Bioscience Biotechnology Research Communications

An Open Access International Journal

P-ISSN: 0974-6455 E-ISSN: 2321-4007

Bioscience Biotechnology Research Communications

An Open Access International Journal

Arul Senghor K. Aravaanan, Renuka Pangaluri, Prabu Muthuperumal, Meera
Shivasekar, Nellaiappa Ganesan and *Vinodhini V. Mohanakrishnan

Department of Biochemistry, SRM Medical College Hospital and Research Centre, SRM Institute
of Science and Technology, Kattankulathur, Kanchipuram, Chennai, Tamil Nadu, India.

Corresponding author email: vinodhiv1@srmist.edu.in

Article Publishing History

Received: 25/10/2021

Accepted After Revision: 15/12/2021

ABSTRACT:

Novel coronavirus causing the pandemic infectious disease termed as COVID-19 is characterized by respiratory illness which may lead on to acute respiratory distress syndrome.  Ferritin is a key mediator of immune dysregulation leading on to cytokine storm. Alterations in various biochemical parameters have been widely reported in COVID-19.  Early identification of effective biomarkers to assess the severity of this disease is essential. Our study was aimed to evaluate the variations in the routinely analysed biochemical parameters and their association with ferritin levels among COVID patients. The study participants consisted of 270 members among which 149 were COVID positive and 121 were negative.  Analysis of the routine biochemical parameters as well as ferritin level were carried out.

Among the 149 positive cases, 84 (56.4%) were mild positive with ferritin levels <500ng/ml and 65 (43.6%) were severe positive with ferritin levels >500ng/ml. We reported significant increase in serum ferritin levels in severe positive samples (1449.84 ± 249.47) compared to mild positive samples (230.04 ± 17.41). We observed increased levels of total bilirubin in 12.7%, direct bilirubin in 16.8%, indirect bilirubin in 8.7%, AST in 65.8%, ALT in 44.3%, ALP in 9.4%, GGT in 51.7%, urea in 18.4%, creatinine in 14.3%, BUN in 18.4% and decreased levels of total protein and albumin in 23.5% positive patients compared to negative patients. Ferritin and its associated biochemical parameters act as predictors of COVID severity. These biochemical alterations suggest the significance of early risk assessment and monitoring of COVID patients.

KEYWORDS:

Biochemical Parameters, COVID-19, Electrolyte Abnormalities, Ferritin, Liver Function Tests.

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Aravaanan A.S.K, Pangaluri R, Muthuperuma P, Shivasekar M, Ganesan N, Mohanakrishnan V.V. Alterations in Various Biochemical Parameters Among Covid-19 Patients: An Observational Retrospective Analysis. Biosc.Biotech.Res.Comm. 2021;14(4).


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Aravaanan A.S.K, Pangaluri R, Muthuperuma P, Shivasekar M, Ganesan N, Mohanakrishnan V.V. Alterations in Various Biochemical Parameters Among Covid-19 Patients: An Observational Retrospective Analysis. Biosc.Biotech.Res.Comm. 2021;14(4). Available from: <a href=”https://bit.ly/3xwKrVZ“>https://bit.ly/3xwKrVZ</a>


INTRODUCTION

COVID-19 which has been officially declared as a pandemic by the World Health Organization is characterised by respiratory illness which may progress on to severe pneumonia and acute respiratory distress syndrome (ARDS) (Park et al. 2020; Mbarka et al. 2020; Ashour et al. 2020). Since the outbreak of the coronavirus pandemic several abnormalities in various biochemical parameters have been reported but their clinical implications need to be investigated.

Several meta-analyses have thrown light on the importance of serial assessment of biochemical parameters namely ferritin, lactate dehydrogenase (LDH), total bilirubin, total protein, albumin, aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), gamma glutamyl transferase (GGT), urea, creatinine and electrolytes in evaluation of risk. Ferritin is a key mediator of immune dysregulation via direct immunosuppressive and pro-inflammatory effects contributing to cytokine storm (Ashour et al. 2020; Henry et al. 2020).

