
M
Mollet
Isabelle
I
Nielsen
Finn
F
Parson
Walther
W
Palo
Jukka
J
Ploski
Rafal
R
Sajantila
Antti
A
Tagliabracci
Adriano
A
Gether
Ulrik
U
Werge
Thomas
T
Rivadeneira
Fernando
F
Hofman
Albert
A
Uitterlinden
André Gerardus
AG
Gieger
Christian
C
Wichmann
Heinz-Erich
HE
Ruether
Andreas
A
Schreiber
Stefan
S
Becker
Christian
C
Nürnberg
Peter
P
Nelson
Matthew Roberts
MR
Kayser
Manfred
M
Krawczak
Michael
M
D004247:DNA / Q000032:analysis / Q000235:genetics; D005060:Europe; D005260:Female; D005819:Genetic Markers; D014644:Genetic Variation; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male; D016555:Matched-Pair Analysis; D020641:Polymorphism, Single Nucleotide; D044382:Population Groups / Q000235:genetics; D012107:Research Design; D017422:Sequence Analysis, DNA
D005819:Genetic Markers; D004247:DNA