- Research article
- Open Access
Scrapie prevalence in sheep of susceptible genotype is declining in a population subject to breeding for resistance
© Hagenaars et al; licensee BioMed Central Ltd. 2010
Received: 19 October 2009
Accepted: 14 May 2010
Published: 14 May 2010
Susceptibility of sheep to scrapie infection is known to be modulated by the PrP genotype of the animal. In the Netherlands an ambitious scrapie control programme was started in 1998, based on genetic selection of animals for breeding. From 2002 onwards EU regulations required intensive active scrapie surveillance as well as certain control measures in affected flocks.
Here we analyze the data on genotype frequencies and scrapie prevalence in the Dutch sheep population obtained from both surveillance and affected flocks, to identify temporal trends. We also estimate the genotype-specific relative risks to become a detected scrapie case.
We find that the breeding programme has produced a steady increase in the level of genetic scrapie resistance in the Dutch sheep population. We also find that a significant decline in the prevalence of scrapie in tested animals has occurred a number of years after the start of the breeding programme. Most importantly, the estimated scrapie prevalence level per head of susceptible genotype is also declining significantly, indicating that selective breeding causes a population effect.
The Dutch scrapie control programme has produced a steady rise in genetic resistance levels in recent years. A recent decline in the scrapie prevalence per tested sheep of susceptible prion protein genotype indicates that selective breeding causes the desired population effect.
Scrapie in sheep is a transmissible spongiform encephalopathy (TSE) present in most sheep-producing countries [1, 2]. Infection with (classical) scrapie is thought to occur at young age, after which it takes an incubation period of one or more years before clinical signs, such as uncoordinated movement, abnormal postures and severe scratching, become apparent. During this incubation period the infectious prion protein PrPSc accumulates in the animal . Scrapie control has become a priority in many countries mainly because experimental infection of sheep with bovine spongiform encephalopathy (BSE) has shown that sheep can be infected via the oral route and that the resulting clinical symptoms are very similar to scrapie . Fears that BSE may have been introduced into sheep through consumption of feed supplements in the past, with potential consequences to public health [5, 6], have eased somewhat recently since tests of millions of sheep have not produced a single sample positive for BSE, neither in the healthy-slaughter nor in the fallen-stock testing stream.
The susceptibility to scrapie is modulated by polymorphisms of the sheep prion protein (PrP) gene. In this paper we focus on classical scrapie, for which the most important polymorphisms occur at the codons 136, 154 and 171. Five alleles (VRQ, ARQ, AHQ, ARH and ARR) are observed in this study. The VRQ allele is known to confer high susceptibility to classical scrapie, the ARQ and ARH alleles are associated with moderate susceptibility and the AHQ allele with low susceptibility. The ARR allele confers resistance, with the homozygous genotype ARR/ARR being extremely resistant [1, 7]. These properties make the use of exclusively ARR/ARR rams for breeding (to be referred to as ram selection below) a means to reduce the number of susceptible animals in a sheep population.
In the European Union (EU) the Regulation EU 2001/999 prescribes the genetic testing, and the selection of rams intended for breeding in scrapie-free flocks of "high genetic merit" (followed by culling of the rams with a VRQ allele). Several years before this EU regulation came into force, some Member states already had a national breeding programme in place, including The Netherlands (started in 1998), Great Britain (started in 2001) [8–12], and France (started in 2002). In the Netherlands, the breeding programme consisted of ARR/ARR ram selection, and initially sheep breeders could join it on a voluntary basis. This programme was made compulsory for the whole Dutch sheep industry in November 2004, thereby becoming the most ambitious programme worldwide.
Another important activity for the control of scrapie is the large active surveillance programme of testing healthy slaughtered sheep and fallen stock for scrapie by a rapid test on brainstem samples. This programme concerns animals over 18 months of age and was introduced in the EU in 2002 . The number of animals to be tested is prescribed yearly by the EU and is a percentage of the total size of the Member states' slaughtered sheep and fallen stock. In the Netherlands in the period 2002-2008 this percentage ranged between 10 and 25% for healthy slaughtered sheep and 2.7% and 11% for fallen stock. Since 2003, the EU Regulation EU 2001/999 governs the control measures in flocks of origin of classical-scrapie positive animals in the active or passive surveillance. These measures consist of either a whole-flock cull or genotyping all animals and culling the animals of susceptible genotype and examining the brain stem of all or a sample of the culled animals of at least 12 months of age for scrapie positivity, using rapid tests.
