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Ma Y, Zhou Y, Jiang D, Dai W, Li J, Deng C, Chen C, Zheng G, Zhang Y, Qiu F, Sun H, Xing S, Han H, Qu J, Wu N, Yao Y, Su J. Integration of human organoids single-cell transcriptomic profiles and human genetics repurposes critical cell type-specific drug targets for severe COVID-19. Cell Prolif 2024; 57:e13558. [PMID: 37807299 PMCID: PMC10905359 DOI: 10.1111/cpr.13558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/31/2023] [Accepted: 09/18/2023] [Indexed: 10/10/2023] Open
Abstract
Human organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single-cell RNA sequencing (scRNA-seq) technology and genome-wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait-relevant cell types or states. Here, we constructed a computational framework to integrate atlas-level organoid scRNA-seq data, GWAS summary statistics, expression quantitative trait loci, and gene-drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID-19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID-19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID-19-damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID-19, and this cell subset showed a notable increase in cell-to-cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID-19 in a cell-type-specific manner. Overall, our results showcase that host genetic determinants have cellular-specific contribution to COVID-19 severity, and identification of cell type-specific drug targets may facilitate to develop effective therapeutics for treating severe COVID-19 and its complications.
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Affiliation(s)
- Yunlong Ma
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Zhejiang, China
| | - Yijun Zhou
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
| | - Dingping Jiang
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Zhejiang, China
| | - Wei Dai
- Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, China
| | - Jingjing Li
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
| | - Chunyu Deng
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Cheng Chen
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
| | - Gongwei Zheng
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
| | - Yaru Zhang
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Zhejiang, China
| | - Fei Qiu
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
| | - Haojun Sun
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
| | - Shilai Xing
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
| | - Haijun Han
- School of Medicine, Hangzhou City University, Hangzhou, China
| | - Jia Qu
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Nan Wu
- Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Key Laboratory of Big Data for Spinal Deformities, Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
| | - Yinghao Yao
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Zhejiang, China
| | - Jianzhong Su
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Zhejiang, China
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Chen L, Mou X, Li J, Li M, Ye C, Gao X, Liu X, Ma Y, Xu Y, Zhong Y. Alterations in gut microbiota and host transcriptome of patients with coronary artery disease. BMC Microbiol 2023; 23:320. [PMID: 37924005 PMCID: PMC10623719 DOI: 10.1186/s12866-023-03071-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 10/16/2023] [Indexed: 11/06/2023] Open
Abstract
BACKGROUND Coronary artery disease (CAD) is a widespread heart condition caused by atherosclerosis and influences millions of people worldwide. Early detection of CAD is challenging due to the lack of specific biomarkers. The gut microbiota and host-microbiota interactions have been well documented to affect human health. However, investigation that reveals the role of gut microbes in CAD is still limited. This study aims to uncover the synergistic effects of host genes and gut microbes associated with CAD through integrative genomic analyses. RESULTS Herein, we collected 52 fecal and 50 blood samples from CAD patients and matched controls, and performed amplicon and transcriptomic sequencing on these samples, respectively. By comparing CAD patients with health controls, we found that dysregulated gut microbes were significantly associated with CAD. By leveraging the Random Forest method, we found that combining 20 bacteria and 30 gene biomarkers could distinguish CAD patients from health controls with a high performance (AUC = 0.92). We observed that there existed prominent associations of gut microbes with several clinical indices relevant to heart functions. Integration analysis revealed that CAD-relevant gut microbe genus Fusicatenibacter was associated with expression of CAD-risk genes, such as GBP2, MLKL, and CPR65, which is in line with previous evidence (Tang et al., Nat Rev Cardiol 16:137-154, 2019; Kummen et al., J Am Coll Cardiol 71:1184-1186, 2018). In addition, the upregulation of immune-related pathways in CAD patients were identified to be primarily associated with higher abundance of genus Blautia, Eubacterium, Fusicatenibacter, and Monoglobus. CONCLUSIONS Our results highlight that dysregulated gut microbes contribute risk to CAD by interacting with host genes. These identified microbes and interacted risk genes may have high potentials as biomarkers for CAD.
