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Untargeted gas chromatography–mass spectrometry-based metabolomics analysis of kidney and liver tissue from the Lewis Polycystic Kidney rat

  • Hayley Abbiss
  • , Garth L. Maker
  • , Joel P.A. Gummer
  • , Catherine Rawlinson
  • , Gabrielle C. Musk
  • , Patricia A. Fleming
  • , Jacqueline K. Phillips
  • , Mary C. Boyce
  • , Robert D. Trengove

Research output: Contribution to journalArticlepeer-review

Abstract

Polycystic kidney disease (PKD) encompasses a spectrum of inherited disorders that lead to end-stage renal disease (ESRD). There is no cure for PKD and current treatment options are limited to renal replacement therapy and transplantation. A better understanding of the pathobiology of PKD is needed for the development of new, less invasive treatments. The Lewis Polycystic Kidney (LPK) rat phenotype has been characterized and classified as a model of nephronophthisis (NPHP9, caused by mutation of the Nek8 gene) for which polycystic kidneys are one of the main pathologic features. The aim of this study was to use a GC–MS-based untargeted metabolomics approach to determine key biochemical changes in kidney and liver tissue of the LPK rat. Tissues from 16-week old LPK (n = 10) and Lewis age- and sex-matched control animals (n = 11) were used. Principal component analysis (PCA) distinguished signal corrected metabolite profiles from Lewis and LPK rats for kidney (PC-1 77%) and liver (PC-1 46%) tissue. There were marked differences in the metabolite profiles of the kidney tissues with 122 deconvoluted features significantly different between the LPK and Lewis strains. The metabolite profiles were less marked between strains for liver samples with 30 features significantly different. Five biochemical pathways showed three or more significantly altered metabolites: transcription/translation, arginine and proline metabolism, alpha-linolenic and linoleic acid metabolism, the citric acid cycle, and the urea cycle. The results of this study validate and complement the current literature and are consistent with the understood pathobiology of PKD.

Original languageEnglish
Pages (from-to)25-32
Number of pages8
JournalJournal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences
Volume1118-1119
DOIs
Publication statusPublished - 15 Jun 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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