The Dutch sheep population consists of a breeding sector with three large pure breeds (Texel, Swifter and Zwartbles), more than 30 smaller breeds, and a production sector dominated by Texel and Swifter sheep. The production sector makes up more than 90% of the Dutch sheep population. The Dutch Agricultural Census counted 14.369 farms with sheep in The Netherlands in 2005, 7286 of which had less than 50 sheep (Statistics Netherlands, Agricultural census database: http://www.cbs.nl). However, as only farms with certain minimum economic value of their overall agricultural activities are included in the census, the total number of farms with sheep, including those that keep sheep for recreational purposes, is much higher .
Scrapie control measures
Year/date of introduction
Scrapie becomes a notifiable disease
Active surveillance (EU)
Control measures in flocks of origin of classical-scrapie positive animals (EU)
Obligatory use of ARR/ARR rams for flocks with more than 10 breeding ewes (except some rare breeds)
Obligatory use of ARR/ARR rams for all flocks (except some rare breeds)
Obligatory use of ARR/ARR rams withdrawn
The three main aims of this paper are to identify trends in scrapie prevalence in slaughtered and fallen sheep in The Netherlands, to identify trends in the frequencies of different genotypes in the Dutch sheep population, and to determine the relative risk of different PrP genotypes to become a detected scrapie case.
Data and analyses
The analysis of the abovementioned trends and risks are carried out based on recently gathered data on both scrapie infection of and genotype frequencies in the Dutch sheep population. These data consist of two parts: surveillance data and culled-flocks data. The surveillance data consist of the scrapie test results accumulated within the Dutch active surveillance on TSEs in sheep (2002-2008), and of a yearly random genotyping sample from this active surveillance (2005-2008), both from the healthy-slaughter and the fallen-stock samples. Details on the sampling strategy, genotyping technique and rapid test used are given below. The culled-flocks data (2003-2008) consist of scrapie genotyping results and scrapie infection test results in animals that were culled, as part of the mandatory scrapie control efforts, on flocks of origin of scrapie index cases. For details on genotyping and testing see below. Immunohistochemistry (IHC) was used for confirmation of the positive cases detected using the rapid test. IHC and Western blotting were used to discriminate between classical and atypical scrapie.
The surveillance data allow us to study any temporal trend in the detected scrapie cases in the Dutch sheep population and at the same time provide a sample from the genotype frequencies at a national level. The combination allows us to study any related trends in case numbers and frequencies of susceptible versus resistant genotypes. Clearly, we expect to see an increase in the frequency of resistant genotypes, and as a result of that, after some delay, a reduction in scrapie case numbers.
When assessing prevalence trends, we are interested in particular to see if not only the overall prevalence but also the prevalence calculated per head of susceptible genotype is declining as a result of the breeding programme. This is because we seek to determine if the breeding programme causes a population effect. The expected population effect is derived using a simple mathematical model in the additional material [Additional file 1].
Apart from the ram selection, also the culling of scrapie flocks will impact on the scrapie transmission potential, measured by the basic reproduction number R0, in two ways. Firstly, in comparison to a situation without culling, the culling of flocks of origin of scrapie cases will reduce the mean duration of flock-level scrapie outbreaks, and thereby reduce the length of the period that infected flocks pose an infection risk to other (still unaffected) flocks. For a mathematical model of this latter effect we refer the reader to the additional material [Additional file 1]. A second way in which the culling of affected flocks impacts on the transmission potential is by reducing the frequency of susceptible genotypes in the population [9, 11, 12], thus aiding the ram selection program in increasing the genetic resistance level.
The culled-flocks data allow us to calculate the detected infection prevalence in different genotypes, and thereby obtain information on the relative risk of infection across different genotypes.
