Article Biomarker Profiles Associated with COVID-19 Severity and Mortality Silvia Sánchez-Díez 1,2 , Carlos Gómez-Ollés 1 , María-Jesús Cruz 1,2, * , Miquel de Homdedeu 1,2 , David Espejo 1 , Jaume Ferrer 1,2 , Oriol Roca 3 , Andrés Pacheco 3 and Xavier Muñoz 1,2,4 1 Pulmonology Service, Department of Medicine, Vall d’Hebron University Hospital, Autonomous University of Barcelona, 08035 Barcelona, Spain 2 CIBER of Respiratory Diseases (CIBERES), 28029 Madrid, Spain 3 Intensive Medicine, Vall d’Hebron University Hospital, Autonomous University of Barcelona, 08035 Barcelona, Spain 4 Department of Cell Biology and Physiology and Immunology, Autonomous University of Barcelona, 08193 Barcelona, Spain * Correspondence: mj.cruz@vhir.org Abstract: Introduction: The aim of this study was to analyze biomarkers that might predict the severity and progression of the SARS-CoV-2 infection, both in the acute phase and after recovery. Methods: Unvaccinated patients infected with the original strain of COVID-19 requiring ward (Group 1, n = 48) or ICU (Group 2, n = 41) admission were included. At the time of admission (visit 1), a clinical history was acquired, and blood samples were obtained. One and six months after discharge from the hospital (visits 2 and 3, respectively), a clinical history, lung function tests, and blood samples were carried out. At visit 2, patients also underwent a chest CT scan. Different cytokines (IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-17A, G-CSF, GM-CSF, IFN-G, MCP-1, MIP-1β, and TNF-α) and lung fibrosis biomarkers (YKL-40 and KL-6) were measured in blood samples obtained at visits 1, 2, and 3. Results: At visit 1, IL-4, IL-5, and IL-6 levels were higher in Group 2 (p = 0.039, 0.011, and 0.045, respectively), and IL-17 and IL-8 levels were higher in Group 1 (p = 0.026 and 0.001, respectively). The number of patients in Groups 1 and 2 who died during hospitalization was 8 and Citation: Sánchez-Díez, S.; 11, respectively. YKL-40 and KL-6 levels were higher in patients who died. Serum YKL-40 and KL-6 Gómez-Ollés, C.; Cruz, M.-J.; de levels determined at visit 2 correlated negatively with FVC (p = 0.022 and p = 0.024, respectively) and Homdedeu, M.; Espejo, D.; Ferrer, J.; FEV1 (p = 0.012 and p = 0.032, respectively) measured at visit 3. KL-6 levels also correlated negatively Roca, O.; Pacheco, A.; Muñoz, X. with the diffusing capacity of the lungs for carbon monoxide (DLCO, p = 0.001). Conclusions: Patients Biomarker Profiles Associated with who required ICU admission had higher levels of Th2 cytokines, while patients admitted to the COVID-19 Severity and Mortality. Curr. Issues Mol. Biol. 2023, 45, ward showed an innate immune response activation, with IL-8 release and Th1/Th17 lymphocyte 1998–2012. https://doi.org/ contribution. Increased levels of YKL-40 and KL-6 were associated with mortality in COVID-19 10.3390/cimb45030128 patients. Academic Editor: Su-Jin Park Keywords: COVID-19; cytokines; serum; lung fibrosis Received: 24 January 2023 Revised: 19 February 2023 Accepted: 23 February 2023 Published: 1 March 2023 1. Introduction The disease caused by the severe acute respiratory syndrome (SARS)-CoV-2 coron- avirus has affected millions of people worldwide since its outbreak in 2019, and the severity Copyright: © 2023 by the authors. of the disease differs from person to person. After SARS-CoV-2 infection, the first variants Licensee MDPI, Basel, Switzerland. of the virus incubate in the upper respiratory tract for 2–5 days before the development This article is an open access article of mild clinical symptoms, such as dry cough and throat pain [1]. At this stage, the in- distributed under the terms and nate immune response is limited, unless there is a significant increase in the viral load. conditions of the Creative Commons Viral progression in the airways is related to a more robust immune response and induces Attribution (CC BY) license (https:// the appearance of other symptoms, such as muscle aches, fever, and in the worst cases, creativecommons.org/licenses/by/ breathing difficulty [2]. In approximately 20% of non-vaccinated patients, there is alveolar 4.0/). progression with pulmonary infiltrates and severe disease, which is often associated with Curr. Issues Mol. Biol. 2023, 45, 1998–2012. https://doi.org/10.3390/cimb45030128 https://www.mdpi.com/journal/cimb Curr. Issues Mol. Biol. 2023, 45 1999 an excessive inflammatory response. At this point, patients require hospitalization due to the appearance of pneumonia and low oxygen saturation in the blood [3]. According to the literature, severe SARS-CoV-2 can trigger an excessive immune response, with massive production of inflammatory cytokines and chemical mediators, known as the cytokine storm [4–7]. Cytokine levels rise during the systemic inflamma- tory response syndrome and may lead to multi-organ failure in some individuals. Severe COVID-19 patients also present high neutrophil counts and low numbers of lymphocytes in the blood. Moreover, CD8+T cells in COVID-19 patients appear to be functionally ex- hausted, indicated by a lower production of IFN-G, TNF-α and IL-2 [8,9]. Recent findings have also highlighted that toll-like receptors (TLR) bind to SARS-CoV-2, inducing the for- mation and release of pro-inflammatory cytokines such as pro-IL-1β, which later becomes IL-1β, causing lung inflammation and fibrosis [10,11]. While our understanding of the acute phase of the disease has expanded rapidly, little is known about the consequences of COVID-19 following clinical remission, although it is assumed that these consequences may be related to events in the acute phase. In addition, it is unclear whether (and if so, how) the profiling of cytokines can be used as a prognostic biomarker for disease outcome and control. Some patients successfully overcome acute COVID-19 infection, without any sequelae. However, patients who are more severely ill can present chronic respiratory symptoms and abnormal chest imaging manifestations after discharge from the hospital [12,13], in some cases associated with a proliferative response characterized by tissue repair that may progress to lung fibrosis [14]. A deeper understanding of the inflammatory and immunological patterns in post- COVID-19 pneumonia is necessary to be able to design follow-up strategies for patients recovering from acute disease, both in the hospital and after discharge. In this context, the present study assesses possible biomarkers of innate and adaptive immunity that can predict the severity and progression of COVID-19 disease towards stages of respiratory sequelae developed in unvaccinated patients infected with the original strain of COVID-19. 