Ferritin may be considered as a strong discriminator for potential progression to critical illness of COVID-19 (Zhou et al. 2020). In view of the limited resources available, the early diagnosis of severe COVID-19 is of great importance to reduce morbidity and mortality. Assessing serum ferritin levels along with identification of derangements of other biochemical parameters during hospitalization can help to identify at risk individuals with COVID-19.

The advantage of utilizing these parameters for effective triaging is the availability of highly standardized automated analyzers and reagent kits which offer rapid, reliable, reproducible results which are also economical (Henry et al. 2020). This study is proposed to identify potential biochemical laboratory markers which can be used to assess the progression of disease from mild to severe form and help in timely triaging of the patients.

MATERIAL AND METHODS

This retrospective study included patients of SRM Medical College Hospital and Research Centre, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Kanchipuram, Chennai, Tamil Nadu, India.  This study was carried out between the months of May and August 2020.   Patients who tested positive for COVID-19 by RT-PCR testing were included as the study group and those who tested negative for COVID-19 by RT-PCR testing on admission were chosen as the control group.  The study protocol was approved by the Scientific and Ethical committees of our Institution (IEC No: 1977/IEC/2020). All the samples were collected and processed as per the ICMR safety guidelines.

The parameters of renal function test, liver function test, serum electrolytes and lactate dehydrogenase were estimated using Beckman Coulter Auto analyser. Ferritin level was measured in Enhanced CLIA-Vitros ECi immunoanalyzer.  After completion of estimations, the sample processing area and instruments were sterilized using hypochlorite solution and alcohol-based sanitizer. The biohazard materials used during the sample processing were disposed appropriately as per instructions in the safety guidelines.

Based on the ferritin values obtained, the patients were categorized as having mild or severe coronavirus disease using a cut-off value of 500 ng/ml (Lin et al. 2020). The statistical analysis of study parameters was done using SPSS software (version 22). Student’s test was used for comparison of parameters between the groups. Pearson’s correlation was utilized to assess the association between the various parameters and multiple comparison analysis was done using ANOVA.

RESULTS AND DISCUSSION

The study participants included 270 symptomatic patients who underwent COVID testing on the day of admission. Among them 149 (55%) tested positive and 121 (45%) were negative.  Among the 149 positive cases, 111 (74.5%) were males and 38 (25.5%) were females. Amidst the 121 negative cases, 75 (62.0%) were males and 46 (38.0%) were females. We observed that males were more prone to COVID infection as compared to females. The maximum numbers of positive cases were found in the age group of above 60 years (Table 1).

Table 1. Age Group of  Participants

Age group Positive (n-149) Negative (121)
<20 0 6 (4.96 %)
20-29 13 (8.72 %) 21 (17.36%)
30-39 33 (22.15%) 39 (32.23%)
40-49 33 (22.15%) 22 (18.18 %)
50-59 25 (16.78 %) 23 (19.01 %)
≥60 45 (30.20 %) 10 (8.26 %)

The lactate dehydrogenase levels in adults ranges from 140-280 U/L. We found 44 (40%) of Covid positive patients having LDH in the normal range whereas 64 (58.2%) had LDH levels greater than 280 U/L.

Table 2. Chi square analysis between gender and ferritin

Ferritin levels

(ng/ml)

Positive (N-149) Negative (N-121)
Male (N-111) Female (N-38) Male (N-75) Female (N-46)
<500 ng/ml 52 (46.8%) 32 (84.2%) 63 (84.0%) 44 (95.7%)
>500 ng/ml 59 (53.2%) 6 (15.8%) 12 (16.0%) 2 (4.3%)

We observed significant increase in the levels of ferritin, lactate dehydrogenase, urea, creatinine, BUN, potassium, total bilirubin, direct bilirubin, alanine transaminase, gamma glutamyl transferase and significant decrease in the levels of sodium, chloride, total protein, albumin between positive and negative COVID samples (Table 3).