PrP genotypes were determined (at codons 136, 154, and 171) by a routine TaqMan test that is completely automated. It can detect polymorphisms 136 A to V, 154 R to H, and 171 Q to R. From 2005 (genotyping sample from surveillance) or 2006 (genotyping of index cases in the surveillance and of culled animals in flocks of origin) onwards our TaqMan genotyping additionally distinguishes between Q and H at codon 171. When analyzing the culled-flocks data we consider total numbers of animals for each genotype across the period 2003-2008 and we therefore group the 2006-2008 ARQ and ARH results together, using the notation ARQ*. The TaqMan principle is a test in which a small part of the PrP gene is amplified. During amplification dedicated fluorescent probes are used to detect absence/presence of specific polymorphisms. A second test, based on pyrosequencing, was used as a confirmatory test on randomly selected samples.
Sampling and testing in the active surveillance
Throughout the period of 2002-2008 the sampling strategy in the Dutch surveillance programme at each of the slaughterhouses (healthy slaughter) consisted of randomly selecting one animal per n slaughtered sheep, with a minimum of one sheep on a slaughter day per slaughterhouse. Here n was chosen such that the expected total number of animals sampled in The Netherlands on a 12-months basis would match EU requirements. Due to changes in the EU target number of animals tested per 12 months (from 1 January 2002 until 22 August 2002: 14,250; from 22 August 2002 until 1 January 2004: 39, 500; from 1 January 2004 until 8 July 2006: 10,000; from 8 July 2006 until 1 July 2007: 23,300 and from 1 July 2007 onwards: 10,000), n changed between periods, with n ranging between 3 and 10.
The sampling of fallen stock at the rendering plant (i.e., at the sole such plant in The Netherlands) also followed a random strategy throughout the period of study. During the period 2002-2008, the sampling strategy was designed to randomly sample sufficient fallen sheep to fulfill the EU requirements of testing a specified minimum number of fallen sheep per 12 months. Most often the minimum number was 10,000 animals per 12 months, and this target could be achieved by randomly sampling at most 72 sheep per working day at the rendering plant. In other periods the sampling strategy was randomly adjusted to the changes in the EU target number of fallen sheep tested per 12 months (from 1 January 2002 until 22 August 2002: 3,000; from 22 August 2002 until 1 January 2004: 5,000; from 1 January 2004 until 8 July 2006: 10,000; from 8 July 2006 until 1 July 2007: 20,000 and from 1 July 2007 onwards: 10,000). The rapid tests used for both the active surveillance and culled flocks were the Prionics Check Western (2002-2006) and the Prionics Check Western SR from June 2006 onwards. For classical scrapie these tests have the same diagnostic and analytical sensitivity in our hands. As a result, we do not expect any temporal bias in the data from the Dutch surveillance programme in the period of study.
Sampling from the active surveillance
Size of sample genotyped
Relative scrapie risks
We will use the genotype ARQ*/VRQ, being the most frequent genotype amongst Dutch scrapie cases, as the reference for defining genotype-specific relative risks. The mathematical definition and statistical estimation of genotype-specific relative scrapie risks are as follows. If the scrapie risk of ARQ*/VRQ animals is given by a (binomial) probability pARQ*/VRQ of being found positive, we write the corresponding probability of genotype γ as p γ = r γ pARQ*/VRQ, where r γ is the relative risk of genotype γ. The parameters r γ are estimated using maximum-likelihood based on binomial probabilities p γ and confidence bounds are based on the likelihood ratio test.
