scholarly journals Shared effect modeling reveals that a fraction of autoimmune disease associations are consistent with eQTLs in three immune cell types

2016 ◽  
Author(s):  
Sung Chun ◽  
Alexandra Casparino ◽  
Nikolaos A Patsopoulos ◽  
Damien Croteau-Chonka ◽  
Benjamin A Raby ◽  
...  
Keyword(s):  
Autoimmune Disease ◽  
Immune Cell ◽  
Cell Types ◽  
Disease Associations

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

scholarly journals A consideration of publication-derived immune-related associations in Coronavirus and related lung damaging diseases

2020 ◽  
Author(s):  
Nophar Geifman ◽  
Anthony D. Whetton
Keyword(s):  
Immune Cell ◽  
Cell Types ◽  
Biomedical Literature ◽  
Respiratory Syndrome Virus ◽  
Future Research ◽  
Close Relative ◽  
Small Proteins ◽  
H5n1 Influenza ◽  
Mesh Terms ◽  
Disease Associations

ABSTRACTThe severe acute respiratory syndrome virus SARS-CoV-2, a close relative of the SARS-CoV virus, is the cause of recent COVID-19 pandemic affecting, to date, nearly 2 million individuals across the globe and demonstrating relatively high rates of infection and mortality. A third virus, the H5N1, responsible for avian influenza, has caused infection with some clinical similarities to those in COVID-19 infections.Cytokines, small proteins that modulate immune responses, have been directly implicated in some of the severe responses seen in COVID-19 patients, e.g. cytokine storms.Understanding the immune processes related to COVID-19, and other similar infections, could help identify diagnostic markers and therapeutic targets.Here we examine data of cytokine, immune cell types, and disease associations captured from biomedical literature associated with coronavirus, SARS, and H5N1 influenza, with the objective of identifying potentially useful relationships and areas for future research. Cytokine and cell-type associations captured from MeSH terms linked to thousands of PubMed abstracts, has identified differing patterns of associations between the three corpuses of abstracts (coronavirus, SARS, or H5N1 influenza). Clustering of cytokine-disease co-occurrences in the context of coronavirus has identified compelling clusters of co-morbidities and symptoms, some of which already known to be linked to COVID-19. Finally, network analysis identified sub-networks of cytokines and immune cell types associated with different manifestations, co-morbidities and symptoms of coronavirus, SARS, and H5N1.Systematic review of research in medicine is essential to facilitate evidence-based choices about health interventions. In a fast moving pandemic the approach taken here will identify trends and enable rapid comparison to the literature of related diseases.

scholarly journals Integrative transcriptomic analysis of SLE reveals IFN-driven cross-talk between immune cells

2020 ◽  
Author(s):  
Bharat Panwar ◽  
Benjamin J. Schmiedel ◽  
Shu Liang ◽  
Brandie White ◽  
Enrique Rodriguez ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Autoimmune Disease ◽  
Cross Talk ◽  
Immune Cell ◽  
Cell Types ◽  
Cell Populations ◽  
Multiple Cell ◽  
Classical Monocytes ◽  
Multiple Immune Cell

ABSTRACTThe systemic lupus erythematosus (SLE) is an incurable autoimmune disease disproportionately affecting women and may lead to damage in multiple different organs. The marked heterogeneity in its clinical manifestations is a major obstacle in finding targeted treatments and involvement of multiple immune cell types further increases this complexity. Thus, identifying molecular subtypes that best correlate with disease heterogeneity and severity as well as deducing molecular cross-talk among major immune cell types that lead to disease progression are critical steps in the development of more informed therapies for SLE. Here we profile and analyze gene expression of six major circulating immune cell types from patients with well-characterized SLE (classical monocytes (n=64), T cells (n=24), neutrophils (n=24), B cells (n=20), conventional (n=20) and plasmacytoid (n=22) dendritic cells) and from healthy control subjects. Our results show that the interferon (IFN) response signature was the major molecular feature that classified SLE patients into two distinct groups: IFN-signature negative (IFNneg) and positive (IFNpos). We show that the gene expression signature of IFN response was consistent (i) across all immune cell types, (ii) all single cells profiled from three IFNpos donors using single-cell RNA-seq, and (iii) longitudinal samples of the same patient. For a better understanding of molecular differences of IFNpos versus IFNneg patients, we combined differential gene expression analysis with differential Weighted Gene Co-expression Network Analysis (WGCNA), which revealed a relatively small list of genes from classical monocytes including two known immune modulators, one the target of an approved therapeutic for SLE (TNFSF13B/BAFF: belimumab) and one itself a therapeutic for Rheumatoid Arthritis (IL1RN: anakinra). For a more integrative understanding of the cross-talk among different cell types and to identify potentially novel gene or pathway connections, we also developed a novel gene co-expression analysis method for joint analysis of multiple cell types named integrated WGNCA (iWGCNA). This method revealed an interesting cross-talk between T and B cells highlighted by a significant enrichment in the expression of known markers of T follicular helper cells (Tfh), which also correlate with disease severity in the context of IFNpos patients. Interestingly, higher expression of BAFF from all myeloid cells also shows a strong correlation with enrichment in the expression of genes in T cells that may mark circulating Tfh cells or related memory cell populations. These cell types have been shown to promote B cell class-switching and antibody production, which are well-characterized in SLE patients. In summary, we generated a large-scale gene expression dataset from sorted immune cell populations and present a novel computational approach to analyze such data in an integrative fashion in the context of an autoimmune disease. Our results reveal the power of a hypothesis-free and data-driven approach to discover drug targets and reveal novel cross-talk among multiple immune cell types specific to a subset of SLE patients. This approach is immediately useful for studying autoimmune diseases and is applicable in other contexts where gene expression profiling is possible from multiple cell types within the same tissue compartment.