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Affiliation(s)
- Liuying Chen
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xuanting Mou
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingjing Li
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, China
| | - Miaofu Li
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Caijie Ye
- Zhejiang Chinese Medical University, Hangzhou, China
| | - Xiaofei Gao
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaohua Liu
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yunlong Ma
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, China.
- Department of Biomedical Informatics, Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, 325027, China.
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Wenzhou, 325101, Zhejiang, China.
| | - Yizhou Xu
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Yigang Zhong
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Yang X, Hou X, Zhang J, Liu Z, Wang G. Research progress on the application of single-cell sequencing in autoimmune diseases. Genes Immun 2023; 24:220-235. [PMID: 37550409 DOI: 10.1038/s41435-023-00216-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 07/26/2023] [Accepted: 07/31/2023] [Indexed: 08/09/2023]
Abstract
Autoimmune diseases (AIDs) are caused by immune tolerance deficiency or abnormal immune regulation, leading to damage to host organs. The complicated pathogenesis and varied clinical symptoms of AIDs pose great challenges in diagnosing and monitoring this disease. Regrettably, the etiological factors and pathogenesis of AIDs are still not completely understood. It is noteworthy that the development of single-cell RNA sequencing (scRNA-seq) technology provides a new tool for analyzing the transcriptome of AIDs. In this essay, we have summarized the development of scRNA-seq technology, and made a relatively systematic review of the current research progress of scRNA-seq technology in the field of AIDs, providing a reference to preferably understand the pathogenesis, diagnosis, and treatment of AIDs.
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Affiliation(s)
- Xueli Yang
- Central Laboratory, Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, China
| | - Xianliang Hou
- Central Laboratory, Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, China.
| | - Junning Zhang
- Central Laboratory, Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, China
| | - Zhenyu Liu
- Central Laboratory, Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, China
| | - Guangyu Wang
- Central Laboratory, Guangxi Health Commission Key Laboratory of Glucose and Lipid Metabolism Disorders, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, China
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Ma Y, Deng C, Zhou Y, Zhang Y, Qiu F, Jiang D, Zheng G, Li J, Shuai J, Zhang Y, Yang J, Su J. Polygenic regression uncovers trait-relevant cellular contexts through pathway activation transformation of single-cell RNA sequencing data. CELL GENOMICS 2023; 3:100383. [PMID: 37719150 PMCID: PMC10504677 DOI: 10.1016/j.xgen.2023.100383] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 05/26/2023] [Accepted: 07/25/2023] [Indexed: 09/19/2023]
Abstract
Advances in single-cell RNA sequencing (scRNA-seq) techniques have accelerated functional interpretation of disease-associated variants discovered from genome-wide association studies (GWASs). However, identification of trait-relevant cell populations is often impeded by inherent technical noise and high sparsity in scRNA-seq data. Here, we developed scPagwas, a computational approach that uncovers trait-relevant cellular context by integrating pathway activation transformation of scRNA-seq data and GWAS summary statistics. scPagwas effectively prioritizes trait-relevant genes, which facilitates identification of trait-relevant cell types/populations with high accuracy in extensive simulated and real datasets. Cellular-level association results identified a novel subpopulation of naive CD8+ T cells related to COVID-19 severity and oligodendrocyte progenitor cell and microglia subsets with critical pathways by which genetic variants influence Alzheimer's disease. Overall, our approach provides new insights for the discovery of trait-relevant cell types and improves the mechanistic understanding of disease variants from a pathway perspective.