Results and Discussion
Trends in genotype frequencies
Trends in scrapie prevalence
Number of positive cases
Percentage of tested animals
Clinical suspects Cases (Number of suspects)
Scrapie flock culls
Flock culls in 2003-2008
Number of flock culls in 2003-2008
Animals present at the time of flock cull
Animals culled (including later individual culls)
Number of secondary cases (i.e. in culled flocks)
Number of culled flocks with secondary cases
Scrapie flock culls by year
Flock culls in 2003-2008
Number of flock culls (all)
Number of flock culls (classical)
Number of secondary cases
Genotype profiles of scrapie-affected flocks
Culled-flocks genotype frequencies
Culled-flocks allele frequencies
Relative susceptibilities of different genotypes
Relative scrapie risks
British cases (1998-2002)
0.0 (0.0 -0.03)
0.0 (0.0 -0.26)
0.0 (0.0 -0.02)
0.0 (0.0 -0.21)
In Table 8 we compare our results with relative risks of clinical scrapie in British sheep calculated from risk estimates by Baylis et al.  from British passive scrapie surveillance data from the period 1998-2002. The same surveillance data have been analyzed by Tongue et al. , but with different genotyping dataset(s) as denominator data. These authors analyzed the risks of clinical scrapie relative to the genotype ARQ/ARQ by estimating odds ratios for the different genotypes. The (point) estimates they obtain, when recalculated relative to ARQ/VRQ, are broadly similar to the relative risks we have calculated here from the estimates by Baylis et al. One striking difference between the two sets of relative risks in Table 8 is observed for the ARR/VRQ genotype: for this genotype the relative infection risk estimated here from the Dutch culled-flocks data is higher than the risk of death from scrapie as estimated by Baylis et al. One possible hypothesis would be that the difference arises due to breed  and/or scrapie strain differences between the countries. Another possible hypothesis would be that the difference arises because ARR/VRQ animals affected by scrapie are less likely to show overt clinical symptoms, and thus to be detected by the British passive surveillance system (1998-2002), than animals of other susceptible genotypes.
In this paper we have analyzed scrapie prevalence data obtained from both surveillance and control, together with yearly genotyping sample from the active surveillance. Although these analyses are specific to The Netherlands, the results seem relevant and encouraging for all other countries interested in scrapie control.
The main results are as follows. Scrapie prevalence in The Netherlands is showing a downward trend in the last four years. Allele and genotype distributions in the Dutch sheep population are showing a clear trend of increasing genetic resistance to scrapie, showing that compliance to the ram selection programme has been substantial. Estimated prevalence levels per head of susceptible genotype are declining significantly, consistently with an anticipated population effect of the breeding programme. Finally, we observe that the relative risk found here for ARR/VRQ animals is much larger than their relative scrapie risk under past passive surveillance in Great Britain.
The observed reduction in scrapie prevalence is likely to be due to two causes: the increasing genetic resistance of the population and culling of scrapie flocks. How much may be attributed to the increase in scrapie resistance, and how much to the shortening of flock-level outbreaks due to the culling of affected flocks? An order-of-magnitude estimation using modelling arguments and using data for 2005 suggests that the contribution of affected-flock culling to the reduction of scrapie prevalence in The Netherlands is small compared to that of selective breeding. For details we refer the reader to the additional material [Additional file 1].
As reported elsewhere , a comparison of the genotyping samples from the active surveillance to an independent genotyping sample, taken on 168 sheep farms, shows a good correspondence. More precisely, in  it is found that the temporal trend in genotype frequencies in the yearly genotyping sample from the active surveillance conforms well to the trend visible in the sample taken on the farms when consecutively removing recent birth cohorts. This result provides further confidence for the assumption that the yearly genotyping sample from the active surveillance streams provides a representative picture of the genotype distribution in the Dutch sheep population. Comparing the overall genotype frequencies estimated above from the surveillance data and from the genotype profiles across the culled flocks, we can investigate to which extent these latter flocks have more susceptible profiles as compared to the national average. We observe that frequencies of susceptible genotypes do not seem to be much above average on farms with scrapie outbreaks, which may seem paradoxical. However, in the presence of ARR ram selection, current between-flock differences in genotype and allele frequencies might not be representative for the differences at the time that the actual scrapie infections took place. Also, the incomplete tracing of flocks of origin of scrapie cases found in the active surveillance might introduce a bias in the culled flocks data towards more professionally organized sheep farmers, that might be more likely to comply with ram selection. Due to the absence of age information in the culled flocks data it requires genetic model extrapolations to correct for these ram selection effects; such analyses will be reported elsewhere.
The relative scrapie risks of different genotypes in positive flocks provide useful clues to the relative susceptibility of these genotypes. The relative susceptibility is of particular interest as a parameter for mathematical models of within-flock scrapie transmission [24–27]. We note that relative prevalence and relative susceptibility cannot be simply equated to each other for two main reasons. The first is that differences in the rate of disease progress between genotypes (as apparent from incubation time differences) are expected to lead to genotype-dependent probabilities of detecting infection in a scrapie test at a given age. This issue is complicated further by genotype-dependent differences in sensitivities of different rapid tests that have been approved for use in the EU screening program . The second is that infection prevalence will only be proportional to susceptibility away from infection saturation levels, i.e. when prevalence is low.
