Biology subjects

Lederer, J. A.

Publications and source records attributed to Lederer, J. A..

11 recordsLinked to original sources

bioRxiv2025

Sub-phenotypes of pneumonia defined by pulmonary histopathological features

Establishing sub-phenotypes of pneumonia based on distinct host processes will be a step towards using host-directed therapies (to complement microbe-directed therapies) more rationally and precisely. Although pneumonia is a pulmonary pathophysiology, histological changes within the lungs have not been leveraged for sub-phenotyping. We addressed this by scoring 18 histopathology features (e.g., type 2 cell hyperplasia or necrosis) across rapid autopsy lung samples from 276 elderly subjects with pneumonia. Machine learning algorithms segregated subjects into seven different sub-phenotypes of pneumonia with distinct histopathology signatures. Quantitative immunofluorescence demonstrated associations of macrophages, neutrophils, T cells, and B cells with select histology features and pulmonary pathology sub-phenotypes. Mouse models revealed corollary sub-phenotypes, although some histology features observed in human lungs were never observed in mice. By illuminating this spectrum of histopathologies and discriminating discrete sub-phenotypes of pneumonia, a foundational framework emerges for developing and using host-directed therapies for subsets of pneumonia patients.

immunology↗

bioRxiv2023

Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease with currently no universally highly effective prevention strategies. Identifying pathogenic immune phenotypes in At-Risk populations prior to clinical disease onset is crucial to establishing effective prevention strategies. Here, we applied mass cytometry to deeply characterize the immunophenotypes in blood from At-Risk individuals identified through the presence of serum antibodies to citrullinated protein antigens (ACPA) and/or first-degree relative (FDR) status (n=52), as compared to established RA (n=67), and healthy controls (n=48). We identified significant cell expansions in At-Risk individuals compared with controls, including CCR2+CD4+ T cells, T peripheral helper (Tph) cells, type 1 T helper cells, and CXCR5+CD8+ T cells. We also found that CD15+ classical monocytes were specifically expanded in ACPA-negative FDRs, and an activated PAX5low naive B cell population was expanded in ACPA-positive FDRs. Further, we developed an "RA immunophenotype score" classification method based on the degree of enrichment of cell states relevant to established RA patients. This score significantly distinguished At-Risk individuals from controls. In all, we systematically identified activated lymphocyte phenotypes in At-Risk individuals, along with immunophenotypic differences among both ACPA+ and ACPA-FDR At-Risk subpopulations. Our classification model provides a promising approach for understanding RA pathogenesis with the goal to further improve prevention strategies and identify novel therapeutic targets.

genomics↗

bioRxiv2021

Aging and interferon gamma response drive the phenotype of neutrophils in the inflamed joint

ObjectivesNeutrophils are typically the most abundant leukocyte in arthritic synovial fluid. We sought to understand changes that occur in neutrophils as they migrate from blood to joint. MethodsWe performed RNA sequencing of neutrophils from healthy human blood, arthritic blood, and arthritic synovial fluid, comparing transcriptional signatures with those from murine K/BxN serum transfer arthritis. We employed mass cytometry to quantify protein expression and sought to reproduce the synovial fluid phenotype ex vivo in cultured healthy blood neutrophils. ResultsBlood neutrophils from healthy donors and patients with active arthritis exhibited largely similar transcriptional signatures. By contrast, synovial fluid neutrophils exhibited more than 1,600 differentially expressed genes. Gene signatures identified a prominent response to interferon gamma (IFN{gamma}), as well as to tumor necrosis factor, interleukin 6, and hypoxia, in both humans and mice. Mass cytometry also found healthy and arthritic donor blood neutrophils largely indistinguishable but revealed a range of neutrophil phenotypes in synovial fluid defined by downregulation of CXCR1 and upregulation of Fc{gamma}RI, HLA-DR, PD-L1, ICAM-1 and CXCR4. Reproduction of key elements of this signature in cultured blood neutrophils required both IFN{gamma} and prolonged culture. ConclusionsCirculating neutrophils from arthritis patients resemble those from healthy controls, but joint fluid cells exhibit a network of changes, conserved across species, that implicate IFN{gamma} response and aging as complementary drivers of the synovial neutrophil phenotype. KEY MESSAGESO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LINeutrophils are central in the effector phase of inflammatory arthritis but their phenotypic heterogeneity in inflamed synovial fluid is poorly understood. C_LI What does this study add?O_LIRNA-seq and mass cytometry identify a hallmark phenotype of neutrophils in synovial fluid consisting of upregulated ICAM-1, HLA-DR, PD-L1, Fc receptors and CXCR4. C_LIO_LITranscriptomics highlight an IFN{gamma} response signature conserved across humans and mice. C_LIO_LIIn vitro experiments implicate aging and IFN{gamma} as complementary factors orchestrating the synovial fluid neutrophil phenotype. C_LI How might this impact on clinical practice or future developments?O_LIUnderstanding the specific features of neutrophils in the arthritic joint may disclose opportunities for safe therapeutic targeting of this lineage. C_LI

