Bayesian latent class estimation of sensitivity and specificity parameters of diagnostic tests for bovine tuberculosis in chronically infected herds in Northern Ireland

Publication history: Accepted - 26 April 2018; Published online - 1 May 2018.In the European Union, the recommended ante-mortem diagnostic methods for bovine tuberculosis (bTB) include the single intradermal cervical comparative tuberculin (SICCT) test and the interferon-gamma (IFN- g) test as an ancillary test. The SICCT test has a moderate sensitivity (Se) and high specificity (Sp), while the IFN-g test has good Se, but a lower Sp than the SICCT test. A retrospective Bayesian latent class analysis was conducted on 71,185 cattle from 806 herds chronically infected with bTB distributed across Northern Ireland (NI) to estimate the Se and Sp of the common ante-mortem tests and meat inspection. Analyses were also performed on data stratified by farming type and herd location to explore possible differences in test performance given the heterogeneity in the population. The mean estimates in chronically infected herds were: (1) ‘standard’ SICCT: Se 40.5–57.7%, Sp 96.3–99.7%; (2) ‘severe’ SICCT: Se 49.0%–60.6%, Sp 94.4–99.4%; (3) IFN-g(bovine–avian) using a NI optical density (OD) cut-off difference of 0.05: IFN-g(B–A)NI: Se 85.8– 93.0%, Sp 75.6–96.2%; (4) IFN-g(bovine–avian) using a standard ‘commercial’ OD cut-off difference of 0.1: IFN-g(B–A)0.1: Se 83.1–92.1%, Sp 83.1–97.3%; and (5) meat inspection: Se 49.0–57.1% Se, Sp 99.1–100%. Se estimates were lower in cattle from dairy farms than from beef farms. There were no notable differences in estimates by location of herds. Certain population characteristics, such as production type, might influence the ability of bTB tests to disclose truly infected cases.This study is part of a larger project on the evaluation of the performance characteristics of the test in chronic bTB herds in NI from 2004 to 2010. It was financed by DAERA (E&I grant code 11/ 03/10)

Monitoring Mycobacterium bovis in Eurasian badgers ( Meles meles ) killed by vehicles in Northern Ireland between 1998 and 2011

Despite extensive long-term eradication programmes, bovine tuberculosis (bTB) remains endemic in much of the British Isles. The cost of the national eradication programme in Northern Ireland was estimated at £23 million in 2010/2011.1 There is evidence that badgers play a role in the maintenance and spread of Mycobacterium bovis to cattle (as reviewed by Allen and others2). Northern Ireland is a small country (13,843 km2) with an agricultural land that is dominated by grass production, which supports 1.6 million cattle among 20,000 farms.3 The estimated badger population of 34,100 (95 per cent confidence interval (CI) 26,200 to 42,000) is widespread and contained within 7600 social groups (95 per cent CI 6200 to 9000).4 A road traffic accident (RTA) survey began in 1998 in Northern Ireland with the aim of describing the occurrence of M bovis within the badger population

Fine-mapping host genetic variation underlying outcomes to Mycobacterium bovis infection in dairy cows

Abstract Background Susceptibility to Mycobacterium bovis infection in cattle is governed in part by host genetics. However, cattle diagnosed as infected with M. bovis display varying signs of pathology. The variation in host response to infection could represent a continuum since time of exposure or distinct outcomes due to differing pathogen handling. The relationships between host genetics and variation in host response and pathological sequelae following M. bovis infection were explored by genotyping 1966 Holstein-Friesian dairy cows at 538,231 SNPs with three distinct phenotypes. These were: single intradermal cervical comparative tuberculin (SICCT) test positives with visible lesions (VLs), SICCT-positives with undetected visible lesions (NVLs) and matched controls SICCT-negative on multiple occasions. Results Regional heritability mapping identified three loci associated with the NVL phenotype on chromosomes 17, 22 and 23, distinct to the region on chromosome 13 associated with the VL phenotype. The region on chromosome 23 was at genome-wide significance and candidate genes overlapping the mapped window included members of the bovine leukocyte antigen class IIb region, a complex known for its role in immunity and disease resistance. Chromosome heritability analysis attributed variance to six and thirteen chromosomes for the VL and NVL phenotypes, respectively, and four of these chromosomes were found to explain a proportion of the phenotypic variation for both the VL and NVL phenotype. By grouping the M. bovis outcomes (VLs and NVLs) variance was attributed to nine chromosomes. When contrasting the two M. bovis infection outcomes (VLs vs NVLs) nine chromosomes were found to harbour heritable variation. Regardless of the case phenotype under investigation, chromosome heritability did not exceed 8% indicating that the genetic control of bTB resistance consists of variants of small to moderate effect situated across many chromosomes of the bovine genome. Conclusions These findings suggest the host genetics of M. bovis infection outcomes is governed by distinct and overlapping genetic variants. Thus, variation in the pathology of M. bovis infected cattle may be partly genetically determined and indicative of different host responses or pathogen handling. There may be at least three distinct outcomes following M. bovis exposure in dairy cattle: resistance to infection, infection resulting in pathology or no detectable pathology

Construction of a full-length infectious cDNA clone of a bovine enterovirus

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Additional file 4: of Fine-mapping host genetic variation underlying outcomes to Mycobacterium bovis infection in dairy cows

Genome-wide association analysis for controls vs cases a Manhattan plot displaying the –log10(P- value) of association of each SNP with the phenotype with respect to genomic position and b Q-Q plot of observed P-values against the expected P-values with a genomic inflation factor of λ = 1.01. Genome-wide (P < 0.05) and suggestive significance (one false positive per genome scan) P-value thresholds are shown as a dashed and dotted line, respectively (PDF 2501 kb)

Additional file 2: of Fine-mapping host genetic variation underlying outcomes to Mycobacterium bovis infection in dairy cows

Significant SNPs using a linear mixed model for each case–control classifications for M. bovis infection. For each trait, the table shows chromosome, significant SNPs, reference SNP id number (rs id), position (in base pairs), the minor allele, minor allele frequency beta coefficient (substitution effect of the minor allele) and P-value of the GWAS analysis (DOCX 15 kb)