Estimation of the proviral load in Japanese Black cattle infected with bovine leukemia virus by statistical modeling
Enzootic bovine leukosis (EBL) is B-cell lymphoma in cattle caused by bovine leukemia virus (BLV) infection. The incidence of EBL has been increasing since 1998 in Japan, resulting in significant economic losses for farms. The BLV genome integrates with the host genome as provirus, leading to sustai...
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| Published in | Journal of Veterinary Medical Science Vol. 86; no. 2; pp. 135 - 140 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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Japan
JAPANESE SOCIETY OF VETERINARY SCIENCE
2024
Japan Science and Technology Agency The Japanese Society of Veterinary Science |
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| Abstract | Enzootic bovine leukosis (EBL) is B-cell lymphoma in cattle caused by bovine leukemia virus (BLV) infection. The incidence of EBL has been increasing since 1998 in Japan, resulting in significant economic losses for farms. The BLV genome integrates with the host genome as provirus, leading to sustainably infection. Although most of the BLV-infected cattle are aleukemic, some cattle cause persistent lymphocytosis (PL) and subsequently develop EBL. Recent reports suggest the association between the risk for the transmission of BLV and the developing EBL and the proviral load (PVL) in BLV-infected cattle, which cannot measure readily in the field. This study aims to build a statistical model for predicting PVL of BLV-infected asymptomatic or PL cattle based on data accessible in the field. Five negative binomial regression models with different linear predictors were built and compared for the predictability of PVL. Consequently, the model with two explanatory variables (age in months and logarithm of lymphocyte count) was selected as the best model. The model can be used in the field as a cost-beneficial supporting tool to estimate the risk of transmission of BLV and developing EBL in infected cattle. |
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| AbstractList | Enzootic bovine leukosis (EBL) is B-cell lymphoma in cattle caused by bovine leukemia
virus (BLV) infection. The incidence of EBL has been increasing since 1998 in Japan,
resulting in significant economic losses for farms. The BLV genome integrates with the
host genome as provirus, leading to sustainably infection. Although most of the
BLV-infected cattle are aleukemic, some cattle cause persistent lymphocytosis (PL) and
subsequently develop EBL. Recent reports suggest the association between the risk for the
transmission of BLV and the developing EBL and the proviral load (PVL) in BLV-infected
cattle, which cannot measure readily in the field. This study aims to build a statistical
model for predicting PVL of BLV-infected asymptomatic or PL cattle based on data
accessible in the field. Five negative binomial regression models with different linear
predictors were built and compared for the predictability of PVL. Consequently, the model
with two explanatory variables (age in months and logarithm of lymphocyte count) was
selected as the best model. The model can be used in the field as a cost-beneficial
supporting tool to estimate the risk of transmission of BLV and developing EBL in infected
