Human Data Logo
NBDC HumanDB
NBDC Research ID:hum0214-v10
Release info
Latest

Research title

Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

Research overview

Aims: To elucidate the regulation of gene expression in each immune cell subset and its contribution to autoimmune diseases.

Methods: JGAS000220 (JGAD000309, JGAD000310): Various immune cell subsets from 21 systemic sclerosis patients, 26 ANCA associated vasculitis, and 28 healthy controls were collected (Naive_B, SM_B, USM_B, DN_B, Plasmablast, Th1, Th2, Th17, Tfh, Naive_CD4, Mem_CD4, Fr._II_eTreg, Naive_CD8, Mem_CD8, mDC, pDC, CD16p_Mono, CD16n_Mono, NK, Neu) and total RNAs were extracted from each subset. RNA-seq was performed for each sample. E-GEAD-397 / E-GEAD-398 / E-GEAD-420: Whole blood and 28 immune cell subsets from study population were collected (Naive_CD4, Mem_CD4, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Th1, Th2, Th17, Tfh, NK, Naive_CD8, Mem_CD8, EM_CD8, CM_CD8, TEMRA_CD8, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono (or CD16n_Mono), CD16p_Mono, Int_Mono, NC_Mono, mDC, pDC, LDG, Neu). Whole genome sequencing was performed with whole blood samples. RNA-seq was performed with each immune cell subset samples. After filtering and normalization of the gene expression data, eQTL analysis was performed in each immune cell type. JGAS000296: 24 peripheral blood immune cell subsets from 50 systemic sclerosis patients and 48 healthy controls were collected (Naive_CD4, Mem_CD4, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Th1, Th2, Th17, Tfh, NK, Naive_CD8, EM_CD8, CM_CD8, TEMRA_CD8, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono, Int_Mono, NC_Mono, mDC, pDC). RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered. JGAS000220 (JGAD000371, JGAD000372, JGAD000373): 19 immune cell subsets from study population were collected (Naive_CD4, Mem_CD4, Fr._II_eTreg, Th1, Th2, Th17, Tfh, NK, Naive_CD8, Mem_CD8, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CD16n_Mono, CD16p_Mono, mDC, pDC). RNA-seq was performed with each immune cell subset sample. ATAC-seq of 15 immune cell subsets was also performed. JGAS000486: Various peripheral blood immune cell subsets from 89 healthy volunteers and 136 systemic lupus erhythematosus (SLE) donors were collected (Naive_CD4, Mem_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Naive_CD8, EM_CD8, CM_CD8, TEMRA_CD8, NK, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono (or CD16n_Mono), CD16p_Mono, Int_Mono, NC_Mono, mDC, pDC, Neu, LDG). 22 SLE patients were analyzed longitudinally. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered. JGAS000598: Various peripheral blood immune cell subsets from 39 healthy volunteers and 50 rheumatoid (RA) donors were collected (CD16p_Mono, CL_Mono, DN_B, Fr_II_eTreg, mDC, Mem_CD4, Naive_B, Naive_CD4, Neu, NK, pDC, Plasmablast, SM_B, Tfh, Th1, Th17, Th2, USM_B). 15 RA patients were analyzed longitudinally. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered. JGAS000485: Peripheral blood B cell subsets from study population were collected (Naive_B, USM_B, SM_B, DN_B, Plasmablast). RNA-seq was performed with each B cell subset samples. B cell receptor sequences were aligned. JGAS000626: 9 immune cell subsets from study population were collected (Naive_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, ThA). RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered. JGAS000627: 27 immune cell subsets from study population were collected (Naive_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, ThA, Naive_CD8, Naive_B, SM_B, USM_B, DN_B, Plasmablast, NK, CD16p_Mono, CL_Mono, Neu, mDC, pDC, TEMRA_CD8, CM_CD8, EM_CD8, NC_Mono, Int_Mono, LDG). RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered. JGAS000648: Peripheral blood, muscle tissue, and bronchial lavage fluid were collected from each subject. For peripheral blood, CD4T cells were collected and scRNA-seq was performed to quantify gene expression. For muscle tissue and bronchial lavage fluid, CD45-positive cells were collected, scRNA-seq was performed, gene expression was quantified, and CD4T cluster was selected. JGAS000762: Peripheral blood T cell subsets from study population were collected (Naive_CD4, Mem_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Naive_CD8, TEMRA_CD8, CM_CD8, EM_CD8). RNA-seq was performed with each T cell subset samples. T cell receptor sequences were aligned.

