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Compendium of skin molecular signatures identifies key pathological features associated with fibrosis in systemic sclerosis
  1. Su-Jin Moon1,
  2. Jung Min Bae2,
  3. Kyung-Su Park3,
  4. Ilias Tagkopoulos4,
  5. Ki-Jo Kim5
  1. 1 Division of Rheumatology, Department of Internal Medicine, Uijeongbu St Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
  2. 2 Department of Dermatology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
  3. 3 Division of Rheumatology, Department of Internal Medicine, St Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
  4. 4 Department of Computer Science & Genome Center, University of California, Davis, Davis, California, USA
  5. 5 Division of Rheumatology, Department of Internal Medicine, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
  1. Correspondence to Dr Ki-Jo Kim, Division of Rheumatology, Department of Internal Medicine, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, 93, Jungbu-daero, Paldal-gu, Suwon-si, Gyeonggi-do, 16247, Republic of Korea; md21c{at}catholic.ac.kr

Abstract

Objectives Treatment of patients with systemic sclerosis (SSc) can be challenging because of clinical heterogeneity. Integration of genome-scale transcriptomic profiling for patients with SSc can provide insights on patient categorisation and novel drug targets.

Methods A normalised compendium was created from 344 skin samples of 173 patients with SSc, covering an intersection of 17 424 genes from eight data sets. Differentially expressed genes (DEGs) identified by three independent methods were subjected to functional network analysis, where samples were grouped using non-negative matrix factorisation. Finally, we investigated the pathways and biomarkers associated with skin fibrosis using gene-set enrichment analysis.

Results We identified 1089 upregulated DEGs, including 14 known genetic risk factors and five potential drug targets. Pathway-based subgrouping revealed four distinct clusters of patients with SSc with distinct activity signatures for SSc-relevant pathways. The inflammatory subtype was related to significant improvement in skin fibrosis at follow-up. The phosphoinositide-3-kinase-protein kinase B (PI3K-Akt) signalling pathway showed both the closest correlation and temporal pattern to skin fibrosis score. COMP, THBS1, THBS4, FN1, and TNC were leading-edge genes of the PI3K-Akt pathway in skin fibrogenesis.

Conclusions Construction and analysis of normalised skin transcriptomic compendia can provide useful insights on pathway involvement by SSc subsets and discovering viable biomarkers for a skin fibrosis index. Particularly, the PI3K-Akt pathway and its leading players are promising therapeutic targets.

  • systemic sclerosis
  • gene expression profiles
  • unsupervised clustering
  • fibrosis
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Footnotes

  • Handling editor Josef S Smolen

  • Contributors K-JK and S-JM designed the study and carried out data collection. K-JK performed computational analysis and drafted the paper, but all authors were involved in critically revising its final preparation. All authors approved the final version to be published.

  • Funding This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No NRF-2018R1A2B6007291).

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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