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Malik S, Jawad Ul Hasnain M, Zaib G, Saadia H, Malik A, Zahid A. Comprehensive structural and functional analyses of RAD50 nsSNPs: from prediction to impact assessment. FRONTIERS IN BIOINFORMATICS 2025; 5:1535482. [PMID: 40206634 PMCID: PMC11979129 DOI: 10.3389/fbinf.2025.1535482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Accepted: 02/24/2025] [Indexed: 04/11/2025] Open
Abstract
Background The RAD50 gene on chromosome 5q3.11 plays an important role in the MRN (Mre11-Rad50-Nbs1) complex. This complex orchestrates cellular responses to the DNA double-strand breaks (DSBs) through several pathways for genome stability. This study aims to investigate the functional impact of non-synonymous single-nucleotide polymorphisms (nsSNPs) in RAD50 (a breast cancer-associated gene) and focuses on their consequences on protein structure and interaction within the MRN complex. Methods A total of 1,806 nsSNPs were retrieved and subjected to variant analysis using a set of computational tools and ConSurf. Pathogenicity and protein stability criteria were established based on specific tools. Highly conserved damaging nsSNPs were prioritized for the structural analysis. GOR-IV was used for secondary structure prediction, whereas AlphaFold, RoseTTAFold, and I-TASSER were used for protein structure prediction. The docking of RAD50-Mre11A complexes was performed using HADDOCK to assess the impact of nsSNPs on protein-protein interactions. Molecular dynamic simulation was performed to verify the role of mutants in molecular docking analysis. Results A subset of pathogenic and disease-associated nsSNPs in the RAD50 gene altered the protein stability and interactions with the Mre11A protein. Substantial alterations in the interacting profiles of mutants (A73P, V117F, L518P, L1092R, N1144S, and A1209T) suggest potential implications for DNA repair mechanisms and genome stability. Conclusion The study discloses the normative impact of RAD50 mutations on the pathophysiology of breast cancer. It can provide the basis to treat RAD50 mutation-deficient cells.
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Affiliation(s)
- Samina Malik
- University College of Medicine and Dentistry, The University of Lahore, IMBB, UOL, Lahore, Pakistan
| | - Mirza Jawad Ul Hasnain
- Department of Biological Sciences, Virtual University of Pakistan, Islamabad, Pakistan
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China
| | - Gul Zaib
- School of Pain and Regenerative Medicine, The University of Lahore, IMBB, UOL, Lahore, Pakistan
| | - Haleema Saadia
- School of Pain and Regenerative Medicine, The University of Lahore, IMBB, UOL, Lahore, Pakistan
| | - Arif Malik
- School of Pain and Regenerative Medicine, The University of Lahore, IMBB, UOL, Lahore, Pakistan
| | - Ayesha Zahid
- School of Pain and Regenerative Medicine, The University of Lahore, IMBB, UOL, Lahore, Pakistan
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Tian D, Li J, Lai X, Yang Q, Zhang Z, Deng F. Single nucleotide polymorphisms: Implications in the early diagnosis and targeted intervention of coronary microvascular dysfunction. Genes Dis 2025; 12:101249. [PMID: 39759113 PMCID: PMC11696767 DOI: 10.1016/j.gendis.2024.101249] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 01/12/2024] [Accepted: 01/21/2024] [Indexed: 01/07/2025] Open
Abstract
Coronary microvascular dysfunction (CMD) is a clinical syndrome of myocardial ischemia caused by structural and/or functional abnormalities of pre-coronary arterioles and arterioles. While genetics and other factors play a role in CMD etiology, the key pathogenic mechanism remains unclear. Currently, the diagnostic procedure for CMD is still cumbersome, and there is a lack of effective targeted interventions. Single nucleotide polymorphisms (SNPs) offer promise in addressing these issues. SNPs, reflecting common genetic variations, have garnered extensive investigation across multiple diseases. Several SNPs associated with CMD have been discovered, and some have the potential to be therapeutic targets. Nevertheless, studies on CMD-related SNPs are relatively nascent and limited in number. In this review, we summarize the previously reported CMD-associated SNPs, delineate their pathophysiological mechanisms, and predict potentially important CMD sites by analyzing the SNPs linked to diseases sharing similar pathogenetic mechanisms and risk factors, such as coronary artery disease. We aim to explore reliable genetic markers implicated in CMD risk and prognosis, thereby providing a novel approach for early diagnosis and gene-targeted interventions of CMD in subsequent studies.
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Affiliation(s)
- Dingyuan Tian
- Department of Pathophysiology, College of High Altitude Military Medicine, Army Medical University, Chongqing 400038, China
- Department of Cardiovascular Medicine, Southwest Hospital, Army Medical University, Chongqing 400038, China
| | - Jie Li
- Department of Cardiovascular Medicine, Southwest Hospital, Army Medical University, Chongqing 400038, China
| | - Xiaoyue Lai
- Department of Ultrasound, Xinqiao Hospital, Army Medical University, Chongqing 400037, China
| | - Qingyuan Yang
- Department of Cardiovascular Medicine, Southwest Hospital, Army Medical University, Chongqing 400038, China
| | - Zhihui Zhang
- Department of Cardiovascular Medicine, Southwest Hospital, Army Medical University, Chongqing 400038, China
- Center for Circadian Metabolism and Cardiovascular Disease, Southwest Hospital, Army Medical University, Chongqing 400038, China
- Key Laboratory of Geriatric Cardiovascular and Cerebrovascular Diseases, Ministry of Education, Chongqing 400038, China
| | - Fang Deng
- Department of Pathophysiology, College of High Altitude Military Medicine, Army Medical University, Chongqing 400038, China
- Key Laboratory of Extreme Environmental Medicine, Ministry of Education of China, Chongqing 400038, China
- Key Laboratory of High Altitude Medicine, PLA, Chongqing 400038, China
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3
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Qi M, Chen TT, Li L, Gao PP, Li N, Zhang SH, Wei W, Sun WY. Insight into the regulatory mechanism of β-arrestin2 and its emerging role in diseases. Br J Pharmacol 2024; 181:3019-3038. [PMID: 38961617 DOI: 10.1111/bph.16488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 05/11/2024] [Accepted: 05/27/2024] [Indexed: 07/05/2024] Open
Abstract
β-arrestin2, a member of the arrestin family, mediates the desensitization and internalization of most G protein-coupled receptors (GPCRs) and functions as a scaffold protein in signalling pathways. Previous studies have demonstrated that β-arrestin2 expression is dysregulated in malignant tumours, fibrotic diseases, cardiovascular diseases and metabolic diseases, suggesting its pathological roles. Transcription and post-transcriptional modifications can affect the expression of β-arrestin2. Furthermore, post-translational modifications, such as phosphorylation, ubiquitination, SUMOylation and S-nitrosylation affect the cellular localization of β-arrestin2 and its interaction with downstream signalling molecules, which further regulate the activity of β-arrestin2. This review summarizes the structure and function of β-arrestin2 and reveals the mechanisms involved in the regulation of β-arrestin2 at multiple levels. Additionally, recent studies on the role of β-arrestin2 in some major diseases and its therapeutic prospects have been discussed to provide a reference for the development of drugs targeting β-arrestin2.
