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Identification of childhood-onset lupus nephritis through integrative bioinformatics: otoferlin as a novel biomarker

Pediatric Research (2025)Cite this article

Abstract

Background

Childhood-onset systemic lupus erythematosus (cSLE) exhibits a higher incidence of lupus nephritis (LN) compared to adult-onset SLE (aSLE). However, the underlying molecular mechanisms remain elusive.

Methods

Gene expression datasets from childhood-onset (GSE65391) and adult-onset (GSE72798) LN patients were obtained. Differential gene expression (DEG) and weighted gene co-expression network analysis (WGCNA) identified key modules associated with cLN. Machine learning algorithms (random forest, SVM-RFE) prioritized hub genes, validated by ROC curves. Immune cell profiles analysis (CIBERSORT, ssGSEA, xCell) evaluated immune cell profiles, and functional enrichment (GSEA, GSVA) explored pathway alterations. Molecular docking and drug sensitivity analysis predicted therapeutic targets for  otoferlin (OTOF)-high cLN.

Results

Distinct gene expression profiles were revealed between cLN and aLN, with significant enrichment of interferon (IFN) pathways in cLN. OTOF emerged as a high diagnostic biomarker for cLN, and was positively correlated with activated dendritic cells and associated with the TLR signaling pathway in cLN. Molecular docking predicted strong binding of OTOF to JAK inhibitors, supported by CMap analysis showing sensitivity of OTOF-high cLN to these drugs.

Conclusions

IFN-related pathways are crucial for the pathogenesis of cLN. OTOF is a promising blood biomarker and contributes to cLN progression through IFN-related pathways.

Impact

  • The molecular mechanisms by which cSLE is more likely to progress to cLN than aSLE are rarely investigated.

  • The crucial role of interferon pathways in cLN pathogenesis is highlighted.

  • OTOF could serve as an early diagnostic biomarker for cLN and promote cLN progression through TLRs.

  • These insights could guide tailored therapeutic strategies for cLN, addressing a critical gap in current clinical management.

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Fig. 1: Identification of DEGs and gene enrichment analysis.
Fig. 2: Immune cell profiles in cLN and aLN.
Fig. 3: Construction of the co-expression network.
Fig. 4: Identification of biomarkers using machine learning algorithms.
Fig. 5: Correlations between OTOF expression and immune cell profiles in cLN.
Fig. 6: GSEA and ssGSEA analyses of OTOF expression levels and drug sensitivity analysis in cLN.

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Data availability

The public datasets used and analyzed in this study are available from NCBI GEO: GSE65391, GSE72798, GSE99967, and GSE81622.

References

  1. Li, X. Z. et al. Humoral immunity and safety of respiratory virus vaccines in systemic lupus erythematosus population: a meta-analysis based on twenty-five observational studies. Ann. Med. 56, 2392882 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Katikaneni, D., Morel, L. & Scindia, Y. Animal models of lupus nephritis: the past, present and a future outlook. Autoimmunity 57, 2319203 (2024).

    Article  PubMed  Google Scholar 

  3. Anders, H. J. et al. Lupus nephritis. Nat. Rev. Dis. Prim. 6, 7 (2020).

    Article  PubMed  Google Scholar 

  4. Vazzana, K. M. et al. Principles of pediatric lupus nephritis in a prospective contemporary multi-center cohort. Lupus 30, 1660–1670 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Baqi, N. et al. Lupus nephritis in children: a longitudinal study of prognostic factors and therapy. J. Am. Soc. Nephrol. 7, 924–929 (1996).

    Article  CAS  PubMed  Google Scholar 

  6. Peng, J. et al. Clinical implications of a new DDX58 pathogenic variant that causes lupus nephritis due to RIG-I hyperactivation. J. Am. Soc. Nephrol. 34, 258–272 (2023).

    Article  PubMed  Google Scholar 

  7. Yoo, E. J. et al. Macrophage transcription factor TonEBP promotes systemic lupus erythematosus and kidney injury via damage-induced signaling pathways. Kidney Int. 104, 163–180 (2023).

    Article  CAS  PubMed  Google Scholar 

  8. Arriens, C. et al. Update on the efficacy and safety profile of voclosporin: an integrated analysis of clinical trials in lupus nephritis. Arthritis Care Res.75, 1399–1408 (2023).

    Article  CAS  Google Scholar 

  9. Peyronel, F. et al. Early-onset lupus nephritis. Clin. Kidney J. 17, sfae212 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Chan, E. Y., Lai, F. F., Ma, A. L. & Chan, T. M. Managing lupus nephritis in children and adolescents. Paediatr. Drugs 26, 145–161 (2024).

    Article  PubMed  Google Scholar 

  11. Liebermeister, W. et al. Visual account of protein investment in cellular functions. Proc. Natl. Acad. Sci. USA 111, 8488–8493 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics9, 559 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Sanz, H. et al. SVM-RFE: selection and visualization of the most relevant features through non-linear kernels. BMC Bioinformatics19, 432 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Rigatti, S. J. Random forest. J. Insur. Med. 47, 31–39 (2017).

    Article  PubMed  Google Scholar 

  17. Ernst, J. & Bar-Joseph, Z. STEM: a tool for the analysis of short time series gene expression data. BMC Bioinformatics7, 191 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Yang, K. et al. CMAP: Complement Map Database. Bioinformatics 29, 1832–1833 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Hong, Y. et al. Exploring the molecular mechanism of Tripterygium wilfordii Hook F in treating systemic lupus erythematosus via network pharmacology and molecular docking. Clin. Rheumatol. 44, 1549–1569 (2025).