Targets: Systemic Sclerosis, Systemic Lupus Erythematosus, Myositis, Mixed Connective Tissue Disease, Sjögren's Syndrome, Rheumatoid Arthritis, Behçet's Disease, Adult Onset Still's Disease, ANCA-associated Vasculitis, Takayasu's Arteritis, healthy individuals

Datasets

Dataset ID
Access type
Type of data
Release date
JGAD000309Controlled-access (Type I)NGS (RNA-seq: Systemic sclerosis)2021-03-09
JGAD000310Controlled-access (Type I)NGS (RNA-seq: Systemic sclerosis)2021-03-09
JGAD000371Controlled-access (Type I)NGS (RNA-seq: Systemic sclerosis)2022-03-16
JGAD000372Controlled-access (Type I)NGS (RNA-seq: Systemic sclerosis)2022-03-16
JGAD000373Controlled-access (Type I)NGS (RNA-seq: Systemic sclerosis)2022-03-16
E-GEAD-397Unrestricted-accessRead count data from RNA-seq2021-04-28
E-GEAD-398Unrestricted-accessConditional eQTL summary data (significant associations)2021-04-28
E-GEAD-420Unrestricted-accessNominal eQTL data (including non-significant associations)2021-04-28
JGAD000406Controlled-access (Type I)NGS (RNA-seq)2022-01-19
JGAD000603Controlled-access (Type I)NGS (RNA-seq)2022-08-24
JGAD000727Controlled-access (Type I)NGS (RNA-seq)2023-03-28
JGAD000602Controlled-access (Type I)B cell receptor repertoire clonotype data from B cell RNA-seq2023-07-10
JGAD000755Controlled-access (Type I)NGS (RNA-seq)2024-02-14
JGAD000756Controlled-access (Type I)NGS (RNA-seq)2024-02-14
JGAD000778Controlled-access (Type I)NGS (scRNA-seq)2024-02-14
JGAD000903Controlled-access (Type I)T cell receptor repertoire clonotype data from T cell RNA-seq2026-06-12

Data provider

    Principal investigator
    Keishi Fujio
    Name
    Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo

Research projects

Name
URL
Immune cell multi-omics analysis of immune-mediated diseaseshttps://www.h.u-tokyo.ac.jp/english/centers-services/clinical-divisions/allergy-and-rheumatology/index.html

Grants

Name
Title
Project number
Practical Research Project for Rare / Intractable Diseases, Japan Agency for Medical Research and Development (AMED)Identification of therapeutic targets and development of intervention strategy for systemic lupus erythematosus based on the comprehensive analysis of genome and transcriptome.
  • JP17ek0109103
Platform Program for Promotion of Genome Medicine, Japan Agency for Medical Research and Development (AMED)Construction of stratification and prognosis prediction models from immune-mediated disease genomic information using immune cell eQTL data
  • JP21tm0424221
Moonshot Research and Development Program, Japan Agency for Medical Research and Development (AMED)Quantum and neuron modulation technologies to suppress tissue-specific disease-related microinflammation
  • JP21zf0127004
Practical Research Project for Allergic Diseases and Immunology, Japan Agency for Medical Research and Development (AMED)Integrative multi-omics analysis of autoimmune diseases based on single cell RNA-sequencing of inflammatory organs
  • JP22ek0410074
Advanced Research and Development Programs for Medical Innovation , Japan Agency for Medical Research and Development (AMED-CREST)Study of T cell subsets associated with immune memory for both cytotoxic and adaptive immune responses in autoimmune diseases
  • JP23gm1810005
KAKENHI Grant-in-Aid for Scientific Research (B)Single-cell multiome profiling and functional analysis of human age-associated T cells in autoimmune diseases
  • 22H03110
Collaborative research fund with Chugai Pharmaceutical Co., Ltd.

