Bridging the Gap in Renal Translational Research: Bringing Large Scale Data Sets into Renal Research Labs audioicon

In biomedicine we are currently experiencing a fundamental transition from research focused on the functions of single entities (molecules or pathways) to an integrative biology analyzing biological systems as a unified whole. The need for systems biology approaches in medicine is rapidly expanding as genome wide technology platforms generate demands for multi-level, multi-dimensional analyses to model biological processes. Based on such data novel hypotheses of organ function and failure can be generated and subsequently tested.

The multilayered complexity of renal function mandates an integrative approach. Accordingly, nephrology offers unique opportunities for the transition to integrative biology. Renal function is closely linked with the integrity of the human organism in a bidirectional manner. Systemic metabolic, vascular or immune diseases impact renal function and vice versa; acute or chronic renal failure is one of the strongest predictors of progression of these systemic diseases towards system failure, i. e. death.

Focused scientific efforts have led to the identification of hundreds of essential processes in renal function and failure. This reductionistic approach mandates evaluation of each of these processes in isolation. With the advent of genome wide analytical capabilities it has become feasible to capture readouts of multiple regulatory biological systems at high precision and depth. To gain a comprehensive understanding of these interacting biological systems requires a multidisciplinary approach for data generation, analysis and integration with available knowledge.
In this presentation I will report our 14 years of experience on building multidisciplinary analysis strategies for large scale data integration in renal disease. A team of nephrologists, pathologists, biologists, bioinformaticians, biochemists and computer-scientists joined forces to provide a platform for large-scale data generation and integration in renal disease. We follow the principle of systems biology and consider disease development to progress along the genome-phenome continuum with multilayered interaction between DNA, RNA, protein, metabolites towards intra-cellular organization, tissue homeostasis and organismal interaction.

Examples of the initial strategies developed for binary analyses, integrating two complex data sets will be presented and a case made for the need to transition to multi-dimensional analysis of renal disease.

Study supported in part by P30 DK081943, U54 DK083912, U54 DA021519, R24 DK082841, R01 DK079912, R01GM071966, NephCure and JDRF.

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This was presented at the ISN Forefronts Symposium event “Systems Biology and the Kidney” that took place from 7-10 June 2012 in AnnArbor , Michigan, US.

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Last modified on Saturday, 22 March 2014 20:09

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