Psoriasis / psoriatic arthritis and metabolic syndrome in young adults: microRNA expression pattern
https://doi.org/10.33667/2078-5631-2026-7-63-69
Abstract
Background. Psoriasis (PsO), psoriatic arthritis (PsA), and metabolic syndrome (MetS) share common immune-inflammatory mechanisms. MicroRNAs are considered potential molecular links integrating inflammatory and metabolic disturbances.
Objective. To evaluate the expression of hsa-miR‑210–3p, hsa-miR‑10b‑5p, hsa-miR‑130a‑3p, and hsa-miR‑126–5p in young patients with PsO and PsA, taking into account the presence of MetS.
Materials and methods. The study included 38 patients with PsO and 37 with PsA under 45 years of age. Plasma microRNA expression was assessed using RT-qPCR (2^-ΔΔCt method). PERMANOVA, SIMPER, ROC analysis, and correlation analysis were performed.
Results. The results of paired multivariate PERMANOVA analysis for the PsO and PsA groups demonstrated statistically significant differences in the overall expression pattern of the studied microRNAs (p=0.003). Statistically significant differences in expression between patients with PsO and PsA were found for two microRNAs: miR‑130a‑3p and miR‑10b‑5p: 57.3 % (p=<0.001) and 22.5 % (p=0.021). The presence of MS in patients with PsA was accompanied by an increase in the expression of miR‑10b‑5p (FC=0.68, p=0.03; log2(2^(–dct) PsA without MS –0.56 [–1.387; –0.198] compared to PsA with MS –1.465 [–1.842; –0.67], p=0.032). The expression level of miR‑130a‑3p positively correlated with glucose, insulin and HOMA-IR.
Conclusion. hsa-miR‑130a‑3p and hsa-miR‑10b‑5p may reflect the transition from cutaneous to articular forms of psoriatic disease and participate in the integration of metabolic and inflammatory pathways, representing potential biomarkers of PsO-to-PsA transformation.
About the Authors
P. A. ShesternyaRussian Federation
Shesternya Pavel A., Dr Med Sci (habil.), professor, vice‑rector for Research, head of Det of Propaedeutics of Internal Diseases and Therapy with a Course in Postgraduate Education
Krasnoyarsk
D. V. Dmitrenko
Russian Federation
Dmitrenko Diana V., Dr Med Sci (habil.), associate professor, head of Dept of Medical Genetics and Clinical Neurophysiology at the Institute of Postgraduate Education, head of Laboratory of Medical Genetics
Krasnoyarsk
E. V. Turchik
Russian Federation
Turchik Evgeniya V., postgraduate student at V. I. Prokhorenkov Dept of Dermatovenereology with a Course in Cosmetology and Postgraduate Education
Krasnoyarsk
E. E. Timechko
Russian Federation
Timechko Elena E., junior researcher at Laboratory of Medical Genetics
Krasnoyarsk
A. M. Yakimov
Russian Federation
Yakimov Alexey M., junior researcher at Laboratory of Medical Genetics
Krasnoyarsk
A. A. Vasilyeva
Russian Federation
Vasilyeva Anastasia A., junior researcher at Laboratory of Medical Genetics
Krasnoyarsk
Yu. Yu. Vinnik
Russian Federation
Vinnik Yuriy Yu., Dr Med Sci (habil.), associate professor, professor at V. I. Prokhorenkov Dept of Dermatovenereology with a Course in Cosmetology and Postgraduate Education, Krasnoyarsk State Medical University named after зrofessor V. F. Voino-Yasenetsky; chief physician, Krasnoyarsk Regional Dermatovenereological Dispensary No. 1
Krasnoyarsk
References
1. Loganathan A, Kamalaraj N, El Haddad C, Pile K. Systematic review and meta analysis on prevalence of metabolic syndrome in psoriatic arthritis, rheumatoid arthritis and psoriasis. Int J Rheum Dis. 2021; 24 (9): 1112–1120. DOI: 10.1111/1756-185X.14147
2. Scarpa R, Caso F, Costa L, et al. Psoriatic Disease 10 Years Later. J Rheumatol. 2017; 44 (9): 1298–1301. DOI: 10.3899/jrheum.161402
3. Boehncke WH. Systemic inflammation and cardiovascular comorbidity in psoriasis patients: causes and consequences. Front Immunol. 2018; 9: 579. DOI: 10.3389/fimmu.2018.00579
4. Liu Q, Wu DH, Han L, et al. Roles of microRNAs in psoriasis: immunological functions and potential biomarkers. Exp Dermatol. 2017; 26 (4): 359–367. DOI: 10.1111/exd.13249
5. Тимечко ЕЕ, Турчик ЕВ, Филипенко ДЕ, и др. Псориаз и коморбидные состояния: исследование молекулярных механизмов на основе метаанализа данных РНК секвенирования. Сибирское медицинское обозрение. 2024; (6): 5–13. DOI: 10.20333/25000136-2024-6-5-13.
