Russian Journal of Infection and ImmunityRussian Journal of Infection and ImmunityИнфекция и иммунитет2220-76192313-7398SPb RAACI200810.15789/2220-7619-UOS-2008ORIGINAL ARTICLESОРИГИНАЛЬНЫЕ СТАТЬИResearch ArticleUse of some bone-related cytokines as predictors for rheumatoid arthritis severity by neural network analysisИспользование ряда цитокинов, ассоциированных с костной тканью, в качестве предикторов тяжести ревматоидного артрита при помощи нейросетевого анализаSalehR. O.СалехР. О.
Iraq

Medical Laboratory Techniques Department

отдел медицинской лабораторной техники

sc.kfwi72@uoanbar.edu.iqMahmoodL. A.МахмудЛ. А.
Iraq

Assistent Professor

Ассистент

sc.kfwi72@uoanbar.edu.iqMohammedM. A.МохаммедМ. А.
Iraq
sc.kfwi72@uoanbar.edu.iqAl-RawiK. F.Аль-РавиХ. Ф.
Russian Federation

PhD, Professor

профессор

sc.kfwi72@uoanbar.edu.iqAl-HakeimH. K.Аль-ХакеймХ. К.
Iraq

Professor

профессор

sc.kfwi72@uoanbar.edu.iqAl-Maarif University CollegeУниверситетский колледж Аль-МаарифCollege of Medicine, University of AnbarМедицинский колледж, Университет АнбарGeneral Directorate of Anbar Education, Ministry of EducationГлавное управление образования провинции Анбар, Министерство образованияCollege of Science, University of AnbarНаучный колледж, Университет АнбарCollege of Science, University of KufaНаучный колледж, Университет Куфы06122022010420231311471552507202206082022Copyright ©; 2023, Saleh R.O., Mahmood L.A., Mohammed M.A., Al-Rawi K.F., Al-Hakeim H.K.Copyright ©; 2023, Салех Р.О., Махмуд Л.А., Мохаммед М.А., Аль-Рави Х.Ф., Аль-Хакейм Х.К.2023Saleh R.O., Mahmood L.A., Mohammed M.A., Al-Rawi K.F., Al-Hakeim H.K.Салех Р.О., Махмуд Л.А., Мохаммед М.А., Аль-Рави Х.Ф., Аль-Хакейм Х.К.https://creativecommons.org/licenses/by/4.0https://iimmun.ru/iimm/article/view/2008

Background. Rheumatoid arthritis (RA) is characterized by synovial membrane inflammation that results in joint damage. Many earlier studies have measured cytokines for a better diagnosis of RA. In the present study, three bone biomarkers [osteopontin, stromelysin-1 (MMP3), and vascular endothelial growth factor-A (VEGF)] are examined for their ability to estimate the severity of disease by using artificial neural network (NN) analysis and binary logistic regression analysis. Methods. The study enrolled 87 RA patients and 44 healthy control subjects. The biomarkers were measured by the enzyme-linked immunosorbent assay technique. Disease Activity Score (28 joints) and C-reactive protein (CRP) (DAS28-CRP) was calculated by using DAS28-CRP calculator. The patients with DAS28-CRP ≥ 5.1 are considered as having high disease activity (HDA). While patients’ group with DAS28-CRP < 5.1 are considered as moderate disease activity (MDA). The neural network (NN) analysis was used for the differentiation between groups. Results. Results showed that the most sensitive predictor for high disease activity (HDA) of RA is MMP3, followed by osteopontin and VEGF. These three biomarkers can differentiate significantly between HDA and MDA with a relatively high size effect (Partial η2 = 0.323, p < 0.001). The HDA group has a significantly higher MMP3, CRP, RF, and anti-citrullinated protein antibodies (ACPA) than the MDA group. MMP3 is strongly associated with two inflammatory indicators; CRP and ESR. Conclusion. There was a significant elevation in the serum level of MMP3 in RA patients with HDA compared to the MDA and control groups. High DAS28, RF, CRP, and ACPA were found in HDA patients compared with the MDA group. The use of the NN analysis indicated that the measured biomarkers help predict the HDA state in RA patients. MMP3 and osteopontin are diagnostic biomarkers for the severity of RA and are related to many disease-related characteristics with a sensitivity of 88.9% and specificity of 68.4%.

