Changes in trace elements and metallothioneins levels and their relationship with clinical, biochemical, and inflammatory parameters in patients with COVID-19 during the early ICU phase

doi:10.21203/rs.3.rs-2718416/v1

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Changes in trace elements and metallothioneins levels and their relationship with clinical, biochemical, and inflammatory parameters in patients with COVID-19 during the early ICU phase

https://doi.org/10.21203/rs.3.rs-2718416/v1

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Background

The levels of trace elements and Metallothioneins (MTs) could play a key role in modulating the inflammatory reaction and pathogenesis of COVID-19. Their effects on clinical variables are of interest for the characterization and management of this disease. Thus, the present study aimed to investigate the association between circulating Iron (Fe), Zinc (Zn), Copper (Cu), Manganese (Mn), and MTs levels, as well as their relationship with clinical, biochemical, and inflammatory parameters in critical care patients with COVID-19 at early Intensive Care Unit (ICU) phase.

Methods

A total of 86 critically ill patients with COVID-19 were monitored from the first day of admission to the ICU until the third day of stay. Clinical parameters were retrieved from the hospital database. Biochemical and inflammatory parameters were analyzed following enzymatic colorimetry and immunoassay procedures. Serum samples were used to assess mineral levels by inductively coupled plasma-mass spectrometry and MTs levels by differential pulse voltammetric.

Results

Levels of Cu and MTs decreased (all P ≤ 0.046) after 3 days of ICU stay, increasing the prevalence of Cu deficient values from 50–65.3% (P = 0.015) on the third day of ICU stay. Fe and Zn were shown to have a predictive value for mortality and severity. Changes in Fe were directly related to changes in Cu and Mn (all r ≥ 0.266; P ≤ 0.019). In contrast, changes in MTs were inversely related to changes in Mn and albumin (all r≥–0.255; P ≤ 0.039).

Conclusions

The present study indicated a risk of trace element deficiencies related to different biochemical and clinical parameters. We suggest monitoring the mineral status and performing nutritional interventions, when appropriate, that could help to improve the altered parameters, such as inflammatory conditions and, thus, the prognosis in critically ill patients with COVID-19.

COVID-19

Iron

Zinc

Copper

Manganese

Metallothionein

Critical care

Coronavirus Disease-19 (COVID-19) is a severe acute respiratory syndrome caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which rapidly spread throughout the world and has been declared a pandemic, with a need for hospitalization and intensive therapy in severe cases ¹. Apart from the well-known respiratory symptoms (e.g., respiratory distress, low oxygen saturation, or respiratory failure) – all of them considered to be the main symptoms of COVID-19 –, the appearance of coagulopathy or cytokine storm processes are also clinical signs and symptoms involved in the systemic inflammatory process that occurs during COVID-19 ^2,3. Despite the improvement in disease management, most of the therapies have shown no perceivable impact – no universal cure for COVID-19 disease is available to date – and the rapidly mutating virus has emerged as a matter of great concern – the effort on combating the disease should not be limited to finding drugs and vaccines – ^4,5. In this regard, a proper nutritional status, which has an important role in optimal well-being and immune function, may be an interesting alternative. Thus, some current therapies in clinical settings consist of immunomodulatory agents – including micronutrients to fight against oxidative stress and modulate inflammation – ⁶.

Trace elements (i.e., Iron (Fe), Zinc (Zn), Copper (Cu), and Manganese (Mn)) are micronutrients mostly responsible for modulating the inflammatory reaction and cytokine production in patients with COVID-19, being their deficiency responsible for the increased risk of morbidity and mortality among these patients ^7,8. It must be noted that excess in circulating mineral levels may also be associated with different complications: (I) Fe overload, as a consequence of the decomposition of the hemoglobin by SARS-CoV-2, causes oxidative damage, inflammation, and immune dysfunction, which can lead to rapid multi-organ failures ⁹; (II) excessive free Zn ions may be toxic by binding at the active site of enzymes or via allosteric inhibition of enzymes ¹⁰, and high concentrations of Zn inhibit T cell functions ¹¹; (III) free Cu may catalyze the formation of highly reactive hydroxyl radicals ¹²; and (IV) Mn at elevated levels is neurotoxic ¹³. Thus, maintaining proper levels of these trace elements is crucial for a good state of health.

Importantly, metal ion concentrations in the body are controlled by the affinity for their ligands ¹⁴. Metallothioneins (MTs) are a family of ubiquitous small proteins with a high cysteine content, which confer them an optimal capacity for metal ion coordination via detoxification, storage, and delivery, participating in a wide range of stress responses, tumorigenesis, neurodegeneration, and inflammatory processes ¹⁵. MTs bind various divalent trace metal ions, protecting cells and tissues against heavy metal toxicity and playing an essential role in intracellular aspects, especially for Zn and Cu ¹⁶. Additionally, it has been shown that circulating MTs can be increased by different oxidative processes in multiple organ systems, although their production often decreases to protect against oxidative tissue injury ¹⁷. Moreover, overexpression and up-regulation of MTs have been associated with carcinogenic processes ¹⁶.