6. Timechko EE, Turchik EV, Filipenko DE, et al. Psoriasis and comorbidities: an investigation of molecular mechanisms based on a meta analysis of RNA sequencing data. Siberian Medical Review. 2024; (6): 5–13. (In Russ.). DOI: 10.20333/25000136-2024-6-5-13
7. Haschka J, Simon D, Bayat S, et al. Identification of circulating microRNA patterns in patients with psoriasis and psoriatic arthritis. Rheumatology (Oxford). 2023; 62 (10): 3448–3458. DOI: 10.1093/rheumatology/kead059
8. Yan X, Zhang Y, Li J, et al. Dysregulated microRNA signatures in psoriatic arthritis identified by RNA sequencing. Front Immunol. 2024; 15: 11745863. DOI: 10.3389/fimmu.2024.11745863
9. Ramos AP, Rossato BG, Scalcon MR, et al. MicroRNAs in psoriasis and psoriatic arthritis: a narrative review of potential diagnostics and current challenges. Journal of Laboratory and Precision Medicine, 2026; 11. DOI: 10.21037/jlpm-25-38
10. Denzler R, McGeary SE, Title AC, et al. Impact of MicroRNA Levels, Target Site Complementarity, and Cooperativity on Competing Endogenous RNA Regulated Gene Expression. Molecular Cell. 2016; 64: 565–569. DOI: 10.1016/j.molcel.2016.09.027
11. World Medical Association. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013; 310 (20): 2191–2194. DOI: 10.1001/jama.2013.281053
12. Chandran V, Schentag CT, Gladman DD. Sensitivity and specificity of the CASPAR criteria for psoriatic arthritis. J Rheumatol. 2008; 35 (10): 2069–2070
13. Рекомендации по ведению больных с метаболическим синдромом. Клинические рекомендации. 2013;43 с. Режим доступа: https://efaidnbmnnnibpcajpcglclefindmkaj/https://mzdrav.rk.gov.ru/file/mzdrav_18042014_Klinicheskie_rekomendacii_Metabolicheskij_sindrom.pdf. Ссылка активна на 01.03.2026
14. Rekomendacii po vedeniju bol’nyh s metabolicheskim sindromom. Klinicheskie rekomendacii. 2013;43. Available https://efaidnbmnnnibpcajpcglclefindmkaj/https://mzdrav.rk.gov.ru/file/mzdrav_18042014_Klinicheskie_rekomendacii_Metabolicheskij_sindrom.pdf. Accessed: 01.03.2026 (In Russ.).