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Affiliation(s)
- Meng Qi
- Institute of Clinical Pharmacology, Anhui Medical University, Key Laboratory of Anti-inflammatory and Immune Medicine, Ministry of Education, Anhui Collaborative Innovation Center of Anhui-inflammatory and Immune Medicine, Hefei, China
| | - Ting-Ting Chen
- Institute of Clinical Pharmacology, Anhui Medical University, Key Laboratory of Anti-inflammatory and Immune Medicine, Ministry of Education, Anhui Collaborative Innovation Center of Anhui-inflammatory and Immune Medicine, Hefei, China
| | - Ling Li
- Institute of Clinical Pharmacology, Anhui Medical University, Key Laboratory of Anti-inflammatory and Immune Medicine, Ministry of Education, Anhui Collaborative Innovation Center of Anhui-inflammatory and Immune Medicine, Hefei, China
| | - Ping-Ping Gao
- Institute of Clinical Pharmacology, Anhui Medical University, Key Laboratory of Anti-inflammatory and Immune Medicine, Ministry of Education, Anhui Collaborative Innovation Center of Anhui-inflammatory and Immune Medicine, Hefei, China
| | - Nan Li
- Institute of Clinical Pharmacology, Anhui Medical University, Key Laboratory of Anti-inflammatory and Immune Medicine, Ministry of Education, Anhui Collaborative Innovation Center of Anhui-inflammatory and Immune Medicine, Hefei, China
| | - Shi-Hao Zhang
- Institute of Clinical Pharmacology, Anhui Medical University, Key Laboratory of Anti-inflammatory and Immune Medicine, Ministry of Education, Anhui Collaborative Innovation Center of Anhui-inflammatory and Immune Medicine, Hefei, China
| | - Wei Wei
- Institute of Clinical Pharmacology, Anhui Medical University, Key Laboratory of Anti-inflammatory and Immune Medicine, Ministry of Education, Anhui Collaborative Innovation Center of Anhui-inflammatory and Immune Medicine, Hefei, China
| | - Wu-Yi Sun
- Institute of Clinical Pharmacology, Anhui Medical University, Key Laboratory of Anti-inflammatory and Immune Medicine, Ministry of Education, Anhui Collaborative Innovation Center of Anhui-inflammatory and Immune Medicine, Hefei, China
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Elgarhy FM, Borham A, Alziny N, AbdElaal KR, Shuaib M, Musaibah AS, Hussein MA, Abdelnaser A. From Drug Discovery to Drug Approval: A Comprehensive Review of the Pharmacogenomics Status Quo with a Special Focus on Egypt. Pharmaceuticals (Basel) 2024; 17:881. [PMID: 39065732 PMCID: PMC11279872 DOI: 10.3390/ph17070881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 06/19/2024] [Accepted: 06/29/2024] [Indexed: 07/28/2024] Open
Abstract
Pharmacogenomics (PGx) is the hope for the full optimization of drug therapy while minimizing the accompanying adverse drug events that cost billions of dollars annually. Since years before the century, it has been known that inter-individual variations contribute to differences in specific drug responses. It is the bridge to what is well-known today as "personalized medicine". Addressing the drug's pharmacokinetics and pharmacodynamics is one of the features of this science, owing to patient characteristics that vary on so many occasions. Mainly in the liver parenchymal cells, intricate interactions between the drug molecules and enzymes family of so-called "Cytochrome P450" occur which hugely affects how the body will react to the drug in terms of metabolism, efficacy, and safety. Single nucleotide polymorphisms, once validated for a transparent and credible clinical utility, can be used to guide and ensure the succession of the pharmacotherapy plan. Novel tools of pharmacoeconomics science are utilized extensively to assess cost-effective pharmacogenes preceding the translation to the bedside. Drug development and discovery incorporate a drug-gene perspective and save more resources. Regulations and laws shaping the clinical PGx practice can be misconceived; however, these pre-/post approval processes ensure the product's safety and efficacy. National and international regulatory agencies seek guidance on maintaining conduct in PGx practice. In this patient-centric era, social and legal considerations manifest in a way that makes them unavoidable, involving patients and other stakeholders in a deliberate journey toward utmost patient well-being. In this comprehensive review, we contemporarily addressed the scientific leaps in PGx, along with various challenges that face the proper implementation of personalized medicine in Egypt. These informative insights were drawn to serve what the Egyptian population, in particular, would benefit from in terms of knowledge and know-how while maintaining the latest global trends. Moreover, this review is the first to discuss various modalities and challenges faced in Egypt regarding PGx, which we believe could be used as a pilot piece of literature for future studies locally, regionally, and internationally.
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Affiliation(s)
- Fadya M. Elgarhy
- Institute of Global Health and Human Ecology, School of Sciences and Engineering, The American University, Cairo 11835, Egypt; (F.M.E.); (A.B.); (N.A.); (M.S.); (A.S.M.); (M.A.H.)
- Egypt Center for Research and Regenerative Medicine (ECRRM), Cairo 4435121, Egypt
| | - Abdallah Borham
- Institute of Global Health and Human Ecology, School of Sciences and Engineering, The American University, Cairo 11835, Egypt; (F.M.E.); (A.B.); (N.A.); (M.S.); (A.S.M.); (M.A.H.)
| | - Noha Alziny
- Institute of Global Health and Human Ecology, School of Sciences and Engineering, The American University, Cairo 11835, Egypt; (F.M.E.); (A.B.); (N.A.); (M.S.); (A.S.M.); (M.A.H.)
| | - Khlood R. AbdElaal
- Graduate Program of Biotechnology, School of Sciences and Engineering, The American University, Cairo 11835, Egypt;
| | - Mahmoud Shuaib
- Institute of Global Health and Human Ecology, School of Sciences and Engineering, The American University, Cairo 11835, Egypt; (F.M.E.); (A.B.); (N.A.); (M.S.); (A.S.M.); (M.A.H.)
| | - Abobaker Salem Musaibah
- Institute of Global Health and Human Ecology, School of Sciences and Engineering, The American University, Cairo 11835, Egypt; (F.M.E.); (A.B.); (N.A.); (M.S.); (A.S.M.); (M.A.H.)
| | - Mohamed Ali Hussein
- Institute of Global Health and Human Ecology, School of Sciences and Engineering, The American University, Cairo 11835, Egypt; (F.M.E.); (A.B.); (N.A.); (M.S.); (A.S.M.); (M.A.H.)
| | - Anwar Abdelnaser
- Institute of Global Health and Human Ecology, School of Sciences and Engineering, The American University, Cairo 11835, Egypt; (F.M.E.); (A.B.); (N.A.); (M.S.); (A.S.M.); (M.A.H.)