2. Material and Methods 2.1. Study Population We performed a prospective study using a representative sample of 89 consecutive patients over the age of 18 with pneumonia due to COVID-19 diagnosed at our center (Vall d’Hebron University Hospital, Barcelona, Spain) and requiring ward (Group 1, n = 48) or intensive care unit (ICU) admission (Group 2, n = 41) in October 2020 (rate of ward admission: 12 patients/day; rate of ICU admission: 5 patients/day) (Figure 1). At the time of admission (visit 1), data from the clinical history were recorded (sociodemographic data, comorbidities, and ventilator support), and an X-ray was performed to confirm the diagnosis of pneumonia. At this stage of the disease, almost all patients were treated with dexamethasone. One and six months after discharge from the hospital (visits 2 and 3, respectively), patients were seen at the pulmonology service of our center and underwent a more exhaustive clinical history, including lung function tests. At visit 2, patients also underwent a high-resolution computed tomography (HRCT) chest scan, and at visit 3, this imaging test was only performed in patients with abnormalities upon physical examination and/or respiratory function tests compatible with respiratory sequelae. At visit 1, 2, and 3, blood samples were obtained, and after blood centrifugation (3000 rpm during 10 min), serum samples were obtained and stored at −80 ◦ C for subsequent biomarker analysis. The study was approved by the local ethics committee (Hospital Vall d’Hebron Ethics Committee approval PR(AG)219/2020), and all subjects signed an informed consent docu- ment prior to their participation. Curr. Issues Mol. Biol. 2023, 3, FOR PEER REVIEW 3 Curr. Issues Mol. Biol. 2023, 45 2000 Figure 1. Flow chart of patient enrollment. A total of 89 consecutive unvaccinated patients with Figure 1. due pneumonia Flowtochart of patientstrain the original enrollment. A total of of COVID-19 89 consecutive diagnosed at Vallunvaccinated patients with d’Hebron University Hospital pneumonia due to the original strain of COVID-19 diagnosed at Vall d’Hebron University Hospital (Barcelona, (Barcelona,Spain) Spain)ininOctober 2020 requiring October 2020 requiringward ward (Group (Group 1, n1,= n48) = or 48)intensive or intensive care(ICU) care unit unit (ICU) admission admission(Group (Group2,2,nn== 41) 41) were includedinin were included the the study. study. A total A total of 8 of 8 patients patients from from GroupGroup 1 and 111 and 11 from from Group Group 2 diedduring 2 died during hospitalization hospitalization due duetotoCOVID-19 COVID-19 infection. Moreover, infection. 5 patients Moreover, from from 5 patients Group Group 1 and4 4from 1 and from Group Group 22could couldnot bebe not contacted contactedfor the forsecond visit ofvisit the second follow-up. At visit 3,At of follow-up. 10 visit 3, patients from Group 1 and 7 from Group 2 could not be contacted. 10 patients from Group 1 and 7 from Group 2 could not be contacted. The study 2.2. Pulmonary was approved Function Testingby the local ethics committee (Hospital Vall d’Hebron Eth- ics Committee approval PR(AG)219/2020), and all subjects signed an informed consent A complete document prior pulmonary function study, including forced spirometry and diffusion to their participation. capacity of the lung for carbon monoxide (DLCO), was carried out in all participants during follow-up on a MasterLab 2.2. Pulmonary system (MasterLab, Jaeger, Germany), in accordance with the Function Testing guidelines of the European A complete pulmonaryRespiratory Society function study, and American including Thoracic Society forced spirometry [15]. All data and diffusion were expressed capacity of theas percentages lung of published for carbon monoxide predicted (DLCO), values. was carried outThe theoretical in all values participants dur- were theing ones proposed follow-up on aby the Global MasterLab Lung(MasterLab, system Function Initiative (GLI) [16]. Jaeger, Germany), Forced vital in accordance capacity with the guidelines (FVC), of the European forced expiratory volume Respiratory Society in 1 second and American (FEV1), FEV1/FVC Thoracic ratio, Society and DLCO[15]. were All data were considered lowexpressed at valuesas ofpercentages <80%, 80%,of70%, published predicted and 80% of thevalues. The theoretical predicted val- value, respectively. ues were the ones proposed by the Global Lung Function Initiative (GLI) [16]. Forced vital 2.3.capacity (FVC),Scanning Chest HRCT forced expiratory volume in 1 second (FEV1), FEV1/FVC ratio, and DLCO were considered low at values of <80%, 80%, 70%, and 80% of the predicted value, respec- Chest high-resolution computed tomography was performed with 1 mm cuts at tively. 10 mm intervals in maximum inspiration during follow-up. All the imaging features were interpreted by two 2.3. Chest HRCT pulmonologists, working independently. To interpret controversial Scanning images, an expert radiologist was consulted. High-resolution computed tomography scans were evaluated for the following characteristics: location (unilateral or bilateral) and distribution (central, peripheral, or both) of the lesion, type of lesion (simple, multiple, or diffuse), presence of ground glass, consolidation, linear opacities, reticulation, and/or mixed pattern, and interstitial changes. Curr. Issues Mol. Biol. 2023, 45 2001 2.4. Cytokine Analysis The concentrations of 17 cytokines/chemokines, including Th1, Th2, and Th17 cy- tokines, and pro-inflammatory cytokines associated with infectious diseases and inflamma- tion were measured: IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-17A, G-CSF, GM-CSF, IFN-G, MCP-1, MIP-1β, and TNF-α. Cytokines were measured in serum samples obtained at each visit using human cytokine multiplex magnetic bead panels (Bio-Plex Pro Human Cytokine 17-plex Assay, Bio-Rad Laboratories S.A., Madrid, Spain), according to the manufacturer’s instructions. Lower limits of detection were 0.24, 0.75, 0.04, 0.86, 0.34, 1.22, 0.36, 0.69, 0.78, 0.22, 1.16, 3.63, 0.19, 1.05, 0.44, 1.41, and 1.13 pg/mL for IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-17A, G-CSF, GM-CSF, IFN-G, MCP-1, MIP-1β, and TNF-α, respectively. 