История вопроса. Ревматоидный артрит (РА) характеризуется воспалением синовиальной оболочки, приводящего к повреждению суставов. Многие более ранние исследования оценивали уровень цитокинов для улучшения диагностики РА. В настоящем исследовании для оценки тяжести заболевания с использованием нейронной сети и бинарного логистического регрессионного анализа были исследованы три костных биомаркера: остеопонтин, стромелизин-1 (ММР3) и фактор роста эндотелия сосудов А (VEGF). Методы. В исследовании приняли участие 87 больных РА и 44 здоровых человека контрольной группы. Уровень биомаркеров определяли методом иммуноферментного анализа. Показатель активности заболевания (28 суставов) и С-реактивный белок (CRP) (DAS28-CRP) рассчитывали с помощью DAS28-CRP-калькулятора. Пациенты с DAS28-CRP ≥ 5,1 считаются имеющими высокую активность заболевания (ВАЗ), в то время как при DAS28-CRP < 5,1 заболевание расценивается как умеренно активное (УАЗ). Нейросетевой анализ использовался для дифференциации между группами. Результаты. Результаты исследования показали, что наиболее чувствительным предиктором высокой активности заболевания (HDA) РА является MMP3, за которым следуют остеопонтин и VEGF. Эти три биомаркера могут существенно дифференцировать HDA и MDA с относительно высокой эффективностью (частичный η2 = 0,323, p < 0,001). Группа с ВАЗ имеет значительно более высокий уровень MMP3, CRP, RF и антител к цитруллинированному белку (ACPA), чем группа с УАЗ. MMP3 тесно связан с двумя индикаторами воспаления: СРБ и СОЭ. Выводы. Отмечалось значительное повышение уровня ММР3 в сыворотке крови и уровней у пациентов с РА с ВАЗ по сравнению с группой с УАЗ и контрольной группой. Высокие уровни DAS28, RF, CRP и ACPA были обнаружены у пациентов с ВАЗ по сравнению с группой пациентов с УАЗ. Использование нейросетевого анализа показало, что измеренные биомаркеры помогают прогнозировать ВАЗ у пациентов с РА. MMP3 и остеопонтин являются диагностическими биомаркерами тяжести заболевания РА с чувствительностью 88,9% и специфичностью 68,4% и связаны со многими характеристиками заболевания.