cattle. Enzootic bovine leukosis (EBL) is B-cell lymphoma in cattle caused by bovine leukemia virus (BLV) infection. The incidence of EBL has been increasing since 1998 in Japan, resulting in significant economic losses for farms. The BLV genome integrates with the host genome as provirus, leading to sustainably infection. Although most of the BLV-infected cattle are aleukemic, some cattle cause persistent lymphocytosis (PL) and subsequently develop EBL. Recent reports suggest the association between the risk for the transmission of BLV and the developing EBL and the proviral load (PVL) in BLV-infected cattle, which cannot measure readily in the field. This study aims to build a statistical model for predicting PVL of BLV-infected asymptomatic or PL cattle based on data accessible in the field. Five negative binomial regression models with different linear predictors were built and compared for the predictability of PVL. Consequently, the model with two explanatory variables (age in months and logarithm of lymphocyte count) was selected as the best model. The model can be used in the field as a cost-beneficial supporting tool to estimate the risk of transmission of BLV and developing EBL in infected cattle.Enzootic bovine leukosis (EBL) is B-cell lymphoma in cattle caused by bovine leukemia virus (BLV) infection. The incidence of EBL has been increasing since 1998 in Japan, resulting in significant economic losses for farms. The BLV genome integrates with the host genome as provirus, leading to sustainably infection. Although most of the BLV-infected cattle are aleukemic, some cattle cause persistent lymphocytosis (PL) and subsequently develop EBL. Recent reports suggest the association between the risk for the transmission of BLV and the developing EBL and the proviral load (PVL) in BLV-infected cattle, which cannot measure readily in the field. This study aims to build a statistical model for predicting PVL of BLV-infected asymptomatic or PL cattle based on data accessible in the field. Five negative binomial regression models with different linear predictors were built and compared for the predictability of PVL. Consequently, the model with two explanatory variables (age in months and logarithm of lymphocyte count) was selected as the best model. The model can be used in the field as a cost-beneficial supporting tool to estimate the risk of transmission of BLV and developing EBL in infected cattle. Enzootic bovine leukosis (EBL) is B-cell lymphoma in cattle caused by bovine leukemia virus (BLV) infection. The incidence of EBL has been increasing since 1998 in Japan, resulting in significant economic losses for farms. The BLV genome integrates with the host genome as provirus, leading to sustainably infection. Although most of the BLV-infected cattle are aleukemic, some cattle cause persistent lymphocytosis (PL) and subsequently develop EBL. Recent reports suggest the association between the risk for the transmission of BLV and the developing EBL and the proviral load (PVL) in BLV-infected cattle, which cannot measure readily in the field. This study aims to build a statistical model for predicting PVL of BLV-infected asymptomatic or PL cattle based on data accessible in the field. Five negative binomial regression models with different linear predictors were built and compared for the predictability of PVL. Consequently, the model with two explanatory variables (age in months and logarithm of lymphocyte count) was selected as the best model. The model can be used in the field as a cost-beneficial supporting tool to estimate the risk of transmission of BLV and developing EBL in infected cattle. |
| ArticleNumber | 23-0157 |
| Author | KOREEDA, Terunori SHIBATA, Shoichi IWAMOTO, Jiro IINO, Mei EITOKU, Rikako |
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| Cites_doi | 10.1006/viro.1997.8784 10.1128/spectrum.02595-22 10.9734/ajpas/2019/v5i230132 10.1292/jvms.12-0374 10.3168/jds.2015-10089 10.1292/jvms.17-0391 10.1186/1742-4690-7-91 10.1016/j.prevetmed.2019.04.009 10.1186/1746-6148-8-167 10.1016/S0167-5877(03)00057-6 10.1016/j.prevetmed.2021.105528 10.1007/s00705-014-2137-9 10.1016/0167-5877(87)90023-7 10.1186/s12917-019-2158-4 10.1292/jvms.16-0022 10.3390/pathogens10101281 10.1016/j.prevetmed.2007.05.010 10.3168/jds.2018-14609 10.3390/v13112167 10.1186/s13567-019-0732-1 10.2460/ajvr.74.5.744 10.1292/jvms.20-0332 10.1016/j.virusres.2015.08.013 10.1292/jvms.16-0601 |
