Targeted proteomic analyses during combined angiotensin-converting enzyme inhibitor and mineralocorticoid receptor antagonist administration (CARDALIS®) in healthy dogs

Abstract

Background

The effects of renin–angiotensin–aldosterone system (RAAS) inhibitors on proteomic biomarkers of cardiovascular disease in dogs remain poorly characterized.

Hypothesis/Objectives

To evaluate the effect of RAAS activation and treatment with a combination of benazepril and spironolactone on circulating proteomic biomarkers in healthy dogs.

Animals

Eighteen healthy beagle dogs.

Methods

Prospective experimental study. Dogs were fed a low-sodium diet to induce RAAS activation and randomly assigned to 1 of 3 dosing regimens for 14 days: (1) benazepril 0.25 mg/kg + spironolactone 2 mg/kg PO q24h (label dose); (2) benazepril 0.25 mg/kg + spironolactone 2 mg/kg PO q12h; or (3) benazepril 0.5 mg/kg + spironolactone 4 mg/kg PO q12h. Plasma samples were collected at multiple time points, and the concentrations of 177 unique proteins were quantified using multiplexed proximity extension assay technology via the Olink Target 96 Inflammation and Cardiovascular II panels. Differences between sampling days and groups were assessed using linear mixed models.

Results

Renin–angiotensin–aldosterone system activation was associated with downregulation of proteins associated with cardioprotection, adaptive immunity, and tissue repair (eg, ACE2, FGF-5, CCL4, and MMP-10; P < .05 for all comparisons). Treatment with benazepril and spironolactone led to upregulation of adaptive immune proteins (eg, CCL4, TSLP) and proteins with cardioprotective functions (eg, ACE2). Dose-related differences were observed for a subset of biomarkers.

Conclusions and clinical importance

In this experimental model of RAAS activation, benazepril/spironolactone combination therapy exerts effects on markers of inflammation and fibrosis in dogs.

Introduction

Drugs that modulate the renin–angiotensin–aldosterone system (RAAS), including angiotensin-converting enzyme inhibitors (ACEi) such as benazepril and mineralocorticoid receptor antagonists (MRAs) like spironolactone, are often prescribed to dogs with cardiac disease.^1,2 The primary way in which the effects of these drugs has been studied experimentally is by measuring their effect on circulating biomarkers of the RAAS, such as angiotensin peptides and aldosterone.³ Research demonstrates that the effects of these drugs on circulating RAAS biomarkers are dose-dependent,^4–6 and some evidence suggests that higher doses of ACEi might be associated with improved clinical outcomes.⁷

In humans, the use of proteomic biomarkers has emerged as a useful tool for diagnosing cardiovascular disease, predicting prognosis, and monitoring response to treatment.^8–11 Proteomic biomarkers can also help to identify pathophysiologic mechanisms of heart disease progression and remodeling.^12,13 Several such biomarkers change during cardiac treatment, including RAAS inhibition.^14–16 Specifically, the addition of spironolactone to standard of care treatment in people with heart failure resulted in lower concentrations of proteomic biomarkers associated with fibrosis and collagen synthesis (MMP2, COL1A1, and PICP), as well as biomarkers associated with inflammation and thrombosis (IL17A, VEGF, and urokinase).^17–19

Dogs have a high degree of conservation of the human cardiac proteome, with many proteins showing > 90% sequence homology between the species.²⁰ Several studies in dogs have identified differences in circulating proteomic biomarker concentrations between healthy dogs and dogs with either myxomatous mitral valve disease (MMVD)^21–25 or dilated cardiomyopathy.^26,27 Differences in abundance were noted for proteins involved in immune and inflammatory pathways, the complement cascade, coagulation, lipid metabolism, and structure of the cytoskeleton and extracellular matrix. These exploratory studies suggest that proteomic analysis may be a valuable tool for investigating both disease pathophysiology and the effects of cardiovascular therapies in dogs, as has been demonstrated in humans. However, proteomic literature in dogs remains sparse, reflecting longstanding technical barriers to detecting low-abundance proteins, as well as the high cost and specialized infrastructure required for advanced proteomic analyses.^28,29 No previous studies in dogs have explored changes in proteomic biomarkers after experimental RAAS activation or treatment with a cardiovascular drug.

The objectives of this study were to evaluate how proteomic biomarkers in healthy dogs are altered by experimental activation of the RAAS and subsequent treatment with the RAAS-inhibiting combination of benazepril and spironolactone (CARDALIS®), and to determine whether the proteomic effects of benazepril/spironolactone are dose-dependent. We hypothesized that RAAS activation would result in proteomic biomarker changes associated with inflammation and fibrosis, that treatment with the combination of benazepril and spironolactone would mitigate these changes, and that higher doses would have more anti-inflammatory and anti-fibrotic effects on proteomic biomarkers.

Materials and methods

This prospective experimental study was conducted as part of an investigation evaluating the dose–exposure–response relationship of benazepril/spironolactone (CARDALIS®) on circulating biomarkers of the RAAS in healthy dogs with experimental RAAS activation. Detailed experimental procedures and pharmacokinetic data have been reported previously.⁶ All procedures were approved by the Institutional Animal Care and Use Committee at Iowa State University (protocol number IACUC 23-035) and were performed in accordance with ARRIVE guidelines.³⁰ See Figure 1 for a schematic representation of the study design. Additional methodological details are provided in the Appendix.

Figure 1.

Schematic representation of experimental design and timeline of sampling. There are 4 sampling days: BAS1 (before experimental RAAS activation with low‐sodium diet), BAS2 (after 5 days of low‐sodium diet), DOS1 (after first dose of benazepril/spironolactone [CARDALIS®]), and DOS14 (after 14 days of dosing). Three groups (n = 6 dogs each) received different doses of benazepril/spironolactone. Colored circles indicate purpose and timing of blood samples collected on each sampling day. Reproduced with permission from https://pubmed.ncbi.nlm.nih.gov/39601373/. Abbreviation: RAAS = renin–angiotensin–aldosterone system.

Eighteen purpose-bred healthy adult beagle dogs (9 castrated males, 9 spayed females; 17-32 months old) were enrolled. Dogs were randomized in a parallel-group design to 1 of 3 oral benazepril/spironolactone treatment protocols (n = 6 per group): (1) benazepril 0.25 mg/kg + spironolactone 2 mg/kg every 24 h; (2) benazepril 0.25 mg/kg + spironolactone 2 mg/kg every 12 h; or (3) benazepril 0.5 mg/kg + spironolactone 4 mg/kg every 12 h. Dogs were fed a low-sodium diet beginning after baseline sampling to induce stable RAAS activation.^31,32 Drug administration began on day 0 and continued through day 13.

