Establishment and evaluation of hematological and serum biochemical reference intervals in Chinese local donkey populations.

This study established standardized blood test reference intervals for Chinese local donkeys and examined how farm origin, age, and sex influence these values. The results show that farm origin is the main driver of variation, while age and sex differences are too small to require separate ranges.

What the study set out to answer

• Whether reliable, CLSI-compliant reference intervals (RIs) could be created for hematology and serum biochemistry specifically for Chinese local donkeys.
• How much farm origin, age, and sex contribute to variation in commonly used blood parameters, and whether separate RIs are needed for these subgroups.

Why this matters

• Using RIs derived from other species (for example, horses) or from donkey populations living under different management systems can misclassify healthy animals as abnormal, or miss true abnormalities.
• Population- and management-adapted RIs improve diagnostic accuracy, herd health surveillance, and conservation decisions for local donkey breeds.

Study design and populations

• Serum biochemistry: 1,163 samples from five geographically distinct farms spanning different conservation/production systems:
  • National conservation farms: Dong’e and Wudi
  • Provincial conservation farms: Yucheng and Zhongrun
  • Local farm: one in Xinjiang
• Hematology: 935 donkeys, all sampled from the Dong’e farm.
• Analytes: 20 serum biochemical parameters covering protein metabolism, liver function, energy and lipid metabolism, mineral balance, and renal function; a standard hematology panel was analyzed for the Dong’e cohort.
• Health status: Only healthy donkeys were included to represent a reference (apparently healthy) population.

Methods in brief

• Reference interval construction followed Clinical and Laboratory Standards Institute (CLSI) C28-A3 guidance.
• Non-parametric methods were used to derive RIs, an approach well-suited to skewed biological data and large samples.
• Partitioning decisions were evaluated using the Harris and Boyd method to determine whether separate RIs were warranted for age or sex subgroups.
• Variation attributable to farm origin was assessed across the five farms for serum biochemical parameters.

Key findings

• CLSI-compliant RIs were established for 20 serum biochemical parameters based on a large, multi-farm dataset.
• Farm origin was the dominant source of variation for most serum biochemical analytes, indicating that management system and population background substantially shape physiological profiles.
• Age and sex showed statistically detectable differences for some parameters; however, Harris and Boyd analysis indicated these differences were not large enough to justify separate RIs for either serum biochemistry or hematology.
• Juveniles displayed expected physiological patterns related to growth and immune maturation, yet these trends stayed within the thresholds where a single (non-partitioned) RI remains appropriate.
• Hematological RIs were generated from the Dong’e population; age- and sex-based partitioning was not supported for these measures either.
• The established RIs differ from those reported in horses and donkeys from other regions, reinforcing that species-related and population/management-specific RIs are not interchangeable.

How to interpret the partitioning results

• Harris and Boyd partitioning focuses on effect size (clinical relevance) rather than statistical significance alone.
• Even when age or sex differences reach statistical significance, if the between-group separation is small relative to overall variability, a single combined RI is recommended.
• In this study, that threshold was not met for either biochemical or hematological parameters, so unified RIs across age and sex are appropriate.

Implications for clinical practice and herd management

• Prefer RIs established on similar populations and management systems to the animals you are evaluating; using equine (horse) RIs or foreign donkey RIs can lead to misinterpretation.
• Where possible, consider the animal’s farm origin when interpreting biochemical results, given the pronounced between-farm differences.
• A single RI across ages and sexes is acceptable for routine interpretation, with clinical awareness that juveniles may sit at different points within the RI due to normal growth-associated physiology.
• These RIs provide benchmarks for:
  • Individual diagnostics and case workups
  • Herd-level health monitoring and screening
  • Conservation breeding and management decisions in Chinese donkey populations

Practical tips for using these RIs

• Match the patient to the reference population as closely as possible (Chinese local donkey, similar management conditions); if farm-specific or management-level RIs are available from this dataset, use them.
• Confirm pre-analytical consistency (sample handling, fasting status, time of day) to reduce non-biological variability.
• Interpret values near RI boundaries with clinical context; small deviations can be normal variation, while consistent trends over time are often more meaningful than a single data point.
• For juveniles, expect shifts within the RI related to growth and immune development; outside-RI values still warrant investigation.

Strengths

• Large sample size across multiple, geographically and managerially distinct farms for serum biochemistry.
• Adherence to CLSI C28-A3 with non-parametric estimation and formal partitioning assessment (Harris and Boyd), enhancing rigor and comparability.
• First large-scale, standardized RIs tailored to Chinese local donkey populations.

Limitations and cautions

• Hematology data came from a single farm (Dong’e), limiting assessment of between-farm effects on hematological parameters.
• Given farm origin strongly influences biochemistry, generalizing a single pooled RI across all management systems may reduce precision; users should consult how the authors report farm-level results and apply them accordingly.
• Findings reflect apparently healthy animals; disease-specific decision limits were not established.

Comparison with other equids

• These donkey-specific RIs differ from horse RIs, underscoring species differences in hematology and biochemistry.
• They also diverge from RIs reported for donkeys in other regions, highlighting the impact of local genetics, diet, climate, and management.

Future directions

• Expand hematology sampling across multiple farms to quantify farm-origin effects on hematological indices.
• Develop or report farm- or management-specific RIs where justified, especially for analytes with strong between-farm variation.
• Longitudinal tracking to characterize maturation curves in juveniles and seasonal dynamics.
• Harmonization and cross-validation across laboratories to facilitate broader adoption and inter-lab comparability.

Bottom line

• This study delivers the first large-scale, CLSI-compliant hematological and serum biochemical RIs for Chinese local donkeys.
• Farm origin substantially shapes biochemical profiles; age and sex do not necessitate separate RIs.
• Applying population- and management-adapted RIs will improve diagnostic accuracy, health monitoring, and conservation management in Chinese donkey herds.