van Baarsen, L. G. M. | Search bioRxiv

bioRxiv2023

Identification and mapping of human lymph node stromal cell subsets by combining single-cell RNA sequencing with spatial transcriptomics.

Lymph node stromal cells (LNSCs) have a crucial immunomodulatory function, but their heterogeneity in human is incompletely understood. Here, we report the single cell RNA sequencing (scRNA-seq) of 12000 LNSCs isolated from a human lymph node (LN). This study comprehensively defines the gene signatures of 10 fibroblast subtypes: CCL21+SC, CCL19+SC, CD34+CXCL14+SC, pericytes, DES+SC, LAMP5+SC, NR4A1+BCAM+ SC, HLA-DR+SC, SEPT4+SC and GLDN+SC. To explore the heterogeneous stromal compartment within the complex LN tissue architecture, we integrated the scRNA-seq profiles of the identified LNSC subsets with a publicly available human spatial transcriptomic LN dataset and predicted their location within the complex LN tissue architecture. Each LNSC subtype was spatially restricted to specific LN regions, indicating different LNSC-lymphocyte interactions which was further investigated using NicheNet. The positioning of distinct LNSC subtypes in different LN regions sets the stage for future research on the relationship between LNSC-specific niches and immunomodulatory function during health and disease.

cell biology↗

bioRxiv2021

Synovial Gene Signatures Associated with the Development of Rheumatoid Arthritis in At Risk Individuals: a Prospective Study

BackgroundPrevious work has shown subtle infiltration of synovial T cells in the absence of overt synovial inflammation in individuals at risk of developing rheumatoid arthritis (RA). ObjectiveTo study the molecular changes in synovium preceding arthritis development in at risk individuals. Materials and methodsWe included sixty-seven individuals with arthralgia who were IgM rheumatoid factor (RF) and/or anti-citrullinated protein antibody (ACPA) positive and without any evidence of arthritis. All individuals underwent mini-arthroscopic synovial tissue sampling of a knee joint at baseline and were followed prospectively. An explorative genome-wide transcriptional profiling study was performed on synovial tissue using Agilent arrays (discovery cohort). Survival analysis was used to identify transcripts associated with arthritis after follow up. Expression levels of differentially expressed genes were validated using quantitative real-time PCR (qPCR). Immunohistochemistry was used to study gene candidates at the protein level in situ. ResultsIn the discovery cohort, 6 of the 13 at risk individuals developed RA after a median follow-up time of 20 months (IQR 2 - 44; pre-RA). The 7 individuals who did not develop RA had a median follow-up time of 85 months (IQR 69 - 86). Using a False Discovery Rate of <5% we found increased expression of 3,151 transcripts correlating with a higher risk of arthritis development, whereas increased expression of 2,437 transcripts correlated with a lower risk. Gene set enrichment analysis revealed that synovial biopsies of pre-RA individuals display higher expression of genes involved in several immune response-related pathways compared with biopsies of individuals who did not develop RA. In contrast, lower expression was observed for genes involved in extracellular matrix receptor interaction, Wnt-mediated signal transduction and lipid metabolism. Two-way hierarchical cluster analysis of 27 genes measured by qPCR classified the synovial biopsies of 61 individuals into two groups, where pre-RA individuals (n=16) showed a preference to cluster together. Synovial tissue from pre-RA individuals were more likely to show podoplanin positive cells and lower lipid staining compared with synovial tissue from individuals who did not develop RA. ConclusionMolecular changes can be detected in synovial tissues before clinical onset of arthritis. Alterations in the immune response genes and lipid metabolism are associated with development of arthritis.

immunology↗