A demonstration and findings of a statistical approach through reanalysis of inflammatory bowel disease data

doi:10.1073/pnas.0403662101

A demonstration and findings of a statistical approach through reanalysis of inflammatory bowel disease data

Shaw-Hwa Lo* and
Tian Zheng*

Department of Statistics, Columbia University, 618 Mathematics, 2990 Broadway, MC 4403, New York, NY 10027

Communicated by Herman Chernoff, Harvard University, Cambridge, MA, May 24, 2004 (received for review March 17, 2004)

Abstract

We test the backward haplotype transmission association algorithm on genome-scan data previously studied by Rioux et al. [Rioux, J. D., et al. (2000) Am. J. Hum. Genet. 66, 1863–1870]. In their study, multipoint linkage methods were applied to affected sib-pairs with inflammatory bowel disease, and significant linkage evidence points to two susceptibility loci. After we apply our approach to these data with a global search accounting for both joint and marginal effects, very interesting results emerge, many of them intriguing. These results provide compelling support for the application of our approach to other data wherever applicable. Results from this project also make it clear that it is important to reinvestigate available family-based datasets that can be suitably reanalyzed. Given previously collected data in the literature, our approach, with its increased efficiency in using available resources, draws additional crucial information that may lead to novel and surprising results.

Footnotes

↵ * To whom correspondence may be addressed. E-mail: slo{at}stat.columbia.edu or tzheng{at}stat.columbia.edu.
Abbreviations: HTA, haplotype transmission association; BHTA, backward HTA; IBD, inflammatory bowel disease; CD, Crohn's disease; UC, ulcerative colitis; HTD, haplotype transmission disequilibrium.
↵ † According to ref. 2, the data included 377 microsatellite markers that were spaced 12 cM apart on average, plus additional microsatellite markers genotyped on the IBD5 region.
↵ ‡ The reason for this adjustment is that the modified score HTA^r(k – 1) will have an expectation of zero when no marker is in association with the trait. In fact, the adjusting term $\text{[math]}$ carries no information for association and represents a fixed amount of value loss caused by the deletion of M_r.
↵ § Certainly, considering the observed genotype on markers nearby will provide more information for the imputation. However, given the disease status of the children, the association among markers has been contaminated by their possible association with the disease trait.
↵ ¶ Marker locations were identified through The Genome Database (http://www.gdb.org), and candidate genes were identified through searches in the Entrez Gene Database of the National Center for Biotechnology Information.