15. Zheng XH, Cui C, Zhou XX, et al. Centrifugation: an important pre analytic procedure that influences plasma microRNA quantification during blood processing. Chin J Cancer. 2013; 32: 667. DOI: 10.5732/CJC.012.10271
16. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real time quantitative PCR and the 2–ΔΔCT method. Methods. 2001; 25: 402–408. DOI: 10.1006/meth.2001.1262
17. Rice J, Roberts H, Rai SN, Galandiuk S. Housekeeping genes for studies of plasma microRNA: a need for more precise standardization. Surgery. 2015; 158: 1345–1351. DOI: 10.1016/j.surg.2015.04.025
18. Van Rossum G, Drake FL. Python 3 Reference Manual. Scotts Valley, CA: CreateSpace; 2009
19. Raybaut P. Spyder documentation [Internet]. 2009. Available from: https://pythonhosted.org
20. Yan K, Zhu J, Zhang M, et al. Differential expression of plasma extracellular vesicle miRNAs as biomarkers for distinguishing psoriatic arthritis from psoriasis. Chin Med J (Engl). 2025: 20; 138 (2): 219–221. DOI: 10.1097/CM9.0000000000003288
21. Pasquali L, Svedbom A, Srivastava A, et al. Circulating microRNAs in extracellular vesicles as potential biomarkers for psoriatic arthritis in patients with psoriasis. J Eur Acad Dermatol Venereol. 2020; 34 (6): 1248–1256. DOI: 10.1111/jdv.16203
22. Wade SM, McGarry T, Wade SC, Fearon U, Veale DJ. Serum MicroRNA Signature as a Diagnostic and Therapeutic Marker in Patients with Psoriatic Arthritis. J Rheumatol. 2020: 1; 47 (12): 1760–1767. DOI: 10.3899/jrheum.190602
23. Lättekivi F, Guljavina I, Midekessa G, et al. Profiling Blood Serum Extracellular Vesicles in Plaque Psoriasis and Psoriatic Arthritis Patients Reveals Potential Disease Biomarkers. Int J Mol Sci. 2022; 4; 23 (7): 4005. DOI: 10.3390/ijms23074005
24. Kiran S, Mandal M, Rakib A, Bajwa A, Singh UP. miR 10a 3p modulates adiposity and suppresses adipose inflammation through TGF β1/Smad3 signaling pathway. Front Immunol. 2023: 2; 14: 1213415. DOI: 10.3389/fimmu.2023.1213415
25. Wu J, Dong T, Chen T, et al. Hepatic exosome derived miR 130a 3p attenuates glucose intolerance via suppressing PHLPP2 gene in adipocyte. Metabolism. 2020; 103: 154006. DOI: 10.1016/j.metabol.2019
26. Al Rawaf HA. Circulating microRNAs and adipokines as markers of metabolic syndrome in adolescents with obesity. Clin Nutr. 2019; 38 (5): 2231–2238. DOI: 10.1016/j.clnu.2018.09.024
27. Karolina DS, Tavintharan S, Armugam A, Sepramaniam S, Pek SL, Wong MT, Lim SC, Sum CF, Jeyaseelan K. Circulating miRNA profiles in patients with metabolic syndrome. J Clin Endocrinol Metab. 2012; 97 (12): E2271–6. DOI: 10.1210/jc.2012-1996
28. Chen Y, Gorski DH. Regulation of angiogenesis through a microRNA (miR 130a) that down regulates antiangiogenic homeobox genes GAX and HOXA5. Blood. 2008: 1; 111 (3): 1217–26. DOI: 10.1182/blood-2007-07-104133.
29. Huang J, Xu X, Yang J. miRNAs Alter T Helper 17 Cell Fate in the Pathogenesis of Autoimmune Diseases. Front Immunol. 2021; 21; 12: 593473. DOI: 10.3389/fimmu.2021
30. Hirahara K, Ghoreschi K, Laurence A, et al. Signal transduction pathways and transcriptional regulation in Th17 cell differentiation. Cytokine Growth Factor Rev. 2010; 21 (6): 425–34. DOI: 10.1016/j.cytogfr.2010.10.006
31. Takegahara, N, Kim H, Choi Y. Unraveling the intricacies of osteoclast differentiation and maturation: insight into novel therapeutic strategies for bone destructive diseases. Exp Mol Med. 2024: 56, 264–272. DOI: 10.1038/s12276-024-01157-7
32. Xie W, Zhou L, Li S, Hui T, Chen D. Wnt/β catenin signaling plays a key role in the development of spondyloarthritis. Ann N Y Acad Sci. 2016; 1364 (1): 25–31. DOI: 10.1111/nyas.12968
Review
For citations:
Shesternya P.A., Dmitrenko D.V., Turchik E.V., Timechko E.E., Yakimov A.M., Vasilyeva A.A., Vinnik Yu.Yu. Psoriasis / psoriatic arthritis and metabolic syndrome in young adults: microRNA expression pattern. Medical alphabet. 2026;(7):63-69. (In Russ.) https://doi.org/10.33667/2078-5631-2026-7-63-69
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