BOVINE LEUKEMIA VIRUS: THE SILENT THIEF

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BOVINE LEUKEMIA VIRUS: THE SILENT THIEF Vickie Ruggerio, LVT, MPH Paul Bartlett, MPH, DVM, PhD Ron Erskine, DVM, PhD* Dept of Large Animal Clinical Sciences College of Veterinary Medicine Michigan State University East Lansing, Michigan 48824 Epidemiology and Pathogenesis Enzootic bovine leukosis is a contagious disease of cattle induced by an exogenous retrovirus, bovine leukemia virus (BLV). The disease complex is characterized by a persistent lymphocytosis which can culminate in B cell lymphoma (Schwartz and Levy, 1994). The National Animal Health Monitoring System (NAHMS) 1996 study indicated that BLV is widely distributed in US dairy operations with herd prevalence of 89% and an average within-herd prevalence of 45% (NAHMS, 1997). In Michigan, a 2010 study also found an average herd prevalence of 35% of cows in herd Erskine et al., 2012a). These estimates may be low compared to the current status of the US dairy industry because, 1) rapid expansion of dairy herds has occurred, with increased inter-herd sale of animals (and spread of disease), 2) changes in management practices in many dairies that result in higher risk of exposure, such as increased injections, palpations, movement of animals among pens, and increased confinement, and 3) lack of monitoring and BLV control programs on most dairies. Most BLV-infected cows never show outward signs of disease, and these animals are referred to as asymptomatic or aleukemic. Approximately 30-50% of BLV-infected cattle will eventually develop a persistent lymphocytosis while fewer than 5% of infected cows will ever develop malignant lymphosarcoma (Schwartz and Levy, 1994). Since BLV seldom causes outward clinical signs of leukemia, the effects of BLV infection on overall bovine health and productivity are minor when only malignant lymphosarcoma is considered. The progression of BLV is now known to significantly affect both humoral and cell-mediated immunity in cattle (Erskine, et al., 2011a). There is a dramatic increase in B lymphocyte populations with significant decreases in the percentages of both CD4 + and CD8 + T lymphocyte populations. Certain type 1 cytokines from CD4 + T lymphyocytes, including interleukin-2 (IL2), IL12, and interferon gamma (IFNγ), are reduced during persistent lymphocytotic BLV infections and this altered cytokine production was suggested to suppress mitogen-induced B- and T - lymphocyte proliferation and function (Okagawa et al., 2012; Konnai et al., 2013; Frie et al., 2017). 1

Practically, the immune dysfunction caused by BLV can impair host immune responses to both infections from other pathogens and immunization. Impairment of rotaviral immune responses in BLV-positive animals were documented in dry cows following vaccination (Archambault et al., 1989). Additionally, serum-neutralization titers for BVD Type I, and ELISA titers for anti-j5 Escherichia coli IgG2 antibodies, were lower in BLV-positive as compared to BLV-negative animals (Erskine et al., 2011b). Negative immune responses among BLV-infected cows to both BHV-1 and Leptospiral immunization and the clinical outcome of concurrent Johne s disease have also been reported (Coussens et al., 2012; Frie et al., 2016). Thus, BLV-induced immune dysfunction may have a greater impact on cattle health than previously believed; and economic losses from this disease are likely underestimated. The possibility that the disease can follow a less obvious course, however, has led to several equivocal studies on how BLV infection may affect dairy cattle productivity. Early studies found no influence on milk production, incidence of mastitis, or reproductive performance. In contrast, more recent studies reported negative effects of BLV infection on reproductive performance, milk production, and in particular, longevity (Ott et al., 2003; Erskine et al., 2012b; Bartlett et al.. 2013; Norby et al., 2016). It is probable that the negative effects of BLV on milk production and reproduction are reduced by early culling of poor performing infected cows, and therefore the major effect of BLV in many herds may primarily be realized by reduced cow longevity. As part of the USDA-NAHMS 1996 dairy study, it was estimated that the average reduction in productivity was approximately $59 per cow for BLV test-positive herds, with losses to the entire dairy industry of $285 million to producers and $240 million for consumers (NAHMS, 1997). Additionally both the NAHMS and 2010 Michigan study found about a 220 lb milk loss from the Rolling Herd Average for each 10% of cows that were infected within a herd, although a more recent study has suggested that this loss could be greater (Figure 1; LaDronka et al., 2015). Cow Longevity In our 2012 Michigan study we found that herds with higher BLV prevalence had a significantly lower proportion of older cows (Erskine, et al., 2012a). This association led to our study of 3,849 dairy cattle that demonstrated a decreased (P<0.0001) survival of cattle with BLV infection as compared to their uninfected herd mates (Bartlett et al., 2013). Compared with age-matched herd mates, infected cattle were 23% more likely to be culled over the 19-month monitoring period, and cattle with the highest ELISA OD values (>.5) were over 40% more likely to be culled. Last year, a large Canadian study corroborated our findings in reporting that BLV positive cattle had a greater probability of being culled or dying when compared to BLV-negative cows (Nekouei et al., 2016). Controlling Within-herd Transmission with Management Transmission of BLV is thought to occur primarily through the transfer of lymphocytes harboring the infectious BLV provirus. Proposed management methods to reduce BLV transmission involve employing single-use hypodermic needles and reproductive sleeves, control of biting flies, freezing or pasteurizing colostrum, avoiding natural breeding, and avoiding blood transfer during tattoos, tail docking, extra teat removal, hoof trims, etc. (Bartlett, 2014). Probably all of these blood borne routes of transmission occur, but the relative importance of each route is unknown and may be different for each farm. Many of these proposed interventions were identified as statistically significant risk factors in observational surveys 2

