Dynamic changes in radiological parameters, immune cells, selected miRNAs, and cytokine levels in peripheral blood of patients with severe COVID‑19

Bukreieva,Tetiana; Bukreieva,Tetiana; Kyryk,Vitalii; Kyryk,Vitalii; Nikulina,Viktoriia; Nikulina,Viktoriia; Svitina,Hanna; Svitina,Hanna; Vega,Alyona; Vega,Alyona; Chybisov,Oleksii; Chybisov,Oleksii; Shablii,Iuliia; Shablii,Iuliia; Mankovska,Oksana; Mankovska,Oksana; Lobyntseva,Galyna; Lobyntseva,Galyna; Nemtinov,Petro; Nemtinov,Petro; Skrypkina,Inessa; Skrypkina,Inessa; Shablii,Volodymyr; Shablii,Volodymyr

doi:10.3892/br.2023.1615

Dynamic changes in radiological parameters, immune cells, selected miRNAs, and cytokine levels in peripheral blood of patients with severe COVID‑19

Authors:
- Tetiana Bukreieva
- Vitalii Kyryk
- Viktoriia Nikulina
- Hanna Svitina
- Alyona Vega
- Oleksii Chybisov
- Iuliia Shablii
- Oksana Mankovska
- Galyna Lobyntseva
- Petro Nemtinov
- Inessa Skrypkina
- Volodymyr Shablii
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Affiliations: Laboratory of Biosynthesis of Nucleic Acids, Department of Functional Genomics, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv 03143, Ukraine, Laboratory of Cell and Tissue Cultures, Department of Cell and Tissue Technologies, State Institute of Genetic and Regenerative Medicine, National Academy of Medical Sciences of Ukraine, Kyiv 04114, Ukraine, Placenta Stem Cell Laboratory, Cryobank, Institute of Cell Therapy, Kyiv 03126, Ukraine, Department of Infectious Diseases, Shupyk National Healthcare University of Ukraine, Kyiv 04112, Ukraine, Endoscopic Unit, CNE Kyiv City Clinical Hospital No. 4, Kyiv 03110, Ukraine, Department of Molecular Oncogenetics, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv 03143, Ukraine
Published online on: March 21, 2023 https://doi.org/10.3892/br.2023.1615
Article Number: 33
Copyright : © Bukreieva et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].

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Abstract

The present study aimed to investigate the dynamic changes in peripheral blood leucocyte subpopulations, cytokine and miRNA levels, and changes in computed tomography (CT) scores in patients with severe coronavirus disease 2019 (COVID‑19) (n=14) and age‑matched non‑COVID‑19 volunteers (n=17), which were included as a reference control group. All data were collected on the day of patient admission (day 0) and on the 7th, 14th and 28th days of follow‑up while CT of the lungs was performed on weeks 2, 8, 24 and 48. On day 0, lymphopenia and leucopenia were detected in most patients with COVID‑19, as well as an increase in the percentage of banded neutrophils, B cells, and CD4⁺ Treg cells, and a decrease in the content of PD‑1^low T cells, classical, plasmacytoid, and regulatory dendritic cells. On day 7, the percentage of T and natural killer cells decreased with a concurrent increase in B cells, but returned to the initial level after treatment discharge. The content of different T and dendritic cell subsets among CD45⁺ cells increased during two weeks and remained elevated, suggesting the activation of an adaptive immune response. The increase of PD‑1‑positive subpopulations of T and non‑T cells and regulatory CD4 T cells in patients with COVID‑19 during the observation period suggests the development of an inflammation control mechanism. The levels of interferon γ‑induced protein 10 (IP‑10), tumor necrosis factor‑α (TNF‑α) and interleukin (IL)‑6 decreased on day 7, but increased again on days 14 and 28. C‑reactive protein and granulocyte colony‑stimulating factor (G‑CSF) levels decreased gradually throughout the observation period. The relative expression levels of microRNA (miR)‑21‑5p, miR‑221‑3p, miR‑27a‑3p, miR‑146a‑5p, miR‑133a‑3p, and miR‑126‑3p were significantly higher at the beginning of hospitalization compared to non‑COVID‑19 volunteers. The plasma levels of all miRs, except for miR‑126‑3p, normalized within one week of treatment. At week 48, CT scores were most prominently correlated with the content of lymphocytes, senescent memory T cells, CD127⁺ T cells and CD57⁺ T cells, and increased concentrations of G‑CSF, IP‑10, and macrophage inflammatory protein‑1α.