Blood samples were collected during 2 baseline sampling periods (BAS1 [day −7] and BAS2 [day −2]) and 2 posttreatment sampling days (DOS1 [day 0] and DOS14 [day 13]). Sampling for proteomic analysis occurred over a 24-h period at 0, 2, 4, 10, 16, and 20 h. Plasma was isolated from EDTA blood samples and stored at −80°C until analysis.

Primary outcomes included changes in circulating proteomic biomarkers associated with inflammation, cardiovascular remodeling, and RAAS-related pathways. Proteins were measured using the Olink Target 96 Inflammation and Cardiovascular II panels (Olink Proteomics AB, Uppsala, Sweden), which quantified 177 unique analytes using proximity extension assay (PEA) technology.³³ Results were reported as normalized protein expression (NPX) values. To calculate fold-differences, NPX values were converted to linear ratios.

Primary statistical analyses focused on 2-h post-dose (T2) samples, selected a priori based on expected peak drug concentrations,⁶ with complementary evaluation of 10-h (T10) samples. Data were analyzed using linear mixed-effects models with biomarker NPX values as the response variable. Fixed effects included sampling day, sampling time, their interaction, and baseline biomarker concentration; dog identity was included as a random effect. Dosage-group comparisons and longitudinal comparisons were performed with Tukey-adjusted P-values. Statistical significance was defined as P < .05. Detailed statistical methods are provided in the Appendix.

Results

Effect of RAAS activation

The effect of RAAS activation on proteomic biomarkers before administration of the combination of benazepril and spironolactone was assessed by comparing concentrations of proteomic biomarkers at the 2-h sampling timepoint at BAS2 compared to BAS1. Biomarkers showing significant downregulation or upregulation at BAS2 compared to BAS1 are shown in Table 1 and Figure 2. Patterns of changes suggest overall downregulation of physiologic immune function and tissue repair (eg, CCL4, IL-10), downregulation of the cardioprotective proteins ACE2 and FGF-5, and upregulation of the acute inflammatory protein IL-18. Corresponding results at the 10-h timepoint are presented in Table S1. Similar functional patterns were observed at the 10-h timepoint, and 4 individual proteins were significantly downregulated at both 2 and 10 h. Scatterplots showing individual protein dynamics for ACE2 and FGF-5 across all timepoints at BAS1 and BAS2 are shown in Figure 3, and scatterplots showing individual protein dynamics for all biomarkers achieving significance are available as a Supplementary File.

Table 1.

Proteomic biomarkers showing significant (P < .05) differences in concentration at the 2-h timepoint for BAS2 (after RAAS activation by consuming a low-sodium diet) compared to BAS1 (before any intervention) in 18 healthy Beagle dogs. Biomarkers are grouped by general biological function; a total of 177 proteins were tested. Fold-difference indicates the linear ratio of mean biomarker concentrations (BAS2/BAS1), such that biomarkers that were upregulated after RAAS activation have fold-differences greater than 1, whereas biomarkers that were downregulated after RAAS activation have fold-differences less than 1. Statistical significance is indicated as ^*(P < .05), ^**(P < .01), or ^***(P < .001).

Effect of low-sodium diet	Function group	Protein	Fold-difference	P-value	Biological function	Reference
Downregulation	Immune function	MCP-4	0.72	.01*	Chemokine promoting leukocyte accumulation	45
		TSLP	0.75	.01*	Drives type-2 immune activation	46
		PD-L1	0.77	.03*	Inhibits anti-tumor immunity	47
		IL5	0.84	.02*	Promotes eosinophil growth and activation	48
		TM	0.85	.03*	Activates protein C; reduces coagulation	49
		TRANCE	0.85	.002**	Immune regulation and bone remodeling	50
		CXCL6	0.85	.03*	Hepatocyte proliferation, neutrophil accumulation and activation	51
		CXCL5	0.86	.02*	Mediates trafficking of immune cells	52
		CCL28	0.86	.001**	T-cell chemokine	53
		IL10	0.86	.04*	Suppresses inflammation via immune regulation	54
		IL-10RB	0.87	.006**	Shared receptor for IL-10 family	54
		CD244	0.88	.02*	Activation and differentiation of immune cells	55
		ADA	0.90	.03*	Immune development and maintenance	56
		IL7	0.91	.02*	Supports T-cell development and survival	57
		CCL4	0.91	.01*	Adaptive immune response	58
	Tissue growth and repair	FS	0.78	.01*	Modulates TGF-β during development	59
		TRAIL	0.81	.005**	Induces apoptosis via death receptors	60
		Dkk-1	0.83	.003**	Inhibits Wnt signaling pathway	61
		OPG	0.84	.004*	Regulates bone remodeling	62
		LIF-R	0.87	.001*	Modulates cell proliferation, differentiation, and survival	63
		SCF	0.88	.007**	Stimulates hematopoietic stem cell growth	64
		MMP-10	0.91	.01*	Metalloproteinase involved in vascular remodeling	65
		VEGFD	0.92	.01*	Promotes lymphangiogenesis and angiogenesis	66
		LIF	0.93	.04*	Modulates cell proliferation, differentiation, and survival	67
		Beta-NGF	0.95	.03*	Involved in neuronal proliferation and survival	68
	Cardioprotection	ACE2	0.89	.02*	Blood pressure regulation via natriuresis and diuresis	36
		FGF-5	0.91	.004*	Cardioprotective effect	69
	Digestion and metabolism	ST1A1	0.81	.001*	Conjugates hormones, neurotransmitters, and drugs	70
		LPL	0.87	.01*	Degrades circulating triglycerides	71
		FABP2	0.87	.04*	Fatty acid metabolism, cell growth modulation	72
Upregulation	Acute inflammation	IL18	1.14	.02*	Induces IFN and inflammatory responses	73

Abbreviation: RAAS = renin–angiotensin–aldosterone system.

Figure 2.

Volcano plot showing differences in proteomic biomarker concentrations at the 2-h timepoint for BAS2 vs BAS1, representing the effects of experimental RAAS activation with 5 days of low-sodium diet consumption. The Y-axis represents −log₁₀ of P-values for group differences; horizontal dashed lines represent P-value cutoffs of < .1 (lower) and < .05 (upper). The X-axis represents fold-differences in biomarker concentration between timepoints such that values below 1.0 indicate downregulation, whereas values above 1.0 indicate upregulation. Abbreviation: RAAS = renin–angiotensin–aldosterone system.

