A new study has revealed psoriatic arthritis may be activated by the same trigger in different patients. Researchers from the University of Oxford and the Wellcome Sanger Institute identified high levels of a specific receptor in immune cells from psoriatic arthritis patients, giving the strongest evidence yet of a single cause for the disease.
It was already known that the disease had a number of genetic predispositions, one of which controls how immune cells called T cells see antigen molecules from disease-causing microorganisms. However, it is not understood exactly what triggers the onset of psoriatic arthritis in patients.
Using cutting edge single cell technology, the researchers analysed thousands of individual immune cells from fluid drained from the knees of patients with psoriatic arthritis. They could see which genes were switched on in each cell and showed these T cells had an activated inflammatory profile. The researchers also amplified and sequenced the RNA from receptor genes, to identify active T cell receptors in each cell. The study showed that many T cells in the joint fluid shared an identical T cell receptor and were therefore clones of each other. These were very likely to have been triggered to reproduce themselves by a particular antigen.
Using machine learning to compare these receptors from different patients, they discovered that the expanded clones of T cells were potentially recognising something in common. These cells also shared other markers, including a receptor called CXCR3, that directed them to the inflammation site.
Transcriptional landscape of CD4 and CD8 T cells in psoriatic arthritis

a UMAP of integrated PsA blood, synovial fluid and synovial tissue memory CD4 and CD8 T cells (paired blood and synovial fluid from three patients; synovial tissue from two other patients). Clusters coloured red comprise CD8 cells, clusters coloured blue are CD4 cells. Clusters in grey contain mixed CD4 and CD8 populations. b Heatmap showing memory CD4 and CD8 immune subset signatures. The relative expression of marker genes (columns) across cell clusters (rows) is shown. c–e UMAPs showing the contribution of PBMC, SFMC and synovial fluid-derived T cells to the integrated UMAP from (a). f–h Volcano plots showing differential expression of genes between blood and synovial fluid T cells in HLA-DR-low (f), HLA-DR-high (g) and ZNF683+ (h) clusters (Supplementary Data 3a–c). Statistics calculated using two-sided Wilcoxon Rank Sum test with Bonferroni correction. Genes where adjusted p value < = 1E−04 and average logFC is greater than 0.75 or less than −0.75 are labelled and shown as red circles. Dotted lines indicate significance and average logFC cut-off for displaying labelled genes (paired blood and synovial fluid from three patients). Source data are provided as a Source Data file.
“Our data suggest that psoriatic arthritis doesn’t just appear out of nowhere. Each receptor is like a unique lock that recognises a molecular key and we discovered, that across the patients, they are recognising a common molecule. This gives the first evidence that the T cells are seeing and reacting to the same molecule, which acts as a trigger for the disease. We don’t know the exact culprit yet, but this a great step forward in understanding the disease.”
Dr Hussein Al-Mossawi – Honorary Research Associate at the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS) at the University of Oxford
The large-scale single cell data from the joints and blood of psoriatic arthritis patients were then used to investigate how the T cells could transfer from the blood to the joint to cause the damage.
“Our study produced the largest single cell dataset from psoriatic arthritis patients to date. It is helping us to understand the intricate mechanisms behind psoriatic arthritis, including starting to unravel the signals that tell the T cells to cross over into the joint fluid. Imagine the cells as train passengers with a ticket that tells them at which station to get off – the single cell data is allowing us to read that destination for each cell, and understand the signals.”
Dr Sam Behjati, Group Leader and Wellcome Trust Intermediate Clinical Fellow at the Wellcome Sanger Institute
“Our findings indicate that specific T cells are likely to be targeted to enter the joint, where they are triggered to expand, creating inflammation and causing psoriatic arthritis. The next stage of research will be to find the key that is unlocking the disease in patients – from the signals that direct cells to the joint, to what then triggers them to expand. If we can understand these, we could move towards creating therapies that would prevent this, potentially providing a cure.”
Professor Paul Bowness – Professor of Experimental Rheumatology at NDORMS
Source – Wellcome Sanger Institute
Penkava F, Velasco-Herrera MDC, Young MD et al. (2020) Single-cell sequencing reveals clonal expansions of pro-inflammatory synovial CD8 T cells expressing tissue-homing receptors in psoriatic arthritis. Nat Commun 11, 4767 . [article]
A new study has revealed psoriatic arthritis may be activated by the same trigger in different patients. Researchers from the University of Oxford and the Wellcome Sanger Institute identified high levels of a specific receptor in immune cells from psoriatic arthritis patients, giving the strongest evidence yet of a single cause for the disease.
It was already known that the disease had a number of genetic predispositions, one of which controls how immune cells called T cells see antigen molecules from disease-causing microorganisms. However, it is not understood exactly what triggers the onset of psoriatic arthritis in patients.
Using cutting edge single cell technology, the researchers analysed thousands of individual immune cells from fluid drained from the knees of patients with psoriatic arthritis. They could see which genes were switched on in each cell and showed these T cells had an activated inflammatory profile. The researchers also amplified and sequenced the RNA from receptor genes, to identify active T cell receptors in each cell. The study showed that many T cells in the joint fluid shared an identical T cell receptor and were therefore clones of each other. These were very likely to have been triggered to reproduce themselves by a particular antigen.
Using machine learning to compare these receptors from different patients, they discovered that the expanded clones of T cells were potentially recognising something in common. These cells also shared other markers, including a receptor called CXCR3, that directed them to the inflammation site.