2.5. YKL-40 and KL-6 Analysis YKL-40 levels were measured in serum samples obtained at each visit by an YKL-40 enzyme immunoassay kit (Quidel, San Diego, CA, USA), in accordance with the manufac- turer’s instructions. KL-6 levels were measured in serum samples obtained at each visit by a chemilumi- nescent enzyme immunoassay (Lumipulse G KL-6, Fujirebio Iberia SL, Barcelona, Spain) using the Lumipulse G System and in accordance with the manufacturer’s instructions. 2.6. Statistical Analysis Categorical variables are expressed as absolute numbers and their corresponding percentages, and continuous variables as means (standard deviation) or medians (range), depending on the symmetry of their distribution. Comparisons between categorical vari- ables were performed using Pearson’s Chi-square test or Fisher’s exact test, according to data distribution evaluated with the Shapiro–Wilk test. Continuous variables were compared using the Student’s t-test or the Mann–Whitney test (when comparing different groups), or the paired t-test or Wilcoxon test (when comparing results in the same group at different time points), depending on data distribution. Multiple comparisons between groups were performed using one-way ANOVA or the Kruskal–Wallis test, as appropriate. Correlations between variables were calculated with the Pearson correlation coefficient (r), according to data distribution. Analyses were conducted using GraphPad Prism 6 for Windows (version 6.01, GraphPad Software Inc, San Diego, CA, USA) and IBM SPSS Statis- tics (version 26, IBM Corporation, Armonk, NY, USA). Differences with a p-value < 0.05 (two-tailed) were considered to be significant. 3. Results 3.1. Study Population Demographic and clinical characteristics of the subjects are shown in Table 1. In Group 2, 27% of patients were active smokers compared to 8% in Group 1 (p = 0.025). The mean BMI for patients in Groups 1 and 2 was 30 and 33, respectively. A total of 18 patients in each group (44% Group 1, 38% Group 2) presented with obesity (BMI > 30). Respiratory comorbidities did not appear to be a risk factor for the development of COVID- 19 (Table 1). The most frequent non-respiratory comorbidities in both groups were arterial hypertension, obesity, and diabetes, without significant differences between groups. A significant difference was observed in solid cancer as a non-respiratory comorbidity in patients admitted to the ward (Group 1, p = 0.009), and 46% of them were already cured from the neoplasia before the infection. A total of 45% of patients in Group 1 and all patients in Group 2 required ventilatory support; however, a larger number of patients admitted to the ICU (Group 2) required invasive mechanical ventilation (p = 0.005). Curr. Issues Mol. Biol. 2023, 45 2002 Table 1. Characteristics and ventilatory support of the subjects included in the study. Group 1 Group 2 p Value (n = 48) (n = 41) Sociodemographic and clinical data Age (years), median (range) 66 (25–90) 63 (40–76) 0.403 Sex (male), n (%) 31 (64) 33 (80) 0.106 BMI (Kg/m2 ), median (range) 30 (15–41) 32.9 (25–33) 0.499 BMI > 30 (Kg/m2 ), n (%) 18 (38) 18 (44) 0.665 Smoking habit, n (%) 0.041 Smoker 4 (8) 11 (27) 0.025 Former smoker 21 (44) 11 (27) 0.123 Non-smoker 21 (44) 16 (39) 0.673 Survival, n (%) 40 (83) 30 (73) 0.303 Respiratory comorbidities, n (%) Asthma 2 (4) 0 (0) 0.497 Obstructive sleep apneas 5 (10) 0 (0) 0.059 Chronic obstructive pulmonary disease 5 (10) 0 (0) 0.059 Bronchiectasis 0 1 (2) 0.461 Pulmonary arterial hypertension 2 (4) 0 (0) 0.497 Pulmonary fibrosis 1 (2) 0 (0) 1.000 Other interstitial diseases 2 (4) 0 (0) 0.497 Lung transplant 2 (4) 0 (0) 0.497 Non-respiratory comorbidities, n (%) Arterial hypertension 24 (50) 20 (49) 1.000 Obesity 18 (38) 18 (44) 0.665 Diabetes 12 (25) 7 (17) 0.441 Chronic renal insufficiency 6 (12) 3 (7) 0.498 Immunosuppression 3 (6) 2 (5) 1.000 Ischemic heart disease 7 (15) 1 (2) 0.065 Heart failure 1 (2) 0 (0) 1.000 Atrial fibrillation 3 (6) 0 (0) 0.246 Other cardiac diseases 4 (8) 2 (5) 0.683 Solid cancer 13 (27) 2 (5) 0.009 Cured 6 (46) 2 (100) 0.467 Leukemia 3 (6) 0 (0) 0.246 Psychiatric disease 5 (10) 3 (7) 0.721 Gastroesophageal reflux 0 (0) 1 (2) 1.000 Ventilatory support, n (%) (n = 47) (n = 40) Yes 21 (45) 40 (100) <0.0001 Type of support, n (%) High-flow nasal cannula (HFNC) 18 (86) 26 (65) 0.133 Non-invasive mechanical ventilation (NIMV) 3 (14) 2 (5) 0.329 Invasive mechanical ventilation (IMV) 13 (62) 37 (93) 0.005 Extracorporeal membrane oxygenation 1 (5) 4 (10) 0.651 Oxygen therapy 100% 2 (10) 3 (8) 1.000 A single patient may present more than one comorbidity or ventilatory support. Percentages in each line are calculated from the total population, except for patients with a neoplasia considered cured and type of ventilatory support, where percentages are calculated from the population with solid cancer and the population with support requirements, respectively. Some variables have missing values: Group 1 (2 for smoking habit, 1 for ventilatory support); Group 2 (3 for smoking habit, 1 for ventilator support). A total of 8 patients from Group 1 and 11 from Group 2 died during hospitalization due to COVID-19 infection. Moreover, 5 patients from Group 1 and 4 from Group 2 could Curr. Issues Mol. Biol. 2023, 45 2003 not be contacted during follow-up (Figure 1). Lung function and radiological characteristics during follow-up are shown in Table 2. DLCO values decreased significantly in Group 2 between visits 2 and 3 (p = 0.044). In Group 1, HRCT scan findings were