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Huang Y, Zhou W, Liu S, Zeng D, Zhou W. Association between polymorphisms and atopic dermatitis susceptibility: A systematic review and meta-analysis. Gene 2024; 913:148397. [PMID: 38513928 DOI: 10.1016/j.gene.2024.148397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 03/13/2024] [Accepted: 03/18/2024] [Indexed: 03/23/2024]
Abstract
AIM Atopic dermatitis (AD) is a chronic pruritic inflammatory skin disease that is closely linked to genetic factors. Previous studies have revealed numerous single nucleotide polymorphisms (SNPs) that been related to susceptibility to AD; however, the results are conflicting. Therefore, a meta-analysis was conducted to assess the associations of these polymorphisms and AD risk. MATERIAL AND METHODS PubMed, Web of Science, Embase, Cochrane Library, and China National Knowledge Infrastructure databases were retrieved to identify eligible studies, with selected polymorphisms being reported in a minimum of three separate studies. The Newcastle-Ottawa Scale (NOS) was used to evaluate study quality. Review Manager 5.3 and STATA 14.0 were used to perform the meta-analysis. RESULTS After screening, 64 studies involving 13 genes (24 SNPs) were selected for inclusion in the meta-analysis. Nine SNPs were positively correlated with AD susceptibility [filaggrin (FLG) R501X, FLG 2282del4, chromosome 11q13.5 rs7927894, interleukin (IL)-17A rs2275913, IL-18 -137 G/C, Toll-like receptor 2 (TLR2) rs5743708, TLR2 A-16934 T, serine protease inhibitor Kazal type-5 (SPINK5) Asn368Ser, interferon-γ (IFN-γ) T874A] and one was negatively associated with AD susceptibility (IL-4 -1098 T/G). The 14 remaining SNPs were not significantly associated with AD susceptibility. CONCLUSIONS Nine SNPs that may be risk factors and one SNP that may be a protective factor for AD were identified, providing a reference for AD prediction, prevention, and therapy.
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Affiliation(s)
- Yunxia Huang
- Department of Dermatology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China; Department of Allergy, Chongqing General Hospital, Chongqing 400014, China
| | - Wei Zhou
- Department of Allergy, Chongqing General Hospital, Chongqing 400014, China
| | - Shunan Liu
- Department of Dermatology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China; Department of Allergy, Chongqing General Hospital, Chongqing 400014, China
| | - Dan Zeng
- Department of Allergy, Chongqing General Hospital, Chongqing 400014, China
| | - Weikang Zhou
- Department of Dermatology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China; Department of Allergy, Chongqing General Hospital, Chongqing 400014, China.
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Farajzadeh-Dehkordi M, Mafakher L, Harifi A, Samiee-Rad F, Rahmani B. Computational analysis of the functional and structural impact of the most deleterious missense mutations in the human Protein C. PLoS One 2023; 18:e0294417. [PMID: 38015884 PMCID: PMC10683990 DOI: 10.1371/journal.pone.0294417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 11/01/2023] [Indexed: 11/30/2023] Open
Abstract
Protein C (PC) is a vitamin K-dependent factor that plays a crucial role in controlling anticoagulant processes and acts as a cytoprotective agent to promote cell survival. Several mutations in human PC are associated with decreased protein production or altered protein structure, resulting in PC deficiency. In this study, we conducted a comprehensive analysis of nonsynonymous single nucleotide polymorphisms in human PC to prioritize and confirm the most high-risk mutations predicted to cause disease. Of the 340 missense mutations obtained from the NCBI database, only 26 were classified as high-risk mutations using various bioinformatic tools. Among these, we identified that 12 mutations reduced the stability of protein, and thereby had the greatest potential to disturb protein structure and function. Molecular dynamics simulations revealed moderate alterations in the structural stability, flexibility, and secondary structural organization of the serine protease domain of human PC for five missense mutations (L305R, W342C, G403R, V420E, and W444C) when compared to the native structure that could maybe influence its interaction with other molecules. Protein-protein interaction analyses demonstrated that the occurrence of these five mutations can affect the regular interaction between PC and activated factor V. Therefore, our findings assume that these mutants can be used in the identification and development of therapeutics for diseases associated with PC dysfunction, although assessment the effect of these mutations need to be proofed in in-vitro.
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Affiliation(s)
- Mahvash Farajzadeh-Dehkordi
- Cellular and Molecular Research Center, Institute for Prevention of Non-Communicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran
- Department of Molecular Medicine, Qazvin University of Medical Sciences, Qazvin, Iran
| | - Ladan Mafakher
- Thalassemia & Hemoglobinopathy Research Center, Health Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Abbas Harifi
- Department of Electrical and Computer Engineering, University of Hormozgan, Bandar Abbas, Iran
| | - Fatemeh Samiee-Rad
- Cellular and Molecular Research Center, Institute for Prevention of Non-Communicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran
- Department of Pathobiology, Faculty of Medical School, Qazvin University of Medical Sciences, Qazvin, Iran
| | - Babak Rahmani
- Cellular and Molecular Research Center, Institute for Prevention of Non-Communicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran
- Department of Molecular Medicine, Qazvin University of Medical Sciences, Qazvin, Iran
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7
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Liang Y, Chen F, Wang K, Lai L. Base editors: development and applications in biomedicine. Front Med 2023; 17:359-387. [PMID: 37434066 DOI: 10.1007/s11684-023-1013-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 05/19/2023] [Indexed: 07/13/2023]
Abstract
Base editor (BE) is a gene-editing tool developed by combining the CRISPR/Cas system with an individual deaminase, enabling precise single-base substitution in DNA or RNA without generating a DNA double-strand break (DSB) or requiring donor DNA templates in living cells. Base editors offer more precise and secure genome-editing effects than other conventional artificial nuclease systems, such as CRISPR/Cas9, as the DSB induced by Cas9 will cause severe damage to the genome. Thus, base editors have important applications in the field of biomedicine, including gene function investigation, directed protein evolution, genetic lineage tracing, disease modeling, and gene therapy. Since the development of the two main base editors, cytosine base editors (CBEs) and adenine base editors (ABEs), scientists have developed more than 100 optimized base editors with improved editing efficiency, precision, specificity, targeting scope, and capacity to be delivered in vivo, greatly enhancing their application potential in biomedicine. Here, we review the recent development of base editors, summarize their applications in the biomedical field, and discuss future perspectives and challenges for therapeutic applications.
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Affiliation(s)
- Yanhui Liang
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, 572000, China
| | - Fangbing Chen
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, 572000, China
- Guangdong Provincial Key Laboratory of Large Animal Models for Biomedicine, Wuyi University, Jiangmen, 529020, China
| | - Kepin Wang
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, 572000, China
- Guangdong Provincial Key Laboratory of Large Animal Models for Biomedicine, Wuyi University, Jiangmen, 529020, China
| | - Liangxue Lai
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China.
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China.
- Sanya Institute of Swine Resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya, 572000, China.
- Guangdong Provincial Key Laboratory of Large Animal Models for Biomedicine, Wuyi University, Jiangmen, 529020, China.
