Relevance: Chronic renal insufficiency (CRI) is a `silent epidemic'affecting an estimated 10 million Americans. CRI progresses at an unpredictable rate to end stage renal disease (ESRD) with the associated high morbidity, mortality and costs. CRI risk factors are incompletely understood and many questions remain concerning the course of CRI. The Chronic Renal Insufficiency Cohort (CRIC) was initiated as the `Framingham study'of kidney disease to better define risk factors for CRI and CVD. The central hypothesis of the CRIC study postulates a set of unknown risk factors of CRI and aims to identify high-risk subgroups with CRI. In preliminary studies a comprehensive human renal biopsy sample repository and the required molecular and biostatistical technologies to examine molecular mechanism driving CRI have been established. Using genome-wide gene expression profiles of renal biopsies, molecular disease pathways of CRI are currently mapped and underlying transcriptional regulatory control mechanism defined. The most immediate clinical application will stem from the molecular phenotyping of CRI to define mechanistic categories of CRI. The principal hypothesis of this ancillary study to CRIC states that progression of CRI is driven by molecular mechanisms that are currently only partially understood and that markers of these mechanisms can serve as potent predictors of CRI.
Our specific aims will extract the most effective non-invasive, accurate and sensitive biomarkers from available expression profiles taking advantage of the unique design of CRIC: ? In Aim 1 candidate mRNA markers of renal function will be extracted from already available renal biopsy gene expression data using biostatistical modeling tools. ? In Aim 2 these candidate markers will be prospectively evaluated in CRIC biopsies to test their power for predicting the primary endpoint of CRIC (i.e. decline of renal function over time measured as slope of GFR). ? In Aim 3 non-invasive markers of CRI will be extracted from the kidney tissue-derived predictors using parallel studies in plasma, urine and leukocyte samples from the same patients studied in Aim 2. ? In Aim 4 the full CRIC cohort will be analyzed to test the strength of the non-invasive marker panel and define effects of age, race, renal function and diabetes on the prediction of progressive CRI. Combining the molecular datasets from renal biopsy profiling study of CRI with the power of a prospectively followed cohort of CRI patients presents the opportunity to fundamentally alter the way we define and manage CRI. Using intra-renal gene expression profiles to guide the identification of non-invasive molecular diagnostic targets will focus the study on the most promising biomarker candidates for risk stratification of CRI. We anticipate that this study will be a crucial step of a transition from a "one size fits all" management of CRI towards an approach valuing the molecular individuality of each kidney patient. Chronic renal failure causes immense cost and human suffering in the US. This ancillary study to the Chronic Renal Insufficiency Cohort study proposes a step-wise approach combining intra-renal gene expression profiles with highly sensitive and focused proteomic analysis to filter the most promising candidates for non- invasive prediction of progressive chronic renal insufficiency.
|Harder, Jennifer L; Hodgin, Jeffrey B; Kretzler, Matthias (2015) Integrative Biology of Diabetic Kidney Disease. Kidney Dis (Basel) 1:194-203|
|Ju, Wenjun; Nair, Viji; Smith, Shahaan et al. (2015) Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker. Sci Transl Med 7:316ra193|
|Martini, Sebastian; Nair, Viji; Keller, Benjamin J et al. (2014) Integrative biology identifies shared transcriptional networks in CKD. J Am Soc Nephrol 25:2559-72|
|Chung, Sharon A; Brown, Elizabeth E; Williams, Adrienne H et al. (2014) Lupus nephritis susceptibility loci in women with systemic lupus erythematosus. J Am Soc Nephrol 25:2859-70|
|Gadegbeku, Crystal A; Gipson, Debbie S; Holzman, Lawrence B et al. (2013) Design of the Nephrotic Syndrome Study Network (NEPTUNE) to evaluate primary glomerular nephropathy by a multidisciplinary approach. Kidney Int 83:749-56|
|Ju, Wenjun; Greene, Casey S; Eichinger, Felix et al. (2013) Defining cell-type specificity at the transcriptional level in human disease. Genome Res 23:1862-73|
|Hodgin, Jeffrey B; Nair, Viji; Zhang, Hongyu et al. (2013) Identification of cross-species shared transcriptional networks of diabetic nephropathy in human and mouse glomeruli. Diabetes 62:299-308|
|Berthier, Celine C; Bethunaickan, Ramalingam; Gonzalez-Rivera, Tania et al. (2012) Cross-species transcriptional network analysis defines shared inflammatory responses in murine and human lupus nephritis. J Immunol 189:988-1001|
|Ju, Wenjun; Smith, Shahaan; Kretzler, Matthias (2012) Genomic biomarkers for chronic kidney disease. Transl Res 159:290-302|
|Komorowsky, Claudiu V; Brosius 3rd, Frank C; Pennathur, Subramaniam et al. (2012) Perspectives on systems biology applications in diabetic kidney disease. J Cardiovasc Transl Res 5:491-508|
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