IL-6 and cfDNA monitoring throughout COVID-19 hospitalisation are accurate markers of its outcomes

doi:10.21203/rs.3.rs-2088926/v1

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Research Article

IL-6 and cfDNA monitoring throughout COVID-19 hospitalisation are accurate markers of its outcomes

https://doi.org/10.21203/rs.3.rs-2088926/v1

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Journal Publication

published 04 May, 2023

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Background: Severe COVID-19 entails a dysregulated immune response, most likely inflammation related to a lack of virus control. A better understanding of immune toxicity, immunosuppression balance, and COVID-19 assessments could help determine whether distinct clinical presentations are driven by specific types of immune responses. The progression of the immune response and tissular damage could predict outcomes and may help in the management of patients.

Methods: We collected 201 serum samples from 93 hospitalised patients classified as moderately, severely, and critically ill. We differentiated the viral, early inflammatory, and late inflammatory phases and included 72 patients with 186 samples in separate stages for longitudinal study as well as 55 controls. We studied selected cytokines, P-selectin, and the issue damage markers lactate dehydrogenase (LDH) and cell-free DNA (cfDNA).

Results TNF-α, IL-6, IL-8, and G-CSF were associated with severity and mortality, but only IL-6 increased since admission in the critical patients and non-survivors, correlating with damage markers. The lack of a significant decrease in IL-6 levels in the critical patients and non-survivors in the early inflammatory phase (a decrease present in the other patients) suggests that these patients did not achieve viral control on days 10–16. For all patients, lactate dehydrogenase and cfDNA levels increased with severity, and cfDNA levels increased in the non-survivors from the first sample (p=0.002) to the late inflammatory phase (p=0.031). In the multivariate study, cfDNA was an independent risk factor for mortality and ICU admission.

Conclusions: The distinct progression of IL-6 levels in the course of the disease, especially on days 10-16, was a good marker of progression to critical status and mortality and could guide the start of IL-6 blockade. cfDNA was an accurate marker of severity and mortality from admission and throughout COVID-19 progression.

COVID-19

cfDNA

IL-6

Immunity

Longitudinal study

Mortality

Severity

Coronavirus disease 2019 (COVID-19) can affect multiple organs, especially when severe, and its pathogenesis includes a dysregulated response of macrophages, neutrophils and T and B cells, proinflammatory cytokine release, and a cytopathic response from the virus, inducing progressive systemic inflammation, and high neutrophil and low lymphocyte counts (1). Inflammatory response markers, such as leukocyte, neutrophil, and lymphocyte counts, C-reactive protein (CRP), ferritin, and D-dimer, are used for managing hospitalised patients.

Markers of inflammatory response, such as leukocytes, neutrophil and lymphocyte counts, C Reactive Protein (CRP), Ferritine, D-dimer, IL-6 levels and others are widely used for the management and decision making of hospitalised patients. Covid-19 patient reports show high levels of some interleukins, endothelial grow factors and other proinflammatory chemokines, as well as signaling proteins in serum (2). The controversial cytokine storm in severe disease (3, 4) have been, together with other complications, especially lymphopenia, have been associated with an elevated risk of ARDS and multiple organ failure (5). T-cell exhaustion due to viral persistence, together with the impaired action of interferons produced by the virus, results in immunodepression and viral control failure, with additional inflammatory responses by Damage-Associated Molecular Patterns (DAMPs) released from tissue damage (6). Longitudinal studies during disease progression can be helpful in better understanding the immune toxicity and immunosuppression balance (7), especially when immune response inhibitors are a therapeutic option.

Since the beginning of the pandemic, the time of evolution has been considered important for prognostic and therapeutic measures. An approximately 7-day period has been theorized from symptom onset, characterized by the presence and shedding of virus (viral phase), followed by decreased shedding and increased inflammation (early inflammatory phase), in which the disease tends to worsen. If the inflammation and unbalanced immune response progress beyond 16 days (late inflammatory phase), severe lung/systemic disorders leading to critical disease and death can occur (8).

We conducted an observational, longitudinal, prospective study of a cohort of hospitalised patients with varying severity during the first COVID-19 pandemic wave and included controls. We examined clinical data, immune cell counts, proinflammatory cytokine levels, inflammatory markers, and tissue damage-related molecules to determine their role in predicting outcomes and improving patient management. Our hypotheses were a) different immune responses correlate with different degrees of severity and b) the progression of certain components of the immune response and of tissular damage throughout the course of the disease can be markers of favorable or unfavorable outcomes and could guide the use of certain therapies.

Patients and controls

In April and May 2020, symptomatic patients hospitalised with COVID-19 demonstrated by polymerase chain reaction or nasopharyngeal swab were recruited. The exclusion criteria were concomitant infection on admission or during hospitalization, refusal to sign informed consent, and significant immunosuppression (transplant recipients, hematologic neoplasms, chemotherapy, prednisone equivalent ≥ 20 mg/day). Based on their Chinese Center for Disease Control and Prevention classification (CCDC score) (9) and the World Health Organization Ordinal Scale (WHO OS) (10), the patients were grouped according to severity as follows: moderately ill (MI), severely ill (SI), and critically ill (CI).

After recording the date of symptom onset on admission to the hospital, we considered 3 phases: viral (1–9 days from symptom onset), inflammatory (10–16 days from symptom onset), and late inflammatory (> 16 days from symptom onset). The samples were obtained from blood requested for healthcare reasons. Patients with at least 2 blood samples in 2 consecutive phases were included in the longitudinal study.

