scholarly journals Gene expression in systemic lupus erythematosus: Bone marrow analysis differentiates active from inactive disease and reveals apoptosis and granulopoiesis signatures

2008 ◽  
Vol 58 (11) ◽  
pp. 3541-3549 ◽  
Author(s):  
Magdalene Nakou ◽  
Nicholas Knowlton ◽  
Mark B. Frank ◽  
George Bertsias ◽  
Jeanette Osban ◽  
...  
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Bone Marrow ◽  
Lupus Erythematosus ◽  
Inactive Disease ◽  
Systemic Lupus ◽  
Bone Marrow Analysis

Bone marrow analysis of immune cells and apoptosis in patients with systemic lupus erythematosus

Lupus ◽  
2014 ◽  
Vol 23 (10) ◽  
pp. 975-985 ◽  
Author(s):  
JW Park ◽  
SY Moon ◽  
JH Lee ◽  
JK Park ◽  
DS Lee ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Bone Marrow ◽  
Immune Cells ◽  
Lupus Erythematosus ◽  
Systemic Lupus ◽  
Bone Marrow Analysis

scholarly journals The gene expression of type 17 T-helper cell-related cytokines in the urinary sediment of patients with systemic lupus erythematosus

Rheumatology ◽  
2009 ◽  
Vol 48 (12) ◽  
pp. 1491-1497 ◽  
Author(s):  
B. C.-H. Kwan ◽  
L.-S. Tam ◽  
K.-B. Lai ◽  
F. M.-M. Lai ◽  
E. K.-M. Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
T Helper Cell ◽  
Helper Cell ◽  
T Helper ◽  
Systemic Lupus ◽  
Urinary Sediment

scholarly journals Positive Selection Affects the Expression of Systemic Lupus Erythematosus Associated Loci in Human Populations

2021 ◽  
Author(s):  
Victoria Oberreiter ◽  
Tobias Goellner ◽  
David L. Morris ◽  
Helmut Schaschl
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Positive Selection ◽  
Lupus Erythematosus ◽  
Lifestyle Changes ◽  
Genetic Ancestry ◽  
Selection Function ◽  
Human Populations ◽  
Systemic Lupus ◽  
A Genome

Abstract Background: Systemic lupus erythematosus (SLE) shows marked population-specific disparities in disease prevalence, including substantial variation in manifestations and complications according to genetic ancestry. Several recent studies suggest that a substantial proportion of variation of gene expression shows genetic ancestry-associated differences in gene regulation on immune responses. Positive selection may act in a population-specific manner on expression quantitative trait loci (eQTLs) and thereby contributes to the difference in the differences of SLE prevalence and manifestation in human populations. We tested the hypothesises that some of the identified SLE risk polymorphisms display pleiotropic effects or polygenicity driven by positive selection. We performed a genome-wide scan for recent positive selection by using integrated Haplotype Score (iHS) statistics in different human populations. In addition, we estimated the timing of beneficial mutations to understand what possible selective pressures drive positive selection at SLE-associated loci. Results: We identified several SLE risk loci that are population-specifically under positive selection. Almost all SNPs that are under positive selection function as cis-eQTLs in different tissue types. We determined that adaptive eQTLs affect the expression of fewer genes than non-adaptive eQTLs, suggesting a limited range of effect of an eQTL at SLE risk sites that show signatures of positive selection. Furthermore, some positively selected SNPs are located in transcription factor binding sequences. The timing of positive selection for the studied loci suggests that both environmental and recent lifestyle changes during as well as after the Neolithic Transition may have become selectively effective. We propose a novel link between positively selected eQTLs at a certain SLE risk locus in Europeans and a physiological pathway not previously considered in SLE.Conclusions: We conclude that population-specific adaptive eQTLs contribute to the observed variation in specific manifestations and complications of SLE in different ethnicities. Our results suggest also that human populations adapt more rapidly to environmental and lifestyle stimuli via modification of gene expression without having to alter the genetic code.

scholarly journals Machine learning applied to whole-blood RNA-sequencing data uncovers distinct subsets of patients with systemic lupus erythematosus

2019 ◽  
Author(s):  
William A Figgett ◽  
Katherine Monaghan ◽  
Milica Ng ◽  
Monther Alhamdoosh ◽  
Eugene Maraskovsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Systemic Lupus Erythematosus ◽  
Clinical Trials ◽  
Lupus Erythematosus ◽  
Whole Blood ◽  
Rna Seq ◽  
Systemic Lupus ◽  
Disease Heterogeneity ◽  
Healthy Donors

ABSTRACTObjectiveSystemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease that is difficult to treat. There is currently no optimal stratification of patients with SLE, and thus responses to available treatments are unpredictable. Here, we developed a new stratification scheme for patients with SLE, based on the whole-blood transcriptomes of patients with SLE.MethodsWe applied machine learning approaches to RNA-sequencing (RNA-seq) datasets to stratify patients with SLE into four distinct clusters based on their gene expression profiles. A meta-analysis on two recently published whole-blood RNA-seq datasets was carried out and an additional similar dataset of 30 patients with SLE and 29 healthy donors was contributed in this research; 141 patients with SLE and 51 healthy donors were analysed in total.ResultsExamination of SLE clusters, as opposed to unstratified SLE patients, revealed underappreciated differences in the pattern of expression of disease-related genes relative to clinical presentation. Moreover, gene signatures correlated to flare activity were successfully identified.ConclusionGiven that disease heterogeneity has confounded research studies and clinical trials, our approach addresses current unmet medical needs and provides a greater understanding of SLE heterogeneity in humans. Stratification of patients based on gene expression signatures may be a valuable strategy to harness disease heterogeneity and identify patient populations that may be at an increased risk of disease symptoms. Further, this approach can be used to understand the variability in responsiveness to therapeutics, thereby improving the design of clinical trials and advancing personalised therapy.

scholarly journals Cell-mediated amegakaryocytic thrombocytopenia associated with systemic lupus erythematosus

Blood ◽  
1986 ◽  
Vol 67 (2) ◽  
pp. 479-483
Author(s):  
T Nagasawa ◽  
T Sakurai ◽  
H Kashiwagi ◽  
T Abe
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Bone Marrow ◽  
T Cells ◽  
Lupus Erythematosus ◽  
Culture System ◽  
Bone Marrow Cells ◽  
Rare Complication ◽  
Systemic Lupus ◽  
Marrow Cells

We studied a patient with a rare complication of amegakaryocytic thrombocytopenia (AMT) associated with systemic lupus erythematosus (SLE). To investigate the underlying pathogenesis of AMT, the effects of peripheral blood T cells and serum on human megakaryocyte progenitor cells were studied using in vitro coculture techniques. Mononuclear bone marrow cells (2 X 10(5) from normal donors produced 33.6 +/- 8.8 (n = 10) colony-forming unit-megakaryocytes (CFU-M) in our plasma clot system. When 2 X 10(5) of the patient's T cells were added to the culture system, the number of CFU-M decreased to only 3.5 +/- 0.6/2 X 10(5) bone marrow cells. No evidence of inhibitory effects was found by the addition of the patient's serum and complement to the culture system. The T cells stored at -80 degrees C on admission were also capable of suppressing autologous CFU-M after recovery from AMT. These results indicate that in vitro suppression of CFU-M from allogenic and autologous bone marrow cells by this patient's T cells provides an explanation for the pathogenesis of AMT associated with SLE.

scholarly journals Immune deposit and vasculopathy in metabolic-active lung tissues of patients with pulmonary tuberculosis

2021 ◽  
Author(s):  
Hui Ma ◽  
Lin Wang ◽  
Zilu Wen ◽  
Xinchun Chen ◽  
Haiying Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Inflammatory Response ◽  
Pulmonary Tuberculosis ◽  
Autoimmune Diseases ◽  
Metabolic Activity ◽  
Lupus Erythematosus ◽  
Immune Complexes ◽  
Systemic Lupus ◽  
Dsdna Antibodies

ABSTRACTMetabolic activity in pulmonary lesion is associated with disease severity and relapse risk in tuberculosis. However, the nature of the metabolic activity associated with tuberculosis in humans remains unclear. Previous works indicate that tuberculosis bears resemblance transcriptionally with systemic lupus erythematosus in peripheral blood, except that the plasma cell component was absent in tuberculosis. Here we reported that the missing transcriptional component was present within the metabolic active tissues in the lung of patients with sputum culture-negative tuberculosis, within which increased levels of circulating immune complexes and anti-dsDNA antibodies were found relative to nearby non-metabolic active tissues. Histological examination revealed specific vascular deposition of immune complexes, neutrophil extracellular traps, and vascular necrosis in the metabolic-active tissue. Thus, tuberculosis-initiated metabolic activity was associated with hyperactive antibody responses and vascular pathology, and shared features with systemic lupus erythematosus and other autoimmune diseases. We discussed these observations in the context of earlier literatures demonstrating that similar effects could be induced in humans and animal models by complete freund’s adjuvant, the most potent antibody response inducer ever reported. Our small case series, if verified in a larger size study, might help inform host-directed therapies to alleviate disease progression and augment treatment efficacy.IMPORTANCEIn patients with pulmonary tuberculosis, lung tissues were destroyed by a hyperactive inflammatory response towards M. tuberculosis. The mechanisms underlying the inflammatory response are still poorly understood. Using 18F-FDG avidity as a surrogate marker of inflammation, we have identified that hyper-inflamed tissues possessed features associated with systemic lupus erythematosus: gene expression signatures of plasma cell and immunoglobulins and increased levels of anti-dsDNA antibodies, immune deposits, and vasculopathy. This observation might suggest an explanation to why patients with tuberculosis share more gene expression signatures with autoimmune diseases than infectious diseases and why they are more likely to develop autoimmune diseases. Defining the inflammatory responses at the lesion could help inform host-directed therapies to intervene disease progression or even accelerate cure.

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