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Zhu J, Fan Q, Deng W, Wang Y, Guo X. BTOB: Extending the Biased GWAS to Bivariate GWAS. Front Genet 2021; 12:654821. [PMID: 34025719 PMCID: PMC8134661 DOI: 10.3389/fgene.2021.654821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Accepted: 04/07/2021] [Indexed: 11/13/2022] Open
Abstract
In recent years, a number of literatures published large-scale genome-wide association studies (GWASs) for human diseases or traits while adjusting for other heritable covariate. However, it is known that these GWASs are biased, which may lead to biased genetic estimates or even false positives. In this study, we provide a method called "BTOB" which extends the biased GWAS to bivariate GWAS by integrating the summary association statistics from the biased GWAS and the GWAS for the adjusted heritable covariate. We employ the proposed BTOB method to analyze the summary association statistics from the large scale meta-GWASs for waist-to-hip ratio (WHR) and body mass index (BMI), and show that the proposed approach can help identify more susceptible genes compared with the corresponding univariate GWASs. Theoretical results and simulations also confirm the validity and efficiency of the proposed BTOB method.
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Affiliation(s)
- Junxian Zhu
- Department of Statistical Science, School of Mathematics, Sun Yat-sen University, Guangzhou, China
| | - Qiao Fan
- Center for Quantitative Medicine, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Wenying Deng
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States
| | - Yimeng Wang
- Department of Statistical Science, School of Mathematics, Sun Yat-sen University, Guangzhou, China
| | - Xiaobo Guo
- Department of Statistical Science, School of Mathematics, Sun Yat-sen University, Guangzhou, China
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Turu G, Soltész-Katona E, Tóth AD, Juhász C, Cserző M, Misák Á, Balla A, Caron MG, Hunyady L. Biased Coupling to β-Arrestin of Two Common Variants of the CB 2 Cannabinoid Receptor. Front Endocrinol (Lausanne) 2021; 12:714561. [PMID: 34484125 PMCID: PMC8415483 DOI: 10.3389/fendo.2021.714561] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 07/08/2021] [Indexed: 01/14/2023] Open
Abstract
β-arrestins are partners of the G protein-coupled receptors (GPCRs), regulating their intracellular trafficking and signaling. Development of biased GPCR agonists, selectively targeting either G protein or β-arrestin pathways, are in the focus of interest due to their therapeutic potential in different pathological conditions. The CB2 cannabinoid receptor (CB2R) is a GPCR involved in various functions in the periphery and the central nervous system. Two common occurring variants of CB2R, harboring Q63R or L133I missense mutations, have been implicated in the development of a diverse set of disorders. To evaluate the effect of these mutations, we characterized the binding profile of these mutant CB2 receptors to G proteins and β-arrestin2. Although their ability to inhibit cAMP signaling was similar, the Q63R mutant had increased, whereas the L133I mutant receptor had decreased β-arrestin2 binding. In line with these observations, the variants also had altered intracellular trafficking. Our results show that two common variants of the CB2 receptor have biased signaling properties, which may contribute to the pathogenesis of the associated disorders and may offer CB2R as a target for further development of biased receptor activation strategies.
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Affiliation(s)
- Gábor Turu
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- MTA-SE Laboratory of Molecular Physiology, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary
- Department of Cell Biology, Duke University Medical Center, Duke University School of Medicine, Durham, NC, United States
- *Correspondence: Gábor Turu, ; László Hunyady,
| | - Eszter Soltész-Katona
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- MTA-SE Laboratory of Molecular Physiology, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary
| | - András Dávid Tóth
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- MTA-SE Laboratory of Molecular Physiology, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary
| | - Cintia Juhász
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Miklós Cserző
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- MTA-SE Laboratory of Molecular Physiology, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary
| | - Ádám Misák
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - András Balla
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- MTA-SE Laboratory of Molecular Physiology, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary
| | - Marc G. Caron
- Department of Cell Biology, Duke University Medical Center, Duke University School of Medicine, Durham, NC, United States
| | - László Hunyady
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- MTA-SE Laboratory of Molecular Physiology, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary
- *Correspondence: Gábor Turu, ; László Hunyady,
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Affiliation(s)
- Tyler C Beck
- Department of Drug Discovery & Biomedical Sciences, Medical University of South Carolina, Charleston, SC, 29425, USA; Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina, Charleston, SC, 29425, USA.
| | - Thomas A Dix
- Department of Drug Discovery & Biomedical Sciences, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Russell A Norris
- Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina, Charleston, SC, 29425, USA.
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Martin F, Sánchez-Hernández S, Gutiérrez-Guerrero A, Pinedo-Gomez J, Benabdellah K. Biased and Unbiased Methods for the Detection of Off-Target Cleavage by CRISPR/Cas9: An Overview. Int J Mol Sci 2016; 17:E1507. [PMID: 27618019 DOI: 10.3390/ijms17091507] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2016] [Revised: 08/29/2016] [Accepted: 08/31/2016] [Indexed: 12/15/2022] Open
Abstract
The clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein 9 endonuclease (Cas9) derived from bacterial adaptive immune systems is a revolutionary tool used in both basic and applied science. It is a versatile system that enables the genome of different species to be modified by generating double strand breaks (DSBs) at specific locations. However, all of the CRISPR/Cas9 systems can also produce DSBs at off-target sites that differ substantially from on-target sites. The generation of DSBs in locations outside the intended site can produce mutations that need to be carefully monitored, especially when using these tools for therapeutic purposes. However, off-target analyses of the CRISPR/Cas9 system have been very challenging, particularly when performed directly in cells. In this manuscript, we review the different strategies developed to identify off-targets generated by CRISPR/cas9 systems and other specific nucleases (ZFNs, TALENs) in real target cells.
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