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 Genomic dissection of Systemic Lupus Erythematosus: Distinct Susceptibility, Activity and Severity Signatures

2018 ◽  
Author(s):  
Nikolaos I. Panousis ◽  
George Bertsias ◽  
Halit Ongen ◽  
Irini Gergianaki ◽  
Maria Tektonidou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Disease Activity ◽  
Lupus Erythematosus ◽  
Whole Blood ◽  
Personalized Therapy ◽  
Flare Activity ◽  
Rna Seq ◽  
Healthy Individuals ◽  
Systemic Lupus

AbstractRecent genetic and genomics approaches have yielded novel insights in the pathogenesis of Systemic Lupus Erythematosus (SLE) but the diagnosis, monitoring and treatment still remain largely empirical1,2. We reasoned that molecular characterization of SLE by whole blood transcriptomics may facilitate early diagnosis and personalized therapy. To this end, we analyzed genotypes and RNA-seq in 142 patients and 58 matched healthy individuals to define the global transcriptional signature of SLE. By controlling for the estimated proportions of circulating immune cell types, we show that the Interferon (IFN) and p53 pathways are robustly expressed. We also report cell-specific, disease-dependent regulation of gene expression and define a core/susceptibility and a flare/activity disease expression signature, with oxidative phosphorylation, ribosome regulation and cell cycle pathways being enriched in lupus flares. Using these data, we define a novel index of disease activity/severity by combining the validated Systemic Lupus Erythematosus Disease Activity Index (SLEDAI)1 with a new variable derived from principal component analysis (PCA) of RNA-seq data. We also delineate unique signatures across disease endo-phenotypes whereby active nephritis exhibits the most extensive changes in transcriptome, including prominent drugable signatures such as granulocyte and plasmablast/plasma cell activation. The substantial differences in gene expression between SLE and healthy individuals enables the classification of disease versus healthy status with median sensitivity and specificity of 83% and 100%, respectively. We explored the genetic regulation of blood transcriptome in SLE and found 3142 cis-expression quantitative trait loci (eQTLs). By integration of SLE genome-wide association study (GWAS) signals and eQTLs from 44 tissues from the Genotype-Tissue Expression (GTEx) consortium, we demonstrate that the genetic causality of SLE arises from multiple tissues with the top causal tissue being the liver, followed by brain basal ganglia, adrenal gland and whole blood. Collectively, our study defines distinct susceptibility and activity/severity signatures in SLE that may facilitate diagnosis, monitoring, and personalized therapy.

scholarly journals Rheumatoid arthritis, systemic lupus erythematosus and primary Sjögren’s syndrome shared megakaryocyte expansion in peripheral blood

2021 ◽  
pp. annrheumdis-2021-220066
Author(s):  
Yukai Wang ◽  
Xuezhen Xie ◽  
Chengpeng Zhang ◽  
Miaotong Su ◽  
Sini Gao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Flow Cytometry ◽  
Lupus Erythematosus ◽  
Peripheral Blood ◽  
Immune Cell ◽  
Primary Sjögren’S Syndrome ◽  
Rna Seq ◽  
Systemic Lupus

ObjectivesRheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and primary Sjögren’s syndrome (pSS) share many clinical manifestations and serological features. The aim of this study was to identify the common transcriptional profiling and composition of immune cells in peripheral blood in these autoimmune diseases (ADs).MethodsWe analysed bulk RNA-seq data for enrichment of biological processes, transcription factors (TFs) and deconvolution-based immune cell types from peripheral blood mononuclear cells (PBMCs) in 119 treatment-naive patients (41 RA, 38 pSS, 28 SLE and 12 polyautoimmunity) and 20 healthy controls. The single-cell RNA-seq (scRNA-seq) and flow cytometry had been performed to further define the immune cell subsets on PBMCs.ResultsSimilar transcriptional profiles and common gene expression signatures associated with nucleosome assembly and haemostasis were identified across RA, SLE, pSS and polyautoimmunity. Distinct TF ensembles and gene regulatory network were mainly enriched in haematopoiesis. The upregulated cell-lineage-specific TFs PBX1, GATA1, TAL1 and GFI1B demonstrated a strong gene expression signature of megakaryocyte (MK) expansion. Gene expression-based cell type enrichment revealed elevated MK composition, specifically, CD41b+CD42b+ and CD41b+CD61+ MKs were expanded, further confirmed by flow cytometry in these ADs. In scRNA-seq data, MKs were defined by TFs PBX1/GATA1/TAL1 and pre-T-cell antigen receptor gene, PTCRA. Cellular heterogeneity and a distinct immune subpopulation with functional enrichment of antigen presentation were observed in MKs.ConclusionsThe identification of MK expansion provided new insights into the peripheral immune cell atlas across RA, SLE, pSS and polyautoimmunity. Aberrant regulation of the MK expansion might contribute to the pathogenesis of these ADs.

scholarly journals AB0009 ASSOCIATION OF STAT4 RS7574865, RUNX1 RS9979383, IL6 RS1800795, IL6R RS2228145, IL6R RS4845618 WITH SYSTEMIC LUPUS ERYTHEMATOSUS SUSCEPTIBILITY AND SOME LUPUS MANIFESTATIONS IN BELARUSIAN POPULATION

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1039.2-1040
Author(s):  
N. Dostanko ◽  
V. Yagur ◽  
R. Goncharova ◽  
E. Siniauskaya ◽  
T. Zybalova
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Diagnostic Odds Ratio ◽  
Protective Role ◽  
Fisher Exact Test ◽  
Systemic Lupus ◽  
Exact Test ◽  
American College Of Rheumatology ◽  
Healthy Donors ◽  
Significant Difference

Background:Systemic lupus erythematosus (SLE) has a significant genetic predisposition. Many genetic variants of susceptibility to SLE have been published and analyzed, but the clinical and functional significance of the various genotypes has not yet been clearly defined [1].Objectives:To estimate the association between some of non-HLA gene polymorphisms such as STAT4 rs7574865, RUNX1 rs9979383, IL6 rs1800795, IL6R rs2228145, IL6R rs4845618 and susceptibility to SLE in Belarusian population as well as some disease manifestations.Methods:We examined 383 healthy blood donors and 54 SLE patients (18-72 years old, median age 35) classified according to the 1997 American College of Rheumatology (ACR) revised classification criteria [2]. Deoxyribonucleic acid was extracted from peripheral blood samples by phenol-chloroform method. Genotyping was performed by real-time PCR with fluorescent probes. Differences of distribution of all the single nucleotide polymorphism (SNP) genotypes and their associations with secondary antiphospholipid syndrom (APS) and lupus arthritis were analyzed using Pearson χ2 (χ2) and two-way Fisher exact test (F, p2-t). Diagnostic odds ratio (dOR), likelihood ratio of positive (LR +) and negative (LR –) tests and corresponding 95% confidence intervals (CI) were also calculated.Results:We revealed significant difference in STAT4 rs7574865 genotypes in SLE patients and healthy donors (χ2=8,27, р=0,016) with significant increase of ТТ genotype frequency in SLE patients vs healthy donors (χ2=6.83 p=0.009; p2-t =0.020; dOR=3.78 (CI95% 1.36-10.55); LR+ =3.44 (CI95% 1.35-8.71); LR– =0.91 (CI95% 0.83-0.98)). Lupus arthritis was more common in risk TT-genotype SLE carriers than in other SLE patients (χ2=5.902 p=0.015; p2-t =0.027).We revealed significant increase of СТ genotype (RUNX1 rs9979383) in healthy donors vs SLE patients (χ2=4.14; p=0.042; dOR=0.53 (CI95% 0.29-0.98); LR+ =0.69 (CI95% 0.45-0.99); LR– =1.3 (CI95% 1.01-1,56)). Lupus arthritis was more common in SLE СТ-genotype carriers than in other SLE patients (χ2=4.66 p=0.031; p2-t =0.058).Significant differences in IL6 rs1800795, IL6R rs2228145 and IL6R rs4845618 genotypes distribution between studied groups were not found (χ2, p=0.427, p=0.559 and p=0.407, correspondingly) but GG-genotype (IL6 rs1800795) carriership in SLE patients was associated with increased APS frequency (χ2=4.45, p=0.035; dOR=0.19 (CI95% 0.04-0.9); LR+ =0.28 (CI95% 0.07-0.93); LR– =1.41 (CI95% 1.03-1.64).Conclusion:Our data suggest the susceptibility to SLE in ТТ genotype of STAT4 rs7574865 polymorphism, protective role of СТ genotype of RUNX1 rs9979383 for SLE and association between GG-genotype of IL6 rs1800795 and APS in SLE patients in Belarusian population. Lupus arthritis was associated with ТТ genotype of STAT4 rs7574865 and СТ genotype of RUNX1 rs9979383.References:[1]Chen L, Morris DL, Vyse TJ. Genetic advances in systemic lupus erythematosus: an update. Curr Opin Rheumatol 2017;29:423–33.[2]Hochberg MC. Updating the American College of Rheumatology Revised Criteria for the classification of Systemic Lupus Erythematosus. Arthritis Rheum 1997;40:1725.Disclosure of Interests:None declared

