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Noël A, Ashbrook DG, Xu F, Cormier SA, Lu L, O’Callaghan JP, Menon SK, Zhao W, Penn AL, Jones BC. Genomic Basis for Individual Differences in Susceptibility to the Neurotoxic Effects of Diesel Exhaust. Int J Mol Sci 2022; 23:12461. [PMID: 36293318 PMCID: PMC9603950 DOI: 10.3390/ijms232012461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 09/19/2022] [Accepted: 09/20/2022] [Indexed: 12/05/2022] Open
Abstract
Air pollution is a known environmental health hazard. A major source of air pollution includes diesel exhaust (DE). Initially, research on DE focused on respiratory morbidities; however, more recently, exposures to DE have been associated with neurological developmental disorders and neurodegeneration. In this study, we investigated the effects of sub-chronic inhalation exposure to DE on neuroinflammatory markers in two inbred mouse strains and both sexes, including whole transcriptome examination of the medial prefrontal cortex. We exposed aged male and female C57BL/6J (B6) and DBA/2J (D2) mice to DE, which was cooled and diluted with HEPA-filtered compressed air for 2 h per day, 5 days a week, for 4 weeks. Control animals were exposed to HEPA-filtered air on the same schedule as DE-exposed animals. The prefrontal cortex was harvested and analyzed for proinflammatory cytokine gene expression (Il1β, Il6, Tnfα) and transcriptome-wide response by RNA-seq. We observed differential cytokine gene expression between strains and sexes in the DE-exposed vs. control-exposed groups for Il1β, Tnfα, and Il6. For RNA-seq, we identified 150 differentially expressed genes between air and DE treatment related to natural killer cell-mediated cytotoxicity per Kyoto Encyclopedia of Genes and Genomes pathways. Overall, our data show differential strain-related effects of DE on neuroinflammation and neurotoxicity and demonstrate that B6 are more susceptible than D2 to gene expression changes due to DE exposures than D2. These results are important because B6 mice are often used as the default mouse model for DE studies and strain-related effects of DE neurotoxicity warrant expanded studies.
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Affiliation(s)
- Alexandra Noël
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70803, USA
| | - David G. Ashbrook
- Department of Genetics, Genomics, and Informatics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Fuyi Xu
- Department of Genetics, Genomics, and Informatics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
- School of Pharmacy, Binzhou Medical University, Yantai 264003, China
| | - Stephania A. Cormier
- Department of Biological Sciences, Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA 70808, USA
| | - Lu Lu
- Department of Genetics, Genomics, and Informatics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - James P. O’Callaghan
- Molecular Neurotoxicology Laboratory, Toxicology, and Molecular Biology Branch, Health Effects Laboratory Division, Centers for Disease Control and Prevention, NIOSH, Morgantown, WV 26508, USA
| | - Shyam K. Menon
- Department of Mechanical and Industrial Engineering, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Wenyuan Zhao
- Department of Genetics, Genomics, and Informatics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Arthur L. Penn
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Byron C. Jones
- Department of Genetics, Genomics, and Informatics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
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Wang X, Liang B, Li J, Pi X, Zhang P, Zhou X, Chen X, Zhou S, Yang R. Identification and characterization of four immune-related signatures in keloid. Front Immunol 2022; 13:942446. [PMID: 35967426 PMCID: PMC9365668 DOI: 10.3389/fimmu.2022.942446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 06/27/2022] [Indexed: 11/29/2022] Open
Abstract
A keloid is a fibroproliferative disorder of unknown etiopathogenesis that requires ill-defined treatment. Existing evidence indicates that the immune system plays an important role in the occurrence and development of keloid. However, there is still a lack of research on the immune-related signatures of keloid. Here we identified immune-related signatures in keloid and explored their pathological mechanisms. Transcriptomic datasets (GSE7890, GSE92566, and GSE44270) of keloid and normal skin tissues were obtained from the Gene Expression Omnibus database. The overlap of differentially expressed genes and immune-related genes was considered as differentially expressed immune-related genes (DEIGs). Functional analysis, expression, and distribution were applied to explore the function and characteristics of DEIGs, and the expression of these DEIGs in keloid and normal skin tissues was verified by immunohistochemistry. Finally, we conducted interactive network analysis and immune infiltration analysis to determine the therapeutic potential and immune correlation. We identified four DEIGs (LGR5, PTN, JAG1, and DKK1). In these datasets, only GSE7890 met the screening criteria. In the GSE7890 dataset, DKK1 and PTN were downregulated in keloid, whereas JAG1 and LGR5 were upregulated in keloid. In addition, we obtained the same conclusion through immunohistochemistry. Functional analysis indicated that these four DEIGs were mainly involved in stem cell, cell cycle, UV response, and therapy resistance. Through interactive network analysis, we found that these DEIGs were associated with drugs currently used to treat keloid, such as hydrocortisone, androstanolone, irinotecan, oxaliplatin, BHQ-880, and lecoleucovorin. Finally, many immune cells, including CD8+ T cells, resting memory CD4+ T cells, and M1 macrophages, were obtained by immune infiltration analysis. In conclusion, we identified four immune signaling molecules associated with keloid (LGR5, PTN, JAG1, and DKK1). These immune-related signaling molecules may be important modules in the pathogenesis of keloid. Additionally, we developed novel therapeutic targets for the treatment of this challenging disease.
