Public Release Type:
Journal
Publication Year: 2007
Authors:
Cantor S,
Cooley PC,
Ray HP,
Scheper CO,
Turner CF,
Ying Q
The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) conducts and supports research on many of the most serious diseases affecting public health, including diabetes, liver and kidney disease. In many cases, the study has collected genetic samples that can be linked to phenotypic data from the subjects; therefore, it is possible to match genotypes to phenotypes and perform many genetic analyses. As high-density genotyping becomes increasingly available, the ability to relate the genetics of patients to results of previous NIDDK-sponsored clinical trials becomes timely. Several NIDDK-supported studies have focused on diabetes and diabetic complications. If consistent phenotypes can be identified across studies and their observations pooled, it might be possible to assemble a dataset with sufficient power to support genetic studies that are not possible from any one individual study. Entirely new studies could be conducted with no additional data collection. To help accomplish that goal and to preserve and distribute valuable resources, NIDDK has established a Central Repository to collect and distribute the data and samples collected by NIDDK-sponsored studies. The Repository co-locates multiple databases to make the data and the associated biological and genetic samples available to the scientific community. The repository also catalogues, retrieves and checks the integrity of study data, manages data requests, and answers researchers' questions. It currently houses publicly available data and samples from 11 studies, including four genetics-based diabetes studies, and is collecting data and samples from more than 20 other ongoing studies for future distribution. The NIDDK Central Repository is a powerful tool for performing in-depth secondary analysis of previously collected data. It will be an important tool for increasing the impact of studies in diabetes, and, ultimately, it will make it possible for researchers to conduct entirely new studies without having to collect data while minimizing biologic sample collection.