Table 3. Analysis of positive and negative samples

Parameters

 

Positive Negative Significance

P-value

N Mean ± SEM N Mean ± SEM
Ferritin (ng/ml) 149 762.16 ± 119.62 121 264.99 ± 31.95 0.000***
LDH (U/L) 110 359.94 ± 22.76 105 272.66 ± 9.74 0.001**
Urea (mg/dl) 149 38.96 ± 3.56 121 24.37 ± 1.40 0.001**
Creatinine (mg/dl) 149 1.55 ± 0.21 121 0.76 ± 0.04 0.001**
BUN (mg/dl) 149 18.20 ± 1.66 121 11.38 ± 0.66 0.001**
Sodium (mmol/l) 146 134.84 ± 0.99 115 137.50 ± 0.28 0.021*
Potassium (mmol/l) 145 4.09 ± 0.05 115 3.94 ± 0.03 0.017*
Chloride (mmol/l) 145 100.67 ± 0.39 115 102.58 ± 0.33 0.000***
Bicarbonate (mmol/l) 145 24.19 ± 0.59 115 24.62 ± 0.28 0.544
Total bilirubin (mg/dl) 149 0.69 ± 0.03 120 0.59 ± 0.03 0.023*
Direct bilirubin (mg/dl) 149 0.20 ± 0.02 120 0.16 ± 0.02 0.049*
Indirect bilirubin (mg/dl) 149 0.49 ± 0.03 120 0.43 ± 0.02 0.092
Total protein (g/dl) 149 7.03 ± 0.08 120 7.34 ± 0.06 0.003**
Albumin (g/dl) 149 3.88 ± 0.06 120 4.08 ± 0.05 0.013*
Globulin (g/dl) 149 3.23 ± 0.04 120 3.25 ± 0.03 0.703
AG ratio 149 1.23 ± 0.02 121 1.26 ± 0.02 0.248
AST (IU/L) 149 59.16 ±11.68 120 35.37 ± 2.02 0.071
ALT (IU/L) 148 50.01 ± 7.40 120 30.08 ± 1.80 0.018*
ALP (IU/L) 148 88.21 ± 6.83 120 84.21 ± 3.34 0.625
GGT (U/L) 149 51.68 ± 4.08 120 40.50 ± 3.63 0.047*
Significance: *P<0.05, **P<0.01, ***P<0.001

We observed significant increase in the levels of ferritin, lactate dehydrogenase, urea, creatinine, BUN, total bilirubin, direct bilirubin, indirect bilirubin, AG ratio, alanine transaminase and gamma glutamyl transferase and significant decrease in the levels of chloride, total protein, albumin in severe positive (ferritin levels >500ng/ml) compared to mild positive (ferritin levels <500ng/ml) [Table 4].

Table 4. Unpaired ‘t test between mild (ferritin <500ng/ml) and severe (ferritin >500ng/ml) positive groups

Parameters Mild positive

Ferritin <500 ng/ml

Severe positive

Ferritin >500 ng/ml

Significance

P-value

N Mean ± SEM N Mean ± SEM
Ferritin (ng/ml) 84 230.04 ± 17.41 65 1449.84 ± 249.47 0.000***
LDH (U/L) 69 285.97 ± 13.25 41 484.41 ± 51.65 0.000***
Urea (mg/dl) 84 27.70 ± 2.23 65 53.51 ± 7.27 0.000***
     Creatinine (mg/dl) 84 1.18 ± 0.22 65 2.02 ± 0.39 0.048*
BUN (mg/dl) 84 12.93 ± 1.04 65 24.99 ± 3.40 0.000*
Sodium (mmol/l) 82 136.38 ± 0.43 64 132.88 ± 2.19 0.081
Potassium (mmol/l) 82 4.09 ± 0.07 63 4.09 ± 0.08 0.977
Chloride (mmol/l) 82 101.79 ± 0.49 63 99.21 ± 0.58 0.001**
Bicarbonate (mmol/l) 82 25.01 ± 0.94 63 23.11 ± 0.59 0.112
  Total bilirubin (mg/dl) 84 0.60 ± 0.04 65 0.80 ± 0.05 0.004**
Direct bilirubin (mg/dl) 84 0.17 ± 0.02 65 0.25 ± 0.03 0.028*
Indirect bilirubin