To date, the relationship between circulating levels of minerals and MTs and their subsequent effects on clinical and inflammatory parameters have not been investigated, at least in the context of COVID-19 disease. Therefore, the present study aimed to investigate the association between circulating Fe, Zn, Cu, Mn, and MTs concentrations and their relationship with clinical, biochemical, and inflammatory parameters in critical care patients with COVID-19 at ICU admission and after 3 days of ICU stay. We hypothesized that trace elements could be directly related to MTs levels – their deficiencies worsening during the ICU stay –.

2.1. Subjects and study design

A prospective observational and analytical study was performed on 86 critically ill patients (18 women) aged 36–96 years with COVID-19 monitored from the first day of admission to the Intensive Care Unit (ICU) (baseline) until the third day of stay (follow-up) at the Hospital Virgen de las Nieves in the province of Granada (Spain). The participants were recruited from 1st April to 1st December 2020 after being informed about the study protocol, which all the patients or their families signed. The diagnosis of COVID-19 was based on a positive Real-Time Reverse Transcriptase–PCR (RT-PCR) test and subsequent RNA sequencing specific for the SARS-CoV-2 testing of nasal and pharyngeal swab samples. The participants were considered critically ill when they presented a respiratory failure requiring mechanical ventilation, needed vasopressor treatment (shock), or had other complications with organ failure requiring monitoring or treatment in the ICU. Inclusion criteria were: (I) 18 years of age or older, (II) to have been previously hospitalized for at least more than 48 hours, (III) to have been admitted to the ICU and to stay for at least 3 days, and (IV) to present a positive PCR test for SARS-CoV-2 according to the Chinese Clinical Guideline for the classification of COVID-19 ¹⁸. Exclusion criteria were: (I) to be under 18 years, (II) to be pregnant, and (III) to not present a positive PCR test even though they presented symptoms compatible with COVID-19. The present study was conducted in accordance with the principles of the Declaration of Helsinki (last revised guidelines, 2013) ¹⁹, following the International Conference on Harmonization/Good Clinical Practice standards, and it was approved by the Ethics Committee of the University of Granada (Ref. 149/CEIH/2016).

2.2. Data collection

Data including positive PCR results against SARS-CoV-2, age, sex, exitus, ICU length of stay, and respiratory and clinical parameters were retrieved from the Hospital electronic database system and recorded for each participant on the first and third days of ICU admission, respectively. The respiratory and clinical parameters collected by the intensivists were: Sequential Organ Failure Assessment (SOFA) scale score ²⁰, Acute Physiology and Chronic Health Evaluation II (APACHE II) scale score ²¹, days on Mechanical Ventilation (MV), Mean Arterial Pressure (MAP), Heart Rate (HR), Breath Rate (BR), Fraction of Inspired Oxygen (FiO₂); Partial Oxygen arterial pressure/FiO₂ (PaO₂/FiO₂), and Positive End-Expiratory Pressure (PEEP).

2.3. Blood sampling and biochemical parameters analysis

Blood samples were collected in the morning under fasting conditions, followed by centrifugation (4°C for 15 minutes at 3500 rpm) to separate plasma and serum. The samples were frozen at − 80.0 ºC until analysis of the different parameters. All measurements were obtained in triplicate, and blind quality control samples were included in the same assay batches to determine laboratory error in the measurements.

2.3.1. Assessment of biochemical and inflammatory parameters and mineral levels

The biochemical and inflammatory variables (i.e., albumin, ferritin, transferrin, Transferrin Saturation Index (TSI), fibrinogen, D-dimer, C-Reactive Protein (CRP), Glutamic Oxaloacetic Transaminase (GOT), Glutamic Pyruvic Transaminase (GPT), Gamma-Glutamyl Transferase (GGT), Lactate Dehydrogenase (LDH), Hemoglobin (Hb), leukocytes, percentage lymphocytes and neutrophils, platelets, Troponin T (TNT), Activated Partial Thromboplastin Time (APTT), and International Normalized Ratio (INR)), were analyzed in the Virgen de las Nieves Hospital – which provided the reference values – using “Alinity,” the Abbott Core Laboratory® autoanalyzer for biochemistry and immunochemistry, following enzymatic colorimetry and immunoassay procedures.

The mineral variables (i.e., Fe, Zn, Cu, and Mn) were analyzed using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) (Perkin Elmer® SCIEX Elan-5000 equipment, Markham, Ontario, Canada) following a previous wet-mineralized way in the Scientific Instrumentation Center from the University of Granada – which provided the references values – as previously described ²².

2.3.2. Sample processing and differential pulse voltammetry Brdicka reaction for determination of MTs

A total of 10.0 µl of serum samples were mixed with 990.0 µl of 0.1 M phosphate buffer (Na₂HPO₄ + NaH₂PO₄, pH 7.0) and subsequently incubated at 99.0 ºC in a thermomixer (Eppendorf 5430, Hamburg, Germany) for 20 min with shaking to remove ballast proteins and peptides, which could influence the electrochemical response. Heat treatment effectively denatures and removes non-thermostable high molecular weight proteins from samples ²³. The denatured homogenates were centrifuged at 4 ºC, 25 000 x g for 20 min (Eppendorf 5402, Hamburg, Germany), and the obtained supernatant was used for MTs analysis.