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Fang C, Ouyang W, Zeng Y, Pei Q, Xia Y, Luo S, Chen M. CYP2A6 and GABRA2 Gene Polymorphisms are Associated With Dexmedetomidine Drug Response. Front Pharmacol 2022; 13:943200. [PMID: 35873555 PMCID: PMC9301121 DOI: 10.3389/fphar.2022.943200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 06/20/2022] [Indexed: 11/20/2022] Open
Abstract
Background: Dexmedetomidine is a commonly used clinical sedative; however, the drug response varies among individuals. Thus, the purpose of this study was to explore the association between dexmedetomidine response and gene polymorphisms related to drug-metabolizing enzymes and drug response (CYP2A6, UGT2B10, UGT1A4, ADRA2A, ADRA2B, ADRA2C, GABRA1, GABRB2, and GLRA1). Methods: This study was a prospective cohort study. A total of 194 female patients aged 18–60 years, American Society of Anesthesiologists (ASA) score I-II, who underwent laparoscopy at the Third Xiangya Hospital of Central South University, were included. The sedative effect was assessed every 2 min using the Ramsay score, and the patient’s heart rate decrease within 20 min was recorded. Peripheral blood was collected from each participant to identify genetic variants in the candidate genes of metabolic and drug effects using the Sequenom MassARRAY® platform. Furthermore, additional peripheral blood samples were collected from the first 99 participants at multiple time points after dexmedetomidine infusion to perform dexmedetomidine pharmacokinetic analysis by Phoenix® WinNonlin 7.0 software. Results: Carriers of the minor allele (C) of CYP2A6 rs28399433 had lower metabolic enzyme efficiency and higher plasma concentrations of dexmedetomidine. In addition, the participants were divided into dexmedetomidine sensitive or dexmedetomidine tolerant groups based on whether they had a Ramsay score of at least four within 20 min, and CYP2A6 rs28399433 was identified to have a significant influence on the dexmedetomidine sedation sensitivity by logistic regression with Plink software [p = 0.003, OR (95% CI): 0.27 (0.11–0.65)]. C allele carriers were more sensitive to the sedative effects of dexmedetomidine than A allele carriers. GABRA2 rs279847 polymorphism was significantly associated with the degree of the heart rate decrease. In particular, individuals with the GG genotype had a 4-fold higher risk of heart rate abnormality than carriers of the T allele (OR = 4.32, 95% CI: 1.96–9.50, p = 0.00027). Conclusion:CYP2A6 rs28399433 polymorphism affects the metabolic rate of dexmedetomidine and is associated with susceptibility to the sedative effects of dexmedetomidine; GABRA2 rs279847 polymorphism is significantly associated with the degree of the heart rate decrease.
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Affiliation(s)
- Chao Fang
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, China
- Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Wen Ouyang
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, China
| | - Youjie Zeng
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, China
| | - Qi Pei
- Department of Pharmacy, Third Xiangya Hospital, Central South University, Changsha, China
| | - Yuhao Xia
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, China
| | - Siwan Luo
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, China
| | - Minghua Chen
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Minghua Chen,
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Liang Y, Xie J, Zhang Q, Wang X, Gou S, Lin L, Chen T, Ge W, Zhuang Z, Lian M, Chen F, Li N, Ouyang Z, Lai C, Liu X, Li L, Ye Y, Wu H, Wang K, Lai L. AGBE: a dual deaminase-mediated base editor by fusing CGBE with ABE for creating a saturated mutant population with multiple editing patterns. Nucleic Acids Res 2022; 50:5384-5399. [PMID: 35544322 PMCID: PMC9122597 DOI: 10.1093/nar/gkac353] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 04/13/2022] [Accepted: 04/26/2022] [Indexed: 12/26/2022] Open
Abstract
Establishing saturated mutagenesis in a specific gene through gene editing is an efficient approach for identifying the relationships between mutations and the corresponding phenotypes. CRISPR/Cas9-based sgRNA library screening often creates indel mutations with multiple nucleotides. Single base editors and dual deaminase-mediated base editors can achieve only one and two types of base substitutions, respectively. A new glycosylase base editor (CGBE) system, in which the uracil glycosylase inhibitor (UGI) is replaced with uracil-DNA glycosylase (UNG), was recently reported to efficiently induce multiple base conversions, including C-to-G, C-to-T and C-to-A. In this study, we fused a CGBE with ABE to develop a new type of dual deaminase-mediated base editing system, the AGBE system, that can simultaneously introduce 4 types of base conversions (C-to-G, C-to-T, C-to-A and A-to-G) as well as indels with a single sgRNA in mammalian cells. AGBEs can be used to establish saturated mutant populations for verification of the functions and consequences of multiple gene mutation patterns, including single-nucleotide variants (SNVs) and indels, through high-throughput screening.
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Affiliation(s)
- Yanhui Liang
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingke Xie
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Guangdong Provincial Key Laboratory of Large Animal models for Biomedicine, Wuyi University, Jiangmen 529020, China
| | - Quanjun Zhang
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou 510005, China
| | - Xiaomin Wang
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Shixue Gou
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China
| | - Lihui Lin
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Tao Chen
- Guangdong Provincial Key Laboratory of Large Animal models for Biomedicine, Wuyi University, Jiangmen 529020, China
| | - Weikai Ge
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Guangdong Provincial Key Laboratory of Large Animal models for Biomedicine, Wuyi University, Jiangmen 529020, China
| | - Zhenpeng Zhuang
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Meng Lian
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China
| | - Fangbing Chen
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Guangdong Provincial Key Laboratory of Large Animal models for Biomedicine, Wuyi University, Jiangmen 529020, China
| | - Nan Li
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Guangdong Provincial Key Laboratory of Large Animal models for Biomedicine, Wuyi University, Jiangmen 529020, China
| | - Zhen Ouyang
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou 510005, China.,Guangdong Provincial Key Laboratory of Large Animal models for Biomedicine, Wuyi University, Jiangmen 529020, China
| | - Chengdan Lai
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou 510005, China.,Guangdong Provincial Key Laboratory of Large Animal models for Biomedicine, Wuyi University, Jiangmen 529020, China
| | - Xiaoyi Liu
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lei Li
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yinghua Ye
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou 510005, China
| | - Han Wu
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou 510005, China
| | - Kepin Wang
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou 510005, China.,Guangdong Provincial Key Laboratory of Large Animal models for Biomedicine, Wuyi University, Jiangmen 529020, China
| | - Liangxue Lai
- China-New Zealand Joint Laboratory on Biomedicine and Health, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou 510530, China.,Sanya institute of Swine resource, Hainan Provincial Research Centre of Laboratory Animals, Sanya 572000, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou 510005, China.,Guangdong Provincial Key Laboratory of Large Animal models for Biomedicine, Wuyi University, Jiangmen 529020, China
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Akther J, Das A, Rahman MA, Saha SK, Hosen MI, Ebihara A, Nakagawa T, Suzuki F, Nabi AHMN. Non-coding Single Nucleotide Variants of Renin and the (Pro)renin Receptor are Associated with Polygenic Diseases in a Bangladeshi Population. Biochem Genet 2021; 59:1116-1145. [PMID: 33677630 DOI: 10.1007/s10528-021-10049-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Accepted: 02/10/2021] [Indexed: 02/06/2023]
Abstract
Non-coding variants or single-nucleotide polymorphisms (SNPs) play pivotal roles in orchestrating pathogeneses of polygenic diseases, including hypertension (HTN) and diabetes. Renin-angiotensin system (RAS) components-renin and (pro)renin receptor [(P)RR]-maintain homeostasis of body fluids. Genetic variants of RAS components are associated with risk of HTN and type 2 diabetes (T2D) in different ethnic groups. We identified associations of SNPs within the renin and (P)RR genes with HTN, T2D, and T2D-associated hypertension in 911 unrelated Bangladeshi individuals. Five non-coding SNPs were involved in modulating regulatory elements in diverse cell types when tagged with other SNPs. rs61827960 was not associated with any disease; rs3730102 was associated with increased risk of HTN and T2D while under dominant model, it showed protective role against T2D-associated HTN. SNP rs11571079 was associated with increased risk of HTN and T2D-associated HTN and decreased risk of T2D, exerting a protective effect. Renin haplotypes GCA and GTG were related to increased risk of T2D and T2D-associated HTN, respectively. Heterogeneous linkage of genotypic and allelic frequencies of rs2968915 and rs3112298 of (P)RR was observed. The (P)RR haplotype GA was associated with increased risk of HTN and significantly decreased risk of T2D. These findings highlight important roles of non-coding variants of renin and (P)RR genes in the etiology of several polygenic diseases.
