Papers

Peer-reviewed
Aug, 2016

Analysis of lipoprotein profiles of healthy cats by gel-permeation high-performance liquid chromatography

JOURNAL OF VETERINARY MEDICAL SCIENCE
  • Hisashi Mizutani
  • ,
  • Toshinori Sako
  • ,
  • Hiroko Okuda
  • ,
  • Nobuaki Arai
  • ,
  • Koji Kuriyama
  • ,
  • Akihiro Mori
  • ,
  • Itaru Yoshimura
  • ,
  • Hidekazu Koyama

Volume
78
Number
8
First page
1277
Last page
1281
Language
English
Publishing type
Research paper (scientific journal)
DOI
10.1292/jvms.16-0052
Publisher
JAPAN SOC VET SCI

Density gradient ultracentrifugation (DGUC) and gel electrophoresis are conventionally used to obtain lipoprotein profiles of animals. We recently applied high-performance liquid chromatography with a gel permeation column (GP-HPLC) and an on-line dual enzymatic system to dogs for lipoprotein profile analysis. We compared the GP-HPLC with DGUC as a method to obtain a feline lipoprotein profile. The lipoprotein profiles showed large and small peaks, which corresponded to high-density lipoprotein (HDL) and low-density lipoprotein (LDL), respectively, whereas very low-density lipoprotein (VLDL) and chylomicron (CM) were only marginally detected. This profile was very similar to that of dogs reported previously. Healthy cats also had a small amount of cholesterol-rich particles distinct from the normal LDL or HDL profile. There was no difference in lipoprotein profiles between the sexes, but males had a significantly larger LDL particle size (P=0.015). This study shows the feasibility of GP-HPLC for obtaining accurate lipoprotein profiles with small sample volumes and provides valuable reference data for healthy cats that should facilitate diagnoses.

Link information
DOI
https://doi.org/10.1292/jvms.16-0052
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/27170431
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000382421600008&DestApp=WOS_CPL
ID information
  • DOI : 10.1292/jvms.16-0052
  • ISSN : 0916-7250
  • eISSN : 1347-7439
  • Pubmed ID : 27170431
  • Web of Science ID : WOS:000382421600008

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