rheumatoid arthritisinflammationneural network analysisstromelysin-1ACPAosteopontinревматоидный артритвоспалениенейросетевой анализстромелизин-1ACPAостеопонтинAl-Hakeim H.K., Moustafa S.R., Jasem K.M. Serum cesium, rhenium, and rubidium in rheumatoid arthritis patients. Biol. Trace Elem. Res., 2019, vol. 189, no. 2, pp. 379–386. doi: 10.1007/s12011-018-1497-5Aletaha D., Neogi T., Silman A.J., Funovits J., Felson D.T., Bingham III CO, Birnbaum N.S., Burmester G.R., Bykerk V.P., Cohen M.D. 2010 rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum., 2010, vol. 62, no. 9, pp. 2569–2581. doi: 10.1136/ard.2010.138461Anandarajah A.P. Clinical aspects of rheumatoid arthritis: highlights from the 2010 ACR conference. Int. J. Clin. Rheumatol, 2011, vol. 6, no. 3: 267. doi: 10.2217/IJR.11.39Boumiza S., Chahed K., Tabka Z., Jacob M.-P., Norel X., Ozen G. MMPs and TIMPs levels are correlated with anthropometric parameters, blood pressure, and endothelial function in obesity. Scientific Reports, 2021, vol. 11, no. 1: 20052. doi: 10.1038/s41598-021-99577-2Cessak G., Kuzawinska O., Burda A., Lis K., Wojnar M., Mirowska-Guzel D., Balkowiec-Iskra E. TNF inhibitors — mechanisms of action, approved and off-label indications. Pharmacol. Rep., 2014, vol. 66, no. 5, pp. 836–844. doi: 10.1016/j.pharep.2014.05.004Chen G., Zhang X., Li R., Fang L., Niu X., Zheng Y., He D., Xu R., Zhang J.Z. Role of osteopontin in synovial Th17 differentiation in rheumatoid arthritis. Arthritis Rheum., 2010, vol. 62, no. 10, pp. 2900–2908. doi: 10.1002/art.27603Chen J.J., Huang J.F., Du W.X., Tong P.J. Expression and significance of MMP3 in synovium of knee joint at different stage in osteoarthritis patients. Asian Pac. J. Trop. Med., 2014, vol. 7, no. 4, pp. 297–300. doi: 10.1016/S1995-7645(14)60042-0Cohen J., Cohen P., West S.G., Aiken L.S. Applied multiple regression/correlation analysis for the behavioral sciences; 3rd edition. Taylor and Francis, 2013, 536 p.Cornec D., Varache S., Morvan J., Devauchelle-Pensec V., Berthelot J.M., Le Henaff-Bourhis C., Hoang S., Martin A., Chalès G., Jousse-Joulin S., Saraux A. Comparison of ACR 1987 and ACR/EULAR 2010 criteria for predicting a 10-year diagnosis of rheumatoid arthritis. Joint Bone Spine, 2012, vol. 79, no. 6, pp. 581–585. doi: 10.1016/j.jbspin.2012.01.015Fadda S., Abolkheir E., Afifi R., Gamal M. Serum matrix metalloproteinase-3 in rheumatoid arthritis patients: Correlation with disease activity and joint destruction. Egyptian Rheumatol., 2016, vol. 38, no. 3, pp. 153–159. doi: 10.1016/j.ejr.2016.01.001Fahim N.K., Negida A., Fahim A.K. Sample Size Calculation Guide — Part 3: How to calculate the sample size for an independent case-control study. Adv. J. Emerg. Med., 2019, vol. 3, no. 2: e20. doi: 10.22114/AJEM.v0i0.138Fane M.E., Ecker B.L., Kaur A., Marino G.E., Alicea G.M., Douglass S.M., Chhabra Y., Webster M.R., Marshall A., Colling R., Espinosa O., Coupe N., Maroo N., Campo L., Middleton M.R., Corrie P., Xu X., Karakousis G.C., Weeraratna A.T. sFRP2 supersedes VEGF as an age-related driver of angiogenesis in melanoma, affecting response to anti-VEGF therapy in older patients. Clin. Cancer. Res., 2020, vol. 26, no. 21, pp. 5709–5719. doi: 10.1158/1078-0432.CCR-20-0446Forootanfar H., Adeli-Sardou M., Nikkhoo M., Mehrabani M., Amir-Heidari