Systemic Lupus Erythematosus Disease Activity Index 2000 Responder Index-50 Enhances the Ability of SLE Responder Index to Identify Responders in Clinical Trials

2011 ◽  
Vol 38 (11) ◽  
pp. 2395-2399 ◽  
Author(s):  
ZAHI TOUMA ◽  
DAFNA D. GLADMAN ◽  
DOMINIQUE IBAÑEZ ◽  
SHAHRZAD TAGHAVI-ZADEH ◽  
MURRAY B. UROWITZ
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Clinical Trials ◽  
Disease Activity ◽  
Lupus Erythematosus ◽  
Activity Index ◽  
Disease Activity Index ◽  
Systemic Lupus ◽  
Original Definition ◽  
Definition Of

Objective.To evaluate the performance of the Systemic Lupus Erythematosus (SLE) Responder Index (SRI) when the SLE Disease Activity Index 2000 (SLEDAI-2K) is substituted with SLEDAI-2K Responder Index-50 (SRI-50), a valid and reliable index of disease activity improvement. Also, to determine whether the SRI-50 will enhance the ability of SRI in detecting responders.Methods.Our study was conducted on patients who attended the Lupus Clinic from September 2009 to September 2010. SLEDAI-2K, SRI-50, the British Isles Lupus Assessment Group measure, and the Physician’s Global Assessment were determined initially and at followup. SRI was determined at the followup visit according to its original definition using the SLEDAI-2K score and by substituting SLEDAI-2K with SRI-50.Results.A total of 117 patients with SLEDAI-2K ≥ 4 at baseline were studied. Patients had 1 followup visit over a 3-month period. Twenty-nine percent of patients met the original definition of SRI and 35% of patients met the definition of SRI when SLEDAI-2K was substituted with SRI-50. The use of SRI-50 allowed determination of significant improvement in 7 additional patients. This improvement could not be discerned with the use of SLEDAI-2K as a component of SRI. At followup visits that showed improvement, SRI-50 scores decreased to a greater extent than SLEDAI-2K scores (p < 0.0001).Conclusion.SRI-50 enhances the ability of SRI to identify patients with clinically important improvement in disease activity. SRI-50 was superior to SLEDAI-2K in detecting partial clinical improvement, ≥ 50%, between visits. These properties of the SRI-50 enable it to be used as an independent outcome measure of improvement or as a component of SRI in clinical trials.

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.

Sign in / Sign up

Export Citation Format

Share Document