pathological in 85% of patients at visit 2 and in 90% at visit 3, compared with 95% at visit 2 and 88% at visit 3 in Group 2. At visits 2 and 3, bilateral involvement was observed in almost all patients, with lesions mostly distributed in peripheral areas. Diffuse injury, mixed pattern, and/or ground glass opacities were the most common findings in both groups at follow-up visits. The rate of ground glass opacities in Group 2 rose from 1 (5%) at visit 2 to 5 (71%) at visit 3 (p = 0.002). Interstitial changes were observed at visit 2 in 6 (21%) patients in Group 1 and in 10 (53%) in Group 2 (p = 0.034). A radiological improvement was detected in patients in both groups at visit 3. Table 2. Lung function and HRCT characteristics in the study population during follow-up. Group 1 Group 2 Pulmonary function parameters Visit 2 (n = 35) Visit 3 (n = 25) p Value Visit 2 (n = 26) Visit 3 (n = 19) p Value FVC (% predicted), median (range) 87 (41–118) 84 (45–118) 0.533 85 (53–137) 81 (37–111) 0.143 FVC < 85%, n (%) 13 (37) 9 (36) 1.000 10 (38) 7 (37) 1.000 FEV1 (% predicted), median (range) 91 (42–134) 89 (43–124) 0.089 91 (56–139) 88 (27–122) 0.653 FEV1 < 80%, n (%) 7 (20) 6 (24) 0.758 6 (23) 3 (16) 0.712 FEV1/FVC (% predicted), median (range) 81 (52–100) 82 (43–99) 0.109 84 (76–98) 86 (56–90) 0.25 FEV1/FVC < 70%, n (%) 3 (9) 2 (8) 1.000 0 (0) 1 (5) 0.422 DLCO (% predicted), median (range) 70 (23–94) 73 (27–86) 0.457 62 (25–106) 57 (29–110) 0.044 DLCO < 80%, n (%) 22 (63) 10 (40) 0.116 16 (62) 8 (42) 0.237 DLCO/VA (% predicted), median (range) 75 (31–123) 75 (44–100) 0.649 78 (42–109) 85 (19–103) 0.097 HRCT, n (%) Visit 2 (n = 33) Visit 3 (n = 11) p Value Visit 2 (n = 20) Visit 3 (n = 8) p Value Pathological findings Yes 28 (85) 10 (90) 1.000 19 (95) 7 (88) 0.497 Location Unilateral 1 (4) 0 (0) 1.000 0 (0) 0 (0) 1.000 Bilateral 27 (96) 10 (100) 1.000 19 (100) 7 (100) 1.000 Distribution Central 1 (4) 0 (0) 1.000 0 (0) 0 (0) 1.000 Peripheral 25 (89) 10 (100) 0.552 19 (100) 7 (100) 1.000 Central and peripheral 2 (7) 0 (0) 1.000 0 (0) 0 (0) 1.000 Type of injury Simple 1 (4) 0 (0) 1.000 0 (0) 0 (0) 1.000 Multiple 1 (4) 0 (0) 1.000 0 (0) 1 (14) 0.269 Diffuse 26 (92) 10 (100) 1.000 19 (100) 6 (86) 0.269 Main imaging features Ground glass 5 (18) 4 (40) 0.205 1 (5) 5 (71) 0.002 Consolidation 2 (7) 0 (0) 1.000 0 (0) 0 (0) 1.000 Linear opacities 0 (0) 1 (10) 1.000 0 (0) 0 (0) 1.000 Reticulation 3 (11) 0 (0) 0.552 5 (26) 0 (0) 0.278 Mixed pattern 15 (54) 5 (50) 1.000 11 (58) 2 (29) 0.378 Interstitial changes 6 (21) * 0 (0) 0.168 10 (53) * 2 (29) 0. 391 Percentages in each line are calculated from the total population, except for HRCT scan parameters, where percentages are calculated from the pathological population. Some variables have missing values: Group 1 (Visit 2: 2 for FVC, 2 for FEV1, 2 for FEV1/FVC, 4 for DLCO, 4 for DLCO/VA, and 2 for HRCT; Visit 3: 8 for FVC, 8 for FEV1, 8 for FEV1/FVC, 11 for DLCO, 11 for DLCO/VA, and 14 for HRCT), and Group 2 (Visit 2: 7 for FVC, 7 for FEV1, 7 for FEV1/FVC, 7 for DLCO, 7 for DLCO/VA, and 6 for HRCT; Visit 3: 8 for FVC, 8 for FEV1, 8 for FEV1/FVC, 9 for DLCO, 9 for DLCO/VA, and 11 for HRCT). * p < 0.05. 3.2. Cytokine Expression Profiles At visit 1, increased IL-1β levels were observed in both groups, and they were higher in patients in Group 1 than in Group 2 (p < 0.0001). At follow-up visits, this cytokine Curr. Issues Mol. Biol. 2023, 3, FOR PEER REVIEW 9 3.2. Cytokine Expression Profiles Curr. Issues Mol. Biol. 2023, 45 2004 At visit 1, increased IL-1β levels were observed in both groups, and they were higher in patients in Group 1 than in Group 2 (p < 0.0001). At follow-up visits, this cytokine was not detectable in either group (Figure 2A). In patients admitted to the ICU (group 2), in- was not detectable in either group (Figure 2A). In patients admitted to the ICU (group 2), creased levels of IL-2 were found during admission (p = 0.019), but these levels were no increased levels of IL-2 were found during admission (p = 0.019), but these levels were longer detectable at follow-up visits (Figure 2B). Increased levels of IFN-ɣ and TNF-α were no longer detectable at follow-up visits (Figure 2B). Increased levels of IFN-G and TNF-α reported during infection (visit 1) in both groups. These levels had fallen at visit 2 in pa- were reported during infection (visit 1) in both groups. These levels had fallen at visit 2 in tients of Group 1 (p < 0.0001 and 0.0002, respectively), while in Group 2, they remained patients of Group 1 (p < 0.0001 and 0.0002, respectively), while in Group 2, they remained high at visit 3 (Figures 2C and 2D). No significant differences were observed in either high at visit 3 (Figure 2C,D). No significant differences were observed in either group for group for IL-12p70 (Figure 2E). IL-12p70 (Figure 2E). Figure2.2.Comparison Figure Comparison of of Th1-related cytokines between Th1-related cytokines between patients patientsof ofGroup Group11andand22from fromvisits visits1 1toto3. 3.(A) (A) At visit 1, increased IL-1β levels in both groups, which were higher in At visit 1, increased IL-1β levels in both groups, which were higher in patients in Grouppatients in Group 1 than 1 than GroupGroup 2 (p 2< (p < 0.0001). 0.0001). (B) Group (B) Group 2: increased 2: increased levels levels of IL-2 of IL-2 during during admission admission (p =(p0.019). = 0.019). (C,D) (C,D) In- creased levels Increased levelsofofIFN-ɣ IFN-Gand andTNF-α TNF-αat at visit visit 11 in in both groups. These levels had fallen fallen at at visit visit 22inin patientsfrom patients fromGroupGroup1 1(p(p< <0.0001 0.0001and and0.0002, 0.0002, respectively), respectively), while while in in Group Group 2, they 2, they remained remained highhigh at at visit visit 3. (E) 3. (E) No No significant significant differences differences werewere observed observed for IL-12p70. for IL-12p70. Atvisit At visit1,1,increased increasedlevels levelsofofIL-4 IL-4and andIL-5 IL-5were wereobserved observedin inpatients patientswho whorequired required ICUadmission ICU admission(Group(Group2),2),but butthese theselevels levels hadhad fallen fallen oneone month month after after thethe infection infection (visit (visit 2) 2) =(p0.039 (p = 0.039 andand p =p 0.011, = 0.011, respectively)(Figure respectively) (Figure3A,B). 