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Nishiyama T, Ohyama A, Miki H, Asashima H, Kondo Y, Tsuboi H, Ohno H, Shimano H, Matsumoto I. Mechanisms of age-related Treg dysfunction in an arthritic environment. Clin Immunol 2024; 266:110337. [PMID: 39111562 DOI: 10.1016/j.clim.2024.110337] [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: 04/24/2024] [Revised: 07/18/2024] [Accepted: 08/01/2024] [Indexed: 08/11/2024]
Abstract
Rheumatoid arthritis (RA) is an autoimmune disease characterized by a polyarticular synovitis. In recent years, elderly onset rheumatoid arthritis (EORA) has been increasing. Treg cells in RA have been reported to be dysfunctional, but the relationship between aging and their functional changes is unclear. Here, we found that Treg cells from EORA patients had increased percentages, but decreased activity compared to those from younger onset RA (YORA) patients. In experiments using arthritis model mice, decreased suppressive function and oxygen consumption rate (OCR) were observed in Treg cells only from old arthritic mice. Furthermore, type I interferon (IFN) signaling was upregulated in Treg cells from old GIA mice, and IFN-β decreased the suppressive function of Treg cells. Our findings demonstrate that increased type I IFN signaling in old Treg cells is induced only in the arthritic environment and relates to decreased suppressive function of Treg cells, gets involved in EORA.
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Affiliation(s)
- Taihei Nishiyama
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Ayako Ohyama
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Haruka Miki
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Hiromitsu Asashima
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Yuya Kondo
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Hiroto Tsuboi
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Hiroshi Ohno
- Department of Endocrinology and Metabolism, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Hitoshi Shimano
- Department of Endocrinology and Metabolism, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Isao Matsumoto
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan.
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2
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Chen M, Zhang Y, Shi W, Song X, Yang Y, Hou G, Ding H, Chen S, Yang W, Shen N, Cui Y, Zuo X, Tang Y. SPATS2L is a positive feedback regulator of the type I interferon signaling pathway and plays a vital role in lupus. Acta Biochim Biophys Sin (Shanghai) 2024. [PMID: 39099414 DOI: 10.3724/abbs.2024132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2024] Open
Abstract
Through genome-wide association studies (GWAS) and integrated expression quantitative trait locus (eQTL) analyses, numerous susceptibility genes ("eGenes", whose expressions are significantly associated with common variants) associated with systemic lupus erythematosus (SLE) have been identified. Notably, a subset of these eGenes is correlated with disease activity. However, the precise mechanisms through which these genes contribute to the initiation and progression of the disease remain to be fully elucidated. In this investigation, we initially identify SPATS2L as an SLE eGene correlated with disease activity. eSignaling and transcriptomic analyses suggest its involvement in the type I interferon (IFN) pathway. We observe a significant increase in SPATS2L expression following type I IFN stimulation, and the expression levels are dependent on both the concentration and duration of stimulation. Furthermore, through dual-luciferase reporter assays, western blot analysis, and imaging flow cytometry, we confirm that SPATS2L positively modulates the type I IFN pathway, acting as a positive feedback regulator. Notably, siRNA-mediated intervention targeting SPATS2L, an interferon-inducible gene, in peripheral blood mononuclear cells (PBMCs) from patients with SLE reverses the activation of the interferon pathway. In conclusion, our research highlights the pivotal role of SPATS2L as a positive-feedback regulatory molecule within the type I IFN pathway. Our findings suggest that SPATS2L plays a critical role in the onset and progression of SLE and may serve as a promising target for disease activity assessment and intervention strategies.
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Affiliation(s)
- Mengke Chen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200001, China
| | - Yutong Zhang
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200001, China
| | - Weiwen Shi
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200001, China
| | - Xuejiao Song
- Department of Dermatology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Yue Yang
- Department of Dermatology, China-Japan Friendship Hospital, Beijing 100029, China
- Department of Pharmacy, China-Japan Friendship Hospital, Beijing 100029, China
| | - Guojun Hou
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200001, China
| | - Huihua Ding
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200001, China
| | - Sheng Chen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200001, China
| | - Wanling Yang
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong 999077, China
| | - Nan Shen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200001, China
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200032, China
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati OH 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati OH 45229, USA
| | - Yong Cui
- Department of Dermatology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Xianbo Zuo
- Department of Dermatology, China-Japan Friendship Hospital, Beijing 100029, China
- Department of Pharmacy, China-Japan Friendship Hospital, Beijing 100029, China
| | - Yuanjia Tang
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200001, China
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3
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Went M, Duran-Lozano L, Halldorsson GH, Gunnell A, Ugidos-Damboriena N, Law P, Ekdahl L, Sud A, Thorleifsson G, Thodberg M, Olafsdottir T, Lamarca-Arrizabalaga A, Cafaro C, Niroula A, Ajore R, Lopez de Lapuente Portilla A, Ali Z, Pertesi M, Goldschmidt H, Stefansdottir L, Kristinsson SY, Stacey SN, Love TJ, Rognvaldsson S, Hajek R, Vodicka P, Pettersson-Kymmer U, Späth F, Schinke C, Van Rhee F, Sulem P, Ferkingstad E, Hjorleifsson Eldjarn G, Mellqvist UH, Jonsdottir I, Morgan G, Sonneveld P, Waage A, Weinhold N, Thomsen H, Försti A, Hansson M, Juul-Vangsted A, Thorsteinsdottir U, Hemminki K, Kaiser M, Rafnar T, Stefansson K, Houlston R, Nilsson B. Deciphering the genetics and mechanisms of predisposition to multiple myeloma. Nat Commun 2024; 15:6644. [PMID: 39103364 DOI: 10.1038/s41467-024-50932-7] [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: 01/03/2024] [Accepted: 07/24/2024] [Indexed: 08/07/2024] Open
Abstract
Multiple myeloma (MM) is an incurable malignancy of plasma cells. Epidemiological studies indicate a substantial heritable component, but the underlying mechanisms remain unclear. Here, in a genome-wide association study totaling 10,906 cases and 366,221 controls, we identify 35 MM risk loci, 12 of which are novel. Through functional fine-mapping and Mendelian randomization, we uncover two causal mechanisms for inherited MM risk: longer telomeres; and elevated levels of B-cell maturation antigen (BCMA) and interleukin-5 receptor alpha (IL5RA) in plasma. The largest increase in BCMA and IL5RA levels is mediated by the risk variant rs34562254-A at TNFRSF13B. While individuals with loss-of-function variants in TNFRSF13B develop B-cell immunodeficiency, rs34562254-A exerts a gain-of-function effect, increasing MM risk through amplified B-cell responses. Our results represent an analysis of genetic MM predisposition, highlighting causal mechanisms contributing to MM development.
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Affiliation(s)
- Molly Went
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK
| | - Laura Duran-Lozano
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | | | - Andrea Gunnell
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK
| | - Nerea Ugidos-Damboriena
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | - Philip Law
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK
| | - Ludvig Ekdahl
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | - Amit Sud
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK
| | | | - Malte Thodberg
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | | | - Antton Lamarca-Arrizabalaga
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | - Caterina Cafaro
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | - Abhishek Niroula
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | - Ram Ajore
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | - Aitzkoa Lopez de Lapuente Portilla
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | - Zain Ali
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | - Maroulio Pertesi
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden
| | - Hartmut Goldschmidt
- Department of Internal Medicine V, University of Heidelberg, 69120, Heidelberg, Germany
| | | | - Sigurdur Y Kristinsson
- Landspitali, National University Hospital of Iceland, IS-101, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, IS-101, Reykjavik, Iceland
| | - Simon N Stacey
- deCODE Genetics/Amgen, Sturlugata 8, IS-101, Reykjavik, Iceland
| | - Thorvardur J Love
- Landspitali, National University Hospital of Iceland, IS-101, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, IS-101, Reykjavik, Iceland
| | - Saemundur Rognvaldsson
- Landspitali, National University Hospital of Iceland, IS-101, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, IS-101, Reykjavik, Iceland
| | - Roman Hajek
- University Hospital Ostrava and University of Ostrava, Ostrava, Czech Republic
| | - Pavel Vodicka
- Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Prague, Czech Republic
| | | | - Florentin Späth
- Department of Radiation Sciences, Umeå University, SE-901 87, Umeå, Sweden
| | - Carolina Schinke
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Frits Van Rhee
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Patrick Sulem
- deCODE Genetics/Amgen, Sturlugata 8, IS-101, Reykjavik, Iceland
| | | | | | | | | | - Gareth Morgan
- Perlmutter Cancer Center, Langone Health, New York University, New York, NY, USA
| | - Pieter Sonneveld
- Department of Hematology, Erasmus MC Cancer Institute, 3075 EA, Rotterdam, The Netherlands
| | - Anders Waage
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Box 8905, N-7491, Trondheim, Norway
| | - Niels Weinhold
- Department of Internal Medicine V, University of Heidelberg, 69120, Heidelberg, Germany
- German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany
| | | | - Asta Försti
- German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany
- Hopp Children's Cancer Center, Heidelberg, Germany
| | - Markus Hansson
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden
- Section of Hematology, Sahlgrenska University Hospital, Gothenburg, SE-413 45, Sweden
- Skåne University Hospital, SE-221 85, Lund, Sweden
| | - Annette Juul-Vangsted
- Department of Haematology, University Hospital of Copenhagen at Rigshospitalet, Blegdamsvej 9, DK-2100, Copenhagen, Denmark
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Sturlugata 8, IS-101, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, IS-101, Reykjavik, Iceland
| | - Kari Hemminki
- German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany
- Faculty of Medicine in Pilsen, Charles University, 30605, Pilsen, Czech Republic
| | - Martin Kaiser
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK
| | - Thorunn Rafnar
- deCODE Genetics/Amgen, Sturlugata 8, IS-101, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE Genetics/Amgen, Sturlugata 8, IS-101, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, IS-101, Reykjavik, Iceland
| | - Richard Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.
| | - Björn Nilsson
- Department of Laboratory Medicine, Lund University, SE-221 84, Lund, Sweden.
- Lund Stem Cell Center, Lund University, SE-221 84, Lund, Sweden.
- Broad Institute, 415 Main Street, Cambridge, MA, 02142, USA.
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4
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Qi T, Song L, Guo Y, Chen C, Yang J. From genetic associations to genes: methods, applications, and challenges. Trends Genet 2024; 40:642-667. [PMID: 38734482 DOI: 10.1016/j.tig.2024.04.008] [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: 11/08/2023] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 05/13/2024]
Abstract
Genome-wide association studies (GWASs) have identified numerous genetic loci associated with human traits and diseases. However, pinpointing the causal genes remains a challenge, which impedes the translation of GWAS findings into biological insights and medical applications. In this review, we provide an in-depth overview of the methods and technologies used for prioritizing genes from GWAS loci, including gene-based association tests, integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data, linking GWAS variants to target genes through enhancer-gene connection maps, and network-based prioritization. We also outline strategies for generating context-dependent xQTL data and their applications in gene prioritization. We further highlight the potential of gene prioritization in drug repurposing. Lastly, we discuss future challenges and opportunities in this field.
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Affiliation(s)
- Ting Qi
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China.
| | - Liyang Song
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China
| | - Yazhou Guo
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China
| | - Chang Chen
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China
| | - Jian Yang
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China.
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5
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Tomofuji Y, Edahiro R, Sonehara K, Shirai Y, Kock KH, Wang QS, Namba S, Moody J, Ando Y, Suzuki A, Yata T, Ogawa K, Naito T, Namkoong H, Xuan Lin QX, Buyamin EV, Tan LM, Sonthalia R, Han KY, Tanaka H, Lee H, Okuno T, Liu B, Matsuda K, Fukunaga K, Mochizuki H, Park WY, Yamamoto K, Hon CC, Shin JW, Prabhakar S, Kumanogoh A, Okada Y. Quantification of escape from X chromosome inactivation with single-cell omics data reveals heterogeneity across cell types and tissues. CELL GENOMICS 2024:100625. [PMID: 39084228 DOI: 10.1016/j.xgen.2024.100625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 05/09/2024] [Accepted: 07/05/2024] [Indexed: 08/02/2024]
Abstract
Several X-linked genes escape from X chromosome inactivation (XCI), while differences in escape across cell types and tissues are still poorly characterized. Here, we developed scLinaX for directly quantifying relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA sequencing (scRNA-seq) data. The scLinaX and differentially expressed gene analyses with large-scale blood scRNA-seq datasets consistently identified the stronger escape in lymphocytes than in myeloid cells. An extension of scLinaX to a 10x multiome dataset (scLinaX-multi) suggested a stronger escape in lymphocytes than in myeloid cells at the chromatin-accessibility level. The scLinaX analysis of human multiple-organ scRNA-seq datasets also identified the relatively strong degree of escape from XCI in lymphoid tissues and lymphocytes. Finally, effect size comparisons of genome-wide association studies between sexes suggested the underlying impact of escape on the genotype-phenotype association. Overall, scLinaX and the quantified escape catalog identified the heterogeneity of escape across cell types and tissues.
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Affiliation(s)
- Yoshihiko Tomofuji
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan.
| | - Ryuya Edahiro
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan
| | - Yuya Shirai
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kian Hong Kock
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Qingbo S Wang
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan
| | - Jonathan Moody
- Laboratory for Genome Information Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Yoshinari Ando
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Akari Suzuki
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Tomohiro Yata
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kotaro Ogawa
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Ho Namkoong
- Department of Infectious Diseases, Keio University School of Medicine, Shinanomachi 160-8582, Japan
| | - Quy Xiao Xuan Lin
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Eliora Violain Buyamin
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Le Min Tan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Radhika Sonthalia
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Kyung Yeon Han
- Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea
| | - Hiromu Tanaka
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinanomachi 160-8582, Japan
| | - Ho Lee
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinanomachi 160-8582, Japan
| | - Tatsusada Okuno
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Boxiang Liu
- Department of Pharmacy, National University of Singapore, Singapore 117549, Republic of Singapore
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Shirokanedai 108-8639, Japan
| | - Koichi Fukunaga
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinanomachi 160-8582, Japan
| | - Hideki Mochizuki
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Woong-Yang Park
- Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea
| | - Kazuhiko Yamamoto
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Chung-Chau Hon
- Laboratory for Genome Information Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Jay W Shin
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore; Laboratory for Advanced Genomics Circuit, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Shyam Prabhakar
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore; Lee Kong Chian School of Medicine, Singapore 308232, Republic of Singapore; Cancer Science Institute of Singapore, Singapore 117599, Republic of Singapore
| | - Atsushi Kumanogoh
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Department of Immunopathology, Immunology Frontier Research Center, Osaka University, Suita 565-0871, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan; Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan; Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita 565-0871, Japan.
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6
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Huang D, Shang W, Xu M, Wan Q, Zhang J, Tang X, Shen Y, Wang Y, Yu Y. Genome-Wide Methylation Analysis Reveals a KCNK3-Prominent Causal Cascade on Hypertension. Circ Res 2024; 135:e76-e93. [PMID: 38841840 DOI: 10.1161/circresaha.124.324455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 05/22/2024] [Indexed: 06/07/2024]
Abstract
BACKGROUND Despite advances in understanding hypertension's genetic structure, how noncoding genetic variants influence it remains unclear. Studying their interaction with DNA methylation is crucial to deciphering this complex disease's genetic mechanisms. METHODS We investigated the genetic and epigenetic interplay in hypertension using whole-genome bisulfite sequencing. Methylation profiling in 918 males revealed allele-specific methylation and methylation quantitative trait loci. We engineered rs1275988T/C mutant mice using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9), bred them for homozygosity, and subjected them to a high-salt diet. Telemetry captured their cardiovascular metrics. Protein-DNA interactions were elucidated using DNA pull-downs, mass spectrometry, and Western blots. A wire myograph assessed vascular function, and analysis of the Kcnk3 gene methylation highlighted the mutation's role in hypertension. RESULTS We discovered that DNA methylation-associated genetic effects, especially in non-cytosine-phosphate-guanine (non-CpG) island and noncoding distal regulatory regions, significantly contribute to hypertension predisposition. We identified distinct methylation quantitative trait locus patterns in the hypertensive population and observed that the onset of hypertension is influenced by the transmission of genetic effects through the demethylation process. By evidence-driven prioritization and in vivo experiments, we unearthed rs1275988 in a cell type-specific enhancer as a notable hypertension causal variant, intensifying hypertension through the modulation of local DNA methylation and consequential alterations in Kcnk3 gene expression and vascular remodeling. When exposed to a high-salt diet, mice with the rs1275988C/C genotype exhibited exacerbated hypertension and significant vascular remodeling, underscored by increased aortic wall thickness. The C allele of rs1275988 was associated with elevated DNA methylation levels, driving down the expression of the Kcnk3 gene by attenuating Nr2f2 (nuclear receptor subfamily 2 group F member 2) binding at the enhancer locus. CONCLUSIONS Our research reveals new insights into the complex interplay between genetic variations and DNA methylation in hypertension. We underscore hypomethylation's potential in hypertension onset and identify rs1275988 as a causal variant in vascular remodeling. This work advances our understanding of hypertension's molecular mechanisms and encourages personalized health care strategies.
