The Connection Between Stress and Immune Status in Pigs: A First Salivary Analytical Panel for Disease Differentiation

Abstract

This paper analyzes the association between stress and immune response activations in different diseases, based on the salivary analytics. Moreover, a first attempt to discriminate between diseases was performed by principal component analysis. The salivary analytics consisted of the measurement of psychosocial stress (cortisol and salivary alpha-amylase) indicators, innate (acute phase proteins: C-reactive protein and haptoglobin), and adaptive immune (adenosine deaminase, Cu and Zn) markers and oxidative stress parameters (antioxidant capacity and oxidative status). A total of 107 commercial growing pigs in the field were divided into six groups according to the signs of disease after proper veterinary clinical examination, especially, healthy pigs, pigs with rectal prolapse, tail-biting lesions, diarrhea, lameness, or dyspnea. Associations between stress and immune markers were observed with different intensities. High associations (r = 0.61) were observed between oxidative stress markers and adaptive immune markers. On the other hand, moderate associations (r = 0.31-0.48) between psychosocial stress markers with both innate and adaptive immune markers were observed. All pathological conditions showed statistically significant differences in at least 4 out of the 11 salivary markers studied, with no individual marker dysregulated in all the diseases. Moreover, each disease condition showed differences in the degree of activation of the analyzed systems which could be used to create different salivary profiles. A total of two dimensions were selected through the principal component analysis to explain the 48.3% of the variance of our data. Lameness and rectal prolapse were the two pathological conditions most distant from the healthy condition followed by dyspnea. Tail-biting lesions and diarrhea were also far from the other diseases but near to healthy animals. There is still room for improvements, but these preliminary results displayed a great potential for disease detection and characterization using salivary biomarkers profiling in the near future.

Keywords: disease discrimination; field study; pig; principal component analysis; salivary analytics.

Figure 1

Concentration of salivary analytes studied [CRP (A), Hp (B), ADA (C), Cu (D), Zn (E), TAC (F), TOS (G), ratio TOS/TAC (H), salivary alpha-amylase (I), cortisol (J) and TP (K)] in healthy pigs (n = 40) and animals suffering from a pathological condition (tail-biting lesions n = 13, rectal prolapse n = 13, diarrhea n = 13, lameness n = 14, or dyspnea n = 14). Graph showing the distribution of the population (depending on whether the plot is widening or narrowing), the median (central horizontal line), 25th and 75th percentiles (non-central horizontal lines within the plot), maximum and minimum (edges of the figure). Statistical differences are indicated by ^*, ^**, ^***, and ^**** for p < 0.05, p < 0.01, p < 0.001, and p < 0.0001, respectively. CRP, C-reactive protein; Hp, haptoglobin; ADA, adenosine deaminase; TAC, total antioxidant capacity; TOS, total oxidant status; TP, total protein.

Figure 2

Principal components 1 (Dim 1) and 2 (Dim 2) of salivary biomarkers data form animals under different health conditions (healthy, rectal prolapse, tail-biting lesions, diarrhea, lameness, or dyspnea). In brackets, the percentage of total variance explained the principal component.

Figure 3

Spearman's correlation coefficients between biomarkers quantified in saliva of healthy (n = 40) and diseased (n = 67) pigs. CRP, C-reactive protein; Hp, haptoglobin; ADA, adenosine deaminase; TAC, total antioxidant capacity; TOS, total oxidant status; TP, total protein. Correlations with statistical significance are indicated by *.