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Metabolic disorders are genetically correlated with the production and reproductive performance of dairy cows: a meta-analysis

Published online by Cambridge University Press:  24 October 2025

Russell Hassani  and
Navid Ghavi Hossein-Zadeh Open the ORCID record for Navid Ghavi Hossein-Zadeh [Opens in a new window]
Russell Hassani
Affiliation:
Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
Navid Ghavi Hossein-Zadeh*
Affiliation:
Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
*
Corresponding author: Navid Ghavi Hossein-Zadeh; Email: navid.hosseinzadeh@gmail.com, nhosseinzadeh@guilan.ac.ir
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Abstract

The present study aimed to conduct a meta-analysis using the random-effects model to merge published genetic parameter estimates for metabolic disorders [mastitis (MA), metritis (ME), ketosis (KE), milk fever (MF), retained placenta (RP), displaced abomasum (DA), and lameness (LA)] in dairy cows. A total of 239 heritability and 355 genetic correlation estimates were extracted from 61 peer-reviewed articles published between 1991 and 2024. Heritability estimates for metabolic disorders were generally low, ranging from 0.034 for ME to 0.067 for DA and MF. These estimates were associated with small standard errors and narrow 95% confidence intervals, with all estimates being statistically significant (P < 0.05). The estimates for genetic correlations between metabolic disorders were positive, ranging from 0.038 (MA-DA) to 0.522 (KE-DA). Furthermore, only the genetic correlations for DA-LA (0.147), RP-ME (0.472), MA-LA (0.239), MA-MF (0.365), KE-DA (0.522), KE-RP (0.124), and KE-ME (0.157) were significant (P < 0.05). Positive and low genetic correlations were observed between MA-milk yield (MY), MF-MY, and LA-MY (0.291, 0.135, and 0.263, respectively; P < 0.05). Similarly, positive correlations were found between DA-fat yield (FY), MA-FY, MA-protein yield (PY), LA-FY, and LA-PY (0.121, 0.170, 0.303, 0.176, and 0.236, respectively; P < 0.05). The genetic correlations between KE-fat to protein ratio (FPR) and DA-FPR were positive and ranged from low to moderate (0.520 and 0.196, respectively; P < 0.05). Significant genetic correlations were also noted between MA-days open (DO) (0.416), MA-days from calving to first service (DCFS) (0.207), and LA-calving interval (CI) (0.210; P < 0.05). This meta-analysis provides valuable insights into the genetic contribution to metabolic disorders in dairy cows and highlights the generally low heritability and the variable genetic correlations between these disorders and performance traits. These findings may contribute to more effective breeding strategies aimed at reducing the occurrence of metabolic disorders in dairy herds.

Keywords

dairy cowgenetic estimatesmeta-analysismetabolic disordersperformance traits

Information

Type
Research Article
Information
Journal of Dairy Research , First View , pp. 1 - 11
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Hannah Dairy Research Foundation.