Figure 3.

Scatterplots displaying individual dog results (gray lines) and group mean (yellow line) with complete protein dynamics across sampling timepoints (0, 2, 4, 10, 16, and 20 h) for selected biomarkers demonstrating significant differences between sampling days. (A) Concentrations of ACE2 and FGF-5 at sampling days BAS1 and BAS2 (effect of experimental RAAS activation); (B) concentrations of LIF and TSLP at sampling days BAS2 and DOS1 (effect of single-dose benazepril/spironolactone [CARDALIS®]). Biomarker concentrations are shown in NPX values. See Tables 1 and 2 for P-values and fold-differences in mean biomarker concentration between sampling days. Abbreviations: NPX = normalized protein expression; RAAS = renin–angiotensin–aldosterone system.

Effect of single-dose benazepril/spironolactone treatment

The effect of benazepril/spironolactone treatment on proteomic biomarkers was assessed after a single dose by comparing concentrations of proteomic biomarkers at the 2-h sampling timepoint at DOS1 compared to BAS2 (see Table 2 and Figure 4). Patterns of changes suggest that the combination of benazepril and spironolactone led to downregulation of a protein involved in tissue remodeling and angiogenesis (GDF-2), upregulation of the adaptive immune response (eg, TSLP, CXCL6), upregulation of proteins associated with tissue repair (eg, LIF, SRC), and increased concentration of the cardioprotective biomarker FGF-5. Single dosing with benazepril/spironolactone led to the opposite effects as RAAS activation on several biomarkers. Specifically, 5 biomarkers (LIF, CCL4, FGF-5, TSLP, and CXCL6) were downregulated with RAAS activation and upregulated after single-dose benazepril/spironolactone treatment. Corresponding results at the 10-h timepoint are presented in Table S2. Although similar functional patterns were observed at the 10-h timepoint (upregulation of proteins involved in adaptive immune function and tissue repair), no individual protein remained significantly up- or downregulated at both the 2- and 10-h timepoints, highlighting the variability in protein expression observed during the acute dosing phase of the study. Scatterplots showing individual protein dynamics for LIF and TSLP across all timepoints at BAS2 and DOS1 are shown in Figure 3, and scatterplots showing individual protein dynamics for all biomarkers achieving significance are available as a Supplementary File.

Table 2.

Proteomic biomarkers showing significant (P < .05) differences in concentration at the 2-h timepoint for DOS1 (after a single dose of benazepril/spironolactone [CARDALIS®]) compared to BAS2 (after RAAS activation) in 18 healthy Beagle dogs. Biomarkers are grouped by general biological function; a total of 177 proteins were tested. Fold-difference indicates the linear ratio of mean biomarker concentrations (DOS1/BAS2), such that biomarkers that were upregulated after benazepril/spironolactone dosing have fold-differences greater than 1, whereas biomarkers that were downregulated after dosing have fold-differences less than 1. Statistical significance is indicated as ^*(P < .05), ^**(P < .01), or ^***(P < .001).

Effect of benazepril/spironolactone (single dose)	Function group	Protein	Fold-difference	P-value	Biological function	Reference
Downregulation	Digestion and metabolism	LEP	0.76	.04*	Regulates appetite and energy balance	74
	Tissue remodeling and differentiation	GDF-2	0.78	.03*	Regulates cartilage and bone development, angiogenesis, neuronal differentiation	75
Upregulation	Immune function	TSLP	1.32	.03*	Drives type-2 immune activation	46
		CXCL6	1.27	.002**	Hepatocyte proliferation, neutrophil accumulation and activation	51
		IL18R1	1.17	.006**	Mediates IL-18 inflammatory signaling	73
		CCL4	1.09	.02*	Inflammatory and chemokinetic activities	58
	Tissue repair	4E-BP1	2.35	.004**	Regulates Cap-dependent protein translation	76
		AXIN1	1.70	.03*	Inhibits Wnt/β-catenin signaling.	77
		STK4	1.30	.043*	Control of cell proliferation	78
		SRC	1.14	.01*	Controls growth, adhesion, migration signaling	79
		LIF	1.09	.02*	Modulates cell proliferation, differentiation, and survival	67
		CASP-8	1.08	.04*	Initiates extrinsic apoptosis signaling	80
	Digestion and metabolism	DECR1	1.50	.03*	Enables PUFA mitochondrial β-oxidation	81
	Cardioprotection	FGF-5	1.11	.001**	Cardioprotective effect	69

Abbreviation: RAAS = renin–angiotensin–aldosterone system.

Figure 4.

Volcano plot showing differences in proteomic biomarker concentrations at the 2-h timepoint for DOS1 vs BAS2, representing the effects of single-dose benazepril/spironolactone (CARDALIS) treatment. The Y-axis represents −log₁₀ of P-values for group differences; horizontal dashed lines represent P-value cutoffs of < .1 (lower) and < .05 (upper). The X-axis represents fold-differences in biomarker concentration between timepoints such that values below 1.0 indicate downregulation, whereas values above 1.0 indicate upregulation.

Effect of repeated-dose benazepril/spironolactone treatment

The effect of benazepril/spironolactone treatment on proteomic biomarkers was assessed at pharmacokinetic steady state by comparing concentrations at the 2-h sampling timepoint at DOS14 compared to BAS2 (see Table 3 and Figure 5). Similar to single dosing, patterns of biomarker changes suggest that repeated dosing led to downregulation of a protein involved in tissue remodeling (GDF-2) and upregulation of biomarkers associated with the adaptive immune response (eg, TSLP, CCL23) and tissue repair (eg, STK4, PGF). Repeated dosing was also associated with increases in ACE2 concentration. Four biomarkers showed consistent directionality after both single and repeated dosing of benazepril/spironolactone (downregulation of GDF-2; upregulation of TSLP, 4E-BP1, and STK4). Corresponding results at the 10-h timepoint are presented in Table S3, and scatterplots showing individual protein dynamics for all biomarkers achieving significance are available as a Supplementary File.

Table 3.