scholarly journals Insights Into the Role of DNA Methylation in Immune Cell Development and Autoimmune Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Jiaqi Li ◽  
Lifang Li ◽  
Yimeng Wang ◽  
Gan Huang ◽  
Xia Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Autoimmune Disease ◽  
Autoimmune Diseases ◽  
Immune Cell ◽  
Gene Expression Regulation ◽  
Cell Types ◽  
Basic Function ◽  
Detailed Knowledge ◽  
Disease Pathogenesis

To date, nearly 100 autoimmune diseases have been an area of focus, and these diseases bring health challenges to approximately 5% of the population worldwide. As a type of disease caused by tolerance breakdown, both environmental and genetic risk factors contribute to autoimmune disease development. However, in most cases, there are still gaps in our understanding of disease pathogenesis, diagnosis, and treatment. Therefore, more detailed knowledge of disease pathogenesis and potential therapies is indispensable. DNA methylation, which does not affect the DNA sequence, is one of the key epigenetic silencing mechanisms and has been indicated to play a key role in gene expression regulation and to participate in the development of certain autoimmune diseases. Potential epigenetic regulation via DNA methylation has garnered more attention as a disease biomarker in recent years. In this review, we clarify the basic function and distribution of DNA methylation, evaluate its effects on gene expression and discuss related key enzymes. In addition, we summarize recent aberrant DNA methylation modifications identified in the most important cell types related to several autoimmune diseases and then provide potential directions for better diagnosing and monitoring disease progression driven by epigenetic control, which may broaden our understanding and contribute to further epigenetic research in autoimmune diseases.

scholarly journals Interleukin-17 and Th17 Lymphocytes Directly Impair Motoneuron Survival of Wildtype and FUS-ALS Mutant Human iPSCs

2021 ◽  
Vol 22 (15) ◽  
pp. 8042
Author(s):  
Mengmeng Jin ◽  
Katja Akgün ◽  
Tjalf Ziemssen ◽  
Markus Kipp ◽  
Rene Günther ◽  
...  
Keyword(s):  
Motor Neurons ◽  
Th17 Cells ◽  
Immune Cell ◽  
Cell Types ◽  
Positive Control ◽  
Interleukin 17 ◽  
Fused In Sarcoma ◽  
Th17 Lymphocytes ◽  
Human Ipscs ◽  
Als Patients

Amyotrophic lateral sclerosis (ALS) is a progressive disease leading to the degeneration of motor neurons (MNs). Neuroinflammation is involved in the pathogenesis of ALS; however, interactions of specific immune cell types and MNs are not well studied. We recently found a shift toward T helper (Th)1/Th17 cell-mediated, pro-inflammatory immune responses in the peripheral immune system of ALS patients, which positively correlated with disease severity and progression. Whether Th17 cells or their central mediator, Interleukin-17 (IL-17), directly affects human motor neuron survival is currently unknown. Here, we evaluated the contribution of Th17 cells and IL-17 on MN degeneration using the co-culture of iPSC-derived MNs of fused in sarcoma (FUS)-ALS patients and isogenic controls with Th17 lymphocytes derived from ALS patients, healthy controls, and multiple sclerosis (MS) patients (positive control). Only Th17 cells from MS patients induced severe MN degeneration in FUS-ALS as well as in wildtype MNs. Their main effector, IL-17A, yielded in a dose-dependent decline of the viability and neurite length of MNs. Surprisingly, IL-17F did not influence MNs. Importantly, neutralizing IL-17A and anti-IL-17 receptor A treatment reverted all effects of IL-17A. Our results offer compelling evidence that Th17 cells and IL-17A do directly contribute to MN degeneration.

