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Li J, Mukiibi R, Jiminez J, Wang Z, Akanno EC, Timsit E, Plastow GS. Applying multi-omics data to study the genetic background of bovine respiratory disease infection in feedlot crossbred cattle. Front Genet 2022; 13:1046192. [PMID: 36579334 PMCID: PMC9790935 DOI: 10.3389/fgene.2022.1046192] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/28/2022] [Indexed: 12/15/2022] Open
Abstract
Bovine respiratory disease (BRD) is the most common and costly infectious disease affecting the wellbeing and productivity of beef cattle in North America. BRD is a complex disease whose development is dependent on environmental factors and host genetics. Due to the polymicrobial nature of BRD, our understanding of the genetic and molecular mechanisms underlying the disease is still limited. This knowledge would augment the development of better genetic/genomic selection strategies and more accurate diagnostic tools to reduce BRD prevalence. Therefore, this study aimed to utilize multi-omics data (genomics, transcriptomics, and metabolomics) analyses to study the genetic and molecular mechanisms of BRD infection. Blood samples of 143 cattle (80 BRD; 63 non-BRD animals) were collected for genotyping, RNA sequencing, and metabolite profiling. Firstly, a genome-wide association study (GWAS) was performed for BRD susceptibility using 207,038 SNPs. Two SNPs (Chr5:25858264 and BovineHD1800016801) were identified as associated (p-value <1 × 10-5) with BRD susceptibility. Secondly, differential gene expression between BRD and non-BRD animals was studied. At the significance threshold used (log2FC>2, logCPM>2, and FDR<0.01), 101 differentially expressed (DE) genes were identified. These DE genes significantly (p-value <0.05) enriched several immune responses related functions such as inflammatory response. Additionally, we performed expression quantitative trait loci (eQTL) analysis and identified 420 cis-eQTLs and 144 trans-eQTLs significantly (FDR <0.05) associated with the expression of DE genes. Interestingly, eQTL results indicated the most significant SNP (Chr5:25858264) identified via GWAS was a cis-eQTL for DE gene GPR84. This analysis also demonstrated that an important SNP (rs209419196) located in the promoter region of the DE gene BPI significantly influenced the expression of this gene. Finally, the abundance of 31 metabolites was significantly (FDR <0.05) different between BRD and non-BRD animals, and 17 of them showed correlations with multiple DE genes, which shed light on the interactions between immune response and metabolism. This study identified associations between genome, transcriptome, metabolome, and BRD phenotype of feedlot crossbred cattle. The findings may be useful for the development of genomic selection strategies for BRD susceptibility, and for the development of new diagnostic and therapeutic tools.
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Affiliation(s)
- Jiyuan Li
- Livestock Gentec, Department of Agriculture, Food & Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Robert Mukiibi
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Janelle Jiminez
- Livestock Gentec, Department of Agriculture, Food & Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Zhiquan Wang
- Livestock Gentec, Department of Agriculture, Food & Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Everestus C. Akanno
- Livestock Gentec, Department of Agriculture, Food & Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Edouard Timsit
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada
| | - Graham S. Plastow
- Livestock Gentec, Department of Agriculture, Food & Nutritional Science, University of Alberta, Edmonton, AB, Canada,*Correspondence: Graham S. Plastow,
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Nogo-A Is a Potential Prognostic Marker for Spinal Cord Injury. DISEASE MARKERS 2022; 2022:2141854. [PMID: 35571610 PMCID: PMC9095389 DOI: 10.1155/2022/2141854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/11/2022] [Accepted: 04/15/2022] [Indexed: 11/30/2022]
Abstract
Objective Spinal cord injury (SCI) has become prevalent worldwide in recent years, and its prognosis is poor and the pathological mechanism has not been fully elucidated. Nogo-A is one of the isoforms of the neurite outgrowth inhibitory protein reticulon 4. The purpose of this study was to determine whether Nogo-A could be used as a marker for predicting the prognosis of SCI. Methods We screened eligible SCI patients and controls based on inclusion and exclusion criteria. We also collected baseline clinical information and peripheral venous blood of the enrolled population. Participants' baseline serum Nogo-A levels were measured by enzyme-linked immunosorbent assay (ELISA). The American Spinal Injury Association (ASIA) scale was used to evaluate the prognosis of SCI patients after 3 months. Results Baseline clinical information (age; gender; smoking; drinking; SBP, systolic blood pressure; DBP, diastolic blood pressure; fasting blood glucose; WBC, white blood cells; CRP, C-reactive protein) of SCI patients and controls were not statistically significant academic differences (p > 0.05). The baseline serum Nogo-A levels of SCI patients and controls were 192.7 ± 13.9 ng/ml and 263.1 ± 22.4 ng/ml, respectively, and there was a statistically significant difference between the two groups (p < 0.05). We divided SCI patients into 4 groups according to their baseline serum Nogo-A quartile levels and analyzed their relationship with ASIA scores. The trend test results showed that with the increase of Nogo-A level, the ASIA sensation score and ASIA motor score were significantly decreased (p < 0.001). Multivariate regression analysis showed that serum Nogo-A levels remained a potential cause affecting the prognosis of SCI after adjusting for confounding factors in multiple models. Conclusions Serum Nogo-A levels were significantly elevated in SCI patients. Moreover, elevated Nogo-A levels often indicate poor prognosis and can be used as a marker to predict the prognosis of SCI.
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Zou Y, Xu Y, Chen X, Wu Y, Fu L, Lv Y. Research Progress on Leucine-Rich Alpha-2 Glycoprotein 1: A Review. Front Pharmacol 2022; 12:809225. [PMID: 35095520 PMCID: PMC8797156 DOI: 10.3389/fphar.2021.809225] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 12/13/2021] [Indexed: 12/18/2022] Open
Abstract
Leucine-rich alpha⁃2 glycoprotein 1 (LRG1) is an important member of the leucine-rich repetitive sequence protein family. LRG1 was mainly involved in normal physiological activities of the nervous system, such as synapse formation, synapse growth, the development of nerve processes, neurotransmitter transfer and release, and cell adhesion molecules or ligand-binding proteins. Also, LRG1 affected the development of respiratory diseases, hematological diseases, endocrine diseases, tumor diseases, eye diseases, cardiovascular diseases, rheumatic immune diseases, infectious diseases, etc. LRG1 was a newly discovered important upstream signaling molecule of transforming growth factor⁃β (TGF⁃β) that affected various pathological processes through the TGF⁃β signaling pathway. However, research on LRG1 and its involvement in the occurrence and development of diseases was still in its infancy and the current studies were mainly focused on proteomic detection and basic animal experimental reports. We could reasonably predict that LRG1 might act as a new direction and strategy for the treatment of many diseases.
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Affiliation(s)
- Yonghui Zou
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China.,School of Clinical Medicine, Nanchang University, Nanchang, China
| | - Yi Xu
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China.,School of Clinical Medicine, Nanchang University, Nanchang, China
| | - Xiaofeng Chen
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China.,School of Clinical Medicine, Nanchang University, Nanchang, China
| | - Yaoqi Wu
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China.,College of Pharmacy, Nanchang University, Nanchang, China
| | - Longsheng Fu
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yanni Lv
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
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