We measured proinflammatory cytokines from the early innate immune response (TNF-α, IL-1β, IL-6), related to neutrophil activation and recruitment (IL-8, G-CSF), and with T-cell response (IL-17A, IFN-γ); endothelial damage marker P-selectin; and tissue damage markers LDH and cell-free DNA (cfDNA).

We selected 55 non-hospitalised controls without any infection, of similar age and chronic pathologies as the patients, all of whom underwent routine laboratory tests. All met the same exclusion criteria as the patient group. To compare the three dependent groups (severity groups or the three disease progression phases), we would need a total sample size of 100 (33 by group).

Blood samples

Blood was collected in anticoagulant EDTA tubes and immediately subjected to hematological analysis (complete blood count and D-dimer levels). Blood was also collected in serum separator tubes containing clot activator and serum separator gel. Serum samples were analyzed and included the following biomarkers: ferritin, LDH, IL-6, CRP, and procalcitonin. The remaining serum was stored at 4°C for up to 24 h before separation into small aliquots and stored at − 80°C until testing for cytokines, P-selectin, and cfDNA.

Cytokines and P-selectin

Serum cytokines (except IL-6) and P-selectin were quantified using a bead-based multiplex immunoassay (LXSAHM-07) according to the manufacturer’s instructions. Cytokines were quantified using a LABScan 100 flow analyzer (Luminex Corporation). Data were analyzed with xPONENT software.

Cell-free DNA

To quantify the circulating serum cfDNA, DNA was first purified using the ChargeSwitch gDNA 1 mL Serum Kit following the manufacturer’s procedure, using 100 µL of sample and adjusting the reactant quantity to that volume. After purification, the DNA was quantified using the Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen P7589). After diluting the sample to 1/5 in TE buffer, PicoGreen reagent was added in a 1:1 ratio. After a 5-min incubation at room temperature in the dark, the sample’s fluorescence was measured using a Synergy HT reader (BioTek) (excitation 485 nm, emission 528 nm). cfDNA concentrations were calculated using Microsoft Excel with the standard provided in the kit.

Statistical analysis

Data are presented as mean (standard deviation) or median (interquartile range), according to normal criteria (Shapiro-Wilks test) and analyzed with Mann-Whitney U, Kruskal-Wallis, Student’s or ANOVA tests, as appropriate. Pearson’s correlation coefficient was used to assess the relationship between biomarkers and clinical variables. The various biomarkers’ predictive power for different outcomes was analyzed using receiver operating characteristic (ROC) analysis.

For the longitudinal study (72 patients, 180 samples), a Wilcoxon signed-rank test was performed.

Univariate/multivariate logistic regression models were performed for specific outcomes, adjusting for age > 60 years, male sex, hypertension, obesity, diabetes, IL-6 levels, and corticosteroid therapy. P-values < 0.05 were considered statistically significant using R version 4.0.5 (R Core Team 2021) software.

Patients and controls

We collected 201 samples from 93 patients, 72 of whom had samples (180) in at least 2 disease progression stages. Table 1 show the distribution on the day of sample extraction. Twelve of the patients required admission to the intensive care unit (ICU) and 19 died.

Table 1. Distribution of the day of sample extraction

Viral phase

(1–9 days)

N=87

Early inflammatory

(10–16 days)

N=53

Late inflammatory

(>16 days)

N=40

Days from symptom onset

6.00 [5.00; 8.00]

12.00 [11.00; 14.00]

20.00 [18.00; 24.25]

Table 2 presents the patients’ information according to severity and samples at each stage. There were no statistically significant differences in the patients’ and controls’ demographics and comorbidities (Table 3).

Table 2. Number of patients in each severity group and number of samples of the patients followed longitudinally, according to time from symptom onset. Abbreviations: CCDC score: Chinese Center for Disease Control and Prevention classification; WHO OS: World Health Organization Ordinal Scale

CCDC scale	1				2				3				TOTAL
Patients (n)	51				15				27				93
WHO OS	8	7		6			5	4		3	2	1	TOTAL
Patients (n)	19	5		1			20	41		7	0	0	93
Illness onset			1–9 days			10–16 days				≥17 days			TOTAL
93 patient samples (n)			97			59				45			201
72 patient samples (n)			87			53				40			180

Table 3. Demographics and comorbidities of the cases and controls

		Patients N=93	Controls N=55	P
Sex	Female	51 (54.84%)	30 (54.55%)	1.000
Sex	Male	42 (45.27%)	25 (45.45%)	1.000
Age (years)		69.00 [55.00; 78.00]	71.00 [57.00; 79.00]	0.441
Hypertension		45 (48.39%)	17 (30.91%)	0.056
Diabetes		28 (30.11%)	12 (21.82%)	0.365
Obesity		13 (13.98%)	4 (7.27%)	0.332
Heart disease		14 (15.05%)	6 (10.91%)	0.643
Chronic respiratory disease		16 (17.20%)	3 (5.45%)	0.070
Liver disease		3 (3.23%)	0 (0.00%)	0.295
Renal disease		8 (8.60%)	6 (10.91%)	0.863
Dementia		18 (19.35%)	4 (7.27%)	0.079
Dyslipidemia		17 (18.28%)	17 (30.91%)	0.118

Advanced age, male sex, and obesity were associated with greater inflammatory responses and tissue damage (Additional file 1 and Supplementary table 1, Additional file 2). In the multivariate study, obesity was a risk factor for a critical condition (odds ratio [OR] 9.25, p=0.019) and ICU admission (OR 46.21, p=0.008) (Additional file 1 and Additional file 3, Supplementary table 2). Lymphopenia was always related to severity/mortality and correlated with tissue damage markers. Lymphocyte count declined with mortality and as severity progressed (Additional file 1, Additional file 4, Supplementary table 3; Additional file 5, Supplementary table 4; Additional file 6, Supplementary table 5, and Additional file 7, Supplementary table 6).