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Affiliation(s)
- Dandan Huang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
- School of Food Science and Technology, Jiangnan University, Wuxi, China (D.H.)
| | - Wenlong Shang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Mengtong Xu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Qiangyou Wan
- Academy of Integrative Medicine, Shanghai University of Traditional Chinese Medicine (Q.W.)
| | - Jin Zhang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Xiaofeng Tang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Yujun Shen
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Yan Wang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Ying Yu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
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7
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Tanaka S, Etori K, Hattori K, Tamura J, Ikeda K, Kageyama T, Meguro K, Iwamoto T, Iwata A, Furuta S, Suto A, Suzuki K, Nakajima H. CCR4 predicts the efficacy of abatacept in rheumatoid arthritis patients through the estimation of Th17 and Treg cell abundance. Mod Rheumatol 2024; 34:700-704. [PMID: 37522614 DOI: 10.1093/mr/road077] [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: 06/01/2023] [Revised: 07/10/2023] [Accepted: 07/14/2023] [Indexed: 08/01/2023]
Abstract
OBJECTIVES Predicting the efficacy of biological disease-modifying antirheumatic drugs is challenging. In this study, we aimed to explore markers that predict the efficacy of abatacept in rheumatoid arthritis (RA) patients. METHODS Thirty RA patients receiving abatacept were recruited, and peripheral blood mononuclear cells from the participants were subjected to DNA microarray analysis. The expression of CC chemokine receptor 4 (CCR4), which was selected by the result of DNA microarray, was determined by flow cytometry in 16 newly diagnosed treatment-naïve RA patients. CCR4 expression on each helper T-cell subset was also measured. RESULTS CCR4 was upregulated in the abatacept responder. The expression levels of CCR4 were significantly correlated with the improvement of the Clinical Disease Activity Index. CCR4 expression was predominantly observed in CD4+ T cells in peripheral blood mononuclear cells. The percentage of CCR4-expressing CD4+ T cells was significantly higher in RA patients than in healthy individuals. Interestingly, Th17 and Treg cells expressed high levels of CCR4 compared to non-Th17-related helper T cells. CONCLUSIONS CCR4 is a Th17- and Treg-related gene, and the high CCR4 expression in peripheral blood samples may predict the efficacy of abatacept in RA.
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Affiliation(s)
- Shigeru Tanaka
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Keishi Etori
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Koto Hattori
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Jun Tamura
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Kei Ikeda
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Takahiro Kageyama
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Kazuyuki Meguro
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Taro Iwamoto
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Arifumi Iwata
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Shunsuke Furuta
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Akira Suto
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
- Graduate School of Medicine, Institute for Advanced Academic Research, Chiba, Japan
| | - Kotaro Suzuki
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Hiroshi Nakajima
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Japan
- Chiba University, Synergy Institute for Futuristic Mucosal Vaccine Research and Development (cSIMVa), Chiba, Japan
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8
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Oguchi A, Suzuki A, Komatsu S, Yoshitomi H, Bhagat S, Son R, Bonnal RJP, Kojima S, Koido M, Takeuchi K, Myouzen K, Inoue G, Hirai T, Sano H, Takegami Y, Kanemaru A, Yamaguchi I, Ishikawa Y, Tanaka N, Hirabayashi S, Konishi R, Sekito S, Inoue T, Kere J, Takeda S, Takaori-Kondo A, Endo I, Kawaoka S, Kawaji H, Ishigaki K, Ueno H, Hayashizaki Y, Pagani M, Carninci P, Yanagita M, Parrish N, Terao C, Yamamoto K, Murakawa Y. An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases. Science 2024; 385:eadd8394. [PMID: 38963856 DOI: 10.1126/science.add8394] [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: 07/17/2022] [Accepted: 05/01/2024] [Indexed: 07/06/2024]
Abstract
Transcribed enhancer maps can reveal nuclear interactions underpinning each cell type and connect specific cell types to diseases. Using a 5' single-cell RNA sequencing approach, we defined transcription start sites of enhancer RNAs and other classes of coding and noncoding RNAs in human CD4+ T cells, revealing cellular heterogeneity and differentiation trajectories. Integration of these datasets with single-cell chromatin profiles showed that active enhancers with bidirectional RNA transcription are highly cell type-specific and that disease heritability is strongly enriched in these enhancers. The resulting cell type-resolved multimodal atlas of bidirectionally transcribed enhancers, which we linked with promoters using fine-scale chromatin contact maps, enabled us to systematically interpret genetic variants associated with a range of immune-mediated diseases.
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Affiliation(s)
- Akiko Oguchi
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- Department of Nephrology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Akari Suzuki
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuichiro Komatsu
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- IFOM ETS - the AIRC Institute of Molecular Oncology, Milan, Italy
| | - Hiroyuki Yoshitomi
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- Department of Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Shruti Bhagat
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
| | - Raku Son
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- Department of Nephrology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | | | - Shohei Kojima
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masaru Koido
- Division of Molecular Pathology, Department of Cancer Biology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kazuhiro Takeuchi
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- Department of Medical Systems Genomics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Keiko Myouzen
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Gyo Inoue
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Tomoya Hirai
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Gastroenterological Surgery, Yokohama City University Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Hiromi Sano
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | | | | | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Nao Tanaka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shigeki Hirabayashi
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Hematology and Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Division of Precision Medicine, Kyushu University Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Riyo Konishi
- Inter-Organ Communication Research Team, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Sho Sekito
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Mie University, Tsu, Japan
| | - Takahiro Inoue
- Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Mie University, Tsu, Japan
| | - Juha Kere
- Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden
- Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
| | - Shunichi Takeda
- Department of Radiation Genetics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Shenzhen University School of Medicine, Shenzhen, Guangdong, China
| | - Akifumi Takaori-Kondo
- Department of Hematology and Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Itaru Endo
- Department of Gastroenterological Surgery, Yokohama City University Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Shinpei Kawaoka
- Inter-Organ Communication Research Team, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
- Department of Integrative Bioanalytics, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Hideya Kawaji
- Research Center for Genome & Medical Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
- Preventive Medicine and Applied Genomics Unit, RIKEN Center for Integrative Medical Science, Yokohama, Japan
- RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Hideki Ueno
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- Department of Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yoshihide Hayashizaki
- K.K. DNAFORM, Yokohama, Japan
- RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Japan
| | - Massimiliano Pagani
- IFOM ETS - the AIRC Institute of Molecular Oncology, Milan, Italy
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi, Milan, Italy
| | - Piero Carninci
- Laboratory for Transcriptome Technology, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Human Technopole, Milan, Italy
| | - Motoko Yanagita
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- Department of Nephrology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nicholas Parrish
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Kazuhiko Yamamoto
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yasuhiro Murakawa
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- IFOM ETS - the AIRC Institute of Molecular Oncology, Milan, Italy
- Department of Medical Systems Genomics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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9
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Sparks R, Rachmaninoff N, Lau WW, Hirsch DC, Bansal N, Martins AJ, Chen J, Liu CC, Cheung F, Failla LE, Biancotto A, Fantoni G, Sellers BA, Chawla DG, Howe KN, Mostaghimi D, Farmer R, Kotliarov Y, Calvo KR, Palmer C, Daub J, Foruraghi L, Kreuzburg S, Treat JD, Urban AK, Jones A, Romeo T, Deuitch NT, Moura NS, Weinstein B, Moir S, Ferrucci L, Barron KS, Aksentijevich I, Kleinstein SH, Townsley DM, Young NS, Frischmeyer-Guerrerio PA, Uzel G, Pinto-Patarroyo GP, Cudrici CD, Hoffmann P, Stone DL, Ombrello AK, Freeman AF, Zerbe CS, Kastner DL, Holland SM, Tsang JS. A unified metric of human immune health. Nat Med 2024:10.1038/s41591-024-03092-6. [PMID: 38961223 DOI: 10.1038/s41591-024-03092-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 05/28/2024] [Indexed: 07/05/2024]
Abstract
Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine.
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Grants
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1ZIAAI001152 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- Z01 AI000825-24 LIR Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 1 ZIA AI001202-07 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- Z-01-A-00646 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- Z-01-A-00647 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- Z-01-A-00646 Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- 5R01AI170116 U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID)
- U19AI089992 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- U19AI089992 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- ZIA-HL006089-12 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- 1ZIAHG200371 U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI)
- 1ZIAHG200373 U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI)
- 1ZIAHG200374 U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI)
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Affiliation(s)
- Rachel Sparks
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Nicholas Rachmaninoff
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
- Graduate Program in Biological Sciences, University of Maryland, College Park, MD, USA
| | - William W Lau
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Dylan C Hirsch
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Neha Bansal
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Andrew J Martins
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Jinguo Chen
- NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA
| | - Candace C Liu
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Foo Cheung
- NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA
| | - Laura E Failla
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Angelique Biancotto
- NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA
| | - Giovanna Fantoni
- NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA
| | - Brian A Sellers
- NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA
| | - Daniel G Chawla
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Katherine N Howe
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | - Darius Mostaghimi
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Rohit Farmer
- NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA
| | - Yuri Kotliarov
- NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA
| | - Katherine R Calvo
- Hematology Section, Department of Laboratory Medicine, Clinical Center, NIH, Bethesda, MD, USA
| | - Cindy Palmer
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | - Janine Daub
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | - Ladan Foruraghi
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | - Samantha Kreuzburg
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | - Jennifer D Treat
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | - Amanda K Urban
- Clinical Research Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Anne Jones
- Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA
| | - Tina Romeo
- Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA
| | | | | | | | - Susan Moir
- Laboratory of Immunoregulation, NIAID, NIH, Bethesda, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, NIA, Baltimore, MD, USA
| | - Karyl S Barron
- Division of Intramural Research, NIAID, NIH, Bethesda, MD, USA
| | | | - Steven H Kleinstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | | | - Neal S Young
- Hematology Branch, NHLBI, NIH, Bethesda, MD, USA
| | | | - Gulbu Uzel
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | | | | | | | | | | | - Alexandra F Freeman
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | - Christa S Zerbe
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | | | - Steven M Holland
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA
| | - John S Tsang
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
- NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA.
- Center for Systems and Engineering Immunology, Departments of Immunobiology and Biomedical Engineering, Yale University School of Medicine, New Haven, CT, USA.
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10
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Sumida TS, Cheru NT, Hafler DA. The regulation and differentiation of regulatory T cells and their dysfunction in autoimmune diseases. Nat Rev Immunol 2024; 24:503-517. [PMID: 38374298 PMCID: PMC11216899 DOI: 10.1038/s41577-024-00994-x] [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] [Accepted: 01/15/2024] [Indexed: 02/21/2024]
Abstract
The discovery of FOXP3+ regulatory T (Treg) cells as a distinct cell lineage with a central role in regulating immune responses provided a deeper understanding of self-tolerance. The transcription factor FOXP3 serves a key role in Treg cell lineage determination and maintenance, but is not sufficient to enable the full potential of Treg cell suppression, indicating that other factors orchestrate the fine-tuning of Treg cell function. Moreover, FOXP3-independent mechanisms have recently been shown to contribute to Treg cell dysfunction. FOXP3 mutations in humans cause lethal fulminant systemic autoinflammation (IPEX syndrome). However, it remains unclear to what degree Treg cell dysfunction is contributing to the pathophysiology of common autoimmune diseases. In this Review, we discuss the origins of Treg cells in the periphery and the multilayered mechanisms by which Treg cells are induced, as well as the FOXP3-dependent and FOXP3-independent cellular programmes that maintain the suppressive function of Treg cells in humans and mice. Further, we examine evidence for Treg cell dysfunction in the context of common autoimmune diseases such as multiple sclerosis, inflammatory bowel disease, systemic lupus erythematosus and rheumatoid arthritis.
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Affiliation(s)
- Tomokazu S Sumida
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
| | - Nardos T Cheru
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - David A Hafler
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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11
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Chi H, Hong X, Dai N, Chen L, Zhang H, Liu H, Cheng X, Ye J, Shi H, Hu Q, Meng J, Zhou Z, Jia J, Liu T, Wang F, Wang M, Ma Y, Chen X, You Y, Zhu D, Tang Z, Yang C, Teng J, Su Y, Sun Y. The landscape of innate and adaptive immune cell subsets in patients with adult-onset Still's disease. Rheumatology (Oxford) 2024; 63:1987-1997. [PMID: 37756690 DOI: 10.1093/rheumatology/kead507] [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: 06/06/2023] [Revised: 08/18/2023] [Accepted: 08/29/2023] [Indexed: 09/29/2023] Open
Abstract
OBJECTIVE Adult-onset Still's disease (AOSD) is a systemic autoinflammatory disorder. The understanding of the changes in adaptive immune cells and the crosstalk between innate and adaptive immune systems in AOSD is limited. This study aimed to examine the peripheral immune cell composition and inflammatory protein levels in AOSD patients. METHODS Twenty-nine active AOSD patients were enrolled. Flow cytometry was used to analyse the cell populations in peripheral blood. Antibody chips were utilized to detect the protein expression profile in serum. RESULTS In active AOSD patients, there was an increase in the percentage of classical and non-classical monocytes among peripheral blood mononuclear cells. The proportion of natural killer (NK) cells decreased, with an increase in CD56dim NK1 cells and a decrease in CD56bright NK2 cells compared with healthy controls (HCs). The percentage of naïve central memory T cells was decreased, while the percentage of effector and effector memory T cells was increased among adaptive lymphocytes. The proportion of naïve B and memory B cells was decreased, while plasma cells were increased in AOSD patients, indicating activation of the adaptive immune system. Additionally, the serum levels of 40 proteins were elevated in AOSD patients, primarily involved in cytokine-cytokine receptor interaction, inflammatory response and regulation of mitogen-activated protein kinase cascade. CONCLUSION Our findings showed the activation of the innate and adaptive immune system in AOSD. The protein-protein interaction analysis suggested potential communication between innate and adaptive cell subsets. These findings provide new insights into the pathogenesis of the disease and the development of targeted therapies.