Differential pulse voltammetry measurements for the determination of MTs in Brdicka reaction according to the modified Brdicka procedure ¹⁶ were performed in the processed samples with a potentiostat/galvanostat AUTOLAB PGSTAT204 (Methrom, Utrecht, Netherlands) connected to a VA-Stand 663 (Metrohm, Utrecht, Netherlands), using a standard cell and 3 electrodes: (I) hanging mercury drop electrode with a drop area of 0.4 mm² was used as the working electrode, (II) Ag/AgCl/3M KCl electrode was the reference, and (III) platinum electrode was the auxiliary electrode. A total of 15 mL of Brdicka supporting electrolyte containing 1 mM Co(NH₃)₆Cl₃ and 1 M ammonia buffer (NH₃(aq) + NH₄Cl, pH 9.6) was used without surface-active agent additives and mixed with 5.0 µL of processed sample. Brdicka reaction of MTs follows the principle of the adsorptive stripping technique and is based on the strong adsorption of the target molecule on the surface of the working electrode at an open electrode circuit. After each measurement, the hanging mercury drop electrode and Brdicka supporting electrolyte are renewed. The measurement parameters were as follows: initial potential of − 0.7 V, end potential of − 1.8 V, modulation time of 0.05 s, time interval of 0.57 s, step potential of − 3.9 mV, and modulation amplitude of 25.0 mV. All experiments were performed at 5 ºC using the thermostat Julabo F25 (Labortechnik, Wasserburg, Germany). MTs were quantified from the calibration straight line using a commercially available ≥ 95%-pure solution isolated from rabbit liver (Enzo Life Sciences, Inc., New York, USA). The obtained calibration curve for MTs was as follows y = 2.017 x – 0.023; R² = 0.996. NOVA 2.1.4 Metrohm Autolab B.V. (EcoChemie, Utrecht, Netherlands) was used for data processing.

2.4. Statistical analysis

Data normal distribution was examined using the Kolmogorov-Smirnov test prior to further statistical evaluation. Quantitative parameters were represented as the arithmetic mean (Standard Deviation (SD)). The paired Student’s t-test for parametric samples was used for the comparative analyses of all the clinical, biochemical, inflammatory, mineral variables, and MTs of the study, and to compare the percentage of deficiency of all minerals between the 1st and 3rd days of ICU admission. The unpaired Student’s t-test for parametric samples was used for the comparative inter-group analysis (i.e., changes in clinical, biochemical, and inflammatory parameters of the study by mean changes in mineral and MTs levels) after 3 days of ICU stay. The predictive value of Fe and Zn levels for mortality and severity at baseline and follow-up was evaluated using the Receiver Operating Curve (ROC). Correlation analyses and partial correlation coefficients between mean changes of all parameters of the study after 3 days of ICU stay were performed using Pearson’s correlation. The SPSS version 26.0 statistical package (IBM SPSS, Armonk, New York, USA) was used throughout the study. Statistical significance was considered for P < 0.05. GraphPad Prism 9 software (GraphPad Software, San Diego, California, USA) was used for plotting the graphs.

The clinical parameters of the study participants are represented in Supplementary Table 1. BR, FiO₂, and PEEP decreased after 3 days of ICU stay (all P ≤ 0.038), whereas the rest of the parameters showed no mean differences (all P ≥ 0.142) on the 3rd day of ICU stay.

*** please insert Supplementary Table 1 here ***

Table 1 represents the biochemical, inflammatory, mineral, and metallothionein values of critically ill patients on the 1st and 3rd days of ICU stay. Fibrinogen, CRP, LDH, hemoglobin, hematocrit, leukocytes, percentage of neutrophils, Cu, and MTs decreased significantly (all P ≤ 0.046). In contrast, transferrin, D-dimer, GPT, GGT, percentage of lymphocytes, and platelets increased (all P ≤ 0.036) on the 3rd day of ICU stay. The rest of the parameters showed no mean differences after 3 days of ICU stay (all P ≥ 0.151).

