Biology subjects

DiCarlo, E.

Publications and source records attributed to DiCarlo, E..

5 recordsLinked to original sources

bioRxiv2026

Conserved Fibroblast Subsets Drive Shared Fibrotic Mechanisms in Osteoarthritis Synovium and Systemic Sclerosis Skin

Osteoarthritis (OA) and systemic sclerosis (SSc) are diseases with distinct etiologies but similar disease phenotypes, most prominently fibrosis, a process governed by the pathological activation of fibroblasts. Mechanisms underpinning fibrosis in these diseases are widely studied, though have yet to be directly compared. We employed single-cell RNA-seq and high-resolution spatial transcriptomics to describe the functional plasticity and the range of fibroblast activation states in both diseases. We identified disease-enriched fibroblast subsets conserved in both diseases, including fibrogenic myofibroblast-like cells, chemokine- and cytokine-expressing inflammatory fibroblasts, and lining-like fibroblasts. These subsets exhibited convergent fibrotic programs also observed in idiopathic pulmonary fibrosis, as well as overlapping osteochondral transcriptional programs. Xenium 5K spatial transcriptomics revealed that conserved, disease-associated fibroblasts reside in highly similar anatomic niches in OA synovium and SSc skin. These consisted of a fibrotic ECM-rich niche harboring myofibroblast-like cells and an inflammatory niche containing inflammatory fibroblasts adjacent to infiltrating immune cells. Disease-associated transcriptional remodeling converged on shared functional pathways and common putative upstream molecular regulators. These findings identify conserved cellular states, spatial niches, and regulatory programs across OA and SSc, suggesting that fibrotic disease is underpinned by shared pathogenic stromal states and candidate targets for therapeutic strategies are applicable across both diseases.

cell biology↗

bioRxiv2026

Synovial transcriptional clusters link cartilage degeneration to cell-type-specific gene expression in knee osteoarthritis

ObjectivesTo identify synovial transcriptional clusters in human knee osteoarthritis (OA) and determine how these relate to synovial histologic features, cell-type-associated gene expression, and cartilage degeneration severity. MethodsBulk RNA sequencing (RNA-seq) of synovial tissue from n = 135 patients with knee OA was analyzed using consensus clustering. Clusters were compared by clinical and histologic features, including cartilage degeneration severity (OARSI score). Single-cell RNA-seq (n = 18) and spatial transcriptomics were used to relate cartilage degeneration-associated gene expression patterns to synovial cell populations. ResultsFour synovial transcriptional clusters that differed in synovial histologic features and cartilage degeneration severity were identified. Greater cartilage degeneration was associated with enrichment of lining fibroblast- and inflammatory myeloid-associated gene expression, whereas lesser cartilage degeneration was associated with enrichment of sublining fibroblast, endothelial, mural cell, and adipocyte-associated gene expression. ConclusionsHuman knee OA synovium segregates into transcriptional clusters associated with cartilage degeneration severity. Synovial transcriptional heterogeneity corresponds to cell-type-associated gene expression. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIOsteoarthritis synovium exhibits marked histologic and molecular heterogeneity. C_LIO_LISynovial inflammation detected by MRI correlates with cartilage degeneration and predicts progressive cartilage loss in knee OA. C_LIO_LIPrior transcriptomic studies have identified molecular subsets of OA synovium, but their relationship to cartilage degeneration severity remains unclear. C_LI What this study addsO_LIOA synovium segregates into four transcriptional clusters: Sublining (C1), Lymphomyeloid (C2), Myeloid (C3), and Major trauma (C4). C_LIO_LIGreater cartilage degeneration is associated with enrichment of inflammatory myeloid and lining fibroblast gene expression, whereas lesser degeneration is associated with enrichment of adipocyte, sublining fibroblast, endothelial, and mural cell-associated gene expression. C_LI How this study might affect research, practice or policyO_LIProvides a framework for a clinically relevant biological stratification of OA patients based on synovial molecular features. C_LIO_LIInforms future efforts to link synovial biology with OA prognosis, cartilage degeneration, treatment allocation, and development of targeted therapeutic strategies. C_LI

genomics↗

bioRxiv2022

Heterogeneity of Inflammation-associated Synovial Fibroblasts in Rheumatoid Arthritis and Its Drivers