Proteomic biomarkers showing significant (P < .05) differences in concentration at the 2-h timepoint for DOS14 (at steady state after 14 days of benazepril/spironolactone [CARDALIS®] treatment) compared to BAS2 (after RAAS activation) in 18 healthy Beagle dogs. Biomarkers are grouped by general biological function; a total of 177 proteins were tested. Fold-difference indicates the linear ratio of mean biomarker concentrations (DOS14/BAS2), such that biomarkers that were upregulated after repeated benazepril/spironolactone dosing have fold-differences greater than 1, whereas biomarkers that were downregulated after repeated dosing have fold-differences less than 1. Statistical significance is indicated as ^*(P < .05), ^**(P < .01), or ^***(P < .001).

Effect of benazepril/spironolactone (steady state)	Function group	Protein	Fold-difference	P-value	Biological function	Reference
Downregulation	Inflammation	IL-1RA	0.69	.03*	Inhibits IL-1a-mediated inflammatory signaling	82
		NEMO	0.69	.005**	Essential NF-κB pathway regulator in immune signaling	83
		IL-20	0.69	.03*	Epithelial/immune cytokine in tissue inflammation	84
		IL-15RA	0.85	.003**	Mediates IL-15 signaling for immune cell survival	85
		IL-18	0.88	.03*	Induces IFN and inflammatory responses	73
		hOSCAR	0.93	.02*	Modulates osteoclast activation and innate immune signaling	86
	Digestion and metabolism	CTSL1	0.85	.02*	Lysosomal protease	87
		CST5	0.90	.0004***	Protective role against proteinases in oral cavity	88
		HO-1	0.93	.02*	Heme degradation, regulation of gene expression and protein translation	89
		CTRC	0.93	.01*	Regulates digestive enzymes	90
	Tissue remodeling and differentiation	GDF-2	0.73	.0001***	Regulates cartilage and bone development, angiogenesis, neuronal differentiation	75
		SIRT2	0.73	.01*	Regulates microtubule dynamics and cellular stress responses	91
		GDNF	0.73	.0001***	Promotes dopaminergic neuron survival and maintenance	92
		IL-12B	0.85	.003**	Growth factor for activated T and NK cells	93
		TRANCE	0.86	.04*	Immune regulation and bone remodeling	50
		OPG	0.87	.04*	Regulates bone remodeling	62
		BOC	0.94	.046*	Promotes differentiation of myogenic and neuronal cells	94
Upregulation	Immune function	CCL19	1.46	.001**	Inflammation and immune response	95
		TWEAK	1.34	.0008***	Cytokine inducing proliferation, inflammation, apoptosis	96
		TSLP	1.34	.0008***	Drives type-2 immune activation	46
		CCL17	1.33	.001**	Attracts Th2 lymphocytes	97
		MCP-2	1.29	.02*	Recruits monocytes and immune cells to inflammation	98
		IFN-gamma	1.28	.01*	Cytokine-inducing and modulating immune responses	99
		IgG Fc receptor II-b	1.28	.009**	Inhibitory receptor regulating antibody-mediated immune responses	100
		MERTK	1.27	.005**	Regulates immune tolerance and phagocytosis	101
		TGM2	1.27	.001**	Mediates CD8+ T cell migration during inflammation	102
		IL-27	1.20	.005**	Regulates T‑cell responses, limits Th17 pathology	103
		CCL23	1.18	.001**	Modulation of the immune response	104
		IL13	1.18	.01*	Regulates inflammation and allergic immune responses	105
		CD244	1.17	.005**	Activation and differentiation of immune cells	55
		IL8	1.08	.03*	Attracts neutrophils and promotes inflammation	106
	Tissue growth and repair	PGF	2.41	.004**	Promotes angiogenesis and vascular development	107
		4E-BP1	1.59	.02*	Regulates Cap-dependent protein translation	76
		STK4	1.52	.007**	Control of cell proliferation	78
		THBS2	1.27	.002**	Inhibits angiogenesis and regulates extracellular matrix	108
		Dkk-1	1.16	.02*	Inhibits Wnt signaling pathway	61
		HO-1	1.16	.02*	Heme degradation, regulation of gene expression and protein translation	89
		DNER	1.16	.02*	Mediates Notch signaling in neuronal differentiation	109
		HGF	1.16	.02*	Stimulates cell growth, motility, morphogenesis	110
		AMBP	1.10	.01*	Prevents oxidative cell damage	111
	Cardioprotection	ACE2	1.10	.02*	Blood pressure regulation via natriuresis and diuresis	36
	Other	FGF-23	1.09	.04*	Regulates phosphate concentration in plasma	112

Abbreviation: RAAS = renin–angiotensin–aldosterone system.

Figure 5.

Volcano plot showing differences in proteomic biomarker concentrations at the 2-h timepoint for DOS14 vs BAS2, representing the effects of repeated-dose (steady state) benazepril/spironolactone (CARDALIS) treatment. The Y-axis represents −log₁₀ of P-values for group differences; horizontal dashed lines represent P-value cutoffs of < .1 (lower) and < .05 (upper). The X-axis represents fold-differences in biomarker concentration between timepoints such that values below 1.0 indicate downregulation, whereas values above 1.0 indicate upregulation.

Dose-dependent effects of benazepril/spironolactone treatment

A dose-dependent effect of the combination of benazepril and spironolactone on proteomic biomarkers was assessed using pairwise analyses after a single dose (DOS1; see Table 4) and after repeated dosing (DOS14; see Table 5). Biomarkers showing greater upregulation with higher dosage of single-dose benazepril/spironolactone included proteins involved in tissue growth and repair (eg, LIF) and metabolism (eg, FGF-21). Biomarkers showing dose-dependent differences between dosage groups after steady state included proteins involved in bone or neuronal development (eg, BMP-6, BOC, and TNFRSF11A), although the direction and magnitude of change did not necessarily follow a consistent dose-dependent pattern, with peak effects sometimes occurring at the mid-range (label dose q12h) dosage group. There was no overlap between the subset of biomarkers showing differences between dosage groups after single dose (at DOS1) and those biomarkers showing dose-related differences after repeated dosing (at DOS14). Corresponding results at the 10-h timepoint are presented in Tables S4 and S5.

Table 4.

Proteomic biomarkers showing significant (P < .05) differences in concentration at the 2-h timepoint after the first dose of benazepril/spironolactone (CARDALIS®; DOS1) in pairwise comparisons of the 3 dosage groups (double label dose q12h, label dose q12h, label dose q24h; n = 6 dogs each). A total of 177 proteins were tested. Fold-difference indicates the linear ratio of mean biomarker concentrations (higher dose/lower dose), such that biomarkers that were relatively increased with higher benazepril/spironolactone dosing have fold-differences greater than 1, whereas biomarkers that were relatively lower with higher benazepril/spironolactone dosing have fold-differences less than 1. Statistical significance is indicated as ^*(P < .05), ^**(P < .01), or ^***(P < .001).