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References

Arechiga-Flores, CF, Cortés-Vidauri, Z, Hernández-Briano, P, Lozano-Domínguez, RR, López-Carlos, MA, Macías-Cruz, U and Avendaño-Reyes, L (2022) Hypocalcemia in the dairy cow. Review. Revista Mexicana de Ciencias Pecuarias 13(4), 1025–1054.10.22319/rmcp.v13i4.5277CrossRefGoogle Scholar
Atalay, H (2024) The relationship between ketosis and transitional nutritional diseases. Journal of Istanbul Veterinary Sciences 8(3), 287–293.Google Scholar
Borenstein, M, Hedges, LV, Higgins, J and Rothstein, HR (2009) Random effects model. In Sharples, K (ed.), Introduction to Meta-analysis. Chichester, UK: John Wiley and Sons, pp. 69–75.10.1002/9780470743386.ch12CrossRefGoogle Scholar
Brito, LF, Bedere, N, Douhard, F, Oliveira, HR, Arnal, M, Peñagaricano, F, Schinckel, AP, Baes, CF and Miglior, F (2021) Review: genetic selection of high-yielding dairy cattle toward sustainable farming systems in a rapidly changing world. Animal 15, Article 100292.10.1016/j.animal.2021.100292CrossRefGoogle Scholar
Chegini, A, Ghavi Hossein-Zadeh, N, Hosseini-Moghadam, SH and Shadparvar, AA (2019) Genetic correlation estimates between milk production traits, mastitis and different measures of somatic cells in Holstein cows. Animal Production Science 59, 1031–1038.10.1071/AN17325CrossRefGoogle Scholar
Chen, K, Hu, BB, Deng, X, Li, Q, Zhang, R, Zhang, Y, Shen, G, Liu, S, Zhang, J and Lu, P (2024) Enhanced protein-metabolite correlation analysis: to investigate the association between Staphylococcus aureus mastitis and metabolic immune pathways. The FASEB Journal 38(7), e23587.10.1096/fj.202302242RRCrossRefGoogle ScholarPubMed
de Jong, E, van der Velden, I, Smid, AC, Ida, JA, Reyher, KK, Kelton, DF and Barkema, HW (2024) Dairy farmers’ considerations for antimicrobial treatment of clinical mastitis in British Columbia and Alberta, Canada. Frontiers in Veterinary Science 11, 1417958.10.3389/fvets.2024.1417958CrossRefGoogle ScholarPubMed
Duffield, T (2000) Subclinical ketosis in lactating dairy cattle. Veterinary Clinics of North America: Food Animal Practice 16(2), 231–253.Google ScholarPubMed
Firrincieli, A, Minuti, A, Cappelletti, M, Ferilli, M, Ajmone‐Marsan, P, Bani, P, Petruccioli, M and Harfouche, A (2024) Structural and functional analysis of the active cow rumen's microbial community provides a catalogue of genes and microbes participating in the deconstruction of cardoon biomass. Biotechnology for Biofuels and Bioproducts 17(1), 53.10.1186/s13068-024-02495-4CrossRefGoogle ScholarPubMed
Fredebeul-Krein, F, Schmenger, A, Wente, N, Zhang, Y and Krömker, V (2022) Factors associated with the severity of clinical mastitis. Pathogens 11(10), 1089.10.3390/pathogens11101089CrossRefGoogle ScholarPubMed
Garvey, M (2022) Lameness in dairy cow herds: disease aetiology, prevention and management. Dairy 3(1), 199–210.10.3390/dairy3010016CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N (2013) Effects of main reproductive and health problems on the performance of dairy cows: a review. Spanish Journal of Agricultural Research 11(3), 718–735.10.5424/sjar/2013113-4140CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N (2022) A meta-analysis of the genetic contribution estimates to major indicators for ketosis in dairy cows. Research in Veterinary Science 153, 8–16.10.1016/j.rvsc.2022.10.008CrossRefGoogle ScholarPubMed
Ghavi Hossein-Zadeh, N and Ardalan, M (2011a) Bayesian estimates of genetic parameters for cystic ovarian disease, displaced abomasum and foot and leg diseases in Iranian Holsteins via Gibbs sampling. Journal of Agricultural Science 149(1), 119–124.10.1017/S0021859610000754CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N and Ardalan, M (2011b) Bayesian estimates of genetic parameters for metritis, retained placenta, milk fever, and clinical mastitis in Holstein dairy cows via Gibbs sampling. Research in Veterinary Science 90(1), 146–149.10.1016/j.rvsc.2010.04.018CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N and Ardalan, M (2011c) Cow-specific risk factors for retained placenta, metritis and clinical mastitis in Holstein cows. Veterinary Research Communications 35, 345–354.10.1007/s11259-011-9479-5CrossRefGoogle Scholar
