Article Figures & Data
Figures
- FIG 1
Schematic framework for multiscale occupancy model. We adopted a multiscale occupancy modeling framework, where our top tier (deer level, ψ) represents the CWD infection status of an individual deer, the second tier (sample level, θ) represents individual saliva samples over time, when the deer may or may not be shedding. The third tier (detection, p) indicates RT-QuIC detection in each replicate from an individual saliva sample. Because we have false-positive and false-negative errors, it is possible that a saliva sample with no prions (no shedding, middle sample) can produce positive replicates in RT-QuIC and that a sample that does contain prions (shedding, left sample) can produce negative replicates in RT-QuIC. Deer and syringe images courtesy of the Integration and Application Network, University of Maryland Center for Environmental Science (http://ian.umces.edu/symbols/).
- FIG 2
Representative RT-QuIC data for saliva from CWD-infected deer over the course of observation. Each sample was tested in quadruplicates in two experiments (n = 8 replicates total). (A) The numbers of samples with 0%, 0 to ≤25%, 25% to ≤50%, 50 to ≤75%, 75 to <100%, or 100% positive replicates (raw, or naive, results) are indicated by the y axis. (B) The percentages of replicates that were positive for individual samples are indicated by bars. The x axis specifies the months postinoculation; a label on the x axis with no bar indicates that a sample was tested, and no replicates were positive. The observations of imperfect detection (A) and apparent randomness in shedding (B) in the raw data, as depicted here, motivated us to pursue a modeling approach that accounts for detection error.
- FIG 3
Sensitivity is imperfect. We compared two methods for the concentration of saliva before testing by RT-QuIC and assessed the effect of sample storage duration (i.e., amount of time stored at −80°C). Because older samples were all tested with IOME and newer samples were all tested with PTA, it is impossible to model the effects of method and storage time separately. However, we can assess their combined effects on sensitivity. The black lines indicate the average probability of detection (or sensitivity) and the gray shaded regions represent the 95% credible intervals. Vertical dotted lines indicate the ranges of sample storage duration for our samples.
- FIG 4
Probability of prion shedding in saliva increases with time. (A) The mean probability of prion shedding in saliva for a male GG deer inoculated with saliva via the oral route is indicated by the higher black line, and the light gray shaded region represents the 95% credible interval. The mean probability of prion shedding in saliva for a male GG deer inoculated with blood via the IV route is indicated by the lower black line, and the dark gray shaded region represents the 95% credible interval. The x axis indicates months postinoculation, from the date of the last inoculation or the date the contact deer were initially exposed to prion-infected deer. (B) We compared the probabilities of shedding in tonsil biopsy specimen-positive and tonsil biopsy specimen-negative samples. The values are derived from male GG deer inoculated with saliva via the oral route. Violin plots portray our knowledge of the effect of tonsil biopsy specimen status on prion shedding. The widths of the violins are proportional to the probabilities of a particular value of shedding probability being the true value, and the heights of the violins span the 95% credible intervals for the probability of shedding (i.e., there is a 95% probability that the true values of prion shedding are encompassed by the violins). The dots represents the “posterior” means and are a point estimate for shedding probability in each case.
- FIG 5
Probability of shedding is not associated with the genotype at codon 96 or with sex. (A) We compared the probabilities of prion shedding in saliva from deer homozygous for glycine at codon 96 (GG, the more susceptible genotype) and deer heterozygous at codon 96 (GS, the more resistant genotype). The values are derived from male deer inoculated with saliva via the oral route. (B) We compared the probabilities of prion shedding in saliva between male and female deer. The values are derived from GG deer inoculated with saliva via the oral route. Violin plots portray our knowledge of the effect of sex or genotype on prion shedding. The widths of the violins are proportional to the probabilities of a particular value of shedding probability being the true value, and the heights of the violins span the 95% credible intervals for the probability of shedding (i.e., there is a 95% probability that the true values of prion shedding are encompassed by the violins). The dots represents the posterior means and are a point estimate for shedding probability in each case.
- FIG 6
Deer inoculated with CWD+ saliva via the oral route were more likely to shed prions in their saliva than those with other inoculum/route combinations. The probabilities of shedding for GG male deer in each source/route group were compared. Violin plots portray our knowledge of the effect of inoculum source/route on prion shedding. The widths of the violins are proportional to the probabilities of a particular value of shedding probability being the true value, and the heights of the violins span the 95% credible intervals for the probability of shedding (i.e., there is a 95% probability that the true values of prion shedding are encompassed by the violins). The dots represents the posterior means and are a point estimate for shedding probability in each case.
Tables
- TABLE 1
Summary of the characteristics of the deer included in the study
Characteristic or groupa No. (%) of deer (n = 45) 96GG 35 (78) 96GS 10 (22) Male 23 (51) Female 22 (49) PTA concn 17 (38) IOME concn 28 (62) Blood-IP 4 (9) Blood-IV 13 (29) Brain-aerosol 6 (13) Brain-IC 1 (2) Brain-PO 11 (24) Contact 4 (9) Saliva-PO 6 (13) ↵a 96GG, deer homozygous for glycine at codon 96, the most susceptible genotype; PTA, saliva concentration by phosphotungstic acid; IOME, saliva concentration by iron oxide magnetic extraction; IP, intraperitoneal; IV, intravenous; IC, intracerebral; PO, per os (oral).
- TABLE 2
Covariates for occupancy model
Covariatea Scale parameterb Prediction Reference(s) Sex θ Males will have higher probability of shedding (θ) because males have a higher CWD incidence in the wild. The difference is likely due to behaviors exhibited by male deer, which may or may not be replicated in exptl conditions in castrated deer. 33, 34 Genotype (codon 96) θ 96GG deer will have a higher probability of shedding because they are more susceptible to disease and because prion replication occurs earlier than in those with 96GS/96SS. 5, 19 Mos postinoculation θ Deer are more likely to shed prions later in the disease course because the prion load in the animal is higher. 19 Tonsil biopsy specimen positive θ Tonsil biopsy can be used to monitor disease progression. We predict that a deer with a positive tonsil biopsy specimen would be more likely to shed prions in its saliva because the deer has a broader prion distribution than a tonsil biopsy specimen-negative individual. 45 Inoculum/route of inoculation θ Deer inoculated with excreta (saliva, etc.) will have a higher probability of shedding than deer inoculated with brain material. We hypothesize that excreted prions are structurally different from CNS prions and these prions may preferentially be shed. Concn technique p The assay type will affect the probability of detection (p). Of the two methods of sample concn, we predict that IOME will result in a higher probability of detection. 45 Storage duration p Increased storage duration will decrease the probability of detection due to sample degradation.
Supplemental material
- Supplemental file 1 -
Appendix SA (Multiscale false-positive occupancy model specification and associated full-conditional distributions)
PDF, 239K
- Supplemental file 2 -
Table S1 (Deer level covariates)
PDF, 48K
- Supplemental file 3 -
Table S2 (Sample level covariates)
PDF, 76K
- Supplemental file 4 -
Text S1 (Source code for implementing the MCMC algorithm used to estimate parameters in the multiscale false-positive occupancy model)
PDF, 52K
- Supplemental file 5 -
Text S2 (R code for occupancy model)
PDF, 119K
- Supplemental file 6 -
Text S3 (R code for simulated data)
PDF, 107K
- Supplemental file 1 -
