Researchers from Osaka University find characteristic changes in CD4+ T cell categories and gene programs associated with autoimmune disease
Much like ripples on the water can betray powerful currents below the surface, small changes in our bodies can sometimes be an indicator of a serious condition. Now, researchers from Japan say that cells in the blood may provide telltale signs of important immune dysfunction.
In a study recently published in Cell Genomics, researchers from Osaka University have revealed that subtle changes in specific immune cell populations may signal the presence of an autoimmune disease.
In autoimmune conditions, which affect up to 5% of the population, the body’s immune cells attack the body instead of disease-causing agents. A subset of immune cells known as CD4+ T cells are known to play a key role in the onset and progression of many autoimmune diseases.
“CD4+ T cells can exist in a naive or memory state, can exhibit polarization to a Th1, Th2, Th17, or Tfh phenotype, or can be regulatory T cells,” says lead author of the study Yoshiaki Yasumizu. “However, there is still a lot of heterogeneity among the cells in these categories, and the effect that this has on autoimmune disease remains largely unclear.”
To address this, the researchers used single-cell RNA sequencing and an analytical approach known as non-negative matrix factorization to analyze the gene expression profiles of CD4+ T cells in healthy individuals and patients with autoimmune diseases. This analysis identified 18 different types of CD4+ T cells and 12 distinct gene programs, which were then used as a reference to analyze almost 2 million CD4+ T cells from nearly 1000 people with 20 different autoimmune diseases.
“The results were very exciting,” explains Shimon Sakaguchi, senior author. “We found that characteristic changes in CD4+ T cells defined by the 18 categories and 12 gene programs were associated with specific autoimmune diseases, suggesting that these conditions have a detectable ‘signature’.”

In addition, the researchers detected distinctive changes in CD4+ T cell categories and gene programs that were linked to aging and sex, two factors that are known to influence the risk of developing an autoimmune disorder. Furthermore, genetic factors that promote disease development accumulated in CD4+ T cells exhibiting specific gene programs.
“Our study presents a comprehensive catalog of the CD4+ T cell changes that are seen in 20 different autoimmune diseases, providing an invaluable resource for researchers,” says Yasumizu.
In the future, this catalog could potentially be used to detect autoimmune disease in patients by simply taking a blood sample and analyzing the CD4+ T cell features, thus paving the way for precision medicine.
Source – Eurekalert
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. (2024) Single-cell transcriptome landscape of circulating CD4+ T cell populations in autoimmune diseases. Cell Genomics [Epub ahead of print]. [article]
Researchers from Osaka University find characteristic changes in CD4+ T cell categories and gene programs associated with autoimmune disease
Much like ripples on the water can betray powerful currents below the surface, small changes in our bodies can sometimes be an indicator of a serious condition. Now, researchers from Japan say that cells in the blood may provide telltale signs of important immune dysfunction.
In a study recently published in Cell Genomics, researchers from Osaka University have revealed that subtle changes in specific immune cell populations may signal the presence of an autoimmune disease.
In autoimmune conditions, which affect up to 5% of the population, the body’s immune cells attack the body instead of disease-causing agents. A subset of immune cells known as CD4+ T cells are known to play a key role in the onset and progression of many autoimmune diseases.
To address this, the researchers used single-cell RNA sequencing and an analytical approach known as non-negative matrix factorization to analyze the gene expression profiles of CD4+ T cells in healthy individuals and patients with autoimmune diseases. This analysis identified 18 different types of CD4+ T cells and 12 distinct gene programs, which were then used as a reference to analyze almost 2 million CD4+ T cells from nearly 1000 people with 20 different autoimmune diseases.
In addition, the researchers detected distinctive changes in CD4+ T cell categories and gene programs that were linked to aging and sex, two factors that are known to influence the risk of developing an autoimmune disorder. Furthermore, genetic factors that promote disease development accumulated in CD4+ T cells exhibiting specific gene programs.
In the future, this catalog could potentially be used to detect autoimmune disease in patients by simply taking a blood sample and analyzing the CD4+ T cell features, thus paving the way for precision medicine.
Source – Eurekalert
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. (2024) Single-cell transcriptome landscape of circulating CD4+ T cell populations in autoimmune diseases. Cell Genomics [Epub ahead of print]. [article]
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Researchers from Osaka University find characteristic changes in CD4+ T cell categories and gene programs associated with autoimmune disease
Much like ripples on the water can betray powerful currents below the surface, small changes in our bodies can sometimes be an indicator of a serious condition. Now, researchers from Japan say that cells in the blood may provide telltale signs of important immune dysfunction.
In a study recently published in Cell Genomics, researchers from Osaka University have revealed that subtle changes in specific immune cell populations may signal the presence of an autoimmune disease.
In autoimmune conditions, which affect up to 5% of the population, the body’s immune cells attack the body instead of disease-causing agents. A subset of immune cells known as CD4+ T cells are known to play a key role in the onset and progression of many autoimmune diseases.
To address this, the researchers used single-cell RNA sequencing and an analytical approach known as non-negative matrix factorization to analyze the gene expression profiles of CD4+ T cells in healthy individuals and patients with autoimmune diseases. This analysis identified 18 different types of CD4+ T cells and 12 distinct gene programs, which were then used as a reference to analyze almost 2 million CD4+ T cells from nearly 1000 people with 20 different autoimmune diseases.
In addition, the researchers detected distinctive changes in CD4+ T cell categories and gene programs that were linked to aging and sex, two factors that are known to influence the risk of developing an autoimmune disorder. Furthermore, genetic factors that promote disease development accumulated in CD4+ T cells exhibiting specific gene programs.
In the future, this catalog could potentially be used to detect autoimmune disease in patients by simply taking a blood sample and analyzing the CD4+ T cell features, thus paving the way for precision medicine.
Source – Eurekalert
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. (2024) Single-cell transcriptome landscape of circulating CD4+ T cell populations in autoimmune diseases. Cell Genomics [Epub ahead of print]. [article]
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Avoiding a sticky situation: how cells stop messenger RNAs from clumping together
New AI approaches to help understand complex biological data
Short-read RNA-seq yields lower estimates of A-to-I RNA editing levels than long-read cDNA sequencing
qMAP reveals RNA fragmentation patterns linked to development and disease
Urine microRNAs may help distinguish bacterial from viral infections in children
Benchmarking RNA sequencing for more accurate alternative splicing analysis
RNA Sequencing identifies new tick-borne virus that causes flu-like illness
Small RNA sequencing reveals regulatory roles for sdRNAs in acute myeloid leukemia
POND-seq enables non-destructive RNA sequencing in living cells
Worm’s radical transformation shows metamorphosis can change the functions of cells
New method allows scientists to follow gene activity over time in the same cells
Single-cell and single-embryo RNA sequencing
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Deep learning improves microRNA target prediction from sequence
Atlas of the brain’s striatum could guide researchers to new drug treatments
scLS – a computationally efficient differentially expressed gene detection algorithm
Spatial mapping of RNA turnover kinetics in the mouse brain
Immune cells offer insights on billion-dollar virus
SPIDER improves spatial transcriptomics data using single-cell RNA sequencing
Ultrafast and reference-free sequence discovery in single-cell data
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