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Hirschsprung Disease clinical trials at University of California Health

1 research study open to eligible people

Showing trials for
  • Identification Genetic, Immunologic and Microbial Markers of Hirschsprung Associated Enterocolitis in Children With Hirschsprung Disease

    open to eligible people ages up to 17 years

    To identify demographic, clinical, genetic, immunologic and/or microbial (i.e., fecal stream characterization) risk factors that influence the likelihood of development of the HAEC phenotype in children who carry the diagnosis of HD. The newly formed HAEC Collaborative Research Group (HCRG) will utilize the 4 participating centers in the current consortia and recruit additional centers to enroll children diagnosed with Hirschsprung disease. 1a: To recruit 200 patients with Hirschsprung disease without HAEC. 1b: To recruit 200 patients with Hirschsprung disease and HAEC using standardized diagnostic criteria by collaborating with participating members of the HAEC Collaborative Research Group[1]. 1c: To collect clinical and demographic information from well-characterized HD patients both with and without HAEC. 1d: To collect samples blood for DNA for genome wide association study (GWAS) by high throughput SNP technology and mutational analysis of known HSCR genes. 1e: To collect serum samples at the time of recruitment in a subset cohort (n=50 HD only, n=50 HD + HAEC) for serological immune markers known for inflammatory bowel disease (IBD) including ANCA, ASCA, OMPC, I2, and CBir1 and any newly identified markers. 1f: To collect and store fresh fecal specimens for future evaluation by molecular methodologies to determine relative proportions of enteric microflora in a subset cohort (n=50 HD only, n=50 HD + HAEC) of children (<18 years). 1g: To establish a Centralized Data Coordinating Center for data collection, data quality and detailed data analyses (CSMC) and tissue bank (CSMC) to facilitate specimen analysis for this study. The HAEC risk factor identification will be completed by multivariate logistic regression analysis. Genetic association will be studied for each SNP in the GWAS together with all other potential risk factors. Further analysis will be carried out to evaluate multiple SNPs/genes simultaneously.

    at UCSF