Diagnosis of Bovine Respiratory Disease in feedlot cattle using blood 1H NMR metabolomics

C Blakebrough-Hall,M J D’Occhio,J Mcmeniman,A Dona,L A González

doi:10.1038/s41598-019-56809-w

C Blakebrough-Hall, M J D’Occhio + Show 3 more

Open Access

https://doi.org/10.1038/s41598-019-56809-w

Copy DOI

Abstract

Current diagnosis methods for Bovine Respiratory Disease (BRD) in feedlots have a low diagnostic accuracy. The current study aimed to search for blood biomarkers of BRD using 1H NMR metabolomics and determine their accuracy in diagnosing BRD. Animals with visual signs of BRD (n = 149) and visually healthy (non-BRD; n = 148) were sampled for blood metabolomics analysis. Lung lesions indicative of BRD were scored at slaughter. Non-targeted 1H NMR metabolomics was used to develop predictive algorithms for disease classification using classification and regression trees. In the absence of a gold standard for BRD diagnosis, six reference diagnosis methods were used to define an animal as BRD or non-BRD. Sensitivity (Se) and specificity (Sp) were used to estimate diagnostic accuracy (Acc). Blood metabolomics demonstrated a high accuracy at diagnosing BRD when using visual signs of BRD (Acc = 0.85), however was less accurate at diagnosing BRD using rectal temperature (Acc = 0.65), lung auscultation score (Acc = 0.61) and lung lesions at slaughter as reference diagnosis methods (Acc = 0.71). Phenylalanine, lactate, hydroxybutyrate, tyrosine, citrate and leucine were identified as metabolites of importance in classifying animals as BRD or non-BRD. The blood metabolome classified BRD and non-BRD animals with high accuracy and shows potential for use as a BRD diagnosis tool.

Highlights

Bovine respiratory disease (BRD) is a multifactorial disease of welfare and economic significance to the feedlot industry globally
Diagnosing Bovine Respiratory Disease (BRD) using the blood metabolome displayed high accuracy (0.77 to 0.93) in the training datasets; the accuracy decreased in the validation data sets (0.64 to 0.85) for all reference diagnosis methods
This decrease in accuracy between the training and validation datasets was more pronounced for the temperature diagnosis, lung auscultation diagnosis and lung lesion diagnosis

Summary

Introduction

Bovine respiratory disease (BRD) is a multifactorial disease of welfare and economic significance to the feedlot industry globally. Recent improvements include enhanced probe design[17], higher field magnets and reduction in equipment size[16], as well as improved methods of identification and quantification[18,19,20] These new developments have allowed for enhanced detection of lower concentration metabolites, increased speed of processing, simplification of the complexity of biofluids and more complete spectral assignments. A common limitation with studies on biomarker discovery for disease diagnosis in cattle are the small sample sizes of less than 50 animals, which do not allow the validation necessary to ensure reproducibility of the results[9,26,31]. Gaps in the literature were addressed by using a large sample size and training and validation datasets to ensure reproducibility of the models with future datasets

Objectives

Methods

Results

Conclusion