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Affiliation(s)
- Yunlong Ma
- School of Biomedical Engineering, School of OphthalmoFlogy & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Wenzhou, Zhejiang 325101, China
| | - Chunyu Deng
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150080, China
| | - Yijun Zhou
- School of Biomedical Engineering, School of OphthalmoFlogy & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Wenzhou, Zhejiang 325101, China
| | - Yaru Zhang
- School of Biomedical Engineering, School of OphthalmoFlogy & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Wenzhou, Zhejiang 325101, China
| | - Fei Qiu
- School of Biomedical Engineering, School of OphthalmoFlogy & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Dingping Jiang
- School of Biomedical Engineering, School of OphthalmoFlogy & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Gongwei Zheng
- School of Biomedical Engineering, School of OphthalmoFlogy & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Jingjing Li
- School of Biomedical Engineering, School of OphthalmoFlogy & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Jianwei Shuai
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Wenzhou, Zhejiang 325101, China
| | - Yan Zhang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150080, China
| | - Jian Yang
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310012, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Jianzhong Su
- School of Biomedical Engineering, School of OphthalmoFlogy & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
- Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Wenzhou, Zhejiang 325101, China
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Zou J, Li J, Zhong X, Tang D, Fan X, Chen R. Liver in infections: a single-cell and spatial transcriptomics perspective. J Biomed Sci 2023; 30:53. [PMID: 37430371 PMCID: PMC10332047 DOI: 10.1186/s12929-023-00945-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 06/27/2023] [Indexed: 07/12/2023] Open
Abstract
The liver is an immune organ that plays a vital role in the detection, capture, and clearance of pathogens and foreign antigens that invade the human body. During acute and chronic infections, the liver transforms from a tolerant to an active immune state. The defence mechanism of the liver mainly depends on a complicated network of intrahepatic and translocated immune cells and non-immune cells. Therefore, a comprehensive liver cell atlas in both healthy and diseased states is needed for new therapeutic target development and disease intervention improvement. With the development of high-throughput single-cell technology, we can now decipher heterogeneity, differentiation, and intercellular communication at the single-cell level in sophisticated organs and complicated diseases. In this concise review, we aimed to summarise the advancement of emerging high-throughput single-cell technologies and re-define our understanding of liver function towards infections, including hepatitis B virus, hepatitis C virus, Plasmodium, schistosomiasis, endotoxemia, and corona virus disease 2019 (COVID-19). We also unravel previously unknown pathogenic pathways and disease mechanisms for the development of new therapeutic targets. As high-throughput single-cell technologies mature, their integration into spatial transcriptomics, multiomics, and clinical data analysis will aid in patient stratification and in developing effective treatment plans for patients with or without liver injury due to infectious diseases.
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Affiliation(s)
- Ju Zou
- Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Jie Li
- Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Xiao Zhong
- Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Daolin Tang
- Department of Surgery, UT Southwestern Medical Center, Dallas, TX, USA
| | - Xuegong Fan
- Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Ruochan Chen
- Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
- Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
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Yang Y, He X, Rojas M, Leung PSC, Gao L. Mechanism-based target therapy in primary biliary cholangitis: opportunities before liver cirrhosis? Front Immunol 2023; 14:1184252. [PMID: 37325634 PMCID: PMC10266968 DOI: 10.3389/fimmu.2023.1184252] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 05/16/2023] [Indexed: 06/17/2023] Open
Abstract
Primary biliary cholangitis (PBC) is an immune-mediated liver disease characterized by cholestasis, biliary injuries, liver fibrosis, and chronic non-suppurative cholangitis. The pathogenesis of PBC is multifactorial and involves immune dysregulation, abnormal bile metabolism, and progressive fibrosis, ultimately leading to cirrhosis and liver failure. Ursodeoxycholic acid (UDCA) and obeticholic acid (OCA) are currently used as first- and second-line treatments, respectively. However, many patients do not respond adequately to UDCA, and the long-term effects of these drugs are limited. Recent research has advanced our understanding the mechanisms of pathogenesis in PBC and greatly facilitated development of novel drugs to target mechanistic checkpoints. Animal studies and clinical trials of pipeline drugs have yielded promising results in slowing disease progression. Targeting immune mediated pathogenesis and anti-inflammatory therapies are focused on the early stage, while anti-cholestatic and anti-fibrotic therapies are emphasized in the late stage of disease, which is characterized by fibrosis and cirrhosis development. Nonetheless, it is worth noting that currently, there exists a dearth of therapeutic options that can effectively impede the progression of the disease to its terminal stages. Hence, there is an urgent need for further research aimed at investigating the underlying pathophysiology mechanisms with potential therapeutic effects. This review highlights our current knowledge of the underlying immunological and cellular mechanisms of pathogenesis in PBC. Further, we also address current mechanism-based target therapies for PBC and potential therapeutic strategies to improve the efficacy of existing treatments.