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1	Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, Villamizar-Peña R, Holguin-Rivera Y, Escalera-Antezana JP, Alvarado-Arnez LE, Bonilla-Aldana DK, Franco-Paredes C, Henao-Martinez AF, et al: Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis. 34(101623)2020.PubMed/NCBI View Article : Google Scholar
2	Ye Q, Wang B and Mao J: The pathogenesis and treatment of the ‘Cytokine Storm’ in COVID-19. J Infect. 80:607–613. 2020.PubMed/NCBI View Article : Google Scholar
3	Chousterman BG, Swirski FK and Weber GF: Cytokine storm and sepsis disease pathogenesis. Semin Immunopathol. 39:517–528. 2017.PubMed/NCBI View Article : Google Scholar
4	Islam MT, Nasiruddin M, Khan IN, Mishra SK, Kudrat-E-Zahan M, Riaz TA, Ali ES, Rahman MS, Mubarak MS, Martorell M, et al: A perspective on emerging therapeutic interventions for COVID-19. Front Public Health. 8(281)2020.PubMed/NCBI View Article : Google Scholar
5	Puneet P, Moochhala S and Bhatia M: Chemokines in acute respiratory distress syndrome. Am J Physiol Lung Cell Mol Physiol. 288:L3–L15. 2005.PubMed/NCBI View Article : Google Scholar
6	Bhatia M, Zemans RL and Jeyaseelan S: Role of chemokines in the pathogenesis of acute lung injury. Am J Respir Cell Mol Biol. 46:566–572. 2012.PubMed/NCBI View Article : Google Scholar
7	Tomashefski JF Jr: Pulmonary pathology of acute respiratory distress syndrome. Clin Chest Med. 21:435–466. 2000.PubMed/NCBI View Article : Google Scholar
8	Lyu P, Liu X, Zhang R, Shi L and Gao J: The performance of chest CT in evaluating the clinical severity of COVID-19 pneumonia: Identifying critical cases based on CT characteristics. Invest Radiol. 55:412–421. 2020.PubMed/NCBI View Article : Google Scholar
9	Zhao W, Zhong Z, Xie X, Yu Q and Liu J: Relation between chest CT findings and clinical conditions of coronavirus disease (COVID-19) pneumonia: A multicenter study. AJR Am J Roentgenol. 214:1072–1077. 2020.PubMed/NCBI View Article : Google Scholar
10	Wu J, Wu X, Zeng W, Guo D, Fang Z, Chen L, Huang H and Li C: Chest CT findings in patients with coronavirus disease 2019 and its relationship with clinical features. Invest Radiol. 55:257–261. 2020.PubMed/NCBI View Article : Google Scholar
11	Alon R, Sportiello M, Kozlovski S, Kumar A, Reilly EC, Zarbock A, Garbi N and Topham DJ: Leukocyte trafficking to the lungs and beyond: Lessons from influenza for COVID-19. Nat Rev Immunol. 21:49–64. 2020.PubMed/NCBI View Article : Google Scholar
12	Zemans RL, Colgan SP and Downey GP: Transepithelial migration of neutrophils: Mechanisms and implications for acute lung injury. Am J Respir Cell Mol Biol. 40:519–535. 2009.PubMed/NCBI View Article : Google Scholar
13	Zhang L, Yan X, Fan Q, Liu H, Liu X, Liu Z and Zhang Z: D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19. J Thromb Haemost. 18:1324–1329. 2020.PubMed/NCBI View Article : Google Scholar
14	Li H, Xiang X, Ren H, Xu L, Zhao L, Chen X, Long H, Wang Q and Wu Q: Serum amyloid A is a biomarker of severe Coronavirus disease and poor prognosis. J Infect. 80:646–655. 2020.PubMed/NCBI View Article : Google Scholar
