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Li HM, Tang F, Huang Q, Pan HF, Zhang TP. Investigation on Probable Association Between IL-13, IL-13RA1, and IL-13RA2 Genes Polymorphism and Pulmonary Tuberculosis. J Inflamm Res 2022; 15:4527-4536. [PMID: 35966004 PMCID: PMC9373994 DOI: 10.2147/jir.s374714] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 07/30/2022] [Indexed: 11/23/2022] Open
Abstract
Objective Our study aimed to explore the association of IL-13, IL-13RA1, and IL-13RA2 genes polymorphisms with PTB susceptibility and its clinical features. Methods Nine SNPs were genotyped by improved multiple ligase detection reaction (iMLDR) in 476 PTB patients and 473 controls. The association between these SNPs and PTB risk was analyzed using SPSS software and haplotype analysis was assessed using SHEsis software. Results The IL-13RA1 rs2495636 GA genotype frequency in PTB patients was significantly decreased, and IL-13RA2 rs5946039 A allele was related to the lower risk of PTB. In IL-13 gene, rs20541 variant was found to be associated with PTB risk under recessive mode. Moreover, IL-13RA1 rs141573089 C allele was significantly lower in PTB presenting with fever, drug resistance, and CC genotype was decreased in PTB presenting with leukopenia. IL-13RA1 rs2495636 polymorphism was associated with drug resistance, pulmonary infection, and IL-13RA2 rs3795175, rs638376 polymorphisms were related to drug resistance in PTB patients. Conclusion IL-13 rs20541, IL-13RA1 rs2495636, IL-13RA2 rs5946039 polymorphisms might be contributed to the genetic background of PTB in Chinese population.
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Affiliation(s)
- Hong-Miao Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, People's Republic of China
| | - Fei Tang
- Department of Interventional Pulmonology and Endoscopic Diagnosis and Treatment Center, Anhui Chest Hospital, Hefei, People's Republic of China
| | - Qian Huang
- Department of Public Health, Medical Department, Qinghai University, Xining, People's Republic of China
| | - Hai-Feng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, People's Republic of China
| | - Tian-Ping Zhang
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China
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Zhang TP, Li R, Li HM, Xiang N, Tan Z, Wang GS, Li XM. The Contribution of Genetic Variation and Aberrant Methylation of Aryl Hydrocarbon Receptor Signaling Pathway Genes to Rheumatoid Arthritis. Front Immunol 2022; 13:823863. [PMID: 35309329 PMCID: PMC8924038 DOI: 10.3389/fimmu.2022.823863] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 02/01/2022] [Indexed: 12/24/2022] Open
Abstract
The aryl hydrocarbon receptor (AHR) signaling pathway participates in immune regulation of multiple autoimmune diseases, including rheumatoid arthritis (RA). We conducted this study to investigate the association of AHR signaling pathway genes (AHR, ARNT, AHRR) single nucleotide polymorphisms (SNPs), as well as their methylation levels, with RA susceptibility. Nine SNPs (AHR gene rs2066853, rs2158041, rs2282885, ARNT gene rs10847, rs1889740, rs11204735, AHRR gene rs2292596, rs2672725, rs349583) were genotyped via improved multiple ligase detection reaction (iMLDR) in 479 RA patients and 496 healthy controls. We used the Illumina Hiseq platform to detect methylation levels of these genes in 122 RA patients and 123 healthy controls. A significant increase in rs11204735 C allele frequency was observed in RA patients when compared to controls. Further, rs11204735 polymorphism was associated with a decreased risk of RA under the dominant model. ARNT CCC haplotype frequency was significantly increased in RA patients in comparison to controls. In the AHRR gene, rs2672725 GG genotype, G allele frequencies were significantly related to an increased risk of RA and rs2292596, rs2672725 polymorphism were significantly associated with an increased risk of RA under the dominant model, recessive model, respectively. However, no significant association was identified between AHR gene polymorphism and RA susceptibility. The AHR methylation level in RA patients was significantly higher than the controls, while AHRR methylation level was abnormally reduced in RA patients. In addition, AHRR rs2672725 genotype distribution was significantly associated with the AHRR methylation level among RA patients. In summary, ARNT rs11204735, AHRR rs2292596, and rs2672725 polymorphisms were associated with RA susceptibility and altered AHR, AHRR methylation levels were related to the risk of RA.
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Affiliation(s)
- Tian-Ping Zhang
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Rui Li
- Department of Nosocomial Infection Management, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Hong-Miao Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, China
| | - Nan Xiang
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Zhen Tan
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Guo-Sheng Wang
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Xiao-Mei Li
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
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Wu G, Du X, Li Z, Du Y, Lv J, Li X, Xu Y, Liu S. The emerging role of long non-coding RNAs in schizophrenia. Front Psychiatry 2022; 13:995956. [PMID: 36226104 PMCID: PMC9548578 DOI: 10.3389/fpsyt.2022.995956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 09/06/2022] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia (SZ) is a severe psychiatric disorder which is contributed by both genetic and environmental factors. However, at present, its specific pathogenesis is still not very clear, and there is a lack of objective and reliable biomarkers. Accumulating evidence indicates that long non-coding RNAs (lncRNAs) are involved in the pathophysiology of several psychiatric disorders, including SZ, and hold promise as potential biomarkers and therapeutic targets for psychiatric disorders. In this review, we summarize and discuss the role of lncRNAs in the pathogenesis of SZ and their potential value as biomarkers and therapeutic targets.
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Affiliation(s)
- Guangxian Wu
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Physiology, School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, China
| | - Xinzhe Du
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Zexuan Li
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Yanhong Du
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Jinzhi Lv
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Physiology, School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, China
| | - Xinrong Li
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Yong Xu
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Mental Health, Shanxi Medical University, Taiyuan, China
| | - Sha Liu
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
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