Antigen-specific nanomedicines for the treatment of autoimmune disease: target cell types, mechanisms and outcomes

2022 ◽  
Vol 74 ◽  
pp. 285-292
Author(s):  
Yang Yang ◽  
Pere Santamaria
Keyword(s):  
Autoimmune Disease ◽  
Target Cell ◽  
Cell Types

scholarly journals Three distinct tolerogenic CD14+ myeloid cell types to actively manage autoimmune disease: Opportunities and challenges

2021 ◽  
Vol 120 ◽  
pp. 102645
Author(s):  
Glenn F. van Wigcheren ◽  
Daphne Roelofs ◽  
Carl G. Figdor ◽  
Georgina Flórez-Grau
Keyword(s):  
Autoimmune Disease ◽  
Myeloid Cell ◽  
Cell Types

Epigenetics In Autoimmune Disease

2018 ◽  
Author(s):  
Matlock A Jeffries
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Autoimmune Disease ◽  
Noncoding Rna ◽  
Specific Treatment ◽  
Cell Types ◽  
Response To Therapy ◽  
Human Immune System ◽  
Treatment Regimens ◽  
New Research

Autoimmunity refers to a pathologic state of immunologic dysregulation in which the human immune system turns inward, attacking healthy tissues. The key step in this process is a break of self-immune tolerance. Recent studies have implicated dysregulation of gene expression via altered epigenetic control as a key mechanism in the development and promotion of autoimmunity. Epigenetics is defined as heritable changes in gene expression as a result of modification of DNA methylation, histone side chains, and noncoding RNA. Studies examining identical twins discordant for lupus, for example, were among the first to identify alterations in DNA methylation leading to lupus. Histone side-chain changes have been studied extensively in rheumatoid arthritis (RA), and many pathogenic cell types in RA exhibit a hyperacetylation phenotype. Finally, new research in the noncoding RNA field has not only uncovered potentially targetable pathways (e.g., miR-155) but may lead to the development of new diagnostic and prognostic biomarkers, helping physicians better tailor specific treatment regimens to improve response to therapy in autoimmune disease.   This review contains 4 figures, 1 table and 47 references Key Words: autoimmunity, big data, biomarkers, computational biology, DNA methylation, epigenetics, histone acetylation, histone methylation, microRNA, noncoding RNA

scholarly journals Limited statistical evidence for shared genetic effects of eQTLs and autoimmune-disease-associated loci in three major immune-cell types

2017 ◽  
Vol 49 (4) ◽  
pp. 600-605 ◽  
Author(s):  
Sung Chun ◽  
Alexandra Casparino ◽  
Nikolaos A Patsopoulos ◽  
Damien C Croteau-Chonka ◽  
Benjamin A Raby ◽  
...  
Keyword(s):  
Autoimmune Disease ◽  
Immune Cell ◽  
Cell Types ◽  
Genetic Effects ◽  
Statistical Evidence ◽  
Shared Genetic

Gap junction-mediated intercellular communication between DRG neurons and three target cell types

1998 ◽  
Vol 114 ◽  
pp. A1141
Author(s):  
H.S. Ennes ◽  
S.H. Young ◽  
J. Goliger ◽  
J. McRoberts ◽  
E.A. Mayer
Keyword(s):  
Gap Junction ◽  
Target Cell ◽  
Intercellular Communication ◽  
Cell Types ◽  
Drg Neurons

scholarly journals Construction and Molecular Analysis of Gene Transfer Systems Derived from Bovine Immunodeficiency Virus

2001 ◽  
Vol 75 (7) ◽  
pp. 3371-3382 ◽  
Author(s):  
Robert Berkowitz ◽  
Heini Ilves ◽  
Wei Yu Lin ◽  
Karl Eckert ◽  
Andrea Coward ◽  
...  
Keyword(s):  
Gene Transfer ◽  
Target Cell ◽  
Expression System ◽  
Cell Types ◽  
Human Cells ◽  
Bovine Immunodeficiency Virus ◽  
Transduction Efficiency ◽  
Hematopoietic Stem ◽  
Immunodeficiency Virus ◽  
Immortalized Cell