B., Shahverdi A.R., Shakibaie M. Antioxidant and cytotoxic effect of biologically synthesized selenium nanoparticles in comparison to selenium dioxide. J. Trace Elem. Med. Biol., 2014, vol. 28, no. 1, pp. 75–79. doi: 10.1016/j.jtemb.2013.07.005Giannini D., Antonucci M., Petrelli F., Bilia S., Alunno A., Puxeddu I. One year in review 2020: pathogenesis of rheumatoid arthritis. Clin. Exp. Rheumatol., 2020, vol. 38, no. 3, pp. 387–397.Gravallese E.M. Osteopontin: a bridge between bone and the immune system. J. Clin. Invest., 2003, vol. 112, no. 2, pp. 147–149. doi: 10.1172/JCI19190Guo X., Wang S., Godwood A., Close D., Ryan P.C., Roskos L.K., White W.I. Pharmacodynamic biomarkers and differential effects of TNF- and GM-CSF-targeting biologics in rheumatoid arthritis. Int. J. Rheum. Dis., 2019, vol. 22, no. 4, pp. 646–653. doi: 10.1111/1756-185X.13395Hattori Y., Kida D., Kaneko A. Normal serum matrix metalloproteinase-3 levels can be used to predict clinical remission and normal physical function in patients with rheumatoid arthritis. Clin. Rheumatol., 2019, vol. 38, no. 1, pp. 181–187. doi: 10.1007/s10067-017-3829-9Horton M.A., Nesbit M.A., Helfrich M.H. Interaction of osteopontin with osteoclast integrins. Ann. NY Acad. Sci., 1995, vol. 760, pp. 190–200. doi: 10.1111/j.1749-6632.1995.tb44630.xHueber A.J., Asquith D.L., Miller A.M., Reilly J., Kerr S., Leipe J., Melendez A.J., McInnes I.B. Cutting edge: mast cells express IL-17A in rheumatoid arthritis synovium. J. Immunol., 2010, vol. 184, no. 7, pp. 3336–3340. doi: 10.4049/jimmunol.0903566Iwadate H., Kobayashi H., Kanno T., Asano T., Saito R., Sato S., Suzuki E., Watanabe H., Ohira H. Plasma osteopontin is correlated with bone resorption markers in rheumatoid arthritis patients. Int. J. Rheum. Dis., 2014, vol. 17, no. 1, pp. 50–56. doi: 10.1111/1756-185X.12115Kariuki S.N., Moore J.G., Kirou K.A., Crow M.K., Utset T.O., Niewold T.B. Age- and gender-specific modulation of serum osteopontin and interferon-alpha by osteopontin genotype in systemic lupus erythematosus. Genes Immun., 2009, vol. 10, no. 5, pp. 487–494. doi: 10.1038/gene.2009.15.Kim H.R., Kim K.W., Kim B.M., Cho M.L., Lee S.H. The effect of vascular endothelial growth factor on osteoclastogenesis in rheumatoid arthritis. PLoS One, 2015, vol. 10, no. 4: e0124909. doi: 10.1371/journal.pone.0124909Klimiuk P.A., Domysławska I., Sierakowski S., Chwiećko J. Regulation of serum matrix metalloproteinases and tissue inhibitor of metalloproteinases-1 following rituximab therapy in patients with rheumatoid arthritis refractory to anti-tumor necrosis factor blockers. Rheumatol. Int., 2015, vol. 35, no. 4, pp. 749–755. doi: 10.1007/s00296-014-3112-1Lee Y.H., Bae S.C. Correlation between circulating VEGF levels and disease activity in rheumatoid arthritis: a meta-analysis. Z. Rheumatol., 2018, vol. 77, no. 3, pp. 240–248. doi: 10.1007/s00393-016-0229-5Lerner A., Neidhofer S., Reuter S., Matthias T. MMP3 is a reliable marker for disease activity, radiological monitoring, disease outcome predictability, and therapeutic response in rheumatoid arthritis. Best Pract. Res. Clin. Rheumatol., 2018, vol. 32, no. 4, pp. 550–562. doi: 10.1016/j.berh.2019.01.006Li L., Cai B., Liao J., Yang B., Huang Z., Wang L. [Clinical value of serum matrix metalloproteinase-3 in evaluating joint destruction and therapeutic effect in rheumatoid arthritis patients]. Xi Bao Yu Fen Zi Mian Yi Xue Za Zhi, 2013, vol. 29, no. 9, pp. 966–969.Liu M.K., Wang L.C., Hu F.L. [Value of serum matrix metalloproteinase 3 in the assessment of early rheumatoid arthritis]. Beijing Da Xue Xue Bao Yi Xue Ban, 2018, vol. 50, no. 6, pp. 981–985.Ma J.