Evidence map›Paper›PMID 40968682›Full record

ReviewAnimal genetics2025

Genetic factors for hematological traits in pigs.

Jiahong Sun, Emil Ibragimov, Peter Karlskov-Mortensen, Merete Fredholm

Abstract readReview
In one paragraph

Review in Animal genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jiahong SunDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark.ORCID https://orcid.org/0000-0001-5163-8897
Emil IbragimovDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark.ORCID https://orcid.org/0009-0001-2491-1306
Peter Karlskov-MortensenDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark.ORCID https://orcid.org/0000-0002-2491-2763
Merete FredholmDepartment of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark.ORCID https://orcid.org/0000-0002-3563-7648

Funding

China Scholarship Council CSC202203250011Novo Nordisk Foundation NNFSA210073688
6 · The paper itself

Abstract

Complete blood count with differential is a critical diagnostic tool for evaluating the physiological and health status of individuals by analyzing white blood cells, red blood cells, and platelets. While extensively used in human medicine, the application of complete blood count biomarkers in pigs remain limited. This review focuses on the genetic architecture of hematological traits in pigs (Sus scrofa) using data from genetic association studies. By compiling data from multiple porcine studies, we identified 509 SNPs within 53 high-confidence QTL supported by more than one study. Among these, 37 QTL were homologous to human loci, with 19 containing plausible candidate genes likely to be influencing hematological traits. These genes are often linked to cytoskeletal formation, hematopoiesis, and immune function, highlighting conserved biological mechanisms across species. Our findings provide a foundation for further investigations into the genetic regulation of blood cell parameters in pigs and their implications for health, welfare, and production traits, offering potential translational insights for both veterinary and human medicine.

Indexed as

Quantitative Trait LociSus scrofaAnimalsBlood Cell CountPolymorphism, Single NucleotideSwinecomplete blood countGWASpig health

Identifiers

PMID40968682
PMCPMC12447022

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.