3A,B).High HighIL-6 IL-6levels levelswere wereobserved observed duringinfection during infectionin inboth bothgroups, groups,although although they they were weremuch much higher higher inin Group Group 22 (p(p== 0.046). 0.046). However,levels However, levelsof ofthis thiscytokine cytokine fell fell during during follow-up follow-up (Figure (Figures3C). 3C).IL-10 IL-10and andIL-13 IL-13levels levels were were increased both groups at the time of admission, although reductions in both both increased in both groups at the time of admission, although reductions in cyto- cytokines kines were were observed observed at visits at visits 2 and2 and 3 (Figure 3 (Figure 3D,E). 3D,E). IL- IL- 17A17A levels levels werewere elevated elevated in in the the acuteacute phase phase of theof infection, the infection, especially especially in Group in Group 1 (p =10.027), (p = 0.027), and thenandfell then fell during during follow- follow-up up (Figure(Figure 3F). 3F). Curr.Issues Curr. IssuesMol. Mol.Biol. Biol.2023, 2023,45 3, FOR PEER REVIEW 10 2005 Figure 3.3. Comparison Figure ComparisonofofTh2 Th2and andTh17 Th17cytokine cytokine expression expression profiles between profiles between patients of Group patients 1 and1 of Group 2and at visit 2 at 1visit and1inandtheinfollow-up visits.visits. the follow-up (A,B)(A,B) At visit At 1, increased visit levelslevels 1, increased of IL-4of and IL-4IL-5 and in patients IL-5 in pa- tients of Groupof Group 2 butlevels 2 but these these levels had fallen had fallen at visitat2visit (p = 20.039 (p = and 0.039p and p =0.011 =0.011 respectively). respectively). (C) High (C) High IL-6 IL-6 levels at visit 1 in both groups, though much higher in Group 2 (p = 0.046). levels at visit 1 in both groups, though much higher in Group 2 (p = 0.046). (D,E) IL-10 and IL-13 (D,E) IL-10 and IL- 13 levels increased in both groups at visit 1. (F) IL- 17A levels elevated at visit 1, especially levels increased in both groups at visit 1. (F) IL- 17A levels elevated at visit 1, especially in Group 1 in Group 1 (p (p = 0.027). = 0.027). Significantly increased Significantly increased levels levels of of IL-7 IL-7 were were observed observed inin both both groups groups six six months months after after the infection (visit 3), particularly in patients admitted to the ward (p = 0.026) (Figure 4A). the infection (visit 3), particularly in patients admitted to the ward (p = 0.026) (Figure 4A). Higher levels Higher levels of of IL-8 IL-8 were were observed observed during during the the acute acute phase phase ofof the the disease disease in in Group Group 11 than than in Group in Group22(p(p==0.001), 0.001),although although these these levels levels decreased decreased with with timetime afterafter infection infection (Figure (Figure 4B). 4B). At At 1, visit visit 1, higher higher levels levels of G-CSFof G-CSF were detected were detected in ICU patients in ICU patients (p = 0.009),(p =but 0.009), but this this cytokine cytokine was was not detectable not detectable at visit 3 at visit 34C). (Figure (Figure 4C). No significant No significant differences differences were observedwere observed in GM- in GM-CSF CSF levels between levels between groups4D). groups (Figure (Figure MCP-1 4D). MCP-1 levels werelevels high were in both high in both groups one groups month one month after after the the infection infection (visit 2) and(visit 2) and remained remained high in Grouphigh invisit 2 at Group3 (p2=at0.002) visit 3(Figure (p = 0.002) 4E). (Figure The 4E).ofThe levels levelswere MIP-1β of MIP-1β wereinincreased increased both groupsin both groups during during infection, infection, but then fellbut over then fell over time time4F). (Figure (Figure 4F). 3.3. Levels of Pulmonary Fibrosis Biomarkers During infection, higher YKL-40 levels were observed in patients admitted to the ICU (Group 2) (p = 0.0004), although these levels fell during follow-up (Figure 5A). High serum KL-6 levels were observed in both groups at the time of admission, but these levels fell in patients admitted to the ward (Group 1) in the follow-up visits (Figure 5B). Curr. Curr.Issues IssuesMol. Mol.Biol. Biol.2023, 2023,3,45FOR PEER REVIEW 11 2006 Comparisonofofpro-inflammatory Figure4.4. Comparison Figure pro-inflammatoryand andadaptive adaptiveimmune immuneresponse responsecytokine cytokineexpression expression profiles profilesbetween betweenpatients patientsofof Groups 1 and Groups 2 at2visit 1 and 1 and at visit 1 at andtheatfollow-up visits.visits. the follow-up (A) Increased levels (A) Increased oflevels IL-7 of were IL-7observed in bothingroups were observed at visitat3,visit both groups particularly in patients 3, particularly of Group in patients 1 (p =10.026). of Group (B) (p = 0.026). Higher (B) Higher levels of IL-8 at visit 1 were observed in Group 1 than in Group 2 (p = 0.001). (C) At visit1,12 levels of IL-8 at visit 1 were observed in Group 1 than in Group 2 (p = 0.001). (C) At visit 1, Curr. Issues Mol. Biol. 2023, 3, FOR PEER REVIEW higher higherlevels levels of of G-CSF were observed G-CSF were observedininpatients patientsofofGroup Group 2 (p 2 (p = 0.009). = 0.009). (D)(D) NoNo significant significant differ- differences ences were observed in GM-CSF levels between groups. (E) MCP-1 levels were high in both groups were observed in GM-CSF levels between groups. (E) MCP-1 levels were high in both groups at visit at visit 2 and remained high in Group 2 at visit 3 (p = 0.002). (F) MIP-1β levels increased in both 2 and remained high in Group 2 at visit 3 (p = 0.002). (F) MIP-1β levels increased in both groups at groups at visit 1. visit 1. 3.3. Levels of Pulmonary Fibrosis Biomarkers During infection, higher YKL-40 levels were observed in patients admitted to the ICU (Group 2) (p = 0.0004), although these levels fell during follow-up (Figure 5A). High serum KL-6 levels were observed in both groups at the time of admission, but these levels fell in patients admitted to the ward (Group 1) in the follow-up visits (Figure 5B). Figure 5. Comparison of YKL-40 and KL-6 levels between patients of Group 1 and 2 at visit 1 and in the follow-up Figure visits (A,B). 