Inflammation of non-barrier immunologically quiescent tissues is associated with a massive influx of blood-borne innate and adaptive immune cells. Cues from the latter are likely to alter and expand the spectrum of states observed in cells that are constitutively resident. However, local communications between immigrant and resident cell types in human inflammatory disease remain poorly understood. Here, we explored heterogeneity of synovial fibroblasts (FLS) in inflamed joints of rheumatoid arthritis (RA) patients using paired single cell RNA and ATAC sequencing (scRNA/ATAC-seq), multiplexed imaging, and spatial transcriptomics along with in vitro modeling of cell extrinsic factor signaling. These analyses suggest that local exposures to myeloid and T cell derived cytokines, TNF, IFN{gamma}, IL-1{beta}, or lack thereof, drive six distinct FLS states some of which closely resemble fibroblast states in other disease-affected tissues including skin and colon. Our results highlight a role for concurrent, spatially distributed cytokine signaling within the inflamed synovium.

immunology↗

bioRxiv2022

Cellular deconstruction of inflamed synovium defines diverse inflammatory phenotypes in rheumatoid arthritis

Rheumatoid arthritis (RA) is a prototypical autoimmune disease that causes destructive tissue inflammation in joints and elsewhere. Clinical challenges in RA include the empirical selection of drugs to treat patients, inadequate responders with incomplete disease remission, and lack of a cure. We profiled the full spectrum of cells in inflamed synovium from patients with RA with the goal of deconstructing the cell states and pathways characterizing pathogenic heterogeneity in RA. Our multicenter consortium effort used multi-modal CITE-seq, RNA-seq, and histology of synovial tissue from 79 donors to build a >314,000 single-cell RA synovial cell atlas with 77 cell states from T, B/plasma, natural killer, myeloid, stromal, and endothelial cells. We stratified tissue samples into six distinct cell type abundance phenotypes (CTAPs) individually enriched for specific cell states. These CTAPs demonstrate the striking diversity of RA synovial inflammation, ranging from marked enrichment of T and B cells (CTAP-TB) to a congregation of specific myeloid, fibroblast, and endothelial cells largely lacking lymphocytes (CTAP-EFM). Disease-relevant cytokines, histology, and serology metrics are associated with certain CTAPs. This comprehensive RA synovial atlas and molecular, tissue-based CTAP stratification reveal new insights into RA pathology and heterogeneity, which could lead to novel targeted-treatment approaches in RA.

genomics↗

bioRxiv2018

Defining Inflammatory Cell States in Rheumatoid Arthritis Joint Synovial Tissues by Integrating Single-cell Transcriptomics and Mass Cytometry

To define the cell populations in rheumatoid arthritis (RA) driving joint inflammation, we applied single-cell RNA-seq (scRNA-seq), mass cytometry, bulk RNA-seq, and flow cytometry to sorted T cells, B cells, monocytes, and fibroblasts from 51 synovial tissue RA and osteoarthritis (OA) patient samples. Utilizing an integrated computational strategy based on canonical correlation analysis to 5,452 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics together revealed cell states expanded in RA synovia: THY1+HLAhigh sublining fibroblasts (OR=33.8), IL1B+ pro-inflammatory monocytes (OR=7.8), CD11c+T-bet+ autoimmune-associated B cells (OR=5.7), and PD-1+Tph/Tfh (OR=3.0). We also defined CD8+ T cell subsets characterized by GZMK+, GZMB+, and GNLY+ expression. Using bulk and single-cell data, we mapped inflammatory mediators to source cell populations, for example attributing IL6 production to THY1+HLAhigh fibroblasts and naive B cells, and IL1B to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis.

immunology↗