Hostname: page-component-74656f9884-j7cmm Total loading time: 0 Render date: 2026-11-10T03:21:19.768Z Has data issue: false hasContentIssue false

Circulating miR-23b-3p, miR-145-5p and miR-200b-3p are potential biomarkers to monitor acute pain associated with laminitis in horses

Published online by Cambridge University Press:  10 July 2017

C. Lecchi
Affiliation:
Dipartimento di Medina Veterinaria, Università degli Studi di Milano, Via Celoria 10, 20133 Milano, Italy
E. Dalla Costa
Affiliation:
Dipartimento di Medina Veterinaria, Università degli Studi di Milano, Via Celoria 10, 20133 Milano, Italy
D. Lebelt
Affiliation:
Havelland Equine Clinic, 14778 Beetzsee, Germany
V. Ferrante
Affiliation:
Dipartimento di Medina Veterinaria, Università degli Studi di Milano, Via Celoria 10, 20133 Milano, Italy
E. Canali
Affiliation:
Dipartimento di Medina Veterinaria, Università degli Studi di Milano, Via Celoria 10, 20133 Milano, Italy
F. Ceciliani
Affiliation:
Dipartimento di Medina Veterinaria, Università degli Studi di Milano, Via Celoria 10, 20133 Milano, Italy
D. Stucke
Affiliation:
Havelland Equine Clinic, 14778 Beetzsee, Germany
M. Minero*
Affiliation:
Dipartimento di Medina Veterinaria, Università degli Studi di Milano, Via Celoria 10, 20133 Milano, Italy

Abstract

Circulating microRNAs (miRNAs) are emerging as promising biomarkers for several disorders and related pain. In equine practice, acute laminitis is a common disease characterised by intense pain that severely compromises horse welfare. Recently, the Horse Grimace Scale (HGS), a facial expression-based pain coding system, was shown to be a valid welfare indicator to identify pain linked to acute laminitis. The present study aimed to: determine whether miRNAs can be used as biomarkers for acute pain in horses (Equus caballus) affected by laminitis; integrate miRNAs to their target genes and to categorise target genes for biological processes; gather additional evidence on concurrent validity of HGS by investigating how it correlates to miRNAs. Nine horses presenting acute laminitis with no prior treatment were recruited. As control group, nine healthy horses were further included in the experimental design. Samples were collected from horses with laminitis at admission before any treatment (‘pre-treatment’) and 7 days after routine laminitis treatment (‘post-treatment’). The expression levels of nine circulating miRNAs, namely hsa-miR-532-3p, hsa-miR-219-5p, mmu-miR-134-5p, mmu-miR-124a-3p, hsa-miR-200b-3p, hsa-miR-146a-5p, hsa-miR-23b-3p, hsa-miR-145-5p and hsa-miR-181a-5p, were detected and assessed as potential biomarkers of pain by quantitative PCR using TaqMan® probes. The area under the receiver operating curve (AUC) was then used to evaluate the diagnostic performance of miRNAs. Molecular data were integrated with HGS scores assessed by one trained treatment and time point blind veterinarian. The comparative analysis demonstrated that the levels of miR-23b-3p (P=0.029), miR-145-5p (P=0.015) and miR-200b-3p (P=0.023) were significantly higher in pre-treatment and the AUCs were 0.854, 0.859 and 0.841, respectively. MiR-200b-3p decreased after routine laminitis treatment (P=0.043). Combining two miRNAs in a panel, namely miR-145-5p and miR-200b-3p, increased efficiency in distinguishing animals with acute pain from controls. In addition, deregulated miRNAs were positively correlated to HGS scores. Computational target prediction and functional enrichment identified common biological pathways between different miRNAs. In particular, the glutamatergic pathway was affected by all three miRNAs, suggesting a crucial role in the pathogenesis of pain. In conclusion, the dynamic expression of circulating miR-23b-3p, miR-145-5p and miR-200b-3p was detected in horses with acute laminitis and miRNAs can be considered potentially promising pain biomarkers. Further studies are needed in order to assess their relevancy in other painful conditions severely compromising horse welfare. An important implication would be the possibility to use them for the concurrent validation of non-invasive indicators of pain in horses.

Information

Type
Research Article
Copyright
© The Animal Consortium 2017 
Figure 0

Figure 1 Box plots for circulating pain-related microRNAs levels: (a) miR-23b-3p, (b) miR-200b-3p, (c) miR-146a-5p, (d) miR-181a-5p and (e) miR-145-5p. a,b,abIndicate significant differences among the groups (control, pre-treatment and post-treatment) with a significance level at P<0.05. The black lines inside the boxes mark the medians. Whiskers indicate variability outside the upper and lower quartiles.

Figure 1

Figure 2 Receiver–operator characteristics curve analysis of candidate pain-related microRNAs. AUC=area under the curve; CI=confidence interval.

Figure 2

Figure 3 Composite Pain Scale (CPS) and Horse Grimace Scale (HGS) scores of the control, pre-treatment and post-treatment groups drawn in a box plot. Differences between the groups (control, pre-treatment and post-treatment) are indicated as follows: ***P<0.000. The black lines inside the boxes mark the medians. Whiskers indicate variability outside the upper and lower quartiles. Circles, labelled with the individual case numbers, represent outliers (1.5 to 3 times length of the box).

Figure 3

Figure 4 Predicted messenger RNA (mRNA) targets for differentially expressed microRNAs (DE-miRNAs). (a) Venn diagram showing the genes that are potential targets of DE-miRNAs. (b) TargetScan software was used to identify potential mRNA targets. The list was filtered by selecting those genes that encode for ion channels: solute carrier family transporters (SLC), potassium voltage-gated channel (KCN), voltage-gated sodium channel (SCN), γ-aminobutyric acid (GABA) receptor, voltage-dependent calcium channel (CACN), adrenoceptor α (ADRA), potassium channel (tetramerization domain) (KCTD), hyperpolarization-activated cyclic nucleotide-gated potassium channel (HCN), two pore segment channel (TPCN), transient receptor potential cation channel (TRP). (c) Glutamatergic pathway identified by KEGG pathway analysis using the mRNA targets. Proteins coded by mRNA targets genes are highlighted in red. Glutamine transporter (GLNT) and excitatory amino acid transporters (EAAT) belong to SLC; voltage-gated Ca2+ channels (VGCC) to CACN.