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Affiliation(s)
- Xiaoxiang Wang
- Guangdong Medical University, Zhanjiang, China
- Department of Burn Surgery, The First People’s Hospital of Foshan, Foshan, China
| | - Bo Liang
- The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jiehua Li
- Department of Dermatology, The First People’s Hospital of Foshan, Foshan, China
| | - Xiaobing Pi
- Department of Dermatology, The First People’s Hospital of Foshan, Foshan, China
| | - Peng Zhang
- Neijiang Health Vocational College, Neijiang, China
| | - Xinzhu Zhou
- The Second School of Medicine, Wenzhou Medical University, Wenzhou, China
| | - Xiaodong Chen
- Department of Burn Surgery, The First People’s Hospital of Foshan, Foshan, China
- *Correspondence: Xiaodong Chen, ; Sitong Zhou, ; Ronghua Yang,
| | - Sitong Zhou
- Department of Dermatology, The First People’s Hospital of Foshan, Foshan, China
- *Correspondence: Xiaodong Chen, ; Sitong Zhou, ; Ronghua Yang,
| | - Ronghua Yang
- Guangdong Medical University, Zhanjiang, China
- Department of Burn and Plastic Surgery, Guangzhou First People’s Hospital, South China University of Technology, Guangzhou, China
- *Correspondence: Xiaodong Chen, ; Sitong Zhou, ; Ronghua Yang,
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Nurzati Y, Zhu Z, Xu H, Zhang Y. Identification and Validation of Novel Diagnostic Biomarkers for Keloid Based on GEO Database. Int J Gen Med 2022; 15:897-912. [PMID: 35115816 PMCID: PMC8801514 DOI: 10.2147/ijgm.s337951] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/15/2021] [Indexed: 12/30/2022] Open
Abstract
Introduction Keloid is a pathological scar type, which invades normal surrounding tissue without self-limiting to cause pain, itching, cosmetic disfigurement, etc. Knowledge of the molecular mechanisms underlying keloid remains unclear. This dilemma leads to no biomarker available for diagnosis. Thus, to seek accurate diagnosis, biomarkers are necessary for keloid diagnosis to help control its incidence. Methods Gene Expression Omnibus (GEO) database was used to select differentially expressed miRNAs (DE-miRNAs) in GSE113620. miRTarBase miRNA–target tools were used to predict the interactions between miRNAs and their target mRNAs. Target mRNAs that were differentially expressed in keloid were selected by analyzing differentially expressed genes (DEGs) in GSE44270 and GSE92566. PPI network analysis, gene enrichment analysis, cell-specific and tissue-specific expression analyses of DE-target mRNAs were conducted. RT-PCR analysis was conducted to validate our results. Results Three novel miRNAs (miR-30b-5p, miR-212-3p, miR-149-5p) and five target mRNAs (SIX1, CCNA2, CCNB1, FOXM1, RUNX2) were identified as potential biomarkers for keloid patients. Additionally, the potential functions of those miRNAs-mRNAs pathways were analyzed. Discussion These findings of keloid-related miRNAs, mRNAs, and miRNA–mRNAs regulatory networks may provide insights into the underlying pathogenesis of keloid and serve as potential biomarkers for keloid diagnosis.
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Affiliation(s)
- Yeletai Nurzati
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 201100, People’s Republic of China
| | - Zhu Zhu
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 201100, People’s Republic of China
| | - Heng Xu
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 201100, People’s Republic of China
- Correspondence: Heng Xu; Yixin Zhang Email ;
| | - Yixin Zhang
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 201100, People’s Republic of China
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Secondary data mining of GEO database for long non-coding RNA and Competing endogenous RNA network in keloid-prone individuals. Aging (Albany NY) 2020; 12:25076-25089. [PMID: 33203788 PMCID: PMC7803517 DOI: 10.18632/aging.104054] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 08/25/2020] [Indexed: 12/02/2022]
Abstract
This study aimed to identify long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) differentially expressed (DE) during keloid formation, predict DElncRNA-DEmiRNA-DEmRNA interactions, and construct a competing endogenous RNA (ceRNA) network through secondary data mining of keloid-related sequencing and microarray data in the open-source Gene Expression Omnibus (GEO) database. The GSE113621 dataset was downloaded from the GEO database, |log2FC|>1 and p<0.05 were set as screening criteria, genes expressed only in keloid-prone individuals were selected as research objects, and DEmRNAs, DElncRNAs, and DEmiRNAs before injury and 6 weeks after injury were screened. A Pearson correlation coefficient (PCC) of > 0.95 was selected as the index to predict the targeting relationships among lncRNAs, miRNAs, and mRNAs; and a network diagram was constructed using Cytoscape. The expression of 2356 lncRNAs was changed in the keloid-prone group—1306 were upregulated and 1050 were downregulated. Six lncRNAs, namely, 2 upregulated (DLEU2 and AP000317.2) and 4 downregulated (ADIRF-AS1, AC006333.2, AL137127.1 and LINC01725) lncRNAs, were expressed only in the keloid-prone group and were used to construct a ceRNA network. DLEU2 may regulate fibroblast proliferation, differentiation, and apoptosis through hsa-miR-30a-5p/hsa-miR-30b-5p. In-depth mining of GEO data indicated that lncRNAs and a ceRNA regulatory network participate in the wound healing process in keloid-prone individuals, possibly providing novel intervention targets and treatment options for keloid scars.
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