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| Copyright | 2024 by the Japanese Society of Veterinary Science 2024. This work is published under https://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2024 The Japanese Society of Veterinary Science 2024 |
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| Keywords | statistical modeling enzootic bovine leukosis bovine leukemia virus persistent lymphocytosis proviral load |
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| References | 23. Senaviratna NAMR, Cooray TMJA. 2019. Diagnosing multicollinearity of logistic regression model. Asian J Probab Stat 5: 1–9. 13. Marawan MA, Alouffi A, El Tokhy S, Badawy S, Shirani I, Dawood A, Guo A, Almutairi MM, Alshammari FA, Selim A. 2021. Bovine leukaemia virus: current epidemiological circumstance and future prospective. Viruses 13: 2167. 11. Kobayashi T, Inagaki Y, Ohnuki N, Sato R, Murakami S, Imakawa K. 2019. Increasing Bovine leukemia virus (BLV) proviral load is a risk factor for progression of Enzootic bovine leucosis: A prospective study in Japan. Prev Vet Med 178: 104680. 21. Okagawa T, Shimakura H, Konnai S, Saito M, Matsudaira T, Nao N, Yamada S, Murakami K, Maekawa N, Murata S, Ohashi K. 2022. Diagnosis and early prediction of lymphoma using high-throughput clonality analysis of bovine leukemia virus-infected cells. Microbiol Spectr 10: e0259522. 10. Johnson R, Kaneene JB, Anderson SM. 1987. Bovine leukemia virus: duration of BLV colostral antibodies in calves from commercial dairy herds. Prev Vet Med 4: 371–376. 24. Somura Y, Sugiyama E, Fujikawa H, Murakami K. 2014. Comparison of the copy numbers of bovine leukemia virus in the lymph nodes of cattle with enzootic bovine leukosis and cattle with latent infection. Arch Virol 159: 2693–2697. 25. Yuan Y, Kitamura-Muramatsu Y, Saito S, Ishizaki H, Nakano M, Haga S, Matoba K, Ohno A, Murakami H, Takeshima SN, Aida Y. 2015. Detection of the BLV provirus from nasal secretion and saliva samples using BLV-CoCoMo-qPCR-2: Comparison with blood samples from the same cattle. Virus Res 210: 248–254. 3. Bai L, Borjigin L, Sato H, Takeshima SN, Asaji S, Ishizaki H, Kawashima K, Obuchi Y, Sunaga S, Ando A, Inoko H, Wada S, Aida Y. 2021. Kinetic study of BLV infectivity in BLV susceptible and resistant cattle in Japan from 2017 to 2019. Pathogens 10: 1281. 9. Jimba M, Takeshima SN, Murakami H, Kohara J, Kobayashi N, Matsuhashi T, Ohmori T, Nunoya T, Aida Y. 2012. BLV-CoCoMo-qPCR: a useful tool for evaluating bovine leukemia virus infection status. BMC Vet Res 8: 167. 14. Mekata H, Yamamoto M, Hayashi T, Kirino Y, Sekiguchi S, Konnai S, Horii Y, Norimine J. 2018. Cattle with a low bovine leukemia virus proviral load are rarely an infectious source. Jpn J Vet Res 66: 157–163. 17. Nakada S, Kohara J, Makita K. 2018. Estimation of circulating bovine leukemia virus levels using conventional blood cell counts. J Dairy Sci 101: 11229–11236. 8. Jimba M, Takeshima SN, Matoba K, Endoh D, Aida Y. 2010. BLV-CoCoMo-qPCR: Quantitation of bovine leukemia virus proviral load using the CoCoMo algorithm. Retrovirology 7: 91. 18. Nishiike M, Haoka M, Doi T, Kohda T, Mukamoto M. 2016. Development of a preliminary diagnostic measure for bovine leukosis in dairy cows using peripheral white blood cell and lymphocyte counts. J Vet Med Sci 78: 1145–1151. 