Anatomical studies
Specimens of ileum were collected from 19 sheep of different ages (0–1 year, 1–2 years and >2 years) from a flock of Cheviot sheep maintained by the Institute of Animal Health Neuropathogenesis Unit (NPU) [20]. The study was limited to animals with no clinical or pathological evidence of intestinal disease. Specimens were obtained from sheep that were either euthanized because of severe arthritis in one or more limbs, died shortly after birth or were culled for flock management reasons. The specimens were opened along their mesenteric borders, and rinsed in cold water. PP tissue and lymphoid follicles were visualised by immersing the intestines in 2% acetic acid for 24 hours, and the follicular content of the patches enhanced by staining with 0.5% methylene blue for 2–5 minutes. PP tissue and lymphoid follicles were easily visualised using this technique.
The terminal ileum (distal 0.6 m of the ileum) was transilluminated on a horizontal X-ray view box and digital images were obtained. Image analysis software (Image-Pro Plus®) was then used to calculate the areas of intestine and of PP tissue. The area of PP tissue was recorded as a percentage of the total area of intestinal tissue.
To determine the number of lymphoid follicles, the stained intestine was placed between two glass slides, the upper of which was etched in square centimetres. Individual lymphoid follicles appeared as bright blue spots against a faintly blue background when viewed on the X-ray box. The number of lymphoid follicles in 6 different sections along the length of the terminal ileum was counted by naked eye, starting at 5 cm from its caudal end and selecting 4 cm2 sections at every 10 cm thereon, proximally. Results were recorded as the average number of lymphoid follicles per cm2 of ileum.
Our results are described in terms of area of PP tissue and lymphoid follicle density in the sheep ileum; analyses indicate that these two measures are closely correlated (rs = 0.958, n = 19, P < 0.001). PP data for cattle and humans were obtained from earlier studies [18, 19]. The studies used different measures to quantify PP tissue from those we obtained here for sheep. The cattle data [18] refer to weight of PP tissue in the small intestine of 94 German beef cattle. The human data [19] refer to number of PPs in the normal small intestine of 46 individuals between 15 and 96 years of age. The study was limited to necropsies performed within a few hours of death, and to patients with no clinical history or pathological evidence of gastrointestinal tract disease. A second, smaller study of human PPs indicates that, in humans, number of PPs and area of PP tissue in the distal ileum were correlated across age classes (r = 0.415, n = 55, P < 0.01) [21]. As far as we are aware, there are no other quantitative data on PP development with respect to age available for these species but, where direct comparisons are possible, it appears that the different measures reflect the same underlying relationship with age.
Scrapie incidence data
The NPU Cheviot flock, a closed flock maintained explicitly as a source of natural scrapie infections, has been comprehensively documented and demographic information and epidemiological data on all sheep are available [20]. In this study, analyses were based on data obtained from an outbreak of scrapie, which spanned the years 1985 to 1994 affecting cohorts born between 1983 and 1992. This represents a total of 1,473 sheep of which 34 developed clinical scrapie. In this flock, scrapie occurs in two PrP genotypes, VRQ/VRQ and VRQ/ARQ [20]. (There is no evidence that PrP genotype influences PP development). Further details of the outbreak are given elsewhere [20].
Age-susceptibility functions
The method for calculating the age susceptibility function for sheep follows that of Boëlle et al. [6] used to derive the age risk function for vCJD. The occurrence of cases in genotype G sheep is modelled by a Poisson process in the (age, time) plane with intensity π
G
(a,t) given by:
where β
G
is the birth rate and r
G
is the relative susceptibility of genotype G individuals, S(a) is the probability of survival (in the absence of scrapie) until age a, h
G
is the probability density function for the incubation period for genotype G individuals, and λ(a,t) is the per capita rate of infection for individuals of age a at time t. The expression sums the contribution to the incidence of infection at age a and time t from animals infected when at age a', taking into account the fact that the number of animals available at age a' to become infected is reduced by those already infected at age u. The low incidence of scrapie in this flock [22] permits modelling of the age and timing of cases as a Poisson process because the course of the outbreak does not significantly impact on the demography of the susceptible sheep.
The survivorship function S(a) is a Weibull function with mean age of death of 2.99 years [23]. The incubation period distribution is a gamma distribution with a mean of 1.9 years [23]. The birth rate β
G
is selected to give the average numbers of sheep of different genotypes born per year. The per capita rate of infection, λ(a,t) has two parts: a time dependent component g(t) which is assumed here to be proportional to an exponential function fitted to the incidence of infection; and an age-dependent component f(a) which represents the relative susceptibilities of different age classes:
where the maximum value taken by f
1
f
2
or f
3
is equal to 1. Standard theory on point processes [24], gives the log-likelihood of the observed age-of-case data to be:
The subscript i denotes actual case data; deaths are known to occur at age a
i
and a time t
i
after the start of the outbreak. Maximum likelihood methods were used to estimate the constant of proportionality, which determines the magnitude of the per capita rate of infection and the age-dependent susceptibility function as defined by f
1
, f
2
and f
3
. We did this for (i) the 34 cases over the 10 year period assuming no differences between genotypes, and (ii) for the 28 genotyped cases allowing the 8 VRQ/ARQ cases to have either a lower susceptibility to infection or (iii) a longer incubation period than the 20 VRQ/VRQ cases. We found that models (ii) and (iii) produced a significant improvement in fit at the 95% level over model (i), but that the shape of the age-dependent susceptibility function was robust to the choice of model. Results are shown for model (ii).
For cattle, estimates of risk of BSE infection were made from n = 158,550 BSE cases in British cattle and were calculated from the cumulative distribution function, defined by Ferguson et al. [5], corresponding to the age-exposure/susceptibility curve (fitted using maximum likelihood methods).
For humans, estimates of risk of vCJD infection were obtained from a previous study that comprised n = 129 vCJD cases in British people, and were fitted using maximum likelihood methods by Boëlle et al. [6].
Concordance between susceptibility data and anatomical data
For each combination of anatomical data and risk of infection estimates we calculated the Spearman's rank correlation coefficient, rs, between the value of the available measure of PP development (area, weight or number) and the risk of infection for an individual of the corresponding age. Sample sizes were n = 19, n = 94 and n = 46 for sheep, cattle and humans, respectively. Correlation coefficients were calculated using S-PLUS 2000 for Windows.