Table 1

Biochemical, inflammatory, mineral, and metallothionein values of critically ill patients with COVID-19 on the 1st and 3rd days of admission to the ICU.
n = 86	References values	1st day (Mean (SD))	3rd day (Mean (SD))	Mean differences	P-Value
Biochemical and inflammatory parameters
Albumin (g/dL)	3.5–5.2	3.2 (0.5)	3.3 (3.0)	+ 0.1	0.923
Ferritin (ng/mL)	20.0–275.0	1,641.2 (1,130.6)	1,768.7 (1,287.6)	+ 127.5	0.213
Transferrin (mg/dL)	200.0–360.0	146.1 (25.5)	161.6 (41.5)	+ 15.5	0.036
TSI (%)	17.1–30.6	46.1 (34.5)	38.3 (26.9)	–7.9	0.183
Fibrinogen (mg/dL)	200.0–350.0	651.1 (211.1)	556.4 (189.9)	–94.6	0.001
D-dimer (ng/mL)	0.0–500.0	1,291.0 (1,246.9)	2,049.6 (1,842.5)	+ 751.3	0.001
CRP (mg/L)	0.0–5.0	120.6 (86.8)	75.5 (70.6)	–45.2	0.001
GOT (U/L)	5–40	42.2 (29.7)	37.5 (32.7)	–4.7	0.238
GPT (U/L)	0–55	48.5 (46.5)	62.1 (73.7)	+ 13.6	0.025
GGT (U/L)	1–55	99.8 (108.6)	142.3 (198.3)	+ 42.5	0.008
LDH (U/L)	0–248	519.6 (19.1)	463.1 (187.8)	–56.5	0.008
Hb (g/dL)	11.0–17.0	13.1 (2.0)	12.4 (2.1)	–0.7	0.001
Hematocrit (%)	30.0–50.0	38.4 (5.7)	36.7 (5.7)	–1.7	0.001
Leukocytes (x10³/µL)	3.5–10.5	11.6 (6.2)	10.5 (5.4)	–1.1	0.046
Lymphocytes (%)	20.0–44.0	7.2 (4.4)	9.7 (8.1)	+ 2.5	0.005
Neutrophils (%)	42.0–77.0	88.4 (5.6)	82.3 (13.8)	–6.1	0.001
Platelets (x10³/µL)	120.0–450.0	232.5 (89.6)	256.6 (104.5)	+ 24.1	0.006
TNT (ng/L)	< 14.0	19.7 (41.5)	12.9 (28.6)	–6.8	0.151
APTT (s)	26.0–37.0	28.9 (3.9)	29.2 (4.2)	–0.3	0.655
INR	0.80–1.2	1.1 (0.3)	1.0 (0.2)	–0.1	0.367
Minerals
Iron (mg/L)	0.6–1.70	1.7 (0.9)	1.5 (0.9)	–0.2	0.197
Zinc (mg/L)	0.7–1.10	0.9 (0.3)	0.8 (0.4)	–0.1	0.607
Copper (µg/L)	0.6–1.40	0.6 (0.4)	0.5 (0.3)	–0.1	0.005
Manganese (µg/L)	0.4–0.85	0.5 (0.1)	0.4 (0.1)	–0.1	0.704
Metallothioneins
MTs (µmol/L)	–	0.3 (0.1)	0.2 (0.1)	–0.1	0.022
n = 86. Data expressed as mean (standard deviation) unless otherwise stated. Paired Student’s t-test was used to compare the evolution of the variables between 1st and 3rd days of the ICU stay. Mean differences represent the difference between the value of the 3rd and 1st days of ICU stay. Significant P-Values are represented in bold. Statistical significance = P < 0.05. Abbreviations: APTT = Activated Partial Thromboplastin Time; CRP = C-Reactive Protein; Cu = Copper; Fe = Iron; GOT = Glutamic Oxaloacetic Transaminase; GPT = Glutamic Pyruvic Transaminase; GGT = Gamma-Glutamyl Transferase; Hb = Hemoglobin; INR = International Normalized Ratio; LDH = Lactate Dehydrogenase; Mn = Manganese; MTs = Metallothioneins; SD = Standard Deviation; TNT = Troponin T; TSI = Transferrin Saturation Index; Zn = Zinc.

*** please insert Table 1here ***

Figure 1 represents the percentage of patients with deficient status in the studied minerals on the 1st and 3rd days of ICU stay. The percentage of Cu deficiency increased significantly from 50–65.3% (P = 0.015) on the 3rd day of ICU stay. The deficiency prevalence in the case of the remaining minerals showed no significant differences after 3 days of ICU stay (all P ≥ 0.05).

*** please insert Fig. 1here ***

Table 2 shows the differences in changes in the clinical, biochemical, and inflammatory parameters occurring during ICU stay based on the median changes in mineral and MTs levels. Higher changes in Fe levels were found in patients presenting higher changes in HR (P = 0.005). Moreover, higher changes in TSI, fibrinogen, CRP, and neutrophils (all P ≤ 0.031) and lower changes in lymphocyte levels (P = 0.023) were found in those presenting higher changes in Cu levels. Furthermore, individuals with higher changes in Mn showed higher changes in albumin (P = 0.044) and lowered CRP (P = 0.038) levels. The rest of the variables showed no differences based on the median changes in the level of minerals and MTs (all P ≥ 0.073).