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Affiliation(s)
- Yushu Yang
- Department of Rheumatology and Immunology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - XiaoSong He
- Division of Rheumatology, Allergy, and Clinical Immunology, University of California, Davis, Davis, CA, United States
| | - Manuel Rojas
- Division of Rheumatology, Allergy, and Clinical Immunology, University of California, Davis, Davis, CA, United States
- Center for Autoimmune Diseases Research (CREA), School of Medicine and Health Sciences, Universidad del Rosario, Bogota, Colombia
| | - Patrick S. C. Leung
- Division of Rheumatology, Allergy, and Clinical Immunology, University of California, Davis, Davis, CA, United States
| | - Lixia Gao
- Department of Rheumatology and Immunology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
- Division of Rheumatology, Allergy, and Clinical Immunology, University of California, Davis, Davis, CA, United States
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Huang Y, Luo J, Zhang Y, Zhang T, Fei X, Chen L, Zhu Y, Li S, Zhou C, Xu K, Ma Y, Lin J, Zhou J. Identification of MKNK1 and TOP3A as ovarian endometriosis risk-associated genes using integrative genomic analyses and functional experiments. Comput Struct Biotechnol J 2023; 21:1510-1522. [PMID: 36851918 PMCID: PMC9957794 DOI: 10.1016/j.csbj.2023.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 01/11/2023] [Accepted: 02/01/2023] [Indexed: 02/07/2023] Open
Abstract
The risk of endometriosis (EM), which is a common complex gynaecological disease, is related to genetic predisposition. However, it is unclear how genetic variants confer the risk of EM. Here, via Sherlock integrative analysis, we combined large-scale genome-wide association studies (GWAS) summary statistics on EM (N = 245,494) with a blood-based eQTL dataset (N = 1490) to identify EM risk-related genes. For validation, we leveraged two independent eQTL datasets (N = 769) for integration with the GWAS data. Thus, we prioritised 14 genes, including GIMAP4, TOP3A, and NMNAT3, which showed significant association with susceptibility to EM. We also utilised two independent methods, Multi-marker Analysis of GenoMic Annotation and S-PrediXcan, to further validate the EM risk-associated genes. Moreover, protein-protein interaction network analysis showed the 14 genes were functionally connected. Functional enrichment analyses further demonstrated that these genes were significantly enriched in metabolic and immune-related pathways. Differential gene expression analysis showed that in peripheral blood samples from patients with ovarian EM, TOP3A, MKNK1, SIPA1L2, and NUCB1 were significantly upregulated, while HOXB2, GIMAP5, and MGMT were significantly downregulated compared with their expression levels in samples from the controls. Immunohistochemistry further confirmed the increased expression levels of MKNK1 and TOP3A in the ectopic and eutopic endometrium compared to normal endometrium, while HOBX2 was downregulated in the endometrium of women with ovarian EM. Finally, in ex vivo functional experiments, MKNK1 knockdown inhibited ectopic endometrial stromal cells (EESCs) migration and invasion. TOP3A knockdown inhibited EESCs proliferation, migration, and invasion, while promoting their apoptosis. Convergent lines of evidence suggested that MKNK1 and TOP3A are novel EM risk-related genes.
