The NIDDK Central Repository at 8 years--Ambition, Revision, Use and Impact

Abstract

The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository makes data and biospecimens from NIDDK-funded research available to the broader scientific community. It thereby facilitates: the testing of new hypotheses without new data or biospecimen collection; pooling data across several studies to increase statistical power; and informative genetic analyses using the Repository’s well-curated phenotypic data. This article describes the initial database plan for the Repository and its revision using a simpler model. Among the lessons learned were the trade-offs between the complexity of a database design and the costs in time and money of implementation; the importance of integrating consent documents into the basic design; the crucial need for linkage files that associate biospecimen IDs with the masked subject IDs used in deposited data sets; and the importance of standardized procedures to test the integrity data sets prior to distribution. The Repository is currently tracking 111 ongoing NIDDK-funded studies many of which include genotype data, and it houses over 5 million biospecimens of more than 25 types including serum, plasma, stool, urine, DNA, red blood cells, buffy coat and tissue. Repository resources have supported a range of biochemical, clinical, statistical and genetic research (188 external requests for clinical data and 31 for biospecimens have been approved or are pending). Genetic research has included GWAS, validation studies, development of methods to improve statistical power of GWAS and testing of new statistical methods for genetic research. We anticipate that the future impact of the Repository’s resources on biomedical research will be enhanced by (i) cross-listing of Repository biospecimens in additional searchable databases and biobank catalogs; (ii) ongoing deployment of new applications for querying the contents of the Repository; and (iii) increased harmonization of procedures, data collection strategies, questionnaires etc. across both research studies and within the vocabularies used by different repositories.Database URL: http://www.niddkrepository.org

Big data from small data: data-sharing in the 'long tail' of neuroscience

“…Researchers often cite the fear that re-analysis of poor quality data sets or even good data sets by non-experts will lead to a flood of bad science in the literature 33 . Although this is certainly a concern, advocates of data sharing point to increased access to additional human capital available for a nalyzing data in new ways.…”

Why democratise bioinformatics?

“…Merging myriad data sets potentially introduces the risk of reanalysis of poor quality data sets or analysis of excellent data sets by non-experts using inappropriate applications, thus flooding the field with conflicting results 18. There is also the financial cost and time investment involved in preparing data and data collection instruments to permit their use by others, but shared standardised tools once developed will avoid this issue and deliver superior research network intensity.…”

Evaluation of Urinary Protein Precipitation Protocols for the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network

“…By standardizing sample collection, shipping, and storage, biorepositories provide researchers opportunities to use well-characterized samples from large cohorts to discover and characterize unique phenotypic and molecular biomarkers for disease progression that may provide targets for clinical intervention. [1][2][3][4][5] Urine is an attractive biospecimen for biomarker discovery. Comprised primarily of shed cells, debris, and secreted components from the urinary tract, as well as blood components that have passed through glomerular filtration and renal tubule reabsorption, urinary components may reflect local renal or urogenital disease, as well as more systemic alterations in distant organs.…”