Table 2

Changes in clinical, biochemical, and inflammatory parameters based on the median changes in minerals and MTs occurring during the ICU stay.
n = 86 Δ Change	Δ Fe		Δ Zn		Δ Cu		Δ Mn		Δ MTs
n = 86 Δ Change	Δ	P-Value	Δ	P-Value	Δ	P-Value	Δ	P-Value	Δ	P-Value
Clinical parameters
SOFA	+ 0.05	0.917	+ 0.45	0.576	+ 0.06	0.908	+ 0.88	0.170	+ 0.08	0.895
MAP	+ 5.50	0.506	–2.40	0.893	+ 16.6	0.095	+ 12.8	0.182	+ 3.62	0.658
HR	–25.1	0.006	–6.15	0.592	+ 2.88	0.807	–11.5	0.295	+ 3.73	0.677
BR	–0.48	0.862	–1.43	0.329	+ 3.23	0.253	–2.09	0.521	+ 2.15	0.509
FiO₂	+ 0.01	0.806	–0.03	0.456	–0.04	0.439	+ 0.05	0.480	–0.05	0.431
PaO₂/FiO₂	+ 23.1	0.618	–0.12	0.415	+ 21.6	0.679	+ 43.1	0.499	+ 74.1	0.151
PEEP	+ 0.93	0.266	–1.23	0.146	–1.10	0.242	–0.87	0.396	+ 0.81	0.322
Biochemical and inflammatory parameters
Albumin	+ 0.75	0.325	–2.25	0.363	–0.04	0.617	+ 1.95	0.044	–0.81	0.359
Ferritin	+ 177.7	0.392	–71.5	0.884	+ 15.5	0.948	–92.8	0.720	–117.4	0.613
Transferrin	–23.4	0.091	+ 26.4	0.214	–1.19	0.944	–5.11	0.764	+ 1.25	0.943
TSI	+ 12.1	0.301	–17.5	0.347	+ 25.5	0.031	+ 19.0	0.153	–5.02	0.726
Fibrinogen	+ 27.2	0.527	+ 58.4	0.427	+ 148.5	0.001	+ 54.1	0.319	+ 15.3	0.737
D-dimer	–1315.0	0.294	+ 1797.0	0.484	+ 504.6	0.723	–1526.2	0.340	+ 265.7	0.855
CRP	–13.8	0.438	+ 18.3	0.605	+ 44.0	0.017	–45.4	0.038	+ 6.62	0.734
GOT	–13.9	0.090	+ 9.71	0.402	–2.09	0.812	–15.8	0.115	–2.01	0.832
GPT	–22.1	0.073	+ 11.7	0.544	–19.9	0.121	+ 2.51	0.866	–8.50	0.522
GGT	+ 35.2	0.284	+ 25.4	0.471	+ 43.4	0.229	+ 87.1	0.211	+ 24.6	0.498
LDH	+ 31.6	0.464	–50.9	0.371	+ 78.0	0.104	+ 18.0	0.746	+ 68.2	0.151
Hb	–0.12	0.615	+ 0.28	0.524	+ 0.18	0.505	+ 0.06	0.843	+ 0.30	0.270
Haematocrit	–0.61	0.432	+ 0.90	0.527	+ 0.46	0.588	+ 0.34	0.714	+ 0.62	0.463
Leukocytes	+ 0.38	0.719	+ 2.63	0.113	+ 1.41	0.221	+ 0.20	0.876	+ 0.14	0.898
Lymphocytes	–0.85	0.639	–0.67	0.880	–4.57	0.023	+ 0.95	0.671	+ 1.74	0.364
Neutrophils	+ 1.63	0.605	–6.33	0.407	+ 6.51	0.030	–0.46	0.890	–3.48	0.243
Platelets	–2.33	0.897	+ 54.9	0.085	–6.65	0.716	+ 0.53	0.979	–16.1	0.416
TNT	+ 13.5	0.290	+ 9.25	0.208	–1.12	0.936	+ 24.2	0.161	–11.1	0.444
APTT	–1.74	0.098	+ 1.85	0.192	–0.20	0.849	–1.07	0.401	–0.62	0.585
INR	–0.12	0.075	–0.14	0.258	+ 0.02	0.811	+ 0.01	0.942	–0.01	0.841
n = 86. Data expressed as mean (standard deviation) unless otherwise stated. Δ represents the difference between the value on the 3rd and the 1st days of the ICU stay. Unpaired Student’s t-test was used to compare the changes in clinical, biochemical, and inflammatory parameters of the study based on the median changes in the levels of minerals and MTs. Significant P-Values are represented in bold. Statistical significance = P < 0.05. Abbreviations: APTT = Activated Partial Thromboplastin Time; BR = Breathing Rate; CRP = C-Reactive Protein; Cu = Copper; Fe = Iron; GOT = Glutamic Oxaloacetic Transaminase; GPT = Glutamic Pyruvic Transaminase; GGT = Gamma-Glutamyl Transferase; Hb = Hemoglobin; HR = Heart Rate; INR = International Normalized Ratio; LDH = Lactate Dehydrogenase; MAP = Mean Arterial Pressure; MTs = Metallothioneins; PaO₂/FiO₂ = Partial Oxygen arterial pressure/Fraction of Inspired Oxygen; PEEP = Positive End-Expiratory Pressure; SOFA = Sequential Organ Failure Assessment. TNT = Troponin T; TSI = Transferrin Saturation Index; Zn = Zinc.

*** please insert Table 2here ***

Table 3 represents the relationship between changes in minerals and MTs with clinical, biochemical, and inflammatory parameters after 3 days of evolution in the ICU. Changes in Fe were directly related to changes in Cu and Mn (all r ≥ 0.266; P ≤ 0.019). Changes in Zn were positively linked to changes in PaO₂/FiO₂ and platelets (all r ≥ 0.494; P ≤ 0.010) and negatively associated with changes in BR and INR (all r≥–0.480; P ≤ 0.026). Changes in Cu were positively related to changes in fibrinogen and CRP (all r≥–0.276; P ≤ 0.019). Changes in Mn were directly associated with changes in fibrinogen (r = 0.250; P = 0.039) and negatively related to changes in GOT (r = 0.221; P = 0.049). Finally, changes in MTs were inversely associated with changes in Mn and albumin (all r≥–0.255; P ≤ 0.039).

