A total of 70 patients with confirmed SARS-CoV-2 infection admitted to the intensive care unit (ICU) were included in the study (Fig. 1A). The median (IQR) age was 61.5 (50.5–69.0), and most of the patients were males (80% [56/70]). The main comorbidities were arterial hypertension (58.6% [41/70]), obesity (18.6% [13/70]), and diabetes mellitus (17.1% [12/70]) (Table 1). More than a quarter of patients developed MACE during ICU stay (25.7% [18/70]), and a total of 22 MACE were reported (Fig. 1B). The most frequent MACE diagnoses in the cohort were myocardial injury (50% [9/18]), followed by new onset arrhythmia (27.8% [5/18]), worsening heart failure (22.2% [4/18]), and myocardial infarction (11.1% [2/18]) (Fig. 1B). Interestingly, only one case of new-onset cardiac failure (5.6% [1/18]) and cardiovascular death (5.6% [1/18]) were documented (Fig. 1B).
Table 1
Demographics characteristics of patients hospitalized due to COVID stratified by the presence of Major Adverse Cardiovascular Events (MACE).
Characteristic | All n = 70 | MACE n = 18 | NO-MACE n = 52 | P value |
Demographic |
Male. n (%) | 56 (80.0) | 18 (100) | 38 (73.1) | 0.03 |
Age. median (IQR) | 61.5 (50.5–69.0) | 67.5 (53.3–70.8) | 59.0 (49.8–68.0) | 0.40 |
Comorbid conditions. n (%) |
Stroke | 1 (1.4) | 0 (0.0) | 1 (1.9) | 0.58 |
Myocardial infarction | 4 (5.7) | 3 (16.7) | 1 (1.9) | 0.08 |
Cardiac arrhythmia | 3 (4.3) | 3 (16.7) | 0 (0.0) | 0.02 |
Asthma | 1 (1.4) | 0 (0.0) | 1 (1.0) | 0.58 |
Diabetes mellitus | 12 (17.1) | 5 (27.8) | 7 (13.7) | 0.30 |
Coronary disease | 2 (2.9) | 1 (5.6) | 1 (1.9) | 0.98 |
Mental Illness | 1 (1.4) | 0 (0.0) | 1 (1.9) | 0.58 |
Chronic kidney disease | 3 (4.3) | 2 (11.1) | 1 (1.9) | 0.33 |
COPD | 8 (11.4) | 1 (5.6) | 7 (13.5) | 0.63 |
Congestive cardiac failure | 2 (2.9) | 2 (11.1) | 0 (0.0) | 0.11 |
Arterial hypertension | 41 (58.6) | 10 (55.6) | 31 (59.6) | 0.98 |
Obesity | 13 (18.6) | 5 (27.8) | 8 (15.4) | 0.42 |
OSAHS | 4 (5.7) | 0 (0.0) | 4 (7.7) | 0.53 |
Smoking | 9 (12.9) | 2 (11.1) | 7 (13.5) | 0.88 |
Dyslipidemia | 3 (4.3) | 3 (16.7) | 0 (0.0) | 0.02 |
Physiological variables during the first 24 hours of admission. median (IQR) |
Heart rate. BPM | 93.5 (82.5–111.0) | 96.5 (83.3-116.5) | 92.0 (83.5-110.3) | 0.16 |
Respiratory rate. BrPM | 22.0 (20.0–30.0) | 24.0 (20.0–30.0) | 22.0 (20.0-27.8) | 0.63 |
Temperature. °C | 36.5 (36.3–37.0) | 36.7 (36.4–37.1) | 36.4 (36.2–37.0) | 0.16 |
SBP. mmHg | 120.5 (108.5–131.0) | 124.5 (115.5–131.0) | 119.5 (104.5–131.0) | 0.55 |
DBP. mmHg | 70.0 (64.0–79.0) | 70.5 (64.5–75.5) | 70.0 (64.0-80.25) | 0.63 |
MAP. mmHg | 87.0 (79.5–98.0) | 87.5 (83.3–93.0) | 86.5 (78.0-98.3) | 1.00 |
SPO2. (%) | 87.0 (72.75-91.0) | 80.5 (67.8–89.8) | 88.5 (80.5–91.0) | 0.12 |
Glasgow | 15.0 (15.0–15.0) | 15.0 (15.0–15.0) | 15.0 (15.0–15.0) | 0.18 |
Laboratory variables at admission. median (IQR) |
Presepsin, ng/L | 716.0 (471.8-1743.8) | 1080.5 (615.8-2458.8) | 683.5 (429.3–1596.0) | 0.14 |
Pro-BNP, pg/mL | 715.5 (171.5-1443.3) | 1860.5 (939.8-4526.5) | 398.0 (132.0-1029.5) | < 0.001 |
Troponin, ng/mL | 12.9 (4.9–89.7) | 106.5 (23.2–354.0) | 8.9 (3.7–21.5) | < 0.001 |
D Dimer, mg/mL | 1.5 (0.9–3.3) | 1.2 (0.7–3.3) | 1.6 (1.0-3.2) | 0.45 |
WBC, cell x 103 | 9.1 (7.1–12.4) | 8.6 (7.1–11.1) | 9.2 (7.2–13.2) | 0.51 |
