More powerful haplotype sharing by accounting for the mode of inheritance.
The concept of haplotype sharing (HS) has received considerable attention recently, and several haplotype association methods have been proposed. Here, we extend the work of Beckmann and colleagues [2005 Hum. Hered. 59:67-78] who derived an HS statistic (BHS) as special case of Mantel's space-time clustering approach. The Mantel-type HS statistic correlates genetic similarity with phenotypic similarity across pairs of individuals. While phenotypic similarity is measured as the mean-corrected cross product of phenotypes, we propose to incorporate information of the underlying genetic model in the measurement of the genetic similarity. Specifically, for the recessive and dominant modes of inheritance we suggest the use of the minimum and maximum of shared length of haplotypes around a marker locus for pairs of individuals. If the underlying genetic model is unknown, we propose a model-free HS Mantel statistic using the max-test approach. We compare our novel HS statistics to BHS using simulated case-control data and illustrate its use by re-analyzing data from a candidate region of chromosome 18q from the Rheumatoid Arthritis (RA) Consortium. We demonstrate that our approach is point-wise valid and superior to BHS. In the re-analysis of the RA data, we identified three regions with point-wise P-values<0.005 containing six known genes (PMIP1, MC4R, PIGN, KIAA1468, TNFRSF11A and ZCCHC2) which might be worth follow-up.
Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Lübeck, Germany. ziegler@imbs.uni-luebeck.de
Andreas
A
Ziegler
Adel
A
Ewhida
Michael
M
Brendel
André
A
Kleensang
D001172:Arthritis, Rheumatoid / Q000235:genetics; D016022:Case-Control Studies; D002887:Chromosomes, Human, Pair 18 / Q000235:genetics; D055106:Genome-Wide Association Study; D006239:Haplotypes; D006801:Humans; D008957:Models, Genetic; D013029:Space-Time Clustering