Table 3

Matrix for correlation coefficients (r) showing the simple linear relationship between minerals and MTs with clinical, biochemical, inflammatory, minerals, and MTs parameters of the study.
n = 86 Δ Change	Δ Fe	Δ Zn	Δ Cu	Δ Mn	Δ MTs
Clinical parameters
SOFA	–0.076	+ 0.026	–0.127	+ 0.209	+ 0.042
MAP	+ 0.087	–0.377	+ 0.226	+ 0.159	+ 0.300
HR	–0.258	–0.189	–0.079	+ 0.073	+ 0.146
BR	–0.229	–0.815^*	+ 0.251	–0.366	–0.133
FiO₂	0.058	–0.179	–0.220	+ 0.390	+ 0.142
PaO₂/FiO₂	–0.166	+ 0.963^*	+ 0.262	–0.653	+ 0.113
PEEP	–0.002	–0.295	–0.083	+ 0.288	–0.095
Biochemical and inflammatory parameters
Albumin	+ 0.060	–0.059	–0.068	+ 0.043	–0.328^*
Ferritin	+ 0.054	+ 0.223	+ 0.069	+ 0.021	+ 0.030
Transferrin	–0.163	+ 0.359	–0.050	+ 0.029	+ 0.025
TSI	+ 0.066	–0.138	+ 0.404	+ 0.232	–0.230
Fibrinogen	+ 0.131	–0.148	+ 0.447^**	+ 0.250^*	+ 0.077
D-dimer	+ 0.015	+ 0.185	+ 0.081	–0.066	+ 0.033
CRP	–0.015	–0.264	+ 0.276^*	–0.079	+ 0.053
GOT	+ 0.029	–0.114	–0.086	–0.221^*	+ 0.030
GPT	+ 0.031	+ 0.115	–0.195	–0.164	–0.054
GGT	+ 0.114	+ 0.215	+ 0.063	+ 0.113	+ 0.001
LDH	+ 0.112	–0.210	+ 0.205	+ 0.145	+ 0.103
Hb	–0.035	+ 0.219	+ 0.160	–0.111	+ 0.083
Hematocrit	–0.064	+ 0.313	+ 0.122	–0.151	0.051
Leukocytes	+ 0.153	+ 0.070	+ 0.129	+ 0.078	–0.194
Lymphocytes	–0.139	–0.031	–0.204	+ 0.012	+ 0.060
Neutrophils	–0.003	–0.183	+ 0.173	+ 0.011	–0.076
Platelets	+ 0.117	+ 0.494^*	+ 0.076	+ 0.068	–0.193
TNT	+ 0.001	+ 0.156	+ 0.019	+ 0.298	–0.022
APTT	–0.174	–0.065	+ 0.006	–0.117	–0.064
INR	–0.147	–0.480^*	–0.199	–0.154	+ 0.040
Minerals
Fe	–	–	–	–	+ 0.039
Zn	–0.262	–	–	–	–0.152
Cu	+ 0.282^*	–0.330	–	–	–0.022
Mn	+ 0.266^*	+ 0.197	+ 0.059	–	–0.255^*
Metallothioneins
MTs	–	–	–	–	–
n = 86. Pearson’s correlation was used to compare the simple linear relationship between changes in minerals and MTs and clinical, biochemical, inflammatory, minerals, and MTs values. Δ represents the difference between the value of the 3rd and the 1st days of the ICU stay. Significant P-Values are represented in bold. Matrix correlations are presented as correlation coefficients (r). Statistical significance = P < 0.05 and *P < 0.001. Abbreviations: APTT = Activated Partial Thromboplastin Time; BR = Breathing Rate; CRP = C-Reactive Protein; Cu = Copper; Fe = Iron; GOT = Glutamic Oxaloacetic Transaminase; GPT = Glutamic Pyruvic Transaminase; GGT = Gamma-Glutamyl Transferase; Hb = Hemoglobin; HR = Heart Rate; INR = International Normalized Ratio; LDH = Lactate Dehydrogenase; MAP = Mean Arterial Pressure; MTs = Metallothioneins; PaO₂/FiO₂ = Partial Oxygen arterial pressure/Fraction of Inspired Oxygen; PEEP = Positive End-Expiratory Pressure; SOFA = Sequential Organ Failure Assessment. TNT = Troponin T; TSI = Transferrin Saturation Index; Zn = Zinc.

*** please insert Table 3here ***

Figure 2 shows the ROC curves of Fe and Zn as mortality and severity predictors. The areas under the curve were 0.655 (95% CI 0.533–0.778) for changes in Fe predicting mortality and 0.652 (95% CI 0.531–0.773) for Fe predicting SOFA at ICU admission. In the same way, the areas under the curve were 0.709 (95% CI 0.503–0.914) for Zn predicting APACHE on the 1st day of ICU stay and 0.768 (95% CI 0.586–0.951) for Zn predicting SOFA on the 3rd day of ICU stay.

*** please insert Fig. 2here ***

The main findings of the present study showed a relatively high prevalence of mineral deficiency (i.e., 11.9–50%) at ICU admission, increasing (i.e., 14.3–65.3%) after 3 days – in the case of Cu being significant–. Additionally, MTs levels decreased after 3 days of ICU stay. Changes in Fe levels were directly associated with changes in circulating Mn and Cu –these changes in Fe also being a prognostic biomarker of severity and mortality –. Changes in Zn levels were also predictors of severity. Contrary to our previous hypothesis, no relationship was found between changes in MTs and changes in both Zn and Cu levels, being MTs changes inversely associated with changes in Mn and albumin levels. The present study highlights the potential benefit of assessing the mineral status and MTs at early stages in critical patients with severe COVID-19 infections to characterize the disease, identify and reverse deficiency conditions, and improve the treatment and prognosis of these patients.