Neutrophils, (%) | 83.6 (78.4–89.4) | 85.4 (78.4–89.7) | 83.5 (79.1–89.3) | 0.84 |
Hemoglobin, g/dL | 15.8 (14.4–17.5) | 16.5 (15.1–17.6) | 15.6 (14.3–17.2) | 0.42 |
Platelet, cell x 103 | 236.5 (179.3-269.3) | 226.5 (178.3-263.8) | 237.0 (179.8-271.5) | 0.73 |
Creatinine, mg/dL | 1.1 (0.8–1.3) | 1.1 (1.0-1.8) | 1.0 (0.8–1.2) | 0.07 |
BUN, mg/dL | 19.9 (15.1–27.3) | 23.9 (14.5–29.1) | 19.1 (15.1–26.4) | 0.34 |
Blood glucose, mg/dL | 138.1 (116.0-163.9) | 167.5 (129.5-209.3) | 129.9 (114.9–149.0) | 0.02 |
Sodium, mEq/L | 136.9 (135.0-139.0) | 135.0 (133.0-136.8) | 137.0 (135.0-140.3) | 0.01 |
Potassium, mEq/L | 4.3 (4.1–4.6) | 4.5 (4.1-5.0) | 4.3 (4.0-4.5) | 0.10 |
Chloride, mEq/L | 98.6 (94.0-101.9) | 96.4 (89.4–99.2) | 99.0 (94.6–103.0) | 0.03 |
Bilirubin max, mg/dL | 0.7 (0.5–1.3) | 0.7 (0.5–0.9) | 0.8 (0.5–1.4) | 0.26 |
ALT, U/L | 60.5 (38.9–83.4) | 53.9 (38.9–83.0) | 60.9 (40.6–87.5) | 0.46 |
AST, U/L | 62.9 (47.7–80.7) | 62.8 (48.9–74.9) | 62.9 (49.0-83.3) | 0.60 |
pH | 7.5 (7.4–7.5) | 7.4 (7.4–7.5) | 7.5 (7.5–7.5) | 0.02 |
PCO2, mmHg | 29 (26.3–33) | 29.0 (27.0–36.0) | 28.0 (26.0–32.0) | 0.44 |
PaO2, mmHg | 59 (51–66) | 54.0 (45.3–59.8) | 61.0 (51.8–67.0) | 0.04 |
HCO3, mmol/L | 21.5 (19.2–23.9) | 21.6 (17.4–25.3) | 21.5 (19.4–23.8) | 0.89 |
Lactic acid, mmol/L | 1.6 (1.2–2.1) | 1.8 (1.3–2.5) | 1.6 (1.2–2.1) | 0.33 |
CRP, mg/L | 204.4 (128.7-276.3) | 246.1 (174.7-274.7) | 191.2 (122.3-274.8) | 0.46 |
PT, seconds | 12.6 (11.5–13.4) | 12.2 (11.2–12.7) | 12.7 (11.9–13.4) | 0.24 |
PTT, seconds | 27.4 (26.1–29.8) | 28.5 (26.9–31.2) | 27.2 (25.9–28.6) | 0.11 |
Outcomes |
Hospital LOS, days (IQR) | 12.5 (9.0–18.0) | 10.5 (9.0-14.5) | 14.0 (9.0–19.0) | 0.33 |
In-Hospital Mortality (%) | 27 (38.6) | 11 (61.1) | 16 (30.8) | 0.02 |
Abbreviations: MACE: major cardiovascular events; IQR: interquartile range; COPD: chronic obstructive pulmonary disease; OSAHS: obstructive sleep apnea-hypopnea syndrome; BPM: beats per minute; BrPM: breaths per minute; SBP: systolic blood pressure; DPB: diastolic blood pressure; MAP: mean arterial pressure; SPO2: oxygen saturation; BNP: brain natriuretic peptide; WBC: white blood cell count; BUN: blood urea nitrogen; ALT: alanine aminotransferase; AST: aspartate aminotransferase; PCO2: partial pressure of carbon dioxide; PaO2: partial pressure of oxygen; HCO3: bicarbonate; CRP: C reactive protein; PT: prothrombin Time; PTT: thromboplastin time; LOS: length of stay. |
Patients who developed MACE were older than those who did not (median [IQR], 67.5 years old [53.3–70.8] vs. 59.0 years old [49.8–68.0], p = 0.04). In addition, patients who developed MACE had more frequently a past medical history of cardiovascular diseases; such as myocardial infarction (16.7% [3/18] vs. 1.9% [1/52]; p = 0.08), cardiac arrhythmia (16.7% [3/18] vs. 0.0 [0/52]; p = 0.02), dyslipidemia (16.7 [3/18] vs. 0.0 [0/52]; p = 0.02), and congestive heart failure (1.1% [2/18] vs. 0.0 [0/52]; p = 0.11). Both groups (i.e., MACE and no-MACE) had similar physiological variables at admission; however, some laboratory results were different among the groups (Table 1). For instance, chloride, sodium, and pH levels were significantly lower in MACE patients than in no-MACE patients (96.4 mEq/L [89.4–99.2] vs. 99.0 mEq/L [94.6–103.0], p = 0.03; 135.0 mEq/L [133.0-136.8] vs. 137.0 mEq/L [135.0-140.3], p = 0.01; 7.4 [7.4–7.5] vs. 7.5 [7.5–7.5], p = 0.02; respectively) (Table 1).
