Correlation between metabolomic profile constituents and feline pancreatic lipase immunoreactivity.

cerebrosides fPLI feline pancreatitis sphingolipids sphingomyelins untargeted metabolomics

Journal

Journal of veterinary internal medicine
ISSN: 1939-1676
Titre abrégé: J Vet Intern Med
Pays: United States
ID NLM: 8708660

Informations de publication

Date de publication:
Mar 2022
Historique:
revised: 16 12 2021
received: 09 09 2021
accepted: 22 12 2021
pubmed: 14 1 2022
medline: 1 4 2022
entrez: 13 1 2022
Statut: ppublish

Résumé

Feline pancreatic lipase immunoreactivity (fPLI) is commonly used to diagnose pancreatitis in cats (FP). Untargeted metabolomics has been extensively applied in human and veterinary medicine, but no metabolomic studies regarding FP have been conducted. To identify metabolites significantly associated with increased fPLI. Forty-nine client-owned cats: 11 clinically healthy and 38 with various clinical conditions. Analytical cross-sectional study with convenience sampling. A panel of 630 metabolites belonging to 26 biochemical classes was quantified in plasma using a commercial metabolomic assay. The correlation between plasma metabolite concentrations and serum fPLI was evaluated using Spearman's rank correlation coefficient (R Four hundred and seven of 630 metabolites (64.6%) were quantified in all cats. When controlled for potential confounders only 3 sphingolipids were significantly positively correlated with fPLI: 2 cerebrosides: HexCer(d18:1/24:0); (R Selected sphingolipids are moderately positively correlated with fPLI and appear to have fair to moderate diagnostic accuracy in discriminating between cats with normal and increased fPLI.

Sections du résumé

BACKGROUND BACKGROUND
Feline pancreatic lipase immunoreactivity (fPLI) is commonly used to diagnose pancreatitis in cats (FP). Untargeted metabolomics has been extensively applied in human and veterinary medicine, but no metabolomic studies regarding FP have been conducted.
OBJECTIVES OBJECTIVE
To identify metabolites significantly associated with increased fPLI.
ANIMALS METHODS
Forty-nine client-owned cats: 11 clinically healthy and 38 with various clinical conditions.
METHODS METHODS
Analytical cross-sectional study with convenience sampling. A panel of 630 metabolites belonging to 26 biochemical classes was quantified in plasma using a commercial metabolomic assay. The correlation between plasma metabolite concentrations and serum fPLI was evaluated using Spearman's rank correlation coefficient (R
RESULTS RESULTS
Four hundred and seven of 630 metabolites (64.6%) were quantified in all cats. When controlled for potential confounders only 3 sphingolipids were significantly positively correlated with fPLI: 2 cerebrosides: HexCer(d18:1/24:0); (R
CONCLUSIONS AND CLINICAL IMPORTANCE CONCLUSIONS
Selected sphingolipids are moderately positively correlated with fPLI and appear to have fair to moderate diagnostic accuracy in discriminating between cats with normal and increased fPLI.

Identifiants

pubmed: 35023223
doi: 10.1111/jvim.16349
pmc: PMC8965226
doi:

Substances chimiques

Lipase EC 3.1.1.3

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

473-481

Subventions

Organisme : Narodowe Centrum Nauki
ID : 2019/03/X/NZ5/00164

Informations de copyright

© 2022 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals LLC on behalf of American College of Veterinary Internal Medicine.