We observed higher G-CSF, IL-6, and cfDNA levels in the patients than the controls, starting from the first sample. However, there were no statistically significant differences in TNF-α, IL-1β, IL-8, and IL-17A levels in the patients and controls, and even higher levels were observed in the controls when comparing them with only the first sample of patients (p<0.05) (Table 4); however, all cytokine levels increased during disease progression. Additional file 8, Supplementary figure 1 shows a graphical representation of the correlations between the biomarkers in the 3 phases of the disease. Additional file 9, Supplementary Table 7 shows a comparison of biomarkers in the 3 severity groups (CCDC score).

Table 4. Comparison of biomarkers between patients and controls for all samples and for only the first sample after admission. Abbreviations: TNF-a: Tumor necrosis factor-a; IL-8: Interleukin-8; IL-1β: interleukin-1b; IFN-γ: interferon- γ; IL-17A: interleukin 17A; G-CSF: Granulocyte colony-stimulating factor; IL-6: Interleukin-6; cfDNA: cell free DNA

All samples	Patients N=201	Controls N=55	p-
TNF-α (pg/mL)	40.02 [34.83; 47.41]	41.07 [38.56; 44.99]	0.156
IL-8 (pg/mL)	54.29 [40.43; 89.22]	56.21 [43.26; 107.75]	0.412
IL-1β (pg/mL)	55.90 [47.80; 66.92]	59.91 [54.04; 62.24]	0.238
IFN-γ (pg/mL)	145.84 [123.72; 176.59]	134.60 [128.65; 142.43]	0.004
IL-17A (pg/mL)	19.40 [14.73; 23.90]	21.31 [18.48; 21.31]	0.204
P-Selectin (ng/mL)	55.48 [42.12; 73.30]	77.44 [67.55; 84.99]	<0.001
G-CSF (pg/mL)	143.97 [123.70; 159.45]	130.47 [124.32; 138.97]	<0.001
IL-6 (pg/mL)	20.41 [4.34; 51.62]	7.80 [5.15; 10.42]	0.004
cfDNA (ng/mL)	7.87 [4.45; 14.40]	2.56 [1.71; 3.61]	<0.001
1^st samples	Patients N=93	Controls N=55	p
TNF-α (pg/mL)	38.51 [32.58; 45.34]	41.07 [38.56; 44.99]	0.013
IL-8 (pg/mL)	47.45 [33.71; 66.16]	56.21 [43.26; 107.75]	0.010
IL-1β (pg/mL)	51.66 [43.09; 59.90]	59.91 [54.04; 62.24]	<0.001
IFN-γ (pg/mL)	134.40 [119.97; 159.07]	134.60 [128.65; 142.43]	0.846
IL-17A (pg/mL)	18.48 [10.79; 22.80]	21.31 [18.48; 21.31]	0.001
P-Selectin (ng/mL)	52.21 [35.63; 71.42]	77.44 [67.55; 84.99]	<0.001
G-CSF (pg/mL)	142.57 [120.38; 162.04]	130.47 [124.32; 138.97]	0.041
IL-6 (pg/mL)	30.52 [6.26; 62.51]	7.80 [5.15; 10.42]	<0.001
cfDNA (ng/mL)	7.68 [4.23; 14.49]	2.56 [1.71; 3.61]	<0.001

Cytokines and tissue damage markers

There were higher levels of cfDNA, TNF-α, IL-8, G-CSF, and especially IL-6 in the CI group (as measured by both scales) and non-survivors (Table 5). The median IL-6 values did not exceed the limit of 40 pg/mL at any time during disease progression for the MI, SI, and survivor groups, while the values remained above this limit for the CI and non-survivor groups (Figure 1). IL-6 was the only cytokine studied that correlated with the tissue damage markers LDH and cfDNA. Additional file 4, Supplementary table 3, shows the relationship between biomarkers and respiratory severity parameters.

Table 5. Comparisons of interleukin-6 and cfDNA levels according to severity and between survivors and non-survivors.

		Severe and Critical	Moderate	p
CCDC scale	IL-6 (pg/mL)	32.44 [5.84; 104.03]	9.00 [2.76; 33.84]	<0.001
CCDC scale	cfDNA (ng/mL)	9.44 [6.15; 20.19]	6.21 [3.46; 10.44]	<0.001
WHO OS	IL-6 (pg/mL)	32.44 [5.69; 99.94]	9.00 [2.90; 33.14]	<0.001
WHO OS	cfDNA (ng/mL)	9.08 [5.54; 19.38]	6.88 [3.61; 10.73]	0.001
		Critical	Moderate and Severe	p
CCDC scale	IL-6 (pg/mL)	59.48 [21.37; 175.20]	10.06 [3.10; 34.21]	<0.001
CCDC scale	cfDNA (ng/mL)	14.11 [7.13; 22.67]	7.01 [4.01; 10.93]	<0.001

		Survivors	Non-survivors	p
Total samples (n=201)	IL-6 (pg/mL)	11.14 [3.49; 39.23] n= 158	52.49 [21.37; 152.90] n=43	<0.001
Total samples (n=201)	cfDNA (ng/mL)	7.06 [4.12; 11.40] n=158	14.98 [7.42; 25.74] n=43	<0.001
1st sample (n=93)	IL-6 (pg/mL)	25.91 [5.77; 51.55] n=74	66.91 [38.38; 162.70] n=19	0.001
1st sample (n=93)	cfDNA (ng/mL)	6.87 [4.01; 10.81] n=74	14.98 [7.73; 22.51] n=19	0.002