	Protein	Pairwise comparison	Fold-difference	P-value	Biological function	Reference
Downregulation	TNFRSF11A	Label dose q12h vs label dose q24h	0.78	.02*	Involved in inflammatory bone loss	113
	BOC	Double label dose q12h vs label dose q12h	0.83	.03*	Tissue remodeling of myogenic and neuronal cells	94
	BOC	Double label dose q12h vs label dose q24h	0.84	.03*	Tissue remodeling of myogenic and neuronal cells	94
Upregulation	FGF-21	Double label dose q12h vs label dose q12h	2.97	.03*	Regulates lipid, glucose, and energy metabolism	114
	Flt3L	Label dose q12h vs label dose q24h	1.88	.03*	Stimulates proliferation of hematopoietic progenitors	115
	LIF	Double label dose q12h vs label dose q12h	1.72	.04*	Modulates cell proliferation, differentiation, and survival	67

Table 5.

Proteomic biomarkers showing significant (P < .05) differences in concentration at the 2-h timepoint after 14 days of benazepril/spironolactone (CARDALIS®; DOS14) in pairwise comparisons of the 3 dosage groups (double label dose q12h, label dose q12h, label dose q24h; n = 6 dogs each). A total of 177 proteins were tested. Fold-difference indicates the linear ratio of mean biomarker concentrations (higher dose/lower dose), such that biomarkers that were relatively increased with higher benazepril/spironolactone dosing have fold-differences greater than 1, whereas biomarkers that were relatively lower with higher benazepril/spironolactone dosing have fold-differences less than 1. Statistical significance is indicated as ^*(P < .05), ^**(P < .01), or ^***(P < .001).

	Protein	Pairwise comparison	Fold-difference	P-value	Biological function	Reference
Downregulation	LOX-1	Label dose q12h vs label dose q24h	0.60	.001**	Receptor-mediating oxidized LDL uptake	116
	BMP-6	Label dose q12h vs label dose q24h	0.78	.01*	Chronic inflammation and fibrosis	117
	IL-20RA	Label dose q12h vs label dose q24h	0.80	.04*	Mediates IL-20 family cytokine signaling	118
	PRSS8	Label dose q12h vs label dose q24h	0.82	.04	Serine protease regulating epithelial sodium channels	119
	Beta-NGF	Double label dose q12h vs label dose q24h	0.93	.02*	Involved in neuronal proliferation and survival	68
Upregulation	BMP-6	Double label dose q12h vs label dose q24h	1.27	.01*	Chronic inflammation and fibrosis	117
	Beta-NGF	Label dose q12h vs label dose q24h	1.06	.03*	Involved in neuronal proliferation and survival	68
	TGM2	Label dose q12h vs label dose q24h	1.32	.04	Mediates CD8+ T cell migration during inflammation	102

Discussion

This study represents a proteomic analysis of RAAS activation and RAAS-modulating therapy in dogs. All reported proteomic effects reflect longitudinal mixed-effects modeling with adjustment for individual baseline values, allowing assessment of within-subject change over time. Overall, differences in concentration were found for a subset of proteins in all conditions of our study—after experimental RAAS activation, after benazepril/spironolactone dosing, and when comparing different doses—providing exploratory support for all 3 aspects of our hypothesis. These findings should be taken in the context that this study was designed as a hypothesis-generating proof-of-concept exploratory analysis, and proteomic findings require confirmation in larger, independently powered studies.

In these healthy dogs, experimental RAAS activation was associated with downregulation of proteins involved in immune function (eg, IL-10, CXCL5, and CCL4), vascular repair (eg, MMP-10), and cardioprotection (eg, ACE2, FGF-5), as well as upregulation of biomarkers linked to acute inflammatory responses (eg, IL-18). This is consistent with the pathophysiology of the classical RAAS, which is a proinflammatory state ultimately leading to fibrosis and vascular remodeling, which can contribute to the pathophysiology of chronic disease.^34,35

Although no previous studies have investigated proteomic biomarker changes with cardiovascular treatment in dogs, several studies have reported differences in proteomic results between dogs with heart disease compared to healthy controls. In different studies, dogs with MMVD have been reported to show differential expression compared to healthy controls in a variety of proteins related to hemostasis, the cytoskeleton, and lipid metabolism²³; iron metabolism, calcium homeostasis, and cell adhesion²⁴; or cytokine release, collagen binding, and the extracellular matrix.²⁵ Other studies comparing among stages of MMVD found differences among disease groups in proteins involved in coagulation, cytokine release, and the extracellular matrix²¹ or endothelin receptors, zinc transport, tumor suppression, and cell membrane transporters.²² In dogs with dilated cardiomyopathy, studies have shown differences compared to healthy controls in proteins associated with the complement cascade, extracellular matrix, and the electron transport chain²⁷ or amino acids and lipid metabolism.²⁶

There is minimal overlap and a lack of consistency across studies in dogs regarding the specific proteins implicated in heart disease, likely due to methodological differences in proteomic analysis (eg, tandem mass tag vs label-free quantification) and peptide identification techniques (eg, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry vs liquid chromatography–mass spectrometry/mass spectrometry). Our study is the first to utilize PEA technology for proteomic analysis in dogs, which offers improved scalability and facilitates cross-species comparisons with similar studies in humans. In addition, our use of an experimental model of RAAS activation rather than dogs with naturally occurring heart disease limits the direct comparability of our findings to prior proteomic studies in dogs. Nonetheless, it is notable that proteins involved in coagulation, collagen metabolism, and extracellular matrix remodeling are frequently differentially expressed in dogs with heart disease. If these pathways contribute to cardiac disease, their effects may be amplified by inflammation and vascular proliferation, as observed in our RAAS-activated model. Importantly, these processes could potentially be attenuated by the anti-inflammatory and anti-fibrotic actions of RAAS inhibitors such as benazepril and spironolactone. These findings highlight the value of exploratory proteomic analyses in uncovering potential mechanisms underlying cardiac disease pathophysiology and informing the development of novel biomarkers and therapeutic targets.