    Related publications

    Title
    DOI
    Dataset ID
    Integrated bulk and single-cell RNA-sequencing identified disease-relevant monocytes and a gene network module underlying systemic sclerosishttps://doi.org/10.1016/j.jaut.2020.102547
    Identifying the most influential gene expression profile in distinguishing ANCA-associated vasculitis from healthy controlshttps://doi.org/10.1016/j.jaut.2021.102617
    Dynamic landscape of immune cell-specific gene regulation in immune-mediated diseaseshttps://doi.org/10.1016/j.cell.2021.03.056
    Dysregulation of the gene signature of effector regulatory T cells in the early phase of systemic sclerosishttps://doi.org/10.1093/rheumatology/keac031
    Immune cell multiomics analysis reveals contribution of oxidative phosphorylation to B-cell functions and organ damage of lupushttps://doi.org/10.1136/annrheumdis-2021-221464
    Distinct transcriptome architectures underlying lupus establishment and exacerbationhttps://doi.org/10.1016/j.cell.2022.07.021
    Immunomics analysis of rheumatoid arthritis identified precursor dendritic cells as a key cell subset of treatment resistancehttps://doi.org/10.1136/ard-2022-223645
    Multimodal repertoire analysis unveils B cell biology in immune-mediated diseaseshttps://doi.org/10.1136/ard-2023-224421
    Age-associated CD4+ T cells with B cell-promoting functions are regulated by ZEB2 in autoimmunityhttps://doi.org/10.1126/sciimmunol.adk1643
    T cell plasticity in systemic lupus erythematosus revealed by large-scale T cell receptor repertoire and transcriptome studieshttps://doi.org/10.1002/art.70218

    Controlled access users

    Principal Investigator
    Affiliation
    Country/Region
    Research title
    Period of data use
    Dataset ID
    Grosso Ana RitaUniversidade Nova de Lisboa - NOVA School of Science and TechnologyPortugalAssessing transcriptional dyregulation of repetitive elements and monoallelic-expressed genes in lupus2023-04-252026-04-10
    Itakura EisukeChiba UniversityJapanLinking SLE Symptoms to Gene Expression Variation through ImmuNexUT2025-10-272026-04-02
    Suzuki HironaoKaken Pharmaceutical,co.,LTD.JapanBioinformatics analysis of immune cells from SLE patients2024-05-092025-04-17
    Li HuiUniversity of VirginiaUSAGene fusions and RNA Trans-splicing in normal and neoplastic human cells2025-06-252026-12-31
    Hamada MichiakiWaseda UniversityJapanConstruction of RNA-targeted Drug Discovery Database2023-01-052027-10-31
    wang jiucundepartment of anthropology and human genetics of fudan universityChinaThe role and mechanism study of glycosyltransferase-B3GNT2 in regulating macrophages of Ankylosing Spondylitis2023-03-082024-03-02
    Jaffe JacobOdyssey TherapeuticsUSAInvestigation of immune cell transition states in autoimmune disease2023-04-062023-11-02
    Matsumoto IsaoInstitute of Medicine, University of TsukubaJapanInvestigation of aging-related functional alterations in CD4⁺ T cells in rheumatoid arthritis and experimental arthritis models2025-12-052029-03-31
    Sood PranidhiWield Therapeutics, IncUSAIdentifying Gene Expression Based Biomarkers in Patients with Autoimmune Diseases to Predict Response to New Therapies Developed by Wield Therapeutics2025-06-252027-04-23
    Kubota ShimpeiHokkaido UniversityJapanCuring autoimmune diseases by quantum and neural forces2024-02-262026-04-01
    takeda yoshitoOsaka UniversityJapanPathophysiology and diagnostic development with a focus on extracellular vesicles in respiratory and immunological diseases2023-04-122025-01-17
    Ban TatsumaYokohama City UniversityJapanPathophysiology and therapeutic development of autoimmune diseases focusing on transcription factors of the immune system2024-11-122027-03-31
    Vyse TimothyKing's College LondonUnited KingdomSequencing Based Genetic Analysis of Systemic Lupus2023-08-252025-10-16
    WANG Yong-FeiThe Chinese University of Hong Kong, ShenzhenChinaInvestigating the Molecular Mechanisms of Systemic Lupus Erythematosus Using Functional Genomics Data2023-06-212025-05-28