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Affiliation(s)
- Yizhou Huang
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Jie Luo
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Yue Zhang
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Tao Zhang
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Xiangwei Fei
- Key Laboratory of Women's Reproductive Health of Zhejiang Province, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Liqing Chen
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Yingfan Zhu
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Songyue Li
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Caiyun Zhou
- Department of Pathology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Kaihong Xu
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Yunlong Ma
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University 325027 Wenzhou, Zhejiang Province, PR China
| | - Jun Lin
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
| | - Jianhong Zhou
- Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, Zhejiang Province, PR China
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Zeng L, Yang K, Zhang T, Zhu X, Hao W, Chen H, Ge J. Research progress of single-cell transcriptome sequencing in autoimmune diseases and autoinflammatory disease: A review. J Autoimmun 2022; 133:102919. [PMID: 36242821 DOI: 10.1016/j.jaut.2022.102919] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 12/07/2022]
Abstract
Autoimmunity refers to the phenomenon that the body's immune system produces antibodies or sensitized lymphocytes to its own tissues to cause an immune response. Immune disorders caused by autoimmunity can mediate autoimmune diseases. Autoimmune diseases have complicated pathogenesis due to the many types of cells involved, and the mechanism is still unclear. The emergence of single-cell research technology can solve the problem that ordinary transcriptome technology cannot be accurate to cell type. It provides unbiased results through independent analysis of cells in tissues and provides more mRNA information for identifying cell subpopulations, which provides a novel approach to study disruption of immune tolerance and disturbance of pro-inflammatory pathways on a cellular basis. It may fundamentally change the understanding of molecular pathways in the pathogenesis of autoimmune diseases and develop targeted drugs. Single-cell transcriptome sequencing (scRNA-seq) has been widely applied in autoimmune diseases, which provides a powerful tool for demonstrating the cellular heterogeneity of tissues involved in various immune inflammations, identifying pathogenic cell populations, and revealing the mechanism of disease occurrence and development. This review describes the principles of scRNA-seq, introduces common sequencing platforms and practical procedures, and focuses on the progress of scRNA-seq in 41 autoimmune diseases, which include 9 systemic autoimmune diseases and autoinflammatory diseases (rheumatoid arthritis, systemic lupus erythematosus, etc.) and 32 organ-specific autoimmune diseases (5 Skin diseases, 3 Nervous system diseases, 4 Eye diseases, 2 Respiratory system diseases, 2 Circulatory system diseases, 6 Liver, Gallbladder and Pancreas diseases, 2 Gastrointestinal system diseases, 3 Muscle, Bones and joint diseases, 3 Urinary system diseases, 2 Reproductive system diseases). This review also prospects the molecular mechanism targets of autoimmune diseases from the multi-molecular level and multi-dimensional analysis combined with single-cell multi-omics sequencing technology (such as scRNA-seq, Single cell ATAC-seq and single cell immune group library sequencing), which provides a reference for further exploring the pathogenesis and marker screening of autoimmune diseases and autoimmune inflammatory diseases in the future.
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Affiliation(s)
- Liuting Zeng
- Department of Rheumatology, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China.
| | - Kailin Yang
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China.
| | - Tianqing Zhang
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China
| | - Xiaofei Zhu
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China.
| | - Wensa Hao
- Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hua Chen
- Department of Rheumatology, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China.
| | - Jinwen Ge
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China; Hunan Academy of Chinese Medicine, Changsha, China.
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9
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Abstract
The human liver is a complex organ made up of multiple specialized cell types that carry out key physiological functions. An incomplete understanding of liver biology limits our ability to develop therapeutics to prevent chronic liver diseases, liver cancers, and death as a result of organ failure. Recently, single-cell modalities have expanded our understanding of the cellular phenotypic heterogeneity and intercellular cross-talk in liver health and disease. This review summarizes these findings and looks forward to highlighting new avenues for the application of single-cell genomics to unravel unknown pathogenic pathways and disease mechanisms for the development of new therapeutics targeting liver pathology. As these technologies mature, their integration into clinical data analysis will aid in patient stratification and in developing treatment plans for patients suffering from liver disease.
