# The potential role of aging on acute phase proteins and hypotalamus-pituitary-adrenal axis: A representative cohort study in pregnant mares

**Authors:** Deborah La Fauci, Pietro Medica, Esterina Fazio, Giuliana Barbiera, Maria Gemma Velasco-Martinez, Katiuska Satué

PMC · DOI: 10.1016/j.vas.2026.100616 · Veterinary and Animal Science · 2026-03-07

## TL;DR

This study shows that older pregnant mares have stronger and longer-lasting inflammation and stress responses compared to younger ones.

## Contribution

The study identifies maternal age as a key factor affecting physiological adaptations during equine pregnancy.

## Key findings

- Older mares show heightened inflammatory and endocrine responses during pregnancy.
- Pregnancy alters acute-phase proteins and HPA axis activity in mares.
- Age influences the regulation of HPA axis and acute-phase response during gestation.

## Abstract

•Serum amyloid A, haptoglobin, C-reactive protein, ACTH, and cortisol were longitudinally monitored throughout gestation.•Pregnancy induces measurable changes in acute-phase proteins and HPA axis activity, with maternal age effects.•Older mares display heightened and prolonged inflammatory and endocrine responses compared to younger counterparts.•Findings identify age as a critical factor influencing physiological adaptation during equine pregnancy.

Serum amyloid A, haptoglobin, C-reactive protein, ACTH, and cortisol were longitudinally monitored throughout gestation.

Pregnancy induces measurable changes in acute-phase proteins and HPA axis activity, with maternal age effects.

Older mares display heightened and prolonged inflammatory and endocrine responses compared to younger counterparts.

Findings identify age as a critical factor influencing physiological adaptation during equine pregnancy.

Pregnancy in mares triggers physiological adaptations involving changes in inflammatory biomarkers, particularly acute-phase proteins (APPs), and the activation of the hypothalamic–pituitary–adrenal (HPA) axis. However, the extent to which these responses are influenced by maternal age remains unclear. The hypothesis of this study was that both APP profile and HPA axis activity during gestation are modulated by the age of the mare. Accordingly, the objective was to evaluate these variables throughout pregnancy and assess the impact of age on their physiological regulation. A total of 41 Spanish Purebred mares were evaluated: n. 31 were pregnant (n. 15 of ≤10 years; n. 16 of >10 years old) and n. 10 were non-pregnant mares. Pregnant mares were monitored monthly throughout gestation, to assess temporal changes in APPs and HPA axis activity. Blood samples were collected to measure serum amyloid A (SAA), haptoglobin (Hp), C-reactive protein (CRP), adrenocorticotropic hormone (ACTH), and cortisol (CORT) concentrations. Statistical analysis included repeated measures ANOVA, and t-tests to assess biomarker differences by age and pregnancy status. Pregnant mares, particularly older individuals, showed elevated concentrations of inflammatory and endocrine markers compared to non-pregnant ones (p < 0.05). These findings demonstrate that pregnancy significantly alters inflammatory and endocrine biomarkers in mares; therefore, older pregnant individuals showed more pronounced and sustained increases compared to both younger pregnant and non-pregnant mares. This suggests that maternal age influences the physiological adaptation to pregnancy, particularly in the regulation of the HPA axis and acute-phase response.

## Linked entities

- **Species:** Equus caballus (taxon 9796)

## Full-text entities

- **Genes:** HP (haptoglobin) [NCBI Gene 3240] {aka HP2ALPHA2, HPA1S}, POMC (proopiomelanocortin) [NCBI Gene 5443] {aka ACTH, CLIP, LPH, MSH, NPP, OBAIRH}, APP (amyloid beta precursor protein) [NCBI Gene 351] {aka AAA, ABETA, ABPP, AD1, APPI, CTFgamma}, CRP (C-reactive protein) [NCBI Gene 1401] {aka PTX1}, SAA [NCBI Gene 6287]
- **Diseases:** inflammatory (MESH:D007249)
- **Chemicals:** CORT (MESH:D006854)

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12995502/full.md

## References

93 references — full list in the complete paper: https://tomesphere.com/paper/PMC12995502/full.md

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Source: https://tomesphere.com/paper/PMC12995502