Technologies in Biomarker Discovery for Animal Diseases: Mechanisms, Classification, and Diagnostic Applications

TL;DR

This review explores how biomarkers and advanced technologies can improve early detection and management of animal diseases.

Contribution

The paper systematically classifies biomarkers and evaluates the role of emerging technologies in veterinary diagnostics.

Findings

High-throughput omics and biosensors are effective in identifying disease-specific molecular signatures.

Case studies show biomarkers are applicable in diagnosing canine melanoma and bovine respiratory disease.

Challenges include standardization and translating biomarker research into clinical practice.

Abstract

The early detection of animal diseases is challenging because clinical signs often appear late or are non-specific. This review explores how biomarkers, measurable molecular indicators, within an animal’s body can assist veterinarians in identifying diseases earlier, predicting their progression, and monitoring treatment response. It highlights the effectiveness of advanced laboratory techniques (including genomics, proteomics, and metabolomics), alongside novel biosensors and imaging technologies, in discovering and utilizing these critical disease markers. Successful applications have already been demonstrated in species such as dogs and cattle. While challenges remain, such as developing cross-species validation methods, integrating biomarker knowledge with these innovative technologies offers significant potential for improving animal health and farm management.

Animal diseases remain a major constraint to livestock productivity and public health, necessitating accurate, early diagnostic methods. This review examines the classification and mechanisms of diagnostic, prognostic, and predictive biomarkers in veterinary medicine and evaluates how advanced technologies enable their discovery. Mechanistically, biomarkers function as molecular indicators of disease presence, progression, or therapeutic response, and are essential in species where clinical signs often appear late or are non-specific. We detail the contribution of high-throughput omics platforms, genomics (NGS, RNA-Seq), proteomics (LC-MS/MS, DIGE), and metabolomics (NMR, LC-MS/MS) in identifying disease-specific molecular signatures. Emerging technologies, including CRISPR/Cas9, AI-enhanced imaging, aptamer-based biosensors, and microfluidic devices, show significant diagnostic potential. Case studies, including canine melanoma, bovine respiratory disease complex (BRDC), and congenital portosystemic shunts in dogs, illustrate the real-world applicability of biomarkers. Challenges such as a lack of standardization, species variability, and poor clinical translation are acknowledged. The review concludes that integrating biomarker mechanisms with advanced analytical technologies is key to advancing veterinary diagnostics and disease control.

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