Background: Serum protein biomarkers are used to diagnose, monitor treatment response, and to differentiate various forms of chronic enteropathies (CE) in humans. The utility of liquid biopsy proteomic approaches has not been examined in cats.
Hypothesis/objectives: To explore the serum proteome in cats to identify markers differentiating healthy cats from cats with CE.
Animals: Ten cats with CE with signs of gastrointestinal disease of at least 3 weeks duration, and biopsy-confirmed diagnoses, with or without treatment and 19 healthy cats were included.
Methods: Cross-sectional, multicenter, exploratory study with cases recruited from 3 veterinary hospitals between May 2019 and November 2020. Serum samples were analyzed and evaluated using mass spectrometry-based proteomic techniques.
Results: Twenty-six proteins were significantly (P < .02, ≥5-fold change in abundance) differentially expressed between cats with CE and controls. Thrombospondin-1 (THBS1) was identified with >50-fold increase in abundance in cats with CE (P < 0.001) compared to healthy cats.
Conclusions And Clinical Importance: Damage to the gut lining released marker proteins of chronic inflammation that were detectable in serum samples of cats. This early-stage exploratory study strongly supports THBS1 as a candidate biomarker for chronic inflammatory enteropathy in cats.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365053 | PMC |
| http://dx.doi.org/10.1111/jvim.16743 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Impact of increasingly complex cell culture conditions on the proteome of human periodontal ligament stem cells.
Regen Med
January 2025
Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Leioa, Spain.
Aims: Human periodontal ligament stem cells (hPDLSCs) exhibit an enormous potential to regenerate periodontal tissue. However, their translatability to the clinical setting is constrained by technical difficulties in standardizing culture conditions. The aim was to assess complex culture conditions using a proteomic-based protocol to standardize multi-layer hPDLSC cultivation methodology.
View Article and Find Full Text PDFProteomic changes upon treatment with semaglutide in individuals with obesity.
Nat Med
January 2025
Data Science, Novo Nordisk A/S, Søborg, Denmark.
Obesity and type 2 diabetes are prevalent chronic diseases effectively managed by semaglutide. Here we studied the effects of semaglutide on the circulating proteome using baseline and end-of-treatment serum samples from two phase 3 trials in participants with overweight or obesity, with or without diabetes: STEP 1 (n = 1,311) and STEP 2 (n = 645). We identified evidence supporting broad effects of semaglutide, implicating processes related to body weight regulation, glycemic control, lipid metabolism and inflammatory pathways.
View Article and Find Full Text PDFBasic Science and Pathogenesis.
Alzheimers Dement
December 2024
University of Kansas Alzheimer's Disease Research Center, Fairway, KS, USA.
Background: Apolipoprotein ε4 (APOE4) is a major risk factor for Alzheimer's disease (AD). APOE4 carriers display altered whole-body metabolism, including increased blood glucose and inuslin. Although conditions affecting whole-body metabolism like obesity and diabetes are AD risk factors, knowledge regarding the contribution of peripheral tissues to this effect is minimal.
View Article and Find Full Text PDFBasic Science and Pathogenesis.
Alzheimers Dement
December 2024
University of Kentucky, Lexington, KY, USA.
Background: Aging microglia accumulate lipid droplets (LDs), secrete pro-inflammatory cytokines, and are defective in phagocytosis. The E4 allele of Apolipoprotein E (APOE) is the strongest genetic risk factor for late-onset Alzheimer's disease (LOAD) and is associated with increased neuroinflammation and LD accumulation. Here, we aimed to determine if the effects of aging and the E4 allele are synergistic in causing the accumulation of LDs seen in LOAD.
View Article and Find Full Text PDFMulti-omic biomarker panel in pancreatic cyst fluid and serum predicts patients at a high risk of pancreatic cancer development.
Sci Rep
January 2025
Department of Surgery, Trinity St. James's Cancer Institute, Trinity Translational Medicine Institute, Trinity College Dublin, St. James's Hospital, Dublin 8, Ireland.
Integration of multi-omic data for the purposes of biomarker discovery can provide novel and robust panels across multiple biological compartments. Appropriate analytical methods are key to ensuring accurate and meaningful outputs in the multi-omic setting. Here, we extensively profile the proteome and transcriptome of patient pancreatic cyst fluid (PCF) (n = 32) and serum (n = 68), before integrating matched omic and biofluid data, to identify biomarkers of pancreatic cancer risk.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!