In our study, treatment with a single dose of benazepril/spironolactone reduced the expression of proteins related to vascular proliferation (eg, GDF-2) and increased levels of biomarkers with cardioprotective or adaptive immune functions (eg, FGF-5, STK4) compared to pretreatment baseline. Repeated dosing also attenuated inflammatory responses (eg, TRANCE, IL-12B) and upregulated ACE2 along with proteins involved in adaptive immune regulation (eg, CCL23, CD244). These patterns are consistent with the expected effects of benazepril and spironolactone, whereby the combination of ACEi and MRA counteracts the pro-inflammatory and pro-fibrotic effects of RAAS. The finding of upregulated ACE2 could be particularly clinically meaningful given its biologic importance in the alternative RAAS pathway stimulating natriuresis, diuresis, and vasodilation.^5,36 The protein GDF-2, a marker of remodeling and differentiation in several different tissue types, was the only protein downregulated after both single-dose and repeated-dose benazepril/spironolactone, perhaps highlighting biologic relevance of this protein with respect to RAAS modulation. GDF-2 is involved in the endothelial stress response and preserving vascular homeostasis during inflammation.^37,38 Downregulation of GDF-2 after benazepril/spironolactone treatment could suggest reduced endothelial activation and greater vascular stability, supporting the drug’s anti-inflammatory and anti-fibrotic effect.

Although it is challenging to compare proteomic findings across studies that utilize different proteomic biomarker panels, these findings are generally similar to those from human studies investigating the effects of spironolactone in people with heart disease. Collating findings from the ALDO-DHF trial (spironolactone vs placebo in people with heart failure with preserved ejection fraction), as well as the HOMAGE trial (spironolactone vs standard of care in people with clinical risk factors for heart failure), spironolactone was associated with downregulation of biomarkers related to fibrosis and collagen synthesis (eg, MMP2, COL1A1, and PICP), as well as reductions in biomarkers linked to inflammation and thrombosis (eg, IL17A, VEGF, and urokinase).^17–19 Human studies investigating the effects of ACEi on proteomic biomarkers have provided less consistent comparative information. In a large cross-sectional health survey of adults in Sweden, use of ACEi was associated with a decrease in myostatin but no difference in ACE2.¹⁵ In another study, people receiving ACEi showed differences from those not receiving ACEi in 13 proteomic biomarkers from the Olink Neurology panel, none of which overlap with those evaluated by the Olink Cardiovascular panels used in the present study.¹⁶ Our study design did not allow us to elucidate whether the proteomic effects of the combination of benazepril and spironolactone are driven primarily by the ACEi or MRA components of the drug, and no previous studies have evaluated the effects of a combination of ACEi and MRA on proteomic biomarkers in humans.

Dose-related differences without a consistent monotonic pattern were observed for several proteomic biomarkers in our study. After single dosing (DOS1), higher doses of benazepril/spironolactone were associated with increased concentrations of some biomarkers involved in tissue growth and repair (LIF) and metabolism (FGF-21), and downregulation of biomarkers involved with tissue remodeling during inflammation (BOC, TNFRSF11A). After repeated dosing (DOS14), several proteins with potential mechanistic relationship to RAAS signaling differed between dose groups, including proteins involved in fibrosis and proliferation of certain tissue types (eg, BMP-6, beta-NGF). However, groupwise differences at DOS14 did not consistently follow a dose-dependent pattern, so these findings may reflect indirect or nonspecific effects rather than true pharmacodynamic responses. It is unknown whether the biomarkers identified with these dose comparisons have actual biologic connection to the RAAS, and these results are intended to be exploratory and hypothesis-generating. Human studies of the proteomic effects of ACEi and spironolactone either utilized a single dose of these medications or combined all dosing groups for analysis, such that dose-dependent effects could not be examined.

For several of our analysis and timepoint comparisons, we also identified differences in proteomic biomarker signals that do not have immediate obvious relevance to the cardiovascular system or benazepril/spironolactone treatment. For example, a single dose of benazepril/spironolactone resulted in upregulation of CXCL6, a protein involved in hepatocyte proliferation; repeated dosing led to downregulation of CTRC, a protein involved in regulation of digestion; and a dose-dependent effect was noted for FGF-21, which is involved with glucose and lipid metabolism. We can only speculate about possible relevance of these findings and generate hypotheses about potential mechanistic explanations. For example, it is possible that these changes represent effects of oral absorption and hepatic biotransformation and metabolism of the drug components, benazepril and spironolactone.^39,40 Alternatively, these findings could reflect a true interaction between cardiovascular drugs and handling of energy sources such as glucose and lipids, as might be predicted by the link between metabolic syndrome and cardiovascular risk in people.⁴¹ Finally, it is possible that these proteomic biomarker signals are incidental byproducts of larger complex signaling pathways or have functions that are not yet fully understood. This study was exploratory in design and given the large number of proteins analyzed and the multiple timepoint comparisons performed, there is a risk of false positive results such that some statistically significant findings might not be associated with biologically meaningful differences.

This study has several limitations. We measured proteomic biomarker signals to gain insight into complex biological processes such as inflammation and fibrosis, but our study was not designed to assess the effects of proteomic biomarkers on long-term outcome. Therefore, although our findings indicate more beneficial proteomic biomarker concentrations at higher doses of benazepril/spironolactone, it is not directly implied that these variations in proteomics translate to clinical advantages based on our data alone. By using targeted proteomic panels (Olink Target 96 Inflammation and Cardiovascular II), we increased the likelihood of detecting differences in proteins associated with broader biological systems relevant to inflammation and cardiovascular function. This targeted approach allows for a focused and manageable subset of proteins, helping to reduce spurious or irrelevant findings; however, it also introduces a bias toward detecting changes within these specific systems, potentially overlooking important alterations in other biological pathways.

A large number of proteomic biomarkers was explored in this study. Statistical inferences were adjusted for multiple comparisons at the level of visits and treatment contrasts within each protein using Tukey’s method, but we did not apply an additional correction across the full panel of 177 analytes. This approach reflects the targeted, hypothesis-driven selection of the cardiovascular and inflammation panels and the proof-of-concept, hypothesis-generating scope of the study, where applying a panel-wide correction would be disproportionately conservative relative to the sample size and study aims. However, the likelihood of false-positive findings remains, and our proteomic results should be interpreted as exploratory pending validation in larger, independently powered, placebo-controlled studies. Furthermore, analysis of individual proteins does not necessarily allow interpretation of a systemic metabolic or homeostatic response; a holistic view of entire pathways is necessary for contextual interpretation of proteomics results and is the subject of future study.