(mg/dl)

84 0.43 ± 0.04 65 0.56 ± 0.03 0.023*
Total protein (g/dl) 84 7.19 ± 0.11 65 6.81 ± 0.11 0.017*
Albumin (g/dl) 84 4.08 ± 0.08 65 3.64 ± 0.07 0.000***
Globulin (g/dl) 84 3.28 ± 0.05 65 3.17 ± 0.07 0.203
AG ratio 84 1.26 ± 0.03 65 1.18 ± 0.03 0.047*
AST (IU/L)  84 40.44 ± 5.30 65 83.35 ± 25.70 0.068
ALT (IU/L) 83 33.08 ±3.25 65 71.61 ± 15.99 0.009**
ALP (IU/L) 83 79.23 ± 3.81 65 99.68 ± 14.72 0.138
GGT (U/L) 84 39.61± 4.16 65 67.29 ± 7.25 0.001**
Significance: *P<0.05, **P<0.01, ***P<0.001

A significant positive correlation of ferritin was found with lactate dehydrogenase, urea, creatinine, BUN, potassium, total bilirubin, direct bilirubin, indirect bilirubin, aspartate transaminase, alanine transaminase and alkaline phosphatase. A significant negative correlation of ferritin was found with chloride and albumin in COVID positive patients [Table 5]. A significant positive correlation of ferritin was found with lactate dehydrogenase, bicarbonate and gamma glutamyl transferase in mild positive patients [Table 5].

A significant positive correlation of ferritin was found with lactate dehydrogenase, urea, creatinine, BUN, potassium, total bilirubin, direct bilirubin, aspartate transaminase, alanine transaminase and alkaline phosphatase. A significant negative correlation of ferritin was found with chloride in severe positive patients [Table 5].

Table 5. Pearson correlation of ferritin with study parameters in positive group, mild positive and severe positive groups

Ferritin

association with

study parameters

Positive group Mild positive Severe positive

 

N R

value

P-

value

N R

value

P-

value

N

 

R

value

P-

value

LDH (U/L) 110 0.562 0.000*** 69 0.266 0.027* 41 0.495 0.001**
Urea (mg/dl) 147 0.590 0.000*** 84

0.034

0.762 63 0.577 0.000***
Creatinine(mg/dl) 149 0.575 0.000*** 84 0.055 0.619 65 0.694 0.000***
BUN (mg/dl) 149 0.589 0.000***   84 0.760

0.034

65 0.581 0.000***
Sodium (mmol/l) 146 -0.090 0.281 82 0.060 0.591 64

0.035

0.782

 

Potassium (mmol/l) 145 0.167 0.045* 82

0.105

0.350

 

63 0.275 0.029*
Chloride (mmol/l) 145 -0.305 0.000*** 82 -0.116 0.300 63 -0.312 0.013*

 

Bicarbonate (mmol/l) 145 -0.105 0.208 82 0.233 0.035* 63 -0.170 0.182

 

Total bilirubin (mg/dl) 149 0.260 0.001** 84 0.193 0.079 65 0.256 0.039*
Direct bilirubin (mg/dl) 149 0.272 0.001** 84 0.167 0.128 65 0.270 0.030*
Indirect bilirubin (mg/dl) 149 0.163 0.047* 84 0.137 0.215 65 0.167 0.185

 

Total protein (g/dl) 149 -0.146 0.075 84 -0.043 0.697 65 -0.116 0.356

 

Albumin (g/dl) 149 -0.199 0.015* 84 0.031 0.782 65 -0.143 0.257

 

Globulin (g/dl) 149 -0.072 0.382 84 -0.118 0.286 65 -0.033 0.794

 

AG ratio 149 -0.131 0.112 84 0.136 0.217 65 -0.115 0.361

 

AST (IU/L) 149 0.440 0.000*** 84 -0.077 0.489 65 0.438 0.000***

 

ALT (IU/L) 148 0.410 0.000*** 83 0.064 0.565 65 0.374 0.002**
ALP (IU/L) 148 0.334 0.000*** 83 0.054 0.630 65 0.330 0.007**
GGT (U/L) 149 0.112 0.174 84 0.385 0.000*** 65 -0.030 0.811
Significance: *P<0.05, **P<0.01, ***P<0.001

We observed the frequency of participants in mild positive as 84 (31%), severe positive as 65 (24%) and negative as 121 (45%). We also observed a significant difference in the levels of urea, creatinine, BUN, sodium, total bilirubin, indirect bilirubin, total protein, aspartate transaminase, alanine transaminase and alkaline phosphatase between mild positive, severe positive and negative groups in ANOVA analysis [Tables 6, 7, 8].

