The McGovern Laboratory, or Translational Genomics Group (TGG), is involved in studies to identify additional susceptibility genes in European populations as well as to identify genes associated with inflammatory bowel diseases (IBD) in the Puerto Rican, Asian, Ashkenazi Jewish and African American populations. The identification of these genes leads to a greater understanding of the underlying processes and causes that lead to IBD.
Relative importance of biological mechanisms in IBD identified through genetic studies. (Figure adapted from Khor B et al. Nature 2011. https://www.nature.com/nature/journal/v474/n7351/full/nature10209.html.)
In addition, the TGG is interested in how genetic variants are associated with different manifestations of IBD including disease severity and response to therapy. Collectively, these genetic data, together with other data including clinical parameters will facilitate the move toward a more personalized approach to clinical medicine.
Repository and Database
To facilitate our research and that of other groups, both within and outside the F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, the TGG also manages the Mucosal Immunology Repository for Inflammatory And Digestive Diseases (MIRIAD) IBD database and research repository. The IBD database allows us to consolidate demographic, clinical, genomic and other datasets, greatly enhancing our ability to perform research. The database also keeps a record of samples collected in our repository, thereby linking biospecimens to both clinical and genomic data. Patients with IBD attending the IBD center's clinics and endoscopy units, and for surgery, are approached to see if they want to contribute samples to the IBD repository.
Mucosal Immunology Repository for Inflammatory And Digestive Diseases (MIRIAD) and its central role in the F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute's research capabilities.
Biostatistics has become an increasing part of our group's research as we generate large data across many different platforms. Our group is interested in developing new analytic methods for integrating and analyzing these data.