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Affiliation(s)
- Jobaida Akther
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, 1000, Bangladesh
| | - Ashish Das
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, 1000, Bangladesh
| | - Md Arifur Rahman
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, 1000, Bangladesh
- National Institute of Cardiovascular Diseases, Sher-e-Bangla Nagar, Dhaka, 1207, Bangladesh
| | - Sajoy Kanti Saha
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, 1000, Bangladesh
| | - Md Ismail Hosen
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, 1000, Bangladesh
| | - Akio Ebihara
- Laboratory of Applied Biochemistry, Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu, 501-1193, Japan
- United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu, 501-1193, Japan
| | - Tsutomu Nakagawa
- Laboratory of Applied Biochemistry, Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu, 501-1193, Japan
- United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu, 501-1193, Japan
| | - Fumiaki Suzuki
- Laboratory of Applied Biochemistry, Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu, 501-1193, Japan
| | - A H M Nurun Nabi
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, 1000, Bangladesh.
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11
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Xie J, Huang X, Wang X, Gou S, Liang Y, Chen F, Li N, Ouyang Z, Zhang Q, Ge W, Jin Q, Shi H, Zhuang Z, Zhao X, Lian M, Wang J, Ye Y, Quan L, Wu H, Wang K, Lai L. ACBE, a new base editor for simultaneous C-to-T and A-to-G substitutions in mammalian systems. BMC Biol 2020; 18:131. [PMID: 32967664 PMCID: PMC7510086 DOI: 10.1186/s12915-020-00866-5] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 09/09/2020] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Many favorable traits of crops and livestock and human genetic diseases arise from multiple single nucleotide polymorphisms or multiple point mutations with heterogeneous base substitutions at the same locus. Current cytosine or adenine base editors can only accomplish C-to-T (G-to-A) or A-to-G (T-to-C) substitutions in the windows of target genomic sites of organisms; therefore, there is a need to develop base editors that can simultaneously achieve C-to-T and A-to-G substitutions at the targeting site. RESULTS In this study, a novel fusion adenine and cytosine base editor (ACBE) was generated by fusing a heterodimer of TadA (ecTadAWT/*) and an activation-induced cytidine deaminase (AID) to the N- and C-terminals of Cas9 nickase (nCas9), respectively. ACBE could simultaneously induce C-to-T and A-to-G base editing at the same target site, which were verified in HEK293-EGFP reporter cell line and 45 endogenous gene loci of HEK293 cells. Moreover, the ACBE could accomplish simultaneous point mutations of C-to-T and A-to-G in primary somatic cells (mouse embryonic fibroblasts and porcine fetal fibroblasts) in an applicable efficiency. Furthermore, the spacer length of sgRNA and the length of linker could influence the dual base editing activity, which provided a direction to optimize the ACBE system. CONCLUSION The newly developed ACBE would expand base editor toolkits and should promote the generation of animals and the gene therapy of genetic diseases with heterogeneous point mutations.
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Affiliation(s)
- Jingke Xie
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xingyun Huang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xia Wang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory, GRMH-GDL), Guangzhou, 510005, China
| | - Shixue Gou
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yanhui Liang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Fangbing Chen
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Nan Li
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhen Ouyang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory, GRMH-GDL), Guangzhou, 510005, China
| | - Quanjun Zhang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory, GRMH-GDL), Guangzhou, 510005, China
| | - Weikai Ge
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qin Jin
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hui Shi
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhenpeng Zhuang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaozhu Zhao
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Meng Lian
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Institute of Physical Science and Information Technology, Anhui University, Hefei, 230601, China
| | - Jiaowei Wang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yinghua Ye
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory, GRMH-GDL), Guangzhou, 510005, China
| | - Longquan Quan
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory, GRMH-GDL), Guangzhou, 510005, China
| | - Han Wu
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory, GRMH-GDL), Guangzhou, 510005, China
| | - Kepin Wang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China.
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China.
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory, GRMH-GDL), Guangzhou, 510005, China.
| | - Liangxue Lai
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China.
- Research Unit of Generation of Large Animal Disease Models, Chinese Academy of Medical Sciences (2019RU015), Guangzhou, 510530, China.
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory, GRMH-GDL), Guangzhou, 510005, China.