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

scholarly journals Single-cell map of diverse immune phenotypes in the acute myeloid leukemia microenvironment

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Rongqun Guo ◽  
Mengdie Lü ◽  
Fujiao Cao ◽  
Guanghua Wu ◽  
Fengcai Gao ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Immune Cell ◽  
Immune Surveillance ◽  
Cell Types ◽  
Developmental Trajectory ◽  
Significant Difference ◽  
Cell Phenotypes ◽  
Acute Myeloid

Abstract Background Knowledge of immune cell phenotypes, function, and developmental trajectory in acute myeloid leukemia (AML) microenvironment is essential for understanding mechanisms of evading immune surveillance and immunotherapy response of targeting special microenvironment components. Methods Using a single-cell RNA sequencing (scRNA-seq) dataset, we analyzed the immune cell phenotypes, function, and developmental trajectory of bone marrow (BM) samples from 16 AML patients and 4 healthy donors, but not AML blasts. Results We observed a significant difference between normal and AML BM immune cells. Here, we defined the diversity of dendritic cells (DC) and macrophages in different AML patients. We also identified several unique immune cell types including T helper cell 17 (TH17)-like intermediate population, cytotoxic CD4+ T subset, T cell: erythrocyte complexes, activated regulatory T cells (Treg), and CD8+ memory-like subset. Emerging AML cells remodels the BM immune microenvironment powerfully, leads to immunosuppression by accumulating exhausted/dysfunctional immune effectors, expending immune-activated types, and promoting the formation of suppressive subsets. Conclusion Our results provide a comprehensive AML BM immune cell census, which can help to select pinpoint targeted drug and predict efficacy of immunotherapy.

scholarly journals Implications of hematopoietic stem cells heterogeneity for gene therapies

Gene Therapy ◽  
2021 ◽  
Author(s):  
Jeremy Epah ◽  
Richard Schäfer
Keyword(s):  
Immune Cell ◽  
Ex Vivo ◽  
Bone Marrow Failure ◽  
Cell Types ◽  
Blood Disorders ◽  
Hematopoietic Stem ◽  
Therapeutic Concept ◽  
Gene Therapies ◽  
Bone Marrow Failure Syndromes ◽  
Immunodeficiency Syndrome

AbstractHematopoietic stem cell transplantation (HSCT) is the therapeutic concept to cure the blood/immune system of patients suffering from malignancies, immunodeficiencies, red blood cell disorders, and inherited bone marrow failure syndromes. Yet, allogeneic HSCT bear considerable risks for the patient such as non-engraftment, or graft-versus host disease. Transplanting gene modified autologous HSCs is a promising approach not only for inherited blood/immune cell diseases, but also for the acquired immunodeficiency syndrome. However, there is emerging evidence for substantial heterogeneity of HSCs in situ as well as ex vivo that is also observed after HSCT. Thus, HSC gene modification concepts are suggested to consider that different blood disorders affect specific hematopoietic cell types. We will discuss the relevance of HSC heterogeneity for the development and manufacture of gene therapies and in exemplary diseases with a specific emphasis on the key target HSC types myeloid-biased, lymphoid-biased, and balanced HSCs.

484 Bioturing browser: interactively explore public single cell sequencing data

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A520-A520
Author(s):  
Son Pham ◽  
Tri Le ◽  
Tan Phan ◽  
Minh Pham ◽  
Huy Nguyen ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cell ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Cell Types ◽  
Sequencing Data ◽  
Single Cell Sequencing ◽  
Data Formats ◽  
Cancer Types ◽  
Cell Data

BackgroundSingle-cell sequencing technology has opened an unprecedented ability to interrogate cancer. It reveals significant insights into the intratumoral heterogeneity, metastasis, therapeutic resistance, which facilitates target discovery and validation in cancer treatment. With rapid advancements in throughput and strategies, a particular immuno-oncology study can produce multi-omics profiles for several thousands of individual cells. This overflow of single-cell data poses formidable challenges, including standardizing data formats across studies, performing reanalysis for individual datasets and meta-analysis.MethodsN/AResultsWe present BioTuring Browser, an interactive platform for accessing and reanalyzing published single-cell omics data. The platform is currently hosting a curated database of more than 10 million cells from 247 projects, covering more than 120 immune cell types and subtypes, and 15 different cancer types. All data are processed and annotated with standardized labels of cell types, diseases, therapeutic responses, etc. to be instantly accessed and explored in a uniform visualization and analytics interface. Based on this massive curated database, BioTuring Browser supports searching similar expression profiles, querying a target across datasets and automatic cell type annotation. The platform supports single-cell RNA-seq, CITE-seq and TCR-seq data. BioTuring Browser is now available for download at www.bioturing.com.ConclusionsN/A

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