Literature DB >> 29478865

How Omics Data Can Be Used in Nephrology.

Eugene P Rhee1.   

Abstract

Advances in technology and computing now permit the high-throughput analysis of multiple domains of biological information, including the genome, transcriptome, proteome, and metabolome. These omics approaches, particularly comprehensive analysis of the genome, have catalyzed major discoveries in science and medicine, including in nephrology. However, they also generate large complex data sets that can be difficult to synthesize from a clinical perspective. This article seeks to provide an overview that makes omics technologies relevant to the practicing nephrologist, framing these tools as an extension of how we approach patient care in the clinic. More specifically, omics technologies reinforce the impact that genetic mutations can have on a range of kidney disorders, expand the catalogue of uremic molecules that accumulate in blood with kidney failure, enhance our ability to scrutinize urine beyond urinalysis for insight on renal pathology, and enable more extensive characterization of kidney tissue when a biopsy is performed. Although assay methodologies vary widely, all omics technologies share a common conceptual framework that embraces unbiased discovery at the molecular level. Ultimately, the application of these technologies seeks to elucidate a more mechanistic and individualized approach to the diagnosis and treatment of human disease.
Copyright © 2018 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Omics; analytic methods; genomics; metabolomics; nephrology research; proteomics; rev; systems biology; transcriptomics; translational research; urinomics

Mesh:

Year:  2018        PMID: 29478865      PMCID: PMC6019111          DOI: 10.1053/j.ajkd.2017.12.008

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN: 0272-6386            Impact factor:   8.860


  58 in total

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Authors:  Joel N Hirschhorn; Mark J Daly
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Review 3.  Understanding the epigenetic syntax for the genetic alphabet in the kidney.

Authors:  Katalin Susztak
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Review 4.  Genetics of kidney failure and the evolving story of APOL1.

Authors:  David J Friedman; Martin R Pollak
Journal:  J Clin Invest       Date:  2011-09-01       Impact factor: 14.808

5.  Proteomics. Tissue-based map of the human proteome.

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Journal:  Science       Date:  2015-01-23       Impact factor: 47.728

6.  Laser microdissection and proteomic analysis of amyloidosis, cryoglobulinemic GN, fibrillary GN, and immunotactoid glomerulopathy.

Authors:  Sanjeev Sethi; Jason D Theis; Julie A Vrana; Fernando C Fervenza; Anjali Sethi; Qi Qian; Patrick Quint; Nelson Leung; Ahmet Dogan; Samih H Nasr
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7.  Plasma concentration of asymmetrical dimethylarginine and mortality in patients with end-stage renal disease: a prospective study.

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Journal:  Lancet       Date:  2001 Dec 22-29       Impact factor: 79.321

Review 8.  Genetic bases and clinical manifestations of coenzyme Q10 (CoQ 10) deficiency.

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9.  Metabolomics reveals signature of mitochondrial dysfunction in diabetic kidney disease.

Authors:  Kumar Sharma; Bethany Karl; Anna V Mathew; Jon A Gangoiti; Christina L Wassel; Rintaro Saito; Minya Pu; Shoba Sharma; Young-Hyun You; Lin Wang; Maggie Diamond-Stanic; Maja T Lindenmeyer; Carol Forsblom; Wei Wu; Joachim H Ix; Trey Ideker; Jeffrey B Kopp; Sanjay K Nigam; Clemens D Cohen; Per-Henrik Groop; Bruce A Barshop; Loki Natarajan; William L Nyhan; Robert K Naviaux
Journal:  J Am Soc Nephrol       Date:  2013-10-10       Impact factor: 10.121

Review 10.  The sequence of sequencers: The history of sequencing DNA.

Authors:  James M Heather; Benjamin Chain
Journal:  Genomics       Date:  2015-11-10       Impact factor: 5.736

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  7 in total

1.  The Serum Metabolome Identifies Biomarkers of Dietary Acid Load in 2 Studies of Adults with Chronic Kidney Disease.

Authors:  Casey M Rebholz; Aditya Surapaneni; Andrew S Levey; Mark J Sarnak; Lesley A Inker; Lawrence J Appel; Josef Coresh; Morgan E Grams
Journal:  J Nutr       Date:  2019-04-01       Impact factor: 4.798

2.  A Comprehensive Proteomics Analysis of Urinary Extracellular Vesicles Identifies a Specific Kinase Protein Profile as a Novel Hallmark of Medullary Sponge Kidney Disease.

Authors:  Maurizio Bruschi; Simona Granata; Andrea Petretto; Alberto Verlato; Gian Marco Ghiggeri; Giovanni Stallone; Giovanni Candiano; Gianluigi Zaza
Journal:  Kidney Int Rep       Date:  2022-03-02

Review 3.  Mendelian Randomization Analysis as a Tool to Gain Insights into Causes of Diseases: A Primer.

Authors:  Adrienne Tin; Anna Köttgen
Journal:  J Am Soc Nephrol       Date:  2021-06-16       Impact factor: 14.978

4.  Metabolomic analysis of uremic pruritus in patients on hemodialysis.

Authors:  Christian G Bolanos; Nhat M Pham; Robert D Mair; Timothy W Meyer; Tammy L Sirich
Journal:  PLoS One       Date:  2021-02-12       Impact factor: 3.240

Review 5.  Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection.

Authors:  Jeong-Hoon Lim; Byung Ha Chung; Sang-Ho Lee; Hee-Yeon Jung; Ji-Young Choi; Jang-Hee Cho; Sun-Hee Park; Yong-Lim Kim; Chan-Duck Kim
Journal:  Korean J Intern Med       Date:  2022-04-15       Impact factor: 3.165

6.  Proteomic Analysis of Renal Biomarkers of Kidney Allograft Fibrosis-A Study in Renal Transplant Patients.

Authors:  Line Aas Mortensen; Anne Marie Svane; Mark Burton; Claus Bistrup; Helle Charlotte Thiesson; Niels Marcussen; Hans Christian Beck
Journal:  Int J Mol Sci       Date:  2020-03-30       Impact factor: 5.923

7.  Changes in Novel AKI Biomarkers after Exercise. A Systematic Review.

Authors:  Wojciech Wołyniec; Wojciech Ratkowski; Joanna Renke; Marcin Renke
Journal:  Int J Mol Sci       Date:  2020-08-07       Impact factor: 5.923

  7 in total

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