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Risk of Early Infection in Idiopathic Inflammatory Myopathies: Cluster Analysis Based on Clinical Features and Biomarkers

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Abstract

Patients with idiopathic inflammatory myopathies (IIMs), referred to as myositis, are prone to infectious complications, which hinder the treatment of the disease and worsen the outcome of patients. The purpose of this study was to explore the different types of infectious complications in patients with myositis and to determine the predisposing factors for clinical reference. A retrospective study was conducted on 66 patients with IIM who were divided into different subpopulations by an unsupervised analysis of their clinical manifestations, laboratory features, and autoantibody characteristics. Combined with the incidence of infectious complications, the types of infectious pathogens and the sites of infection, the characteristics of infection, and susceptibility factors were explored. Three clusters with significantly different clinical characteristics and coinfection rates were identified (76.2% vs. 41.6% vs. 36.4%, p = 0.0139). Cluster 1 (n = 12) had a moderate risk of infection, with an infection rate of 41.6%. The patients in cluster 1 had a high probability of positive mechanic’s hands, periungual erythema, anti-Ro52 antibody, and anti-Jo1 antibody. CD3 and CD4 were the highest among the three groups. Cluster 2 (n = 21) had a high risk of infection, and the incidence of infection was 76.2%. Almost all patients in this cluster had a rash, prominent clinical symptoms, and decreased WBC, PMN, LYM, CD3, and CD4 counts. Cluster 3 (n = 33) had a low risk of infection, with an infection rate of 36.4%. Compared with the other two clusters, cluster 3 (n = 33) lacked a typical rash but had a high ANA-positive rate. The patients in cluster 1 and cluster 3 were mainly infected by viruses, followed by bacterial infections. In cluster 2 patients, bacterial infections were the most prevalent. Fungal and Pneumocystis carinii were common causes of cluster 2 and 3 infections. In addition, the patients within a cluster often have a single infection, and pulmonary infections are the most common. We clustered the patients with IIM complicated with infection into three different types by their clinical symptoms and found that there were differences in the infection risk and infection types among the different cluster groups.

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The data supporting the conclusions of this article are included within the article and its additional file.

References

  1. Baig, S., and J.J. Paik. 2020. Inflammatory muscle disease — an update. Best Practice & Research: Clinical Rheumatology 34(1):101484. https://doi.org/10.1016/j.berh.2019.101484

  2. Schmidt, J. 2018. Current classification and management of inflammatory myopathies. Journal of Neuromuscular Diseases 5 (2): 109–129. https://doi.org/10.3233/JND-180308.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Dalakas, M.C. 2015. Inflammatory muscle diseases. New England Journal of Medicine 372 (18): 1734–1747. https://doi.org/10.1056/NEJMra1402225.

    Article  PubMed  Google Scholar 

  4. Carstens, P.O., and J. Schmidt. 2014. Diagnosis, pathogenesis and treatment of myositis: Recent advances. Clinical and Experimental Immunology 175 (3): 349–358. https://doi.org/10.1111/cei.12194.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Marie, I., E. Hachulla, P. Chérin, M.F. Hellot, S. Herson, H. Levesque, and P.Y. Hatron. 2005. Opportunistic infections in polymyositis and dermatomyositis. Arthritis and Rheumatism 53 (2): 155–165. https://doi.org/10.1002/art.21083.

    Article  PubMed  Google Scholar 

  6. Redondo-Benito, A., A. Curran, A. Villar-Gomez, E. Trallero-Araguas, A. Fernández-Codina, I. Pinal-Fernandez, J.Á. Rodrigo-Pendás, and A. Selva-O’Callaghan. 2018. Opportunistic infections in patients with idiopathic inflammatory myopathies. International Journal of Rheumatic Diseases 21 (2): 487–496. https://doi.org/10.1111/1756-185X.13255.

    Article  CAS  PubMed  Google Scholar 

  7. Juárez, M., R. Misischia, and G.S. Alarcón. 2003. Infections in systemic connective tissue diseases: Systemic lupus erythematosus, scleroderma, and polymyositis/dermatomyositis. Rheumatic Diseases Clinics of North America 29 (1): 163–184. https://doi.org/10.1016/s0889-857x(02)00100-x.

    Article  PubMed  Google Scholar 

  8. Bohan, A., and J.B. Peter. 1975. Polymyositis and dermatomyositis (first of two parts) (J). New England Journal of Medicine 292 (7): 344–347.

