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Dendrou, C.

Publications and source records attributed to Dendrou, C..

8 recordsLinked to original sources
bioRxiv2025

Single-cell and spatial transcriptomic analyses of gene therapy-associatedretinal inflammation in non-human primates

Adeno-associated viral (AAV) vectors are rapidly advancing as gene therapies for inherited and common retinal disorders, but gene therapy-associated uveitis (GTAU) limits their broader application. To investigate the primate ocular immune response, we administered subretinal AAV gene therapy to two non-human primates (NHPs): NHP1 received AAV2-CAG-hRPE65 (voretigene neparvovec) bilaterally at clinical dose; NHP2 received AAV8-GRK1-hRPGRco alongside an analogous mScarlet reporter vector in separate blebs. Longitudinal assessments over three months included multimodal imaging, electroretinography and cytokine profiling, followed by immunohistological, single-cell and spatial transcriptomic analyses of retinal punches. Both therapies were well-tolerated, with preserved retinal structure and function. Single-cell RNA-sequencing revealed that the AAV8 vector transduced 80% of cones/rods in treated areas, while AAV2 targeted 30% of retinal pigment epithelium (RPE)/rods. Transgene expression did not correlate with apoptotic markers. Persistent immune infiltration (dominated by myeloid and T cells) suggested a type 1 cell-mediated response. Adjunctive intravitreal anti-TNF (adalimumab) did not appear to mitigate this anti-viral response. Spatial analysis highlighted microglia migration to the subretinal space, consistent with upregulated cytokines (MCP-1/CCL2, IP-10/CXCL10, IL-8/CXCL8, IL-6), which implicate monocytic phagocytes in driving local inflammation. These findings elucidate the mechanism of GTAU and identify potential therapeutic targets to prevent immune-mediated complications in retinal gene therapy.

immunology↗
bioRxiv2024

CD4+ tissue resident memory Th17 cells drive IL-17A-mediated joint pathology in Spondyloarthritis

ObjectivesInterleukin (IL)-17A is a key driver of Spondyloarthritis (SpA) joint pathology. We aimed to identify its cellular source in synovial tissue from patients with two forms of SpA namely Axial SpA (AxSpA) and Psoriatic arthritis (PsA). MethodsSynovial tissue from patients with SpA was profiled using single-cell RNA sequencing (scRNA-seq: AxSpA, n=5 and PsA, n=6) or spatial RNA profiling (PsA, n=4). CellPhoneDB was used to infer cell-cell communication. Tissue resident memory Th17 (TRM17)-like cells were generated in vitro using blood memory CD4+ T cells from SpA patients. An epigenetic inhibitor library, siRNA and clustered regularly interspaced short palindromic repeats (CRISPR) were used to identify epigenetic regulator(s) for TRM17. ResultsscRNA-seq showed that CD4+CXCR6+ TRM17 cells are the predominant spontaneous IL17A producers in SpA synovium. Cell-cell communication and single-cell spatial analysis support the interaction between TRM17 and CLEC10A+ dendritic cells, which were activated in SpA. Both sublining and lining fibroblasts in SpA synovium showed evidence of IL-17A activation. In vitro-generated CD4+ TRM17-like cells phenocopied joint tissue TRM17, producing IL-17A/F upon T cell receptor (TCR) stimulation, which was further enhanced by cytokines. Perturbation of BRD1 inhibited the generation of TRM17-like cells. ConclusionsCD4+ TRM17 cells are the predominant source of IL-17A in SpA synovial tissue. TCR stimulation is essential for the secretion of IL-17A by CD4+TRM17-like cells. The epigenetic regulator BRD1 contributes to the generation of CD4+TRM17. Depleting CD4+TRM17 cells in SpA is thus a therapeutic strategy with potential to induce long-term remission. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSInterleukin (IL)-17A plays a key role in the immunopathogenesis of Spondyloarthritis (SpA), but its cellular source in joint tissue has not been determined previously. The induction and accumulation of CD4+ tissue resident memory Th17 (TRM17) cells following the clearance of pathogens has been described in skin, lung and kidney. Whether CD4+ TRM17 cells also accumulate in the joint and contribute to the pathology of SpA is not clear. What this study addsO_LICD4+ TRM17 cells are present in SpA synovial tissue and are the predominant source of IL17A C_LIO_LICD4+ TRM17 cells in SpA joints express IL17A without any in vitro exogenous stimulation C_LIO_LIT cell receptor (TCR) rather than cytokine stimulation is essential for IL-17A production by CD4+ TRM17-like cells C_LIO_LIThe epigenetic regulator BRD1 contributes to the generation of CD4+ TRM17-like cells. C_LI How this study might affect research, practice or policyOur findings identify CD4+ TRM17 cells as the primary source of IL-17A in SpA synovium, a previously unrecognized role for these cells. Key questions remain: How do CD4+ TRM17 cells relate to IL-17A producers in synovial fluid? What mechanisms induce and maintain them in the joint? How do they interact with other cells to promote arthritis? These questions warrant further investigation. In addition, our data suggest that targeting CD4+ TRM17 cells, the "factory" of IL-17A in SpA synovial tissue, has the potential to induce long-term remission, encouraging future efforts to develop new therapies to deplete CD4+ TRM17 cells in SpA.