immunology↗

bioRxiv2021

Longitudinal immune cell profiling in early systemic lupus erythematosus

ObjectiveTo investigate the immune cell profiling and their longitudinal changes in systemic lupus erythematosus (SLE). MethodsWe employed mass cytometry with three different 38-39 marker panels (Immunophenotyping, T cell/monocyte, and B cell) in cryopreserved peripheral blood mononuclear cells (PBMCs) from nine patients with early SLE, 15 patients with established SLE, and 14 non-inflammatory controls. We used machine learning-driven clustering, FlowSOM (Flow Self-Organizing Maps) and dimensional reduction with tSNE (t-distributed Stochastic Neighbor Embedding) to identify unique cell populations in early and established SLE. For the nine early SLE patients, longitudinal mass cytometry analysis was applied to PBMCs at three time points (at enrollment, six months post-enrollment, and one year post-enrollment). Serum samples were also assayed for 65 cytokines by Luminex multiplex assay, and associations between cell types and cytokines/chemokines assessed. ResultsT peripheral helper cells (Tph cells), T follicular helper cells (Tfh cells) and several Ki67+ proliferating subsets (ICOS+ Ki67+ CD8 T cells, Ki67+ regulatory T cells, CD19int Ki67hi plasmablasts, and Ki67hi PU.1hi monocytes) were increased in early SLE. Longitudinal mass cytometry and multiplex serum cytokine assays of samples from early SLE patients revealed that Tfh cells and CXCL10 decreased at one year post-enrollment. CXCL13 correlated positively with several of the expanded cell populations in early SLE. ConclusionsTwo major helper T cell subsets and unique Ki67+ proliferating immune cell subsets were expanded in the early phase of SLE, and the immunologic features characteristic of early SLE evolved over time.

immunology↗

bioRxiv2021

Robust integration of single-cell cytometry datasets

Combining single-cell cytometry datasets increases the analytical flexibility and the statistical power of data analyses. However, in many cases the full potential of co-analyses is not reached due to technical variance between data from different experimental batches. Here, we present cyCombine, a method to robustly integrate cytometry data from different batches, experiments, or even different experimental techniques, such as CITE-seq, flow cytometry, and mass cytometry. We demonstrate that cyCombine maintains the biological variance and the structure of the data, while minimizing the technical variance between datasets. cyCombine does not require technical replicates across datasets, and computation time scales linearly with the number of cells, allowing for integration of massive datasets. Robust, accurate, and scalable integration of cytometry data enables integration of multiple datasets for primary data analyses and the validation of results using public datasets.

bioinformatics↗

bioRxiv2021

Single Cell RNA-seq and Mass Cytometry Reveals a Novel and a Targetable Population of Macrophages in Idiopathic Pulmonary Fibrosis

In this study, we leveraged a combination of single cell RNAseq, cytometry by time of flight (CyTOF), and flow cytometry to study the biology of a unique macrophage population in pulmonary fibrosis. Using the profiling data from 312,928 cells derived from 32 idiopathic pulmonary fibrosis (IPF), 29 healthy control and 18 chronic obstructive pulmonary disease (COPD) lungs, we identified an expanded population of macrophages in IPF that have a unique transcriptional profile associated with pro-fibrotic signature. These macrophages attain a hybrid transitional state between alveolar and interstitial macrophages, are enriched with biological processes of pro-fibrotic immune cells, and express novel surface markers and genes that have not been previously reported. We then applied single cell CyTOF to simultaneously measure 37 markers to precisely phenotype the uniquely expanded macrophage subset in IPF lungs. The SPADE algorithm independently identified an expanded macrophage cluster, and validated CD84 and CD36 as novel surface markers that highly label this cluster. Using a separate validation cohort, we confirmed an increase in CD84++CD36++ macrophage population in IPF compared to control and COPD lungs by flow cytometry. Further, using the signature from the IPF-specific macrophages and the LINCS drug database, we predicted small molecules that could reverse the signature of IPF-specific macrophages, and validated two molecules, CRT and Cucur, using THP-1 derived human macrophages and precision-cut lung slices (PCLS) from IPF patients. Utilizing a multi-dimensional translational approach, our work identified a novel and targetable population of macrophages found in end-stage pulmonary fibrosis. One Sentence SummarySingle cell RNAseq, CyTOF, and flow cytometry reveal the presence of an aberrant macrophage population in pulmonary fibrosis