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Affiliation(s)
- Huihui Chi
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinyue Hong
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ningqi Dai
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Longfang Chen
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hao Zhang
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Honglei Liu
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaobing Cheng
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junna Ye
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hui Shi
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiongyi Hu
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jianfen Meng
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhuochao Zhou
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jinchao Jia
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tingting Liu
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fan Wang
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mengyan Wang
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuning Ma
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xia Chen
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yijun You
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dehao Zhu
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zihan Tang
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chengde Yang
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jialin Teng
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yutong Su
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yue Sun
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Singh MK, Rallabandi HR, Zhou XJ, Qi YY, Zhao ZZ, Gan T, Zhang H, Looger LL, Nath SK. KLF2 enhancer variant rs4808485 increases lupus risk by modulating inflammasome machinery and cellular homoeostasis. Ann Rheum Dis 2024; 83:879-888. [PMID: 38373841 PMCID: PMC11168881 DOI: 10.1136/ard-2023-224953] [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: 09/01/2023] [Accepted: 02/01/2024] [Indexed: 02/21/2024]
Abstract
OBJECTIVE A recent genome-wide association study linked KLF2 as a novel Asian-specific locus for systemic lupus erythematosus (SLE) susceptibility. However, the underlying causal functional variant(s), cognate target gene(s) and genetic mechanisms associated with SLE risk are unknown. METHODS We used bioinformatics to prioritise likely functional variants and validated the best candidate with diverse experimental techniques, including genome editing. Gene expression was compared between healthy controls (HCs) and patients with SLE with or without lupus nephritis (LN+, LN-). RESULTS Through bioinformatics and expression quantitative trait locus analyses, we prioritised rs4808485 in active chromatin, predicted to modulate KLF2 expression. Luciferase reporter assays and chromatin immunoprecipitation-qPCR demonstrated differential allele-specific enhancer activity and binding of active histone marks (H3K27ac, H3K4me3 and H3K4me1), Pol II, CTCF, P300 and the transcription factor PARP1. Chromosome conformation capture-qPCR revealed long-range chromatin interactions between rs4808485 and the KLF2 promoter. These were directly validated by CRISPR-based genetic and epigenetic editing in Jurkat and lymphoblastoid cells. Deleting the rs4808485 enhancer in Jurkat (KO) cells disrupted NLRP3 inflammasome machinery by reducing KLF2 and increasing CASPASE1, IL-1β and GSDMD levels. Knockout cells also exhibited higher proliferation and cell-cycle progression than wild type. RNA-seq validated interplay between KLF2 and inflammasome machinery in HC, LN+ and LN-. CONCLUSIONS We demonstrate how rs4808485 modulates the inflammasome and cellular homoeostasis through regulating KLF2 expression. This establishes mechanistic connections between rs4808485 and SLE susceptibility.
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Affiliation(s)
- Manish Kumar Singh
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Harikrishna Reddy Rallabandi
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Xu-Jie Zhou
- Renal Division, Peking University Institute of Nephrology, Peking University First Hospital, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Yuan-Yuan Qi
- Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
| | - Zhan-Zheng Zhao
- Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
| | - Ting Gan
- Renal Division, Peking University Institute of Nephrology, Peking University First Hospital, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
| | - Hong Zhang
- Renal Division, Peking University Institute of Nephrology, Peking University First Hospital, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
| | - Loren L Looger
- Howard Hughes Medical Institute, Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Swapan K Nath
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
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13
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Tsuchiya H, Ota M, Takahashi H, Hatano H, Ogawa M, Nakajima S, Yoshihara R, Okamura T, Sumitomo S, Fujio K. Epigenetic targets of Janus kinase inhibitors are linked to genetic risks of rheumatoid arthritis. Inflamm Regen 2024; 44:29. [PMID: 38831367 PMCID: PMC11149281 DOI: 10.1186/s41232-024-00337-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 05/15/2024] [Indexed: 06/05/2024] Open
Abstract
BACKGROUND Current strategies that target cytokines (e.g., tumor necrosis factor (TNF)-α), or signaling molecules (e.g., Janus kinase (JAK)) have advanced the management for allergies and autoimmune diseases. Nevertheless, the molecular mechanism that underpins its clinical efficacy have largely remained elusive, especially in the local tissue environment. Here, we aimed to identify the genetic, epigenetic, and immunological targets of JAK inhibitors (JAKis), focusing on their effects on synovial fibroblasts (SFs), the major local effectors associated with destructive joint inflammation in rheumatoid arthritis (RA). METHODS SFs were activated by cytokines related to inflammation in RA, and were treated with three types of JAKis or a TNF-α inhibitor (TNFi). Dynamic changes in transcriptome and chromatin accessibility were profiled across samples to identify drug targets. Furthermore, the putative targets were validated using luciferase assays and clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing. RESULTS We found that both JAKis and the TNFi targeted the inflammatory module including IL6. Conversely, specific gene signatures that were preferentially inhibited by either of the drug classes were identified. Strikingly, RA risk enhancers for CD40 and TRAF1 were distinctively regulated by JAKis and the TNFi. We performed luciferase assays and CRISPR-based genome editing, and successfully fine-mapped the single causal variants in these loci, rs6074022-CD40 and rs7021049-TRAF1. CONCLUSIONS JAKis and the TNFi had a direct impact on different RA risk enhancers, and we identified nucleotide-resolution targets for both drugs. Distinctive targets of clinically effective drugs could be useful for tailoring the application of these drugs and future design of more efficient treatment strategies.
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Affiliation(s)
- Haruka Tsuchiya
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Mineto Ota
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Haruka Takahashi
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Hiroaki Hatano
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Megumi Ogawa
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Sotaro Nakajima
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Risa Yoshihara
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Tomohisa Okamura
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Shuji Sumitomo
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Keishi Fujio
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan.
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14
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Xu LL, Gan T, Li Y, Chen P, Shi SF, Liu LJ, Lv JC, Zhang H, Zhou XJ. Combined Genetic Association and Differed Expression Analysis of UBE2L3 Uncovers a Genetic Regulatory Role of (Immuno)proteasome in IgA Nephropathy. KIDNEY DISEASES (BASEL, SWITZERLAND) 2024; 10:167-180. [PMID: 38835407 PMCID: PMC11149991 DOI: 10.1159/000537987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/20/2024] [Indexed: 06/06/2024]
Abstract
Introduction IgA nephropathy (IgAN) is a leading cause of end-stage renal disease. The exact pathogenesis of IgAN is not well defined, but some genetic studies have led to a novel discovery that the (immuno)proteasome probably plays an important role in IgAN. Methods We firstly analyzed the association of variants in the UBE2L3 region with susceptibility to IgAN in 3,495 patients and 9,101 controls, and then analyzed the association between lead variant and clinical phenotypes in 1,803 patients with regular follow-up data. The blood mRNA levels of members of the ubiquitin-proteasome system including UBE2L3 were analyzed in peripheral blood mononuclear cells from 53 patients and 28 healthy controls. The associations between UBE2L3 and the expression levels of genes involved in Gd-IgA1 production were also explored. Results The rs131654 showed the most significant association signal in UBE2L3 region (OR: 1.10, 95% CI: 1.04-1.16, p = 2.29 × 10-3), whose genotypes were also associated with the levels of Gd-IgA1 (p = 0.04). The rs131654 was observed to exert cis-eQTL effects on UBE2L3 in various tissues and cell types, particularly in immune cell types in multiple databases. The UBE2L3, LUBAC, and proteasome subunits were highly expressed in patients compared with healthy controls. High expression levels of UBE2L3 were not only associated with higher proteinuria (r = 0.34, p = 0.01) and lower eGFR (r = -0.28, p = 0.04), but also positively correlated with the gene expression of LUBAC and other proteasome subunits. Additionally, mRNA expression levels of UBE2L3 were also positively correlated with IL-6 and RELA, but negatively correlated with the expression levels of the key enzyme in the process of glycosylation including C1GALT1 and C1GALT1C1. Conclusion In conclusion, by combined genetic association and differed expression analysis of UBE2L3, our data support a role of genetically conferred dysregulation of the (immuno)proteasome in regulating galactose-deficient IgA1 in the development of IgAN.
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Affiliation(s)
- Lin-Lin Xu
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Ting Gan
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Yang Li
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Pei Chen
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Su-Fang Shi
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Li-Jun Liu
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Ji-Cheng Lv
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
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Kasher M, Freidin MB, Williams FMK, Cherny SS, Ashkenazi S, Livshits G. Glycoprotein Acetyls Is a Novel Biomarker Predicting Cardiovascular Complications in Rheumatoid Arthritis. Int J Mol Sci 2024; 25:5981. [PMID: 38892172 PMCID: PMC11173129 DOI: 10.3390/ijms25115981] [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: 04/30/2024] [Revised: 05/25/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
Abstract
The relationship between rheumatoid arthritis (RA) and early onset atherosclerosis is well depicted, each with an important inflammatory component. Glycoprotein acetyls (GlycA), a novel biomarker of inflammation, may play a role in the manifestation of these two inflammatory conditions. The present study examined a potential mediating role of GlycA within the RA-atherosclerosis relationship to determine whether it accounts for the excess risk of cardiovascular disease over that posed by lipid risk factors. The UK Biobank dataset was acquired to establish associations among RA, atherosclerosis, GlycA, and major lipid factors: total cholesterol (TC), high- and low-density lipoprotein (HDL, LDL) cholesterol, and triglycerides (TGs). Genome-wide association study summary statistics were collected from various resources to perform genetic analyses. Causality among variables was tested using Mendelian Randomization (MR) analysis. Genes of interest were identified using colocalization analysis and gene enrichment analysis. MR results appeared to indicate that the genetic relationship between GlycA and RA and also between RA and atherosclerosis was explained by horizontal pleiotropy (p-value = 0.001 and <0.001, respectively), while GlycA may causally predict atherosclerosis (p-value = 0.017). Colocalization analysis revealed several functionally relevant genes shared between GlycA and all the variables assessed. Two loci were apparent in all relationships tested and included the HLA region as well as SLC22A1. GlycA appears to mediate the RA-atherosclerosis relationship through several possible pathways. GlycA, although pleiotropically related to RA, appears to causally predict atherosclerosis. Thus, GlycA is suggested as a significant factor in the etiology of atherosclerosis development in RA.
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Affiliation(s)
- Melody Kasher
- Department of Morphological Sciences, Adelson School of Medicine, Ariel University, Ariel 4070000, Israel; (M.K.); (S.A.)
| | - Maxim B. Freidin
- Department of Biology, School of Biological and Behavioural Sciences, Queen Mary University of London, London E1 4NS, UK;
| | - Frances M. K. Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, London WC2R 2LS, UK;
| | - Stacey S. Cherny
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel;
- Department of Epidemiology and Preventive Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Shai Ashkenazi
- Department of Morphological Sciences, Adelson School of Medicine, Ariel University, Ariel 4070000, Israel; (M.K.); (S.A.)
| | - Gregory Livshits
- Department of Morphological Sciences, Adelson School of Medicine, Ariel University, Ariel 4070000, Israel; (M.K.); (S.A.)
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, London WC2R 2LS, UK;
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel;
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16
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Inamo J, Suzuki A, Ueda MT, Yamaguchi K, Nishida H, Suzuki K, Kaneko Y, Takeuchi T, Hatano H, Ishigaki K, Ishihama Y, Yamamoto K, Kochi Y. Long-read sequencing for 29 immune cell subsets reveals disease-linked isoforms. Nat Commun 2024; 15:4285. [PMID: 38806455 PMCID: PMC11133395 DOI: 10.1038/s41467-024-48615-4] [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: 12/04/2022] [Accepted: 05/02/2024] [Indexed: 05/30/2024] Open
Abstract
Alternative splicing events are a major causal mechanism for complex traits, but they have been understudied due to the limitation of short-read sequencing. Here, we generate a full-length isoform annotation of human immune cells from an individual by long-read sequencing for 29 cell subsets. This contains a number of unannotated transcripts and isoforms such as a read-through transcript of TOMM40-APOE in the Alzheimer's disease locus. We profile characteristics of isoforms and show that repetitive elements significantly explain the diversity of unannotated isoforms, providing insight into the human genome evolution. In addition, some of the isoforms are expressed in a cell-type specific manner, whose alternative 3'-UTRs usage contributes to their specificity. Further, we identify disease-associated isoforms by isoform switch analysis and by integration of several quantitative trait loci analyses with genome-wide association study data. Our findings will promote the elucidation of the mechanism of complex diseases via alternative splicing.
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Affiliation(s)
- Jun Inamo
- Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, 113-8510, Japan
- Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, 160-8582, Japan
| | - Akari Suzuki
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - Mahoko Takahashi Ueda
- Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, 113-8510, Japan
| | - Kensuke Yamaguchi
- Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, 113-8510, Japan
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
- Biomedical Engineering Research Innovation Center, Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University (TMDU), Tokyo, 113-8510, Japan
| | - Hiroshi Nishida
- Department of Molecular Systems Bioanalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, 606-8501, Japan
| | - Katsuya Suzuki
- Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, 160-8582, Japan
| | - Yuko Kaneko
- Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, 160-8582, Japan
| | - Tsutomu Takeuchi
- Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, 160-8582, Japan
- Saitama Medical University, 38 Morohongo, Moroyama, Iruma, Saitama, 350-0495, Japan
| | - Hiroaki Hatano
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - Yasushi Ishihama
- Department of Molecular Systems Bioanalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, 606-8501, Japan
- Laboratory of Proteomics for Drug Discovery, National Institute of Biomedical Innovation, Health and Nutrition, Ibaraki, Osaka, 567-0085, Japan
| | - Kazuhiko Yamamoto
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - Yuta Kochi
- Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, 113-8510, Japan.
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.
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Koido M, Tomizuka K, Terao C. Fundamentals for predicting transcriptional regulations from DNA sequence patterns. J Hum Genet 2024:10.1038/s10038-024-01256-3. [PMID: 38730006 DOI: 10.1038/s10038-024-01256-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 04/10/2024] [Accepted: 04/25/2024] [Indexed: 05/12/2024]
Abstract
Cell-type-specific regulatory elements, cataloged through extensive experiments and bioinformatics in large-scale consortiums, have enabled enrichment analyses of genetic associations that primarily utilize positional information of the regulatory elements. These analyses have identified cell types and pathways genetically associated with human complex traits. However, our understanding of detailed allelic effects on these elements' activities and on-off states remains incomplete, hampering the interpretation of human genetic study results. This review introduces machine learning methods to learn sequence-dependent transcriptional regulation mechanisms from DNA sequences for predicting such allelic effects (not associations). We provide a concise history of machine-learning-based approaches, the requirements, and the key computational processes, focusing on primers in machine learning. Convolution and self-attention, pivotal in modern deep-learning models, are explained through geometrical interpretations using dot products. This facilitates understanding of the concept and why these have been used for machine learning for DNA sequences. These will inspire further research in this genetics and genomics field.
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Affiliation(s)
- Masaru Koido
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan.
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan.
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18
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Khatri R, Machart P, Bonn S. DISSECT: deep semi-supervised consistency regularization for accurate cell type fraction and gene expression estimation. Genome Biol 2024; 25:112. [PMID: 38689377 PMCID: PMC11061925 DOI: 10.1186/s13059-024-03251-5] [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: 07/10/2023] [Accepted: 04/17/2024] [Indexed: 05/02/2024] Open
Abstract
Cell deconvolution is the estimation of cell type fractions and cell type-specific gene expression from mixed data. An unmet challenge in cell deconvolution is the scarcity of realistic training data and the domain shift often observed in synthetic training data. Here, we show that two novel deep neural networks with simultaneous consistency regularization of the target and training domains significantly improve deconvolution performance. Our algorithm, DISSECT, outperforms competing algorithms in cell fraction and gene expression estimation by up to 14 percentage points. DISSECT can be easily adapted to other biomedical data types, as exemplified by our proteomic deconvolution experiments.
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Affiliation(s)
- Robin Khatri
- Institute of Medical Systems Biology, Center for Molecular Neurobiology, Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Pierre Machart
- Institute of Medical Systems Biology, Center for Molecular Neurobiology, Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stefan Bonn
- Institute of Medical Systems Biology, Center for Molecular Neurobiology, Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
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19
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Reyna J, Fetter K, Ignacio R, Marandi CCA, Rao N, Jiang Z, Figueroa DS, Bhattacharyya S, Ay F. Loop Catalog: a comprehensive HiChIP database of human and mouse samples. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.26.591349. [PMID: 38746164 PMCID: PMC11092438 DOI: 10.1101/2024.04.26.591349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
HiChIP enables cost-effective and high-resolution profiling of regulatory and structural loops. To leverage the increasing number of publicly available HiChIP datasets from diverse cell lines and primary cells, we developed the Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring HiChIP loop calls for 1319 samples across 133 studies and 44 high-resolution Hi-C loop calls. We demonstrate its utility in interpreting fine-mapped GWAS variants (SNP-to-gene linking), in identifying enriched sequence motifs and motif pairs at loop anchors, and in network-level analysis of loops connecting regulatory elements (community detection). Our comprehensive catalog, spanning over 4M unique 5kb loops, along with the accompanying analysis modalities constitutes an important resource for studies in gene regulation and genome organization.
