Details of a Researcher - Ishigaki, Kazuyoshi

Papers - Ishigaki, Kazuyoshi

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Interferon subverts an AHR–JUN axis to promote CXCL13+ T cells in lupus

Law C., Wacleche V.S., Cao Y., Pillai A., Sowerby J., Hancock B., Horisberger A., Bracero S., Skidanova V., Li Z., Adejoorin I., Dillon E., Benque I.J., Nunez D.P., Simmons D.P., Keegan J., Chen L., Baker T., Brohawn P.Z., Al-Mossawi H., Hao L.Y., Jones B., Rao N., Qu Y., Alves S.E., Albrecht J., Anolik J.H., Apruzzese W., Barnas J.L., Bathon J.M., Ben-Artzi A., Boyce B.F., Boyle D.L., Bridges S.L., Bykerk V.P., Campbell D., Ceponis A., Chicoine A., Curtis M., Deane K.D., DiCarlo E., Donlin L.T., Dunn P., Filer A., Carr H., Firestein G.S., Forbess L., Geraldino-Pardilla L., Goodman S.M., Gravallese E.M., Gregersen P.K., Guthridge J.M., Gutierrez-Arcelus M., Holers V.M., Horowitz D., Hughes L.B., Ivashkiv L.B., Ishigaki K., James J.A., Jonsson A.H., Kang J.B., Keras G., Korsunsky I., Lakhanpal A., Lederer J.A., Lewis M.J., Li Y., Liao K., Mandelin A.M., Mantel I., Marks K.E., Maybury M., McDavid A., McGeachy M.J., Mears J.R., Meednu N., Millard N., Moreland L., Nayar S., Nerviani A., Orange D.E., Perlman H., Pitzalis C., Rangel-Moreno J., Raychaudhuri S., Raza K., Reshef Y., Ritchlin C., Rivellese F., Robinson W.H., Rumker L., Sahbudin I., Sakaue S., Seifert J.A., Scheel-Toellner D., Singaraju A., Slowikowski K., Smith M., Tabechian D., Utz P.J.

Nature 631 ( 8022 ) 857 - 866 2024.07

ISSN 00280836

Systemic lupus erythematosus (SLE) is prototypical autoimmune disease driven by pathological T cell–B cell interactions1,2. Expansion of T follicular helper (T<inf>FH</inf>) and T peripheral helper (T<inf>PH</inf>) cells, two T cell populations that provide help to B cells, is a prominent feature of SLE3,4. Human T<inf>FH</inf> and T<inf>PH</inf> cells characteristically produce high levels of the B cell chemoattractant CXCL13 (refs. 5,6), yet regulation of T cell CXCL13 production and the relationship between CXCL13+ T cells and other T cell states remains unclear. Here, we identify an imbalance in CD4+ T cell phenotypes in patients with SLE, with expansion of PD-1+/ICOS+ CXCL13+ T cells and reduction of CD96hi IL-22+ T cells. Using CRISPR screens, we identify the aryl hydrocarbon receptor (AHR) as a potent negative regulator of CXCL13 production by human CD4+ T cells. Transcriptomic, epigenetic and functional studies demonstrate that AHR coordinates with AP-1 family member JUN to prevent CXCL13+ T<inf>PH</inf>/T<inf>FH</inf> cell differentiation and promote an IL-22+ phenotype. Type I interferon, a pathogenic driver of SLE7, opposes AHR and JUN to promote T cell production of CXCL13. These results place CXCL13+ T<inf>PH</inf>/T<inf>FH</inf> cells on a polarization axis opposite from T helper 22 (T<inf>H</inf>22) cells and reveal AHR, JUN and interferon as key regulators of these divergent T cell states.

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An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases

Oguchi A., Suzuki A., Komatsu S., Yoshitomi H., Bhagat S., Son R., Bonnal R.J.P., 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.