(Erskine, et al., 2012c). Direct transmission from the exchange of body fluids (nasal secretions, milk, saliva, feces, etc.) can realistically only be controlled by segregation of the infected animals from the rest of the herd. Switching to single use needles and obstetric sleeves is probably the most frequently attempted method of control. Anecdotal reports from several herds that switched to single-use needles and/or reproductive sleeves often indicate no measurable decrease in their BLV prevalence. However, there certainly are other reasons for improvement in medical hygiene in that veterinarians need to be 100% sure that they are not in any way causing any disease transmission. Our 3-herd intervention trial to reduce BLV transmission found that the rate of new BLV infections in cattle receiving single-use hypodermic needles and rectal examination sleeves did not differ from herd mate controls (Ruggiero, et al., 2017). We speculate that specific management interventions by themselves showed little effect due to their inability to control all of the multiple routes of direct and indirect transmission. Detecting Super-shedders for Culling or Segregation Proviral load (PVL) is the number of viral copies per cell or volume of blood, nasal secretions, saliva, milk or other fluids (Jaworski et al., 2016; Yuan et al., 2015). In collaboration with our Japanese colleagues, we now routinely perform the qpcr CoCoMo proviral load assay for several of our research projects (Jimba et al., 2010; Takeshima et al., 2015). PVL differs vastly among ELISA-positive cattle. The first herd we tested 2 years ago had 12 ELISA-positive cattle, with PVL ranging from 30 to 48,826 (x 10 4 copies per μl of blood). This means that the cow with the highest PVL had 1,648 times more provirus per unit of blood than did the cow with the lowest PVL. Hence, the term Super-Shedder is used for high-pvl cattle. The standard BLV antibody ELISA test cannot distinguish low PVL from high PVL cattle (Ruggiero, et al., 2017). The Pearson s correlation between PVL and ELISA optical density is r = 0.4453 (based on 583 tests). Field data supports the idea that most natural BLV transmission is from high PVL cattle. Juliarena (2016) found no transmission in the subsequent 20 months after 20 low PVL cows were introduced into a herd of 105 BLV ELISA-negative cattle. The same paper also notes that the minimum BLV infective dose from low PVL cattle would require the transfer of such a large volume of blood between animals that this would rarely happen. Cattle infected with less than 3 copies /100 cells (i.e. low PVL) did not transmit BLV to other cattle for more than 30 months (Mekata et al., 2015). All observed transmission was from cattle with higher PVL. This laboratory and field evidence strongly supports our working hypothesis that PVL is positively associated with infectivity. The many routes of BLV direct and indirect transmission appear to be largely dependent upon transmission from this subset of highly infectious cattle, making their removal from the herd (via culling or segregation) the obvious critical control point. Recent studies have shown a low BLV proviral load in milk, saliva, nasal secretions, smegma and semen, especially when blood PVL values are high (Jaworski et al., 2016; Yuan et al., 2015; Jimba et al., 2010; Takeshima et al., 2015). Focusing on transmission from so many infectious fluids could prove very difficult compared to removing the high PVL cows whose presence in the herd is the common factor and the weakest link in the various chains of transmission. 3