15	Gao L, Jiang D, Wen XS, Cheng XC, Sun M, He B, You LN, Lei P, Tan XW, Qin S, et al: Prognostic value of NT-proBNP in patients with severe COVID-19. Respir Res. 21(83)2020.PubMed/NCBI View Article : Google Scholar
16	Al Balushi A, Al Shekaili J, Al Kindi M, Ansari Z, Al-Khabori M, Khamis F, Ambusaidi Z, Al Balushi A, Al Huraizi A, Al Sulaimi S, et al: Immunological predictors of disease severity in patients with COVID-19. Int J Inf Dis. 110:83–92. 2021.PubMed/NCBI View Article : Google Scholar
17	Sidiropoulou P, Docea AO, Nikolaou V, Katsarou MS, Spandidos DA, Tsatsakis A, Calina D and Drakoulis N: Unraveling the roles of vitamin D status and melanin during COVID-19 (Review). Int J Mol Med. 47:92–100. 2021.PubMed/NCBI View Article : Google Scholar
18	Hussain T, Zhao D, Shah SZA, Wang J, Yue R, Liao Y, Sabir N, Yang L and Zhou X: MicroRNA 27a-3p regulates antimicrobial responses of murine macrophages infected by mycobacterium avium subspecies paratuberculosis by targeting interleukin-10 and TGF-β-activated protein kinase 1 binding protein 2. Front Immunol. 11(1915)2018.PubMed/NCBI View Article : Google Scholar
19	de Gonzalo-Calvo D, Benitez ID, Pinilla L, Carratala A, Moncusi-Moix ANNA, Gort-Paniello C, Molinero M, González J, Torres G, Bernal M, et al: Circulating microRNA profiles predict the severity of COVID-19 in hospitalized patients. Transl Res. 236:147–159. 2021.PubMed/NCBI View Article : Google Scholar
20	Lev S, Gottesman T, Levin GS, Lederfein D, Berkov E, Diker D, Zaidman A, Nutman A, Ber AI, Angel A, et al: Observational cohort study of IP-10's potential as a biomarker to aid in inflammation regulation within a clinical decision support protocol for patients with severe COVID-19. PLoS One. 16(e0245296)2021.PubMed/NCBI View Article : Google Scholar
21	Iannetta M, Buccisano F, Fraboni D, Malagnino V, Campogiani L, Teti E, Spalliera I, Rossi B, Di Lorenzo A, Palmieri R, et al: Baseline T-lymphocyte subset absolute counts can predict both outcome and severity in SARS-CoV-2 infected patients: A single center study. Sci Rep. 11(12762)2021.PubMed/NCBI View Article : Google Scholar
22	Deng R, Wang C, Ye Y, Gou L, Fu Z, Ye B, Shao F, Zhang X, Fu W, Xiao J, et al: Clinical manifestations of blood cell parameters and inflammatory factors in 92 patients with COVID-19. Ann Transl Med. 9(62)2021.PubMed/NCBI View Article : Google Scholar
23	Shi H, Wang W, Yin J, Ouyang Y, Pang L, Feng Y, Qiao L, Guo X, Shi H, Jin R and Chen D: The inhibition of IL-2/IL-2R gives rise to CD8 + T cell and lymphocyte decrease through JAK1-STAT5 in critical patients with COVID-19 pneumonia. Cell Death Dis. 11(429)2020.PubMed/NCBI View Article : Google Scholar
24	Liao M, Liu Y, Yuan J, Wen Y, Xu G, Zhao J, Cheng L, Li J, Wang X, Wang F, et al: Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19. Nat Med. 26:842–844. 2020.PubMed/NCBI View Article : Google Scholar
25	Clinical management of severe acute respiratory infection when novel coronavirus (nCoV) infection is suspected [Internet]. [cited 2021 Jul 25]. Available from: https://www.who.int/publications/i/item/10665-332299.
