Identification of diagnostic biomarkers of and immune cell infiltration analysis in bovine respiratory disease

Hui Sheng ^1* Junxing Zhang ² Xiaodi Shi ¹ Long Zhang ¹ Dawei Yao ¹ Peipei Zhang ¹ Yupeng Li ¹ Jinlong Zhang ¹ Xiaofei Guo ¹ Xiaosheng Zhang ¹

• ¹ Tianjin Academy of Agricultural Sciences, Tianjin, China
• ² Tianjin Agricultural University, Tianjin, Tianjin Municipality, China

Bovine respiratory disease (BRD) is one of the most common and costly diseases in the cattle industry, which affects lifetime productivity, the use of antibiotics and global food safety. This study identified DEGs associated with BRD by analyzing an expression dataset related to bovine BRD disease, and conducted a KEGG enrichment and GO annotation analysis on these DEGs. Meanwhile, the key modules related to BRD disease were screened by WGCNA, and the genes in the module were intersected with DEGs. Then, LASSO and RF were used to identify hub gene. Finally, GSEA was used to explore the potential mechanism of hub gene, and the diagnostic significance of hub gene was determined through ROC curve analysis and RT-qPCR detection. In addition, immune cell infiltration in BRD disease was evaluated using the CIBERSORT algorithm and the correlation between biomarkers and immune cell infiltration was analyzed. The results showed that a total of 1,097 DEGs were screened, and DEGs were mainly enriched in pathways inflammatory response、defense response、Complement and coagulation cascades and Antigen processing and presentation. WGCNA analysis determined that the cyan module had the highest correlation with BRD. A total of 833 overlapping genes were found by Venn analysis of the results of difference analysis and WGCNA analysis. After Lasso analysis and random forest analysis, five hub genes were identified as possible biomarkers of BRD. RT-qPCR testing and data set analysis showed that the expression levels of these five hub genes in nasal mucus and blood of BRD cattle were significantly higher than those of healthy cattle. GSEA analysis revealed that hub genes are mainly involved in Neutrophil extracellular trap formation, Complement and coagulation cascades, T cell receptor signaling pathway. The results of CIBERSORT algorithm showed that there was a significant difference in immune cells between the BRD group and the healthy group, and the diagnostic biomarkers were closely related to the immune cells. In conclusion, this study confirmed that ADGRG3, CDKN1A, CA4, GGT5 and SLC26A8 can be used as diagnostic markers of BRD disease, which is of great significance for finding new targets of immunotherapy and disease prevention and treatment.