-D., Zhou J.-J., Zheng D.-H., Chen L.-F., Mo Y.-Q., Wei X.-N., Yang L.-J., Dai L. Serum matrix metalloproteinase-3 as a noninvasive biomarker of histological synovitis for diagnosis of rheumatoid arthritis. Mediat. Inflamm., 2014, vol. 2014: 179284. doi: 10.1155/2014/179284Ma J., Wang X., Mo Y., Chen L., Zheng D., Wei X., Dai L. [Value of serum matrix metalloproteinase-3 in the assessment of active disease in patients with rheumatoid arthritis]. Zhonghua Yi Xue Za Zhi, 2015, vol. 95, no. 47, pp. 3823–3828.Ma M.J., Liu H.C., Qu X.Q., Wang J.L. Matrix metalloproteinase-3 gene polymorphism and its mRNA expression in rheumatoid arthritis. Genet. Mol. Res., 2015, vol. 14, no. 4, pp. 15652–9. doi: 10.4238/2015.December.1.17Malemud C.J. Growth hormone, VEGF and FGF: involvement in rheumatoid arthritis. Clin. Chim. Acta, 2007, vol. 375, no. 1–2, pp. 10–19. doi: 10.1016/j.cca.2006.06.033Mamehara A., Sugimoto T., Sugiyama D., Morinobu S., Tsuji G., Kawano S., Morinobu A., Kumagai S. Serum matrix metalloproteinase-3 as predictor of joint destruction in rheumatoid arthritis, treated with non-biological disease modifying anti-rheumatic drugs. Kobe J. Med. Sci., 2010, vol. 56, no. 3, pp. E98–107.Mateen S., Zafar A., Moin S., Khan A.Q., Zubair S. Understanding the role of cytokines in the pathogenesis of rheumatoid arthritis. Clin. Chim. Acta, 2016, vol. 455, pp. 161–171. doi: 10.1016/j.cca.2016.02.010Miossec P. Rheumatoid arthritis: still a chronic disease. Lancet, 2013, vol. 381, no. 9870, pp. 884–886. doi: 10.1016/S0140-6736(12)62192-8Mohammed Ali D.M., Al-Fadhel S.Z., Al-Ghuraibawi NHA, Al-Hakeim H.K. Serum chemerin and visfatin levels and their ratio as possible diagnostic parameters of rheumatoid arthritis. Reumatologia, 2020, vol. 58, no. 2, pp. 67–75. doi: 10.5114/reum.2020.95359Mu N., Gu J.T., Huang T.L., Liu N.N., Chen H., Bu X., Zheng Z.H., Jia B., Liu J., Wang B.L., Wang Y.M., Zhu Z.F., Zhang Y., Zhang Y.Q., Xue X.C., Li M., Zhang W. Blockade of discoidin domain receptor 2 as a strategy for reducing inflammation and joint destruction in rheumatoid arthritis via altered interleukin-15 and dkk-1 signaling in fibroblast-like synoviocytes. Arthritis Rheumatol., 2020, vol. 72, no. 6, pp. 943–956. doi: 10.1002/art.41205Ohshima S., Yamaguchi N., Nishioka K., Mima T., Ishii T., Umeshita-Sasai M., Kobayashi H., Shimizu M., Katada Y., Wakitani S., Murata N., Nomura S., Matsuno H., Katayama R., Kon S., Inobe M., Uede T., Kawase I., Saeki Y. Enhanced local production of osteopontin in rheumatoid joints. J. Rheumatol., 2002, vol. 29, no. 10, pp. 2061–2067.Orr C., Najm A., Biniecka M., McGarry T., Ng C.T., Young F., Fearon U., Veale D.J. Synovial immunophenotype and anti-citrullinated peptide antibodies in rheumatoid arthritis patients: relationship to treatment response and radiologic prognosis. Arthritis Rheum., 2017, vol. 69, no. 11, pp. 2114–2123. doi: 10.1002/art.40218Page-McCaw A., Ewald A.J., Werb Z. Matrix metalloproteinases