26	Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 25:402–408. 2001.PubMed/NCBI View Article : Google Scholar
27	Büttner L, Aigner A, Fleckenstein FN, Hamper CM, Jonczyk M, Hamm B, Scholz O and Böning G: Diagnostic value of initial chest CT findings for the need of ICU treatment/intubation in patients with COVID-19. Diagnostics (Basel). 10(929)2020.PubMed/NCBI View Article : Google Scholar
28	Liu J, Li S, Liu J, Liang B, Wang X, Wang H, Li W, Tong Q, Yi J, Zhao L, et al: Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients. EBioMedicine. 55(102763)2020.PubMed/NCBI View Article : Google Scholar
29	Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, et al: Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 395:497–506. 2020.PubMed/NCBI View Article : Google Scholar
30	Lax SF, Skok K, Zechner P, Kessler HH, Kaufmann N, Koelblinger C, Vander K, Bargfrieder U and Trauner M: Pulmonary arterial thrombosis in COVID-19 with fatal outcome: Results from a prospective, single-center, clinicopathologic case series. Ann Intern Med. 173:350–361. 2020.PubMed/NCBI View Article : Google Scholar
31	Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, Liu S, Zhao P, Liu H, Zhu L, et al: Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 8:420–422. 2020.PubMed/NCBI View Article : Google Scholar
32	Marté JL, Toney NJ, Cordes L, Schlom J, Donahue RN and Gulley JL: Original research: Early changes in immune cell subsets with corticosteroids in patients with solid tumors: Implications for COVID-19 management. J Immunother Cancer. 8(e001019)2020.PubMed/NCBI View Article : Google Scholar
33	Abdin SM, Elgendy SM, Alyammahi SK, Alhamad DW and Omar HA: Tackling the cytokine storm in COVID-19, challenges and hopes. Life Sci. 257(118054)2020.PubMed/NCBI View Article : Google Scholar
34	Tomić S, Đokić J, Stevanović D, Ilić N, Gruden-Movsesijan A, Dinić M, Radojević D, Bekić M, Mitrović N, Tomašević R, et al: Reduced expression of autophagy markers and expansion of myeloid-derived suppressor cells correlate with poor T cell response in severe COVID-19 patients. Front Immunol. 22(614599)2021.PubMed/NCBI View Article : Google Scholar
35	Deng Z, Zhang M, Zhu T, Zhili N, Liu Z, Xiang R, Zhang W and Xu Y: Dynamic changes in peripheral blood lymphocyte subsets in adult patients with COVID-19. Int J Infect Dis. 98:353–358. 2020.PubMed/NCBI View Article : Google Scholar
36	Riley JL: PD-1 signaling in primary T cells. Immunol Rev. 229:114–125. 2009.PubMed/NCBI View Article : Google Scholar
37	Pyzik A, Grywalska E, Matyjaszek-Matuszek B, Smoleń A, Pyzik D and Roliński J: Frequencies of PD-1-positive T CD3+CD4+, T CD3+CD8+ and B CD19+ lymphocytes in female patients with Graves' disease and healthy controls-preliminary study. Mol Cell Endocrinol. 448:28–33. 2017.PubMed/NCBI View Article : Google Scholar
38	Nascimbeni M, Shin EC, Chiriboga L, Kleiner DE and Rehermann B: Peripheral CD4(+)CD8(+) T cells are differentiated effector memory cells with antiviral functions. Blood. 104:478–486. 2004.PubMed/NCBI View Article : Google Scholar
39	Overgaard NH, Jung JW, Steptoe RJ and Wells JW: CD4+/CD8+ double-positive T cells: More than just a developmental stage? J Leukoc Biol. 97:31–38. 2015.PubMed/NCBI View Article : Google Scholar