This study was performed in a small cohort of healthy dogs with experimentally induced RAAS upregulation as a result of being fed a low-sodium diet,⁴² and the results might differ in dogs with naturally occurring cardiac disease or those receiving other cardiac therapies with effects on RAAS (eg, loop diuretics). Furthermore, the low-sodium diet itself might have had direct effects on protein expression independent of RAAS activation, which could account for variability seen in the changes in protein expression between 2- and 10-h timepoints when comparing BAS2 to BAS1. This further underscores the exploratory nature of this preliminary work and might limit its generalizability. In addition, a concurrent placebo group was not included in this proteomic experiment. Although placebo data from a historical control arm will be integrated into a separate quantitative systems pharmacology pharmacokinetic/pharmacodynamic model of benazepril and spironolactone’s effects on the RAAS, this does not fully mitigate the internal validity limitations of the present proteomic analysis.

Reference ranges for proteomic biomarker concentrations in healthy dogs have not been established; therefore, alterations in proteomic biomarkers were interpreted in relation to differences among study timepoints and dosage groups. Equal numbers of male and female dogs were included, but possible sex-based differences were not explored; there is no published information regarding expected proteomic differences by sex in dogs. Because a combination drug product was studied, it was impossible to separate the individual effects of benazepril vs spironolactone on proteomic biomarkers. Interindividual variability was evident in the pharmacokinetics of benazepril and spironolactone as reported in the primary study,⁶ which aligns with previous literature documenting significant intersubject variability in the pharmacokinetics and pharmacodynamics of ACEi^4,5,32,42,43 and MRA⁴⁴ in dogs.

Conclusion

Experimental RAAS activation led to downregulation of proteomic biomarkers associated with immune function and healing and upregulation of biomarkers associated with the acute inflammatory response. Treatment with the combination of benazepril and spironolactone led to downregulation of proteomic biomarkers associated with inflammation and vascular proliferation, combined with upregulation of cardioprotective and adaptive immune system signals. Dose-related differences were also observed for a subset of relevant biomarkers. These exploratory proteomic biomarker data are intended to be hypothesis-generating and proof-of-concept. Our initial findings can further inform mechanistic studies of the pathophysiology of RAAS activation and inhibition, as well as clinical trials of dogs with cardiac disease.

Abbreviations

ACEi

angiotensin-converting enzyme inhibitor

CHF

congestive heart failure

MMVD

myxomatous mitral valve disease

NPX

normalized protein expression

PK

pharmacokinetic

RAAS

renin–angiotensin–aldosterone system

Appendix: Materials and methods

Animals

This study took place in the context of an experiment investigating the dose–exposure–response relationship of benazepril/spironolactone (CARDALIS®) on circulating biomarkers of the RAAS in healthy dogs with experimental RAAS activation. Study design, experimental procedures, and pharmacokinetic results have been detailed previously.⁶ All procedures were approved by the Institutional Animal Care and Use Committee at Iowa State University (protocol number IACUC 23-035). The study was performed according to the relevant guidelines and regulations, and methods are reported according to ARRIVE guidelines.³⁰

Briefly, 18 purpose-bred healthy beagle dogs (9 castrated males, 9 spayed females; pair-housed in opposite-sex pairs), aged 17-32 months, were used for the study. Dog pairs were randomized into 1 of 3 treatment groups (3 groups of 6 dogs each) receiving different dosages of benazepril/spironolactone in a parallel design. Dogs were allocated to dosing groups using stratified randomization by housing pen and baseline body weight to ensure a balanced distribution of housing and body weight across treatment groups.

Study design

This study was designed as a prospective experiment that took place over 21 days (see Figure 1 for schematic representation of study design). Three groups of 6 dogs each received oral benazepril/spironolactone at the following dosages: (1) benazepril 0.25 mg/kg + spironolactone 2 mg/kg every 24 h (label dose q24h); (2) benazepril 0.25 mg/kg + spironolactone 2 mg/kg every 12 h (label dose q12h); and (3) benazepril 0.5 mg/kg + spironolactone 4 mg/kg every 12 h (double label dose q12h). These dosages were chosen to represent the label dose of CARDALIS®, the label dose given twice daily, and a dose required to reach the benazepril dosage currently recommended in consensus guidelines (0.5 mg/kg twice daily).²

Blood sampling time points included 2 baseline sampling days (BAS1 [day −7] and BAS2 [day −2]) and 2 post-treatment sampling days (DOS1 [day 0] and DOS14 [day 13]). During each timepoint, blood sampling was performed over a 24-h period beginning at 07:00, with blood collected for proteomic biomarkers at 6 timepoints (0, 2, 4, 10, 16, and 20 h). The schedule of blood collection for other testing performed as part of the primary study has been detailed previously.⁶

Starting after sampling at BAS1, the dogs were fed a low-sodium diet (Hill’s Prescription h/d Heart Care; 17 mg sodium per 100 kcal, 0.08% sodium on a dry matter basis) to attain a steady activation of RAAS.^31,32 Starting on the first day of the dosing period (DOS1, day 0) and continuing through the final sampling day (DOS14, day 13), CARDALIS (spironolactone 25 mg and benazepril hydrochloride 2.5 mg tablets, Ceva Santé Animale) was administered orally after 0-h blood sampling (approximately 07:00, all dosage groups) and 12-h blood sampling (approximately 19:00, twice-daily dosage groups only).

Venous blood samples were collected from an external jugular, lateral saphenous, or cephalic vein using a 1-inch, 20-, or 22-gauge needle attached to either a 3 or 6 mL syringe at each timepoint. For proteomic biomarker analysis, 0.5-1.0 mL of whole blood was placed in an EDTA tube with no protease inhibitors or other additives. Samples were centrifuged at 3000 rpm for 15 min, and plasma was transferred into cryovials that were stored at −80°C for later analysis. Maximum time from sample collection to freezing was 2 h.

Proteomic biomarker analysis

Proteins were measured using the Olink Target 96 Inflammation and Cardiovascular II panels (Olink Proteomics AB, Uppsala, Sweden) according to the manufacturer’s instructions. These panels were selected a priori because they provide focused coverage of pathways most directly relevant to RAAS activation, cardiovascular remodeling, vascular inflammation, and the known pharmacologic actions of benazepril and spironolactone. In the context of this proof-of-concept study and the modest sample size, targeted panels were favored over broader discovery platforms to prioritize biologically plausible pathways and maintain an analytically tractable number of proteins.