ABSTRACT Because lentiviruses are able to infect nondividing cells, these viruses might be utilized in gene therapy applications where the target cell does not divide. However, it has been suggested that the introduction of primate lentivirus sequences, particularly those of human immunodeficiency virus, into human cells may pose a health risk for the patient. To avoid this concern, we have constructed gene transfer systems based on a nonprimate lentivirus, bovine immunodeficiency virus. A panel of vectors and packaging constructs was generated and analyzed in a transient expression system for virion production and maturation, vector expression and encapsidation, and envelope protein pseudotyping. Virion preparations were also analyzed for transduction efficiency in a panel of human and nonhuman primary cells and immortalized cell lines. The virion preparations transduced most of the target cell types, with efficiencies up to 90% and with titers of unconcentrated virus up to 5 × 105infectious doses/ml. In addition, infection of nondividing human cells, including unstimulated hematopoietic stem cells and irradiated endothelial cells, was observed.

scholarly journals Effects of rottlerin on silica-exacerbated systemic autoimmune disease in New Zealand mixed mice

2005 ◽  
Vol 289 (6) ◽  
pp. L990-L998 ◽  
Author(s):  
Jared M. Brown ◽  
Corbin M. Schwanke ◽  
Mark A. Pershouse ◽  
Jean C. Pfau ◽  
Andrij Holian
Keyword(s):  
New Zealand ◽  
Autoimmune Disease ◽  
Cell Types ◽  
Complement C3 ◽  
Systemic Autoimmune Disease ◽  
Silica Exposure ◽  
Protein Levels ◽  
Systemic Autoimmunity ◽  
Induced Apoptosis

Environmental crystalline silica exposure has been associated with formation of autoantibodies and development of systemic autoimmune disease, but the mechanisms leading to these events are unknown. Silica exposure in autoimmune-prone New Zealand mixed (NZM) mice results in a significant exacerbation of systemic autoimmunity as measured by increases in autoantibodies and glomerulonephritis. Previous studies have suggested that silica-induced apoptosis of alveolar macrophages (AM) contributes to the generation of the autoantibodies and disease. Rottlerin has been reported to inhibit apoptosis in many cell types, possibly through direct or indirect effects on PKCδ. In this study, rottlerin reduced silica-induced apoptosis in bone marrow-derived macrophages as measured by DNA fragmentation. In NZM mice, RNA and protein levels of PKCδ were significantly elevated in AM 14 wk after silica exposure. Therefore, rottlerin was used to reduce apoptosis of AM and evaluate the progress of silica-exacerbated systemic autoimmune disease. Fourteen weeks after silica exposure, NZM mice had increased levels of anti-histone autoantibodies, high proteinuria, and glomerulonephritis. However, silica-instilled mice that also received weekly instillations of rottlerin had significantly lower levels of proteinuria, anti-histone autoantibodies, complement C3, and IgG deposition within the kidney. Weekly instillations of rottlerin in silica-instilled NZM mice also inhibited the upregulation of PKCδ in AM. Together, these data demonstrate that in vivo treatment with rottlerin significantly decreased the exacerbation of autoimmunity by silica exposure.

scholarly journals A novel innate lymphoid cell delineates childhood autoimmune arthritis

2018 ◽  
Author(s):  
Martin Del Castillo Velasco-Herrera ◽  
Matthew D Young ◽  
Felipe A Vieira Braga ◽  
Elizabeth C. Rosser ◽  
Elena Miranda ◽  
...  
Keyword(s):  
Autoimmune Disease ◽  
Synovial Fluid ◽  
Immune Cells ◽  
Messenger Rna ◽  
Cell Types ◽  
Lymphoid Cells ◽  
Autoimmune Arthritis ◽  
Cellular Interactions ◽  
Activated T Cells ◽  
Adaptive Immune Cells