40	Yang X, Dai T, Zhou X, Qian H, Guo R, Lei L, Zhang X, Zhang D, Shi L, Cheng Y, et al: Naturally activated adaptive immunity in COVID-19 patients. J Cell Mol Med. 24:12457–12463. 2020.PubMed/NCBI View Article : Google Scholar
41	Kalfaoglu B, Almeida-Santos J, Tye CA, Satou Y and Ono M: T-cell hyperactivation and paralysis in severe COVID-19 infection revealed by single-cell analysis. Front Immunol. 11(589380)2020.PubMed/NCBI View Article : Google Scholar
42	Chen X, Huang J, Huang Y, Chen J, Huang Y, Jiang X and Shi Y: Characteristics of immune cells and cytokines in patients with coronavirus disease 2019 in Guangzhou, China. Hum Immunol. 81:702–708. 2020.PubMed/NCBI View Article : Google Scholar
43	Neidleman J, Luo X, Frouard J, Xie G, Gill G, Stein ES, McGregor M, Ma T, George AF, Kosters A, et al: SARS-CoV-2-Specific T cells exhibit phenotypic features of helper function, lack of terminal differentiation, and high proliferation potential. Cell Rep Med. 1(1000081)2020.PubMed/NCBI View Article : Google Scholar
44	Wang W, Xiang HP, Wang HP, Zhu LX and Geng XP: CD4 + CD25 + CD127 high cells as a negative predictor of multiple organ failure in acute pancreatitis. World J Emerg Surg. 12(7)2017.PubMed/NCBI View Article : Google Scholar
45	Kalfaoglu B, Almeida-Santos J, Tye CA, Satou Y and Ono M: T-cell dysregulation in COVID-19. Biochem Biophys Res Commun. 538:204–210. 2021.PubMed/NCBI View Article : Google Scholar
46	Hanna SJ, Codd AS, Gea-Mallorqui E, Scourfield DO, Richter FC, Ladell K, Borsa M, Compeer EB, Moon OR, Galloway SAE, et al: T cell phenotypes in COVID-19-a living review. Oxf Open Immunol. 2(iqaa007)2021.PubMed/NCBI View Article : Google Scholar
47	Kusnadi A, Ramírez-Suástegui C, Fajardo V, Chee SJ, Meckiff BJ, Simon H, Pelosi E, Seumois G, Ay F, Vijayanand P and Ottensmeier CH: Severely ill COVID-19 patients display impaired exhaustion features in SARS-CoV-2-reactive CD8+ T cells. Sci Immunol. 6(eabe4782)2021.PubMed/NCBI View Article : Google Scholar
48	Peng Y, Mentzer AJ, Liu G, Yao X, Yin Z, Dong D, Dejnirattisai W, Rostron T, Supasa P, Liu C, et al: Broad and strong memory CD4+ and CD8+ T cells induced by SARS-CoV-2 in UK convalescent individuals following COVID-19. Nat Immunol. 21:1336–1345. 2020.PubMed/NCBI View Article : Google Scholar
49	Neagu M, Calina D, Docea AO, Constantin C, Filippini T, Vinceti M, Drakoulis N, Poulas K, Nikolouzakis TK, Spandidos DA and Tsatsakis A: Back to basics in COVID-19: Antigens and antibodies-completing the puzzle. J Cell Mol Med. 25:4523–4533. 2021.PubMed/NCBI View Article : Google Scholar
50	De Biasi S, Meschiari M, Gibellini L, Bellinazzi C, Borella R, Fidanza L, Gozzi L, Iannone A, Lo Tartaro D, Mattioli M, et al: Marked T cell activation, senescence, exhaustion and skewing towards TH17 in patients with COVID-19 pneumonia. Nat Commun. 11(3434)2020.PubMed/NCBI View Article : Google Scholar
51	Qin C, Zhou L, Hu Z, Zhang S, Yang S, Tao Y, Xie C, Ma K, Shang K, Wang W and Tian DS: Dysregulation of immune response in patients with COVID-19 in Wuhan, China. Clin Infect Dis. 71:762–768. 2020.PubMed/NCBI View Article : Google Scholar
52	Wang F, Hou H, Luo Y, Tang G, Wu S, Huang M, Liu W, Zhu Y, Lin Q, Mao L, et al: The laboratory tests and host immunity of COVID-19 patients with different severity of illness. JCI Insight. 5(e137799)2020.PubMed/NCBI View Article : Google Scholar
