How Omics Data Can Be Used in Nephrology

Am J Kidney Dis. 2018 Jul;72(1):129-135. doi: 10.1053/j.ajkd.2017.12.008. Epub 2018 Feb 23.

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.

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

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Genomics / methods*
  • Genomics / trends
  • Humans
  • Metabolomics / methods*
  • Metabolomics / trends
  • Nephrology / methods*
  • Nephrology / trends
  • Proteomics / methods*
  • Proteomics / trends
  • Renal Insufficiency, Chronic / diagnosis
  • Renal Insufficiency, Chronic / genetics*
  • Renal Insufficiency, Chronic / metabolism*
  • Transcriptome / genetics