Table 6. Multiple comparison of study parameters in mild positive, severe positive and negative groups by ANOVA

Study parameters Sum of Squares df Mean Square F Sig.
LDH                    Between

Groups

With in

Groups

Total

11560407.152

 

506958.167

 

12067365.319

249

 

20

 

269

46427.338

 

25347.908

 

1.832 .056
Urea                   Between

Groups

With in

Groups

Total

310592.609

 

8921.167

 

319513.776

248

 

19

 

267

1252.390

 

469.535

2.667 .007**

 

Creatinine          Between

Groups

With in

Groups

Total

1054.846

 

1.687

 

1056.533

249

 

20

 

269

4.236

 

.084

 

50.233 .000***
BUN                    Between

Groups

With in

Groups

Total

    68319.249

 

1949.185

 

70268.434

249

 

20

 

269

274.374

 

97.459

 

2.815

 

 

.004**

 

Sodium               Between

Groups

With in

Groups

Total

22278.939

 

221.000

 

22499.939

242

 

18

 

260

92.062

 

12.278

 

7.498 .000***

 

Potassium          Between

Groups

With in

Groups

Total

67.761

 

3.782

 

71.542

241

 

18

 

259

.281

 

.210

 

1.338 .240

 

Chloride             Between

Groups

With in

Groups

Total

4503.938

 

277.000

 

4780.938

241

 

18

 

259

18.689

 

15.389

 

1.214 328
Bicarbonate       Between

Groups

With in

Groups

Total

5635.395

 

2717.667

 

8353.062

241

 

18

 

259

     23.383

 

150.981

 

.155 1.000
Significance: *P<0.05, **P<0.01, ***P<0.001

Table 7. Multiple comparison of study parameters in mild positive, severe positive and negative groups by ANOVA

Study parameters Sum of Squares df Mean Square F Sig.
Total bilirubin       Between

Groups

With in

Groups

Total

36.355

 

1.301

 

37.657

248

 

20

 

268

.147

 

.065

 

2.253 . .018*
Direct bilirubin      Between

Groups

With in

Groups

Total

9.959

 

.486

 

10.445

248

 

20

 

268

.040

 

.024

 

1.653 .092

 

Indirect bilirubin    Between

Groups

With in

Groups

Total

19.426

 

.658

 

20.084

248

 

20

 

268

.078

 

.033

 

2.380

 

 

.013*
Total protein           Between

Groups

With in

Groups

Total

188.533

 

5.955

 

194.488

248

 

20

 

268

.760

 

.298

 

2.553 .008**
Albumin                   Between

Groups

With in

Groups

Total

106.440

 

5.590

 

112.030

248

 

20

 

268

.429

 

.280

 

1.536 .129
Globulin                   Between

Groups

With in

Groups

Total

49.981

 

2.585

 

52.566

248

 

20

 

268

.202

 

.129

 

1.559 .121

 

AG ratio                   Between

Groups

With in

Groups

Total

16.718

 

.948

 

17.667

249

 

20

 

269

.067

 

.047

1.416 .181

 

Significance: *P<0.05, **P<0.01, ***P<0.001

Table 8. Multiple comparison of study parameters in mild positive, severe positive and negative groups by ANOVA

Study parameters Sum of Squares df Mean Square F Sig.
Aspartate                  Between transaminase           Groups

With in

Groups

Total

3103587.502

 

2767.167

 

3106354.669

248

 

20

 

268

12514.466

 

138.358

 

90.450 .000***
Alanine                    Between transaminase           Groups

With in

Groups

Total

1256918.527

 