5. Comparison (A) At visit of YKL-40 and 1, higher KL-6 YKL-40 levels levels between were observed patients of Groupin patients 1 and 2 at of Group visit 1 and2 (p in = the0.0004). (B) High follow-up visitsserum (A,B). KL-6 (A) Atlevels visit were observed 1, higher in levels YKL-40 both groups at visit 1,inbut were observed these levels patients fell of Group in patients 2 (p of Group = 0.0004). (B) High1 inserum the follow-up visits. KL-6 levels were observed in both groups at visit 1, but these levels fell in patients of Group 1 in the follow-up visits. 3.4. Relation between Mortality and Cytokines or Pulmonary Fibrotic Biomarkers Dividing patients according to survival or non-survival during hospitalization (visit 1), survivors presented higher levels of IL-1β (p = 0.052) (Figure 6A). Increased levels of IL-6 and IL-13 were related to death (p = 0.029 and p = 0.031, respectively) (Figure 6A). Regarding fibrotic biomarkers, both YKL-40 and KL-6 were higher in patients who died Figure 5. Comparison of YKL-40 and KL-6 levels between patients of Group 1 and 2 at visit 1 and Curr. Issues Mol. Biol. 2023, 45 2007 in the follow-up visits (A,B). (A) At visit 1, higher YKL-40 levels were observed in patients of Group 2 (p = 0.0004). (B) High serum KL-6 levels were observed in both groups at visit 1, but these levels fell in patients of Group 1 in the follow-up visits. 3.4. Relation between Mortality 3.4. Relation andMortality between Cytokines orCytokines and Pulmonary Fibrotic Biomarkers or Pulmonary Fibrotic Biomarkers Dividing patients according Dividing toaccording patients survival or non-survival to survival during hospitalization or non-survival (visit (visit during hospitalization 1), survivors presented higher 1), survivors levelshigher presented of IL-1β (p of levels = 0.052) IL-1β (p(Figure = 0.052)6A). Increased (Figure levels of 6A). Increased levels of IL-6 and IL-13 IL-6 were related and to death IL-13 were (p = related to 0.029 (p = p death and = 0.031, 0.029 and prespectively) (Figure(Figure = 0.031, respectively) 6A). 6A). Regarding fibrotic biomarkers, Regarding fibrotic both YKL-40 biomarkers, andYKL-40 both KL-6 were higher and KL-6 wereinhigher patients who died in patients who died (p < 0.0001 and(pp <=0.0001 and 0.0002, p = 0.0002, respectively) respectively) (Figure 6B).(Figure 6B). Figure of Figure 6. Comparison 6. Comparison of fibrotic(A) fibrotic biomarkers biomarkers (A) and and cytokine (B)cytokine (B) concentrations concentrations betweenbetween patientspatients of Group 1 and 2, according to survival or non-survival during hospitalization (visit 1). (A) Higher of Group 1 and 2, according to survival or non-survival during hospitalization (visit 1). (A) Higher levels of IL-1β were observed in survivors (p = 0.052). Increased levels of IL-6 and IL-13 were related levels of IL-1β were Curr. Issues Mol. Biol. 2023, 3, FOR PEER REVIEW observed to death in survivors (p = 0.029 (p = 0.052). and p = 0.031, Increased respectively). levels (B). Both of IL-6and YKL-40 and IL-13 KL-6 were were related higher in patients 13 to death (p = 0.029 and p = 0.031, respectively). (B). Both YKL-40 who died (p < 0.0001 and p = 0.0002, respectively). and KL-6 were higher in patients who died (p < 0.0001 and p = 0.0002, respectively). 3.5. 3.5.Predictive PredictiveValue ValueofofCytokines CytokinesandandPulmonary PulmonaryFibrotic FibroticBiomarkers Biomarkers IL-10 IL-10and andIL-17A IL-17Alevels levelsanalyzed analyzedatatbaseline baseline(visit (visit1)1)correlated correlatednegatively negativelywith with DLCO/VA DLCO/VA measured measured six six months after hospitalization hospitalization (% (% predicted, predicted,IL-10: −0.416, IL-10:r r= =−0.416, p= p 0.048; = 0.048; IL-17A: IL-17A: = −0.46, r =r−0.46, p = p0.024) = 0.024) (Figure (Figure 7A 7A andand 7B, B, respectively). respectively). Figure7.7.Correlations Figure Correlationsbetween betweencytokines cytokines(analyzed (analyzedatatvisit visit1)1)ororfibrotic fibroticbiomarkers biomarkers(determined (determinedatat visit 2) and lung function parameters (measured at visit 3). (A,B) IL-10 and IL-17A levels at at visit 2) and lung function parameters (measured at visit 3). (A,B) IL-10 and IL-17A levels visit visit 1 1 correlated negatively with DLCO/VA measured at visit 3. (% predicted, IL-10: r = −0.416, p = 0.048; IL-17A: r = −0.46, p = 0.024). (C–F) Serum YKL-40 and KL-6 levels measured at visit 2 correlated negatively with FVC (L, YKL-40: r = −0.438, p = 0.022; % predicted, KL-6: r = −0.426, p = 0.024) and FEV1 (L, YKL-40: r = −0.476, p = 0.012; % predicted, KL-6: r = −0.407, p = 0.032) measured at visit 3. (G) KL-6 levels at visit 2 correlated negatively with DLCO (% predicted, r = −0.614, p = 0.001) meas- ured at visit 3. Curr. Issues Mol. Biol. 2023, 45 2008 correlated negatively with DLCO/VA measured at visit 3. (% predicted, IL-10: r = −0.416, p = 0.048; IL-17A: r = −0.46, p = 0.024). (C–F) Serum YKL-40 and KL-6 levels measured at visit 2 correlated negatively with FVC (L, YKL-40: r = −0.438, p = 0.022; % predicted, KL-6: r = −0.426, p = 0.024) and FEV1 (L, YKL-40: r = −0.476, p = 0.012; % predicted, KL-6: r = −0.407, p = 0.032) measured at visit 3. (G) KL-6 levels at visit 2 correlated negatively with DLCO (% predicted, r = −0.614, p = 0.001) measured at visit 3. Serum YKL-40 and KL-6 levels measured one month after the infection (visit 2) corre- lated negatively with FVC (L, YKL-40: r = -0.438, p = 0.022; % predicted, KL-6: r = −0.426, p = 0.024) and FEV1 (L, YKL-40: r = −0.476, p = 0.012; % predicted, KL-6: r = −0.407, p = 0.032) measured at visit 3 (Figure 7C–F). In addition, KL-6 levels at visit 2 correlated negatively with DLCO (% predicted, r = −0.614, p = 0.001) measured six months after recovery (Figure 7G). 