Science 385 ( 6704 ) eadd8394 2024.07

ISSN 00368075

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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Tissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles

Sakaue S., Weinand K., Isaac S., Dey K.K., Jagadeesh K., Kanai M., Watts G.F.M., Zhu Z., Brenner M.B., McDavid A., Donlin L.T., Wei K., Price A.L., Raychaudhuri S., Albrecht J., Anolik J.H., Apruzzese W., Banda N., Barnas J.L., Bathon J.M., Ben-Artzi A., Boyce B.F., Boyle D.L., Bridges S.L., Bykerk V.P., Campbell D., Carr H.L., Ceponis A., Chicoine A., Cordle A., Curtis M., Deane K.D., DiCarlo E., Dunn P., Filer A., Firestein G.S., Forbess L., Geraldino-Pardilla L., Goodman S.M., Gravallese E.M., Gregersen P.K., Guthridge J.M., Gutierrez-Arcelus M., Gurajala S., Michael Holers V., Horowitz D., Hughes L.B., Ishigaki K., Ivashkiv L.B., James J.A., Jonsson A.H., Kang J.B., Keras G., Korsunsky I., Lakhanpal A., Lederer J.A., Li Z.J., Li Y., Liao K.P., Mandelin A.M., Mantel I., Maybury M., Mears J., Meednu N., Millard N., Moreland L.W., Nathan A., Nerviani A., Orange D.E., Perlman H., Pitzalis C., Rangel-Moreno J., Rao D.A., Raza K., Reshef Y., Ritchlin C., Rivellese F., Robinson W.H., Rumker L., Sahbudin I., Seifert J.A., Slowikowski K., Smith M.H., Tabechian D., Scheel-Toellner D., Utz P.J., Weisenfeld D., Weisman M.H., Xiao Q., Zhang F.

Nature Genetics 56 ( 4 ) 615 - 626 2024.04

ISSN 10614036

Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer–gene maps from disease-relevant tissues. Building enhancer–gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer–gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer–gene maps, essential for defining noncoding variant function.

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Age-associated CD4+ T cells with B cell–promoting functions are regulated by ZEB2 in autoimmunity

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.

Science Immunology 9 ( 93 ) eadk1643 2024.03

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 (T<inf>H</inf>A) cells.” T<inf>H</inf>A 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 T<inf>H</inf>A cells, gene expression in T<inf>H</inf>A 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 T<inf>H</inf>A cells infiltrate damaged organs in patients with autoimmune diseases. Together, our characterization of T<inf>H</inf>A cells may facilitate improved understanding of the relationship between aging and autoimmune diseases.

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Associations Between Rheumatoid Arthritis Clinical Factors and Synovial Cell Types and States

Weisenfeld D., Zhang F., Donlin L., Jonsson A.H., Apruzzese W., Campbell D., Albrecht J., Barnas J.L., Bathon J.M., Ben-Artzi A., Boyce B.F., Boyle D.L., Louis Bridges S., Carr H.L., Ceponis A., Chicoine A., Cordle A., Curtis M., Deane K.D., DiCarlo E., Dunn P., Firestein G.S., Forbess L., Geraldino-Pardilla L., Gregersen P.K., Guthridge J.M., Gutierrez-Arcelus M., Gurajala S., Horowitz V.D., Hughes L.B., Ishigaki K., Ivashkiv L.B., James J.A., Kang J.B., Keras G., Korsunsky I., Lakhanpal A., Lederer J.A., Lewis M., Li Z.J., Li Y., Mandelin A.M., Mantel I., Marks K., Maybury M., McDavid A., McGeachy M.J., Mears J., Meednu N., Millard N., Nathan A., Nayar S., Nerviani A., Orange D.E., Perlman H., Pitzalis C., Rangel-Moreno J., Raza K., Reshef Y., Ritchlin C., Rivellese F., Robinson W.H., Rumker L., Sahbudin I., Sakaue S., Scheel-Toellner D., Seifert J.A., Singaraju A., Slowikowski K., Smith M.H., Tabechian D., Utz P.J., Watts G.F.M., Weinand K., Weisman M.H., Wyse A., Xiao Q., Zhu Z., Rao D.A., Wei K., Holers V.M., Gravallese E., Moreland L., Goodman S., Brenner M., Raychaudhuri S., Filer A., Anolik J., Bykerk V., Liao K.P.

