Russian Federation
Russian Federation
Yekaterinburg, Russian Federation
Abstract. The purpose of this study was to identify and explain patterns of biochemical parameters in dairy cows, taking into account the characteristics of their breed. Methods. A comparison was made of samples of animals of five breeds (Holstein, Tagil, Suksun, Sychevsk, Istoben) according to 17 biochemical parameters. The total number of animals studied was 407. To analyze the obtained results, statistical analysis methods were used, including the method of nonlinear principal component analysis using the CATPCA (Categorical PCA) algorithm. Scientific novelty. The chosen method made it possible to summarize a large number of biochemical indicators and identify processes in which the studied groups of cows differed to a greater or lesser extent. Results. Five principal components were identified and interpreted, explaining a total of 67.4 % of the total variance. Some observed patterns may indicate the development of pathological conditions in animals. Similar biochemical patterns were observed, on the one hand, in cows of the Tagil, Holstein and Suksun breeds, and on the other, in the Istoben and Sychev breeds. The animals of the Suksun breed were closest to the physiological norm. More pronounced changes associated with a negative energy balance were observed in Holstein cows.
metabolomics, cattle, biochemical parameters, principal component analysis, breed differences
1. Andjelić B., Djoković R., Cincović M., Bogosavljević-Bošković S., Petrović M., Mladenović J., Čukić A. Relationships between milk and blood biochemical parameters and metabolic status in dairy cows during lactation // Metabolites. 2022. Vol. 12, No. 8. Article number 733. DOI:https://doi.org/10.3390/metabo12080733.; ; EDN: https://elibrary.ru/ADBYFD
2. Guliński P. Ketone bodies – causes and effects of their increased presence in cows' body fluids: A review // Veterinary World. 2021. Vol. 14, No. 6. Pp. 1492–1503. DOI:https://doi.org/10.14202/vetworld.2021.1492-1503.
3. Tufarelli V., Puvača N., Glamočić D., Pugliese G., Colonna, M. A. The most important metabolic diseases in dairy cattle during the transition period // Animals. 2024. Vol. 14. Article number 816. DOI:https://doi.org/10.3390/ani14050816.; ; EDN: https://elibrary.ru/SLILAC
4. Tran H., McConville M., Loukopoulos P. Metabolomics in the study of spontaneous animal diseases // Journal of Veterinary Diagnostic Investigation. 2020. Vol. 32, No. 5. Pp. 635–647. DOI:https://doi.org/10.1177/1040638720948505.
5. Chen Y., Li E. M., Xu L. Y. Guide to metabolomics analysis: A bioinformatics workflow // Metabolites. 2022. Vol. 12, No. 4. Article number 357. DOI:https://doi.org/10.3390/metabo12040357.; ; EDN: https://elibrary.ru/AVQGJJ
6. Brscic M., Cozzi G., Lora I., Stefani A. L., Contiero B., Ravarotto L. and Gottardo F. Short communication: Reference limits for blood analytes in Holstein late-pregnant heifers and dry cows: Effects of parity, days relative to calving, and season // Journal of Dairy Science. 2015. Vol. 98, No. 11. Pp. 7886–7892. DOI:https://doi.org/10.3168/jds.2015-9345.
7. Kim S., Jung S., Do Y., Jung Y., Choe C., Ha S. et al.. Haemato-chemical and immune variations in Holstein cows at different stages of lactation, parity, and age // Veterinární medicína Czech. 2020. Vol. 65, No. 3. Pp. 95–103. DOI:https://doi.org/10.17221/110/2019-VETMED.
8. Guyot H., Legroux D., Eppe J., Bureau F., Cannon L., Ramery E. Hematologic and serum biochemical characteristics of Belgian blue cattle // Veterinary Sciences. 2024. Vol. 11. No. 5. Article number 222. DOI:https://doi.org/10.3390/vetsci11050222.; ; EDN: https://elibrary.ru/IROFPA
9. Štolcová M., Řehák D., Bartoň L., Rajmon R. Blood biochemical parameters measured during the periparturient period in cows of Holstein and Fleckvieh breeds differing in production purpose // Czech Journal of Animal Science. 2020. Vol. 65, No. 5. Pp. 172–181. DOI:https://doi.org/10.17221/99/2020-CJAS.