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13
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Chang W, Liu W, Shen H, Chen S, Liao P, Liu Y. Molecular AND logic gate for multiple single-nucleotide mutations detection based on CRISPR/Cas9n system-trigged signal amplification. Anal Chim Acta 2020; 1112:46-53. [DOI: 10.1016/j.aca.2020.03.058] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 03/27/2020] [Accepted: 03/28/2020] [Indexed: 12/26/2022]
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14
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Mustafa MI, Murshed NS, Abdelmoneim AH, Abdelmageed MI, Elfadol NM, Makhawi AM. Extensive In Silico Analysis of ATL1 Gene : Discovered Five Mutations That May Cause Hereditary Spastic Paraplegia Type 3A. SCIENTIFICA 2020; 2020:8329286. [PMID: 32322428 PMCID: PMC7140133 DOI: 10.1155/2020/8329286] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 01/31/2020] [Accepted: 02/21/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Hereditary spastic paraplegia type 3A (SPG3A) is a neurodegenerative disease inherited type of Hereditary spastic paraplegia (HSP). It is the second most frequent type of HSP which is characterized by progressive bilateral and mostly symmetric spasticity and weakness of the legs. SPG3A gene mutations and the phenotype-genotype correlations have not yet been recognized. The aim of this work was to categorize the most damaging SNPs in ATL1 gene and to predict their impact on the functional and structural levels by several computational analysis tools. METHODS The raw data of ATL1 gene were retrieved from dbSNP database and then run into numerous computational analysis tools. Additionally; we submitted the common six deleterious outcomes from the previous functional analysis tools to I-mutant 3.0 and MUPro, respectively, to investigate their effect on the structural level. The 3D structure of ATL1 was predicted by RaptorX and modeled using UCSF Chimera to compare the differences between the native and the mutant amino acids. RESULTS Five nsSNPs out of 249 were classified as the most deleterious (rs746927118, rs979765709, rs119476049, rs864622269, and rs1242753115). CONCLUSIONS In this study, the impact of nsSNPs in the ATL1 gene was investigated by various in silico tools that revealed five nsSNPs (V67F, T120I, R217Q, R495W, and G504E) are deleterious SNPs, which have a functional impact on ATL1 protein and, therefore, can be used as genomic biomarkers specifically before 4 years of age; also, it may play a key role in pharmacogenomics by evaluating drug response for this disabling disease.
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Affiliation(s)
| | - Naseem S. Murshed
- Department of Microbiology, International University of Africa, Khartoum, Sudan
| | | | | | - Nafisa M. Elfadol
- Department of Microbiology, National Ribat University, Khartoum, Sudan
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15
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Analysis of a large single institution cohort of related donors fails to detect a relation between SDF1/CXCR4 or VCAM/VLA4 genetic polymorphisms and the level of hematopoietic progenitor cell mobilization in response to G-CSF. PLoS One 2020; 15:e0228878. [PMID: 32134938 PMCID: PMC7058310 DOI: 10.1371/journal.pone.0228878] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 01/24/2020] [Indexed: 02/07/2023] Open
Abstract
We studied a cohort of 367 healthy related donors who volunteered to donate their hematopoietic stem cells for allogeneic transplantation. All donors were homogeneously cared for at a single institution, and received rhG-CSF as a mobilization treatment prior to undergoing apheresis. Peripheral blood CD34+ cell counts were used as the main surrogate marker for rhG-CSF induced mobilization. We searched whether inter-individual variations in known genetic polymorphisms located in genes whose products are functionally important for mobilization, could affect the extent of CD34+ mobilization, either individually or in combination. We found little or no influence of individual SNPs or haplotypes for the SDF1, CXCR4, VCAM and VLA4 genes, whether using CD34+ cell counts as a continuous or a categorical variable. Simple clinical characteristics describing donors such as body mass index, age and possibly sex are more potent predictors of stem cell mobilization. The size of our cohort remains relatively small for genetic analyses, however compares favorably with cohorts analyzed in previously published reports suggesting associations of genetic traits to response to rhG-CSF; notwithstanding this limitation, our data do not support the use of genetic analyses when the choice exists of several potential donors for a given patient.
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16
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Zhang H, Li X, Pang J, Zhao X, Cao S, Wang X, Wang X, Li H. Predicting SSRI-Resistance: Clinical Features and tagSNPs Prediction Models Based on Support Vector Machine. Front Psychiatry 2020; 11:493. [PMID: 32581871 PMCID: PMC7283444 DOI: 10.3389/fpsyt.2020.00493] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Accepted: 05/15/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND A large proportion of major depressive patients will experience recurring episodes. Many patients still do not response to available antidepressants. In order to meaningfully predict who will not respond to which antidepressant, it may be necessary to combine multiple biomarkers and clinical variables. METHODS Eight hundred fifty-seven patients with recurrent major depressive disorder who were followed up 3-10 years involved 32 variables including socio-demographic, clinical features, and SSRIs treatment features when they received the first treatment. Also, 34 tagSNPs related to 5-HT signaling pathway, were detected by using mass spectrometry analysis. The training samples which had 12 clinical variables and four tagSNPs with statistical differences were learned repeatedly to establish prediction models based on support vector machine (SVM). RESULTS Twelve clinical features (psychomotor retardation, psychotic symptoms, suicidality, weight loss, SSRIs average dose, first-course treatment response, sleep disturbance, residual symptoms, personality, onset age, frequency of episode, and duration) were found significantly difference (P< 0.05) between 302 SSRI-resistance and 304 SSRI non-resistance group. Ten SSRI-resistance predicting models were finally selected by using support vector machine, and our study found that mutations in tagSNPs increased the accuracy of these models to a certain degree. CONCLUSION Using a data-driven machine learning method, we found 10 predictive models by mining existing clinical data, which might enable prospective identification of patients who are likely to resistance to SSRIs antidepressant.
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Affiliation(s)
- Huijie Zhang
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Xianglu Li
- College of Economics and Management, Zhongyuan University of Technology, Zhengzhou, China
| | - Jianyue Pang
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Xiaofeng Zhao
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Suxia Cao
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Xinyou Wang
- Department of Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Xingbang Wang
- Beijing Center for Health Development Studies, Beijing, China
| | - Hengfen Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
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17
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Mustafa MI, Mohammed ZO, Murshed NS, Elfadol NM, Abdelmoneim AH, Hassan MA. In Silico Genetics Revealing 5 Mutations in CEBPA Gene Associated With Acute Myeloid Leukemia. Cancer Inform 2019; 18:1176935119870817. [PMID: 31621694 PMCID: PMC6777061 DOI: 10.1177/1176935119870817] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Accepted: 07/30/2019] [Indexed: 12/11/2022] Open
Abstract
Background: Acute myeloid leukemia (AML) is an extremely heterogeneous malignant
disorder; AML has been reported as one of the main causes of death in
children. The objective of this work was to classify the most deleterious
mutation in CCAAT/enhancer-binding protein-alpha (CEBPA)
and to predict their influence on the functional, structural, and expression
levels by various Bioinformatics analysis tools. Methods: The single nucleotide polymorphisms (SNPs) were claimed from the National
Center for Biotechnology Information (NCBI) database and then submitted into
various functional analysis tools, which were done to predict the influence
of each SNP, followed by structural analysis of modeled protein followed by
predicting the mutation effect on energy stability; the most damaging
mutations were chosen for additional investigation by Mutation3D, Project
hope, ConSurf, BioEdit, and UCSF Chimera tools. Results: A total of 5 mutations out of 248 were likely to be responsible for the
structural and functional variations in CEBPA protein, whereas in the
3′-untranslated region (3′-UTR) the result showed that among 350 SNPs in the
3′-UTR of CEBPA gene, about 11 SNPs were predicted. Among
these 11 SNPs, 65 alleles disrupted a conserved miRNA site and 22 derived
alleles created a new site of miRNA. Conclusions: In this study, the impact of functional mutations in the CEBPA gene was
investigated through different bioinformatics analysis techniques, which
determined that R339W, R288P, N292S, N292T, and D63N are pathogenic
mutations that have a possible functional and structural influence,
therefore, could be used as genetic biomarkers and may assist in genetic
studies with a special consideration of the large heterogeneity of AML.