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Affiliation(s)
- Jawairia Atif
- Ajmera Transplant Centre, Schwartz Reisman Liver Research Centre, Toronto General Research Institute, University Health Network, Toronto, Ontario, Canada
- Department of Immunology, University of Toronto, Medical Sciences Building, Toronto, Ontario, Canada
| | - Cornelia Thoeni
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Gary D. Bader
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
| | - Ian D. McGilvray
- Ajmera Transplant Centre, Schwartz Reisman Liver Research Centre, Toronto General Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Sonya A. MacParland
- Ajmera Transplant Centre, Schwartz Reisman Liver Research Centre, Toronto General Research Institute, University Health Network, Toronto, Ontario, Canada
- Department of Immunology, University of Toronto, Medical Sciences Building, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
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10
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How genetic risk contributes to autoimmune liver disease. Semin Immunopathol 2022; 44:397-410. [PMID: 35650446 PMCID: PMC9256578 DOI: 10.1007/s00281-022-00950-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 05/06/2022] [Indexed: 12/16/2022]
Abstract
Genome-wide association studies (GWAS) for autoimmune hepatitis (AIH) and GWAS/genome-wide meta-analyses (GWMA) for primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) have been successful over the past decade, identifying about 100 susceptibility loci in the human genome, with strong associations with the HLA locus and many susceptibility variants outside the HLA locus with relatively low risk. However, identifying causative variants and genes and determining their effects on liver cells and their immunological microenvironment is far from trivial. Polygenic risk scores (PRSs) based on current genome-wide data have limited potential to predict individual disease risk. Interestingly, results of mediated expression score regression analysis provide evidence that a substantial portion of gene expression at susceptibility loci is mediated by genetic risk variants, in contrast to many other complex diseases. Genome- and transcriptome-wide comparisons between AIH, PBC, and PSC could help to better delineate the shared inherited component of autoimmune liver diseases (AILDs), and statistical fine-mapping, chromosome X-wide association testing, and genome-wide in silico drug screening approaches recently applied to GWMA data from PBC could potentially be successfully applied to AIH and PSC. Initial successes through single-cell RNA sequencing (scRNA-seq) experiments in PBC and PSC now raise high hopes for understanding the impact of genetic risk variants in the context of liver-resident immune cells and liver cell subpopulations, and for bridging the gap between genetics and disease.
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11
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Lan T, Qian S, Tang C, Gao J. Role of Immune Cells in Biliary Repair. Front Immunol 2022; 13:866040. [PMID: 35432349 PMCID: PMC9005827 DOI: 10.3389/fimmu.2022.866040] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 03/08/2022] [Indexed: 02/06/2023] Open
Abstract
The biliary system is comprised of cholangiocytes and plays an important role in maintaining liver function. Under normal conditions, cholangiocytes remain in the stationary phase and maintain a very low turnover rate. However, the robust biliary repair is initiated in disease conditions, and different repair mechanisms can be activated depending on the pathological changes. During biliary disease, immune cells including monocytes, lymphocytes, neutrophils, and mast cells are recruited to the liver. The cellular interactions between cholangiocytes and these recruited immune cells as well as hepatic resident immune cells, including Kupffer cells, determine disease outcomes. However, the role of immune cells in the initiation, regulation, and suspension of biliary repair remains elusive. The cellular processes of cholangiocyte proliferation, progenitor cell differentiation, and hepatocyte-cholangiocyte transdifferentiation during biliary diseases are reviewed to manifest the underlying mechanism of biliary repair. Furthermore, the potential role of immune cells in crucial biliary repair mechanisms is highlighted. The mechanisms of biliary repair in immune-mediated cholangiopathies, inherited cholangiopathies, obstructive cholangiopathies, and cholangiocarcinoma are also summarized. Additionally, novel techniques that could clarify the underlying mechanisms of biliary repair are displayed. Collectively, this review aims to deepen the understanding of the mechanisms of biliary repair and contributes potential novel therapeutic methods for treating biliary diseases.