12. Konishi M, Kobayashi S, Tokunaga T, Chiba Y, Tsutsui T, Arai S, Kameyama KI, Yamamoto T. 2019. Simultaneous evaluation of diagnostic marker utility for enzootic bovine leukosis. BMC Vet Res 15: 406. 22. Sajiki Y, Konnai S, Nishimori A, Okagawa T, Maekawa N, Goto S, Nagano M, Kohara J, Kitano N, Takahashi T, Tajima M, Mekata H, Horii Y, Murata S, Ohashi K. 2017. Intrauterine infection with bovine leukemia virus in pregnant dam with high viral load. J Vet Med Sci 79: 2036–2039. 4. Fechner H, Blankenstein P, Looman AC, Elwert J, Geue L, Albrecht C, Kurg A, Beier D, Marquardt O, Ebner D. 1997. Provirus variants of the bovine leukemia virus and their relation to the serological status of naturally infected cattle. Virology 237: 261–269. 7. Iwamoto J, Furukawa M. 2020. The estimation of duration of maternally-derived antibodies against Akabane, Aino, and Chuzan virus in calves by the receiver operating characteristic analysis. J Vet Med Sci 82: 1614–1618. 1. Acaite J, Tamosiunas V, Lukauskas K, Milius J, Pieskus J. 2007. The eradication experience of enzootic bovine leukosis from Lithuania. Prev Vet Med 82: 83–89. 15. Murakami K, Kobayashi S, Konishi M, Kameyama K, Tsutsui T. 2013. Nationwide survey of bovine leukemia virus infection among dairy and beef breeding cattle in Japan from 2009-2011. J Vet Med Sci 75: 1123–1126. 19. Norby B, Bartlett PC, Byrem TM, Erskine RJ. 2016. Effect of infection with bovine leukemia virus on milk production in Michigan dairy cows. J Dairy Sci 99: 2043–2052. 20. Nuotio L, Rusanen H, Sihvonen L, Neuvonen E. 2003. Eradication of enzootic bovine leukosis from Finland. Prev Vet Med 59: 43–49. 16. Nakada S, Fujimoto Y, Kohara J, Adachi Y, Makita K. 2022. Estimation of economic loss by carcass weight reduction of Japanese dairy cows due to infection with bovine leukemia virus. Prev Vet Med 198: 105528–105528. 2. Alvarez I, Gutiérrez G, Gammella M, Martínez C, Politzki R, González C, Caviglia L, Carignano H, Fondevila N, Poli M, Trono K. 2013. Evaluation of total white blood cell count as a marker for proviral load of bovine leukemia virus in dairy cattle from herds with a high seroprevalence of antibodies against bovine leukemia virus. Am J Vet Res 74: 744–749. 6. Hayashi T, Mekata H, Sekiguchi S, Kirino Y, Mitoma S, Honkawa K, Horii Y, Norimine J. 2017. Cattle with the BoLA class II DRB3*0902 allele have significantly lower bovine leukemia proviral loads. J Vet Med Sci 79: 1552–1555. 5. Forletti A, Lützelschwab CM, Cepeda R, Esteban EN, Gutiérrez SE. 2020. Early events following bovine leukaemia virus infection in calves with different alleles of the major histocompatibility complex DRB3 gene. Vet Res (Faisalabad) 51: 4. 22 23 24 25 10 11 12 13 14 15 16 17 18 19 1 2 3 4 5 6 7 8 9 20 21 |
| References_xml | – reference: 21. Okagawa T, Shimakura H, Konnai S, Saito M, Matsudaira T, Nao N, Yamada S, Murakami K, Maekawa N, Murata S, Ohashi K. 2022. Diagnosis and early prediction of lymphoma using high-throughput clonality analysis of bovine leukemia virus-infected cells. Microbiol Spectr 10: e0259522. – reference: 3. Bai L, Borjigin L, Sato H, Takeshima SN, Asaji S, Ishizaki H, Kawashima K, Obuchi Y, Sunaga S, Ando A, Inoko H, Wada S, Aida Y. 2021. Kinetic study of BLV infectivity in BLV susceptible and resistant cattle in Japan from 2017 to 2019. Pathogens 10: 1281. – reference: 20. Nuotio L, Rusanen H, Sihvonen L, Neuvonen E. 2003. Eradication of enzootic bovine leukosis from Finland. Prev Vet Med 59: 43–49. – reference: 7. Iwamoto J, Furukawa M. 2020. The estimation of duration of maternally-derived antibodies against Akabane, Aino, and Chuzan virus in calves by the receiver operating characteristic analysis. J Vet Med Sci 82: 1614–1618. – reference: 1. Acaite J, Tamosiunas V, Lukauskas K, Milius J, Pieskus J. 2007. The eradication experience of