53	Chen G, Wu D, Guo W, Cao Y, Huang D, Wang H, Wang T, Zhang X, Chen H, Yu H, et al: Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Invest. 130:2620–2629. 2020.PubMed/NCBI View Article : Google Scholar
54	Yang J, Zhang E, Zhong M, Yang Q, Hong K, Shu T, Zhou D, Xiang J, Xia J, Zhou X, et al: Longitudinal characteristics of t cell responses in asymptomatic SARS-CoV-2 infection. Virol Sin. 35:838–841. 2020.PubMed/NCBI View Article : Google Scholar
55	Sanchez-Cerrillo I, Landete P, Aldave B, Sanchez-Alonso S, Sanchez-Azofra A, Marcos-Jimenez A, Avalos E, Alcaraz-Serna A, de Los Santos I, Mateu-Albero T, et al: Differential redistribution of activated monocyte and dendritic cell subsets to the lung associates with severity of COVID-19. medRxiv. 2020(20100925)2020.PubMed/NCBI View Article : Google Scholar
56	Leng Z, Zhu R, Hou W, Feng Y, Yang Y, Han Q, Shan G, Meng F, Du D, Wang S, et al: Transplantation of ACE2- mesenchymal stem cells improves the outcome of patients with COVID-19 pneumonia. Aging Dis. 11:216–228. 2020.PubMed/NCBI View Article : Google Scholar
57	Fujita S, Seino KI and Sato K, Sato Y, Eizumi K, Yamashita N, Taniguchi M and Sato K: Regulatory dendritic cells act as regulators of acute lethal systemic inflammatory response. Blood. 107:3656–3664. 2006.PubMed/NCBI View Article : Google Scholar
58	Boor PPC, Metselaar HJ, Mancham S, Tilanus HW, Kusters JG and Kwekkeboom J: Prednisolone suppresses the function and promotes apoptosis of plasmacytoid dendritic cells. Am J Transplant. 6:2332–2341. 2006.PubMed/NCBI View Article : Google Scholar
59	Shin KS, Jeon I, Kim BS, Kim IK, Park YJ, Koh CH, Song B, Lee JM, Lim J, Bae EA, et al: Monocyte-derived dendritic cells dictate the memory differentiation of CD8+ T cells during acute infection. Front Immunol. 10(1887)2019.PubMed/NCBI View Article : Google Scholar
60	Calina D, Sarkar C, Arsene AL, Salehi B, Docea AO, Mondal M, Islam MT, Zali A and Sharifi-Rad J: Recent advances, approaches and challenges in targeting pathways for potential COVID-19 vaccines development. Immunol Res. 68:315–324. 2020.PubMed/NCBI View Article : Google Scholar
61	Aldridge JR Jr, Moseley CE, Boltz DA, Negovetich NJ, Reynolds C, Franks J, Brown SA, Doherty PC, Webster RG and Thomas PG: From the cover: TNF/iNOS-producing dendritic cells are the necessary evil of lethal influenza virus infection. Proc Natl Acad Sci USA. 106:5306–5311. 2009.PubMed/NCBI View Article : Google Scholar
62	Iijima N, Mattei LM and Iwasaki A: Recruited inflammatory monocytes stimulate antiviral Th1 immunity in infected tissue. Proc Natl Acad Sci USA. 108:284–289. 2011.PubMed/NCBI View Article : Google Scholar
63	Haroun RAH, Osman WH and Eessa AM: Interferon-γ-induced protein 10 (IP-10) and serum amyloid A (SAA) are excellent biomarkers for the prediction of COVID-19 progression and severity. Life Sci. 269(119019)2021.PubMed/NCBI View Article : Google Scholar
64	Wang G, Wu C, Zhang Q, Wu F, Yu B, Lv J, Li Y, Li T, Zhang S, Wu C, et al: C-reactive protein level may predict the risk of COVID-19 aggravation. Open Forum Infect Dis. 7(ofaa153)2020.PubMed/NCBI View Article : Google Scholar
65	Chen W, Zheng KI, Liu S, Yan Z, Xu C and Qiao Z: Plasma CRP level is positively associated with the severity of COVID-19. Ann Clin Microbiol Antimicrob. 19(18)2020.PubMed/NCBI View Article : Google Scholar