and the regulation of tissue remodelling. Nat. Rev. Mol. Cell Biol., 2007, vol. 8, no. 3, pp. 221–233. doi: 10.1038/nrm2125Rakieh C., Nam J.L., Hunt L., Hensor E.M., Das S., Bissell L.A., Villeneuve E., McGonagle D., Hodgson R., Grainger A., Wakefield R.J., Conaghan P.G., Emery P. Predicting the development of clinical arthritis in anti-CCP positive individuals with non-specific musculoskeletal symptoms: a prospective observational cohort study. Ann. Rheum. Dis., 2015, vol. 74, no. 9, pp. 1659–1666. doi: 10.1136/annrheumdis-2014-205227Ribbens C., Martin y Porras M., Franchimont N., Kaiser M.J., Jaspar J.M., Damas P., Houssiau F.A., Malaise M.G. Increased matrix metalloproteinase-3 serum levels in rheumatic diseases: relationship with synovitis and steroid treatment. Ann. Rheum. Dis., 2002, vol. 61, no. 2, pp. 161–166. doi: 10.1136/ard.61.2.161Sasaki S., Iwata H., Ishiguro N., Obata K., Miura T. Detection of stromelysin in synovial fluid and serum from patients with rheumatoid arthritis and osteoarthritis. Clin. Rheumatol., 1994, vol. 13, no. 2, pp. 228–233. doi: 10.1007/BF02249017Schuerwegh A.J., Ioan-Facsinay A., Dorjee A.L., Roos J., Bajema I.M., van der Voort E.I., Huizinga T.W., Toes R.E. Evidence for a functional role of IgE anticitrullinated protein antibodies in rheumatoid arthritis. Proc. Natl Acad. Sci. USA, 2010, vol. 107, no. 6, pp. 2586–2591. doi: 10.1073/pnas.0913054107Sponholtz T.R., Zhang X., Fontes J.D., Meigs J.B., Cupples L.A., Kiel D.P., Hannan M.T., McLean R.R. Association between inflammatory biomarkers and bone mineral density in a community-based cohort of men and women. Arthritis Care Res. (Hoboken), 2014, vol. 66, no. 8, pp. 1233–1240. doi: 10.1002/acr.22270Sun S., Bay-Jensen A.-C., Karsdal M.A., Siebuhr A.S., Zheng Q., Maksymowych W.P., Christiansen T.G., Henriksen K. The active form of MMP-3 is a marker of synovial inflammation and cartilage turnover in inflammatory joint diseases. BMC Musculoskelet. Disord., 2014, vol. 15, no. 93, pp. 1–12. doi: 10.1186/1471-2474-15-93Tetlow L.C., Lees M., Ogata Y., Nagase H., Woolley D.E. Differential expression of gelatinase B (MMP-9) and stromelysin-1 (MMP-3) by rheumatoid synovial cells in vitro and in vivo. Rheumatol. Int., 1993, vol. 13, no. 2, pp. 53–59. doi: 10.1007/BF00307734Tokai N., Yoshida S., Kotani T., Yoshikawa A., Kimura Y., Fujiki Y., Matsumura Y., Takeuchi T., Makino S., Arawaka S. Serum matrix metalloproteinase 3 levels are associated with an effect of iguratimod as add-on therapy to biological DMARDs in patients with rheumatoid arthritis. PLoS One, 2018, vol. 13, no. 8: e0202601. doi: 10.1371/journal.pone.0202601Tuncer T., Kaya A., Gulkesen A., Kal G.A., Kaman D., Akgol G. Matrix metalloproteinase-3 levels in relation to disease activity and radiological progression in rheumatoid arthritis. Adv. Clin. Exp. Med., 2019, vol. 28, no. 5, pp. 665–670. doi: 10.17219/acem/94065Uemura Y., Hayashi H., Takahashi T., Saitho T., Umeda R., Ichise Y., Sendo S., Tsuji G., Kumagai S. [MMP-3 as a biomarker of disease activity of rheumatoid arthritis]. Rinsho Byori, 2015, vol. 63, no. 12, pp. 1357–1364.Umeda N., Matsumoto I., Sumida T. [The pathogenic role of ACPA in rheumatoid arthritis]. Nihon Rinsho Meneki Gakkai Kaishi, 2017, vol. 40, no. 6, pp. 391–395. doi: 10.2177/jsci.40.391Van de