The term Super-Shedder is relative to the distribution of PVL values within each herd. For example, on our three pilot farms, every 6 months we provide producers with a list of test results sorted in descending order of PVL. The producers start at the top of the list and prioritize these cattle for culling or temporary segregation until they can be culled. At each semi-annual visit, the cattle at the top of the list have progressively lower values for PVL and LC. Therefore, in application, the term super-shedders is defined as the highest PVL relative to herd mates. We have therefore resisted giving a firm definition of the term Super-shedder or to define high PVL or high lymphocyte count (lymphocytosis; LC). Blood Lymphocyte Count The original test for BLV was the Bendixen Key test, which was basically an age-adjusted lymphocyte count. On-farm, chute-side complete blood count (CBC) with differential white blood counts are now being marketed (Advanced Animal Diagnostics, NC). One of these portable machines costs ~$18,000, provides a blood count for $5 per animal, and includes an easy blood collection system for collecting the requisite drop of blood from the jugular. In our pilot project, it is taking one of us about 45 seconds to process each sample and another 45 seconds for the analysis. In contrast, the cost of a CBC at our veterinary school s clinical pathology laboratory is $35 and the results are not usually available for several hours after handdelivery to the laboratory. This remarkable advance in diagnostic technology has suddenly made it economical for the food animal industry to utilize the CBC, which is probably the most common and useful diagnostic test in human and companion animal medicine. Every veterinarian that graduated in the last 40 years is familiar with using CBC data for diagnosis and prognosis. Until now this diagnostic information has never been used commonly used food animal medicine because of the cost, the need to transport blood samples to a laboratory and the delay in obtaining the results. Virtually no training will be needed for the entire population of dairy veterinarians to instantly start employing the CBC as a diagnostic tool. Lymphocyte count (LC), is strongly correlated with PVL and is usually the most easily measured metric of disease progression and a disrupted immune system. The correlation between PVL and LC was reported at r =.88 (Takeshima, 2016), and our data is currently showing a correlation of r =.78 (Ruggiero, et al., 2017). Field studies would be needed to determine what combination of LC, PVL or microrna is the best predictor of infectivity to herdmates. So far, we have been providing both LC and PVL to the three farms participating in our field trial to selectively cull (or segregate) those cattle with the highest PVL and/or LC. Statistically significant reductions in prevalence are being achieved in these herds. First steps: The BLV Herd Profile The first step for a dairy client interested in BLV is the BLV herd profile (Erskine, et al., 2012c; Figure 3), which can be done via ELISA testing of either blood or milk samples. Milk samples submitted through the local DHI organization is usually the easiest, and can be done whether or not the herd uses routine DHI testing. The 10 most recently calved cows in the 1 st, 2 nd, 3 rd and 4 th + lactations are tested. Don t let the producer pick and choose which cattle to test. The prevalence in each lactation group is simply the percentage of tested animals which were positive. The 1 st lactation prevalence is particularly useful because it reflects transmission that 4

occurred in the young stock. An estimate of overall prevalence in the herd is determined by taking the simple average of the 4 lactation-specific measures of prevalence. This average is independent of the herd age breakdown so it can be used to compare among herds and with historical records from the same herd. Herds with a low estimated prevalence may choose to do a whole herd test and cull positive cows to be free of the disease, providing they maintain a closed herd and make sure their young stock are also negative. If herds choose to reduce BLV transmission, the herd profile to help identify age groups where management should be targeted. For example, the herd profile in Figure 2 shows the typical pattern of first lactation cows entering the milking herd at a low prevalence, but then increasing prevalence in later lactations. For a herd with this pattern, management changes should be targeted to reduce transmission within the milking herd. The herd profile in Figure 3 is less common, and demonstrates a pattern where cows are entering the herd already having a high BLV prevalence, which is maintained relatively constant in later lactations. Such a herd should focus their efforts on eliminating risk factors for calves and growing heifers. More information about the BLV herd profile, as well as a spreadsheet that can be used to input the test results and generate a herd profile, can be found on our BLV website www.blvusa.com under the resources tab. Once the BLV herd profile is complete, our partial budget cost estimator worksheet (BLVUSA.com under Resources ) can be used to estimate the economic impact of the disease in the herd. Summary: The prevalence of BLV in our U.S. dairy cows has increased from about 10% in the 1970s to almost 50%. Along with this increase in prevalence has been a new recognition of the hidden economic impact of this disease on milk production and cow longevity. Successful eradication programs in other countries have relied on culling antibody-positive cattle, sometimes preceded by temporary segregation. Management interventions to reduce intra-herd transmission may be unsuccessful if monitoring of herd prevalence and PVL cows ( super-shedders ) is not done concurrently. New diagnostic and disease control approaches are under development to help dairy producers control BLV transmission. Acknowledgements This material is based on work supported by the United States Department of Agriculture and the National Institute of Food and Agriculture award numbers 2014-67015-21632, 2014-68004- 21881 and 2015-67028-23652 5