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Affiliation(s)
- Joaquin Reyna
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
| | - Kyra Fetter
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093 USA
| | - Romeo Ignacio
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
| | - Cemil Can Ali Marandi
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
| | - Nikhil Rao
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA 92093 USA
| | - Zichen Jiang
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Department of Mathematics, University of California San Diego, La Jolla, CA 92093 USA
| | - Daniela Salgado Figueroa
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
| | - Sourya Bhattacharyya
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
| | - Ferhat Ay
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA 92093 USA
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20
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Hitomi Y, Ueno K, Aiba Y, Nishida N, Kono M, Sugihara M, Kawai Y, Kawashima M, Khor SS, Sugi K, Kouno H, Kohno H, Naganuma A, Iwamoto S, Katsushima S, Furuta K, Nikami T, Mannami T, Yamashita T, Ario K, Komatsu T, Makita F, Shimada M, Hirashima N, Yokohama S, Nishimura H, Sugimoto R, Komura T, Ota H, Kojima M, Nakamuta M, Fujimori N, Yoshizawa K, Mano Y, Takahashi H, Hirooka K, Tsuruta S, Sato T, Yamasaki K, Kugiyama Y, Motoyoshi Y, Suehiro T, Saeki A, Matsumoto K, Nagaoka S, Abiru S, Yatsuhashi H, Ito M, Kawata K, Takaki A, Arai K, Arinaga-Hino T, Abe M, Harada M, Taniai M, Zeniya M, Ohira H, Shimoda S, Komori A, Tanaka A, Ishigaki K, Nagasaki M, Tokunaga K, Nakamura M. A genome-wide association study identified PTPN2 as a population-specific susceptibility gene locus for primary biliary cholangitis. Hepatology 2024:01515467-990000000-00853. [PMID: 38652555 DOI: 10.1097/hep.0000000000000894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/22/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND AND AIMS Previous genome-wide association studies (GWAS) have indicated the involvement of shared (population-nonspecific) and nonshared (population-specific) susceptibility genes in the pathogenesis of primary biliary cholangitis (PBC) among European and East-Asian populations. Although a meta-analysis of these distinct populations has recently identified more than 20 novel PBC susceptibility loci, analyses of population-specific genetic architecture are still needed for a more comprehensive search for genetic factors in PBC. APPROACH AND RESULTS Protein tyrosine phosphatase nonreceptor type 2 ( PTPN2) was identified as a novel PBC susceptibility gene locus through GWAS and subsequent genome-wide meta-analysis involving 2181 cases and 2699 controls from the Japanese population (GWAS-lead variant: rs8098858, p = 2.6 × 10 -8 ). In silico and in vitro functional analyses indicated that the risk allele of rs2292758, which is a primary functional variant, decreases PTPN2 expression by disrupting Sp1 binding to the PTPN2 promoter in T follicular helper cells and plasmacytoid dendritic cells. Infiltration of PTPN2-positive T-cells and plasmacytoid dendritic cells was confirmed in the portal area of the PBC liver by immunohistochemistry. Furthermore, transcriptomic analysis of PBC-liver samples indicated the presence of a compromised negative feedback loop in vivo between PTPN2 and IFNG in patients carrying the risk allele of rs2292758. CONCLUSIONS PTPN2 , a novel susceptibility gene for PBC in the Japanese population, may be involved in the pathogenesis of PBC through an insufficient negative feedback loop caused by the risk allele of rs2292758 in IFN-γ signaling. This suggests that PTPN2 could be a potential molecular target for PBC treatment.
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Affiliation(s)
- Yuki Hitomi
- Department of Human Genetics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Kazuko Ueno
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Yoshihiro Aiba
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Nao Nishida
- The Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Ichikawa, Japan
- Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
| | - Michihiro Kono
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Mitsuki Sugihara
- Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
| | - Yosuke Kawai
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | | | - Seik-Soon Khor
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Kazuhiro Sugi
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Hirotaka Kouno
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Hiroshi Kohno
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Atsushi Naganuma
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Satoru Iwamoto
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Shinji Katsushima
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Kiyoshi Furuta
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Toshiki Nikami
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Tomohiko Mannami
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Tsutomu Yamashita
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Keisuke Ario
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Tatsuji Komatsu
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Fujio Makita
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Masaaki Shimada
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Noboru Hirashima
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Shiro Yokohama
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Hideo Nishimura
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Rie Sugimoto
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Takuya Komura
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Hajime Ota
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Motoyuki Kojima
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Makoto Nakamuta
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Naoyuki Fujimori
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Kaname Yoshizawa
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Yutaka Mano
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Hironao Takahashi
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Kana Hirooka
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Satoru Tsuruta
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Takeaki Sato
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Kazumi Yamasaki
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Yuki Kugiyama
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | | | - Tomoyuki Suehiro
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Akira Saeki
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Kosuke Matsumoto
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Shinya Nagaoka
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Seigo Abiru
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | | | - Masahiro Ito
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
| | - Kazuhito Kawata
- Hepatology Division, Department of Internal Medicine II, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Akinobu Takaki
- Department of Gastroenterology and Hepatology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Kuniaki Arai
- Department of Gastroenterology, Kanazawa University Graduate School of Medicine, Kanazawa, Japan
| | - Teruko Arinaga-Hino
- Division of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Kurume, Japan
| | - Masanori Abe
- Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine, Matsuyama, Japan
| | - Masaru Harada
- The Third Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Makiko Taniai
- Department of Medicine and Gastroenterology, Tokyo Women's Medical University, Tokyo, Japan
| | - Mikio Zeniya
- Department of Gastroenterology and Hepatology, Tokyo Jikei University School of Medicine, Tokyo, Japan
| | - Hiromasa Ohira
- Department of Gastroenterology, Fukushima Medical University, Fukushima, Japan
| | - Shinji Shimoda
- Division of Gastroenterology and Hepatology, Third Department of Internal Medicine, Kansai Medical University, Hirakata, Japan
| | - Atsumasa Komori
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
- Department of Hepatology, Nagasaki University Graduate School of Biomedical Sciences, Omura, Japan
| | - Atsushi Tanaka
- Department of Medicine, Teikyo University School of Medicine, Tokyo, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masao Nagasaki
- Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
- Human Biosciences Unit for the Top Global Course Center for the Promotion of Interdisciplinary Education and Research, Kyoto University, Kyoto, Japan
| | - Katsushi Tokunaga
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Minoru Nakamura
- Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
- Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
- Department of Hepatology, Nagasaki University Graduate School of Biomedical Sciences, Omura, Japan
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21
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Tremmel R, Martínez Pereyra V, Broders I, Schaeffeler E, Hoffmann P, Nöthen MM, Bekeredjian R, Sechtem U, Schwab M, Ong P. Genetic associations of cardiovascular risk genes in European patients with coronary artery spasm. Clin Res Cardiol 2024:10.1007/s00392-024-02446-x. [PMID: 38635033 DOI: 10.1007/s00392-024-02446-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 03/27/2024] [Indexed: 04/19/2024]
Abstract
BACKGROUND Coronary artery spasm (CAS) is a frequent finding in patients presenting with angina pectoris. Although the pathogenesis of CAS is incompletely understood, previous studies suggested a genetic contribution. Our study aimed to elucidate genetic variants in a cohort of European patients with angina and unobstructed coronary arteries who underwent acetylcholine (ACh) provocation testing. METHODS A candidate association analysis of 208 genes previously associated with cardiovascular conditions was performed using genotyped and imputed variants in patients grouped in epicardial (focal, diffuse) CAS (n = 119) and microvascular CAS (n = 87). Patients with a negative ACh test result (n = 45) served as controls. RESULTS We found no association below the genome-wide significance threshold of p < 5 × 10-8, thus not confirming variants in ALDH2, NOS3, and ROCK2 previously reported in CAS patients of Asian ancestry. However, the analysis identified suggestive associations (p < 10-05) for the groups of focal epicardial CAS (CDH13) and diffuse epicardial CAS (HDAC9, EDN1). Downstream analysis of the potential EDN1 risk locus showed that CAS patients have significantly increased plasma endothelin-1 levels (ET-1) compared to controls. An EDN1 haplotype comprising rs9349379 and rs2070698 was significantly associated to ET-1 levels (p = 0.01). CONCLUSIONS In summary, we suggest EDN1 as potential genetic risk loci for patients with diffuse epicardial CAS, and European ancestry. Plasma ET-1 levels may serve as a potential cardiac marker.
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Affiliation(s)
- Roman Tremmel
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Valeria Martínez Pereyra
- Department of Cardiology and Angiology, Robert-Bosch-Hospital, Auerbachstr. 110, 70376, Stuttgart, Germany
| | - Incifer Broders
- Department of Cardiology and Angiology, Robert-Bosch-Hospital, Auerbachstr. 110, 70376, Stuttgart, Germany
| | - Elke Schaeffeler
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Raffi Bekeredjian
- Department of Cardiology and Angiology, Robert-Bosch-Hospital, Auerbachstr. 110, 70376, Stuttgart, Germany
| | - Udo Sechtem
- Department of Cardiology and Angiology, Robert-Bosch-Hospital, Auerbachstr. 110, 70376, Stuttgart, Germany
| | - Matthias Schwab
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- Departments of Clinical Pharmacology, and Pharmacy and Biochemistry, University of Tübingen, Tübingen, Germany
- University of Tübingen, Tübingen, Germany
| | - Peter Ong
- Department of Cardiology and Angiology, Robert-Bosch-Hospital, Auerbachstr. 110, 70376, Stuttgart, Germany.
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22
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Zhu X, Chen Y, Yin Z, Zhang Y, Shen Y, Dai D, Lin X, Zou LH, Shen N, Ye Z, Ding H, Hou G. Novel potential lncRNA biomarker in B cells indicates essential pathogenic pathway activation in patients with SLE. Lupus Sci Med 2024; 11:e001065. [PMID: 38599668 PMCID: PMC11015226 DOI: 10.1136/lupus-2023-001065] [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: 09/28/2023] [Accepted: 04/01/2024] [Indexed: 04/12/2024]
Abstract
OBJECTIVES Systemic lupus erythematosus (SLE) is a highly heterogeneous disease, and B cell abnormalities play a central role in the pathogenesis of SLE. Long non-coding RNAs (lncRNAs) have also been implicated in the pathogenesis of SLE. The expression of lncRNAs is finely regulated and cell-type dependent, so we aimed to identify B cell-expressing lncRNAs as biomarkers for SLE, and to explore their ability to reflect the status of SLE critical pathway and disease activity. METHODS Weighted gene coexpression network analysis (WGCNA) was used to cluster B cell-expressing genes of patients with SLE into different gene modules and relate them to clinical features. Based on the results of WGCNA, candidate lncRNA levels were further explored in public bulk and single-cell RNA-sequencing data. In another independent cohort, the levels of the candidate were detected by RT-qPCR and the correlation with disease activity was analysed. RESULTS WGCNA analysis revealed one gene module significantly correlated with clinical features, which was enriched in type I interferon (IFN) pathway. Among non-coding genes in this module, lncRNA RP11-273G15.2 was differentially expressed in all five subsets of B cells from patients with SLE compared with healthy controls and other autoimmune diseases. RT-qPCR validated that RP11-273G15.2 was highly expressed in SLE B cells and positively correlated with IFN scores (r=0.7329, p<0.0001) and disease activity (r=0.4710, p=0.0005). CONCLUSION RP11-273G15.2 could act as a diagnostic and disease activity monitoring biomarker for SLE, which might have the potential to guide clinical management.
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Affiliation(s)
- Xinyi Zhu
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, China
| | - Yashuo Chen
- Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, Guangdong, China
| | - Zhihua Yin
- Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, Guangdong, China
| | - Yutong Zhang
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, China
| | - Yiwei Shen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, China
| | - Dai Dai
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, China
| | - Xiaojing Lin
- Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, Guangdong, China
| | - Ling-Hua Zou
- Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, Guangdong, China
| | - Nan Shen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, China
| | - Zhizhong Ye
- Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, Guangdong, China
| | - Huihua Ding
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, China
| | - Guojun Hou
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, China
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23
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de Smith AJ, Wahlster L, Jeon S, Kachuri L, Black S, Langie J, Cato LD, Nakatsuka N, Chan TF, Xia G, Mazumder S, Yang W, Gazal S, Eng C, Hu D, Burchard EG, Ziv E, Metayer C, Mancuso N, Yang JJ, Ma X, Wiemels JL, Yu F, Chiang CWK, Sankaran VG. A noncoding regulatory variant in IKZF1 increases acute lymphoblastic leukemia risk in Hispanic/Latino children. CELL GENOMICS 2024; 4:100526. [PMID: 38537633 PMCID: PMC11019360 DOI: 10.1016/j.xgen.2024.100526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 12/11/2023] [Accepted: 02/27/2024] [Indexed: 04/04/2024]
Abstract
Hispanic/Latino children have the highest risk of acute lymphoblastic leukemia (ALL) in the US compared to other racial/ethnic groups, yet the basis of this remains incompletely understood. Through genetic fine-mapping analyses, we identified a new independent childhood ALL risk signal near IKZF1 in self-reported Hispanic/Latino individuals, but not in non-Hispanic White individuals, with an effect size of ∼1.44 (95% confidence interval = 1.33-1.55) and a risk allele frequency of ∼18% in Hispanic/Latino populations and <0.5% in European populations. This risk allele was positively associated with Indigenous American ancestry, showed evidence of selection in human history, and was associated with reduced IKZF1 expression. We identified a putative causal variant in a downstream enhancer that is most active in pro-B cells and interacts with the IKZF1 promoter. This variant disrupts IKZF1 autoregulation at this enhancer and results in reduced enhancer activity in B cell progenitors. Our study reveals a genetic basis for the increased ALL risk in Hispanic/Latino children.
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Affiliation(s)
- Adam J de Smith
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA.
| | - Lara Wahlster
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Soyoung Jeon
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Susan Black
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jalen Langie
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Liam D Cato
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Tsz-Fung Chan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Guangze Xia
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
| | - Soumyaa Mazumder
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Wenjian Yang
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Steven Gazal
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Celeste Eng
- Department of Medicine, Institute for Human Genetics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Bioengineering and Biotherapeutic Sciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Donglei Hu
- Department of Medicine, Institute for Human Genetics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Esteban González Burchard
- Department of Medicine, Institute for Human Genetics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Bioengineering and Biotherapeutic Sciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Elad Ziv
- Department of Medicine, Institute for Human Genetics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Catherine Metayer
- School of Public Health, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Jun J Yang
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Xiaomei Ma
- Yale School of Public Health, New Haven, CT 06520, USA
| | - Joseph L Wiemels
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Fulong Yu
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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24
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Goto M, Takahashi H, Yoshida R, Itamiya T, Nakano M, Nagafuchi Y, Harada H, Shimizu T, Maeda M, Kubota A, Toda T, Hatano H, Sugimori Y, Kawahata K, Yamamoto K, Shoda H, Ishigaki K, Ota M, Okamura T, Fujio K. Age-associated CD4 + T cells with B cell-promoting functions are regulated by ZEB2 in autoimmunity. Sci Immunol 2024; 9:eadk1643. [PMID: 38330141 DOI: 10.1126/sciimmunol.adk1643] [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: 08/06/2023] [Accepted: 02/01/2024] [Indexed: 02/10/2024]
Abstract
Aging is a significant risk factor for autoimmunity, and many autoimmune diseases tend to onset during adulthood. We conducted an extensive analysis of CD4+ T cell subsets from 354 patients with autoimmune disease and healthy controls via flow cytometry and bulk RNA sequencing. As a result, we identified a distinct CXCR3midCD4+ effector memory T cell subset that expands with age, which we designated "age-associated T helper (THA) cells." THA cells exhibited both a cytotoxic phenotype and B cell helper functions, and these features were regulated by the transcription factor ZEB2. Consistent with the highly skewed T cell receptor usage of THA cells, gene expression in THA cells from patients with systemic lupus erythematosus reflected disease activity and was affected by treatment with a calcineurin inhibitor. Moreover, analysis of single-cell RNA sequencing data revealed that THA cells infiltrate damaged organs in patients with autoimmune diseases. Together, our characterization of THA cells may facilitate improved understanding of the relationship between aging and autoimmune diseases.