This research was financed by the Dutch Ministry of Agriculture, Nature and Food Quality (LNV). We thank three anonymous referees for their careful comments.
- Detwiler LA, Baylis M: The epidemiology of scrapie. Rev Sci Tech . 2003, 22: 121-143.PubMedGoogle Scholar
- Fediaevsky A, Tongue SC, Noremark M, Calavas D, Ru G, Hopp P: A descriptive study of the prevalence of atypical and classical scrapie in sheep in 20 European countries. BMC Vet Res. 2008, 4: 19-10.1186/1746-6148-4-19.PubMed CentralPubMedView ArticleGoogle Scholar
- van Keulen LJM, Bossers A, van Zijderveld F: TSE pathogenesis in cattle and sheep. Vet Res. 2008, 39: 24-10.1051/vetres:2007061.PubMedView ArticleGoogle Scholar
- Foster JD, Parnham D, Chong A, Goldmann W, Hunter N: Clinical signs, histopathology and genetics of experimental transmission of BSE and natural scrapie to sheep and goats. Vet Rec. 2001, 148: 165-171.PubMedView ArticleGoogle Scholar
- Ferguson NM, Ghani AC, Donnelly CA, Hagenaars TJ, Anderson RM: Estimating the human health risk from possible BSE infection of the British sheep flock. Nature. 2002, 415: 420-424. 10.1038/nature709.PubMedView ArticleGoogle Scholar
- Kao RR, Gravenor MB, Baylis M, Bostock CJ, Chihota CM, Evans JC, Goldmann W, Smith AJA, McLean AR: The potential size and duration of an epidemic of bovine spongiform encephalopathy in British sheep. Science. 2002, 295: 332-335. 10.1126/science.1067475.PubMedView ArticleGoogle Scholar
- Baylis M, Chihota C, Stevenson E, Goldmann W, Smith A, Sivam K, Tongue S, Gravenor MB: Risk of scrapie in British sheep of different prion protein genotype. J Gen Virol. 2004, 85: 2735-2740. 10.1099/vir.0.79876-0.PubMedView ArticleGoogle Scholar
- Arnold M, Meek C, Webb CR, Hoinville LJ: Assessing the efficacy of a ram-genotyping programme to reduce susceptibility to scrapie in Great Britain. Prev Vet Med. 2002, 56: 227-249. 10.1016/S0167-5877(02)00159-9.PubMedView ArticleGoogle Scholar
- Gubbins S, Webb CR: Simulation of the options for a national control programme to eradicate scrapie from Great Britain. Prev Vet Med. 2005, 69: 175-187.PubMedView ArticleGoogle Scholar
- Gubbins S, Roden JA: Breeding programmes for TSE resistance in British sheep - II. Assessing the impact on the prevalence and incidence of scrapie. Prev Vet Med. 2006, 73: 17-31. 10.1016/j.prevetmed.2005.08.001.PubMedView ArticleGoogle Scholar
- Kao RR, Gravenor MB, McLean AR: Modelling the national scrapie eradication programme in the UK. Math Biosci. 2001, 174: 61-76. 10.1016/S0025-5564(01)00082-7.PubMedView ArticleGoogle Scholar
- Truscott JE, Ferguson NM: Control of scrapie in the UK sheep population. Epidemiol Infect. 2009, 137: 775-786. 10.1017/S0950268808001064.PubMedView ArticleGoogle Scholar
- Vilas V, Bohning D, Kuhnert R: A comparison of the active surveillance of scrapie in the European Union. Vet Res. 2008, 39: 37-10.1051/vetres:2008014.View ArticleGoogle Scholar
- Treep L, Brandwijk T, Olink J, Tillie F, Veer M, Verhoek A: Verkenning Hobbydierhouderij. Report (in Dutch) of the "Expertisecentrum LNV", Ministry of Agriculture, Nature and Food Quality. 2004Google Scholar