Arthritis and Rheumatology 76 ( 3 ) 356 - 362 2024.03

ISSN 23265191

Objective: Recent studies have uncovered diverse cell types and states in the rheumatoid arthritis (RA) synovium; however, limited data exist correlating these findings with patient-level clinical information. Using the largest cohort to date with clinical and multicell data, we determined associations between RA clinical factors with cell types and states in the RA synovium. Methods: The Accelerated Medicines Partnership Rheumatoid Arthritis study recruited patients with active RA who were not receiving disease-modifying antirheumatic drugs (DMARDs) or who had an inadequate response to methotrexate (MTX) or tumor necrosis factor inhibitors. RA clinical factors were systematically collected. Biopsies were performed on an inflamed joint, and tissue were disaggregated and processed with a cellular indexing of transcriptomes and epitopes sequencing pipeline from which the following cell type percentages and cell type abundance phenotypes (CTAPs) were derived: endothelial, fibroblast, and myeloid (EFM); fibroblasts; myeloid; T and B cells; T cells and fibroblasts (TF); and T and myeloid cells. Correlations were measured between RA clinical factors, cell type percentage, and CTAPs. Results: We studied 72 patients (mean age 57 years, 75% women, 83% seropositive, mean RA duration 6.6 years, mean Disease Activity Score-28 C-reactive Protein 3 [DAS28-CRP3] score 4.8). Higher DAS28-CRP3 correlated with a higher T cell percentage (P < 0.01). Those receiving MTX and not a biologic DMARD (bDMARD) had a higher percentage of B cells versus those receiving no DMARDs (P < 0.01). Most of those receiving bDMARDs were categorized as EFM (57%), whereas none were TF. No significant difference was observed across CTAPs for age, sex, RA disease duration, or DAS28-CRP3. Conclusion: In this comprehensive screen of clinical factors, we observed differential associations between DMARDs and cell phenotypes, suggesting that RA therapies, more than other clinical factors, may impact cell type/state in the synovium and ultimately influence response to subsequent therapies.

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How can genetics analysis allow for early detection of rheumatoid arthritis

Yamamoto K., Ishigaki K., Okada Y.

Seminars in Arthritis and Rheumatism 64 152323 2024.02

ISSN 00490172

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Natural history of Becker muscular dystrophy: a multicenter study of 225 patients.

Nakamura A, Matsumura T, Ogata K, Mori-Yoshimura M, Takeshita E, Kimura K, Kawashima T, Tomo Y, Arahata H, Miyazaki D, Takeshima Y, Takahashi T, Ishigaki K, Kuru S, Wakisaka A, Awano H, Funato M, Sato T, Saito Y, Takada H, Sugie K, Kobayashi M, Ozasa S, Fujii T, Maegaki Y, Oi H, Tachimori H, Komaki H

Annals of clinical and translational neurology 10 ( 12 ) 2360 - 2372 2023.12

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Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

Kang J.B., Shen A.Z., Gurajala S., Nathan A., Rumker L., Aguiar V.R.C., Valencia C., Lagattuta K.A., Zhang F., Jonsson A.H., Yazar S., Alquicira-Hernandez J., Khalili H., Ananthakrishnan A.N., Jagadeesh K., Dey K., Albrecht J., Apruzzese W., Banda N., Barnas J.L., Bathon J.M., Ben-Artzi A., Boyce B.F., Boyle D.L., Bridges S.L., Bykerk V.P., Campbell D., Carr H.L., Ceponis A., Chicoine A., Cordle A., Curtis M., Deane K.D., DiCarlo E., Dunn P., Filer A., Firestein G.S., Forbess L., Geraldino-Pardilla L., Goodman S.M., Gravallese E.M., Gregersen P.K., Guthridge J.M., Holers V.M., Horowitz D., Hughes L.B., Ishigaki K., Ivashkiv L.B., James J.A., Keras G., Korsunsky I., Lakhanpal A., Lederer J.A., Lewis M., Li Z.J., Li Y., Liao K.P., Mandelin A.M., Mantel I., Marks K.E., Maybury M., McDavid A., McGeachy M.J., Mears J., Meednu N., Millard N., Moreland L.W., Nayar S., Nerviani A., Orange D.E., Perlman H., Pitzalis C., Rangel-Moreno J., Raza K., Reshef Y., Ritchlin C., Rivellese F., Robinson W.H., Sahbudin I., Singaraju A., Seifert J.A., Slowikowski K., Smith M.H., Tabechian D., Scheel-Toellner D., Utz P.J., Watts G.F.M., Wei K., Weinand K., Weisenfeld D., Weisman M.H., Wyse A., Xiao Q., Zhu Z., Daly M.J., Xavier R.J., Donlin L.T., Anolik J.H., Powell J.E., Rao D.A.

