Serum miR-30b is increased in Labrador Retrievers with elevated hepatic copper levels
Bibliographic record
Abstract
Copper associated hepatitis is a hereditary disease in Labrador Retrievers with a complex genetic background. Currently, liver biopsies are needed for diagnosis and treatment monitoring. A serum-based biomarker for hepatic copper levels could provide a less invasive diagnostic approach. Circulating microRNAs (miRNAs) are increasingly studied for their diagnostic potential in hepatobiliary disease and could be utilized in assessing hepatic copper levels. Currently, information on the potential use of copper specific miRNAs in dogs is lacking. The aim of this pilot study was to identify miRNAs associated with elevated hepatic copper levels in Labrador Retrievers. Client-owned Labrador Retrievers with normal (n = 15) and elevated hepatic copper levels (n = 21) were retrospectively selected from a patient database. We performed a miRNA screening array of 277 miRNAs in blood serum from a retrospective case-control group of Labrador Retrievers with normal (n = 5) and elevated hepatic copper levels (n = 5). MicroRNAs that were upregulated in Labrador Retrievers with elevated hepatic copper in the screen, were analyzed with qPCR in a replication cohort of Labrador Retrievers with normal (n = 13) and elevated (n = 18) hepatic copper levels. Results showed that six out of the 277 serum miRNAs were significantly upregulated in elevated hepatic copper cases and these were analyzed in the replication cohort. After Bonferroni correction, cfa-miR-30b (fold-change 2.17, p-value.002) was significantly upregulated in the replication cohort. In this exploratory study, cfa-miR-30b is increased in Labrador Retrievers with elevated hepatic copper levels. This result justifies validation in an extended set of dogs, with different forms of liver disease or in other breeds with copper toxicosis. • Copper associated hepatitis in dogs has to be diagnosed and monitored through liver biopsies, which is both invasive and costly • A blood-based biomarker would be a valuable tool for diagnosis and treatment monitoring • In this pilot study microRNA levels of 277 microRNAs were screened in client-owned Labrador retrievers with normal and elevated hepatic copper levels • Upregulated microRNAs were validated in a replication cohort of Labrador Retrievers with normal and elevated hepatic copper levels. • cfa-miR-30b was significantly upregulated in Labrador retrievers with hepatic copper accumulation and a potential blood-based diagnostic biomarker
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".