In our longitudinal study, we observed a statistically significant decrease (p=0.021) in IL-6 levels from days 10–16 (10.38 [2.59; 31.52]) versus days 1–9 (29.11 [6.49; 58.41]) (Table 6). A similar statistically significant decrease (p=0.001) in IL-6 levels was observed on days 10–16 (5.28 [1.50; 23.10]) vs. days 1–9 (27.27 [5.78; 51.08]) in the survivors but not in the non-survivors (Figure 1 and Additional file 10, Supplementary Table 8). We also analyzed the IL-6 levels through the COVID-19 progression phases according to severity: per the CCDC score, there was a 7-fold and 3-fold decrease in MI (p=0.006) and SI groups, respectively, for days 1–9 versus days 10–16. Per the WHO OS, there was a 5-fold and 4-fold decrease in the MI (p=0.007) and SI (p=0.049) groups, respectively (Figure 1). This IL-6 decrease was maintained in the late inflammatory phase in the MI, SI and survivor groups. In contrast, the CI group (WHO OS) presented a clear increase in IL-6 in the late inflammatory phase (152.8 [12.88; 447.90]). In the SI group, the statistically significant IL-6 decrease in the early inflammatory phase coincided with normalization of their initial lymphopenia, in contrast to the CI group.

Table 6. Comparison of biomarkers during the three disease progression phases. Abbreviations: N/L ratio: neutrophils/lymphocytes ratio; CRP: C-reactive protein; PCT: procalcitonin; LDH: lactate dehydrogenase; TNF-a: Tumor necrosis factor-a; IL-8: Interleukin-8; IL-1β: interleukin-1b; IFN-γ: interferon- γ: IL-17A: intereleukin-17A; G-CSF: Granulocyte colony-stimulating factor; IL-6: Interleukin-6; cfDNA: cell free DNA; SaO2/ FiO2: oxygen saturation/fraction of inspired oxygen; SaO2: oxygen saturation.

	Viral phase (1) N=87	Early inflammatory (2) N=53	Late inflammatory (3) N=40	p	p 1 vs 2	p 1 vs 3	p 2 vs 3
Leukocytes/mm³	7000 [5300;9050]	8000 [6400;11400]	8200 [6450;11800]	0.034	0.092	0.056	0.582
Neutrophils/mm³	5100 [3350;6950]	6000 [4400;8700]	6050 [4100;8225]	0.069	0.119	0.119	0.874
Lymphocytes/mm³	1000 [650;1400]	1000 [700;1600]	1150 [675;1900]	0.705	0.858	0.858	0.858
N/L ratio	5.12 [2.71;9.11]	6.02 [2.61;14.35]	4.96 [2.74;11.03]	0.700	0.836	0.836	0.836
Platelet/mm³	234000 [167500;285500]	278000 [197000;367000]	227000 [186000;278250]	0.030	0.028	0.667	0.114
CRP (mg/L)	50.00 [17.70;108.05]	25.10 [9.40;74.60]	17.00 [3.08;51.45]	0.004	0.032	0.011	0.261
PCT (ng/mL)	0.08 [0.05;0.16]	0.07 [0.04;0.12]	0.08 [0.04;0.23]	0.415	0.564	0.620	0.620
LDH (U/L)	294.50 [223.25;385.25]	274.00 [201.00;345.00]	232.00 [173.00;327.25]	0.127	0.362	0.135	0.362
D-Dimer (µg/L)	865.00 [434.00;1464.00]	855.50 [495.25;1597.75]	698.50 [345.50;1951.25]	0.776	0.998	0.848	0.848
Ferritin (ng/mL)	445.00 [219.80;620.90]	647.50 [321.67;945.40]	397.00 [248.50;726.10]	0.107	0.103	0.808	0.343
TNF-α (pg/mL)	36.40 [32.80;43.59]	44.28 [38.81;49.81]	41.11 [37.36;48.52]	<0.001	0.001	0.010	0.381
IL-8 (pg/mL)	52.01 [34.96;68.72]	55.52 [45.64;91.01]	77.32 [50.36;106.06]	0.002	0.048	0.002	0.108
IL-1β (pg/mL)	50.63 [43.09;61.88]	60.12 [54.10;69.95]	64.34 [53.61;69.23]	<0.001	<0.001	<0.001	0.954
IFN-ʏ (pg/mL)	131.17 [116.20;158.99]	164.89 [143.24;179.26]	157.76 [134.66;188.20]	<0.001	<0.001	0.001	0.578
IL-17A (pg/mL)	18.48 [10.79;22.80]	21.69 [18.71;28.26]	23.90 [15.45;24.77]	<0.001	<0.001	0.001	0.714
P-Selectin (ng/mL)	47.42 [34.91;60.86]	65.42 [49.03;80.14]	64.95 [51.05;79.88]	<0.001	<0.001	<0.001	0.842
G-CSF (pg/mL)	139.08 [120.98;160.64]	147.85 [129.84;162.19]	148.79 [132.43;157.64]	0.478	0.488	0.488	0.964
IL-6 (pg/mL)	29.11 [6.49;58.41]	10.38 [2.59;31.52]	10.06 [3.20;50.89]	0.024	0.021	0.190	0.552
cfDNA (ng/mL)	6.40 [3.61;13.99]	7.87 [5.34;14.65]	10.53 [5.56;17.30]	0.041	0.200	0.043	0.200
SaO₂/FiO₂	444.50 [365.00;460.75]	429.00 [339.00;457.00]	330.50 [170.75;467.75]	0.832	0.938	0.938	0.938
SaO₂	94.00 [88.50;96.00]	90.00 [87.00;95.00]	93.00 [88.00;95.00]	0.035	0.057	0.109	0.466

Serum IL-1β, IFN-γ, and IL-17A levels had no relationship with severity. IL-8, G-CSF, IL-6, and cfDNA were associated with mortality from the first sample onwards (Table 7).