Nature Genetics 55 ( 12 ) 2255 - 2268 2023.12

ISSN 10614036

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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Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin

Xiao Q., Mears J., Nathan A., Ishigaki K., Baglaenko Y., Lim N., Cooney L.A., Harris K.M., Anderson M.S., Fox D.A., Smilek D.E., Krueger J.G., Raychaudhuri S.

Nature Communications 14 ( 1 ) 2023.12

Psoriasis is a chronic, systemic inflammatory condition primarily affecting skin. While the role of the immune compartment (e.g., T cells) is well established, the changes in the skin compartment are more poorly understood. Using longitudinal skin biopsies (n = 375) from the “Psoriasis Treatment with Abatacept and Ustekinumab: A Study of Efficacy”(PAUSE) clinical trial (n = 101), we report 953 expression quantitative trait loci (eQTLs). Of those, 116 eQTLs have effect sizes that were modulated by local skin inflammation (eQTL interactions). By examining these eQTL genes (eGenes), we find that most are expressed in the skin tissue compartment, and a subset overlap with the NRF2 pathway. Indeed, the strongest eQTL interaction signal – rs1491377616-LCE3C – links a psoriasis risk locus with a gene specifically expressed in the epidermis. This eQTL study highlights the potential to use biospecimens from clinical trials to discover in vivo eQTL interactions with therapeutically relevant environmental variables.

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Genome-wide association study reveals BET1L associated with survival time in the 137,693 Japanese individuals

Akiyama M., Sakaue S., Takahashi A., Ishigaki K., Hirata M., Matsuda K., Momozawa Y., Okada Y., Ninomiya T., Koido M., Morisaki T., Nagai A., Sagiya Y., Terao C., Murakami Y., Kubo M., Kamatani Y.

Communications Biology 6 ( 1 ) 143 2023.12

Human lifespan is reported to be heritable. Although previous genome-wide association studies (GWASs) have identified several loci, a limited number of studies have assessed the genetic associations with the real survival information on the participants. We conducted a GWAS to identify loci associated with survival time in the Japanese individuals participated in the BioBank Japan Project by carrying out sex-stratified GWASs involving 78,029 males and 59,664 females. Of them, 31,324 (22.7%) died during the mean follow-up period of 7.44 years. We found a novel locus associated with survival (BET1L; P = 5.89 × 10−9). By integrating with eQTL data, we detected a significant overlap with eQTL of BET1L in skeletal muscle. A gene-set enrichment analysis showed that genes related to the BCAR1 protein–protein interaction subnetwork influence survival time (P = 1.54 × 10−7). These findings offer the candidate genes and biological mechanisms associated with human lifespan.

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Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes

Zhang F., Jonsson A.H., Nathan A., Millard N., Curtis M., Xiao Q., Gutierrez-Arcelus M., Apruzzese W., Watts G.F.M., Weisenfeld D., Nayar S., Rangel-Moreno J., Meednu N., Marks K.E., Mantel I., Kang J.B., Rumker L., Mears J., Slowikowski K., Weinand K., Orange D.E., Geraldino-Pardilla L., Deane K.D., Tabechian D., Ceponis A., Firestein G.S., Maybury M., Sahbudin I., Ben-Artzi A., Mandelin A.M., Nerviani A., Lewis M.J., Rivellese F., Pitzalis C., Hughes L.B., Horowitz D., DiCarlo E., Gravallese E.M., Boyce B.F., Albrecht J., Barnas J.L., Bathon J.M., Boyle D.L., Bridges S.L., Campbell D., Carr H.L., Chicoine A., Cordle A., Dunn P., Forbess L., Gregersen P.K., Guthridge J.M., Ivashkiv L.B., Ishigaki K., James J.A., Keras G., Korsunsky I., Lakhanpal A., Lederer J.A., Li Z.J., Li Y., McDavid A., McGeachy M.J., Raza K., Reshef Y., Ritchlin C., Robinson W.H., Sakaue S., Seifert J.A., Singaraju A., Smith M.H., Scheel-Toellner D., Utz P.J., Weisman M.H., Wyse A., Zhu Z., Moreland L.W., Goodman S.M., Perlman H., Holers V.M., Liao K.P., Filer A., Bykerk V.P., Wei K., Rao D.A., Donlin L.T., Anolik J.H., Brenner M.B., Raychaudhuri S.