References Archambault, D., G. Morin, and M. A. Elazhary. 1989. Possible impairment of rotavirus immune response in cattle infected with BLV. Vet. Rec. 124: 570 572. Bartlett, P. C., B. Norby, T. M. Byrem, A. Parmelee, J. T. Ledergerber, and R. J. Erskine. 2013. Bovine leukemia virus and cow longevity in Michigan dairy herds. J. Dairy Sci. 96: 1591-1597. Bartlett, P.C., L. M. Sordillo, T. M. Byrem, B. Norby, D. L. Grooms, C. L. Swenson, J. Zalucha, and R. J. Erskine. 2014. Options for the control of bovine leukemia virus in dairy cattle. J. Am. Coussens, P. M., S. Sipkovsky, B. Murphy, J. Roussey, and C. J. Colvin. 2012. Regulatory T cells in cattle and their potential role in bovine paratuberculosis. Comp Immunol Microbio Infect Diseases. Erskine, R. J., C. M. Corl, J. C. Gandy, and L. M. Sordillo. 2011a. Effect of infection with bovine leukosis virus on lymphocyte proliferation and apoptosis in dairy cattle. Am J Vet Res 72:1059 1064. Erskine R. J., P. C. Bartlett, K. M. Sabo, and L. M. Sordillo. 2011b. Bovine leukemia virus infection in dairy cattle: effect on serological response to immunization against J5 Escherichia coli bacterin. Vet Med Int Available at: www.hindawi.com/journals/vmi/2011/915747/. Accessed Feb 28, 2014. Erskine, R.J., Bartlett, P.C., Byrem, T.M., Render, C.L., Febvay, C., and Houseman, J.T. (2012a). Using a herd profile to determine age-specific prevalence of bovine leukemia virus in Michigan dairy herds. Vet. Med. Intl. 2012:350-374. Erskine, R.J., Bartlett, P.C., Byrem, T.M., Render, C.L., Febvay, C., and Houseman, J.T. (2012b). Association between bovine leukemia virus, production, and population age in Michigan dairy herds. J. Dairy Sci. 95:727-734. Erskine, R.J., P. C. Bartlett, T. M. Byrem, C. L. Render, C. Febvay, and J. T. Houseman. 2012c. Herdlevel determinants of bovine leukemia virus prevalence in dairy farms. J. Dairy Res. 79:445-450. Frie, M. C., K. R. Sporer, J. C. Wallace, R. K. Maes, L. M. Sordillo, P. C. Bartlett, and P. M. Coussens. 2016. Reduced humoral immunity and atypical cell-mediated immunity inresponse to vaccination in cows naturally infected with bovineleukemia virus. Vet. Imm. Immunopath.182:125-135. Frie, M. C., K. R. B. Sporer, O. J. Benitez, J. C. Wallace, C. J. Droscha, P. C. Bartlett, and P. M. Coussens. 2017. Dairy cows naturally infected with Bovine Leukemia Virus exhibit abnormal B- and T- cell phenotypes after primary and secondary exposures to Keyhole Limpet Hemocyanin. Front. Vet. Sci. 4: doi: 10.3389/fvets.2017.00112. Jaworski, J.P., N. G. Porta, G. Gutierrez, R. P. Politzki, I. Alvarez, R. Galarza, A. Abdala, L. Calvinho, and K. G. Trono. 2016. Short communication: Relationship between the level of bovine leukemia virus antibody and provirus in blood and milk of cows from a naturally infected herd. J. Dairy Sci. 99:5629-5634. Jimba, M., S. N. Takeshima, K. Matoba, D. Endoh, and Y. Aida. 2010. BLV-CoCoMo-qPCR: Quantitation of bovine leukemia virus proviral load using the CoCoMo algorithm. Retrovirology 7:91-98. 6

