Evidence mapPaperPMID 40872649Full record

ArticleVeterinary sciences2025

Metabolic Profiles of Feline Obesity Revealed by Untargeted and Targeted Mass Spectrometry-Based Metabolomics Approaches.

Renata Barić Rafaj, Ivana Rubić, Josipa Kuleš, Dominik Prišćan, Alberto Muñoz-Prieto, Jelena Gotić, Luka Ećimović, Nada Kučer, Marko Samardžija, Mislav Kovačić and 1 more

Abstract read
In one paragraph

Article in Veterinary sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Trial
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Renata Barić RafajDepartment of Chemistry and Biochemistry, Faculty of Veterinary Medicine, University of Zagreb, 10000 Zagreb, Croatia.
Ivana RubićLaboratory of Proteomics, Clinic for Internal Diseases, Faculty of Veterinary Medicine, University of Zagreb, 10000 Zagreb, Croatia.
Josipa KulešDepartment of Chemistry and Biochemistry, Faculty of Veterinary Medicine, University of Zagreb, 10000 Zagreb, Croatia.ORCID 0000-0002-4945-4690
Dominik PrišćanLaboratory of Proteomics, Clinic for Internal Diseases, Faculty of Veterinary Medicine, University of Zagreb, 10000 Zagreb, Croatia.
Alberto Muñoz-PrietoInterdisciplinary Laboratory of Clinical Pathology, Interlab-UMU, Campus of Excellence Mare Nostrum, University of Murcia, 30100 Murcia, Spain.ORCID 0000-0001-6865-8712
Jelena GotićClinic for Internal Diseases, Faculty of Veterinary Medicine, University of Zagreb, 10000 Zagreb, Croatia.
Luka EćimovićClinical Pathology Laboratory, University Animal Hospital, Swedish University of Agricultural Sciences, SE-75007 Uppsala, Sweden.
Nada KučerClinic for Internal Diseases, Faculty of Veterinary Medicine, University of Zagreb, 10000 Zagreb, Croatia.
Marko SamardžijaClinic for Reproduction and Obstetretic, Faculty of Veterinary Medicine, University of Zagreb, 10000 Zagreb, Croatia.ORCID 0000-0003-0402-3173
Mislav KovačićDepartment of Biology, J.J. Strossmayer University of Osijek, 31000 Osijek, Croatia.ORCID 0000-0001-9805-5226
Vladimir MrljakClinic for Internal Diseases, Faculty of Veterinary Medicine, University of Zagreb, 10000 Zagreb, Croatia.ORCID 0000-0002-0723-7815

Funding

European Regional Development Fund KK.01.1.1.04.0086University of Zagreb nn
6 · The paper itself

Abstract

Obesity is currently one of the major medical problems affecting humans and companion animals, including cats; however, a detailed understanding of the metabolic processes altered in feline obesity remains limited. This study aimed to investigate obesity-related changes in the serum metabolome of three groups of cats, metabolically healthy normal-weight (MHN) cats, metabolically healthy overweight (MHO) cats, and metabolically unhealthy overweight (MUO) cats. Metabolome changes were assessed using LC-MS (untargeted), LC-MS (targeted), and FIA-MS (targeted) methods. Untargeted analysis detected 141 significant annotated features, while targeted approach identified 48 metabolites significantly associated with obesity. Both untargeted and targeted analyses showed lower kynurenine levels in the MUO group compared to the MHN group. Targeted LC-MS analysis identified 11 significant metabolites, whereas the FIA-MS approach detected 37. Four metabolites-glycine, citrulline, and two phosphatidylcholines-were found at lower levels in the MHO group compared to the MHN group. Arginine and proline metabolism, along with methionine metabolism, were significantly altered pathways, while thyroid hormone synthesis was independently altered with the highest enrichment ratio. The obtained results suggest that cats with a healthy phenotype exhibit an intermediate-metabolic-risk profile and provide new insights into the metabolic mechanisms and pathways underlying feline obesity.

Indexed as

felinemass spectrometrymetabolomicsobesity

Identifiers

PMID40872649
PMCPMC12390338

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.