Testing association and linkage using affected-sib-parent study designs
Article first published online: 24 AUG 2005
© 2005 Wiley-Liss, Inc.
Volume 29, Issue 3, pages 225–233, November 2005
How to Cite
Millstein, J., Siegmund, K. D., Conti, D. V. and Gauderman, W. J. (2005), Testing association and linkage using affected-sib-parent study designs. Genet. Epidemiol., 29: 225–233. doi: 10.1002/gepi.20091
- Issue published online: 18 OCT 2005
- Article first published online: 24 AUG 2005
- Manuscript Accepted: 6 JUL 2005
- Manuscript Received: 5 APR 2005
- National Institute of Environmental Health Sciences. Grant Number: ES10421 and 5P30-ES07048
- National Cancer Institute. Grant Number: CA52862
- Institute of General Medicine. Grant Number: GM58897
- linkage disequilibrium;
We have developed a method for jointly testing linkage and association using data from affected sib pairs and their parents. We specify a conditional logistic regression model with two covariates, one that quantifies association (either direct association or indirect association via linkage disequilibrium), and a second that quantifies linkage. The latter covariate is computed based on expected identity-by-descend (ibd) sharing of marker alleles between siblings. In addition to a joint test of linkage and association, our general framework can be used to obtain a linkage test comparable to the mean test (Blackwelder and Elston  Genet. Epidemiol. 2:85–97), and an association test comparable to the Family-Based Association Test (FBAT; Rabinowitz and Laird  Hum. Hered. 50:211–223). We present simulation results demonstrating that our joint test can be more powerful than some standard tests of linkage or association. For example, with a relative risk of 2.7 per variant allele at a disease locus, the estimated power to detect a nearby marker with a modest level of LD was 58.1% by the mean test (linkage only), 69.8% by FBAT, and 82.5% by our joint test of linkage and association. Our model can also be used to obtain tests of linkage conditional on association and association conditional on linkage, which can be helpful in fine mapping. Genet. Epidemiol. © 2005 Wiley-Liss, Inc.