GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Frontiers Media SA ; 2019
    In:  Frontiers in Immunology Vol. 10 ( 2019-10-21)
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 10 ( 2019-10-21)
    Type of Medium: Online Resource
    ISSN: 1664-3224
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2019
    detail.hit.zdb_id: 2606827-8
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    In: Frontiers in Genetics, Frontiers Media SA, Vol. 5 ( 2015-01-08)
    Type of Medium: Online Resource
    ISSN: 1664-8021
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2015
    detail.hit.zdb_id: 2606823-0
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    Online Resource
    Online Resource
    Frontiers Media SA ; 2023
    In:  Frontiers in Lupus Vol. 1 ( 2023-10-3)
    In: Frontiers in Lupus, Frontiers Media SA, Vol. 1 ( 2023-10-3)
    Abstract: Systemic lupus erythematosus (SLE) is a chronic autoimmune condition with complex causes involving genetic and environmental factors. While genome-wide association studies (GWASs) have identified genetic loci associated with SLE, the functional genomic elements responsible for disease development remain largely unknown. Mendelian Randomization (MR) is an instrumental variable approach to causal inference based on data from observational studies, where genetic variants are employed as instrumental variables (IVs). Methods This study utilized a two-step strategy to identify causal genes for SLE. In the first step, the classical MR method was employed, assuming the absence of horizontal pleiotropy, to estimate the causal effect of gene expression on SLE. In the second step, advanced probabilistic MR methods (PMR-Egger, MRAID, and MR-MtRobin) were applied to the genes identified in the first step, considering horizontal pleiotropy, to filter out false positives. PMR-Egger and MRAID analyses utilized whole blood expression quantitative trait loci (eQTL) and SLE GWAS summary data, while MR-MtRobin analysis used an independent eQTL dataset from multiple immune cell types along with the same SLE GWAS data. Results The initial MR analysis identified 142 genes, including 43 outside of chromosome 6. Subsequently, applying the advanced MR methods reduced the number of genes with significant causal effects on SLE to 66. PMR-Egger, MRAID, and MR-MtRobin, respectively, identified 13, 7, and 16 non-chromosome 6 genes with significant causal effects. All methods identified expression of PHRF1 gene as causal for SLE. A comprehensive literature review was conducted to enhance understanding of the functional roles and mechanisms of the identified genes in SLE development. Conclusions The findings from the three MR methods exhibited overlapping genes with causal effects on SLE, demonstrating consistent results. However, each method also uncovered unique genes due to different modelling assumptions and technical factors, highlighting the complementary nature of the approaches. Importantly, MRAID demonstrated a reduced percentage of causal genes from the Major Histocompatibility complex (MHC) region on chromosome 6, indicating its potential in minimizing false positive findings. This study contributes to unraveling the mechanisms underlying SLE by employing advanced probabilistic MR methods to identify causal genes, thereby enhancing our understanding of SLE pathogenesis.
    Type of Medium: Online Resource
    ISSN: 2813-6934
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 4
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 10 ( 2019-4-2)
    Type of Medium: Online Resource
    ISSN: 1664-3224
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2019
    detail.hit.zdb_id: 2606827-8
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 5
    Online Resource
    Online Resource
    Frontiers Media SA ; 2020
    In:  Frontiers in Immunology Vol. 11 ( 2020-10-21)
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 11 ( 2020-10-21)
    Type of Medium: Online Resource
    ISSN: 1664-3224
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2020
    detail.hit.zdb_id: 2606827-8
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 6
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Immunology Vol. 13 ( 2022-10-4)
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 13 ( 2022-10-4)
    Abstract: Seropositivity for autoantibodies against multiple islet antigens is associated with development of autoimmune type 1 diabetes (T1D), suggesting a role for B cells in disease. The importance of B cells in T1D is indicated by the effectiveness of B cell-therapies in mouse models and patients. B cells contribute to T1D by presenting islet antigens, including insulin, to diabetogenic T cells that kill pancreatic beta cells. The role of B cell receptor (BCR) affinity in T1D development is unclear. Here, we employed single cell RNA sequencing to define the relationship between BCR affinity for insulin and B cell phenotype during disease development. We utilized immunoglobulin (Ig) heavy chain (VH125) mouse models in which high-affinity insulin-reactive B cells (IBCs) were previously shown to be anergic in diabetes-resistant VH125.C57BL/6-H2g7 and activated in VH125. NOD mice developing disease. Here, high-affinity IBCs were found in the spleen of prediabetic VH125. NOD mice and exhibited marginal zone or follicular phenotypes. Ig light chains expressed by these B cells are unmutated and biased toward Vκ4-74 and Vκ4-57 usage. Receptors expressed by anergic high-affinity IBCs of diabetes-resistant VH125.C57BL/6-H2g7 are also unmutated; however, in this genetic background light chains are polymorphic relative to those of NOD. Light chains derived from NOD and C57BL/6-H2g7 genetic backgrounds conferred divergent kinetics of binding to insulin when paired with the VH125 heavy chain. These findings suggest that relaxation of tolerance mechanisms in the NOD mouse leads to accumulation and partial activation of B cells expressing germline encoded high-affinity BCRs that support development of autoimmunity.
    Type of Medium: Online Resource
    ISSN: 1664-3224
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2606827-8
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 7
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Immunology Vol. 13 ( 2022-8-24)
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 13 ( 2022-8-24)
    Abstract: Most B cells produced in the bone marrow have some level of autoreactivity. Despite efforts of central tolerance to eliminate these cells, many escape to periphery, where in healthy individuals, they are rendered functionally non-responsive to restimulation through their antigen receptor via a process termed anergy. Broad repertoire autoreactivity may reflect the chances of generating autoreactivity by stochastic use of germline immunoglobulin gene segments or active mechanisms may select autoreactive cells during egress to the naïve peripheral B cell pool. Likewise, it is unclear why in some individuals autoreactive B cell clones become activated and drive pathophysiologic changes in autoimmune diseases. Both of these remain central questions in the study of the immune system(s). In most individuals, autoimmune diseases arise from complex interplay of genetic risk factors and environmental influences. Advances in genome sequencing and increased statistical power from large autoimmune disease cohorts has led to identification of more than 200 autoimmune disease risk loci. It has been observed that autoantibodies are detectable in the serum years to decades prior to the diagnosis of autoimmune disease. Thus, current models hold that genetic defects in the pathways that control autoreactive B cell tolerance set genetic liability thresholds across multiple autoimmune diseases. Despite the fact these seminal concepts were developed in animal (especially murine) models of autoimmune disease, some perceive a disconnect between human risk alleles and those identified in murine models of autoimmune disease. Here, we synthesize the current state of the art in our understanding of human risk alleles in two prototypical autoimmune diseases – systemic lupus erythematosus (SLE) and type 1 diabetes (T1D) along with spontaneous murine disease models. We compare these risk networks to those reported in murine models of these diseases, focusing on pathways relevant to anergy and central tolerance. We highlight some differences between murine and human environmental and genetic factors that may impact autoimmune disease development and expression and may, in turn, explain some of this discrepancy. Finally, we show that there is substantial overlap between the molecular networks that define these disease states across species. Our synthesis and analysis of the current state of the field are consistent with the idea that the same molecular networks are perturbed in murine and human autoimmune disease. Based on these analyses, we anticipate that murine autoimmune disease models will continue to yield novel insights into how best to diagnose, prognose, prevent and treat human autoimmune diseases.
    Type of Medium: Online Resource
    ISSN: 1664-3224
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2606827-8
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...