Juliarena, M. A., C. N. Barrios, M. C. Ceriani, and E. N. Esteban. 2016. Hot topic: Bovine leukemia virus (BLV)-infected cows with low proviral load are not a source of infection for BLV-free cattle. J. Dairy Sci. 99:4586-4589. Konnai, S., S. Suzuki, T. Shirai, et al. 2013. Enhanced expression of LAG-3 on lymphocyte subpopulations from persistently lymphocytotic cattle infected with bovine leukemia virus. Comp. Immunol. Microbiol. Infect. Dis. 36:63 69..LaDronka, R.M., B. Norby, T.M. Byrem, R.J. Erskine, P.C. Bartlett. Impact of bovine leukemia virus on herd level production indicators on US dairy farms. Conference of Research Workers in Animal Diseases, December 2015, Chicago, IL. Abstract and presentation. Mekata, H., Sekiguchi, S., Konnai, S., Kirino, Y., Horii, Y., and Norimine, J. (2015). Horizontal transmission and phylogenetic analysis of bovine leukemia virus in two districts of Miyazaki, Japan. J. Vet. Med. Sci. 77:1115-1120. NAHMS-USDA 1997. High Prevalence of Bovine Leukosis Virus (BLV) in U.S. Dairy Herds. Veternary Services Info sheet. Nekouei, O., J. VanLeeuwen, J., H. Stryhn, H., D. Kelton, D., and G. Keefe 2016. Lifetime effects of infection with bovine leukemia virus on longevity and milk production of dairy cows. Prev. Vet. Med. 133:1-9. Norby, B., P. C. Bartlett, T. M. Byrem, and R. J. Erskine. 2016. Effect of infection with bovine leukemia virus on milk production in Michigan dairy cows. J. Dairy Sci. 99:2043-2052. Okagawa T, S. Konnai, R. Ikebuchi, et al. 2012. Increased bovine Tim-3 and its ligand expressions during bovine leukemia virus infection. Vet Res 43:43 45 Ott, S.L., R. Johnson, and S. J. Wells. 2003. Association between bovine-leukosis virus seroprevalence and herd-level productivity on US dairy farms. Preventive veterinary medicine 61, 249-262. Ruggiero, V.J., O.J. Benitez, Y. Tsai, C. Tsai, Y. Lin, P.A. Lee, H.G. Chang, H.T. Wang, and P. Bartlett; Bovine Leukemia Virus Research at MSU, August 2017, Michigan State University, E. Lansing, MI Schwartz, I., and D. Levy. 1994. Pathobiology of bovine leukemia virus. Vet Res. 25:521 536. Takeshima, S. How to Use the Data from BLV-CoCoMo-qPCR. Bovine Leukemia Virus Research at MSU, August 2016 Takeshima, S.N., Y. Kitamura-Muramatsu, Y. Yuan, M. Polat, M., S. Saito, and Y. Aida. 2015. BLV- CoCoMo-qPCR-2: improvements to the BLV-CoCoMo-qPCR assay for bovine leukemia virus by reducing primer degeneracy and constructing an optimal standard curve. Arch.Virol. 160:1325-1332. Yuan, Y., Y. Kitamura-Muramatsu, S. Saito, H. Ishizaki, M. Nakano, S. Haga, K. Matoba, A. Ohno, H. Murakami, and S. N. Takeshima. 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. 7

Figure 1. Association between herd prevalence of bovine leukemia virus and rolling herd average milk production (NAHMS USDA, 1999; Erskine, 2012a; Ott, 2003; LaDronka, 2015) 30000 National Study 2016 14000 25000 MI 2010 12000 Rolling Herd Average (lbs) 20000 15000 10000 NAHMS 1996 10000 8000 6000 4000 Rolling Herd Average (Kg) 5000 2000 0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0 Percent Cows in Herd BLV Positive NAHMS 19962 MI 2010 National Study 2016 8

Figure 2. Results of a BLV herd profile in which cows enter the milking herd with low prevalence but then become positive in subsequent lactations. This pattern suggests that most transmission is in the milking herd. PERCENT COWS BLV POSITIVE 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 90% 70% 40% 10% 1st 2nd 3rd 4th and greater LACTATION GROUP 53% Average 9

Figure 3. An example of a BLV herd profile in which a high percentage of young stock enter the milking herd already infected with BLV. 100% 90% 80% PERCENT COWS BLV POSITIVE 70% 60% 50% 40% 30% 20% 40% 60% 40% 30% 43% 10% 0% 1st 2nd 3rd 4th and greater Average LACTATION GROUP 10