6295.667

 

1263214.194

247

 

20

 

267

5088.739

 

314.783

16.166 .000***
Alkaline                   Between phosphatase            Groups

With in

Groups

Total

1131998.188

 

43489.167

 

1175487.354

247

 

20

 

267

4582.989

 

2174.458

2.108 .026*
Gamma                    Between glutamyl                   Groups

transferase              With in

Groups

Total

518302.004

 

45353.000

 

563655.004

248

 

20

 

268

2089.927

 

2267.650

 

. 922 .634
Significance: *P<0.05, **P<0.01, ***P<0.001

Table 9. Incidence of liver function parameters

Parameters ranges Positive participants Negative participants
Total bilirubin (mg/dl) Positive (n-149) Negative (n-120)
<0.5 53 (35.6%) 55 (45.8%)
0.5-1.0 77 (51.7%) 55 (45.8%)
>1.0 19 (12.7%) 10 (8.4%)
Direct bilirubin (mg/dl) Positive (n-149) Negative (n-120)
<0.1 26 (17.4%) 44 (36.7%)
0.1-0.3 98 (65.8%) 67 (55.8%)
>0.3 25 (16.8%) 9 (7.5%)
Indirect bilirubin (mg/dl) Positive (n-149) Negative (n-120)
<0.2 11 (7.4%) 4 (3.4%)
0.2-0.8 125 (83.9%) 109 (90.8%)
>0.8 13 (8.7%) 7 (5.8%)
Total Protein (g/dL) Positive (n-149) Negative (n-120)
<6.6 35 (23.5%) 14 (11.7%)
6.6-8.3 110 (73.8%) 105 (87.5%)
>8.3 4 (2.7%) 1 (0.8%)
Albumin (g/dL) Positive (n-149) Negative (1-120)
<3.5 35 (23.5%) 18 (15%)
3.5-5.2 113 (75.8%) 102 (85%)
>5.2 1 (0.7%) 0 (0%)
Globulin (g/dL) Positive (n-149) Negative (n-120)
<2.5 7 (4.7%) 1 (0.8%)
2.5-3.0 45 (30.2%) 38 (31.7%)
>3.0 97 (65.1%) 81 (67.5%)
AG ratio Positive (n-149) Negative (n-120)
<1.4 120 (80.6%) 86 (71.7%)
1.4-1.7 23 (15.4%) 31 (25.8%)
>1.7 6 (4.0%) 3 (2.5%)
AST (IU/L) Positive (n-149) Negative (n-120)
<31 51 (34.2%) 62 (51.7%)
>31 98 (65.8%) 58 (48.3%)
ALT (IU/L) Positive (n-149) Negative (n-120)
<34 83 (55.7%) 83 (69.2%)
>34 66 (44.3%) 37 (30.8%)
ALP (IU/L) Positive (n-149) Negative (n-120)
<30 2 (1.3%) 0 (0%)
30-120 133 (89.3%) 111 (92.5%)
>120 14 (9.4%) 9 (7.5%)
GGT (U/L) Positive (n-149) Negative (n-120)
<38 72 (48.3%) 79 (65.8%)
>38 77 (51.7%) 41 (34.2%)


Table 10. Incidence of kidney function parameters

Parameters ranges Positive participants Negative participants
Urea (mg/dL) Positive (n-147) Negative (n-121)
<17 15 (10.2%) 31 (25.6%)
17-43 105 (71.4%) 84 (69.4%)
>43 27 (18.4%) 6 (5.0%)
Creatinine (mg/dL) Positive (n-147) Negative (n-121)
<0.5 2 (1.4%) 8 (6.6%)
0.5-1.2 124 (84.3%) 109 (90.1%)
>1.2 21 (14.3%) 4 (3.3%)
BUN (mg/dL) Positive (n-147) Negative (n-121)
<6 4 (2.7%) 8 (6.6%)
6-20 116 (78.9%) 107 (88.4%)
>20 27 (18.4%) 6 (5.0%)