SARSCoV-2 infection is a heterogeneous illness because not all patients develop the same symptoms. However, some parameters have been reported as a common finding in cases with worse prognosis (i.e., thrombocytopenia or higher CRP, D-dimer, transferrin, and LDH levels, among others) ²⁴. In our study, patients showed altered values for most clinical and biochemical parameters at ICU admission, observing changes with an apparent trend towards normalized values (i.e., BR, PaO₂/FiO₂, transferrin, fibrinogen, leukocytes) after 3 days. However, levels of many variables remained altered, worsening during ICU stay (i.e., D-dimer, GGT, GPT), underscoring the complexity of the clinical situation of these patients. Over-exuberant inflammatory response and dysregulated host immune system are common findings in severe cases of COVID-19 ²⁵. Among other effects, inflammatory processes lead to oxidative stress and altered levels of different trace elements in serum ²⁶.

Regarding Fe levels, our results showed normal mean values for this mineral at baseline and follow-up, being the prevalence of deficiency around 10%. Moreover, Fe levels at baseline predicted severity, and changes in its levels during ICU stay predicted mortality. The relationship between Fe levels and susceptibility to infection remains complex because, on the one hand, Fe could reduce the vulnerability to respiratory infections via enhancing natural killer cell activity, T lymphocyte proliferation, or production of T helper 1 cytokines, but on the other, infections caused by organisms that spend part of their life-cycle intracellularly may be enhanced by Fe ²⁷. Indeed, it has been described that coronavirus can capture Fe and generate reactive oxygen species to damage the human immune system ²⁸. Additionally, it must be noted that, although Fe levels were within normal values, important disturbances were found in ferritin levels. It has been reported that changes in Fe metabolism can be used to predict death in patients admitted to ICU because serum ferritin has been identified as one of the predictors of death in COVID-19 patients ^29,30. Hyperferritinemia – a key acute-phase reactant – could represent a host defense mechanism depriving bacterial growth of iron and protecting immune cell function. However, there is a need for further investigation of the role of ferritin in uncontrolled inflammatory conditions ²⁹.

Similarly, we found normal mean values of circulating Zn – more than one-third of the patients presenting deficient levels – at ICU admission and after 3 days of stay. Lower Zn levels during the early phase of ICU stay in patients with COVID-19 infection have been reported previously ^31,32. Hypozincemia in these patients is characteristic, and it is possible due to redistribution processes from blood to the liver at the expense of Zn in other tissues ³³. Furthermore, we found that changes in Zn levels were directly associated with changes in PaO₂/FiO₂ and platelets and inversely related to changes in BR and INR. Likewise, Zn levels presented predictive values for severity scales. These results, altogether, appear to suggest that higher levels of Zn are related to better clinical outcomes. In consistency with that, Maares et al. ³⁴ found an association between serum Zn levels and increased risk of death, suggesting that Zn may serve as a prognostic marker for the severity and course of COVID-19. Additionally, Notz et al. ³⁵ reported that circulating Zn – below the reference range in patients with severe COVID-19 – was restored after supplementation within two weeks of intensive care, supporting the possible beneficial effect of Zn supplementation.

Circulating Cu levels decreased during ICU stay – the mean levels being below normal values – reaching 65% the prevalence of deficiency at the first 3 days of ICU stay. Cu levels were directly related to fibrinogen, platelets, and CRP levels, and inversely related to INR. Moreover, patients with higher changes in Cu levels presented higher variations in TSI and neutrophils and lower changes in lymphocyte levels. A decrease in lymphocyte levels has been previously linked to a higher mortality risk, and an increase in CRP is linked to severe prognosis in COVID-19 patients ²⁴. Our study shows that better clinical, biochemical, and inflammatory parameters are associated with lower concentrations of circulating Cu during this acute phase of infection. Indeed, Cu levels have been previously associated with CRP, suggesting an association between serum Cu levels and COVID-19 severity ³¹. Thus, a possible inflammatory and pro-oxidant role of Cu in COVID-19 pathogenesis has been hypothesized ³⁶. In contrast, Hackler et al. ³⁷ found elevated serum Cu levels at hospital admission in the surviving patients compared with non-survivors and with the reference range – no patient showing Cu levels below the reference range –. These discrepancies could be due to differences in patients’ severity and inflammatory conditions. Further research is needed to know the role of circulating Cu on outcomes in critically ill patients with COVID-19.

Concerning Mn levels, our study revealed that the prevalence of deficiency affected one-third of patients at follow-up, being Mn changes inversely related to changes in GOT and MTs levels and directly associated with changes in fibrinogen, Fe, and Cu. No differences in Mn levels were found by Zhou et al. ³⁸ when they compared mild and severe groups of patients with COVID-19. On the other hand, Zeng et al. ³⁹ found higher urinary excretion of Mn and other trace elements in severe patients than in non-severe cases. In general, Mn levels appear to follow the trend of other trace elements, and Mn could play a role in the pathogenesis of this disease. However, the evidence assessing Mn levels and their effects on COVID-19 is scarce and inconclusive to date.