    Article  CAS  PubMed  Google Scholar 

  9. Furst, D.E., A.A. Amato, Ş.R. Iorga, K. Gajria, and A.W. Fernandes. 2012. Epidemiology of adult idiopathic inflammatory myopathies in a U.S. managed care plan. Muscle Nerve 45 (5): 676–83. https://doi.org/10.1002/mus.23302

  10. Strauss, T., and M.J. von Maltitz. 2017 Generalising Ward’s method for use with Manhattan distances. PLoS One 12 (1): e0168288. https://doi.org/10.1371/journal.pone.0168288

  11. Coombes, C.E., X. Liu, Z.B. Abrams, K.R. Coombes, and G. Brock. 2021. Simulation-derived best practices for clustering clinical data. Journal of Biomedical Informatics 118: 103788. https://doi.org/10.1016/j.jbi.2021.103788

  12. Falagas, M.E., K.G. Manta, G.I. Betsi, and G. Pappas. 2007. Infection-related morbidity and mortality in patients with connective tissue diseases: A systematic review. Clinical Rheumatology 26 (5): 663–670. https://doi.org/10.1007/s10067-006-0441-9.

    Article  PubMed  Google Scholar 

  13. Miró, O., M. Laguno, J.R. Alonso, J. Casademont, C. Herrero, A. Selva, A. Urbano-Márquez, and J.M. Grau. 1999. Evolución de las miopatías inflamatorias idiopáticas: complicaciones, supervivencia y factores pronósticos Clinical course of idiopathic inflammatory myopathies: complications, survival and prognostic factors. Medicina Clínica 112 (14): 521–6. Spanish. PMID: 10363237

  14. Connolly, A., P.A. Gordon, J. Hannah, and D. Creamer. 2021. The chameleon rash: A review of the polyphenotypic dermatoses of dermatomyositis. Clinical and Experimental Dermatology 46 (6): 1016–1022. https://doi.org/10.1111/ced.14689.

    Article  CAS  PubMed  Google Scholar 

  15. Ge, Y.P., X.M. Shu, L.R. He, G.C. Wang, and X. Lu. 2022. Infection is not rare in patients with idiopathic inflammatory myopathies. Clinical and Experimental Rheumatology 40 (2): 254–259. https://doi.org/10.55563/clinexprheumatol/yps7ai.

    Article  PubMed  Google Scholar 

  16. Chen, I.J., W.P. Tsai, Y.J. Wu, S.F. Luo, H.H. Ho, L.B. Liou, J.Y. Chen, C.F. Kuo, H.C. Chang, C.H. Yang, and K.H. Yu. 2010. Infections in polymyositis and dermatomyositis: Analysis of 192 cases. Rheumatology (Oxford) 49 (12): 2429–2437. https://doi.org/10.1093/rheumatology/keq279.

    Article  PubMed  Google Scholar 

  17. Wik, J.A., and B.S. Skålhegg. 2022. T cell metabolism in infection. Frontiers in Immunology 13: 840610. https://doi.org/10.3389/fimmu.2022.840610

  18. Medzhitov, R. 2007. Recognition of microorganisms and activation of the immune response. Nature 449 (7164): 819–826. https://doi.org/10.1038/nature06246.

    Article  CAS  PubMed  Google Scholar 

  19. Feng, M., H. Guo, C. Zhang, C. Wang, Z. Liang, X. Zhao, Y. Qin, Y. Wu, G. Liu, C. Gao, and J. Luo. 2019. Absolute reduction of regulatory T cells and regulatory effect of short-term and low-dose IL-2 in polymyositis or dermatomyositis. International Immunopharmacology 77: 105912. https://doi.org/10.1016/j.intimp.2019.105912

  20. Arning, M., and C. Aul. 1994. Mykose-Prophylaxe bei neutrozytopenischen Patienten [Prophylaxis against mycoses in neutropenic patients]. Mycoses 37 Suppl 2: 70–6. German

  21. Xiao, Y., X. Zuo, Y. You, H. Luo, L. Duan, W. Zhang, Y. Li, Y. Xie, Y. Zhou, W. Ning, T. Li, S. Liu, H. Zhu, Y. Jiang, S. Wu, and H. Zhao. 2016. Investigation into the cause of mortality in 49 cases of idiopathic inflammatory myopathy: A single center study. Experimental and Therapeutic Medicine 11 (3): 885–889. https://doi.org/10.3892/etm.2016.3006.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Chatterjee, R., P. Mehta, V. Agarwal, and L. Gupta. 2021. High burden of infections in Indian patients with Idiopathic Inflammatory Myopathy: Validation of observations from the MyoCite dataset. Rheumatology (Oxford) 60 (9): 4315–4326. https://doi.org/10.1093/rheumatology/keab015.