Nature 623 ( 7987 ) 616 - 624 2023.11

ISSN 00280836

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.

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Identification of a regulatory pathway governing TRAF1 via an arthritis-associated non-coding variant

Wang Q., Martínez-Bonet M., Kim T., Sparks J.A., Ishigaki K., Chen X., Sudman M., Aguiar V., Sim S., Hernandez M.C., Chiu D.J., Wactor A., Wauford B., Marion M.C., Gutierrez-Arcelus M., Bowes J., Eyre S., Nordal E., Prahalad S., Rygg M., Videm V., Raychaudhuri S., Weirauch M.T., Langefeld C.D., Thompson S.D., Nigrovic P.A.

Cell Genomics 3 ( 11 ) 2023.11

TRAF1/C5 was among the first loci shown to confer risk for inflammatory arthritis in the absence of an associated coding variant, but its genetic mechanism remains undefined. Using Immunochip data from 3,939 patients with juvenile idiopathic arthritis (JIA) and 14,412 control individuals, we identified 132 plausible common non-coding variants, reduced serially by single-nucleotide polymorphism sequencing (SNP-seq), electrophoretic mobility shift, and luciferase studies to the single variant rs7034653 in the third intron of TRAF1. Genetically manipulated experimental cells and primary monocytes from genotyped donors establish that the risk G allele reduces binding of Fos-related antigen 2 (FRA2), encoded by FOSL2, resulting in reduced TRAF1 expression and enhanced tumor necrosis factor (TNF) production. Conditioning on this JIA variant eliminated attributable risk for rheumatoid arthritis, implicating a mechanism shared across the arthritis spectrum. These findings reveal that rs7034653, FRA2, and TRAF1 mediate a pathway through which a non-coding functional variant drives risk of inflammatory arthritis in children and adults.

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Multimodal repertoire analysis unveils B cell biology in immune-mediated diseases

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.

Annals of the Rheumatic Diseases 82 ( 11 ) 1455 - 1463 2023.11

ISSN 00034967

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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Multimodal repertoire analysis unveils B cell biology in immune-mediated diseases.

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

Annals of the rheumatic diseases 82 ( 11 ) 1455 - 1463 2023.11

ISSN 0003-4967

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Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin.

Xiao Q, Mears J, Nathan A, Ishigaki K, Baglaenko Y, Lim N, Cooney LA, Harris KM, Anderson MS, Fox DA, Smilek DE, Krueger JG, Raychaudhuri S

Nature communications 14 ( 1 ) 6268 2023.10

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Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease

Sakaue S., Gurajala S., Curtis M., Luo Y., Choi W., Ishigaki K., Kang J.B., Rumker L., Deutsch A.J., Schönherr S., Forer L., LeFaive J., Fuchsberger C., Han B., Lenz T.L., de Bakker P.I.W., Okada Y., Smith A.V., Raychaudhuri S.

Nature Protocols 18 ( 9 ) 2625 - 2641 2023.09

ISSN 17542189

The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software (https://github.com/immunogenomics/HLA_analyses_tutorial). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.

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Population-specific reference panel improves imputation quality and enhances locus discovery and fine-mapping

2023.08

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Immunomics analysis of rheumatoid arthritis identified precursor dendritic cells as a key cell subset of treatment resistance

Yamada S., Nagafuchi Y., Wang M., Ota M., Hatano H., Takeshima Y., Okubo M., Kobayashi S., Sugimori Y., Masahiro N., Yoshida R., Hanata N., Suwa Y., Tsuchida Y., Iwasaki Y., Sumitomo S., Kubo K., Shimane K., Setoguchi K., Azuma T., Kanda H., Shoda H., Zhang X., Yamamoto K., Ishigaki K., Okamura T., Fujio K.