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Affiliation(s)
- Manaka Goto
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Hideyuki Takahashi
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Ryochi Yoshida
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Takahiro Itamiya
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Masahiro Nakano
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Yasuo Nagafuchi
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Hiroaki Harada
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Toshiaki Shimizu
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Meiko Maeda
- Department of Neurology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Akatsuki Kubota
- Department of Neurology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Tatsushi Toda
- Department of Neurology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Hiroaki Hatano
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Yusuke Sugimori
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Kimito Kawahata
- Department of Rheumatology and Allergology, St. Marianna University School of Medicine, Kawasaki, Kanagawa, Japan
| | - Kazuhiko Yamamoto
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Hirofumi Shoda
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Mineto Ota
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Tomohisa Okamura
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Keishi Fujio
- Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
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25
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Lin W, Wall JD, Li G, Newman D, Yang Y, Abney M, VandeBerg JL, Olivier M, Gilad Y, Cox LA. Genetic regulatory effects in response to a high-cholesterol, high-fat diet in baboons. CELL GENOMICS 2024; 4:100509. [PMID: 38430910 PMCID: PMC10943580 DOI: 10.1016/j.xgen.2024.100509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 11/20/2023] [Accepted: 02/05/2024] [Indexed: 03/05/2024]
Abstract
Steady-state expression quantitative trait loci (eQTLs) explain only a fraction of disease-associated loci identified through genome-wide association studies (GWASs), while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Using a baboon model, we found hundreds of eQTLs that emerge in adipose, liver, and muscle after prolonged exposure to high dietary fat and cholesterol. Diet-responsive eQTLs exhibit genomic localization and genic features that are distinct from steady-state eQTLs. Furthermore, the human orthologs associated with diet-responsive eQTLs are enriched for GWAS genes associated with human metabolic traits, suggesting that context-responsive eQTLs with more complex regulatory effects are likely to explain GWAS hits that do not seem to overlap with standard eQTLs. Our results highlight the complexity of genetic regulatory effects and the potential of eQTLs with disease-relevant GxE interactions in enhancing the understanding of GWAS signals for human complex disease using non-human primate models.
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Affiliation(s)
- Wenhe Lin
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA.
| | - Jeffrey D Wall
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Ge Li
- Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Deborah Newman
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX 78229, USA
| | - Yunqi Yang
- Committee on Genetics, Genomics and System Biology, The University of Chicago, Chicago, IL 60637, USA
| | - Mark Abney
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
| | - John L VandeBerg
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA
| | - Michael Olivier
- Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Yoav Gilad
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA; Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL 60637, USA.
| | - Laura A Cox
- Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX 78229, USA.
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26
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Zhou Z, Du J, Wang J, Liu L, Gordon MG, Ye CJ, Powell JE, Li MJ, Rao S. SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues. Database (Oxford) 2024; 2024:baae010. [PMID: 38459946 PMCID: PMC10924434 DOI: 10.1093/database/baae010] [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: 09/04/2023] [Revised: 01/09/2024] [Accepted: 02/11/2024] [Indexed: 03/11/2024]
Abstract
Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches, which cannot shed light on the cell type- and environment-specific regulation of disease-associated genetic variants. Here, we introduce our Single-cell eQTL Interactive Database which collects single-cell eQTL (sc-eQTL) datasets and provides online visualization of sc-eQTLs across different cell types in a user-friendly manner. Although sc-eQTL mapping is still in its early stage, our database curates the most comprehensive summary statistics of sc-eQTLs published to date. sc-eQTL studies have revolutionized our understanding of gene regulation in specific cellular contexts, and we anticipate that our database will further accelerate the research of functional genomics. Database URL: http://www.sqraolab.com/scqtl.
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Affiliation(s)
- Zhiwei Zhou
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 288 Nanjing Road, Tianjin 300020, China
- Tianjin Institutes of Health Science, 28 Tuanbo Avenue, Tianjin 301600, China
| | - Jingyi Du
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 288 Nanjing Road, Tianjin 300020, China
- Tianjin Institutes of Health Science, 28 Tuanbo Avenue, Tianjin 301600, China
| | - Jianhua Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, 22 Qixiangtai Road, Tianjin 300070, China
| | - Liangyi Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 288 Nanjing Road, Tianjin 300020, China
| | - M Gracie Gordon
- Biological and Medical Informatics Graduate Program, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Division of Rheumatology, Department of Medicine, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Institute for Human Genetics, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
| | - Chun Jimmie Ye
- Division of Rheumatology, Department of Medicine, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Institute for Human Genetics, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Rosalind Russell/Ephraim P. Engleman Rheumatology Research Center, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Parker Institute for Cancer Immunotherapy, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Chan Zuckerberg Biohub, 499 Illinois Street, San Francisco, CA 94158, USA
- Bakar Computational Health Sciences Institute, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
| | - Joseph E Powell
- Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, 384 Victoria Street, Sydney, NSW 2010, Australia
- UNSW Cellular Genomics Futures Institute, University of New South Wales, UNSW Sydney, Sydney, NSW 2052, Australia
| | - Mulin Jun Li
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, 22 Qixiangtai Road, Tianjin 300070, China
| | - Shuquan Rao
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 288 Nanjing Road, Tianjin 300020, China
- Tianjin Institutes of Health Science, 28 Tuanbo Avenue, Tianjin 301600, China
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27
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Yamada S, Nagafuchi Y, Fujio K. Pathophysiology and stratification of treatment-resistant rheumatoid arthritis. Immunol Med 2024; 47:12-23. [PMID: 37462450 DOI: 10.1080/25785826.2023.2235734] [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: 04/23/2023] [Accepted: 07/09/2023] [Indexed: 02/23/2024] Open
Abstract
Early diagnosis and timely therapeutic intervention are clinical challenges of rheumatoid arthritis (RA), especially for treatment-resistant or difficult-to-treat patients. Little is known about the immunological mechanisms involved in refractory RA. In this review, we summarize previous research findings on the immunological mechanisms of treatment-resistant RA. Genetic prediction of treatment-resistant RA is challenging. Patients with and without anti-cyclic citrullinated peptide autoantibodies are considered part of distinct subgroups, especially regarding long-term clinical prognosis and treatment responses. B cells, T cells and other immune cells and fibroblasts are of pathophysiological importance and are associated with treatment responses. Finally, we propose a new hypothesis that stratifies patients with RA into two subgroups with distinct immunological pathologies based on our recent immunomics analysis of RA. One RA subgroup with a favorable prognosis is characterized by increased interferon signaling. Another subgroup with a worse prognosis is characterized by enhanced acquired immune responses. Increases in dendritic cell precursors and diversified autoreactive anti-modified protein antibodies may have pathophysiological roles, especially in the latter subgroup. These findings that improve treatment response predictions might contribute to future precision medicine for RA.
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Affiliation(s)
- Saeko Yamada
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yasuo Nagafuchi
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Keishi Fujio
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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28
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Zhu X, Zhang Y, Yin Z, Ye Z, Qin Y, Cheng Z, Shen Y, Yin Z, Ma J, Tang Y, Ding H, Guo Y, Hou G, Shen N. Three-Dimensional Chromosomal Landscape Revealing miR-146a Dysfunctional Enhancer in Lupus and Establishing a CRISPR-Mediated Approach to Inhibit the Interferon Pathway. Arthritis Rheumatol 2024; 76:384-395. [PMID: 37728419 DOI: 10.1002/art.42703] [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: 02/05/2023] [Revised: 08/28/2023] [Accepted: 09/12/2023] [Indexed: 09/21/2023]
Abstract
OBJECTIVE The diminished expression of microRNA-146a (miR-146a) in systemic lupus erythematosus (SLE) contributes to the aberrant activation of the interferon pathway. Despite its significance, the underlying mechanism driving this reduced expression remains elusive. Considering the integral role of enhancers in steering gene expression, our study seeks to pinpoint the SLE-affected enhancers responsible for modulating miR-146a expression. Additionally, we aim to elucidate the mechanisms by which these enhancers influence the contribution of miR-146a to the activation of the interferon pathway. METHODS Circular chromosome conformation capture sequencing and epigenomic profiles were applied to identify candidate enhancers of miR-146a. CRISPR activation was performed to screen functional enhancers. Differential analysis of chromatin accessibility was used to identify SLE-dysregulated enhancers, and the mechanism underlying enhancer dysfunction was investigated by analyzing transcription factor binding. The therapeutic value of a lupus-related enhancer was further evaluated by targeting it in the peripheral blood mononuclear cells (PBMCs) of patients with SLE through a CRISPR activation approach. RESULTS We identified shared and cell-specific enhancers of miR-146a in distinct immune cells. An enhancer 32.5 kb downstream of miR-146a possesses less accessibility in SLE, and its chromatin openness was negatively correlated with SLE disease activity. Moreover, CCAAT/enhancer binding protein α, a down-regulated transcription factor in patients with SLE, binds to the 32.5-kb enhancer and induces the epigenomic change of this locus. Furthermore, CRISPR-based activation of this enhancer in SLE PBMCs could inhibit the activity of interferon pathway. CONCLUSION Our work defines a promising target for SLE intervention. We adopted integrative approaches to define cell-specific and functional enhancers of the SLE critical gene and investigated the mechanism underlying its dysregulation mediated by a lupus-related enhancer.
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Affiliation(s)
- Xinyi Zhu
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China and Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, China
| | - Yutong Zhang
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zihang Yin
- Sheng Yushou Center of Cell Biology and Immunology, Shanghai Jiao Tong University, Shanghai, China
| | - Zhizhong Ye
- Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, China
| | - Yuting Qin
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhaorui Cheng
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiwei Shen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhihua Yin
- Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, China
| | - Jianyang Ma
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuanjia Tang
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huihua Ding
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ya Guo
- Sheng Yushou Center of Cell Biology and Immunology, Shanghai Jiao Tong University, Shanghai, China
| | - Guojun Hou
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China and Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, China
| | - Nan Shen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen, China, and Cincinnati Children's Hospital Medical Center and University of Cincinnati, Cincinnati, Ohio
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29
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Zhang Y, Hou G, Shen N. Non-coding DNA variants for risk in lupus. Best Pract Res Clin Rheumatol 2024:101937. [PMID: 38429183 DOI: 10.1016/j.berh.2024.101937] [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: 01/17/2024] [Revised: 02/08/2024] [Accepted: 02/12/2024] [Indexed: 03/03/2024]
Abstract
Systemic Lupus Erythematosus (SLE) is a multifactorial autoimmune disease that arises from a dynamic interplay between genetics and environmental triggers. The advent of sophisticated genomics technology has catalyzed a shift in our understanding of disease etiology, spotlighting the pivotal role of non-coding DNA variants in SLE pathogenesis. In this review, we present a comprehensive examination of the non-coding variants associated with SLE, shedding light on their role in influencing disease risk and progression. We discuss the latest methodological advancements that have been instrumental in the identification and functional characterization of these genomic elements, with a special focus on the transformative power of CRISPR-based gene-editing technologies. Additionally, the review probes into the therapeutic opportunities that arise from modulating non-coding regions associated with SLE. Through an exploration of the complex network of non-coding DNA, this review aspires to decode the genetic puzzle of SLE and set the stage for groundbreaking gene-based therapeutic interventions and the advancement of precision medicine strategies tailored to SLE management.
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Affiliation(s)
- Yutong Zhang
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, 200001, China
| | - Guojun Hou
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, 200001, China
| | - Nan Shen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, 200001, China.
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30
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Yasumizu Y, Takeuchi D, Morimoto R, Takeshima Y, Okuno T, Kinoshita M, Morita T, Kato Y, Wang M, Motooka D, Okuzaki D, Nakamura Y, Mikami N, Arai M, Zhang X, Kumanogoh A, Mochizuki H, Ohkura N, Sakaguchi S. Single-cell transcriptome landscape of circulating CD4 + T cell populations in autoimmune diseases. CELL GENOMICS 2024; 4:100473. [PMID: 38359792 PMCID: PMC10879034 DOI: 10.1016/j.xgen.2023.100473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 09/07/2023] [Accepted: 12/05/2023] [Indexed: 02/17/2024]
Abstract
CD4+ T cells are key mediators of various autoimmune diseases; however, their role in disease progression remains unclear due to cellular heterogeneity. Here, we evaluated CD4+ T cell subpopulations using decomposition-based transcriptome characterization and canonical clustering strategies. This approach identified 12 independent gene programs governing whole CD4+ T cell heterogeneity, which can explain the ambiguity of canonical clustering. In addition, we performed a meta-analysis using public single-cell datasets of over 1.8 million peripheral CD4+ T cells from 953 individuals by projecting cells onto the reference and cataloging cell frequency and qualitative alterations of the populations in 20 diseases. The analyses revealed that the 12 transcriptional programs were useful in characterizing each autoimmune disease and predicting its clinical status. Moreover, genetic variants associated with autoimmune diseases showed disease-specific enrichment within the 12 gene programs. The results collectively provide a landscape of single-cell transcriptomes of CD4+ T cell subpopulations involved in autoimmune disease.
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Affiliation(s)
- Yoshiaki Yasumizu
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Department of Neurology, Graduate School of Medicine, Osaka University, Osaka, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan
| | - Daiki Takeuchi
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Faculty of Medicine, Osaka University, Osaka, Japan
| | - Reo Morimoto
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Yusuke Takeshima
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Tatsusada Okuno
- Department of Neurology, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Makoto Kinoshita
- Department of Neurology, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Takayoshi Morita
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yasuhiro Kato
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Immunopathology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Min Wang
- Clinical Immunology Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Daisuke Motooka
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan; Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Daisuke Okuzaki
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan; Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Yamami Nakamura
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Norihisa Mikami
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Masaya Arai
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Xuan Zhang
- Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Atsushi Kumanogoh
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Immunopathology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Center for Infectious Diseases for Education and Research, Osaka University, Osaka, Japan
| | - Hideki Mochizuki
- Department of Neurology, Graduate School of Medicine, Osaka University, Osaka, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Osaka, Japan
| | - Naganari Ohkura
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Department of Frontier Research in Tumor Immunology, Graduate School of Medicine, Osaka University, Osaka, Japan.
| | - Shimon Sakaguchi
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Osaka, Japan; Department of Experimental Immunology, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan.
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Li H, Yu Z, Du F, Song L, Gao Y, Shi F. sscNOVA: a semi-supervised convolutional neural network for predicting functional regulatory variants in autoimmune diseases. Front Immunol 2024; 15:1323072. [PMID: 38380333 PMCID: PMC10876991 DOI: 10.3389/fimmu.2024.1323072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 01/15/2024] [Indexed: 02/22/2024] Open
Abstract
Genome-wide association studies (GWAS) have identified thousands of variants in the human genome with autoimmune diseases. However, identifying functional regulatory variants associated with autoimmune diseases remains challenging, largely because of insufficient experimental validation data. We adopt the concept of semi-supervised learning by combining labeled and unlabeled data to develop a deep learning-based algorithm framework, sscNOVA, to predict functional regulatory variants in autoimmune diseases and analyze the functional characteristics of these regulatory variants. Compared to traditional supervised learning methods, our approach leverages more variants' data to explore the relationship between functional regulatory variants and autoimmune diseases. Based on the experimentally curated testing dataset and evaluation metrics, we find that sscNOVA outperforms other state-of-the-art methods. Furthermore, we illustrate that sscNOVA can help to improve the prioritization of functional regulatory variants from lead single-nucleotide polymorphisms and the proxy variants in autoimmune GWAS data.