10. Buryakov N., Aleshin D., Buryakova M., Zaikina A., Nasr M., Nassan M., Fathala M. Productive performance and blood biochemical parameters of dairy cows fed different levels of high-protein concentrate // Frontiers in Veterinary Science. 2022. Vol. 9. Article number 852240. DOI:https://doi.org/10.3389/fvets.2022.852240.; ; EDN: https://elibrary.ru/WUTBIF
11. Le Boedec K. Reference interval estimation of small sample sizes: A methodologic comparison using a computer-simulation study // Veterinary Clinical Pathology. 2019. Vol. 48, No. 2. Pp. 335–346. DOI:https://doi.org/10.1111/vcp.12725.
12. Friedrichs K. R. ASVCP reference interval guidelines: determination of de novo reference intervals in veterinary species and other related topics // Veterinary Clinical Pathology. 2012. Vol. 41, No. 4. P. 441–453. DOI:https://doi.org/10.1111/vcp.12006.
13. Briscik M. Improvement of variables interpretability in kernel PCA // BMC Bioinformatics. 2023. Vol. 24. Article number 282. DOI:https://doi.org/10.1186/s12859-023-05404-y.; ; EDN: https://elibrary.ru/CJHYXD
14. Smith A. K., Ropella G. E. P., McGill M. R., Krishnan P., Dutta L., Kennedy R. C., Jaeschke H., Hunt C. A. Contrasting model mechanisms of alanine aminotransferase (ALT) release from damaged and necrotic hepatocytes as an example of general biomarker mechanisms // PLOS Computational Biology. 2020. Vol. 16, No. 6. Article number e1007622. DOI:https://doi.org/10.1371/journal.pcbi.1007622.
15. Kanoh N. An integrated screening system for the selection of exemplary substrates for natural and engineered cytochrome P450s // Scientific Reports. 2019. Vol. 9, No. 1. Article number 18023. DOI:https://doi.org/10.1038/s41598-019-54473-8.
16. Puppel K. Comparison of enzyme activity in order to describe the metabolic profile of dairy cows during early lactation // International Journal of Molecular Sciences. 2022. Vol. 23, No. 17. Article number 9771. DOI:https://doi.org/10.3390/ijms23179771.; ; EDN: https://elibrary.ru/AKTMZS
17. Alberghina D. Reference intervals for total protein concentration, serum protein fractions, and albumin/globulin ratios in clinically healthy dairy cows // Journal of Veterinary Diagnostic Investigation. 2011. Vol. 23, No. 1. Pp. 111–114. DOI:https://doi.org/10.1177/104063871102300119.
18. Eckersall P. D. Proteins, proteomics, and the dysproteinemias. Clinical biochemistry of domestic animals. 6th ed. California: Elsevier Academic Press. 2008. Pp. 117–155. DOI:https://doi.org/10.1016/B978-0-12-370491-7.00005-2.
19. Kalyuzhnyy I. I. Scherbakov G. G., Yashin A. V. Klinicheskaya gastroenterologiya zhivotnyh: uchebnoe posobie. Sankt-Peterburg: Lan', 2022. 448 s.
20. Moroz M. T., Zaharov V. V., Samorukov V. I. Sovremennye tehnologii povysheniya produktivnosti sel'skohozyaystvennyh zhivotnyh, uluchsheniya kachestva zhivotnovodcheskoy produkcii. Organizaciya biologicheski polnocennogo kormleniya vysokoproduktivnyh korov: uchebnoe posobie. Sankt-Peterburg: SPbGAU, 2023. 110 s.; EDN: https://elibrary.ru/WMBGBJ
21. Vasil'ev Yu. G., Troshin E. I., Lyubimov A. I. Veterinarnaya klinicheskaya gematologiya. Sankt-Peterburg: Lan', 2022. 656 s.; EDN: https://elibrary.ru/YXSJRE