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Affiliation(s)
- Mujahed I Mustafa
- Department of Biotechnology, Africa City of Technology, Khartoum North, Sudan
| | - Zainab O Mohammed
- Department of Haematology, Ribat University Hospital, Khartoum, Sudan
| | - Naseem S Murshed
- Department of Biotechnology, Africa City of Technology, Khartoum North, Sudan
| | - Nafisa M Elfadol
- Department of Biotechnology, Africa City of Technology, Khartoum North, Sudan
| | | | - Mohamed A Hassan
- Department of Biotechnology, Africa City of Technology, Khartoum North, Sudan
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18
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Bassagh A, Jafarzadeh A, Kazemipour N, Nemati M, Aminizadeh N, Larussa T, Ghazizadeh M, Abasi MH, Mirkamandar E. Decreased circulating interleukin-33 concentration in Helicobacter pylori-infected patients with peptic ulcer: Evaluation of its association with a cytokine gene polymorphism, gender of patients and bacterial virulence factor CagA. Microb Pathog 2019; 136:103708. [PMID: 31491552 DOI: 10.1016/j.micpath.2019.103708] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 08/30/2019] [Accepted: 09/02/2019] [Indexed: 01/10/2023]
Abstract
IL-33 has powerful immunoregulatory activities such as reinforcement of Th2 cell responses. The aim was to assess the circulating IL-33 levels and IL-33 rs1929992 polymorphism in H. pylori-infected peptic ulcer (PU) patients and asymptomatic (AS) subjects. Blood samples were obtained from 100 PU patients, 100 AS subjects and 100 uninfected individuals. Circulating IL-33 levels were detected by ELISA. After DNA extraction, the IL-33 rs1929992 polymorphism was determined using PCR-RFLP method. Serum IL-33 quantities were significantly lower in PU patients compared with AS and uninfected groups. IL-33 levels were higher in AS subjects compared with uninfected group. In PU, AS and uninfected groups, IL-33 levels were significantly higher in women than men. In PU and AS groups, the CagA+H. pylori-infected subjects exhibit higher IL-33 levels compared with carriers of CagA-H. pylori strains. In PU patients, the frequency of genotype GG and allele G at IL-33 rs1929992 was significantly higher compared with all healthy subjects (AS + uninfected groups). The presence of genotypes GG and AG, and allele G in rs1929992 conferred greater risk for PU. In whole H. pylori-infected population (PU + AS groups), IL-33 levels in individuals with genotype AA or allele A at rs1929992 were higher than subjects with GG genotype or allele G. The reduced IL-33 production could contribute to the PU development during H. pylori infection. The IL-33 levels may be affected by individual gender, rs1929992 polymorphism, and the CagA status of bacteria. The rs1929992-related GG genotype and G allele may be associated with PU development.
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Affiliation(s)
- Arezoo Bassagh
- Department of Immunology, Medical School, Kerman University of Medical Sciences, Kerman, Iran
| | - Abdollah Jafarzadeh
- Department of Immunology, Medical School, Kerman University of Medical Sciences, Kerman, Iran; Department of Immunology, Medical School, Rafsanjan University of Medical Sciences, Rafsanjan, Iran.
| | - Nadia Kazemipour
- Department of Microbiology, Islamic Azad University of Kerman Branch, Kerman, Iran
| | - Maryam Nemati
- Immunology of Infectious Diseases Research Center, Research Institute of Basic Medical Sciences, Rafsanjan University of Medical Sciences, Rafsanjan, Iran; Department of Hematology and Laboratory Sciences, School of Para-Medicine, Kerman University of Medical Sciences, Kerman, Iran
| | - Najmeh Aminizadeh
- Department of Anatomy, Islamic Azad University of Kerman Branch, Kerman, Iran
| | - Tiziana Larussa
- Department of Health Sciences, University of Catanzaro "Magna Graecia", 88100, Catanzaro, Italy
| | | | | | - Ehsan Mirkamandar
- Department of Hematology and Laboratory Sciences, School of Para-Medicine, Kerman University of Medical Sciences, Kerman, Iran
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19
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Abstract
Health care provision is changing, and so is the information we use to guide decisions related to patient care. Increasingly, health practitioners will need to deal with genetics and 'big data' in the context of clinical practice. Indeed, commercial packages for consumer genetic testing are already widely available, and devices enabling self-monitoring of health are in daily use by many of our patients. "Precision health" (distinct from "precision medicine") provides a model, which allows us to bring our genome together with our external environment (lifestyles, societal influences etc.) and eventually, our transient internal environment (reflected by 'omics'), to optimise disease prevention and care. Such advancements have given rise to a need for primary health care clinicians to understand basic genetic and precision health concepts. This editorial meets this need, serving as a primer by providing the following: an introduction to current primary health challenges; description of the key elements of the precision health model; an overview of basic genetic, and associated research concepts; a snapshot of some clinically pertinent research in the context of precision health; and a brief discussion of challenges and future directions.
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Affiliation(s)
- Cameron Dickson
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, GPO Box 2471, Adelaide, South Australia 5001, Australia.
| | - Elina Hyppönen
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, GPO Box 2471, Adelaide, South Australia 5001, Australia; Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, London, UK; South Australian Health and Medical Research Institute, PO Box 11060, Adelaide, South Australia 5001, Australia.
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20
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Zhang W, Hu F, Zhang X, Meng W, Zhang Y, Song Y, Wang H, Wang P, Gu Y. Ligase chain reaction-based electrochemical biosensor for the ultrasensitive and specific detection of single nucleotide polymorphisms. NEW J CHEM 2019. [DOI: 10.1039/c9nj03994e] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
In this study, a sensitive electrochemical biosensor for universally, robustly, specifically, and sensitively detecting SNPs was developed by using LCR as a signal amplification strategy.