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Affiliation(s)
- Haibo Li
- School of Information Engineering, Ningxia University, Yinchuan, China
| | - Zhenhua Yu
- School of Information Engineering, Ningxia University, Yinchuan, China
- Collaborative Innovation Center for Ningxia Big Data and Artificial Intelligence Co-founded by Ningxia Municipality and Ministry of Education, Yinchuan, Ningxia University, Yinchuan, China
| | - Fang Du
- School of Information Engineering, Ningxia University, Yinchuan, China
- Collaborative Innovation Center for Ningxia Big Data and Artificial Intelligence Co-founded by Ningxia Municipality and Ministry of Education, Yinchuan, Ningxia University, Yinchuan, China
| | - Lijuan Song
- School of Information Engineering, Ningxia University, Yinchuan, China
- Collaborative Innovation Center for Ningxia Big Data and Artificial Intelligence Co-founded by Ningxia Municipality and Ministry of Education, Yinchuan, Ningxia University, Yinchuan, China
| | - Yang Gao
- School of Medical Technology, North Minzu University, Yinchuan, China
| | - Fangyuan Shi
- School of Information Engineering, Ningxia University, Yinchuan, China
- Collaborative Innovation Center for Ningxia Big Data and Artificial Intelligence Co-founded by Ningxia Municipality and Ministry of Education, Yinchuan, Ningxia University, Yinchuan, China
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32
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Alda-Catalinas C, Ibarra-Soria X, Flouri C, Gordillo JE, Cousminer D, Hutchinson A, Sun B, Pembroke W, Ullrich S, Krejci A, Cortes A, Acevedo A, Malla S, Fishwick C, Drewes G, Rapiteanu R. Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens. Genome Biol 2024; 25:42. [PMID: 38308274 PMCID: PMC10835965 DOI: 10.1186/s13059-024-03176-z] [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: 06/18/2023] [Accepted: 01/18/2024] [Indexed: 02/04/2024] Open
Abstract
BACKGROUND Drug targets with genetic evidence are expected to increase clinical success by at least twofold. Yet, translating disease-associated genetic variants into functional knowledge remains a fundamental challenge of drug discovery. A key issue is that the vast majority of complex disease associations cannot be cleanly mapped to a gene. Immune disease-associated variants are enriched within regulatory elements found in T-cell-specific open chromatin regions. RESULTS To identify genes and molecular programs modulated by these regulatory elements, we develop a CRISPRi-based single-cell functional screening approach in primary human T cells. Our pipeline enables the interrogation of transcriptomic changes induced by the perturbation of regulatory elements at scale. We first optimize an efficient CRISPRi protocol in primary CD4+ T cells via CROPseq vectors. Subsequently, we perform a screen targeting 45 non-coding regulatory elements and 35 transcription start sites and profile approximately 250,000 T -cell single-cell transcriptomes. We develop a bespoke analytical pipeline for element-to-gene (E2G) mapping and demonstrate that our method can identify both previously annotated and novel E2G links. Lastly, we integrate genetic association data for immune-related traits and demonstrate how our platform can aid in the identification of effector genes for GWAS loci. CONCLUSIONS We describe "primary T cell crisprQTL" - a scalable, single-cell functional genomics approach for mapping regulatory elements to genes in primary human T cells. We show how this framework can facilitate the interrogation of immune disease GWAS hits and propose that the combination of experimental and QTL-based techniques is likely to address the variant-to-function problem.
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Affiliation(s)
| | | | | | | | | | | | - Bin Sun
- Genomic Sciences, GSK, Stevenage, UK
| | | | | | | | | | | | | | | | - Gerard Drewes
- Genomic Sciences, GSK, Stevenage, UK
- Genomic Sciences, GSK, Collegeville, PA, USA
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33
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Ishikawa Y, Tanaka N, Asano Y, Kodera M, Shirai Y, Akahoshi M, Hasegawa M, Matsushita T, Saito K, Motegi SI, Yoshifuji H, Yoshizaki A, Kohmoto T, Takagi K, Oka A, Kanda M, Tanaka Y, Ito Y, Nakano K, Kasamatsu H, Utsunomiya A, Sekiguchi A, Niiro H, Jinnin M, Makino K, Makino T, Ihn H, Yamamoto M, Suzuki C, Takahashi H, Nishida E, Morita A, Yamamoto T, Fujimoto M, Kondo Y, Goto D, Sumida T, Ayuzawa N, Yanagida H, Horita T, Atsumi T, Endo H, Shima Y, Kumanogoh A, Hirata J, Otomo N, Suetsugu H, Koike Y, Tomizuka K, Yoshino S, Liu X, Ito S, Hikino K, Suzuki A, Momozawa Y, Ikegawa S, Tanaka Y, Ishikawa O, Takehara K, Torii T, Sato S, Okada Y, Mimori T, Matsuda F, Matsuda K, Amariuta T, Imoto I, Matsuo K, Kuwana M, Kawaguchi Y, Ohmura K, Terao C. GWAS for systemic sclerosis identifies six novel susceptibility loci including one in the Fcγ receptor region. Nat Commun 2024; 15:319. [PMID: 38296975 PMCID: PMC10830486 DOI: 10.1038/s41467-023-44541-z] [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: 03/20/2023] [Accepted: 12/18/2023] [Indexed: 02/02/2024] Open
Abstract
Here we report the largest Asian genome-wide association study (GWAS) for systemic sclerosis performed to date, based on data from Japanese subjects and comprising of 1428 cases and 112,599 controls. The lead SNP is in the FCGR/FCRL region, which shows a penetrating association in the Asian population, while a complete linkage disequilibrium SNP, rs10917688, is found in a cis-regulatory element for IRF8. IRF8 is also a significant locus in European GWAS for systemic sclerosis, but rs10917688 only shows an association in the presence of the risk allele of IRF8 in the Japanese population. Further analysis shows that rs10917688 is marked with H3K4me1 in primary B cells. A meta-analysis with a European GWAS detects 30 additional significant loci. Polygenic risk scores constructed with the effect sizes of the meta-analysis suggest the potential portability of genetic associations beyond populations. Prioritizing the top 5% of SNPs of IRF8 binding sites in B cells improves the fitting of the polygenic risk scores, underscoring the roles of B cells and IRF8 in the development of systemic sclerosis. The results also suggest that systemic sclerosis shares a common genetic architecture across populations.
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Affiliation(s)
- Yuki Ishikawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Nao Tanaka
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
- Department of Rheumatology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yoshihide Asano
- Department of Dermatology, Tohoku University Graduate School of Medicine, Sendai, Japan
- Department of Dermatology, The University of Tokyo, Tokyo, Japan
| | - Masanari Kodera
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Yuichiro Shirai
- Department of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan
| | - Mitsuteru Akahoshi
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
- Department of Rheumatology, Saga University Hospital, Saga, Japan
| | - Minoru Hasegawa
- Faculty of Medical Sciences, Department of Dermatology, University of Fukui, Fukui, Japan
| | - Takashi Matsushita
- Department of Dermatology, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan
| | - Kazuyoshi Saito
- The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan
| | - Sei-Ichiro Motegi
- Department of Dermatology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Hajime Yoshifuji
- Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ayumi Yoshizaki
- Department of Dermatology, The University of Tokyo, Tokyo, Japan
| | - Tomohiro Kohmoto
- Aichi Cancer Center Research Institute, Division of Molecular Genetics, Nagoya, Japan
| | - Kae Takagi
- Tokyo Women's Medical University, Adachi Medical Center, Tokyo, Japan
| | - Akira Oka
- Department of Molecular Life Sciences, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Miho Kanda
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Yoshihito Tanaka
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Yumi Ito
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Kazuhisa Nakano
- The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan
| | - Hiroshi Kasamatsu
- Faculty of Medical Sciences, Department of Dermatology, University of Fukui, Fukui, Japan
| | - Akira Utsunomiya
- Faculty of Medical Sciences, Department of Dermatology, University of Fukui, Fukui, Japan
| | - Akiko Sekiguchi
- Department of Dermatology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Hiroaki Niiro
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
| | - Masatoshi Jinnin
- Department of Dermatology, Wakayama Medical University Graduate School of Medicine, Wakayama, Japan
| | - Katsunari Makino
- Department of Dermatology and Plastic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Takamitsu Makino
- Department of Dermatology and Plastic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Hironobu Ihn
- Department of Dermatology and Plastic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Motohisa Yamamoto
- Department of Rheumatology and Allergy, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Chisako Suzuki
- Department of Rheumatology and Clinical Immunology, Sapporo Medical University School of Medicine, Sapporo, Japan
| | - Hiroki Takahashi
- Department of Rheumatology and Clinical Immunology, Sapporo Medical University School of Medicine, Sapporo, Japan
| | - Emi Nishida
- Department of Geriatric and Environmental Dermatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Department of Dermatology, Okazaki City Hospital, Okazaki, Japan
| | - Akimichi Morita
- Department of Geriatric and Environmental Dermatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Toshiyuki Yamamoto
- Department of Dermatology, Fukushima Medical University, School of Medicine, Fukushima, Japan
| | - Manabu Fujimoto
- Department of Dermatology, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Yuya Kondo
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Daisuke Goto
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Takayuki Sumida
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Naho Ayuzawa
- Department of Clinical Immunology, National Hospital Organization, Utano National Hospital, Kyoto, Japan
| | - Hidetoshi Yanagida
- Department of Clinical Immunology, National Hospital Organization, Utano National Hospital, Kyoto, Japan
| | - Tetsuya Horita
- Faculty of Medicine and Graduate School of Medicine, Department of Rheumatology, Endocrinology and Nephrology, Hokkaido University, Sapporo, Japan
| | - Tatsuya Atsumi
- Faculty of Medicine and Graduate School of Medicine, Department of Rheumatology, Endocrinology and Nephrology, Hokkaido University, Sapporo, Japan
| | - Hirahito Endo
- Omori Medical Center, Toho University, Rheumatic Disease Center, Tokyo, Japan
| | - Yoshihito Shima
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Atsushi Kumanogoh
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Jun Hirata
- Immunology Frontier Center, Osaka University, Statistical Immunology, Osaka, Japan
| | - Nao Otomo
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Hiroyuki Suetsugu
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Yoshinao Koike
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Kohei Tomizuka
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Soichiro Yoshino
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Xiaoxi Liu
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Shuji Ito
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Keiko Hikino
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Pharmacogenomics, Yokohama, Japan
| | - Akari Suzuki
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Autoimmune Diseases, Yokohama, Japan
| | - Yukihide Momozawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Genotyping Development, Yokohama, Japan
| | - Shiro Ikegawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Bone and Joint Diseases, Yokohama, Japan
| | - Yoshiya Tanaka
- The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan
| | - Osamu Ishikawa
- Department of Dermatology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kazuhiko Takehara
- Department of Dermatology, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan
| | | | - Shinichi Sato
- Department of Dermatology, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Immunology Frontier Center, Osaka University, Statistical Immunology, Osaka, Japan
| | - Tsuneyo Mimori
- Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Ijinkai Takeada General Hospital, Kyoto, Japan
| | - Fumihiko Matsuda
- Graduate School of Medicine, Kyoto University, Center for Genomic Medicine, Kyoto, Japan
| | - Koichi Matsuda
- Institute of Medical Science, The University of Tokyo, Laboratory of Genome Technology, Human Genome Center, Tokyo, Japan
- Department of Computational Biology and Medical Sciences, Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Tiffany Amariuta
- Center for Data Sciences, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Graduate School of Arts and Sciences, Harvard University, Cambridge, MA, USA
| | - Issei Imoto
- Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Keitaro Matsuo
- Aichi Cancer Center Research Institute, Division of Cancer Epidemiology and Prevention, Nagoya, Japan
| | - Masataka Kuwana
- Department of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan
| | - Yasushi Kawaguchi
- Tokyo Women's Medical University, Division of Rheumatology, Department of Internal Medicine, Tokyo, Japan
| | - Koichiro Ohmura
- Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Chikashi Terao
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan.
- Shizuoka General Hospital, The Clinical Research Center, Shizuoka, Japan.
- The Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan.
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34
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Louarn M, Collet G, Barré È, Fest T, Dameron O, Siegel A, Chatonnet F. Regulus infers signed regulatory relations from few samples' information using discretization and likelihood constraints. PLoS Comput Biol 2024; 20:e1011816. [PMID: 38252636 PMCID: PMC10833539 DOI: 10.1371/journal.pcbi.1011816] [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: 12/16/2022] [Revised: 02/01/2024] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
MOTIVATION Transcriptional regulation is performed by transcription factors (TF) binding to DNA in context-dependent regulatory regions and determines the activation or inhibition of gene expression. Current methods of transcriptional regulatory circuits inference, based on one or all of TF, regions and genes activity measurements require a large number of samples for ranking the candidate TF-gene regulation relations and rarely predict whether they are activations or inhibitions. We hypothesize that transcriptional regulatory circuits can be inferred from fewer samples by (1) fully integrating information on TF binding, gene expression and regulatory regions accessibility, (2) reducing data complexity and (3) using biology-based likelihood constraints to determine the global consistency between a candidate TF-gene relation and patterns of genes expressions and region activations, as well as qualify regulations as activations or inhibitions. RESULTS We introduce Regulus, a method which computes TF-gene relations from gene expressions, regulatory region activities and TF binding sites data, together with the genomic locations of all entities. After aggregating gene expressions and region activities into patterns, data are integrated into a RDF (Resource Description Framework) endpoint. A dedicated SPARQL (SPARQL Protocol and RDF Query Language) query retrieves all potential relations between expressed TF and genes involving active regulatory regions. These TF-region-gene relations are then filtered using biological likelihood constraints allowing to qualify them as activation or inhibition. Regulus provides signed relations consistent with public databases and, when applied to biological data, identifies both known and potential new regulators. Regulus is devoted to context-specific transcriptional circuits inference in human settings where samples are scarce and cell populations are closely related, using discretization into patterns and likelihood reasoning to decipher the most robust regulatory relations.
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Affiliation(s)
- Marine Louarn
- Univ Rennes, CNRS, Inria, IRISA - UMR 6074, Rennes, France
- UMR_S 1236, Université Rennes 1, INSERM, Etablissement Français du Sang, Rennes, France
| | | | - Ève Barré
- Univ Rennes, CNRS, Inria, IRISA - UMR 6074, Rennes, France
| | - Thierry Fest
- UMR_S 1236, Université Rennes 1, INSERM, Etablissement Français du Sang, Rennes, France
- Laboratoire d’Hématologie, Pôle de Biologie, CHU de Rennes, Rennes, France
| | | | - Anne Siegel
- Univ Rennes, CNRS, Inria, IRISA - UMR 6074, Rennes, France
| | - Fabrice Chatonnet
- UMR_S 1236, Université Rennes 1, INSERM, Etablissement Français du Sang, Rennes, France
- Laboratoire d’Hématologie, Pôle de Biologie, CHU de Rennes, Rennes, France
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35
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Hitomi Y, Ueno K, Aiba Y, Nishida N, Kawai Y, Kawashima M, Khor SS, Takada S, Iwabuchi C, Nagasaki M, Tokunaga K, Nakamura M. rs10924104 in the expression enhancer motif of CD58 confers susceptibility to human autoimmune diseases. Hum Genet 2024; 143:19-33. [PMID: 37994973 DOI: 10.1007/s00439-023-02617-2] [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: 06/13/2023] [Accepted: 09/28/2023] [Indexed: 11/24/2023]
Abstract
CD58 plays roles in cell adhesion and co-stimulation with antigen presentation from major histocompatibility complex class II on antigen-presenting cells to T-cell antigen receptors on naïve T cells. CD58 reportedly contributes to the development of various human autoimmune diseases. Recently, genome-wide association studies (GWASs) identified CD58 as a susceptibility locus for autoimmune diseases such as systemic lupus erythematosus (SLE), multiple sclerosis (MS), and primary biliary cholangitis (PBC). However, the primary functional variant and molecular mechanisms of susceptibility to autoimmune diseases in the CD58 locus were not clarified. Here, rs10924104, located in the ZNF35-binding motif within the gene expression regulatory motif, was identified as the primary functional variant for SLE, MS, and PBC among genetic variants showing stronger linkage disequilibrium (LD) with GWAS-lead variants in the CD58 locus. Expression-quantitative trait locus (e-QTL) data for each distinct blood cell type and in vitro functional analysis using the CRISPR/Cas9 system corroborated the functional role of rs10924104 in the upregulation of CD58 transcription by the disease-risk allele. Additionally, the strength of disease susceptibility observed in the CD58 locus could be accounted for by the strength of LD between rs10924104 and each GWAS-lead variant. In conclusion, the present study demonstrated for the first time the existence of a shared autoimmune disease-related primary functional variant (i.e., rs10924104) that regulates the expression of CD58. Clarifying the molecular mechanism of disease susceptibility derived from such a shared genetic background is important for understanding human autoimmune diseases and human immunology.