Références

Pancreatology. 2017 Jul - Aug;17(4):543-549
pubmed: 28487129
J Vet Intern Med. 2014 Nov-Dec;28(6):1699-701
pubmed: 25272985
Int J Mol Sci. 2018 Oct 23;19(11):
pubmed: 30360494
Toxicology. 2008 Mar 20;245(3):194-205
pubmed: 18291570
PLoS One. 2017 May 22;12(5):e0177675
pubmed: 28531195
Biochim Biophys Acta Mol Basis Dis. 2021 Jul 1;1867(7):166123
pubmed: 33713791
J Vet Intern Med. 1993 Jan-Feb;7(1):25-33
pubmed: 8455180
Diabetes. 1989 Nov;38(11):1478-83
pubmed: 2695376
Turk J Emerg Med. 2018 Aug 07;18(3):91-93
pubmed: 30191186
J Vet Intern Med. 2013 Sep-Oct;27(5):1077-82
pubmed: 23888903
PLoS One. 2020 Jul 2;15(7):e0235480
pubmed: 32614877
J Small Anim Pract. 2015 Jan;56(1):13-26
pubmed: 25586803
J Comp Pathol. 2020 Jan;174:63-72
pubmed: 31955805
Vet Clin Pathol. 2012 Sep;41(3):312-24
pubmed: 22861648
Int J Mol Sci. 2018 Oct 12;19(10):
pubmed: 30321983
J Vet Intern Med. 2022 Mar;36(2):473-481
pubmed: 35023223
Hepatogastroenterology. 2012 Oct;59(119):2314-7
pubmed: 22328301
J Vet Intern Med. 2018 Nov;32(6):1874-1885
pubmed: 30315665
Vet Clin North Am Small Anim Pract. 2020 Sep;50(5):1107-1121
pubmed: 32680667
Am J Epidemiol. 1995 Nov 1;142(9):904-8
pubmed: 7572970
J Pharm Biomed Anal. 2015 Sep 10;113:108-20
pubmed: 25577715
J Vet Intern Med. 2021 Mar;35(2):703-723
pubmed: 33587762
Vet Pathol. 2007 Jan;44(1):39-49
pubmed: 17197622
Surgery. 2016 Jun;159(6):1638-1645
pubmed: 26962006
J Vet Intern Med. 2015 Mar-Apr;29(2):589-96
pubmed: 25818213
J Feline Med Surg. 2014 May;16(5):395-406
pubmed: 24794036
Cancer. 2000 Apr 15;88(8):1828-36
pubmed: 10760759
J Vet Intern Med. 2001 Jul-Aug;15(4):327-8
pubmed: 11467588
J Vet Intern Med. 2014 Nov-Dec;28(6):1676-83
pubmed: 25231385
Nat Rev Mol Cell Biol. 2008 Feb;9(2):139-50
pubmed: 18216770
J Small Anim Pract. 2015 Jan;56(1):40-9
pubmed: 25586805
J Vet Intern Med. 2020 Jul;34(4):1406-1412
pubmed: 32452547
J Vet Res. 2020 Nov 06;64(4):581-588
pubmed: 33367148
Top Companion Anim Med. 2008 Nov;23(4):185-92
pubmed: 19081552
J Am Vet Med Assoc. 2003 Aug 15;223(4):469-74
pubmed: 12930084
Lab Med. 2020 Mar 10;51(2):116-121
pubmed: 31340007
Biomolecules. 2013 Jul 25;3(3):435-48
pubmed: 24970174
J Vet Intern Med. 2016 Jul;30(4):1031-45
pubmed: 27296565
Diabetologia. 2019 Jun;62(6):1036-1047
pubmed: 30955045
Front Vet Sci. 2020 May 15;7:218
pubmed: 32500084
Sci Rep. 2021 Apr 28;11(1):9198
pubmed: 33911166
Pancreas. 2018 Aug;47(7):898-903
pubmed: 29939906
J Feline Med Surg. 2011 Aug;13(8):570-6
pubmed: 21719332
PLoS One. 2021 Apr 22;16(4):e0249322
pubmed: 33886598
Int J Mol Sci. 2017 Dec 04;18(12):
pubmed: 29207545
Vet Clin North Am Small Anim Pract. 2003 Sep;33(5):1181-95
pubmed: 14552167
J Vet Intern Med. 2016 May;30(3):764-70
pubmed: 26968865
J Small Anim Pract. 2010 Sep;51(9):484-9
pubmed: 21050218
Metabolomics. 2020 Jan 18;16(2):16
pubmed: 31955274
Prev Vet Med. 2000 May 30;45(1-2):23-41
pubmed: 10802332
J Am Vet Med Assoc. 2014 May 1;244(9):1060-5
pubmed: 24739116
J Proteome Res. 2014 Dec 5;13(12):5362-75
pubmed: 25160714
Vet J. 2016 Sep;215:87-95
pubmed: 26951862
Front Vet Sci. 2017 Feb 14;4:17
pubmed: 28261588

Auteurs

Magdalena Maria Krasztel (MM)

Division of Veterinary Epidemiology and Economics, Institute of Veterinary Medicine, Warsaw University of Life Sciences-SGGW, Warsaw, Poland.

Michał Czopowicz (M)

Division of Veterinary Epidemiology and Economics, Institute of Veterinary Medicine, Warsaw University of Life Sciences-SGGW, Warsaw, Poland.

Olga Szaluś-Jordanow (O)

Department of Small Animal Diseases with Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences-SGGW, Warsaw, Poland.

Agata Moroz (A)

Division of Veterinary Epidemiology and Economics, Institute of Veterinary Medicine, Warsaw University of Life Sciences-SGGW, Warsaw, Poland.

Marcin Mickiewicz (M)

Division of Veterinary Epidemiology and Economics, Institute of Veterinary Medicine, Warsaw University of Life Sciences-SGGW, Warsaw, Poland.

Jarosław Kaba (J)

Division of Veterinary Epidemiology and Economics, Institute of Veterinary Medicine, Warsaw University of Life Sciences-SGGW, Warsaw, Poland.

Articles similaires

Humans United States Aged Cross-Sectional Studies Medicare Part C
Robotic Surgical Procedures Animals Humans Telemedicine Models, Animal

Odour generalisation and detection dog training.

Lyn Caldicott, Thomas W Pike, Helen E Zulch et al.
1.00
Animals Odorants Dogs Generalization, Psychological Smell
Animals TOR Serine-Threonine Kinases Colorectal Neoplasms Colitis Mice

Classifications MeSH