66	Mardani R, Namavar M, Ghorbi E, Shoja Z, Zali F, Kaghazian H, Aghasadeghi MR, Sadeghi SA, Sabeti S, Darazam IA, et al: Association between serum inflammatory parameters and the disease severity in COVID-19 patients. J Clin Lab Anal. 36(e24162)2022.PubMed/NCBI View Article : Google Scholar
67	Peruzzi B, Bencini S, Capone M, Mazzoni A, Maggi L, Salvati L, Vanni A, Orazzini C, Nozzoli C, Morettini A, et al: Quantitative and qualitative alterations of circulating myeloid cells and plasmacytoid DC in SARS-CoV-2 infection. Immunology. 161:345–353. 2020.PubMed/NCBI View Article : Google Scholar
68	Mangano C and Oliva BM: Relationship between lymphocyte subsets values and C-reactive protein in COVID-19 patients. Cytometry A. 99:462–465. 2021.PubMed/NCBI View Article : Google Scholar
69	Tyurin AV, Salimgareeva MK, Miniakhmetov IR, Khusainova RI, Samorodov A, Pavlov VN and Kzhyshkowska J: Correlation of the imbalance in the circulating lymphocyte subsets with c-reactive protein and cardio-metabolic conditions in patients with COVID-19. Front Immunol. 13(856883)2022.PubMed/NCBI View Article : Google Scholar
70	Meizlish ML, Pine AB, Bishai JD, Goshua G, Nadelmann ER, Simonov M, Chang CH, Zhang H, Shallow M, Bahel P, et al: A neutrophil activation signature predicts critical illness and mortality in COVID-19. Blood Adv. 5:1164–1177. 2021.PubMed/NCBI View Article : Google Scholar
71	Hasanvand A: COVID-19 and the role of cytokines in this disease. Inflammopharmacology. 30:789–798. 2022.PubMed/NCBI View Article : Google Scholar
72	Tavakkoli M, Wilkins CR, Mones JV and Mauro MJ: A novel paradigm between leukocytosis, G-CSF secretion, neutrophil-to-lymphocyte ratio, myeloid-derived suppressor cells, and prognosis in non-small cell lung cancer. Front Oncol. 9(295)2019.PubMed/NCBI View Article : Google Scholar
73	Miles B: G-CSF in Covid-19 patients: Increased need for mechanical ventilation and inferior 60-day survival. Supportive Care in Cancer [Internet]. 2022 Jun 1 [cited 2022 Sep 15];30:S77-S77. Available from: https://doi.org/10.1007/s00520-022-07099-y.
74	Chen Y, Wang J, Liu C, Su L, Zhang D, Fan J, Yang Y, Xiao M, Xie J, Xu Y, et al: IP-10 and MCP-1 as biomarkers associated with disease severity of COVID-19. Mol Med. 26(97)2020.PubMed/NCBI View Article : Google Scholar
75	Pons MJ, Ymaña B, Mayanga-Herrera A, Sáenz Y, Alvarez-Erviti L, Tapia-Rojas S, Gamarra R, Blanco AB, Moncunill G and Ugarte-Gil MF: Cytokine profiles associated with worse prognosis in a hospitalized peruvian COVID-19 cohort. Front Immunol. 12(700921)2021.PubMed/NCBI View Article : Google Scholar
76	Tjan LH, Furukawa K, Nagano T, Kiriu T, Nishimura M, Arii J, Hino Y, Iwata S, Nishimura Y and Mori Y: Early differences in cytokine production by severity of coronavirus disease 2019. J Infect Dis. 223:1145–1149. 2021.PubMed/NCBI View Article : Google Scholar
77	Yang AP, Li HM, Tao WQ, Yang XJ, Wang M, Yang WJ and Liu JP: Infection with SARS-CoV-2 causes abnormal laboratory results of multiple organs in patients. Aging (Albany NY). 12:10059–10069. 2020.PubMed/NCBI View Article : Google Scholar
78	Liu Y, Tan W, Chen H, Zhu Y, Wan L, Jiang K, Guo Y, Tang K, Xie C, Yi H, et al: Dynamic changes in lymphocyte subsets and parallel cytokine levels in patients with severe and critical COVID-19. BMC Infect Dis. 21(79)2021.PubMed/NCBI View Article : Google Scholar