    Article  PubMed  Google Scholar 

  20. Hong, Y. et al. Environmental triggers and future risk of developing autoimmune diseases: molecular mechanism and network toxicology analysis of bisphenol A. Ecotoxicol. Environ. Saf. 288, 117352 (2024).

    Article  CAS  PubMed  Google Scholar 

  21. Holcar, M., Goropevšek, A. & Avčin, T. Altered homeostasis of regulatory T lymphocytes and differential regulation of STAT1/STAT5 in CD4+ T lymphocytes in childhood-onset systemic lupus erythematosus. J. Rheumatol. 47, 557–566 (2020).

    Article  CAS  PubMed  Google Scholar 

  22. Ding, H. et al. Membrane protein OTOF is a type I interferon-induced entry inhibitor of HIV-1 in macrophages. mBio 13, e0173822 (2022).

    Article  PubMed  Google Scholar 

  23. Rönnblom, L. & Leonard, D. Interferon pathway in SLE: one key to unlocking the mystery of the disease. Lupus Sci. Med. 6, e000270 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Parodis, I. et al. Interferon and B-cell signatures inform precision medicine in lupus nephritis. Kidney Int. Rep. 9, 1817–1835 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Arazi, A. et al. The immune cell landscape in kidneys of patients with lupus nephritis. Nat. Immunol. 20, 902–914 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ambrose, N. et al. Differences in disease phenotype and severity in SLE across age groups. Lupus 25, 1542–1550 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Mosca, M. et al. Brief Report: How do patients with newly diagnosed systemic lupus erythematosus present? A multicenter cohort of early systemic lupus erythematosus to inform the development of new classification criteria. Arthritis Rheumatol. 71, 91–98 (2019).

    Article  PubMed  Google Scholar 

  28. Li, Y., Tang, D., Yin, L. & Dai, Y. New insights for regulatory T cell in lupus nephritis. Autoimmun. Rev. 21, 103134 (2022).

    Article  CAS  PubMed  Google Scholar 

  29. Dmitriev, D. A. et al. Predicting the impact of OTOF gene missense variants on auditory neuropathy spectrum disorder. Int. J. Mol. Sci. 24, 17240 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Yalcin, E. et al. Evidence that melatonin downregulates Nedd4-1 E3 ligase and its role in cellular survival. Toxicol. Appl. Pharmacol. 379, 114686 (2019).

    Article  CAS  PubMed  Google Scholar 

  31. Zhong, Y. et al. Screening biomarkers for Sjogren’s Syndrome by computer analysis and evaluating the expression correlations with the levels of immune cells. Front. Immunol. 14, 1023248 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Liu, J., Zhang, X. & Cao, X. Dendritic cells in systemic lupus erythematosus: from pathogenesis to therapeutic applications. J. Autoimmun. 132, 102856 (2022).

    Article  CAS  PubMed  Google Scholar 

  33. Corridoni, D. et al. NOD2 and TLR2 signal via TBK1 and PI31 to direct cross-presentation and CD8 T cell responses. Front. Immunol. 10, 958 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Swaraj, S. & Tripathi, S. Interference without interferon: interferon-independent induction of interferon-stimulated genes and its role in cellular innate immunity. mBio 15, e0258224 (2024).

    Article  PubMed  Google Scholar 

  35. Oikonomou, V. et al. The role of interferon-γ in autoimmune polyendocrine syndrome type 1. N. Engl. J. Med. 390, 1873–1884 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kandhaya-Pillai, R. et al. TNF-α/IFN-γ synergy amplifies senescence-associated inflammation and SARS-CoV-2 receptor expression via hyper-activated JAK/STAT1. Aging Cell 21, e13646 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This study was a re-analysis based on published data from the GEO database. We would like to thank these databases for sharing the data.

Funding

This work was supported by the Natural Science Foundation of Zhejiang Province (grant number LTGY23H100001), Science and Technology Plan Project of Wenzhou Municipality, China (grant numbers Y20220389, Y20220045), National innovation and Entrepreneurship Training Program for College Students (grant number 202310343025); Zhejiang College Students Innovative Entrepreneurial Training Program (New Young Talent Program) (grant number 2023R413025).

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Author notes

  1. These authors contributed equally: Xinlei Wu, Xinyue Liang.

Authors and Affiliations

  1. School of the 2nd Clinical Medical Sciences, Wenzhou Medical University, Wenzhou, China

    Xinlei Wu

  2. School of Ophthalmology and Optometry, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, China

    Xinyue Liang & Siyan Chen

  3. School of the 1st Clinical Medical Sciences, Wenzhou Medical University, Wenzhou, China

    Yang Li

  4. School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, China

    Yuanyuan Xie & Chunyan Hua

  5. Laboratory Animal Center, Wenzhou Medical University, Wenzhou, China

    Sheng Gao

Authors
  1. Xinlei Wu
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  4. Siyan Chen
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  5. Yuanyuan Xie
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Contributions

Xinlei Wu designed the research, analyzed the data, and wrote the manuscript; Xinyue Liang and Yang Li analyzed and interpreted the data; Siyan Chen and Yuanyua Xie corrected the manuscript. Chunyan Hua and Sheng Gao designed this study, revised the manuscript, and received funding support.

Corresponding authors

Correspondence to Chunyan Hua or Sheng Gao.

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Wu, X., Liang, X., Li, Y. et al. Identification of childhood-onset lupus nephritis through integrative bioinformatics: otoferlin as a novel biomarker. Pediatr Res (2025). https://doi.org/10.1038/s41390-025-04171-1

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  • DOI: https://doi.org/10.1038/s41390-025-04171-1

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