Stadt L.A., de Koning M.H., van de Stadt R.J., Wolbink G., Dijkmans B.A., Hamann D., van Schaardenburg D. Development of the anti-citrullinated protein antibody repertoire prior to the onset of rheumatoid arthritis. Arthritis Rheum., 2011, vol. 63, no. 11, pp. 3226–3233. doi: 10.1002/art.30537Van Riel P., Renskers L. The Disease Activity Score (DAS) and the Disease Activity Score using 28 joint counts (DAS28) in the management of rheumatoid arthritis. Clin. Exp. Rheumatol., 2016, vol. 34, no. 5 (suppl. 101), pp. S4–S40.Vasilev G., Manolova I., Ivanova M., Stanilov I., Miteva L., Stanilova S. The role of IL-18 in addition to Th17 cytokines in rheumatoid arthritis development and treatment in women. Sci. Rep., 2021, vol. 11, no. 1: 15391. doi: 10.1038/s41598-021-94841-xVickers N.J. Animal communication: when i’m calling you, will you answer too? Curr. Biol., 2017, vol. 27, no. 14, pp. R713–R715. doi: 10.1016/j.cub.2017.05.064Wasserman A. Rheumatoid arthritis: common questions about diagnosis and management. Am. Fam. Physician., 2018, vol. 97, no. 7, pp. 455–462.Wijbrandts C.A., Vergunst C.E., Haringman J.J., Gerlag D.M., Smeets T.J., Tak P.P. Absence of changes in the number of synovial sublining macrophages after ineffective treatment for rheumatoid arthritis: implications for use of synovial sublining macrophages as a biomarker. Arthritis Rheumatol., 2007, vol. 56, no. 11, pp. 3869–3871. doi: 10.1002/art.22964Wu J., Li Q., Deng J., Zhao J.J., Yu Q.H. Association between IL-33 and other inflammatory factors in patients with rheumatoid arthritis and in fibroblast-like synoviocytes in vitro. Exp. Ther. Med., 2021, vol. 21, no. 2: 161. doi: 10.3892/etm.2020.9592Xu J., Feng Z., Chen S., Zhu J., Wu X., Chen X., Li J. Taxol alleviates collagen-induced arthritis in mice by inhibiting the formation of microvessels. Clin. Rheumatol., 2019, vol. 38, no. 1, pp. 19–27 doi: 10.1007/s10067-017-3646-1Yoshihara Y., Obata Ki, Fujimot N., Yamashita K., Hayakawa T., Shimmei M. Increased levels of stromelysin-1 and tissue inhibitor of metalloproteinases-1 in sera from patients with rheumatoid arthritis. Arthritis Rheumatol., 1995, vol. 38, no. 7, pp. 969–975. doi: 10.1002/art.1780380713Yumoto K., Ishijima M., Rittling S.R., Tsuji K., Tsuchiya Y., Kon S., Nifuji A., Uede T., Denhardt D.T., Noda M. Osteopontin deficiency protects joints against destruction in anti-type II collagen antibody-induced arthritis in mice. Proc. Natl Acad. Sci. USA, 2002, vol. 99, no. 7, pp. 4556–4561. doi: 10.1073/pnas.052523599Zhang F.-J., Gao S.-G., Cheng L., Tian J., Xu W.-S., Luo W., Song Y., Yang Y., Lei G.-H. The effect of hyaluronic acid on osteopontin and CD44 mRNA of fibroblast-like synoviocytes in patients with osteoarthritis of the knee. Rheumatol Int., 2013, vol. 33, no. 1, pp. 79–83. doi: 10.1007/s00296-011-2339-3Zhang F., Luo W., Li Y., Gao S., Lei G. Role of osteopontin in rheumatoid arthritis. Rheumatol. Int., 2015, vol. 35, no. 4, pp. 589–595. doi: 10.1007/s00296-014-3122-zZheng W., Li R., Pan H., He D., Xu R., Guo T.B., Guo Y., Zhang J.Z. Role of osteopontin in induction of monocyte chemoattractant protein 1 and macrophage inflammatory protein 1β through the NF-κB and MAPK pathways in rheumatoid arthritis. Arthritis Rheum., 2009, vol. 60, no. 7, pp. 1957–1965. doi: 10.1002/art.24625