enzootic bovine leukosis from Lithuania. Prev Vet Med 82: 83–89. – reference: 2. Alvarez I, Gutiérrez G, Gammella M, Martínez C, Politzki R, González C, Caviglia L, Carignano H, Fondevila N, Poli M, Trono K. 2013. Evaluation of total white blood cell count as a marker for proviral load of bovine leukemia virus in dairy cattle from herds with a high seroprevalence of antibodies against bovine leukemia virus. Am J Vet Res 74: 744–749. – reference: 18. Nishiike M, Haoka M, Doi T, Kohda T, Mukamoto M. 2016. Development of a preliminary diagnostic measure for bovine leukosis in dairy cows using peripheral white blood cell and lymphocyte counts. J Vet Med Sci 78: 1145–1151. – reference: 6. Hayashi T, Mekata H, Sekiguchi S, Kirino Y, Mitoma S, Honkawa K, Horii Y, Norimine J. 2017. Cattle with the BoLA class II DRB3*0902 allele have significantly lower bovine leukemia proviral loads. J Vet Med Sci 79: 1552–1555. – reference: 22. Sajiki Y, Konnai S, Nishimori A, Okagawa T, Maekawa N, Goto S, Nagano M, Kohara J, Kitano N, Takahashi T, Tajima M, Mekata H, Horii Y, Murata S, Ohashi K. 2017. Intrauterine infection with bovine leukemia virus in pregnant dam with high viral load. J Vet Med Sci 79: 2036–2039. – reference: 19. Norby B, Bartlett PC, Byrem TM, Erskine RJ. 2016. Effect of infection with bovine leukemia virus on milk production in Michigan dairy cows. J Dairy Sci 99: 2043–2052. – reference: 5. Forletti A, Lützelschwab CM, Cepeda R, Esteban EN, Gutiérrez SE. 2020. Early events following bovine leukaemia virus infection in calves with different alleles of the major histocompatibility complex DRB3 gene. Vet Res (Faisalabad) 51: 4. – reference: 16. Nakada S, Fujimoto Y, Kohara J, Adachi Y, Makita K. 2022. Estimation of economic loss by carcass weight reduction of Japanese dairy cows due to infection with bovine leukemia virus. Prev Vet Med 198: 105528–105528. – reference: 12. Konishi M, Kobayashi S, Tokunaga T, Chiba Y, Tsutsui T, Arai S, Kameyama KI, Yamamoto T. 2019. Simultaneous evaluation of diagnostic marker utility for enzootic bovine leukosis. BMC Vet Res 15: 406. – reference: 11. Kobayashi T, Inagaki Y, Ohnuki N, Sato R, Murakami S, Imakawa K. 2019. Increasing Bovine leukemia virus (BLV) proviral load is a risk factor for progression of Enzootic bovine leucosis: A prospective study in Japan. Prev Vet Med 178: 104680. – reference: 13. Marawan MA, Alouffi A, El Tokhy S, Badawy S, Shirani I, Dawood A, Guo A, Almutairi MM, Alshammari FA, Selim A. 2021. Bovine leukaemia virus: current epidemiological circumstance and future prospective. Viruses 13: 2167. – reference: 14. Mekata H, Yamamoto M, Hayashi T, Kirino Y, Sekiguchi S, Konnai S, Horii Y, Norimine J. 2018. Cattle with a low bovine leukemia virus proviral load are rarely an infectious source. Jpn J Vet Res 66: 157–163. – reference: 4. 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| Snippet | Enzootic bovine leukosis (EBL) is B-cell lymphoma in cattle caused by bovine leukemia virus (BLV) infection. The incidence of EBL has been increasing since... Enzootic bovine leukosis (EBL) is B-cell lymphoma in cattle caused by bovine leukemia virus (BLV) infection. The incidence of EBL has been increasing since... |
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| SubjectTerms | B-cell lymphoma bovine leukemia virus Bovine leukosis Cattle Cell number enzootic bovine leukosis Epidemiology Genomes Leukemia Leukosis Lymphocytes Lymphocytes B Lymphocytosis Mathematical models persistent lymphocytosis proviral load Regression analysis statistical modeling |
| Title | Estimation of the proviral load in Japanese Black cattle infected with bovine leukemia virus by statistical modeling |
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