Table 11. Incidence of electrolyte imbalances

Parameters ranges Positive participants Negative participants
Sodium (mmol/L) Positive (n-145) Negative (n-115)
<130 11 (7.6%) 1 (0.9%)
130-145 132 (91%) 113 (98.2)
>145 2 (1.4%) 1 (0.9)
Potassium (mmol/L) Positive (n-145) Negative (n-115)
<3.5 14 (9.7%) 7(6.1%)
3.5-5.0 121 (83.4%) 107 (93%)
>5.0 10 (6.9%) 1 (0.9%)
Chloride (mmol/L) Positive (n-145) Negative (n-115)
<95 14 (9.7%) 1 (0.9%)
95-105 116 (80%) 96 (83.5%)
>105 15 (10.3%) 18 (15.6%)
Bicarbonate (mmol/L) Positive (n-145) Negative (n-115)
<21 28 (19.3%) 7(6.1%)
21-31 114 (78.6%) 107 (93%)
>31 3 (2.1%) 1 (0.9%)

We observed that the prevalence of COVID infection was more in males compared to females.  Similar results were observed by Huang et al. (2020) and Chen et al. (2020). MERS-CoV and SARS-CoV have also been found to infect more males than females (Badawi et al. 2016).  These findings could be linked to the protection associated with sex hormones which modulate both innate and adaptive immunity (Jaillon et al. 2019; Channappanavar et al. 2020). The mean age of COVID positive group was found to be 50.28 ± 15.19 years in our study.  We observed that a greater number of COVID positive patients were in the age group of more than 60 years (30.2%) whereas Chen et al reported an increased incidence of COVID infection in the age group of 50-59years (30%) (Chen et al. 2020).

Ferritin is an iron-binding molecule which helps to store iron in its active form and protects from iron toxicity. Each apoferritin is made up of 24 subunits of two types namely the H and L subunits.  The L-subunit rich ferritin predominantly occurs in liver, spleen whereas the H-subunit rich ferritin is present in heart and kidneys (Harrison et al. 1996; Knovich et al. 2009). Oxidative stress, growth factors, thyroid hormone, second messengers, hyperoxia and hypoxia-ischemia are some of the major factors regulating the expression of ferritin (Torti et al. 2002). The hepatocytes, kupffer cells and macrophages secrete ferritin (Recalcati et al. 2008; Wang et al. 2010; Cohen et al. 2010).

The serum ferritin (iron poor form) is mostly made up of L-subunits only. H-ferritin with its immunomodulatory effects causes diminished antibody production, allergic responses as well as phagocytosis (Broxmeyer et al. 1981; Hann et al. 1989; Morikawa et al. 1994; Recalcati et al. 2008). The L-subunit (predominant in serum) acts as a pro-inflammatory mediator (Ruddell et al. 2009; Wang et al. 2010; Channappanavar et al. 2020).

Ferritin expression is found to be induced by pro-inflammatory cytokines (IL-6) and in turn ferritin enhances the expression of the pro-inflammatory cytokines.  Moreover, induction of the anti-inflammatory cytokines (IL-10) also by ferritin explains its immunosuppressive effects.  Ferritin as well as the cytokines regulate both inflammation and immunosuppression.  Hence ferritin can play a role as either an immunosuppressive or a pro-inflammatory agent through different receptors, pathways and effectors (L- versus H-ferritin). An already existing proinflammatory state, sepsis or genetic susceptibility may influence the pathogenic role of ferritin (Rosário et al. 2013).

Several mechanisms have been suggested to explain the association of hyperferritinemia with severity of disease in COVID-19 patients.  The viral infection mediated production of the proinflammatory cytokines (IL-l β, IL-6, TNF- α) as well as leakage of intracellular ferritin as a consequence of inflammation mediated cellular damage have been implicated as the cause of hyperferritinemia commonly occurring in COVID-19 patients. Heightened reactive oxygen species driven iron release from ferritin may also promote a vicious cycle of inflammation (Kobune et al. 1994; Kell et al. 2014; Channappanavar et al. 2020).