4. Discussion The present study assesses the profile of Th1, Th2, Th17, pro-inflammatory cytokines, and levels of pulmonary fibrosis biomarkers in patients with COVID-19, during infection and after recovery. High concentrations of IFNG, TNFα, IL-10, IL-13, and MIP-1β were found during infection, as well as high concentrations of IL-7 and MCP-1 after recovery, in both the hospital ward and the ICU. However, the presence of some biomarkers differed between the groups during hospitalization. Specifically, patients who required admission to the ICU exhibited higher levels of cytokines related to a Th2-type response, such as IL-4, IL-5 and IL-6, while patients admitted to the ward presented high levels of innate response proinflammatory cytokines, such as IL-8 or IL-1β, but also IL-17A. A relationship was also observed between the markers of progression to pulmonary fibrosis (i.e., YKL-40 and KL-6), IL-6, IL-10, and IL-13 cytokines and mortality. Moreover, YKL-40, KL-6, IL-10 and IL-17 were predictors of lung function in these patients. Recent studies have shown an exaggerated immune response in individuals with severe COVID-19 illness [17]. These patients showed high levels of inflammatory cytokines such as IL-1β, IL-2, IL-6 IL-7, IL-8, IL-10, TNF-α, and/or GM-CSF [18]. In fact, more than 20 cytokines have been linearly associated with increased viral load and lung injury, and are considered potential biomarkers for the severity of the disease. Our reports of high levels of the cytokines mentioned above in our study population are in line with those described in the literature. However, in the present study, the response differed depending on the severity of the disease. In this regard, an increase in Th1 cytokines was observed in all patients, but the patients admitted to the ICU, and who therefore, exhibited more serious disease, had increased levels of certain Th2 response cytokines. In relation to this differential response, some studies have associated the severity of COVID-19 with a specific cytokine profile. For instance, in 41 subjects from the Wuhan region with COVID-19, Huang et al. [19] observed that infected patients presented high plasma levels of IL-1β, IFNG, and MCP-1, which likely leads to the activation of a Th1 cell profile. In addition, recent studies analyzing the immune response after vaccination observed that, in vaccinated patients, the response to infection is characterized by a Th1 profile that is associated with a better outcome in infected patients [20]. However, our findings highlighted that patients admitted to the ICU had a higher secretion of Th2-related cytokines (e.g., IL-4, IL-5, and IL-6). The specific activation of type 2 immunity has also been confirmed by other groups. Roncati et al. [21] reported that in all 15 peripheral blood samples analyzed from intensive care COVID-19 patients, cytological signals of a Th2 immune response were found, namely eosinophilia, basophilia, degranulated eosinophils, and plasma cells. In addition, after recovery from the infection, both groups of patients presented elevated levels of IL-7, a pleiotropic cytokine essential for lymphocyte survival and ex- pansion [22]. Interestingly, IL-7 shows proven efficacy as an antiviral agent and has been shown to restore lymphocyte counts and functional activity, leading to decreased viral load and clinical improvement in several life-threating viral infections. It also increases CD4 and Curr. Issues Mol. Biol. 2023, 45 2009 CD8 T-cell levels 3-fold, improves T-cell activation, and reduces levels of proinflammatory cytokines [23]. The increase observed in this cytokine may indicate a restoration of the immune system after infection. Pulmonary fibrosis is a known sequela of ARDS. In this context, early analyses of patients with COVID-19 at hospital discharge suggest that more than one-third of recovered patients develop fibrotic abnormalities [24]. The use of biomarkers in the diagnosis and prognosis of pulmonary fibrosis in these patients may be particularly interesting, given the difficulty of establishing a well-defined diagnosis in early stages of the disease. YKL-40, also known as chitinase 3-like-1, and Krebs von den Lungen-6 (KL-6) are two promising biomarkers that may play an important role in the diagnosis and prognosis of patients with interstitial lung diseases. YKL-40 is mainly secreted by macrophages, neutrophils, and epithelial cells, but also by fibroblasts and other cells [25,26]. Although the function of YKL- 40 is still debatable, there is some evidence that it has effects on fibroblasts [26,27]. KL-6 is a human mucin primarily expressed in regenerating type II pneumocytes and the bronchiolar epithelium. This glycoprotein has chemotactic and anti-apoptotic effects on fibroblasts, promoting fibroblast proliferation and the progression of pulmonary fibrosis [28,29]. In the present study, we found a possible relationship between these two biomarkers and patient mortality. Although this is an issue that has not been studied in depth, certain authors have shown that serum concentrations of KL-6 were only elevated in severely ill patients admitted to the ICU and requiring intubation and mechanical ventilation for diffuse interstitial pneumonia, but not in mild to moderately ill patients with less severe respiratory impairment [30–32]. In this context, some studies published in the literature suggest that COVID-19 patients also had higher levels of YKL-40 compared to control populations and that, within the COVID-19 population, YKL-40 was an indicator of the severity of infection, since it is linked to complications such as ICU admission [33]. Our findings also demonstrate that in these patients, YKL-40 and KL-6 levels remained el- evated during follow-up, and that these levels correlated with reduced lung function, especially FVC, FEV1, or DLCO six months after the infection. In fact, recent studies have demonstrated that COVID-19 infection can cause lung function impairment, manifested as restricted ventilation dysfunction, small airway dysfunction, and diffuse dysfunction [34]. Ferioli et al. [35] also reported that the most common six-month functional alteration ob- served after COVID-19 hospitalization was DLCO impairment, which seems to be related to the severity of acute pneumonia. In this context, a study carried out in 87 patients concluded that severely ill COVID-19 