Hu, HH, Mu, T, Zhang, ZB, Zhang, JX, Feng, X, Han, LY, Hao, F, Ma, YF, Jiang, Y and Ma, Y (2024) Genetic analysis of health traits and their associations with longevity, fertility, production, and conformation traits in Holstein cattle. Animal 18, 101177.10.1016/j.animal.2024.101177CrossRefGoogle ScholarPubMed
Hu, X, Li, S, Mu, R, Guo, J, Zhao, C, Cao, Y, Zhang, N and Fu, Y (2022) The rumen microbiota contributes to the development of mastitis in dairy cows. Microbiology Spectrum 10(1), e0251221.10.1128/spectrum.02512-21CrossRefGoogle Scholar
Huedo-Medina, TB, S´anchez-meca, J, Marín-Martínez, F and Botella, J (2006) Assessing heterogeneity in meta-analysis: q statistic or I2 index?. Psychological Methods 11, 193–206.10.1037/1082-989X.11.2.193CrossRefGoogle ScholarPubMed
Ingvartsen, KL (2006) Feeding- and management-related diseases in the transition cow: physiological adaptations around calving and strategies to reduce feeding-related diseases. Animal Feed Science and Technology 126, 175–213. https://doi.org/10.1016/j.anifeedsci.2005.08.003CrossRefGoogle Scholar
Janevski, A, Nikolovski, M, Cvetkovikj, I, Andreevska, S, Todorovski, A and Mitrov, D (2023) Clinical mastits incidence in small-scale dairy cow farms. Macedonian Veterinary Review 46(1), 35–41.10.2478/macvetrev-2023-0010CrossRefGoogle Scholar
Jukna, V, Meškinytė, E, Urbonavičius, G, Bilskis, R, Antanaitis, R, Kajokienė, L and Juozaitienė, V (2024) Association of lameness prevalence and severity in early-lactation cows with milk traits, metabolic profile, and dry period. Agriculture 14(11), 2030.10.3390/agriculture14112030CrossRefGoogle Scholar
Kapusniaková, M, Juráček, M, Hanušovský, O, Duchoň, A, Rolinec, M, Gálik, B, Džima, M, Rajčok, D and Šimko, M (2024) Alimentary metabolic disorders in high-producing dairy cows: a review. Acta Fytotechn Zootechn 26(4), 354–359.10.15414/afz.2023.26.04.354-359CrossRefGoogle Scholar
Kašná, E, Zavadilová, L, Krupová, Z, Šlosárková, S and Fleischer, P (2023) The most common reproductive disorders of cows in Holstein cattle breeding. Czech Journal of Animal Science 68(11), 433–442.10.17221/86/2023-CJASCrossRefGoogle Scholar
Khan, MZ, Huang, B, Kou, X, Chen, Y, Liang, H, Ullah, Q, Khan, IM, Khan, A, Chai, W and Wang, C (2024) Enhancing bovine immune, antioxidant and anti-inflammatory responses with vitamins, rumen-protected amino acids, and trace minerals to prevent periparturient mastitis. Frontiers in Immunology 14, 1290044.10.3389/fimmu.2023.1290044CrossRefGoogle ScholarPubMed
Klein, SL, Scheper, C, May, K and König, S (2020) Genetic and nongenetic profiling of milk β-hydroxybutyrate and acetone and their associations with ketosis in Holstein cows. Journal of Dairy Science 103(11), 10332–10346.10.3168/jds.2020-18339CrossRefGoogle ScholarPubMed
Köck, A, Fuerst-Waltl, B, Steininger, F and Egger-Danner, C (2016) Genetic parameters for body weight, body condition score and lameness in Austrian dairy cows. Interbull Bulletin 50, 51–53.Google Scholar
Koeck, A, Jamrozik, J, Kistemaker, GJ, Schenkel, FS, Moore, RK, Lefebvre, DM, Kelton, DF and Miglior, F (2016) Genetic and phenotypic associations of milk β-hydroxybutyrate with ketosis in Canadian Holsteins. Canadian Journal of Animal Science 96, 302–305.10.1139/cjas-2015-0206CrossRefGoogle Scholar
Koeck, A, Miglior, F, Jamrozik, J, Kelton, DF and Schenkel, FS (2013) Genetic associations of ketosis and displaced abomasum with milk production traits in early first lactation of Canadian Holsteins. Journal of Dairy Science 96(7), 4688–4696.10.3168/jds.2012-6408CrossRefGoogle ScholarPubMed