Regarding the clinical outcomes, MACE patients had a shorter length of stay when compared with no-MACE patients; however, this difference was not statistically significant (10.5 days [9.0-14.5] vs. 14.0 days [9.0–19.0], p = 0.33). In contrast, we found that patients who developed MACE during hospital admission had a significantly higher mortality rate (61.1% [11/18] vs. 30.8% [16/52], p < 0.02). All demographic characteristics are presented in Table 1.
The relation between serum viral load and the development of MACE
To determine whether serum viral load was associated with the development of MACE, we assessed the amount of SARS-CoV-2 in the serum of the cohort at hospital admission. We found that the patients who developed MACE had higher Log copies/mL of SARS-CoV-2 (1.422 [0.000-6.971] vs. 0.363 [0.000-3.582], p < 0.05) when tested via quantitative RT-PCR in serum (Fig. 2A).
The relation of serum biomarkers and cytokines with MACE development
Different critical mediators were measured to define possible biomarkers for MACE development. MACE patients had increased serum concentration of cardiac biomarkers, principally Troponin I (106.5 ng per mL [23.2–354.0] vs. 8.9 ng per mL [3.7–21.5]; p < 0.001) (Fig. 2B) and pro-B-type natriuretic peptide (pro-BNP) (1860.5 [939.8-4526.5] vs. 398.0 [132.0-1029.5]; p < 0.001) at hospital admission (Fig. 2C). Notably, D-dimer and presepsin were not increased in MACE patients at hospital admission (Fig. 2D, Fig. 2E). Moreover, cytokines levels also showed differences among MACE and no-MACE patients, mainly by elevation of interferon-g-induced protein-10 (IP-10) (6689.22 ng per mL [1083.44-20327.7] vs. 10625.92 ng per mL [3492.59-18129.20]; p = 0.05) and interleukin (IL)-10 (105.56 ng per mL [28.83-243.87] vs. 46.68 ng per mL [3.58-271.29]; p < 0.05) or a decrease in levels of IL-17ɑ (1.54 ng per mL [0.0000745-7.22] vs. 261.63 ng per mL [0.00000411-1822]; p < 0.05), IL-1β (0.025 ng per mL [0.00144-0.052] vs. 0.381 ng per mL [0.000356-6.68]; p < 0.05), Il-4 (3.34 ng per mL [0.412–8.97] vs. 26.16 ng per mL [0.006–149.76]; p < 0.05), and IL-6 (37.05 ng per mL [16.79–60.21] vs. 72.86 ng per mL [0.06-345.13]; p < 0.05) compared to the no-MACE group (Fig. 2F).
Neutralization of SARS-CoV-2 variants and the development of MACE
Spike-specific neutralizing antibodies are generally considered correlates of protection against COVID-19. We want to determine whether there were any significant differences in the neutralization titers between the MACE and no-MACE groups, which could explain the disease trajectory following ICU admission. No significant differences were observed in the ability to neutralize pseudoviruses from the variant of concerns: SARS-CoV-2 (D614) or Beta, Gamma, Delta, and Omicron subvariants (both BA.1 and BA.2). While a partial increase in the neutralization of D614 was observed in the no-MACE group and an increase of Delta neutralization in the MACE group, these were not statistically significant. Our results suggest that at the time of ICU admission, the robustness of neutralizing antibody activity does not appear to be involved in preventing MACE (Fig. 3). Moreover, these data also suggest that MACE was not associated with a particular viral variant of concern.
