Salivary and serum haptoglobin, adenosine deaminase, and immunoglobulin G in growing pigs

TL;DR

The study examines how salivary and serum biomarkers change in pigs during different growth stages and finds saliva could be useful for health monitoring.

Contribution

This study is the first to describe the dynamics of salivary and serum haptoglobin, adenosine deaminase, and IgG across the entire pig production cycle.

Findings

Salivary biomarker concentrations were highest in suckling piglets.

Saliva showed stronger correlations between biomarkers than serum.

Gender influenced some biomarker concentrations.

Abstract

Identification of animals in need of medical treatment is important in porcine health management, where analytical samples applicable at farm level could be utilized. Several biomarkers are measurable in saliva, which is less stressful to collect than blood. Saliva sampling is easy to learn and repeatable, making it suitable for monitoring purposes. Previous research suggests that porcine health biomarkers are dependent on production stage and gender, and that combining biomarkers improves diagnostic sensitivity. However, proper monitoring of biomarkers during the complete production cycle has not been studied. We aimed to describe the dynamics of salivary and serum haptoglobin (Hp), adenosine deaminase (ADA), and immunoglobulin G (IgG) in four production stages (suckling, early growing, late growing, finishing), on commercial Finnish pig farms using a total of 117 piglets. The relationship between gender and biomarker dynamics was investigated, as well as the relationships between these biomarkers in saliva and serum.

The highest salivary concentrations of Hp, ADA and IgG were measured in suckling piglets. The differences between production stages were generally larger in saliva than for the corresponding serum biomarkers. All correlation coefficients between salivary biomarkers were positive in each production stage and the strength of the correlation varied from 0.245 to 0.762. No similar trend was observed regarding correlation coefficients either between serum biomarkers or between salivary and serum biomarkers. Gender was associated with some biomarker concentrations.

The biomarker dynamics supported previous findings that collection of analytical samples should be conducted in age-matched populations. Positive and even strong relationships between salivary biomarkers indicate the potential to use especially saliva for health monitoring. Our results also suggest the importance of considering gender effects when assessing some salivary or serum biomarkers.

The online version contains supplementary material available at 10.1186/s40813-024-00368-8.