Mass spectrometry-based proteomics profiling of dogs with and without oral diseases: a systematic review.

BACKGROUND

Understanding the distinct proteomics profiles in dogs' oral biofluids enhances diagnostic and therapeutic insights for canine oral diseases, fostering cross-species translational research in dentistry and medicine. This study aimed to conduct a systematic review to investigate the similarities and differences between the oral biofluids' proteomics profile of dogs with and without oral diseases.

METHODS

PubMed, Web of Science, and Scopus were searched with no restrictions on publication language or year to address the following focused question: "What is the proteome signature of healthy versus diseased (oral) dogs' biofluids?" Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes pathway analyses of the most abundant proteins were performed. Moreover, protein-protein interaction analysis was conducted. The risk of bias (RoB) among the included studies was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Studies Reporting Prevalence Data.

RESULTS

In healthy dogs, the proteomic analysis identified 5,451 proteins, with 137 being the most abundant, predominantly associated with 'innate immune response'. Dogs with oral diseases displayed 6,470 proteins, with distinct associations: 'defense response to bacterium' (periodontal diseases), 'negative regulation of transcription' (dental calculus), and 'positive regulation of transcription' (oral tumors). Clustering revealed significant protein clusters in each case, emphasizing the diverse molecular profiles in health and oral diseases. Only six studies were provided to the JBI tool, as they encompassed case-control evaluations that compared healthy dogs to dogs with oral disease(s). All included studies were found to have low RoB (high quality).

CONCLUSION

Significant differences in the proteomics profiles of oral biofluids between dogs with and without oral diseases were found. The synergy of animal proteomics and bioinformatics offers a promising avenue for cross-species research, despite persistent challenges in result validation.