Integrated analyses of single-cell transcriptome and Mendelian randomization reveal the protective role of FCRL3 in multiple sclerosis

被引:3
作者
Yu, Kefu [1 ]
Jiang, Ruiqi [1 ,2 ]
Li, Ziming [2 ]
Ren, Xiaohui [3 ]
Jiang, Haihui [4 ]
Zhao, Zhigang [1 ,2 ]
机构
[1] Capital Med Univ, Beijing Tiantan Hosp, Dept Pharm, Beijing, Peoples R China
[2] Capital Med Univ, Sch Pharmaceut Sci, Beijing, Peoples R China
[3] Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, Beijing, Peoples R China
[4] Peking Univ, Peking Univ Third Hosp, Dept Neurosurg, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Mendelian randomization; single-cell transcriptome; colocalization; pharmaceutical targets; multiple sclerosis; biomarkers; GENE;
D O I
10.3389/fimmu.2024.1428962
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background Multiple sclerosis (MS) represents a multifaceted autoimmune ailment, prompting the development and widespread utilization of numerous therapeutic interventions. However, extant medications for MS have proven inadequate in mitigating relapses and halting disease progression. Innovative drug targets for preventing multiple sclerosis are still required. The objective of this study is to discover novel therapeutic targets for MS by integrating single-cell transcriptomics and Mendelian randomization analysis.Methods The study integrated MS genome-wide association study (GWAS) data, single-cell transcriptomics (scRNA-seq), expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data for analysis and utilized two-sample Mendelian randomization study to comprehend the causal relationship between proteins and MS. Sequential analyses involving colocalization and Phenome-wide association studies (PheWAS) were conducted to validate the causal role of candidate genes.Results Following stringent quality control preprocessing of scRNA-seq data, 1,123 expression changes across seven peripheral cell types were identified. Among the seven most prevalent cell types, 97 genes exhibiting at least one eQTL were discerned. Examination of MR associations between 28 proteins with available index pQTL signals and the risk of MS outcomes was conducted. Co-localization analyses and PheWAS indicated that FCRL3 may exert influence on MS.Conclusion The integration of scRNA-seq and MR analysis facilitated the identification of potential therapeutic targets for MS. Notably, FCRL3, implicated in immune function, emerged as a significant drug target in the deCODE databases. This research underscores the importance of FCRL3 in MS therapy and advocates for further investigation and clinical trials targeting FCRL3.
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页数:8
相关论文
共 27 条
[1]   Updates and advances in multiple sclerosis neurotherapeutics [J].
Amin, Moein ;
Hersh, Carrie M. .
NEURODEGENERATIVE DISEASE MANAGEMENT, 2023, 13 (01) :47-70
[2]   Is FCRL3 a new general autoimmunity gene? [J].
Chistiakov, Dimitry A. ;
Chistiakov, Alexander P. .
HUMAN IMMUNOLOGY, 2007, 68 (05) :375-383
[3]   An integrative analysis of single-cell and bulk transcriptome and bidirectional mendelian randomization analysis identified C1Q as a novel stimulated risk gene for Atherosclerosis [J].
Cui, Hong-Kai ;
Tang, Chao-Jie ;
Gao, Yu ;
Li, Zi-Ang ;
Zhang, Jian ;
Li, Yong-Dong .
FRONTIERS IN IMMUNOLOGY, 2023, 14
[4]   FCRL3 promotes IL-10 expression in B cells through the SHP-1 and p38 MAPK signaling pathways [J].
Cui Xiao ;
Liu Chong-mei ;
Liu Qi-bing .
CELL BIOLOGY INTERNATIONAL, 2020, 44 (09) :1811-1819
[5]   Multiple sclerosis - a review [J].
Dobson, R. ;
Giovannoni, G. .
EUROPEAN JOURNAL OF NEUROLOGY, 2019, 26 (01) :27-40
[6]  
Doshi Anisha, 2016, Clin Med (Lond), V16, ps53
[7]   Large-scale integration of the plasma proteome with genetics and disease [J].
Ferkingstad, Egil ;
Sulem, Patrick ;
Atlason, Bjarni A. ;
Sveinbjornsson, Gardar ;
Magnusson, Magnus I. ;
Styrmisdottir, Edda L. ;
Gunnarsdottir, Kristbjorg ;
Helgason, Agnar ;
Oddsson, Asmundur ;
Halldorsson, Bjarni V. ;
Jensson, Brynjar O. ;
Zink, Florian ;
Halldorsson, Gisli H. ;
Masson, Gisli ;
Arnadottir, Gudny A. ;
Katrinardottir, Hildigunnur ;
Juliusson, Kristinn ;
Magnusson, Magnus K. ;
Magnusson, Olafur Th. ;
Fridriksdottir, Run ;
Saevarsdottir, Saedis ;
Gudjonsson, Sigurjon A. ;
Stacey, Simon N. ;
Rognvaldsson, Solvi ;
Eiriksdottir, Thjodbjorg ;
Olafsdottir, Thorunn A. ;
Steinthorsdottir, Valgerdur ;
Tragante, Vinicius ;
Ulfarsson, Magnus O. ;
Stefansson, Hreinn ;
Jonsdottir, Ingileif ;
Holm, Hilma ;
Rafnar, Thorunn ;
Melsted, Pall ;
Saemundsdottir, Jona ;
Norddahl, Gudmundur L. ;
Lund, Sigrun H. ;
Gudbjartsson, Daniel F. ;
Thorsteinsdottir, Unnur ;
Stefansson, Kari .
NATURE GENETICS, 2021, 53 (12) :1712-+
[8]   Prioritization of Drug Targets for Neurodegenerative Diseases by Integrating Genetic and Proteomic Data From Brain and Blood [J].
Ge, Yi-Jun ;
Ou, Ya-Nan ;
Deng, Yue-Ting ;
Wu, Bang-Sheng ;
Yang, Liu ;
Zhang, Ya-Ru ;
Chen, Shi-Dong ;
Huang, Yu-Yuan ;
Dong, Qiang ;
Tan, Lan ;
Yu, Jin-Tai .
BIOLOGICAL PSYCHIATRY, 2023, 93 (09) :770-779
[9]   The MR-Base platform supports systematic causal inference across the human phenome [J].
Hemani, Gibran ;
Zhengn, Jie ;
Elsworth, Benjamin ;
Wade, Kaitlin H. ;
Haberland, Valeriia ;
Baird, Denis ;
Laurin, Charles ;
Burgess, Stephen ;
Bowden, Jack ;
Langdon, Ryan ;
Tan, Vanessa Y. ;
Yarmolinsky, James ;
Shihab, Hashem A. ;
Timpson, Nicholas J. ;
Evans, David M. ;
Relton, Caroline ;
Martin, Richard M. ;
Smith, George Davey ;
Gaunt, Tom R. ;
Haycock, Philip C. .
ELIFE, 2018, 7
[10]   Summary-data-based Mendelian randomization prioritizes potential druggable targets for multiple sclerosis [J].
Jacobs, Benjamin M. ;
Taylor, Thomas ;
Awad, Amine ;
Baker, David ;
Giovanonni, Gavin ;
Noyce, Alastair J. ;
Dobson, Ruth .
BRAIN COMMUNICATIONS, 2020, 2 (02)