    Article  CAS  PubMed  Google Scholar 

  23. Marie, I., E. Hachulla, and P. Che´rin, et al. 2005. Opportunistic infections in polymyositis and dermatomyositis. Arthritis Rheumatoid 53: 155–65, Infections in polymyositis and dermatomyositis: analysis of 192 cases

  24. Huang, L., W. Zhu, Y. Ye, X. Wu, Q. Yan, Z. Wang, Y. Lin, and S. Chen. 2021. Association of cytomegalovirus infection with anti-MDA5 antibody-positive dermatomyositis: a prospective cohort study. Frontiers in Medicine (Lausanne) 8: 740154. https://doi.org/10.3389/fmed.2021.740154

  25. Mecoli, C.A., and S.K. Danoff. 2020. Pneumocystis jirovecii pneumonia and other infections in idiopathic inflammatory myositis. Current Rheumatology Reports 22 (2): 7. https://doi.org/10.1007/s11926-020-0883-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Haldule, S., M. Chatterjee, R.P. Goswami, I. Vadsaria, P. Gaur, C. Kavadichanda, D.P. Misra, H. Chinoy, V. Agarwal, R. Aggarwal, and L. Gupta. 2022. A systematic review and meta-analysis of mycobacterial infections in patients with idiopathic inflammatory myopathies. Rheumatology (Oxford) 61 (9): 3521–3533. https://doi.org/10.1093/rheumatology/keac041.

    Article  PubMed  Google Scholar 

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Funding

This work was supported by the National Natural Science Foundation of China (82001728, 81973540); 1·3·5 project for Outstanding interdisciplinary project of West China Hospital, Sichuan University (ZYGD18015, ZYJC18003, ZYJC18024); Sichuan Science and Technology Program (20YYJC3358); and from zero to one Innovative Research Program of Sichuan University (2022SCUH0020).

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Author notes

  1. Lu Cheng and Yanhong Li contributed equally.

Authors and Affiliations

  1. Department of Rheumatology and Immunology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China

    Lu Cheng, Yanhong Li, Yinlan Wu, Yubin Luo, Ji Wen, Xiuping Liang, Tong Wu, Chunyu Tan & Yi Liu

  2. Rare Diseases Center, West China Hospital, Sichuan University, Chengdu, China

    Lu Cheng, Yanhong Li, Yinlan Wu, Yubin Luo, Ji Wen, Xiuping Liang, Tong Wu, Chunyu Tan & Yi Liu

  3. Institute of Immunology and Inflammation, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Chengdu, China

    Lu Cheng, Yanhong Li, Yinlan Wu, Yubin Luo, Ji Wen, Xiuping Liang, Tong Wu, Chunyu Tan & Yi Liu

  4. Department of Respiratory and Critical Care Medicine, Chengdu First People’s Hospital, Chengdu, China

    Yu Zhou

  5. Meishan People’s Hospital, Meishan, Sichuan, China

    Zehui Liao

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  1. Lu Cheng
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Contributions

L. Y., T. C. Y., and L. Y. B. conceived and designed the study. L. Y. and T. C. Y. guided the study. C. L., L. Y. H., W. Y. L., Z. Y., L. Z. H., W. J., L. X. P., and W. T. collected the clinical samples. C. L., L. Y. H., and W. Y. L. analyzed the data. All authors drafted and revised the manuscript. All authors drafted and revised the manuscript. Lu Cheng and Yanhong Li contributed equally to this work.

Corresponding authors

Correspondence to Chunyu Tan or Yi Liu.

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Ethics Approval and Consent to Participate

The study was approved by the ethical committee of West China Hospital of Sichuan University (No. 695 in 2020) and complied with the Declaration of Helsinki. The study did not involve animal studies, and no ethical approval was needed.

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All patients and controls provided written informed consent.

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The authors declare no competing interests.

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Cheng, L., Li, Y., Wu, Y. et al. Risk of Early Infection in Idiopathic Inflammatory Myopathies: Cluster Analysis Based on Clinical Features and Biomarkers. Inflammation 46, 1036–1046 (2023). https://doi.org/10.1007/s10753-023-01790-w

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