Inflammation in autoimmune disease is mediated by a complex network of interacting cells. Their identity and cross-talk are encoded in messenger RNA (mRNA). Juvenile idiopathic arthritis (JIA), a chronic autoimmune arthritis of childhood, is characterised by synovial inflammation with infiltration of both innate and adaptive immune cells1. Activated T cells play a role in disease2 but the cell types that drive the recruitment and activation of immune cells within the synovium are not known. Here, we utilised droplet-based and full length single cell mRNA sequencing to obtain a quantitative map of the cellular landscape of JIA. We studied 45,715 cells from the synovial fluid of inflamed knee joints and peripheral blood. We identified a population of synovial innate lymphoid cells (ILCs), shared across patients, that exhibited a unique transcriptional profile in comparison to canonical ILC subtypes. Validation at protein-level across a spectrum of autoimmune arthritides revealed that these ILCs are pathologically expanded in a particular type of JIA. Using statistical tools to assess cellular interactions in synovial fluid, ILCs emerged as a central node of communication, expressing the full repertoire of genes required to orchestrate and maintain the inflammatory milieu. Several ILC-mediated signalling pathways may lend themselves as novel therapeutic targets. Together our findings demonstrate a distinct ILC subtype associated with a tissue-specific childhood autoimmune disease.

scholarly journals Evaluating Cell Identity from Transcription Profiles

2018 ◽  
Author(s):  
Nancy Mah ◽  
Katerina Taškova ◽  
Khadija El Amrani ◽  
Krithika Hariharan ◽  
Andreas Kurtz ◽  
...  
Keyword(s):  
Target Cell ◽  
Drug Testing ◽  
Cell Types ◽  
Patient Specific ◽  
List Type ◽  
Cell Type ◽  
Cell Identity ◽  
Transcription Profiles ◽  
Cell Based Therapy ◽  
A Cell

SummaryInduced pluripotent stem cells (iPS) and direct lineage programming offer promising autologous and patient-specific sources of cells for personalized drug-testing and cell-based therapy. Before these engineered cells can be widely used, it is important to evaluate how well the engineered cell types resemble their intended target cell types. We have developed a method to generate CellScore, a cell identity score that can be used to evaluate the success of an engineered cell type in relation to both its initial and desired target cell type, which are used as references. Of 20 cell transitions tested, the most successful transitions were the iPS cells (CellScore > 0.9), while other transitions (e.g. induced hepatocytes or motor neurons) indicated incomplete transitions (CellScore < 0.5). In principle, the method can be applied to any engineered cell undergoing a cell transition, where transcription profiles are available for the reference cell types and the engineered cell type.HighlightsA curated standard dataset of transcription profiles from normal cell types was created.CellScore evaluates the cell identity of engineered cell types, using the curated dataset.CellScore considers the initial and desired target cell type.CellScore identifies the most successfully engineered clones for further functional testing.

scholarly journals Estimating and Correcting for Off-Target Cellular Contamination in Brain Cell Type Specific RNA-Seq Data

2021 ◽  
Vol 14 ◽  
Author(s):  
Jordan Sicherman ◽  
Dwight F. Newton ◽  
Paul Pavlidis ◽  
Etienne Sibille ◽  
Shreejoy J. Tripathy
Keyword(s):  
Single Cell ◽  
Differential Expression ◽  
Rna Sequencing ◽  
Target Cell ◽  
Differential Expression Analysis ◽  
Cell Types ◽  
Brain Cell ◽  
Cell Type ◽  
Cell Purification ◽  
Single Cell Type

Transcriptionally profiling minor cellular populations remains an ongoing challenge in molecular genomics. Single-cell RNA sequencing has provided valuable insights into a number of hypotheses, but practical and analytical challenges have limited its widespread adoption. A similar approach, which we term single-cell type RNA sequencing (sctRNA-seq), involves the enrichment and sequencing of a pool of cells, yielding cell type-level resolution transcriptomes. While this approach offers benefits in terms of mRNA sampling from targeted cell types, it is potentially affected by off-target contamination from surrounding cell types. Here, we leveraged single-cell sequencing datasets to apply a computational approach for estimating and controlling the amount of off-target cell type contamination in sctRNA-seq datasets. In datasets obtained using a number of technologies for cell purification, we found that most sctRNA-seq datasets tended to show some amount of off-target mRNA contamination from surrounding cells. However, using covariates for cellular contamination in downstream differential expression analyses increased the quality of our models for differential expression analysis in case/control comparisons and typically resulted in the discovery of more differentially expressed genes. In general, our method provides a flexible approach for detecting and controlling off-target cell type contamination in sctRNA-seq datasets.

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