Next generation sequencing (NGS) in peripheral blood and hematopoietic stem cells (HSC) in SLE: mechanisms of disease, novel therapeutic targets and biomarkers for disease activity and response to therapy


Several types of cells are involved in SLE, all of which originate from HSCs. We have used RNA-Seq and genome-wide association studies to uncover genes and their products (RNA or proteins) that can be used as markers to predict patients more likely to develop severe lupus and respond to therapy. We also sought to interrogate the HSC in the bone marrow so to identify targets for new therapies.

Facts and figures

Project lead
D Boumpas
University of Athens,
FOREUM research grant: € 300.000
2016 - 2019

Meet the team

D Boumpas
University of Athens
G Bertsias
University of Crete
F Hiepe
Charité Berlin
C Pamfil
University of Medicine and Pharmacy
L Rönnblom
Uppsala University
T Vyse
King's College


Several types of cells are involved in SLE, all of which originate from HSC. We have used RNA Sequencing to uncover genes and their products (RNA or proteins) that can be used as markers to predict patients who may be more susceptible to certain serious manifestations of lupus as well as to interrogate the cells in the bone marrow (stem cells) to identify targets for new therapies.


Human Peripheral Blood RNA-seq

RNA-seq resulted in a comprehensive characterization of the transcriptome in SLE finding a higher number of DEGs and eQTLs. We also used machine learning techniques in order to detect the smallest set of genes predicting SLE disease activity from the same dataset and found:

  • Distinct transcriptome disturbances at inactive and active stages (“susceptibility and activity signature”)
  • The oxidative phosphorylation (mitochondrial hyperpolarization) pathway is implicated for the first time in the disease activity and severity
  • Active nephritis has distinct transcriptome changes that reflect granulocyte activation, humoral immunity and the proteasome (all potentially drug-able targets)
  • Organ involvement was predicted with high accuracy (accuracy=0.89, sensitivity=0.89, specificity=0.88 in the validation data) using 25 genes based on the elastic net generalised linear model. Among the 25 best predictors were MPO, ITGA3 and CD38.
  • SLEDAI-2K could not be predicted with high accuracy (accuracy 0.75, sensitivity=0.79, specificity=0.67) using 50 genes based on the neural network model. Performance was still the same even when 1648 genes (after first feature selection step) were used as predictors of SLEDAI-2K.

Human HSC RNA-seq

  • Transcriptome analysis of hematopoietic progenitors in the bone marrow of lupus vs healthy patients displayed enhanced proliferation/activation and myeloid skewing
  • Comparable transcriptional profiles for both  human and murine hematopoietic progenitors

Murine HSC RNA-seq

Bone marrow (BM) transcriptome analysis in lupus mice before and during the disease onset demonstrates:

  • Hypercellular BM and HSCs
  • Lupus bone marrow produces more myeloid progenitors
  • Differentiation arrest in the myeloid level of hematopoietic tree by suppression of conventional regulators of granulopoiesis with alternative granulopoiesis pathway
  • Transcriptome reprogramming reminiscent of “trained immunity”
  • Aberrant myelopoiesis might contribute to persistent inflammation and flares


  • Bertsias G et al. Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity. ARD2019 (In Press).
  • Nikolaos I Panousis, George Bertsias, Halit Ongen, Irini Gergianaki, Maria Tektonidou, Maria Trachana, Luciana Romano-Palumbo, Deborah Bielser, Cedric Howald, Cristina Pamfil, Antonis Fanouriakis, Despoina Kosmara, Argyro Repa, Prodromos Sidiropoulos, Emmanouil T Dermitzakis, Dimitrios T Boumpas. Genomic dissection of Systemic Lupus Erythematosus: Distinct Susceptibility, Activity and Severity Signatures. bioRxiv  255109; currently under review.
  • Gkirtzimanaki et al. IFNa Impairs Autophagic Degradation of mtDNA Promoting Autoreactivity of SLE Monocytes in a STING-Dependent Fashion. Cell Reports 25, 921–933 (2018)
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  • Grigoriou M, Anastasiou M, Verginis P, Pavlidis P, Nikolaou C, Bertsias G, Boumpas D T, Banos A. Rna-seq profiling of hematopoietic stem cells in murine systemic lupus erythematosus (sle): validation and functional characterisation. Ann Rheum Dis 2017;76:A57-A58.
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  • Bertsias G, Panousis N, Gergianaki I, Tektonidou M, Trachana M, Pamfil C, Fanouriakis A, Dermitzakis E, Boumpas D. The genomic architecture of Systemic Lupus Erythemathosus (SLE) by RNA-seq: Distinct disease susceptibility, activity and severity signatures and extensive genetic effects on whole blood gene expression. Abstract EULAR 2017, Madrid – accepted as Oral Presentation.
  • A Banos, M Grigoriou, P Verginis, P Pavlidis, G Bertsias, DT Boumpas. Transcriptome profiling by next generation sequencing of hematopoietic progenitors in murine systemic lupus erythematosus (SLE). Ann Rheum Dis 2016;75:A50.
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  • Bertsias G, Panousis N, Gergiannaki I, Tektonidou M, Trachana M, Banos A, Fanouriakis A, Pamfil C, Dermitzakis E, Boumpas D . Molecular characterization of SLE by RNA-Seq; Identification of genes and expression – quantitative trait loci contributing to pathogenesis, severity and tissue susceptibility  Clin Exp Rheumatol. 2016; 34(4): Suppl.99: S-49.
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Abstracts EULAR 2019

  • OP0277: RNA sequencing and machine learning techniques predict major organ involvement in patients with Systemic Lupus Erythematosus
  • THU0205: The hematopoietic stem cells (HSCS) in Systemic Lupus Erythematosus (SLE) reprogram their transcriptome: implications for the pathogenesis of the disease