Bioinformatic Resources For Diabetic Nephropathy - Bioinformatic Resources For Diabetic Nephropathy - Open Access Pub

The number of individuals with diabetes is increasing worldwide and a large subset of those affected will develop diabetic nephropathy. Diabetic nephropathy is the leading cause of end-stage renal disease, has serious health consequences for affected individuals, and represents a major monetary cost to healthcare providers. Technological and analytical developments have enabled large-scale, collaborative studies that are revealing risk factors associated with diabetic nephropathy. However, much of the inherited predisposition and biological mechanisms underpinning risk of this disease remain to be identified. Meta-analyses and integrated pathway studies are becoming an increasingly important part of research for diabetic nephropathy including, genetic, epigenetic, transcriptomic, proteomic research, clinical observations and the development of animal models. This report highlights current bioinformatic resources and standards of reporting to maximise interdisciplinary research for diabetic nephropathy. The identification of an -Omics profile that can lead to earlier diagnosis and / or offer improved clinical evaluation of individuals with diabetes would not only provide significant health benefits to affected individuals, but may also have major utility for the efficient use of healthcare resources. DOI10.14302/issn.2374-9431.jbd-13-226 Diabetes is a major public health concern with rates of diabetes increasing globally and approximately 40% of affected individuals developing diabetic nephropathy 1, 2, 3, 4. Diabetic nephropathy is the leading cause of end-stage renal disease and represents a substantial cost to healthcare providers 5, 6. Strategies that can help predict those individuals at higher risk of developing diabetic nephropathy, improve understanding of the pathogenesis of this disease, or suggest novel targets for optimised therapies are urgently required. With the increasing size and complexity of research studies, bioinformatics has become an essential discipline to help unravel the biological mechanisms that lead to diabetic nephropathy and end-stage renal disease in individuals with diabetes. Clinically-based resources such as routine laboratory measurements, hospitalisation records, treatment regimens and patient outcomes may help inform strategic planning, change healthcare policy, and contribute to ‘basic’ research discoveries 7, 8. Epidemiological studies confirm inherited risk factors influence the development and progression of diabetic nephropathy, however identifying clinically useful biomarkers and effective therapies is proving