Hearts of hamsters infected with SARS-COV-2 show upregulation of major pathways associated with injury, cell death, antiviral immune responses, and metabolic changes.
To understand the underlying effects of severe SARS-CoV-2 infection in the heart, we used a recently established Golden Syrian Hamster model of severe infection [31]. Hamsters were infected intratracheally with SARS-CoV-2 strain USA-WA-1/2020 at a 9 X 10^5 PFU dose. Four days later, mice were sacrificed, and hearts were excised for assessment of viral titers and RNA sequencing (Fig. 4A). We observed a stark increase in viral titers (plaque forming units, PFU) in the hearts of hamsters 4 days post-infection when compared to mock-infected animals (Fig. 4B). At this time point, viral titers in the lungs were shown to start decreasing in a previous report by our group, using the same model [31]. Then, the cardiac transcriptome was evaluated by transcriptome sequencing (RNA-seq) of uninfected hearts and hearts infected with SARS-CoV-2 on day 4 post-infection. The infection resulted in the differential expression of 1,084 transcripts with a p-value of ≤ 0.05 out of 12,556 transcripts for a change of 8.63% of the total cardiac transcriptome. Gene ontology (biological processes) analysis for the significantly changed transcripts showed major changes in terms associated with programmed cell death (Fig. 4C), regulation of reactive oxygen species (ROS) (Fig. 4D), defense response to the virus (Fig. 4E), and carbohydrate metabolic processes (Fig. 4F). Of note, cell death and ROS activity in the heart have been linked to active pathogenesis of cardiovascular diseases [32] and cardiac damage in models of severe pneumococcal and pandemic influenza infections [15, 33–35]. The stark response to viral infection shown in the transcriptional increase of factors such as Ifitm2, Irf7, Stat1, and Eif2a, among others (Fig. 4E), indicates a heart actively mounting a host response to the invading SARS-CoV-2 (Fig. 4B).
Hamsters and humans show the activity of programmed necrosis, i.e., necroptosis in the heart and serum, respectively.
Analysis of transcriptional changes of the effectors of the two major programmed necrosis pathways, necroptosis (mixed lineage kinase domain-like; MLKL) and pyroptosis (gasdermin D; GSDMD), showed necroptosis to be starkly elevated in SARS-CoV-2 infected hamsters compared to the hearts of the uninfected group (Fig. 5A). We used immunoblots to confirm whether these transcription changes reflected protein and activity levels. Blots for the phosphorylated MLKL (pMLKL), the active form of MLKL, in hamster hearts showed significant activity of necroptosis in the hearts of SARS-CoV-2-infected hamsters (Fig. 5B).
While hamsters provide a pivotal model to study SARS-CoV-2 cardiac pathogenesis, we aimed to define if such a strong indicator of tissue injury was present in our MACE-experiencing human cohort. Immunoblots for pMLKL showed a distinct increase in the presence of this molecular marker of necroptotic cell death in the serum of MACE patients compared to those without MACE (Fig. 5C). These results suggest necroptosis activation in patients with MACE, which correlates with the findings described in the animal model. The complete uncropped gel and blot images can be found in the Additional File (Figure S1)
Markers of cardiac injury, inflammation, necroptosis, and circulating SARS-CoV-2 strongly correlate with the development of MACE
Using an annotated heatmap, we evaluated the association of MACE with all analyzed serum biomarkers (Fig. 6A). We observed that Troponin-I and pMLKL were the main variables associated with the development of MACE in humans. Then, single linear regressions were performed to analyze these relations further. We found a strong correlation between serum pMLKL and serum Troponin-I levels with a regression coefficient of 0.3589, p = 0.0086 (Fig. 6B) in MACE patients but not in the no-MACE (Fig. 6E). Notably, the serum viral burden evaluated by SARS-CoV-2 copies was associated with Troponin-I release in patients with MACE (Fig. 6C), with a regression coefficient of 0.2576, p = 0.03, but not in no-MACE patients (Fig. 6F). SARS-CoV-2 copies and pMLKL levels in serum were found not to correlate in both the MACE (Fig. 6D) and no-MACE (Fig. 6G) groups. Of note, the top four biomarkers for the development of MACE were observed using a mean accuracy plot and defined to be pMLKL, Troponin-I, serum presence of SARS-CoV-2, and Pro-BNP (Additional File Figure S2). These findings illustrate the relation between necroptosis, cardiac injury, and viral burden with the development of MACE.