immunology↗
bioRxiv2024

Ex vivo Model of Functioning Human Lymph Node Reveals Pivotal Role for Innate Lymphoid Cells and Stromal Populations in Response to Vaccine Adjuvant

Immunological processes that underpin the administration of therapeutics and vaccines are poorly defined due to a lack of models which faithfully recapitulate human immune responses. Inbred mice lack the diversity inherent to people, while the microanatomical organisation of human tissue is lost in isolated cell suspensions. We describe precision-cut human lymph node (LN) slices as architecturally-preserved, functioning lymphoid tissue model system, and explore early inflammatory responses to a potent vaccine liposomal adjuvant containing a TLR4-agonist and QS21 saponin. Combining scRNA-seq, multiplexed immunofluorescence and secretome analysis, we dissect direct and indirect signalling pathways in both leukocytes and stromal cells to reveal communication networks linking innate and adaptive immunity. Application of molecular inhibitors reveals that secretion of IL-1{beta}, but not IL-18, is TLR4-dependent in human LN. Retaining donor-to-donor immune variation, this ex vivo LN model system enables the study of pathways previously difficult to observe in humans, paving the way towards precision medicine.

immunology↗
bioRxiv2023

A longitudinal single-cell therapeutic atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease

Precision medicine in immune-mediated inflammatory diseases (IMIDs) requires an understanding of how cellular networks change following therapy. We describe a therapeutic atlas for Crohns disease (CD) and ulcerative colitis (UC) following anti-tumour necrosis factor (TNF) therapy. We generated ~1 million single-cell transcriptomes, organised into 109 cell states, from 216 gut biopsies from 38 patients and three controls, revealing disease- and therapy-specific differences. A systems-biology analysis identified distinct spatially-resolved cellular microenvironments: granuloma signatures in CD and interferon (IFN)-response signatures localising to T-cell aggregates and epithelial damage in CD and UC. Longitudinal comparisons demonstrated that disease progression in non-responders associated with myeloid and stromal cell perturbations in CD and increased multi-cellular IFN signalling in UC. IFN signalling was also observed in rheumatoid arthritis (RA) synovium with a lymphoid pathotype. Our therapeutic atlas informs drug positioning across IMIDs, and suggests a rationale for the use of janus kinase (JAK) inhibition following anti-TNF resistance.

immunology↗
bioRxiv2023

Panpipes: a pipeline for multiomic single-cell data analysis.

Single-cell multiomic analysis of the epigenome, transcriptome and proteome allows for comprehensive characterisation of the molecular circuitry that underpins cell identity and state. However, the holistic interpretation of such datasets presents a challenge given a paucity of approaches for systematic, joint evaluation of different modalities. Here, we present Panpipes, a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customisable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.

bioinformatics↗
bioRxiv2018

Systematic classification of shared components of genetic risk for common human diseases

Disease classification is fundamental to clinical practice, but current taxonomies do not necessarily reflect the pathophysiological processes that are common or unique to different disorders, such as those determined by genetic risk factors. Here, we use routine healthcare data from the 500,000 participants in the UK Biobank to map genome-wide associations across 19,628 diagnostic terms. We find that 3,510 independent genetic risk loci affect multiple clinical phenotypes, which we cluster into 629 distinct disease association profiles. We use multiple approaches to link clusters to different underlying biological pathways and show how these clusters define the genetic architecture of common medical conditions, including hypertension and immune-mediated diseases. Finally, we demonstrate how clusters can be utilised to re-define disease relationships and to inform therapeutic strategies.\n\nOne sentence summarySystematic classification of genetic risk factors reveals molecular connectivity of human diseases with clinical implications

genetics↗
bioRxiv2017

Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank

Genetic discovery from the multitude of phenotypes extractable from routine healthcare data has the ability to radically transform our understanding of the human phenome, thereby accelerating progress towards precision medicine. However, a critical question when analysing high-dimensional and heterogeneous data is how to interrogate increasingly specific subphenotypes whilst retaining statistical power to detect genetic associations. Here we develop and employ a novel Bayesian analysis framework that exploits the hierarchical structure of diagnosis classifications to jointly analyse genetic variants against UK Biobank healthcare phenotypes. Our method displays a more than 20% increase in power to detect genetic effects over other approaches, such that we uncover the broader burden of genetic variation: we identify associations with over 2,000 diagnostic terms. We find novel associations with common immune-mediated diseases (IMD), we reveal the extent of genetic sharing between specific IMDs, and we expose differences in disease perception or diagnosis with potential clinical implications.

genetics↗