Lean, I, Rabiee, A, Duffield, T and Dohoo, I (2009) Invited review: use of meta-analysis in animal health and reproduction: methods and applications. Journal of Dairy Science 92, 3545–3565.10.3168/jds.2009-2140CrossRefGoogle ScholarPubMed
Lean, IJ and Golder, HM (2024) Milk as an indicator of dietary imbalance. Australian Veterinary Journal 102(1–2), 19–25.10.1111/avj.13294CrossRefGoogle Scholar
LeBlanc, SJ (2008) Postpartum uterine disease and dairy herd reproductive performance: a review. Veterinary Journal 176, 102–114.10.1016/j.tvjl.2007.12.019CrossRefGoogle ScholarPubMed
Lei, MAC and Simões, J (2021) Invited review: ketosis diagnosis and monitoring in high-producing dairy cows. Dairy 2(2), 303–325.10.3390/dairy2020025CrossRefGoogle Scholar
Llonch, P, Mainau, E, Ipharraguerre, IR, Bargo, F, Tedó, G, Blanch, M and Manteca, X (2018) Chicken or the egg: the reciprocal association between feeding behavior and animal welfare and their impact on productivity in dairy cows. Frontiers in Veterinary Science 5, 305.10.3389/fvets.2018.00305CrossRefGoogle ScholarPubMed
Ma, N, Guo, J, Li, Z, Xu, L, Zhang, K, Chang, G, Loor, JJ and Shen, X (2024) Disturbances of ruminal microbiota and liver inflammation, mediated by LPS and histamine, in dairy cows fed a high-concentrate diet. Animals 14(10), 1495.10.3390/ani14101495CrossRefGoogle ScholarPubMed
Mekuriaw, Y (2023) Negative energy balance and its implication on productive and reproductive performance of early lactating dairy cows: review paper. Journal of Applied Animal Research 51(1), 220–228.10.1080/09712119.2023.2176859CrossRefGoogle Scholar
Melendez, P and Serrano, MV (2024) Update on ketosis in dairy cattle with major emphasis on subclinical ketosis and abdominal adiposity. Veterinary Medicine and Science 10(5), e1525.10.1002/vms3.1525CrossRefGoogle ScholarPubMed
Miglior, F, Fleming, A, Malchiodi, F, Brito, LF, Martin, P and Baes, CF (2017) A 100-Year Review: identification and genetic selection of economically important traits in dairy cattle. Journal of Dairy Science 100(12), 10251–10271.10.3168/jds.2017-12968CrossRefGoogle ScholarPubMed
Mota, LFM, Giannuzzi, D, Pegolo, S, Trevisi, E, Ajmone-Marsan, P and Cecchinato, A (2023) Integrating on-farm and genomic information improves the predictive ability of milk infrared prediction of blood indicators of metabolic disorders in dairy cows. Genetics Selection Evolution 55(1), 23.10.1186/s12711-023-00795-1CrossRefGoogle ScholarPubMed
Ohtsuka, H, Fukuda, S, Kudo, K, Tomioka, M, Koiwa, M and Kimura, K (2013) Changes in leukocyte populations of cows with milk fever or displaced abomasum after calving. Canadian Journal of Veterinary Research 77(3), 226–230.Google ScholarPubMed
Oliveira Junior, GA, Schenkel, FS, Alcantara, L, Houlahan, K, Lynch, C and Baes, CF (2021) Estimated genetic parameters for all genetically evaluated traits in Canadian Holsteins. Journal of Dairy Science 104(8), 9002–9015.10.3168/jds.2021-20227CrossRefGoogle ScholarPubMed
Ospina, PA, Nydam, DV, Stokol, T and Overton, TR (2010) Associations of elevated nonesterified fatty acids and beta-hydroxybutyrate concentrations with early lactation reproductive performance and milk production in transition dairy cattle in the northeastern United States. Journal of Dairy Science 93(4), 1596–1603.10.3168/jds.2009-2852CrossRefGoogle ScholarPubMed
Pegolo, S, Momen, M, Morota, G, Rosa, GJM, Gianola, D, Bittante, G and Cecchinato, A (2020) Structural equation modeling for investigating multi-trait genetic architecture of udder health in dairy cattle. Scientific Reports 10(1), 7751.10.1038/s41598-020-64575-3CrossRefGoogle ScholarPubMed
Pryce, JE, Parker Gaddis, KL, Koeck, A, Bastin, C, Abdelsayed, M, Gengler, N, Miglior, F, Heringstad, B, Egger-Danner, C, Stock, KF, Bradley, AJ and Cole, JB (2016) Invited review: opportunities for genetic improvement of metabolic diseases. Journal of Dairy Science 99(9), 6855–6873.10.3168/jds.2016-10854CrossRefGoogle ScholarPubMed
