The overall goal of this proposed project is to identify rare genetic variants contributing to childhood onset- Crohn disease. Crohn disease is a chronic inflammatory disorder of the gastrointestinal tract of unclear etiology and no known cure. Affected children suffer from diarrhea, abdominal pain, growth disturbances, and an impaired quality of life. The identified Crohn disease susceptibility alleles have improved our understanding of Crohn disease pathogenesis. However, the identified susceptibility alleles do not account for the observed heritability, nor have disease-causing alleles in many genomic regions been identified. For the proposed studies, we will use 1) existing DNA samples collected from high-risk Crohn kindreds identified using the extensive genealogical records available only in Utah, 2) existing DNA samples obtained from very young children with Crohn disease and their parents, and 3) existing DNA samples obtained from healthy controls that are free of a personal or family history of autoimmune disorders. Our overall hypothesis is that childhood- onset Crohn disease is caused in part by rare disease susceptibility alleles.
In Aim 1, we will perform shared genomic segment analysis and exome sequencing in children in high-risk Crohn disease kindreds.
In Aim 2, we will perform targeted re-sequencing studies and a case-control study in which the cases are very young children with Crohn disease.
In Aim 3, we will test the hypothesis that, as a consequence of the evolutionary forces, Crohn disease susceptibility alleles have hitchhiked on a previously identified disease risk haplotype in which the disease-causing variant(s) remains unknown. In this proposal, we will use a novel and powerful resource, the Utah Population Database, and further develop innovative analytical strategies to perform gene- mapping studies in large kindreds. We will utilize a phenotypic extreme-childhood-onset Crohn disease-to characterize the rare genetic variation in known susceptibility alleles. Finally, we will explore the evolutionary forces shaping a Crohn disease susceptibility locus, which may provide insight into the disease-causing gene. These studies will improve our understanding of the causes of Crohn disease, help develop clinically useful molecular classification schemes, and lead to improved therapy.

Public Health Relevance

/RELEVANCE TO PUBLIC HEATLH Crohn disease is a chronic inflammatory disorder of the intestine of unclear etiology and no known cure. Affected children suffer from diarrhea, abdominal pain, growth disturbances, and an impaired quality of life. The overall goal of this project is to identify new genetic risk factors by studying high-risk Crohn disease kindreds and very young children affected by Crohn disease. These studies may help us better understand the causes of Crohn disease, and develop clinically relevant tools to classify patients at high risk of developing disease or adverse outcomes of disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK091374-03
Application #
8507726
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Karp, Robert W
Project Start
2011-09-26
Project End
2015-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
3
Fiscal Year
2013
Total Cost
$272,706
Indirect Cost
$89,682
Name
University of Utah
Department
Pediatrics
Type
Schools of Medicine
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
Hu, Hao; Roach, Jared C; Coon, Hilary et al. (2014) A unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data. Nat Biotechnol 32:663-9
Singleton, Marc V; Guthery, Stephen L; Voelkerding, Karl V et al. (2014) Phevor combines multiple biomedical ontologies for accurate identification of disease-causing alleles in single individuals and small nuclear families. Am J Hum Genet 94:599-610
Li, Hong; Glusman, Gustavo; Hu, Hao et al. (2014) Relationship estimation from whole-genome sequence data. PLoS Genet 10:e1004144
Xing, Jinchuan; Wuren, Tana; Simonson, Tatum S et al. (2013) Genomic analysis of natural selection and phenotypic variation in high-altitude mongolians. PLoS Genet 9:e1003634
Hu, Hao; Huff, Chad D; Moore, Barry et al. (2013) VAAST 2.0: improved variant classification and disease-gene identification using a conservation-controlled amino acid substitution matrix. Genet Epidemiol 37:622-34