79	Leisman DE, Ronner L, Pinotti R, Taylor MD, Sinha P, Calfee CS, Hirayama AV, Mastroiani F, Turtle CJ, Harhay MO, et al: Cytokine elevation in severe and critical COVID-19: A rapid systematic review, meta-analysis, and comparison with other inflammatory syndromes. Lancet Respir Med. 8:1233–1244. 2020.PubMed/NCBI View Article : Google Scholar
80	Han H, Ma Q, Li C, Liu R, Zhao L, Wang W, Zhang P, Liu X, Gao G, Liu F, et al: Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors. Emerg Microbes Infect. 9:1123–1130. 2020.PubMed/NCBI View Article : Google Scholar
81	Lambert KA, Roff AN, Panganiban RP, Douglas S and Ishmael FT: MicroRNA-146a is induced by inflammatory stimuli in airway epithelial cells and augments the anti-inflammatory effects of glucocorticoids. PLoS One. 13(e0205434)2018.PubMed/NCBI View Article : Google Scholar
82	Taganov KD, Boldin MP, Chang KJ and Baltimore D: NF-κB-dependent induction of microRNA miR-146, an inhibitor targeted to signaling proteins of innate immune responses. Proc Natl Acad Sci USA. 103:12481–12486. 2006.PubMed/NCBI View Article : Google Scholar
83	Zeng Z, Gong H, Li Y, Jie K, Ding C, Shao Q, Liu F, Zhan Y, Nie C, Zhu W and Qian K: Upregulation of miR-146a contributes to the suppression of inflammatory responses in LPS-induced acute lung injury. Exp Lung Res. 39:275–282. 2013.PubMed/NCBI View Article : Google Scholar
84	Donyavi T, Bokharaei-Salim F, Baghi HB, Khanaliha K, Janat-Makan MA, Karimi B, Nahand JS, Mirzaei H, Khatami A, Garshasbi S, et al: Acute and post-acute phase of COVID-19: Analyzing expression patterns of miRNA-29a-3p, 146a-3p, 155-5p, and let-7b-3p in PBMC. Int Immunopharmacol. 97(107641)2021.PubMed/NCBI View Article : Google Scholar
85	Garg A, Seeliger B, Derda AA, Xiao K, Gietz A, Scherf K, Sonnenschein K, Pink I, Hoeper MM, Welte T, et al: Circulating cardiovascular microRNAs in critically ill COVID-19 patients. Eur J Heart Fail. 23:468–475. 2021.PubMed/NCBI View Article : Google Scholar
86	Meng G, Wei J, Wang Y, Qu D and Zhang J: MiR-21 regulates immunosuppression mediated by myeloid-derived suppressor cells by impairing RUNX1-YAP interaction in lung cancer. Cancer Cell Int. 20(495)2020.PubMed/NCBI View Article : Google Scholar
87	Wang T, Jiang L, Wei X, Dong Z, Liu B, Zhao J, Wang L, Xie P, Wang Y and Zhou S: Inhibition of miR-221 alleviates LPS-induced acute lung injury via inactivation of SOCS1/NF-κB signaling pathway. Cell Cycle. 18:1893–1907. 2019.PubMed/NCBI View Article : Google Scholar
88	Xu P, Xin J, Song L, Chen Y, Ma J, Liu L, Qi Z, Pan X and Zhou S: Serum miR-133 as a potential biomarker in acute cerebral infarction patients. Clin Lab. 66:1923–1928. 2020.PubMed/NCBI View Article : Google Scholar
89	Huang J, Zhu L, Qiu C, Xu X, Zhang L, Ding X, Liao Q, Xu J and Zhang X: MicroRNA miR-126-5p enhances the inflammatory responses of monocytes to lipopolysaccharide stimulation by suppressing cylindromatosis in chronic HIV-1 Infection. J Virol. 5:e02048–e02016. 2017.PubMed/NCBI View Article : Google Scholar
90	Fogel O, Tinggaard AB, Fagny M, Sigrist N, Roche E, Leclere L, Deleuze JF, Batteux F, Dougados M, Miceli-Richard C and Tost J: Deregulation of microRNA expression in monocytes and CD4+ T lymphocytes from patients with axial spondyloarthritis. Arthritis Res Ther. 21(51)2019.PubMed/NCBI View Article : Google Scholar