Table 7. Comparison of biomarkers between survivors and non-survivors in the first sample. Abbreviations: N/L ratio: neutrophils/lymphocytes ratio; CRP: C-reactive protein; PCT: procalcitonin; LDH: lactate dehydrogenase; TNF-a: Tumor necrosis factor-a; IL-8: Interleukin-8; IL-1β: interleukin-1b; IFN-γ: interferon- γ: IL-17A: intereleukin-17A; G-CSF: Granulocyte colony-stimulating factor; IL-6: Interleukin-6; cfDNA: cell free DNA; SaO2/ FiO2: oxygen saturation/fraction of inspired oxygen; SaO2: oxygen saturation.

	Survivors N=74	Non-survivors N=19	p
Leukocytes/mm³	7200 [5425;8775]	9800 [6600;13150]	0.028
Neutrophils/mm³	5050 [3725;6550]	8400 [4950;11750]	0.009
Lymphocytes/mm³	1200 [800;1600]	700 [532.50;800]	0.001
N/L ratio	4.46 [2.51;7.72]	13.50 [6.75;20.95]	0.001
Platelet/mm³	245000 [168750;279750]	228000 [192000;327000]	0.675
CRP (mg/L)	33.90 [11.70;95.10]	104.10 [59.20;197.00]	0.008
PCT (ng/mL)	0.07 [0.04;0.11]	0.14 [0.08;0.60]	0.025
LDH (U/L)	255.00 [208.50;366.50]	323.00 [237.50;403.50]	0.223
D-Dimer (µg/L)	828.50 [471.75;1378.50]	1533.50 [1009.75;2671.00]	0.009
Ferritin (ng/mL)	427.30 [176.00;623.90]	491.70 [392.35;963.60]	0.110
TNF-α (pg/mL)	37.84 [31.76;44.02]	40.91 [32.95;49.72]	0.194
IL-8 (pg/mL)	42.11 [33.18;56.48]	61.83 [52.88;89.06]	0.016
IL-1β (pg/mL)	50.63 [43.09;58.71]	53.75 [45.44;65.57]	0.314
IFN-ʏ (pg/mL)	132.22 [119.97;154.89]	144.93 [117.45;166.73]	0.737
IL-17A (pg/mL)	15.67 [10.79;22.80]	19.40 [13.35;22.53]	0.287
P-Selectin (ng/mL)	49.25 [35.63;71.35]	53.59 [36.85;69.489]	0.900
G-CSF (pg/mL)	134.22 [118.12;153.99]	160.09 [139.92;184.10]	0.012
IL-6 (pg/mL)	25.91 [5.77;51.55]	66.91 [38.36;162.70]	0.001
cfDNA (ng/mL)	6.87 [4.01;10.81]	14.98 [7.73;22.51]	0.002
SaO₂/FiO₂	452.00 [425.50;462.00]	380.00 [323.00;416.50]	0.003
SaO₂ (%)	95.00 [90.00;97.00]	85.00 [75.50;86.50]	<0.001

The MI group had a statistically significant increase in TNF-α, IL-8, IL-1β, IFN-γ, IL-17A, and P-selectin levels from the viral phase to the early/late inflammatory phase but not from the early to the late inflammatory phases. The SI group had stable levels while the CI group had decreased levels, unlike the situation with the IL-6 levels.

IL-6 levels correlated significantly with LDH throughout the 3 disease progression phases, in the 3 severity groups (See Additional file 11.docx, Supplementary Table 9), and with cfDNA in the early inflammatory phase, showing significantly higher levels from the first sample onwards in the CI and non-survivors. In our ROC analysis, the area under the curve (AUC) for an IL-6 concentration of 59.13 in the first sample for predicting death was 0.7561 (sensitivity 0.6875, specificity 0.7916) (Figure 2).

LDH levels increased as severity increased, but unlike IL-6 and cfDNA, LDH was not related to mortality in the first sample (Table 7) and only showed higher levels in the late phase of the non-survivors (p=0.001). LDH, IL-6, CRP, and cfDNA levels increased in the patients with baseline SaO₂ <93%, SaO₂/FiO₂<315, and with radiological infiltrates in >50% of the lung fields (Additional file 4, Supplementary table 3).

cfDNA levels were significantly higher in the CI group than in the MI (p<0.001) and SI groups (p=0.004) (according to the CCDC score) and were higher in the SI and CI groups than in the MI group of WHO OS (p=0.001) (Table 8) and non-survivors, starting with the first sample after admission (p=0.002) (Table 5). Along with neutrophil count, lymphopenia, N/L ratio, and CRP, cfDNA was the only persistent and significantly higher biomarker in the non-survivors during the 3 phases of the disease (Table 9). In the late inflammatory phase, median cfDNA levels were quadruple the initial values (p=0.031) in the non-survivors, remaining stable in the survivors (Table 8). In the CI group, cfDNA levels were double those of the MI and SI groups (Additional file 9, Supplementary Table 7), during the entire disease progression and were correlated with hospital stay for the survivors (r=0.311, p=0.000).

Table 8. cfDNA according to severity (Chinese Center for Disease Control and World Health Organization scales) and mortality and its correlation with interleukin-6 and lactate dehydrogenase. (N=samples).

