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Perspectives on Systems Biology Applications in Diabetic Kidney Disease

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Abstract

Diabetic kidney disease (DKD) is a microvascular complication of type 1 and 2 diabetes with a devastating impact on individuals with the disease, their families, and society as a whole. DKD is the single most frequent cause of incident chronic kidney disease cases and accounts for over 40 % of the population with end-stage renal disease. Contributing factors for the high prevalence are the increase in obesity and subsequent diabetes combined with an improved long-term survival with diabetes. Environment and genetic variations contribute to DKD susceptibility and progressive loss of kidney function. How the molecular mechanisms of genetic and environmental exposures interact during DKD initiation and progression is the focus of ongoing research efforts. The development of standardized, unbiased high-throughput profiling technologies of human DKD samples opens new avenues in capturing the multiple layers of DKD pathobiology. These techniques routinely interrogate analytes on a genome-wide scale generating comprehensive DKD-associated fingerprints. Linking the molecular fingerprints to deep clinical phenotypes may ultimately elucidate the intricate molecular interplay in a disease stage and subtype-specific manner. This insight will form the basis for accurate prognosis and facilitate targeted therapeutic interventions. In this review, we present ongoing efforts from large-scale data integration translating “-omics” research efforts into improved and individualized health care in DKD.

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Abbreviations

GWAS:

Genome-wide association study

SNP:

Single nucleotide polymorphism

CNV:

Copy number variation

NF-κB:

Nuclear factor κ-light chain enhancer of activated B cells

JAK/STAT:

Janus kinase/signal transducer and activator of transcription

MCP-1/CCL2:

Macrophage chemoattractant protein 1

FDA:

Food and Drug Administration

DCCT/EDIC:

The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study

UKPDS:

The UK Prospective Diabetes Study

ERCB:

European Renal cDNA Bank–Kröner–Fresenius Biopsy Bank

MIAME:

Minimum Information About a Microarray Experiment

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Acknowledgments

This work was supported by grants from the Juvenile Diabetes Research Foundation to M.K. and S.P., the German Research Foundation to C.V.K. (KO 4266/1-1), the National Institutes of Health, National Institute of Diabetes, and Digestive and Kidney Disease (P30-DK-081943 to F.C.B. and M.K; DK083912 to M.K.; DK089503, DK094292 to S.P.; DK082841 to M.K. and S.P.). The authors appreciate the assistance of Dr. Jeff B. Hodgin (Department of Pathology, University of Michigan) in providing the histological images. We further thank Chandra Hall for carefully proofreading the manuscript and the editor and referees for helpful comments and suggestions on an earlier version of the manuscript. The authors apologize to those colleagues whose work we were unable to cite in this review due to space limitation.

Conflict of Interest

The authors declare no competing financial interest.

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Authors and Affiliations

  1. Division of Nephrology, Department of Internal Medicine, University of Michigan Medical School, 1150 West Medical Center Drive, MSRB II. Room 1570, Ann Arbor, MI, 48109 0676, USA

    Claudiu V. Komorowsky, Frank C. Brosius 3rd, Subramaniam Pennathur & Matthias Kretzler

  2. Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 1150 West Medical Center Drive, MSRB II, Room 1570, Ann Arbor, MI, 48109-0676, USA

    Matthias Kretzler

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  1. Claudiu V. Komorowsky
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  2. Frank C. Brosius 3rd
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  3. Subramaniam Pennathur
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  4. Matthias Kretzler
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Correspondence to Subramaniam Pennathur or Matthias Kretzler.

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Komorowsky, C.V., Brosius, F.C., Pennathur, S. et al. Perspectives on Systems Biology Applications in Diabetic Kidney Disease. J. of Cardiovasc. Trans. Res. 5, 491–508 (2012). https://doi.org/10.1007/s12265-012-9382-7

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  • DOI: https://doi.org/10.1007/s12265-012-9382-7

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