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Affiliation(s)
- Wancun Zhang
- Children's Hospital Affiliated of Zhengzhou University
- 450000 Zhenzhou
- China
| | - Fang Hu
- State Key Laboratory of Natural Medicines
- Department of Biomedical Engineering
- School of Engineering
- China Pharmaceutical University
- 210009 Nanjing
| | - Xianwei Zhang
- Children's Hospital Affiliated of Zhengzhou University
- 450000 Zhenzhou
- China
| | - Wei Meng
- Key Laboratory of Biomedical Functional Materials
- School of Science
- China Pharmaceutical University
- Nanjing 211198
- China
| | - Yaodong Zhang
- Children's Hospital Affiliated of Zhengzhou University
- 450000 Zhenzhou
- China
| | - Yinsen Song
- Children's Hospital Affiliated of Zhengzhou University
- 450000 Zhenzhou
- China
| | | | - Peng Wang
- State Key Laboratory of Natural Medicines
- Department of Biomedical Engineering
- School of Engineering
- China Pharmaceutical University
- 210009 Nanjing
| | - Yueqing Gu
- State Key Laboratory of Natural Medicines
- Department of Biomedical Engineering
- School of Engineering
- China Pharmaceutical University
- 210009 Nanjing
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21
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Xue Y, Ma C, Hanna I, Pan G. Intestinal Transporter-Associated Drug Absorption and Toxicity. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1141:361-405. [DOI: 10.1007/978-981-13-7647-4_8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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22
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Lei W, Xu Y, Su J, Chong CM, Su HX, Luo J, Fang EF, Bao Z, Chen G. Applications of high-throughput ‘omics’ data in the study of frailty. TRANSLATIONAL MEDICINE OF AGING 2019. [DOI: 10.1016/j.tma.2019.04.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
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23
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Le BT, Hughes Q, Rakesh S, Baker R, Jørgensen PT, Wengel J, Veedu RN. Unlocked nucleic acid modified primer-based enzymatic polymerization assay: towards allele-specific genotype detection of human platelet antigens. RSC Adv 2018; 8:32770-32774. [PMID: 35547719 PMCID: PMC9086379 DOI: 10.1039/c8ra06050a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Accepted: 08/24/2018] [Indexed: 12/12/2022] Open
Abstract
Accurate detection of single nucleotide polymorphisms (SNPs) is paramount for the appropriate therapeutic intervention of debilitating diseases associated with SNPs. However, in some cases current nucleic acid probes fail to detect allele-specific mutations, for example, human platelet antigens, HPA-15a (TCC) and HPA-15b (TAC) alleles associated with neonatal alloimmune thrombocytopenia. Towards this, it is necessary to develop a novel assay for detection of allele-specific mutations. In this study, we investigated the potential of unlocked nucleic acid (UNA)-modified primers in SNP detection utilising an enzymatic polymerisation-based approach. Our results of primer extension and asymmetric polymerase chain reaction by KOD XL DNA polymerase revealed that UNA-modified primers achieved excellent allele-specificity in discriminating the human platelet antigen DNA template, whereas the DNA control primers were not able to differentiate between the normal and mutant alleles, demonstrating the scope of this novel UNA-based enzymatic approach as a robust methodology for efficient detection of allele-specific mismatches. Although further evaluation is required for other disease conditions, we firmly believe that our findings offer a great promise for the diagnosis of neonatal alloimmune thrombocytopenia and other SNP-related diseases.
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Affiliation(s)
- Bao T Le
- Centre for Comparative Genomics, Murdoch University Perth Australia-6150
- Perron Institute for Neurological and Translational Science Perth Australia-6009
| | | | | | - Ross Baker
- Perth Blood Institute Nedlands Perth WA Australia
| | - Per T Jørgensen
- BioNEC, Department of Physics, Chemistry and Pharmacy, University of Southern Denmark Odense M 5231 Denmark
| | - Jesper Wengel
- BioNEC, Department of Physics, Chemistry and Pharmacy, University of Southern Denmark Odense M 5231 Denmark
| | - Rakesh N Veedu
- Centre for Comparative Genomics, Murdoch University Perth Australia-6150
- Perron Institute for Neurological and Translational Science Perth Australia-6009
- BioNEC, Department of Physics, Chemistry and Pharmacy, University of Southern Denmark Odense M 5231 Denmark
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24
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POLYMORPHISMS OF DRUG-METABOLIZING ENZYMES CYP1A2, CYP2D6, GST, NAT2 AND TRANSPORTER MDR1 IN POPULATION OF BELARUS: COMPARISON WITH SELECTED EUROPEAN AND ASIAN POPULATIONS. EUREKA: LIFE SCIENCES 2016. [DOI: 10.21303/2504-5695.2016.00105] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Drug therapeutic efficiency and development of unfavorable pharmacologic responses as well as the disease predisposition are caused first of all by patient’s genetic features. Genetic variations in genes encoding drug-metabolizing enzymes and transporter proteins are essential to understand the ethnic differences in disease occurrence, development, prognosis, therapeutic response and toxicity of drugs. For that reason, it is necessary to establish the normative frequency distribution of genotypes and alleles of these genes in a particular population. Data on frequency of pharmacogenetic polymorphisms in the of Belarus population are limited. The goal of our investigation was to analyze the frequency distribution of genotypes and alleles of genes encoding drug-metabolizing enzymes (CYP1А2, CYP2D6 – I phase; GSTs, NAT2 – II phase) and transporter protein MDR1 in the population of Belarus and comparisons with other ethnic populations. Our results indicate that clinically important genes are genetically highly variable and differ considerably between populations. Differences in allele frequencies across continents should be considered when designing clinical trials of new drugs continents should be considered when designing clinical trials of new drugs.
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25
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Medhasi S, Pasomsub E, Vanwong N, Ngamsamut N, Puangpetch A, Chamnanphon M, Hongkaew Y, Limsila P, Pinthong D, Sukasem C. Clinically relevant genetic variants of drug-metabolizing enzyme and transporter genes detected in Thai children and adolescents with autism spectrum disorder. Neuropsychiatr Dis Treat 2016; 12:843-51. [PMID: 27110117 PMCID: PMC4835132 DOI: 10.2147/ndt.s101580] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Single-nucleotide polymorphisms (SNPs) among drug-metabolizing enzymes and transporters (DMETs) influence the pharmacokinetic profile of drugs and exhibit intra- and interethnic variations in drug response in terms of efficacy and safety profile. The main objective of this study was to assess the frequency of allelic variants of drug absorption, distribution, metabolism, and elimination-related genes in Thai children and adolescents with autism spectrum disorder. Blood samples were drawn from 119 patients, and DNA was extracted. Genotyping was performed using the DMET Plus microarray platform. The allele frequencies of the DMET markers were generated using the DMET Console software. Thereafter, the genetic variations of significant DMET genes were assessed. The frequencies of SNPs across the genes coding for DMETs were determined. After filtering the SNPs, 489 of the 1,931 SNPs passed quality control. Many clinically relevant SNPs, including CYP2C19*2, CYP2D6*10, CYP3A5*3, and SLCO1B1*5, were found to have frequencies similar to those in the Chinese population. These data are important for further research to investigate the interpatient variability in pharmacokinetics and pharmacodynamics of drugs in clinical practice.
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Affiliation(s)
- Sadeep Medhasi
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; Department of Pharmacology, Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Ekawat Pasomsub
- Division of Virology, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Natchaya Vanwong
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Nattawat Ngamsamut
- Yuwaprasart Waithayopathum Child and Adolescent Psychiatric Hospital, Department of Mental Health Services, Ministry of Public Health, Samut Prakarn, Thailand
| | - Apichaya Puangpetch
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Montri Chamnanphon
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Yaowaluck Hongkaew
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Penkhae Limsila
- Yuwaprasart Waithayopathum Child and Adolescent Psychiatric Hospital, Department of Mental Health Services, Ministry of Public Health, Samut Prakarn, Thailand
| | - Darawan Pinthong
- Department of Pharmacology, Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Chonlaphat Sukasem
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
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