Literature DB >> 33516748

Increased inflammatory markers reflecting fibrogenesis are independently associated with cardiac involvement in hospitalized COVID-19 patients.

Ueland T1, Dyrhol-Riise Am2, Woll Bm3, Holten Ar4, Petteresen F5, Lind A6, Dudman Sg7, Heggelund L8, Holter Jc7, Aukrust P9.   

Abstract

Entities:  

Year:  2021        PMID: 33516748      PMCID: PMC7842139          DOI: 10.1016/j.jinf.2021.01.017

Source DB:  PubMed          Journal:  J Infect        ISSN: 0163-4453            Impact factor:   6.072


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Dear Editor, a high proportion of COVID-19 infected patients have cardiac involvement [1], and elevated surrogate markers of myocardial injury and stress, such as troponins [2] and N-terminal pro-B-type natriuretic peptide (NT-proBNP) , are found in patients with poor outcome. Beyond direct angiotensin-converting enzyme 2 (ACE2) related mechanisms, overwhelming inflammatory responses could activate regulatory fibrotic pathways, induce tissue damage and be harmful for the host, and such “hyperinflammatory” mechanisms may be involved in COVID-19 associated cardiac involvement [3]. However, systemic inflammatory responses have been linked to both pulmonary and myocardial injury during COVID-19 disease [4], and it is unclear if enhanced cardiac stress is due to respiratory failure, rather than direct cardiac involvement. Underlying cardiovascular disease (CVD) promotes poor prognosis in COVID-19 disease and could further enhance the inflammatory burden. We examined a range of inflammatory and fibrotic markers during COVID-19 hospitalization in relation to elevation of troponins and NT-proBNP. As cardiac markers and acute phase responses are influenced by kidney function, we focused on identifying inflammatory and fibrotic markers that displayed an association with elevated cardiac markers, beyond that explained by hyperinflammation (CRP), kidney- (estimated glomerular filtration rate, eGFR) and respiratory-function (P/F ratio) and co-morbid CVD. Thirty-nine adult patients (≥18 years old) with confirmed COVID-19 were consecutively recruited between March 6 and April 14 to a clinical cohort study (Norwegian SARS-CoV-2 study; ClinicalTrials.gov, number NCT04381819). Clinical information and routine laboratory samples were collected at the earliest time-point after hospitalization. 1–3 plasma samples were collected at day 0–2 (within 48 h of admission), day 3–5 and day 7–10. Informed consents were obtained from all patients or next-of-kin if patients were incapacitated of giving consent. For reference, inflammatory markers were also analyzed in plasma from 16 healthy controls (Table 1 ). The study was approved by the South-Eastern Norway Regional Health Authority (reference number: 106,624).
Table 1

Characterization of the study group.

ControlsAll patientsCardiovascular endpoint
(n = 16)(n = 39)No (n = 17)Yes (n = 22)
Women, n (%)7 (44)10 (25)6 (35.3)4 (18.2)
Age, years66 ± 760 ± 1558 ± 1363 ± 16
Time from symptoms, days9.6 ± 3.69.7 ± 4.29.6 ± 3.2
Caucasian, n (%)16 (100)28 (70)10 (59)17 (77)
Current smoker, n (%)3 (19)8 (20)2 (12)7 (32)
P/F ratio41 ± 1544 ± 1838 ± 12
Comorbidities, n (%)
Cardiovascular0 (0)9 (23)2 (12)7 (32)
Pulmonary0 (0)1 (3)0 (0)1 (3)
Asthma0 (0)8 (20)4 (24)4 (18)
Renal0 (0)4 (10)0 (0)4 (18)
Liver0 (0)0 (0)0 (0)0 (0)
Neurological0 (0)1 (3)0 (0)1 (5)
cancer0 (0)1 (3)1 (6)0 (0)
hematological0 (0)1 (3)1 (6)0 (0)
Obesity0 (0)5 (13)2 (12)3 (14)
Diabetes0 (0)3 (8)1 (6)2 (9)
Rheumatic0 (0)4 (10)1 (5)3 (14)
Biochemistry
Hemoglobin, g/dL14.4 ± 0.913.3 ± 1.7**12.7 ± 1.613.7 ± 1.7
Leukocytes, x109/L5.6 ± 1.96.6 ± 3.25.3 ± 2.07.7 ± 3.6*
Lymphocytes, x109/L1.68 ± 0.661.07 ± 0.45**1.22 ± 0.450.95 ± 0.42
Monocyte, x109/L0.54 ± 0.180.44 ± 0.20.48 ± 0.220.41 ± 0.17
Neutrophils, x109/L3.24 ± 0.715.09 ± 3.2*3.5 ± 1.96.3 ± 3.6*
Platelets, x109/L254 ± 70202 ± 59**212±52*194±66
ALT, U/L29 ± 1343 ± 4058±5532±19
AST, U/L32 ± 949 ± 3858±4736±10
eGFR, mL/min/1.73m282 ± 1282 ± 3088 ± 2077 ± 37
CRP, mg/L†1.6 [0.8. 3.9]53 [31, 153]***31 [15,41]144 [53,191]***

Continuous data are given as mean±standard deviation. Cut-offs for NT-proBNP, cTni and cTnT are give in the methods section. *p < 0.05, **p < 0.01 vs. patients with no ICU/Death. †median [25th, 75th percentile].