patients had higher prevalence rates of abnormal spirometry and residual fibrosis as seen in radiography when compared to patients with mild symptoms and non-severe pneumonia [36]. Thus, in these patients, special attention should be paid to the development of pulmonary fibrosis as a possible sequel to infection by the SARS-CoV-2 virus; KL-6 and YKL-40 are useful tools in this follow-up. In this study, an association was also observed between the prognosis of patients with COVID-19 infection and increased levels of certain cytokines. In particular, patients who did not survive hospitalization had higher levels of IL-6, IL-10, and IL-13. In this regard, in a study carried out in more than 1400 patients hospitalized with COVID-19 disease, Del Valle et al. [37] concluded that high serum IL-6 levels at the time of hospitalization were strong and independent predictors of patient death. Similarly, Laguna-Goya et al. [38] reported that increased IL-6 levels were predictive of mortality in these patients. As for IL-13, recently published studies also demonstrated the association of this cytokine with severe outcomes in patients with COVID-19 [39,40]. To the best of our knowledge, our study is the first to establish a negative correlation between IL-10 and IL-17 levels at the moment of the acute infection with lung function, especially DLCO/VA values, after recovery from COVID-19. However, some studies in the literature highlight the association between increased levels of IL-10 and disease severity and mortality in patients with COVID infection throughout the hospitalization period [41–43]. As for IL-17, there is no evidence of its relationship with pulmonary parameters in follow-up visits. Nevertheless, Maslennikov et al. [44] reported that during Curr. Issues Mol. Biol. 2023, 45 2010 hospitalization, patients with COVID-10 who received IL-17 antagonist treatment presented lower mortality rates and required ICU admission and additional ventilatory support less frequently. In addition, in a study carried out in 171 patients with severe COVID- 19 pneumonia, Avdeev et al. [45] concluded that anti-IL-17 therapy might mitigate the inflammatory response and improve oxygenation in these patients. This study has some limitations. The first is in relation to the follow-up study, as we were only able to perform a short follow-up time and to reevaluate 61 (in visit 2) and 44 (in visit 3) of the 81 patients initially included, mainly due to exitus. In addition, therapies to which patients were subjected during hospitalization should be recorded in clinical histories to evaluate their possible effects on the inflammatory response. Secondly, the small sample size in the present study makes it difficult to draw definitive conclusions. Third, about 40% of the patients in the two groups expressed a BMI value > 30 (Kg/m2 ); therefore, they are obese and probably have low-grade inflammation, with a higher expression of various pro-inflammatory cytokines, regardless of SARS-CoV-2 infection. Despite this fact, the number of obese people is similar in the two groups, so the observed differences can generally be attributed to SARS-CoV-2 infection. Moreover, as a single-center study, the study has limited external validity. Future multicenter studies are necessary to clarify the role of these cytokines in the severity of disease and mortality in COVID-19. In this sense, the study of biomarkers such as cytokines in COVID-19 patients has shed light on the pathogenesis of the infection of SARS-CoV-2. Nevertheless, molecular and cellular studies of the pathogenesis of this novel coronavirus are still in the early stages of research. For this reason, one of the lessons learned for the current infections is that further studies are needed to clarify the exact roles of cellular signaling pathways once SARS-CoV-2 infects its host cell, which will allow for the identification and design of better molecular drugs. In conclusion, patients with severe COVID-19 pneumonia had higher levels of Th2 cytokines such as IL-5 and IL-13. This may indicate the existence of a Th2 immune re- sponse that contributes directly to the immunopathology of the infection. Patients with mild infection showed an innate immune response activation, with IL-8 release and the involvement of Th1/Th17 lymphocytes. Increased levels of IL-6, IL-13, YKL-40, and KL-6 were associated with mortality in COVID-19 patients. Author Contributions: S.S.-D.: conceptualization, formal analysis, methodology, investigation, writing—original draft, writing—review and editing; C.G.-O.: formal analysis, methodology, writing— review and editing; M.-J.C.: conceptualization, funding acquisition, project administration, supervi- sion, writing—original draft, writing—review and editing; M.d.H.: methodology, writing—review and editing; D.E.: methodology, writing—review and editing; J.F.: writing—review and editing; O.R.: methodology, writing—review and editing; A.P.: methodology, writing—review and editing; X.M.: methodology, supervision, writing—review and editing. All authors have read and agreed to the published version of the manuscript. Funding: S.S.D. is a researcher supported by CIBER, and M.J.C is a researcher supported by the Miguel Servet Programme from the Instituto de Salud Carlos III (MSII17/00025). This project was supported by Air Liquide, Instituto de Salud Carlos III (FIS PI21/01046) and Fondo Europeo de Desarrollo Regional (FEDER). The funders had no role in the study design, data collection and analysis, the decision to publish, or the preparation of the manuscript. Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Ethics Committee (Hospital Vall d’Hebron Ethics Committee approval PR(AG)219/2020). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: Clinical data is unavailable due to privacy and ethical restrictions. Conflicts of Interest: The authors have no competing interests to declare. Curr. Issues Mol. Biol. 2023, 45 2011 References 1. Subbarao, K.; Mahanty, S. Respiratory Virus Infections: Understanding COVID-19. Immunity 2020, 52, 905–909. [CrossRef] [PubMed] 2. 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