Severity	cfDNA (ng/mL)	p
CCDC scale		<0.001
Moderate (N=105)	6.42 (3.49–10.48)
Severe (N=38)	7.47 (5.32–13.37)
Critical (N=58)	14.92 (7.18–24.68)
Critical vs. moderate		<0.001
Critical vs. severe		0.004
WHO OS		0.001
Moderate; N=102	6.97 (3.76–10.83)
Severe/Critical; N=99	9.36 (5.56–19.60)
Mortality	cfDNA (ng/mL)	p
Non-survivors N=39		0.021
Viral (1–9 days); N=17	7.87 [5.52–22.38]
Early inflammatory (10–16 days); N=11	12.59 [7.88–26.36]
Late inflammatory (>17 days); N=11	30.34 [18.47–39.39]
Viral phase vs late inflammatory		0.031
Survivors N= 141		0.328
Viral (1-9 days); N=70	5.98 (3.12–11.45)
Early inflammatory (10-16 days); N=42	7.11 (4.59–10.60)
Late inflammatory (>17 days); N=29	7.83 (4.65–12.18)
Correlation cfDNA with IL-6 and LDH	r	p
IL-6
Viral (1–9 days)	0.12, (-0.104–0.332)	0.294
Early inflammatory (10–16 days)	0.468 (0.192–0.672)	0.002
Late inflammatory (>17 days)	-0.005 (-0.348–0.339)	0.977
LDH
Viral (1–9 days)	0.296 (0.079–0.486)	0.009
Early inflammatory (10–16 days)	0.376 (0.115–0.589)	0.006
Late inflammatory (>17 days)	0.294 (-0.024-0.558)	0.069

Table 9. Comparison of biomarkers between survivors and non-survivors in the 3 phases of the disease. Abbreviations: N/L ratio: neutrophils/lymphocytes ratio; CRP: C-reactive protein; PCT: procalcitonin; IL-6: Interleukin-6; cfDNA: cell free DNA; LDH: lactate dehydrogenase.

Viral phase (1-9 days) N=97	Survivors N=78	Non-survivors N=19	p
Neutrophils/mm³	4500 [3150;6600]	7000 [4600;10550]	0.011
Lymphocytes/mm³	1200 [800;1600]	600 [450;800]	<0.001
N/L ratio	4.25 [2.10;7.49]	13.50 [6.75;25.85]	<0.001
CRP (mg/L)	38.0 [12.33;93.83]	95.00 [59.20;153.40]	0.047
Ferritin (ng/mL)	406.00 [176.00;569.50]	558.90 [460.75;1046.17]	0.015
IL-6 (pg/mL)	27.27 [5.78;51.08]	57.27 [31.73;98.75]	0.039
cfDNA (ng/mL)	6.11 [3.48;11.45]	7.87 [5.08;22.21]	0.037
Early inflammatory (10-16 days) N=59	Survivors N=48	Non-survivors N=11	p
Leukocytes/mm³	7500 [6475;8825]	12600 [8900;16250]	0.004
Neutrophils/mm³	5600 [4275;7000]	11400 [7650;14550]	<0.001
Lymphocytes/mm³	1200 [775;1800]	700 [400;800]	0.002
N/L ratio	4.40 [2.39;9.06]	17.14 [15.59;24.93]	<0.001
CRP (mg/L)	20.30 [5.65;41.20]	72.25 [38.75;128.12]	0.004
PCT (ng/mL)	0.05 [0.04;0.11]	0.12 [0.07;0.21]	0.023
D-Dimer (µg/L)	705.50 [469.50;1020.75]	3256.50 [1292.25;4987.75]	0.014
IL-6 (pg/mL)	5.28 [1.50;23.10]	49.12 [26.78;214.49]	0.001
cfDNA (ng/mL)	7.11 [4.46;9.75]	12.59 [7.88;26.36]	0.008
Late inflammatory (>16 days) N=45	Survivors N=32	Non-survivors N=13	p
Leukocytes/mm³	7400 [6300;10250]	9800 [8700;18700]	0.003
Neutrophils/mm³	5250 [4075;6625]	8400 [6500;16400]	0.001
Lymphocytes/mm³	1300 [800;2300]	600 [400;1100]	0.002
N/L ratio	3.82 [2.55;6.19]	15.50 [7.64;41.00]	<0.001
CRP (mg/L)	9.40 [1.75;19.70]	236.50 [138.15;459.38]	<0.001
PCT (ng/mL)	0.06 [0.04;0.09]	0.34 [0.26;0.88]	<0.001
LDH (U/L)	199.00 [170.50;275.50]	341.50 [298.75;446.00]	0.001
D-Dimer (µg/L)	692.00 [336.50;1619.50]	2392.00 [1525.00;2925.50]	0.020
cfDNA (ng/mL)	8.35 [4.91;12.94]	24.62 [19.21;39.06]	<0.001

The correlation between cfDNA and LDH was not robust (Table 8), and cfDNA correlated better than LDH with common severity markers (neutrophilia, lymphopenia, CRP, SaO₂, SaO₂/FiO₂), especially in the CI group and late inflammatory phases (e-Figure 1). The ROC analysis showed a mortality AUC of 0.7399 for cfDNA in the first sample (sensitivity 0.6111, specificity 0.8260) (Figure 2).

cfDNA was the only biomarker that was a independent risk factor for ICU admittance (OR 1.22, p=0.025) and mortality (OR 1.08, p=0.014) (Additional file, Supplementary table 2).