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Affiliation(s)
- Tian Lan
- Lab of Gastroenterology and Hepatology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.,Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China
| | - Shuaijie Qian
- Lab of Gastroenterology and Hepatology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.,Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China
| | - Chengwei Tang
- Lab of Gastroenterology and Hepatology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.,Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China
| | - Jinhang Gao
- Lab of Gastroenterology and Hepatology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.,Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China
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12
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Ma Y, Qiu F, Deng C, Li J, Huang Y, Wu Z, Zhou Y, Zhang Y, Xiong Y, Yao Y, Zhong Y, Qu J, Su J. Integrating single-cell sequencing data with GWAS summary statistics reveals CD16+monocytes and memory CD8+T cells involved in severe COVID-19. Genome Med 2022; 14:16. [PMID: 35172892 PMCID: PMC8851814 DOI: 10.1186/s13073-022-01021-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 02/06/2022] [Indexed: 02/08/2023] Open
Abstract
Background Understanding the host genetic architecture and viral immunity contributes to the development of effective vaccines and therapeutics for controlling the COVID-19 pandemic. Alterations of immune responses in peripheral blood mononuclear cells play a crucial role in the detrimental progression of COVID-19. However, the effects of host genetic factors on immune responses for severe COVID-19 remain largely unknown. Methods We constructed a computational framework to characterize the host genetics that influence immune cell subpopulations for severe COVID-19 by integrating GWAS summary statistics (N = 969,689 samples) with four independent scRNA-seq datasets containing healthy controls and patients with mild, moderate, and severe symptom (N = 606,534 cells). We collected 10 predefined gene sets including inflammatory and cytokine genes to calculate cell state score for evaluating the immunological features of individual immune cells. Results We found that 34 risk genes were significantly associated with severe COVID-19, and the number of highly expressed genes increased with the severity of COVID-19. Three cell subtypes that are CD16+monocytes, megakaryocytes, and memory CD8+T cells were significantly enriched by COVID-19-related genetic association signals. Notably, three causal risk genes of CCR1, CXCR6, and ABO were highly expressed in these three cell types, respectively. CCR1+CD16+monocytes and ABO+ megakaryocytes with significantly up-regulated genes, including S100A12, S100A8, S100A9, and IFITM1, confer higher risk to the dysregulated immune response among severe patients. CXCR6+ memory CD8+ T cells exhibit a notable polyfunctionality including elevation of proliferation, migration, and chemotaxis. Moreover, we observed an increase in cell-cell interactions of both CCR1+ CD16+monocytes and CXCR6+ memory CD8+T cells in severe patients compared to normal controls among both PBMCs and lung tissues. The enhanced interactions of CXCR6+ memory CD8+T cells with epithelial cells facilitate the recruitment of this specific population of T cells to airways, promoting CD8+T cell-mediated immunity against COVID-19 infection. Conclusions We uncover a major genetics-modulated immunological shift between mild and severe infection, including an elevated expression of genetics-risk genes, increase in inflammatory cytokines, and of functional immune cell subsets aggravating disease severity, which provides novel insights into parsing the host genetic determinants that influence peripheral immune cells in severe COVID-19. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-022-01021-1.
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Affiliation(s)
- Yunlong Ma
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China
| | - Fei Qiu
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China
| | - Chunyu Deng
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China
| | - Jingjing Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Yukuan Huang
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China
| | - Zeyi Wu
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China
| | - Yijun Zhou
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China
| | - Yaru Zhang
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China
| | - Yichun Xiong
- Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, 325011, China
| | - Yinghao Yao
- Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, 325011, China
| | - Yigang Zhong
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jia Qu
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China
| | - Jianzhong Su
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China. .,Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, 325011, China.
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