Polymorphisms in the gene encoding bovine interleukin-10 receptor alpha are associated with Mycobacterium avium ssp. paratuberculosis infection status
Bibliographic record
Abstract
BACKGROUND: Johne's disease is a chronic inflammatory bowel disease (IBD) of ruminants caused by Mycobacterium avium ssp. paratuberculosis (MAP). Since this pathogen has been implicated in the pathogenesis of human IBDs, the goal of this study was to assess whether single nucleotide polymorphism (SNPs) in several well-known candidate genes for human IBD are associated with susceptibility to MAP infection in dairy cattle. METHODS: The bovine candidate genes, interleukin-10 (IL10), IL10 receptor alpha/beta (IL10RA/B), transforming growth factor beta 1 (TGFB1), TGFB receptor class I/II (TGFBR1/2), and natural resistance-associated macrophage protein 1 (SLC11A1) were sequenced for SNP discovery using pooled DNA samples, and the identified SNPs were genotyped in a case-control association study comprised of 242 MAP negative and 204 MAP positive Holstein dairy cattle. Logistic regression was used to determine the association of SNPs and reconstructed haplotypes with MAP infection status. RESULTS: A total of 13 SNPs were identified. Four SNPs in IL10RA (984G > A, 1098C > T, 1269T > C, and 1302A > G) were tightly linked, and showed a strong additive and dominance relationship with MAP infection status. Haplotypes AGC and AAT, containing the SNPs IL10RA 633C > A, 984G > A and 1185C > T, were associated with an elevated and reduced likelihood of positive diagnosis by serum ELISA, respectively. CONCLUSIONS: SNPs in IL10RA are associated with MAP infection status in dairy cattle. The functional significance of these SNPs warrants further investigation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".