Dataset Information

Single-cell transcriptome landscape of circulating CD4⁺ T cell populations in autoimmune diseases.

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.

SUBMITTER: Yasumizu Y

PROVIDER: S-EPMC10879034 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Single-cell transcriptome landscape of circulating CD4+ T cell populations in autoimmune diseases.

Yasumizu Yoshiaki Y Takeuchi Daiki D Morimoto Reo R Takeshima Yusuke Y Okuno Tatsusada T Kinoshita Makoto M Morita Takayoshi T Kato Yasuhiro Y Wang Min M Motooka Daisuke D Okuzaki Daisuke D Nakamura Yamami Y Mikami Norihisa N Arai Masaya M Zhang Xuan X Kumanogoh Atsushi A Mochizuki Hideki H Ohkura Naganari N Sakaguchi Shimon S

Cell genomics 20240103 2

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 perf ...[more]

PMID: 38359792

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Project description:Epigenetics may play a central, yet unexplored, role in the profound changes that the maternal immune system undergoes during pregnancy and could be involved in the pregnancy-induced modulation of several autoimmune diseases. We investigated changes in the methylome in isolated circulating CD4+ T-cells in non-pregnant and pregnant women, during the 1st and 2nd trimester, using the Illumina Infinium Human Methylation 450K array, and explored how these changes were related to autoimmune diseases that are known to be affected during pregnancy. Pregnancy was associated with several hundreds of methylation differences, particularly during the 2nd trimester. A network-based modular approach identified several genes, e.g., CD28, FYN, VAV1 and pathways related to T-cell signalling and activation, highlighting T-cell regulation as a central component of the observed methylation alterations. The identified pregnancy module was significantly enriched for disease-associated methylation changes related to multiple sclerosis, rheumatoid arthritis and systemic lupus erythematosus. A negative correlation between pregnancy-associated methylation changes and disease-associated changes was found for multiple sclerosis and rheumatoid arthritis, diseases that are known to improve during pregnancy whereas a positive correlation was found for systemic lupus erythematosus, a disease that instead worsens during pregnancy. Thus, the directionality of the observed changes is in line with the previously observed effect of pregnancy on disease activity. Our systems medicine approach supports the importance of the methylome in immune regulation of T-cells during pregnancy. Our findings highlight the relevance of using pregnancy as a model for understanding and identifying disease-related mechanisms involved in the modulation of autoimmune diseases.Abbreviations: BMIQ: beta-mixture quantile dilation; DMGs: differentially methylated genes; DMPs: differentially methylated probes; FE: fold enrichment; FDR: false discovery rate; GO: gene ontology; GWAS: genome-wide association studies; MDS: multidimensional scaling; MS: multiple sclerosis; PBMC: peripheral blood mononuclear cells; PBS: phosphate buffered saline; PPI; protein-protein interaction; RA: rheumatoid arthritis; SD: standard deviation; SLE: systemic lupus erythematosus; SNP: single nucleotide polymorphism; TH: CD4+ T helper cell; VIStA: diVIsive Shuffling Approach.

Dataset Information

Single-cell transcriptome landscape of circulating CD4⁺ T cell populations in autoimmune diseases.

Publications

Single-cell transcriptome landscape of circulating CD4<sup>+</sup> T cell populations in autoimmune diseases.

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