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Affiliation(s)
- Yuki Hitomi
- Department of Human Genetics, Research Institute, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan.
| | - Kazuko Ueno
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan
| | - Yoshihiro Aiba
- Clinical Research Center, National Hospital Organization (NHO) Nagasaki Medical Center, Omura, Japan
| | - Nao Nishida
- Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yosuke Kawai
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan
| | - Minae Kawashima
- Database Center for Life Science, Research Organization of Information and Systems, Kashiwa, Japan
| | - Seik-Soon Khor
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Sanami Takada
- Department of Human Genetics, Research Institute, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan
| | - Chisato Iwabuchi
- Department of Human Genetics, Research Institute, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan
| | - Masao Nagasaki
- Division of Biomedical Information Analysis, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
| | - Katsushi Tokunaga
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan
| | - Minoru Nakamura
- Clinical Research Center, National Hospital Organization (NHO) Nagasaki Medical Center, Omura, Japan
- Department of Hepatology, Nagasaki University Graduate School of Biomedical Sciences, Omura, Japan
- Headquarters of PBC Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
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36
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Yoshida H. Dissecting the Immune System through Gene Regulation. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1444:219-235. [PMID: 38467983 DOI: 10.1007/978-981-99-9781-7_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
The immune system plays a dual role in human health, functioning both as a protector against pathogens and, at times, as a contributor to disease. This feature emphasizes the importance to uncover the underlying causes of its malfunctions, necessitating an in-depth analysis in both pathological and physiological conditions to better understand the immune system and immune disorders. Recent advances in scientific technology have enabled extensive investigations into gene regulation, a crucial mechanism governing cellular functionality. Studying gene regulatory mechanisms within the immune system is a promising avenue for enhancing our understanding of immune cells and the immune system as a whole. The gene regulatory mechanisms, revealed through various methodologies, and their implications in the field of immunology are discussed in this chapter.
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Affiliation(s)
- Hideyuki Yoshida
- YCI Laboratory for Immunological Transcriptomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
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Boocock J, Alexander N, Tapia LA, Walter-McNeill L, Munugala C, Bloom JS, Kruglyak L. Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.07.570640. [PMID: 38106186 PMCID: PMC10723400 DOI: 10.1101/2023.12.07.570640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in Saccharomyces cerevisiae by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene GPA1, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.
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Affiliation(s)
- James Boocock
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Noah Alexander
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Leslie Alamo Tapia
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Laura Walter-McNeill
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Chetan Munugala
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Joshua S Bloom
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Leonid Kruglyak
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
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Perez AA, Goronzy IN, Blanco MR, Guo JK, Guttman M. ChIP-DIP: A multiplexed method for mapping hundreds of proteins to DNA uncovers diverse regulatory elements controlling gene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.14.571730. [PMID: 38187704 PMCID: PMC10769186 DOI: 10.1101/2023.12.14.571730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Gene expression is controlled by the dynamic localization of thousands of distinct regulatory proteins to precise regions of DNA. Understanding this cell-type specific process has been a goal of molecular biology for decades yet remains challenging because most current DNA-protein mapping methods study one protein at a time. To overcome this, we developed ChIP-DIP (ChIP Done In Parallel), a split-pool based method that enables simultaneous, genome-wide mapping of hundreds of diverse regulatory proteins in a single experiment. We demonstrate that ChIP-DIP generates highly accurate maps for all classes of DNA-associated proteins, including histone modifications, chromatin regulators, transcription factors, and RNA Polymerases. Using these data, we explore quantitative combinations of protein localization on genomic DNA to define distinct classes of regulatory elements and their functional activity. Our data demonstrate that ChIP-DIP enables the generation of 'consortium level', context-specific protein localization maps within any molecular biology lab.
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Cai M, Qin Y, Wan A, Jin H, Tang J, Chen Z. COX5A as a potential biomarker for disease activity and organ damage in lupus. Clin Exp Med 2023; 23:4745-4756. [PMID: 37891386 DOI: 10.1007/s10238-023-01215-w] [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: 06/04/2023] [Accepted: 10/02/2023] [Indexed: 10/29/2023]
Abstract
Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease with limited therapeutic targets or clinical outcome predictors. This study aimed to gain more insights into the underlying immunological pathways and prognostic biomarkers of SLE. Integrated analyses of RNA-seq data from 64 SLE and 62 healthy controls, examining 27 immune cell types to explore the key pathways and driver genes in SLE pathogenesis. Single-cell RNA sequencing data from the skin and kidney were used to determine the association of COX5A expression with organ damage. The associations of COX5A with SLE phenotypes were further evaluated in two independent cohorts, and receiver operating characteristic (ROC) curves were constructed to assess the value of COX5A as a biomarker for disease activity and organ damage in SLE. We found that oxidative phosphorylation (OXPHOS) is the most significantly altered metabolic pathway in SLE, especially in effector T cells. Notably, we identified an OXPHOS-related enzyme, COX5A, whose expression was significantly higher in effector T cells than in naïve T cells and showed associations with disease activity, organ damage, and steroid treatment of SLE. Furthermore, ROC curves showed that COX5A is a robust biomarker for disease activity, kidney involvement, and new-onset skin lesions, with the area under the curve (AUC) values of 0.880, 0.801, and 0.805, respectively. Our results identified the OXPHOS signature as a prominent feature in SLE T cells, and COX5A as a potential candidate biomarker for disease activity and organ damage in SLE.
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Affiliation(s)
- Minglong Cai
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China
| | - Yi Qin
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China
| | - An Wan
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China
| | - Huizhi Jin
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China
| | - Jun Tang
- Department of Dermatology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
| | - Zhu Chen
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
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40
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Zhang J, Zhao H. eQTL studies: from bulk tissues to single cells. J Genet Genomics 2023; 50:925-933. [PMID: 37207929 PMCID: PMC10656365 DOI: 10.1016/j.jgg.2023.05.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 05/02/2023] [Accepted: 05/04/2023] [Indexed: 05/21/2023]
Abstract
An expression quantitative trait locus (eQTL) is a chromosomal region where genetic variants are associated with the expression levels of specific genes that can be both nearby or distant. The identifications of eQTLs for different tissues, cell types, and contexts have led to a better understanding of the dynamic regulations of gene expressions and implications of functional genes and variants for complex traits and diseases. Although most eQTL studies have been performed on data collected from bulk tissues, recent studies have demonstrated the importance of cell-type-specific and context-dependent gene regulations in biological processes and disease mechanisms. In this review, we discuss statistical methods that have been developed to enable the detection of cell-type-specific and context-dependent eQTLs from bulk tissues, purified cell types, and single cells. We also discuss the limitations of the current methods and future research opportunities.
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Affiliation(s)
- Jingfei Zhang
- Information Systems and Operations Management, Emory University, Atlanta, GA 30322, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 208034, USA.
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Kang JB, Shen AZ, Gurajala S, Nathan A, Rumker L, Aguiar VRC, Valencia C, Lagattuta KA, Zhang F, Jonsson AH, Yazar S, Alquicira-Hernandez J, Khalili H, Ananthakrishnan AN, Jagadeesh K, Dey K, Daly MJ, Xavier RJ, Donlin LT, Anolik JH, Powell JE, Rao DA, Brenner MB, Gutierrez-Arcelus M, Luo Y, Sakaue S, Raychaudhuri S. Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution. Nat Genet 2023; 55:2255-2268. [PMID: 38036787 PMCID: PMC10787945 DOI: 10.1038/s41588-023-01586-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 10/19/2023] [Indexed: 12/02/2023]
Abstract
The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.
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Affiliation(s)
- Joyce B Kang
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Amber Z Shen
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Saisriram Gurajala
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Aparna Nathan
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Laurie Rumker
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Vitor R C Aguiar
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Cristian Valencia
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kaitlyn A Lagattuta
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology and the Center for Health Artificial Intelligence, University of Colorado School of Medicine, Aurora, CO, USA
| | - Anna Helena Jonsson
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Seyhan Yazar
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | | | - Hamed Khalili
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ashwin N Ananthakrishnan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Kushal Dey
- Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Physiology, Biophysics and Systems Biology Program, Weill Cornell Medicine, New York, NY, USA
| | - Mark J Daly
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ramnik J Xavier
- Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Laura T Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jennifer H Anolik
- Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | - Joseph E Powell
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Deepak A Rao
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael B Brenner
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Maria Gutierrez-Arcelus
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yang Luo
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Saori Sakaue
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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Singh MK, Maiti GP, Reddy-Rallabandi H, Fazel-Najafabadi M, Looger LL, Nath SK. A Non-Coding Variant in SLC15A4 Modulates Enhancer Activity and Lysosomal Deacidification Linked to Lupus Susceptibility. FRONTIERS IN LUPUS 2023; 1:1244670. [PMID: 38317862 PMCID: PMC10843804 DOI: 10.3389/flupu.2023.1244670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Systemic lupus erythematosus (SLE) is a complex autoimmune disease with a strong genetic basis. Despite the identification of several single nucleotide polymorphisms (SNPs) near the SLC15A4 gene that are significantly associated with SLE across multiple populations, specific causal SNP(s) and molecular mechanisms responsible for disease susceptibility are unknown. To address this gap, we employed bioinformatics, expression quantitative trait loci (eQTLs), and 3D chromatin interaction analysis to nominate a likely functional variant, rs35907548, in an active intronic enhancer of SLC15A4. Through luciferase reporter assays followed by chromatin immunoprecipitation (ChIP)-qPCR, we observed significant allele-specific enhancer effects of rs35907548 in diverse cell lines. The rs35907548 risk allele T is associated with increased regulatory activity and target gene expression, as shown by eQTLs and chromosome conformation capture (3C)-qPCR. The latter revealed long-range chromatin interactions between the rs35907548 enhancer and the promoters of SLC15A4, GLTLD1, and an uncharacterized lncRNA. The enhancer-promoter interactions and expression effects were validated by CRISPR/Cas9 knock-out (KO) of the locus in HL60 promyeloblast cells. KO cells also displayed dramatically dysregulated endolysosomal pH regulation. Together, our data show that the rs35907548 risk allele affects multiple aspects of cellular physiology and may directly contribute to SLE.
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Affiliation(s)
- Manish Kumar Singh
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City OK, USA
| | - Guru Prashad Maiti
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City OK, USA
| | | | - Mehdi Fazel-Najafabadi
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City OK, USA
| | - Loren L. Looger
- Howard Hughes Medical Institute, Department of Neurosciences, University of California San Diego, La Jolla CA, USA
| | - Swapan K. Nath
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City OK, USA
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Ota M, Nakano M, Nagafuchi Y, Kobayashi S, Hatano H, Yoshida R, Akutsu Y, Itamiya T, Ban N, Tsuchida Y, Shoda H, Yamamoto K, Ishigaki K, Okamura T, Fujio K. Multimodal repertoire analysis unveils B cell biology in immune-mediated diseases. Ann Rheum Dis 2023; 82:1455-1463. [PMID: 37468219 DOI: 10.1136/ard-2023-224421] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 07/04/2023] [Indexed: 07/21/2023]
Abstract
OBJECTIVES Despite the involvement of B cells in the pathogenesis of immune-mediated diseases (IMDs), biological mechanisms underlying their function are scarcely understood. To overcome this gap, here we constructed and investigated a large-scale repertoire catalogue of five B cell subsets of patients with IMDs. METHODS We mapped B cell receptor regions from RNA sequencing data of sorted B cell subsets. Our dataset consisted of 595 donors under IMDs and health. We characterised the repertoire features from various aspects, including their association with immune cell transcriptomes and clinical features and their response to belimumab treatment. RESULTS Heavy-chain complementarity-determining region 3 (CDR-H3) length among naïve B cells was shortened among autoimmune diseases. Strong negative correlation between interferon signature strength and CDR-H3 length was observed in naïve B cells and suggested the role for interferon in premature B cell development. VDJ gene usage was skewed especially in plasmablasts and unswitched-memory B cells of patients with systemic lupus erythematosus (SLE). We developed a scoring system to quantify this skewing, and it positively correlated with peripheral helper T cell transcriptomic signatures and negatively correlated with the amount of somatic hyper mutations in plasmablasts, suggesting the association of extrafollicular pathway. Further, this skewing led to high usage of IGHV4-34 gene with 9G4 idiotypes in unswitched-memory B cells, which showed a prominent positive correlation with disease activity in SLE. Gene usage skewing in unswitched-memory B cells was ameliorated after belimumab treatment. CONCLUSIONS Our multimodal repertoire analysis enabled us the system-level understanding of B cell abnormality in diseases.
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Affiliation(s)
- Mineto Ota
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
| | - Masahiro Nakano
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yasuo Nagafuchi
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
| | - Satomi Kobayashi
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
| | - Hiroaki Hatano
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Ryochi Yoshida
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
| | - Yuko Akutsu
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
| | - Takahiro Itamiya
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
| | - Nobuhiro Ban
- Research Division, Chugai Pharmaceutical Co Ltd, Yokohama, Japan
| | - Yumi Tsuchida
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
| | - Hirofumi Shoda
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
| | - Kazuhiko Yamamoto
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Tomohisa Okamura
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
- Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
| | - Keishi Fujio
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan
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44
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Zhu Z, Chen X, Zhang S, Yu R, Qi C, Cheng L, Zhang X. Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective. Hum Genet 2023; 142:1543-1560. [PMID: 37755483 DOI: 10.1007/s00439-023-02602-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/14/2023] [Indexed: 09/28/2023]
Abstract
Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.
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Affiliation(s)
- Zijun Zhu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Xinyu Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Sainan Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Rui Yu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Changlu Qi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China.
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China.
| | - Xue Zhang
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
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45
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Mostafavi H, Spence JP, Naqvi S, Pritchard JK. Systematic differences in discovery of genetic effects on gene expression and complex traits. Nat Genet 2023; 55:1866-1875. [PMID: 37857933 DOI: 10.1038/s41588-023-01529-1] [Citation(s) in RCA: 43] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 09/14/2023] [Indexed: 10/21/2023]
Abstract
Most signals in genome-wide association studies (GWAS) of complex traits implicate noncoding genetic variants with putative gene regulatory effects. However, currently identified regulatory variants, notably expression quantitative trait loci (eQTLs), explain only a small fraction of GWAS signals. Here, we show that GWAS and cis-eQTL hits are systematically different: eQTLs cluster strongly near transcription start sites, whereas GWAS hits do not. Genes near GWAS hits are enriched in key functional annotations, are under strong selective constraint and have complex regulatory landscapes across different tissue/cell types, whereas genes near eQTLs are depleted of most functional annotations, show relaxed constraint, and have simpler regulatory landscapes. We describe a model to understand these observations, including how natural selection on complex traits hinders discovery of functionally relevant eQTLs. Our results imply that GWAS and eQTL studies are systematically biased toward different types of variant, and support the use of complementary functional approaches alongside the next generation of eQTL studies.
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Affiliation(s)
| | | | - Sahin Naqvi
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA, USA
| | - Jonathan K Pritchard
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Department of Biology, Stanford University, Stanford, CA, USA.
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46
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Cretin J, Adjemout M, Dieppois C, Gallardo F, Torres M, Merard Z, Sawadogo SA, Picard C, Rihet P, Paul P. A Non-Coding Fc Gamma Receptor Cis-Regulatory Variant within the 1q23 Gene Cluster Is Associated with Plasmodium falciparum Infection in Children Residing in Burkina Faso. Int J Mol Sci 2023; 24:15711. [PMID: 37958695 PMCID: PMC10650193 DOI: 10.3390/ijms242115711] [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: 08/07/2023] [Revised: 08/27/2023] [Accepted: 08/31/2023] [Indexed: 11/15/2023] Open
Abstract
Antibodies play a crucial role in activating protective immunity against malaria by interacting with Fc-gamma receptors (FcγRs). Genetic variations in genes encoding FcγRs can affect immune cell responses to the parasite. In this study, our aim was to investigate whether non-coding variants that regulate FcγR expression could influence the prevalence of Plasmodium falciparum infection. Through bioinformatics approaches, we selected expression quantitative trait loci (eQTL) for FCGR2A, FCGR2B, FCGR2C, FCGR3A, and FCGR3B genes encoding FcγRs (FCGR), in whole blood. We prioritized two regulatory variants, rs2099684 and rs1771575, located in open genomic regions. These variants were identified using RegVar, ImmuNexUT, and transcription factor annotations specific to immune cells. In addition to these, we genotyped the coding variants FCGR2A/rs1801274 and FCGR2B/rs1050501 in 234 individuals from a malaria-endemic area in Burkina Faso. We conducted age and family-based analyses to evaluate associations with the prevalence of malarial infection in both children and adults. The analysis revealed that the regulatory rs1771575-CC genotype was predicted to influence FCGR2B/FCGR2C/FCGR3A transcripts in immune cells and was the sole variant associated with a higher prevalence of malarial infection in children. In conclusion, this study identifies the rs1771575 cis-regulatory variant affecting several FcγRs in myeloid and neutrophil cells and associates it with the inter-individual capacity of children living in Burkina Faso to control malarial infection.