Characterization of the study group. Continuous data are given as mean±standard deviation. Cut-offs for NT-proBNP, cTni and cTnT are give in the methods section. *p < 0.05, **p < 0.01 vs. patients with no ICU/Death. †median [25th, 75th percentile]. The CV endpoint was defined prior to analysis as cardiac markers above reference values at any time during hospitalization (Fig. 1 A/B): NT-proBNP (women: <50 years (y) ≥170 ng/L; 50–69 y ≥ 300 ng/L; ≥70 y ≥ 760 ng/L, men: <50y≥85 ng/L; 50–69 y ≥ 250 ng/L; ≥70 y ≥ 500 ng/L) or cardiac (c) Tnt (≥14 ng/mL), cTni (women ≥15 ng/mL, men ≥30 ng/mL). Cut‐off references as provided by local laboratories based on product information from Roche (NT‐proBNP and TnT) and Abbot (TnI).
Fig. 1

Inflammatory markers and cardiac involvement during COVID-19 disease. A) Circulating markers measured in the study reflecting inflammation in relevant tissues or cells (pulmonary, adipose, cardiac, renal, platelets) or related to function (fibrogenesis, vascular inflammation). The table shows the F statistic from the generalized linear mixed model evaluated the impact of the temporal course of plasma markers on the CV endpoint. In adjusted analysis, C-reactive protein (CRP), estimated glomerular filtration rate (eGFR), P/F ratio and presence of cardiovascular comorbidity (CVD) were cumulatively added as covariates. *p < 0.01, **p < 0.01, ***p < 0.001. B) Temporal course of GDF15, POSN, TIMP-1 and YKL-40 (all ng/mL) during COVID-19 infection according to the CV-endpoint. Data are presented as back-transformed estimated marginal means with 95% confidence intervals from the mixed model analysis (see statistical methods). The gray area represents the estimated marginal mean (line) and 95% confidence interval (gray area) of healthy controls (n = 16). Available samples at the different time-points was 0–2 days: n = 31, 3–5 days: n = 22, 7–10 days: n = 19. C) Pearson correlation between NT-proBNP and cardiac troponins (cTn) and the selected markers (log transformed) at different time-points (day 0–2 blue, day 3–5 red, day 7–10 green) during the course of the study. SpD, surfactant protein D; PARC/CCL18, pulmonary and activation-regulated chemokine; ST-2, suppression of tumorigenesis-2; Gal-3, Galectin-3 ; sCD40L, soluble CD40 ligand; NAP2/CXCL7, neutrophil activating peptide; NGAL, neutrophil gelatinase-associated lipocalin; vWF, von Willebrand factor; AngP2, angiopoietin 2; PTX-3, pentraxin 3; sTNFR1, soluble tumor necrosis factor receptor type 1; CXCL16, C-X-C Motif Chemokine Ligand 16; VCAM1, vascular cell adhesion molecule 1; GDF-15, growth differentiation factor; POSN, periostin; OPN, osteopontin; MMP-9, matrix metallopeptidase 9; TIMP1, tissue inhibitor of matrix metalloproteinase; YKL-40 also known as chitinase-3-like protein 1. . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Inflammatory markers and cardiac involvement during COVID-19 disease. A) Circulating markers measured in the study reflecting inflammation in relevant tissues or cells (pulmonary, adipose, cardiac, renal, platelets) or related to function (fibrogenesis, vascular inflammation). The table shows the F statistic from the generalized linear mixed model evaluated the impact of the temporal course of plasma markers on the CV endpoint. In adjusted analysis, C-reactive protein (CRP), estimated glomerular filtration rate (eGFR), P/F ratio and presence of cardiovascular comorbidity (CVD) were cumulatively added as covariates. *p < 0.01, **p < 0.01, ***p < 0.001. B) Temporal course of GDF15, POSN, TIMP-1 and YKL-40 (all ng/mL) during COVID-19 infection according to the CV-endpoint. Data are presented as back-transformed estimated marginal means with 95% confidence intervals from the mixed model analysis (see statistical methods). The gray area represents the estimated marginal mean (line) and 95% confidence interval (gray area) of healthy controls (n = 16). Available samples at the different time-points was 0–2 days: n = 31, 3–5 days: n = 22, 7–10 days: n = 19. C) Pearson correlation between NT-proBNP and cardiac troponins (cTn) and the selected markers (log transformed) at different time-points (day 0–2 blue, day 3–5 red, day 7–10 green) during the course of the study. SpD, surfactant protein D; PARC/CCL18, pulmonary and activation-regulated chemokine; ST-2, suppression of tumorigenesis-2; Gal-3, Galectin-3 ; sCD40L, soluble CD40 ligand; NAP2/CXCL7, neutrophil activating peptide; NGAL, neutrophil gelatinase-associated lipocalin; vWF, von Willebrand factor; AngP2, angiopoietin 2; PTX-3, pentraxin 3; sTNFR1, soluble tumor necrosis factor receptor type 1; CXCL16, C-X-C Motif Chemokine Ligand 16; VCAM1, vascular cell adhesion molecule 1; GDF-15, growth differentiation factor; POSN, periostin; OPN, osteopontin; MMP-9, matrix metallopeptidase 9; TIMP1, tissue inhibitor of matrix metalloproteinase; YKL-40 also known as chitinase-3-like protein 1. . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) A list of the various markers in relation to tissues and functions is given in Fig. 1A. Plasma markers were measured in duplicate by enzyme immunoassays using commercially available antibodies (R&D Systems, Minneapolis, MN) in a 384 format with intra-assay coefficient of variation <5%. Patient characteristics were compared using student's t-test or chi-square for continuous and categorical variables, respectively (Table 1). Associations between the temporal profile of the inflammatory and fibrotic markers and CV-endpoint were evaluated in a generalized linear mixed model with patient number as random factor and time as fixed and cumulatively including CRP, eGFR, P/F ratio and comorbid CVD as covariates. These are reported with the F-statistic (Fig. 1A). Due to high number of markers, limited patient population with varying follow-up samples and multiple covariates we did not perform post-hoc testing. Markers of interest were visualized (Fig. 1B) and scatterplots (Pearson) with NT-proBNP and cardiac troponins assessed at each time-point (Fig. 1C). P-values are two-sided and considered significant when <0.05. Of 39 COVID-19 patients, 18 and 10 patients had levels of NT-proBNP and troponins above age- and sex- adjusted reference levels, respectively, during hospitalization. Combined, 22 patients had cardiac markers above reference limits, defined as the CV endpoint in the study. These patients were characterized by high neutrophil counts and markedly higher CRP levels (Table 1). The linear mixed model revealed multiple markers that were associated the CV endpoint in unadjusted analysis (Fig. 1A). However, after full adjustment for CRP, eGFR, P/F ratio and comorbid CVD, only the fibrotic markers GDF-15, POSN, TIMP1 and YKL-40 remained associated with the CV endpoint (Fig. 1A). All markers revealed a stable temporal profile and for GDF15, TIMP1 and YKL40, levels remained higher compared to patients without the CV endpoint and healthy controls (Fig. 1B). Of note, Spd, NGAL and in particular the vascular markers PTX3 and sTNFR1 were associated with the CV endpoint adjusting for CRP and eGFR but not following adjustment for pulmonary function. Fig. 1C shows the correlation analysis with continuous measures of NT-proBNP (left side) and troponins (right side) during the course of the study. As shown, GDF-15, TIMP-1 and YKL-40 were strongly positively associated with NT-proBNP and troponins and these associations were consistent at all time-points. In the present study, over half of the hospitalized COVID-19 patients reached the CV endpoint as reflected by elevated levels of NT-proBNP and cardiac troponins supporting frequent cardiac involvement in these patients. Enhanced fibrosis has been related to respiratory failure in COVID-19 patients, but the fibrotic markers GDF-15, POSN, TIMP-1 and YKL-40 remained elevated in patients with cardiac involvement following adjustment with the P/F ratio obtained at the same time of sampling. Previous experimental and clinical studies have identified a role for TIMP-1, GDF-15 and YKL-40 5, 6, 7 in promoting cardiac fibrosis and we suggest that the strong correlation with cardiac markers reflects a more direct role in cardiac fibrosis in COVID-19 patients. Cardiac involvement in COVID-19 disease has been speculated to involve downregulation of the ACE2, and of relevance, downregulation of ACE2 in experimental models enhances cardiac remodeling and fibrosis involving upregulation of TIMP-1 [8] and POSN [9]. Furthermore, GDF-15 correlated with poor outcome in hospitalized COVID19 patients [10]. Thus, activation of these inflammatory pathways involved in fibrogenesis and ECM remodeling may represent novel targets for intervention in COVID-19 patients. In conclusion, our study shows that fibrosis and ECM remodeling may play an important role in the cardiac involvement during COVID-19 infection

Declaration of Competing Interest

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