Therapies

Of the 93 patients, only 6 received tocilizumab, 4 received remdesivir, and 29 received corticosteroids, the latter of whom showed a higher degree of severity according to the CCDC (p=0.025) and WHO (p=0.008) scales but were not associated with lower in-hospital mortality (p>0.05). Samples obtained in the early viral (and inflammatory phase) of those treated with corticosteroids showed clinical and analytical parameters of greater severity than those not treated (Additional file 12, Supplementary Table 10), while no differences were observed after day 17 of progression between the two groups. In the multivariate model, taking corticosteroids was an independent risk factor for pneumonia (OR 4.55, p=0.034) and extension of infiltrates in >50% of lung fields (OR 4.87, p=0.025) (Additional file 3, Supplementary table 2).

Our main finding was the demonstration of the usefulness of cfDNA levels as markers of critical status and mortality in patients hospitalised for COVID-19 from admission and throughout the course of the disease. cfDNA also correlated with hospital stay in survivors.

Another finding was that IL-6 was the only cytokine studied that correlated with tissue damage markers. IL-6 levels throughout hospitalization differed completely between the critically ill and non-survivor patients on one hand and the rest of the patients on the other. This could help identify patients who will progress to more severe forms and mortality, especially between days 10 and 16 from symptom onset and those who would benefit from IL-6 blockade.

LDH, which is commonly used clinically as a marker of tissue damage, showed variations parallel to those of IL-6 and was related to severity, although its correlation with standard severity markers was clearly lower than that of cfDNA.

cfDNA is a tissue damage marker released after cell destruction and, like LDH, acts as a DAMP (11), contributing to cytokine production, apoptosis, and tissue damage via Toll-like receptor 9, and is attenuated with specific Toll-like receptor 9 inhibitors. In healthy individuals, cfDNA is present in the circulation in small amounts (12), has a short life (13), and is derived primarily from hematopoietic cells. cfDNA, including nuclear and mitochondrial-derived cfDNA, is released following apoptosis and necrosis and is secreted by cells (14). Elevated cfDNA levels indicate disease before clinical manifestations and histopathological changes (15). The main sources of cfDNA in hospitalised COVID-19 patients are hematopoietic cells, vascular endothelium, hepatocytes, adipocytes, and kidney, heart, and lung cells (15). Non-hematopoietic cell derivative levels are 10–1000 times higher in COVID-19 patients than in healthy individuals, with levels up to 11 times higher than in hospitalised patients with influenza or respiratory syncytial virus (15). We found elevated cfDNA levels in the COVID-19 patients, with a significant correlation with the standard parameters of severity (15–17). As in other studies, our non-survivor group also showed higher cfDNA levels in the first sample after admission (6, 15, 17, 18) and thereafter. cfDNA was the only biomarker whose concentrations remained higher in these patients during the 3 phases of the disease, increasing steadily (especially in the late inflammatory phase), quadrupling its initial values while remaining stable in survivors. The sustained increase in cfDNA levels also significantly predicted disease progression (6). cfDNA was therefore the marker best related to severity and mortality, tissue damage, and outcomes in COVID-19 and was an independent risk factor for ICU admission and mortality, as another study showed for severity (15). At admission, cfDNA especially identified the patients at risk for critical illness and death.

In our longitudinal study, non-critical and surviving patients did not present median IL-6 values higher than 40 pg/mL at any time during their progression. In these patients, there was an important, sustained, and significant decrease in IL-6 levels on days 10–16, which was not observed in the CI patients and non-survivors, in whom the levels remained elevated or increased further. One study associated patients with baseline IL-6 concentrations above 40 pg/mL with an increased likelihood of disease progression (19). There is increasing evidence of the importance of achieving viral control for a favorable disease evolution (20, 21), and of an association between the persistence of a high viral load in respiratory samples (22, 23) and in plasma (24, 25), with mortality and other unfavorable outcomes. It has been observed that at week 1 of evolution there were no differences in viral load between ICU-ventilated and non-ventilated patients, but the viral load decreased at week 2 in non-ventilated patients, while it remained high in ventilated patients (26). One study showed that viral clearance occurred around day 10 in 90% of non-severe cases, and remained positive in the most severe patients (27). Although the gold standard for virus viability is its culture, one of the few studies available confirmed a coincidence of viable virus with high viral loads within the first 10 days (18). There is also evidence of an association between respiratory cell infection with the release of large amounts of IL-6, which was halted with Remdesivir (28), and of a relationship between RNAaemia with increased levels of IL-6 (29) and lastly of a correlation of IL-6 levels and viral load in critically ill patients (30, 31). The scarce longitudinal data on cytokines in COVID-19 patients include a decrease in IL-6 in survivors (32), in other proinflammatory cytokines by day 16 (33), and in IL-6 two days after convalescent plasma transfusion (34). Viral loads correlated with elevated cytokines, declining steadily in the MI, especially after day 10 (35). We found a decreased IL-6 levels on days 10–16, suggesting an earlier viral control in our less ill patients. In critical patients and non-survivors, persistent infection would lead to more prolonged inflammation (IL-6), neutrophil activation (G-CSF and IL-8), and tissue damage (cfDNA). The exclusion criteria included concomitant infection during evolution, therefore no patient included in the study showed clinical, analytical or radiological changes attributable to nosocomial infection and the differences in IL-6 levels could not be attributed to this circumstance.

The correct selection of patients who will benefit from treatment with IL-6 blockade (8, 36–38) and its timing decreases the probability of its low utility (39–41); however, inadequate immunosuppression can also impair virus clearance (42), increase the selection of variants of concern (43), and increase the risk of infections (44). A decrease in anti-SARS-CoV-2 neutralizing antibody activity has been reported in critical patients treated with IL-6 and IL-1 inhibitors who recovered (45). IL-6 blocking has been recommended in severely and critically ill hospitalised patients with elevated inflammatory markers, especially CRP > 75 mg/L (46, 47). Studies have reported that treatment is more effective when started early (7, 31, 36, 48). Our study suggests that increased IL-6 levels > 40 pg/mL are related to a higher mortality risk. The lack of an at least 3-fold decrease in IL-6 from an elevated baseline on days 10–16 could indicate persistent infection and the need to start IL-6 blockade, perhaps in association with antiviral therapy, regardless of a low severity as assessed by clinical criteria. Although several Covid-19 phenotypes have been proposed, the 3 disease phases included in the study were proposed at the beginning of the pandemic, at the time of our study. However, the importance of the time course of the disease persists, for prognostic and therapeutic purposes.