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Affiliation(s)
- Jules Cretin
- INSERM 1090, TAGC Theories and Approaches of Genomic Complexity, Campus de Luminy, Aix Marseille University, 13288 Marseille, France (M.A.); (C.D.); (F.G.); (M.T.)
- Institut MarMaRa, 13288 Marseille, France
| | - Mathieu Adjemout
- INSERM 1090, TAGC Theories and Approaches of Genomic Complexity, Campus de Luminy, Aix Marseille University, 13288 Marseille, France (M.A.); (C.D.); (F.G.); (M.T.)
- Institut MarMaRa, 13288 Marseille, France
| | - Christelle Dieppois
- INSERM 1090, TAGC Theories and Approaches of Genomic Complexity, Campus de Luminy, Aix Marseille University, 13288 Marseille, France (M.A.); (C.D.); (F.G.); (M.T.)
| | - Frederic Gallardo
- INSERM 1090, TAGC Theories and Approaches of Genomic Complexity, Campus de Luminy, Aix Marseille University, 13288 Marseille, France (M.A.); (C.D.); (F.G.); (M.T.)
| | - Magali Torres
- INSERM 1090, TAGC Theories and Approaches of Genomic Complexity, Campus de Luminy, Aix Marseille University, 13288 Marseille, France (M.A.); (C.D.); (F.G.); (M.T.)
| | - Zachary Merard
- ADES UMR, Aix Marseille University, 13288 Marseille, France (C.P.)
| | - Serge Aimé Sawadogo
- Unité de Formation en Sciences de la Santé (UFR/SDS), Université Joseph KI-ZERBO, Ouagadougou 03 BP 7021, Burkina Faso;
- Centre PrïmO-Nelson Mandela, 84 rue Sao Tomé et Principe, Ouagadougou 09 BP 706, Burkina Faso
| | - Christophe Picard
- ADES UMR, Aix Marseille University, 13288 Marseille, France (C.P.)
- Immunogenetics Laboratory, Etablissement Français du Sang PACA-Corse, 13001 Marseille, France
| | - Pascal Rihet
- INSERM 1090, TAGC Theories and Approaches of Genomic Complexity, Campus de Luminy, Aix Marseille University, 13288 Marseille, France (M.A.); (C.D.); (F.G.); (M.T.)
| | - Pascale Paul
- INSERM 1090, TAGC Theories and Approaches of Genomic Complexity, Campus de Luminy, Aix Marseille University, 13288 Marseille, France (M.A.); (C.D.); (F.G.); (M.T.)
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Shoda H, Natsumoto B, Fujio K. Investigation of immune-related diseases using patient-derived induced pluripotent stem cells. Inflamm Regen 2023; 43:51. [PMID: 37876023 PMCID: PMC10594759 DOI: 10.1186/s41232-023-00303-4] [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: 08/08/2023] [Accepted: 10/16/2023] [Indexed: 10/26/2023] Open
Abstract
The precise pathogenesis of immune-related diseases remains unclear, and new effective therapeutic choices are required for the induction of remission or cure in these diseases. Basic research utilizing immune-related disease patient-derived induced pluripotent stem (iPS) cells is expected to be a promising platform for elucidating the pathogenesis of the diseases and for drug discovery. Since autoinflammatory diseases are usually monogenic, genetic mutations affect the cell function and patient-derived iPS cells tend to exhibit disease-specific phenotypes. In particular, iPS cell-derived monocytic cells and macrophages can be used for functional experiments, such as inflammatory cytokine production, and are often employed in research on patients with autoinflammatory diseases.On the other hand, the utilization of disease-specific iPS cells is less successful for research on autoimmune diseases. One reason for this is that autoimmune diseases are usually polygenic, which makes it challenging to determine which factors cause the phenotypes of patient-derived iPS cells are caused by. Another reason is that protocols for differentiating some lymphocytes associated with autoimmunity, such as CD4+T cells or B cells, from iPS cells have not been well established. Nevertheless, several groups have reported studies utilizing autoimmune disease patient-derived iPS cells, including patients with rheumatoid arthritis, systemic lupus erythematosus (SLE), and systemic sclerosis. Particularly, non-hematopoietic cells, such as fibroblasts and cardiomyocytes, differentiated from autoimmune patient-derived iPS cells have shown promising results for further research into the pathogenesis. Recently, our groups established a method for differentiating dendritic cells that produce interferon-alpha, which can be applied as an SLE pathological model. In summary, patient-derived iPS cells can provide a promising platform for pathological research and new drug discovery in the field of immune-related diseases.
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Affiliation(s)
- Hirofumi Shoda
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-8655, Japan.
| | - Bunki Natsumoto
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-8655, Japan
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehirocho, Tsurumi-Ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Keishi Fujio
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-8655, Japan
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48
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Oberemok VV, Andreeva O, Laikova K, Alieva E, Temirova Z. Rheumatoid Arthritis Has Won the Battle but Not the War: How Many Joints Will We Save Tomorrow? MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1853. [PMID: 37893571 PMCID: PMC10608469 DOI: 10.3390/medicina59101853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/06/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023]
Abstract
Rheumatoid arthritis refers to joint diseases of unclear etiology whose final stages can lead to unbearable pain and complete immobility of the affected joints. As one of the most widely known diseases of the joints, it serves as a study target for a large number of research groups and pharmaceutical companies. Modern treatment with anti-inflammatory drugs, including janus kinase (JAK) inhibitors, monoclonal antibodies, and botanicals (polyphenols, glycosides, alkaloids, etc.) has achieved some success and hope for improving the course of the disease. However, existing drugs against RA have a number of side effects which push researchers to elaborate on more selective and effective drug candidates. The avant-garde of research, which aims to develop treatment of rheumatoid arthritis using antisense oligonucleotides along with nonsteroidal drugs and corticosteroids against inflammation, increases the chances of success and expands the arsenal of drugs. The primary goal in the treatment of this disease is to find therapies that allow patients with rheumatoid arthritis to move their joints without pain. The main purpose of this review is to show the victories and challenges for the treatment of rheumatoid arthritis and the tortuous but promising path of research that aims to help patients experience the joy of freely moving joints without pain.
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Grants
- No. FZEG-2021-0009 Department of Molecular Genetics and Biotechnologies, Institute of Biochemical Technologies, Ecology and Pharmacy, V.I. Vernadsky Crimean Federal University, Simferopol, Crimea
- No. FZEG-2021-0009 Department of Molecular Genetics and Biotechnologies, Institute of Biochemical Technologies, Ecology and Pharmacy, V.I. Vernadsky Crimean Federal University, Simferopol, Crimea
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Affiliation(s)
- Volodymyr V. Oberemok
- Department of Molecular Genetics and Biotechnologies, Institute of Biochemical Technologies, Ecology and Pharmacy, V.I. Vernadsky Crimean Federal University, Simferopol 295007, Crimea; (O.A.); (K.L.); (E.A.); (Z.T.)
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49
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Zhu WS, Wheeler BD, Ansel KM. RNA circuits and RNA-binding proteins in T cells. Trends Immunol 2023; 44:792-806. [PMID: 37599172 PMCID: PMC10890840 DOI: 10.1016/j.it.2023.07.006] [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: 05/28/2023] [Revised: 07/13/2023] [Accepted: 07/17/2023] [Indexed: 08/22/2023]
Abstract
RNA is integral to the regulatory circuits that control cell identity and behavior. Cis-regulatory elements in mRNAs interact with RNA-binding proteins (RBPs) that can alter RNA sequence, stability, and translation into protein. Similarly, long noncoding RNAs (lncRNAs) scaffold ribonucleoprotein complexes that mediate transcriptional and post-transcriptional regulation of gene expression. Indeed, cell programming is fundamental to multicellular life and, in this era of cellular therapies, it is of particular interest in T cells. Here, we review key concepts and recent advances in our understanding of the RNA circuits and RBPs that govern mammalian T cell differentiation and immune function.
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Affiliation(s)
- Wandi S Zhu
- Department of Microbiology & Immunology, Sandler Asthma Basic Research Center, University of California San Francisco, San Francisco, CA 94143, USA
| | - Benjamin D Wheeler
- Department of Microbiology & Immunology, Sandler Asthma Basic Research Center, University of California San Francisco, San Francisco, CA 94143, USA
| | - K Mark Ansel
- Department of Microbiology & Immunology, Sandler Asthma Basic Research Center, University of California San Francisco, San Francisco, CA 94143, USA.
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50
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Jiang P, Wang C, Zhang M, Tian Y, Zhao W, Xin J, Huang Y, Zhao Z, Sun W, Long J, Tang R, Qiu F, Shi X, Zhao Y, Zhu L, Dai N, Liu L, Wu X, Nie J, Jiang B, Shao Y, Gao Y, Yu J, Hu Z, Zang Z, Gong Y, Dai Y, Wang L, Ding N, Xu P, Chen S, Wang L, Xu J, Zhang L, Hong J, Qian R, Li H, Jiang X, Chen C, Tian W, Wu J, Jiang Y, Han C, Zhang K, Qiu H, Li L, Fan H, Chen L, Zhang J, Sun Z, Han X, Dai Z, Li E, Gershwin ME, Lian Z, Ma X, Seldin MF, Chen W, Wang M, Liu X. Differential regulation of JAK1 expression by ETS1 associated with predisposition to primary biliary cholangitis. J Genet Genomics 2023; 50:807-812. [PMID: 37348755 DOI: 10.1016/j.jgg.2023.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 06/05/2023] [Accepted: 06/07/2023] [Indexed: 06/24/2023]
Affiliation(s)
- Peng Jiang
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Chan Wang
- Institute of Translational Medicine, Yangzhou University Medical College, Yangzhou, Jiangsu 225009, China
| | - Mingming Zhang
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Ye Tian
- Department of Radiology & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, China
| | - Weifeng Zhao
- The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China
| | - Junyi Xin
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yexi Huang
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Zhibin Zhao
- Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China
| | - Wenjuan Sun
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Jie Long
- Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China
| | - Ruqi Tang
- Department of Gastroenterology and Hepatology, Shanghai Institute of Digestive Diseases, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai 200001, China
| | - Fang Qiu
- Department of Laboratory Medicine, The Fourth Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210031, China
| | - Xingjuan Shi
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Yi Zhao
- Department of Gastrointestinal Endoscopy, Eastern Hepatobiliary Surgery Hospital, Shanghai 201800, China
| | - Li Zhu
- The Fifth People's Hospital, Soochow University, Suzhou, Jiangsu 215007, China
| | - Na Dai
- Department of Gastroenterology, Jiangsu University Affiliated Kunshan Hospital, Kunshan, Jiangsu 215300, China
| | - Lei Liu
- Department of Gastroenterology, Yixing People's Hospital, Yixin, Jiangsu 214200, China
| | - Xudong Wu
- Department of Gastroenterology, Yancheng First People's Hospital, Yancheng, Jiangsu 224005, China
| | - Jinshan Nie
- Department of Gastroenterology, Taicang First People's Hospital, Soochow University, Taicang, Jiangsu 215400, China
| | - Bo Jiang
- Department of Hepatology, Jingjiang Second People's Hospital, Jingjiang, Jiangsu 214500, China
| | - Youlin Shao
- Department of Hepatology, The Third People's Hospital of Changzhou, Changzhou, Jiangsu 213001, China
| | - Yueqiu Gao
- Department of Liver Diseases, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Jianjiang Yu
- Department of Laboratory Medicine, Jiangyin People's Hospital, Southeast University, Jiangyin, Jiangsu 214400, China
| | - Zhigang Hu
- Department of Laboratory Medicine, Wuxi Children's Hospital, Wuxi, Jiangsu 214023, China
| | - Zhidong Zang
- Department of Hepatology, The Second Hospital of Nanjing, Southeast University, Nanjing, Jiangsu 210003, China
| | - Yuhua Gong
- Department of Laboratory Medicine, The Third People's Hospital of Zhenjiang, Zhenjiang, Jiangsu 212021, China
| | - Yaping Dai
- Department of Laboratory Medicine, The Fifth People's Hospital of Wuxi, Wuxi, Jiangsu 214000, China
| | - Lan Wang
- Department of Laboratory Medicine, The 81st Hospital of PLA, Nanjing, Jiangsu 210002, China
| | - Ningling Ding
- The Fifth People's Hospital, Soochow University, Suzhou, Jiangsu 215007, China
| | - Ping Xu
- The Fifth People's Hospital, Soochow University, Suzhou, Jiangsu 215007, China
| | - Sufang Chen
- The Fifth People's Hospital, Soochow University, Suzhou, Jiangsu 215007, China
| | - Lu Wang
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Jing Xu
- Department of Clinical Laboratory, Southeast University ZhongDa Hospital, Nanjing, Jiangsu 210009, China
| | - Luyao Zhang
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Junyan Hong
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Ruonan Qian
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Hu Li
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Xuan Jiang
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Congwei Chen
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China
| | - Wenyan Tian
- The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China
| | - Jian Wu
- The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China
| | - Yuzhang Jiang
- Department of Laboratory Medicine, Huai'an First People's Hospital, Nanjing Medical University, Huai'an, Jiangsu 223300, China
| | - Chongxu Han
- Department of Laboratory Medicine, Subei People's Hospital, Clinical Medical College, Yangzhou University, Yangzhou, Jiangsu 225001, China
| | - Kui Zhang
- Department of Laboratory Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, China
| | - Hong Qiu
- Department of Laboratory Medicine, The 81st Hospital of PLA, Nanjing, Jiangsu 210002, China
| | - Li Li
- Department of Clinical Laboratory, Southeast University ZhongDa Hospital, Nanjing, Jiangsu 210009, China
| | - Hong Fan
- Southeast University Medical College, Nanjing, Jiangsu 210009, China
| | - Liming Chen
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, Institute of Cancer, Department of Biochemistry, Nanjing Normal University College of Life Sciences, Nanjing, Jiangsu 210023, China
| | - Jianqiong Zhang
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China; Southeast University Medical College, Nanjing, Jiangsu 210009, China
| | - Zhongsheng Sun
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiao Han
- Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Zhenhua Dai
- Section of Immunology & Joint Immunology Program, The Second Clinical Medical College of Guangzhou University of Chinese Medicine, And Guangdong Provincial Academy of Chinese Medical Sciences, Guangzhou, Guangdong 510006, China
| | - Erguang Li
- Jiangsu Laboratory of Molecular Medicine, Nanjing University Medical School, Nanjing, Jiangsu 210093, China
| | - M Eric Gershwin
- Division of Rheumatology, Allergy and Clinical Immunology, University of California at Davis School of Medicine, Davis, CA, 95616, USA
| | - Zhexiong Lian
- Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China
| | - Xiong Ma
- Department of Gastroenterology and Hepatology, Shanghai Institute of Digestive Diseases, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai 200001, China
| | - Michael F Seldin
- Department of Biochemistry and Molecular Medicine, University of California at Davis School of Medicine, Davis, CA, 95616, USA
| | - Weichang Chen
- The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
| | - Meilin Wang
- Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affilated Cancer Hospital of Nanjing Medical University, Nanjing, Jiangsu 211166, China.
| | - Xiangdong Liu
- Key Laboratory of Developmental Genes and Human Diseases, School of Life Science and Technology, Southeast University, Nanjing, Jiangsu 210096, China.
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