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801 Modular gene analysis reveal distinct molecular signatures for cutaneous lupus patient subsets
  1. Jane L Zhu1,
  2. Ly Tran2,
  3. Miles Smith2,
  4. Frank Zheng2,
  5. Ling Cai3,
  6. Judith James2,
  7. Joel Guthridge2 and
  8. Benjamin F Chong1
  1. 1University of Texas at Southwestern Medical Center, Department of Dermatology, Dallas, TX, USA
  2. 2Oklahoma Medical Research Foundation, Arthritis and Clinical Research Immunology Program, Oklahoma City, OK, USA
  3. 3University of Texas at Southwestern Medical Center, Quantitative Biomedical Research Center, Department of Population and Data Sciences, Dallas, TX, USA


Background Cutaneous lupus erythematosus (CLE) is a heterogeneous autoimmune disease with clinical sequelae such as itching, dyspigmentation, and scarring. However, studies investigating the molecular heterogeneity of CLE patients are lacking. We applied a previously described modular analysis approach to assess the molecular heterogeneity of CLE patients.

Methods Whole blood transcriptomes of RNA sequencing data from a racially and ethnically diverse group of CLE patients (n=62) were used to calculate gene co-expression module scores. An unsupervised cluster analysis and K-means clustering based on these module scores were then performed. We used Fisher’s exact tests and Kruskal Wallis tests to compare characteristics between patient clusters.

Results Six unique clusters of CLE patients were identified from the cluster analysis (figure 1). We observed that seven inflammation modules were elevated in two CLE patient clusters.

Additionally, these clusters were characterized by interferon, neutrophil and cell death signatures, suggesting that interferon-related proteins, neutrophils, and cell death processes could be driving the inflammatory response in these subgroups. Three different clusters had a predominant T cell signature, which were supported by lymphocyte counts (figure 2).

Conclusion Our data support a diverse molecular profile in CLE that further adds to the clinical variations of this skin disease, and may affect disease course and treatment selection. Future studies with a larger and diverse CLE patient cohort are warranted to confirm these findings.

Abstract 801 Figure 1

Clustering of CLE patients based on gene expression module scores. (A) Random forest and k-mean clustering using expression module scores identified six molecularly distinct CLE patient subsets. Each point on this plot represents a patient. (B) Heat map of expression module scores of the six CLE patient subsets was shown. Modules were grouped by primary function. Boxes were color-coded by relative activation of modules. Purple represented less activation and yellow represented more activation.

Abstract 801 Figure 2

Molecular profiles of six CLE patient clusters. Radar plots showed modified z- scores of relative gene expression module scores in each of the molecularly-defined patient cluster indicated by legend. Cluster 1 had increased interferon (M1.2, M3.4, M5.12) module scores. Clusters 1 and 3 had increased inflammation (M2.2, M4.2, M4.6, M4.13, M5.1, M5.7, and M7.1), neutrophil (M5.15), low density granulocyte (LDG1.1), cell death (M6.13), and apoptosis (M6.6) module scores. Clusters 2, 4, and 5 had elevated T cell (M4.1 and M4.15) module scores.

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