Annals of the Rheumatic Diseases 82 ( 6 ) 809 - 819 2023.06

ISSN 00034967

Objectives Little is known about the immunology underlying variable treatment response in rheumatoid arthritis (RA). We performed large-scale transcriptome analyses of peripheral blood immune cell subsets to identify immune cells that predict treatment resistance. Methods We isolated 18 peripheral blood immune cell subsets of 55 patients with RA requiring addition of new treatment and 39 healthy controls, and performed RNA sequencing. Transcriptome changes in RA and treatment effects were systematically characterised. Association between immune cell gene modules and treatment resistance was evaluated. We validated predictive value of identified parameters for treatment resistance using quantitative PCR (qPCR) and mass cytometric analysis cohorts. We also characterised the identified population by synovial single cell RNA-sequencing analysis. Results Immune cells of patients with RA were characterised by enhanced interferon and IL6-JAK-STAT3 signalling that demonstrate partial normalisation after treatment. A gene expression module of plasmacytoid dendritic cells (pDC) reflecting the expansion of dendritic cell precursors (pre-DC) exhibited strongest association with treatment resistance. Type I interferon signalling was negatively correlated to pre-DC gene expression. qPCR and mass cytometric analysis in independent cohorts validated that the pre-DC associated gene expression and the proportion of pre-DC were significantly higher before treatment in treatment-resistant patients. A cluster of synovial DCs showed both features of pre-DC and pro-inflammatory conventional DC2s. Conclusions An increase in pre-DC in peripheral blood predicted RA treatment resistance. Pre-DC could have pathophysiological relevance to RA treatment response.

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Prediction of the cell-type-specific transcription of non-coding RNAs from genome sequences via machine learning

Koido M., Hon C.C., Koyama S., Kawaji H., Murakawa Y., Ishigaki K., Ito K., Sese J., Parrish N.F., Kamatani Y., Carninci P., Terao C.

Nature Biomedical Engineering 7 ( 6 ) 830 - 844 2023.06

Gene transcription is regulated through complex mechanisms involving non-coding RNAs (ncRNAs). As the transcription of ncRNAs, especially of enhancer RNAs, is often low and cell type specific, how the levels of RNA transcription depend on genotype remains largely unexplored. Here we report the development and utility of a machine-learning model (MENTR) that reliably links genome sequence and ncRNA expression at the cell type level. Effects on ncRNA transcription predicted by the model were concordant with estimates from published studies in a cell-type-dependent manner, regardless of allele frequency and genetic linkage. Among 41,223 variants from genome-wide association studies, the model identified 7,775 enhancer RNAs and 3,548 long ncRNAs causally associated with complex traits across 348 major human primary cells and tissues, such as rare variants plausibly altering the transcription of enhancer RNAs to influence the risks of Crohn’s disease and asthma. The model may aid the discovery of causal variants and the generation of testable hypotheses for biological mechanisms driving complex traits.

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Mobile element variation contributes to population-specific genome diversification, gene regulation and disease risk

Kojima S., Koyama S., Ka M., Saito Y., Parrish E.H., Endo M., Takata S., Mizukoshi M., Hikino K., Takeda A., Gelinas A.F., Heaton S.M., Koide R., Kamada A.J., Noguchi M., Hamada M., Matsuda K., Yamanashi Y., Furukawa Y., Morisaki T., Murakami Y., Muto K., Nagai A., Obara W., Yamaji K., Takahashi K., Asai S., Takahashi Y., Suzuki T., Sinozaki N., Yamaguchi H., Minami S., Murayama S., Yoshimori K., Nagayama S., Obata D., Higashiyama M., Masumoto A., Koretsune Y., Kamatani Y., Murakawa Y., Ishigaki K., Nakamura Y., Ito K., Terao C., Momozawa Y., Parrish N.F.

Nature Genetics 55 ( 6 ) 939 - 951 2023.06

ISSN 10614036

Mobile genetic elements (MEs) are heritable mutagens that recursively generate structural variants (SVs). ME variants (MEVs) are difficult to genotype and integrate in statistical genetics, obscuring their impact on genome diversification and traits. We developed a tool that accurately genotypes MEVs using short-read whole-genome sequencing (WGS) and applied it to global human populations. We find unexpected population-specific MEV differences, including an Alu insertion distribution distinguishing Japanese from other populations. Integrating MEVs with expression quantitative trait loci (eQTL) maps shows that MEV classes regulate tissue-specific gene expression by shared mechanisms, including creating or attenuating enhancers and recruiting post-transcriptional regulators, supporting class-wide interpretability. MEVs more often associate with gene expression changes than SNVs, thus plausibly impacting traits. Performing genome-wide association study (GWAS) with MEVs pinpoints potential causes of disease risk, including a LINE-1 insertion associated with keloid and fasciitis. This work implicates MEVs as drivers of human divergence and disease risk.

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