cell biology↗

bioRxiv2018

The immune cell landscape in kidneys of lupus nephritis patients

Lupus nephritis is a potentially fatal autoimmune disease, whose current treatment is ineffective and often toxic. To gain insights into disease mechanisms, we analyzed kidney samples from lupus nephritis patients and healthy controls using single-cell RNA-seq. Our analysis revealed 21 subsets of leukocytes active in disease, including multiple populations of myeloid, T, NK and B cells, demonstrating both pro-inflammatory and resolving responses. We found evidence of local activation of B cells correlated with an age-associated B cell signature, and of progressive stages of monocyte differentiation within the kidney. A clear interferon response was observed in most cells. Two chemokine receptors, CXCR4 and CX3CR1, were broadly expressed, pointing to potential therapeutic targets. Gene expression of immune cells in urine and kidney was highly correlated, suggesting urine may be a surrogate for kidney biopsies. Our results provide a first comprehensive view of the complex network of leukocytes active in lupus nephritis kidneys.

immunology↗

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↗

bioRxiv2018

High dimensional analyses of cells dissociated from cryopreserved synovial tissue

BackgroundDetailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership (AMP) RA/SLE network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples.\n\nMethodsMultiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10%-DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T cell, B cell, and macrophage suspensions for bulk population RNA-seq and plate-based single cell CEL-Seq2 RNA-seq.\n\nResultsUpon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with [~]30 arthroplasty and [~]20 biopsy samples yielded a consensus digestion protocol using 100{micro}g/mL of Liberase TL enzyme. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished: 1) diverse fibroblast phenotypes, 2) distinct populations of memory B cells and antibody-secreting cells, and 3) multiple CD4+ and CD8+ T cell activation states. Bulk RNA sequencing of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified.\n\nConclusionWe have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

immunology↗

bioRxiv2018

A protocol for single-cell transcriptomics from cryopreserved renal tissue and urine for the Accelerating Medicine Partnership (AMP) RA/SLE network

OBJECTIVEThere is a critical need to define the cells that mediate tissue damage in lupus nephritis. Here we aimed to establish a protocol to preserve lupus nephritis kidney biopsies and urine cell samples obtained at multiple clinical sites for subsequent isolation and transcriptomic analysis of single cells.\n\nMETHODSFresh and cryopreserved kidney tissue from tumor nephrectomies and lupus nephritis kidney biopsies were disaggregated by enzymatic digestion. Cell yields and cell composition were assessed by flow cytometry. Transcriptomes of leukocytes and epithelial cells were evaluated by low-input and single cell RNA-seq.\n\nRESULTSCryopreserved kidney tissue from tumor nephrectomies and lupus nephritis biopsies can be thawed and dissociated to yield intact, viable leukocytes and epithelial cells. Cryopreservation of intact kidney tissue provides higher epithelial cell yields compared to cryopreservation of single cell suspensions from dissociated kidneys. Cell yields and flow cytometric cell phenotypes are comparable between cryopreserved kidney samples and paired kidney samples shipped overnight on wet ice. High-quality single cell and low-input transcriptomic data were generated from leukocytes from both cryopreserved lupus nephritis kidney biopsies and urine, as well as from a subset of kidney epithelial cells.\n\nCONCLUSIONThe AMP RA/SLE cryopreserved tissue analysis pipeline provides a method for centralized processing of lupus nephritis kidney biopsies and urine samples to generate robust transcriptomic analyses in multi-center studies.

immunology↗

bioRxiv2017

Single Cell Transcriptomics And Flow Cytometry Reveal Disease-Associated Fibroblast Subsets In Rheumatoid Arthritis

Fibroblasts mediate normal tissue matrix remodeling, but they can cause fibrosis or tissue destruction following chronic inflammation. In rheumatoid arthritis (RA), synovial fibroblasts expand, degrade cartilage, and drive joint inflammation. Little is known about fibroblast heterogeneity or if aberrations in fibroblast subsets relate to disease pathology. Here, we used an integrative strategy, including bulk transcriptomics on targeted subpopulations and unbiased single-cell transcriptomics, to analyze fibroblasts from synovial tissues. We identify 7 phenotypic fibroblast subsets with distinct surface protein phenotypes, and these collapsed into 3 subsets based on transcriptomics data. One subset expressing PDPN, THY1, but lacking CD34 was 3-fold expanded in RA relative to osteoarthritis (P=0.007); most of these cells expressed CDH11. The subsets were found to differ in expression of cytokines and matrix metalloproteinases, localization in synovial microanatomy, and in response to TNF. Our approach provides a template to identify pathogenic stromal cellular subsets in complex diseases.

immunology↗