Transcriptional landscape of CD4 and CD8 T cells in psoriatic arthritis
a UMAP of integrated PsA blood, synovial fluid and synovial tissue memory CD4 and CD8 T cells (paired blood and synovial fluid from three patients; synovial tissue from two other patients). Clusters coloured red comprise CD8 cells, clusters coloured blue are CD4 cells. Clusters in grey contain mixed CD4 and CD8 populations. b Heatmap showing memory CD4 and CD8 immune subset signatures. The relative expression of marker genes (columns) across cell clusters (rows) is shown. c–e UMAPs showing the contribution of PBMC, SFMC and synovial fluid-derived T cells to the integrated UMAP from (a). f–h Volcano plots showing differential expression of genes between blood and synovial fluid T cells in HLA-DR-low (f), HLA-DR-high (g) and ZNF683+ (h) clusters (Supplementary Data 3a–c). Statistics calculated using two-sided Wilcoxon Rank Sum test with Bonferroni correction. Genes where adjusted p value < = 1E−04 and average logFC is greater than 0.75 or less than −0.75 are labelled and shown as red circles. Dotted lines indicate significance and average logFC cut-off for displaying labelled genes (paired blood and synovial fluid from three patients). Source data are provided as a Source Data file.
The large-scale single cell data from the joints and blood of psoriatic arthritis patients were then used to investigate how the T cells could transfer from the blood to the joint to cause the damage.
Source – Wellcome Sanger Institute
Penkava F, Velasco-Herrera MDC, Young MD et al. (2020) Single-cell sequencing reveals clonal expansions of pro-inflammatory synovial CD8 T cells expressing tissue-homing receptors in psoriatic arthritis. Nat Commun 11, 4767 . [article]
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A new study has revealed psoriatic arthritis may be activated by the same trigger in different patients. Researchers from the University of Oxford and the Wellcome Sanger Institute identified high levels of a specific receptor in immune cells from psoriatic arthritis patients, giving the strongest evidence yet of a single cause for the disease.
It was already known that the disease had a number of genetic predispositions, one of which controls how immune cells called T cells see antigen molecules from disease-causing microorganisms. However, it is not understood exactly what triggers the onset of psoriatic arthritis in patients.
Using cutting edge single cell technology, the researchers analysed thousands of individual immune cells from fluid drained from the knees of patients with psoriatic arthritis. They could see which genes were switched on in each cell and showed these T cells had an activated inflammatory profile. The researchers also amplified and sequenced the RNA from receptor genes, to identify active T cell receptors in each cell. The study showed that many T cells in the joint fluid shared an identical T cell receptor and were therefore clones of each other. These were very likely to have been triggered to reproduce themselves by a particular antigen.
Using machine learning to compare these receptors from different patients, they discovered that the expanded clones of T cells were potentially recognising something in common. These cells also shared other markers, including a receptor called CXCR3, that directed them to the inflammation site.
Transcriptional landscape of CD4 and CD8 T cells in psoriatic arthritis
a UMAP of integrated PsA blood, synovial fluid and synovial tissue memory CD4 and CD8 T cells (paired blood and synovial fluid from three patients; synovial tissue from two other patients). Clusters coloured red comprise CD8 cells, clusters coloured blue are CD4 cells. Clusters in grey contain mixed CD4 and CD8 populations. b Heatmap showing memory CD4 and CD8 immune subset signatures. The relative expression of marker genes (columns) across cell clusters (rows) is shown. c–e UMAPs showing the contribution of PBMC, SFMC and synovial fluid-derived T cells to the integrated UMAP from (a). f–h Volcano plots showing differential expression of genes between blood and synovial fluid T cells in HLA-DR-low (f), HLA-DR-high (g) and ZNF683+ (h) clusters (Supplementary Data 3a–c). Statistics calculated using two-sided Wilcoxon Rank Sum test with Bonferroni correction. Genes where adjusted p value < = 1E−04 and average logFC is greater than 0.75 or less than −0.75 are labelled and shown as red circles. Dotted lines indicate significance and average logFC cut-off for displaying labelled genes (paired blood and synovial fluid from three patients). Source data are provided as a Source Data file.
The large-scale single cell data from the joints and blood of psoriatic arthritis patients were then used to investigate how the T cells could transfer from the blood to the joint to cause the damage.
Source – Wellcome Sanger Institute
Penkava F, Velasco-Herrera MDC, Young MD et al. (2020) Single-cell sequencing reveals clonal expansions of pro-inflammatory synovial CD8 T cells expressing tissue-homing receptors in psoriatic arthritis. Nat Commun 11, 4767 . [article]
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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
ARCADIA combines RNA sequencing and spatial proteomics to reveal how tissue location shapes cell behavior
An end-to-end computational framework for “Record-seq” transcriptional recording data
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
ExoShorkie – predicting RNA-seq coverage of exogenous genomes in yeast by transfer learning
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Bonsai reconstructs tree representations for distortion-free visualization and exploration of high-dimensional data
MiRQuery – a user-friendly web app for the interactive analysis and visualization of microRNA sequencing data
RNA sequencing resolves cryptic pathogenic variants in mitochondrial disease
Unlocking the past – new method helps gain insights into old tissue
New RNA sequencing model improves sequencing depth planning for UMI transcriptomics
Combining RNA sequencing and pathology images identifies glioblastoma subgroups linked to survival
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