Although MTs play a major role in the homeostasis of Zn and Cu and detoxification processes, their biological function is still debatable ^40,41. In cellular processes, MTs are known to have metallo-regulatory functions (i.e., growth, differentiation, and protective role in oxidative stress) ¹⁶. Our results showed a significant decrease in circulating MTs concentration during ICU stay, being these changes in MTs levels inversely correlated to changes in albumin levels. Metal-Cys clusters in MTs – together with disulfide moieties in serum albumins – are considered good interceptors of free radicals ⁴². Therefore, circulating MTs could be determinant in antioxidant processes; their levels are influenced by oxidative stress and inflammation. Moreover, contrary to our previous hypothesis, no relationship was found between changes in MTs levels and Zn and Cu levels, being only inversely associated with changes in Mn levels. It has been observed that chronic low-level exposure to Mn in rats significantly decreases hepatic MTs – the liver being the organ with the highest concentration of MTs – ⁴³. Furthermore, the effect of inflammation on circulating MTs and mineral levels remains unclear. In patients with chronic exacerbated pancreatitis, a significant increase in circulating MTs concentration was accompanied by a decrease in Zn and an increase in Cu levels ⁴⁴. Nevertheless, MTs levels were lower in patients with hepatitis C than in healthy controls. In contrast, in other chronic hepatitis cases, MTs levels increased gradually, followed by the progression of the disease to liver cirrhosis and hepatocellular carcinoma ⁴⁵. Further studies are needed to fully understand the relationships between MTs and mineral levels and their implications in clinical outcomes, especially during inflammatory conditions. Moreover, the last revised European Society of Parenteral and Enteral Nutrition (ESPEN) guidelines ⁴⁶ about early nutritional supply and micronutrient supplements should also be considered in these patients’ management.

The findings reported in the present study should be treated with caution as some limitations arise. Firstly, follow-up during the 3-day stay in the ICU did not allow us to establish causal relationships as no intervention was performed. Secondly, the recruited patients were from a single Hospital, and some potential confounding factors (sociodemographic and socioeconomic status) were not evaluated. Thus, these outcomes cannot be generalized to other populations, especially considering the wide range of COVID-19 prevalence. Finally, the overall negative results may be related to the heterogeneity of the subjects and their underlying disease conditions or severity. Replicating this study in a larger and heterogeneous critically ill population with a control group could further corroborate our findings.

In summary, the present study in critically ill patients with COVID-19 indicated an apparent risk of deficiency of trace element status at ICU admission, worsening after 3 days of stay. Cu and MTs levels decreased significantly during this period, whereas Fe and Zn levels were shown as mortality and severity predictors. Different biochemical and clinical parameters were related to the studied variables. Therefore, we suggest monitoring the mineral status and performing nutritional interventions, when appropriate, that could help to improve the altered parameters, such as inflammatory conditions and, thus, the prognosis in critically ill patients with COVID-19.

Informed Consent Statement: Informed consent and consent for publication was obtained from all subjects involved in the study.

Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the University of Granada (protocol code 149/CEIH/2016).

Availability of Data and Materials: Data will be shared upon reasonable request by the corresponding authors: Héctor Vázquez-Lorente & Lourdes Herrera-Quintana.

Conflict of interest: The authors have declared no conflicts of interest. Complete Declaration of Interest forms for each author has been uploaded at the time of manuscript submission.

Funding/support: This research was funded by Project FIS PI10/1993 from the Spanish Carlos III Health Institute, the European Regional Development Fund (ERDF) “a way of making Europe” funded via the Consejería de Universidad, Investigación e Innovación de la Junta de Andalucía [REF. A-CTS-708-UGR20]. Lourdes Herrera-Quintana [REF. FPU18/03702] and Héctor Vázquez-Lorente [REF. FPU18/03655] were awarded a FPU fellowship from the Spanish Ministry of Education.

Authors’ Contributions: Conceptualization, L. H.-Q., H. V.-L. and E. P.; Methodology, L. H.-Q., H. V.-L., A. V., L. R. and E. P.; Software, H. V.-L., L. H.-Q. and Y. G.-M.; Formal analysis, L. H.-Q., H. V.-L., A. V. and L. R.; Investigation, Y. G.-M.; Resources, E. P. and J. M.-L.; Writing - original draft preparation, L. H.-Q. and H. V.-L.; Writing - review and editing, L. H.-Q., H. V.-L., J. M.-L. and E. P.; Supervision, J. M.-L. and E. P.; Project administration, E. P.; Funding acquisition, E. P. All authors approved the final draft of the manuscript for publication.

Acknowledgements: The authors thank all the patients who participated in our study and the personnel from the hospital Virgen de las Nieves and FIBAO foundation in Granada (Spain). We also acknowledge Nutraceutical Translations for English language editing.

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No competing interests reported.

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Changes in trace elements and metallothioneins levels and their relationship with clinical, biochemical, and inflammatory parameters in patients with COVID-19 during the early ICU phase

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1. Introduction

2. Materials And Methods

2.1. Subjects and study design

2.2. Data collection

2.3. Blood sampling and biochemical parameters analysis

2.3.1. Assessment of biochemical and inflammatory parameters and mineral levels

2.3.2. Sample processing and differential pulse voltammetry Brdicka reaction for determination of MTs

2.4. Statistical analysis

3. Results

4. Discussion

5. Conclusions

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