The proximity extension assay (PEA) technology used for the Olink protocol has been well described,³³ and enabled 177 unique analytes to be analyzed across 2 panels, each simultaneously quantifying 92 biomarkers, using 1 μL of sample. The total number of distinct analytes is less than the theoretical 184 due to partial overlap in biomarker content between the 2 panels. In brief, pairs of oligonucleotide-labeled antibody probes bind to their targeted protein, and with correct target binding the 2 probes are brought in close proximity allowing the oligonucleotides to hybridize in a pair-wise manner. The addition of a DNA polymerase leads to a proximity-dependent DNA polymerization event, generating a unique polymerase chain reaction (PCR) target sequence. The resulting DNA sequence is subsequently detected and quantified using a microfluidic real-time PCR instrument (Signature q100, Standard Biotools). The resulting Ct-data are then quality controlled and normalized using a set of internal and external controls.

The final assay read-out is presented in normalized protein expression (NPX) values, which is a relative quantitation using an arbitrary unit on a log2-scale where a high value corresponds to a higher protein expression. For data calculation of fold-differences in tables, NPX values were converted to a linear scale (linear_value = 2^NPX_value), with fold-difference indicating the linear ratio of mean biomarker concentrations between timepoints. For example, when comparing BAS2 to BAS1, the fold-difference would be calculated as (2^NPX_BAS2/2^NPX_BAS1); a fold-difference of 1.5 in this setting would mean that the biomarker was upregulated by 50% after RAAS activation compared to baseline, whereas a fold-difference of 0.75 would mean that the biomarker was downregulated by 25% after RAAS activation compared to baseline.

The internal controls are designed to mimic and monitor the different steps of the PEA. They consist of 2 incubation/immuno controls, an extension control and a detection control. The internal controls are introduced to all samples as well as to the external controls and are used for quality control and normalization of the data. The external controls consist of a negative control used to calculate the limit of detection, as well as a triplicate of interplate controls that are used for data normalization. Quality control of the data is performed in 2 steps. First, the run is quality controlled by calculating the standard deviation for the detection control and the incubation/immuno controls. The SD should be below 0.2 for a run to pass quality control. Secondly, each sample is quality controlled by comparing the results for the detection control and one of the incubation controls against the run median. Samples that fall more than 0.3 NPX from the run median with regards to these 2 internal controls will fail the quality control.³³

All assay validation data (detection limits, intra- and inter-assay precision data, etc) are available on the manufacturer’s website (www.olink.com).

Statistical analysis

Primary proteomic analyses were focused on the 2-h post-dose sample (T2), which was selected a priori to coincide with the time of maximum plasma concentration of benazepril and spironolactone metabolites in dogs.⁶ This was complemented by evaluation of a later 10-h post-dose sample (T10) to capture more delayed changes in circulating protein expression and downstream pathway activation. Future studies will consider the full time-course of proteomic biomarker concentrations with comparison between 0-, 2-, 4-, 10-, 16-, and 20-h results.

All statistical analyses were conducted using R software (version 4.2.2; R Core Team, 2022). Descriptive statistics were used tosummarize the data. Group comparisons were performed using a linear mixed model with NPX data as the response variable. Sampling day, time of sampling (T2 or T10), the interaction between sampling day and time, and baseline value (T0) of the biomarker were included as fixed effects; dog identity was included as a random effect. Normality of the residuals was graphically evaluated using Q-Q plots.

For comparisons of biomarkers by sampling day (eg, BAS2 vs BAS1), all benazepril/spironolactone dosage groups were pooled. For comparisons by dosage, pairwise comparisons were performed among the 3 dosage groups. P-values were adjusted in each linear mixed model to account for multiplicity across sampling days and dosage comparisons using the Tukey method. P-values < .05 were considered statistically significant. A P-value cutoff of < .1 was also included in the figures to highlight the trend effect on some markers. Fold-difference in biomarker concentration was calculated as the linear ratio of mean biomarker concentrations for the comparisons (later sampling day/earlier sampling day, or higher dose/lower dose), such that biomarkers that were upregulated at a later sampling day or higher dosage had fold-differences greater than 1, whereas biomarkers that were downregulated under the same conditions had fold-differences less than 1.

Author contributions

Jessica Ward (Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing—original draft, Writing—review & editing), Jessica Goodman (Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing—review & editing), Thomas Blondel (Data curation, Formal analysis, Funding acquisition, Methodology, Resources, Software, Validation, Visualization, Writing—review & editing), Christopher Zdyrski (Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Writing—review & editing), Elizabeth A. Manson (Conceptualization, Data curation, Investigation, Methodology, Project administration, Supervision, Writing—review & editing), Maria Merodio (Data curation, Investigation, Methodology, Project administration, Writing—review & editing), Ryan Lamers (Conceptualization, Investigation, Methodology, Resources, Software, Validation, Writing—review & editing), Karin Allenspach (Conceptualization, Investigation, Methodology, Project administration, Supervision, Writing—review & editing), Emilie Guillot (Conceptualization, Funding acquisition, Methodology, Resources, Writing—review & editing), and Jonathan P. Mochel (Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing—original draft, Writing—review & editing)

Conflicts of interest

Authors E.G. and T.B. are employees of Ceva Santé Animale. Authors J.L.W., K.A., and J.P.M. have served as consultants for Ceva Santé Animale and have received reimbursement and honoraria for consulting, expert testimony, travel, and service as key opinion leaders (KOLs). Although Ceva Santé Animale provided funding and study drug for this research, and this study describes the effects of a drug manufactured by Ceva Santé Animale, the study logistics and sample handling were performed with randomization and by study personnel with no conflicts of interest (E.M. and M.M.). Authors J.G. and R.P.L. are employees of Olink Proteomics, part of Thermo Fisher Scientific.

Funding

Funding for this study was provided by Ceva Santé Animale.

Off-label antimicrobial declaration

The authors declare no off-label use of antimicrobials.

Institutional animal care and use committee or other approval declaration

Institutional Animal Care and Use Committee approval was granted through Iowa State University (protocol number 23-035).

Human ethics approval declaration

The authors declare human ethics approval was not needed.

Declaration of assistive AI in scientific writing

ChatGPT-5.1 (OpenAI, 2025) was used to support the writing process. Its use was limited to improving grammar and enhancing readability of this manuscript, without generating new data, analyses, or conclusions. Use of AI assistance is disclosed in line with prevailing authorship and publication-ethics guidance from the Committee on Publication Ethics (COPE¹) and the International Committee of Medical Journal Editors (ICMJE²). All AI-generated text was reviewed and edited thoroughly by the authors, who take full responsibility for the final content of the publication.