LDH, the other tissue damage marker, is related to intracellular infection, with the release of proteins and cytoplasmic material and DNA fragmentation. LDH is a marker of tissue damage, especially in the lungs, heart, and hematopoietic cells (8). The correlations and parallelism of IL-6 and LDH that we found (Additional file 11, Table 9) suggest that the decrease in LDH in less severely ill patients (less inflammation and tissue damage), occurs after viral control is achieved. The IL-6/LDH association appeared to better reflect the inflammatory situation at various disease stages, probably as a function of viral control, while cfDNA probably more broadly reflected tissue damage (6) and is therefore more related to severity and mortality. The association between SARS-CoV-2 viral load in plasma and immune response dysregulation with increased proinflammatory cytokines (IL-6), markers of tissue damage (LDH, GPT), and critical illness has been demonstrated (43). However, the relationship of LDH with severity and mortality was clearly less strong than that of cfDNA.

A discussion of the relationship between comorbidities, lymphopenia, CT CD4+ -derived cytokines, macrophages, Pathogen Associated Molecular Patterns (PAMPs), Damage Associated Molecular Patterns (DAMPs), and the citokine storm and corticosteroids, severity and mortality can be found in Additional file 13.

Our study has several strengths. There have been few studies of proinflammatory cytokines and markers of tissue damage throughout the progression of COVID-19 patients. Longitudinal studies can monitor infection response dysregulation and observe its trend (4). Changes in these parameters reveal disease dynamics and show a course towards recovery or worsening (6). As far as we know, ours is the first study combining these parameters with those used in the clinical management of hospitalised COVID-19 patients, according to survival and the varying severity and across the various phases of the disease.

Our study also has certain limitations. The cohort was recruited from a single hospital, was small and did not include COVID-19-related coagulation disorders. Problems in assessing cytokine levels included difficulties distinguishing a vigorous beneficial immune response from a dysregulated reaction, their short half-life, and the lack of thresholds to consider an increase as abnormal (4). Whether the primary problem is immune hyperactivity or a failure to resolve the inflammatory response due to persistent viral replication is unclear; it is likely that both were involved. Another limitation is that we could not measure the evolution of viral loads in respiratory samples or in plasma, and relating them to the parameters studied.

Circulating cfDNA has been shown, from symptom onset and throughout the disease, to be an excellent prognostic and progression marker. The evolution of IL-6 levels, especially on days 10–16 from disease onset, also provides important prognostic information, indicating that the monitoring of both markers is highly useful for the follow-up of hospitalised patients and with potential implications for their clinical management.

LDH: lactate dehydrogenase

cfDNA: cell free DNA

TNF-a: Tumour necrosis factor-a

IL-6: Interleukin-6

IL-8: Interleukin-8

G-CSF: Granulocyte colony-stimulating factor

CRP: C-reactive protein

DAMPS: Damage-Associated Molecular Patterns

CCDC score: Chinese Center for Disease Control and Prevention classification

WHO OS: World Health Organisation Ordinal Scale

MI: moderately il

SI: severely ill

CI: critically ill

IL-1β: interleukin-1b

IL-17A: intereleukin-17A

IFN-γ: interferon-g

PCT: procalcitonin

SaO2: oxygen saturation

FiO2: fraction of inspired oxygen

GPT: glutamic pyruvic transaminase

PAMPS: Pathogen-Associated Molecular Patterns

Ethics approval and consent to participate

The study was approved (01/04/2020) by IRB Aragón (Aragon Research Ethics Committee [CEICA]) (Record Nº 07/2020).

Consent for publication:

Not applicable

Availability of data and materials:

The datasets supporting the conclusions of this article are available in the Zenodo repository, in https://zenodo.org/record/7099678#.Yyrg1NpByUk

Competing interests: ATO: Advisory Board and lectures: Pfizer, MSD, Jansen, Menarini, bioMérieux. The rest of the authors do not report conflicts of interest related to the submitted work.

Funding source: This work was supported with funds from the Pneumoaragon Foundation of the Aragonese Society of Pneumology (SADAR).

Author contributions:

Conception and design: SB, ABL
Acquisition of data: LLV, CDD, LT, PRG, ATE, RL, CA, CB
Analysis and interpretation of data: JG, AC, BJ, ABL, SB, ATO
Writing of the manuscript: SB, ABL, ATO
Drafting or revising of the article: SB, ABL, ATO
Final approval of the manuscript: SB, ABL, LLV, CDD, LT, PRG, RL, CA, JG, AC, BJ, CB, ATE, ATO

Acknowledgements

Not applicable

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No competing interests reported.

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published 04 May, 2023

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Editorial decision: Major revision
09 Mar, 2023
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Reviewers agreed at journal
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IL-6 and cfDNA monitoring throughout COVID-19 hospitalisation are accurate markers of its outcomes

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Abstract

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Background

Methods

Patients and controls

Blood samples

Cytokines and P-selectin

Cell-free DNA

Statistical analysis

Results

Discussion

Conclusions

Abbreviations

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References

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Supplementary Files

Status:

Journal Publication

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