- Computational prediction modeling of diabetic neuropathy progression
- Database for diabetes model and patient array data analyses
- Comprehensive analyses of scientific literature
Bioinformatics is a broad field of research combining computer science and biology to help accelerate the research. PNR&D scientists are collecting massive quantities of data which are used to guide the formulation of computational models to aid in the search for disease mechanisms. The public sharing of large data sets between investigators is also important to advance research progress. Bioinformatics efforts in the PNR&D aim to bring all of this data together, to get a fast, reliable and detailed picture of how computer-based technologies can aid in our quest to understand and treat neurological conditions.
Computational prediction models are currently being developed to understand and calculate progression rates for human diabetic neuropathy. These models use high-throughput gene analyses on sural nerve tissue from patients with diabetic neuropathy. Using this approach, subsets of gene expression alterations that correlate with neuropathy progression in a small set of patients have been identified. These models will be extensively tested on additional patient cohorts and refined to incorporate expression profiles from readily-accessible human body fluids such as blood and urine. These models will help to identify patients at high risk of developing progressive diabetic neuropathy so that therapeutic intervention can begin as early as possible.
Microarray experiments allow scientists to investigate changes in gene expression that correlate with disease. In the PNR&D, multiple transcriptomic studies of human sural nerves from subjects with diabetic neuropathy, and various mouse models including both type 1 (DBA/2J with STZ) and type 2 (db/db, BTBR ob/ob, and high fat-fed) models of diabetes, have been completed. To aid in analyses and facilitate comparisons between these data sets, PNR&D scientists are developing a database to deposit and analyze genomic data. Results from both human and animal model nerve array studies, as well as transcript profiles from various other complication-prone tissues such as eyes and kidneys from human patients and murine models, may be compared to help us better understand the underlying mechanisms of the onset and the progression of diabetic complications. Using this knowledge, comprehensive therapies that impact multiple aspects of the disease can be developed.
Science progresses at an incredible pace, and more scientific papers are published every day than any single scientist could read. Therefore, we developed a program that can scan all of the papers published and available on-line (currently numbering in the millions) for the names of genes. It can then tell you what genes are most important to a particular subject, like diabetic neuropathy or amyotrophic lateral sclerosis. This tool can be used to discover new connections between diseases and gain better insight into how neurological diseases develop and progress.