- Heres L, Brus DJ, Hagenaars TJ: Spatial analysis of BSE cases in the Netherlands. BMC Vet Res. 2008, 4: 21-10.1186/1746-6148-4-21.PubMed CentralPubMedView ArticleGoogle Scholar
- Philippe S, Ducrot C, Roy P, Remontet L, Jarrige N, Calavas D: Sheep feed and scrapie, France. Emerg Infect Dis. 2005, 11: 1274-1279.PubMed CentralPubMedView ArticleGoogle Scholar
- Reckzeh C, Hoffmann C, Buschmann A, Buda S, Budras KD, Reckling KF, Bellmann S, Knobloch H, Erhardt G, Fries R, Groschup MH: Rapid testing leads to the underestimation of the scrapie prevalence in an affected sheep and goat flock. Vet Microbiol. 2007, 123: 320-327. 10.1016/j.vetmic.2007.04.009.PubMedView ArticleGoogle Scholar
- Webb CR, Wilesmith JW, Simmons MM, Hoinville LJ: A stochastic model to estimate the prevalence of scrapie in Great Britain using the results of an abattoir-based survey. Prev Vet Med. 2001, 51: 269-287. 10.1016/S0167-5877(01)00222-7.PubMedView ArticleGoogle Scholar
- Gubbins S: Prevalence of sheep infected with classical scrapie in Great Britain: integrating multiple sources of surveillance data for 2002. J R Soc Interface. 2008, 5: 1343-1351. 10.1098/rsif.2008.0021.PubMed CentralPubMedView ArticleGoogle Scholar
- Gubbins S, McIntyre KM: Prevalence of sheep infected with classical scrapie in Great Britain, 1993-2007. Epidemiol Infect. 2009, 137: 787-791. 10.1017/S0950268809002519.PubMedView ArticleGoogle Scholar
- Tongue SC, Pfeiffer DU, Warner R, Elliott H, Vilas VD: Estimation of the relative risk of developing clinical scrapie: the role of prion protein (PrP) genotype and selection bias. Vet Rec. 2006, 158: 43-50.PubMedView ArticleGoogle Scholar
- Gubbins S, McIntyre KM: Prevalence of sheep infected with classical scrapie in Great Britain, 1993-2007. Epidemiol Infect. 2009, 137: 787-791. 10.1017/S0950268809002519.PubMedView ArticleGoogle Scholar
- Melchior MB, Windig JJ, Hagenaars TJ, Bossers A, Davidse A, van Zijderveld FG: Eradication of scrapie with selective breeding: are we nearly there?. BMC Vet Res. 2010, 6: 24-10.1186/1746-6148-6-24.PubMed CentralPubMedView ArticleGoogle Scholar
- Hagenaars TJ, Donnelly CA, Ferguson NM, Anderson RM: The transmission dynamics of the aetiological agent of scrapie in a sheep flock. Math Biosci. 2000, 168: 117-135. 10.1016/S0025-5564(00)00048-1.PubMedView ArticleGoogle Scholar
- Hagenaars TJ, Ferguson NM, Donnelly CA, Anderson NM: Persistence patterns of scrapie in a sheep flock. Epidemiol Infect. 2001, 127: 157-167. 10.1017/S0950268801005738.PubMed CentralPubMedGoogle Scholar
- Matthews L, Woolhouse MEJ, Hunter N: The basic reproduction number for scrapie. Proc R Soc B. 1999, 266: 1085-1090. 10.1098/rspb.1999.0747.PubMed CentralPubMedView ArticleGoogle Scholar
- Woolhouse ME, Stringer SM, Matthews L, Hunter N, Anderson RM: Epidemiology and control of scrapie within a sheep flock. Proc R Soc B. 1998, 265: 1205-1210. 10.1098/rspb.1998.0421.PubMed CentralPubMedView ArticleGoogle Scholar
- Tongue SC, Wilesmith JW, Nash J, Kossaibati M, Ryan J: The importance of the PrP genotype in active surveillance for ovine scrapie. Epidemiol Infect. 2008, 136: 703-712. 10.1017/S0950268807008928.PubMed CentralPubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.