Rasmussen, P, Barkema, HW, Osei, PP, Taylor, J, Shaw, AP, Conrady, B, Chaters, G, Muñoz, V, Hall, DC, Apenteng, OO, Rushton, J and Torgerson, PR (2024) Global losses due to dairy cattle diseases: a comorbidity-adjusted economic analysis. Journal of Dairy Science 107(9), 6945–6970.10.3168/jds.2023-24626CrossRefGoogle ScholarPubMed
Ren, X, Lu, H, Wang, Y, Yan, L, Liu, C, Chu, C, Yang, Z, Bao, X, Yu, M, Zhang, Z and Zhang, S (2024) Phenotypic and genetic analyses of mastitis, endometritis, and ketosis on milk production and reproduction traits in Chinese Holstein cattle. Animals 14, 2372.10.3390/ani14162372CrossRefGoogle ScholarPubMed
Roche, JR (2006) The effect of nutritional management of the transition cow on reproductive performance. Animal Reproduction Science 96(3–4), 282–296.10.1016/j.anireprosci.2006.08.007CrossRefGoogle Scholar
Sadiq, MB, Ramanoon, SZ, Mansor, R, Mossadeq, WMS, Syed-Hussain, SS, Yimer, N, Kaka, U, Ajat, M and Abdullah, FFJ (2024) Potential biomarkers for lameness and claw lesions in dairy cows: a scoping review. Journal of Dairy Research 91(2), 202–210.10.1017/S0022029924000487CrossRefGoogle Scholar
Schmidtmann, C, Segelke, D, Bennewitz, J, Tetens, J and Thaller, G (2023) Genetic analysis of production traits and body size measurements and their relationships with metabolic diseases in German Holstein cattle. Journal of Dairy Science 106(1), 421–438.10.3168/jds.2022-22363CrossRefGoogle ScholarPubMed
Thorup, VM, Nielsen, BL, Robert, PE, Giger-Reverdin, S, Konka, J, Michie, C and Friggens, NC (2016) Lameness affects cow feeding but not rumination behavior as characterized from sensor data. Frontiers in Veterinary Science 3, 37.10.3389/fvets.2016.00037CrossRefGoogle Scholar
Tufarelli, V, Puvača, N, Glamočić, D, Pugliese, G and Colonna, MA (2024) The most important metabolic diseases in dairy cattle during the transition period. Animals 14(5), 816.10.3390/ani14050816CrossRefGoogle ScholarPubMed
Urban‐Chmiel, R, Mudroň, P, Abramowicz, B, Kurek, Ł and Stachura, R (2024) Lameness in cattle—etiopathogenesis, prevention and treatment. Animals 14(12), 1836.10.3390/ani14121836CrossRefGoogle ScholarPubMed
van der Drift, SG, van Hulzen, KJ, Teweldemedhn, TG, Jorritsma, R, Nielen, M and Heuven, HC (2012) Genetic and nongenetic variation in plasma and milk β-hydroxybutyrate and milk acetone concentrations of early-lactation dairy cows. Journal of Dairy Science 95(11), 6781–6787.10.3168/jds.2012-5640CrossRefGoogle ScholarPubMed
van Soest, FJS, Mourits, MCM, Blanco-Penedo, I, Duval, J, Fall, N, Krieger, M, Sjöstrom, K and Hogeveen, H (2019) Farm-specific failure costs of production disorders in European organic dairy herds. Preventive Veterinary Medicine 168, 19–29.10.1016/j.prevetmed.2019.03.029CrossRefGoogle ScholarPubMed
Wang, Z, Ma, Z, Tian, Z, Jia, H, Zhang, S, Mao, Y, Yang, Z, Zhu, L and Li, M (2024) Microbial dysbiosis in the gut–mammary axis as a mechanism for mastitis in dairy cows. International Journal of Dairy Technology. https://doi.org/10.1111/1471-0307.13150Google Scholar
Zhang, J, Han, L, Zhang, H, Hu, H, Sheng, H, Yang, T, Zhang, Y, Wen, W, Ma, L, Ma, Y and Wang, Y (2024) Genetic parameters for health traits and their association with fertility and milk production in Chinese Holsteins. Journal of Animal Breeding and Genetics 141(1), 52–64.10.1111/jbg.12825CrossRefGoogle ScholarPubMed
Zhao, C, Hu, X, Qiu, M, Bao, L, Wu, K, Meng, X, Zhao, Y, Feng, L, Duan, S, He, Y, Zhang, N and Fu, Y (2023) Sialic acid exacerbates gut dysbiosis-associated mastitis through the microbiota-gut-mammary axis by fueling gut microbiota disruption. Microbiome 11(1), 78.10.1186/s40168-023-01528-8CrossRefGoogle ScholarPubMed
Zhao, Y, Nan, X, Wang, H, Liu, J, Yang, L, Yao, J and Xiong, B (2024) Nutrition, gastrointestinal microorganisms and metabolites in mastitis occurrence and control. Animal Nutrition 17, 220–231.Google Scholar
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