A scoping review of neuroendocrinological biomarkers with potential for use in equine behavioral medicine practice.

This scoping review maps which neuroendocrine biomarkers are being used to indicate horses’ emotional states and welfare, highlighting ACTH, cortisol, and serotonin as most studied and noting others like oxytocin, melatonin, dopamine, and tryptophan. It finds that varied methods and contexts currently limit clinical usefulness and calls for standardized protocols and clearer definitions to enable routine practice.

What the review set out to do and why it matters

• Identify which neuroendocrinological biomarkers have been studied over the last two decades for assessing equine emotions and welfare relevant to behavioral medicine.
• Appraise how methodological, subject-related, and context-dependent factors influence biomarker values and interpretation.
• Clarify the current clinical utility of these measures for diagnosis, case monitoring, and selection of biological therapies in equine behavioral medicine.
• Support the growing demand for objective indicators of affective state and welfare in horses across training, management, clinical, and research contexts.

Scope and approach of the review

• Covered published findings from roughly the last two decades focusing on neuroendocrine markers linked to stress, arousal, mood, social bonding, circadian rhythms, and reward.
• Summarized the frequency of use and reported utility of each biomarker and the conditions under which they were sampled and interpreted.
• Assessed factors that could alter reference values, including biological rhythms, environment, handling, assay methods, and horse-specific characteristics.
• Adopted a scoping (mapping) methodology to synthesize breadth of evidence rather than a narrow meta-analytic estimate of effect sizes.

Key biomarkers identified and their typical interpretations

• Adrenocorticotropic hormone (ACTH)
  • Commonly measured; reflects pituitary-adrenal axis activation and is also central in diagnosing pituitary pars intermedia dysfunction (PPID).
  • Sensitive to seasonality (notably in autumn), stressors, pain, and handling; interpretation requires strict control for time-of-year and context.
• Cortisol
  • Among the most frequently used indicators of HPA-axis activity and stress reactivity.
  • Measured in plasma/serum, saliva, feces, hair; each matrix reflects different time windows (acute minutes–hours vs. chronic weeks–months).
  • Influenced by circadian rhythm, exercise, novelty, social context, disease, and sampling stress.
• Serotonin (5-HT)
  • Explored in relation to mood, impulsivity, and affect regulation.
  • Peripheral measures (e.g., blood) may not mirror central serotonergic tone; diet (tryptophan), gut factors, and platelets can confound values.
• Oxytocin
  • Less frequently reported; of interest for social bonding, affiliative behavior, and stress-buffering.
  • Assay and pre-analytical handling challenges complicate interpretation; context of positive human–horse interactions is relevant.
• Melatonin
  • Marker of photoperiod and circadian timing; relevant to seasonally varying physiology and potentially to mood and arousal patterns.
  • Strong diurnal and seasonal variation necessitates strict sampling schedules.
• Dopamine
  • Associated with motivation, reward, and some stereotypic behaviors.
  • Peripheral measures are indirect proxies of central dopaminergic activity; handling and stress can alter levels.
• Tryptophan
  • Serotonin precursor; used as a dietary supplement in some management strategies.
  • Blood levels reflect diet and metabolism more than emotional state per se; interpret in conjunction with behavior and other biomarkers.

Factors that affect reference values and interpretation

• Biological rhythms and timing
  • Strong circadian and seasonal effects on ACTH, cortisol, melatonin; timing of collection critically alters values.
• Sampling matrix and window
  • Blood and saliva reflect acute states; feces and hair index cumulative exposure; choice must match the clinical question.
• Subject-related characteristics
  • Age, sex/reproductive status, breed/type, temperament, fitness level, health conditions (e.g., PPID), and medication history.
• Management and environmental context
  • Housing, turnout, social grouping, feeding schedule and diet, training intensity, transport, and recent stressful events.
• Sampling and handling procedures
  • Human–horse interaction during sampling, restraint, venipuncture stress, assay choice, pre-analytical storage, and units reported.
• Behavioral context and concurrent measures
  • Interpretation improves when paired with validated behavioral observations and other physiological measures (e.g., heart rate variability).

Methodological diversity and limitations highlighted

• Heterogeneous protocols
  • Differences in sample matrices, collection times, handling, assays, and reporting units hinder cross-study comparison and clinical translation.
• Variability in definitions and outcomes
  • Lack of consensus on operational definitions of specific emotional states makes linking biomarkers to subjective states challenging.
• Study design constraints
  • Small sample sizes, varied populations, and limited longitudinal tracking reduce generalizability and establishment of reference intervals.
• Potential confounding and bias
  • Sampling stress, seasonality, diet, medication, and comorbidities often insufficiently controlled or reported.

Clinical implications for equine behavioral medicine

• Current utility
  • ACTH and cortisol are most ready for cautious clinical use, especially within well-controlled contexts and for monitoring change within individuals.
  • Serotonin and others show promise but require careful interpretation and stronger validation before routine decision-making.
• Use cases
  • Baseline and follow-up assessment during behavior modification or management changes.
  • Supporting differential diagnosis when stress, pain, or endocrine dysregulation is suspected, alongside clinical exam and behavior data.
  • Evaluating candidate biological therapies or supplements, with pre-registered outcomes and standardized sampling.
• Interpretation principles
  • Prioritize within-horse changes over single absolute values; account for time-of-day/season and context.
  • Integrate multiple data streams (behavioral scoring, HR/HRV, clinical signs) rather than relying on a single biomarker.

Recommendations for standardization and reporting

• Protocol harmonization
  • Agreed sampling times relative to circadian/seasonal cycles and events; standardized matrices and handling procedures.
• Assay and unit consistency
  • Validated assays with cross-lab calibration; consistent units and clear reporting of limits of detection and variability.
• Contextual metadata
  • Comprehensive reporting of horse demographics, management, recent stressors, medications, diet, and behavioral context.
• Outcome definitions
  • Consensus on operational definitions and validated instruments for specific emotional states to link biomarkers to subjective experience.
• Reference intervals
  • Establish season- and matrix-specific reference ranges, including age and sex strata, using adequately powered samples.

Practical guidance for current use in the field

• Planning and sampling
  • Define the question (acute stress vs. chronic welfare) and choose matrix accordingly; schedule consistent times and control for season.
  • Minimize sampling stress; consider saliva or feces for less invasive collection when appropriate.
• Documentation and co-measures
  • Record behavior, environment, recent events, diet, and medications; collect repeated measures to establish individual baselines.
  • Pair biomarkers with behavioral assessments and physiological measures to improve validity.
• Analytical considerations
  • Select validated assays; adhere to storage and transport requirements; report units and methods transparently.

Research gaps and future directions

• Validation studies linking biomarkers to well-defined emotional states in ecologically valid settings.
• Longitudinal and within-subject designs to establish reliable baselines and trajectories.
• Multi-biomarker panels integrated with behavior and physiology for improved specificity and sensitivity.
• Standardized reporting guidelines and collaborative datasets to enable robust reference intervals and benchmarking.

Conclusions and take-home messages

• ACTH, cortisol, and serotonin are most frequently studied, with oxytocin, melatonin, dopamine, and tryptophan showing emerging potential.
• Methodological diversity and context effects currently limit direct clinical translation and cross-study comparability.
• Consensus on emotional state definitions and standardized protocols for sampling, analysis, and reporting are essential for clinical adoption.
• The review provides a foundation to refine assays and protocols so these biomarkers can become practical tools for equine behavioral medicine and welfare assessment.