Genomic biomarkers for chronic kidney disease

Ju, Wenjun; Smith, Shahaan; Kretzler, Matthias

doi:10.1016/j.trsl.2012.01.020

Cited by 34 publications

(24 citation statements)

References 72 publications

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“…71–75 In particular, new noninvasive urinary and serum/plasma biomarkers for DKD provide valuable insights in interpreting the disease pathogenesis and show potential roles in clinical medicine. To better understand the role of DKD biomarkers in the development of disease, Saito et al 76 integrated 13 previously reported DKD urinary metabolite bio-markers with publicly available protein–protein interaction networks.…”

Section: Understanding Dkd Using a Systems Biology Approachmentioning

confidence: 99%

The Warburg Effect in Diabetic Kidney Disease

Zhang

Darshi

Sharma

2018

Seminars in Nephrology

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Summary Diabetic kidney disease (DKD) is the leading cause of morbidity and mortality in diabetic patients. Defining risk factors for DKD using a reductionist approach has proven challenging. Integrative omics-based systems biology tools have shed new insights in our understanding of DKD and have provided several key breakthroughs for identifying novel predictive and diagnostic biomarkers. In this review, we highlight the role of the Warburg effect in DKD and potential regulating factors such as sphingomyelin, fumarate, and pyruvate kinase muscle isozyme M2 in shifting glucose flux from complete oxidation in mitochondria to the glycolytic pathway and its principal branches. With the development of highly sensitive instruments and more advanced automatic bioinformatics tools, we believe that omics analyses and imaging techniques will focus more on singular-cell-level studies, which will allow in-depth understanding of DKD and pave the path for personalized kidney precision medicine.

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Section: Understanding Dkd Using a Systems Biology Approachmentioning

confidence: 99%

The Warburg Effect in Diabetic Kidney Disease

Zhang

Darshi

Sharma

2018

Seminars in Nephrology

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“…The great potential of genomic biomarkers in evaluation and treatment of patients with chronic renal disease is discussed by Ju and co-workers (36). Genomic markers are measurements of the expression, function or regulation of genes and may consist of one or more DNA characteristics (such as single nucleotide polymorphisms, DNA modifications, haplotypes or cytogenetic rearrangements) or RNA characteristics (such as RNA sequences and expression levels).…”

Section: Biomarkers and Renal Diseasementioning

confidence: 99%

Biomarkers: hopes and challenges in the path from discovery to clinical practice

Frangogiannis

2012

Translational Research

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Biomarkers are objectively measured indicators of normal or pathological processes that may be helpful in diagnosis, staging, monitoring treatment, or prognostic evaluation of a disease. Although development of genomic, metabolomic and proteomic technologies has contributed to an explosion in identification of candidate analytes, validation remains expensive and challenging, and successful introduction of new biomarkers to clinical practice occurs at a very slow pace. The goal of this introductory overview is to provide the context for a series of review manuscripts published in the special issue on biomarkers. The promises and challenges of biomarker discovery are highlighted. Discovery and implementation of transformative new biomarkers in clinical practice requires close collaborations between scientists, clinicians and industry. High throughput technologies can identify a myriad of promising candidates but cannot predict their clinical value. In addition to rapid effective and systematic approaches for clinical validation, there is a need to study and establish links between the purported biomarker and the pathophysiologic basis of the disease of interest. Biomarkers are most informative when they provide insights into activation of specific pathways, thus serving as windows into the molecular basis of the disease.

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“…Biomarkers can be classified according to their purpose: diagnostic, disease staging and prognostic, as well as source based – genomic, transcriptomic, proteomic and metabolomic marker(s). The field of biomarkers in DKD and kidney disease in general is rapidly evolving and has been extensively reviewed in [119,197,198]. …”

Section: Biomarker: the Surrogates For Diagnosis Risk Assessment Andmentioning

confidence: 99%

Perspectives on Systems Biology Applications in Diabetic Kidney Disease

Komorowsky

Brosius

Pennathur

et al. 2012

J. of Cardiovasc. Trans. Res.

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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 (CKD) cases and accounts for over 40% of the population with end stage renal disease (ESRD). 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 are 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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Genomic biomarkers for chronic kidney disease

Cited by 34 publications

References 72 publications

The Warburg Effect in Diabetic Kidney Disease

The Warburg Effect in Diabetic Kidney Disease

Biomarkers: hopes and challenges in the path from discovery to clinical practice

Perspectives on Systems Biology Applications in Diabetic Kidney Disease

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