# Hair Metabolomic Profiling of Diseased Forest Musk Deer (Moschus berezovskii) Using Ultra-High-Performance Liquid Chromatography–Tandem Mass Spectrometry (UHPLC-MS/MS)

## TL;DR

This study uses deer hair to detect diseases in forest musk deer without invasive methods, showing potential for early diagnosis.

## Contribution

The study introduces non-invasive hair metabolomics for early disease detection in endangered forest musk deer.

## Key findings

- Hair metabolomics identified 2119 metabolites, with significant differences between healthy and diseased deer.
- Differential metabolites were linked to pathways related to cancer, parasitism, energy metabolism, and stress.
- Candidate biomarkers showed good sample classification with AUC values exceeding 0.7.

## Abstract

The population of captive forest musk deer (FMD, Moschus berezovskii) is threatened by various diseases, including hemorrhagic pneumonia, phytobezoar disease, and abscess disease, which significantly impact their health and growth. Due to the status of FMD as a protected endangered species, invasive sampling and live animal experiments are conducted under strict legal and regulatory supervision. It is crucial to shift some attention toward research utilizing non-invasive samples. We conducted a comparison of untargeted hair metabolomics data between healthy and diseased FMDs, identifying significantly altered metabolites and functional pathways in the diseased group. The observed differences were found to correlate with the corresponding diseases in the existing literature, and the candidate biomarkers demonstrated capacities for sample classification. In conclusion, non-invasive hair metabolomics presents significant potential for the early detection of FMD diseases and the development of diagnostic tools.

Hair, as a non-invasive biospecimen, retains metabolic deposits from sebaceous glands and capillaries, reflecting substances from the peripheral circulation, and provides valuable biochemical information linked to phenotypes, yet its application in animal disease research remains limited. This work applied ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) to compare the hair metabolomic characteristics of healthy forest musk deer (FMD, Moschus berezovskii) and those diagnosed with hemorrhagic pneumonia (HP), phytobezoar disease (PD), and abscess disease (AD). A total of 2119 metabolites were identified in the FMD hair samples, comprising 1084 metabolites in positive ion mode and 1035 metabolites in negative ion mode. Differential compounds analysis was conducted utilizing the orthogonal partial least squares–discriminant analysis (OPLS-DA) model. In comparison to the healthy control group, the HP group displayed 85 upregulated and 92 downregulated metabolites, the PD group presented 124 upregulated and 106 downregulated metabolites, and the AD group exhibited 63 upregulated and 62 downregulated metabolites. Functional annotation using the Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that the differential metabolites exhibited significant enrichment in pathways associated with cancer, parasitism, energy metabolism, and stress. Receiver operating characteristic (ROC) analysis revealed that both the individual and combined panels of differential metabolites exhibited area under the curve (AUC) values exceeding 0.7, demonstrating good sample discrimination capability. This research indicates that hair metabolomics can yield diverse biochemical insights and facilitate the development of non-invasive early diagnostic techniques for diseases in captive FMD.