Based on the ferritin values obtained, the patients were categorized into mild and severe groups using a cut-off value of 500 ng/ml.  Among the 149 positive cases, 84 (56.4%) were found to have ferritin levels <500ng/ml and 65 (43.6%) had ferritin levels >500 ng/ml whereas of the 121 negative cases, 107 (88.4%) had ferritin level <500 ng/ml and 14 (11.6%) had ferritin levels >500 ng/ml.  Serum ferritin levels are also found to be increased in a variety of diseases and other inflammatory states also especially diabetes mellitus which could explain this finding (Lin et al. 2020). Lin et al. (2020) in their analysis of 147 confirmed cases of COVID-19 found 29.93 % of patients to have hyperferritinemia (>500 ng/ml) whereas in our study 43.6% of patients had hyperferritinemia (Lin et al. 2020).

We reported significant increase in serum ferritin levels in severe positive samples (1449.84 ± 249.47) compared to mild positive samples (230.04 ± 17.41).  Zhou et al found that individuals with severe COVID infection exhibited greater elevations of serum ferritin levels (Zhou et al. 2020). Jenifer et al in their review of studies which documented serum ferritin levels among severe and non-severe COVID-19 patients only at the time of hospital admission observed ferritin concentrations to be within the normal range in non-severe disease and presence of hyperferritinemia in severe disease state (Gomez-Pastoraa et al. 2020).

These findings are similar to the observations of our study. Lin et al. (2020) observed bilateral pulmonary infiltration rate to be more in patients who had ferritin levels more than 500 ng/ml.  Wu et al. (2020) in their investigation of 201 COVID-19 patients found that increased risk of development of ARDS was associated with higher serum ferritin levels. On the other hand, Mo et al. (2020) found ferritin levels to be elevated in both mild as well as in severe COVID patients.  Among the non survivors, ferritin levels remained elevated throughout the course of the disease (Mo et al. 2020; Zhou et al. 2020).

Thus, ferritin levels estimated at admission as well as during the progress of the disease may help to differentiate those with severe manifestations and help in planning effective treatment strategies.  Circulating ferritin levels may not only indicate an acute phase response but may also play a key inflammatory role in pathogenesis of COVID-19.  Hence the role of iron chelators as well as reduction of dietary iron can also be considered as treatment strategies in the setting of hyperferritinemia (Fleming et al. 2002; Mobarra et al. 2016). LDH, an intracellular enzyme which occurs in cells of most organs is composed of two major subunits and occurs as five major isozymes. Cytokine mediated tissue damage following severe infection causes LDH release into circulation (Martinez-Outschoorn et al. 2011; Ju et al. 2016; Henry et al. 2020).

The isoenzyme of LDH derived from the lungs (LDH-3) is found to be elevated as a consequence of interstitial pneumonia which may progress on to acute respiratory distress syndrome, a common feature of COVID (Kaplan et al. 2002; Patschan et al. 2006; Zhang et al. 2014). Early laboratory data analysis of COVID-19 patients had indicated significant variations in LDH levels among patients with severe disease manifestations (Henry et al. 2020).

We observed that 58.2% of COVID positive patients had LDH levels greater than 280 U/L. By January 2020, Huang et al. (2020) reported 73% of COVID infected patients with elevated LDH levels. LDH levels were also significantly elevated in the severe positive group (ferritin >500ng/ml). Henry et al. (2020) carried out a meta-analysis of 9 published studies with 1532 COVID-19 patients to study the association between elevated LDH levels at the time of admission and disease outcome and found that elevated LDH levels represented a sixfold increase in the risk of developing severe disease and a sixteen-fold increase in mortality (Henry et al. 2020).

Huang et al. (2020) and Greater increase in LDH levels was seen among patients admitted in the intensive care unit and those who progressed onto acute respiratory distress syndrome (ARDS) respectively (Huang et al. 2020; Wu et al. 2020). Nearly 60 % of patients with SARS and also those infected with MERS-CoV have reported liver impairment (Chau et al. 2004; Alsaad et al. 2018). Direct viral infection of the hepatic cells has been implicated as the cause for liver damage in patients infected with coronavirus. Data from large scale case studies have indicated that 2-11% of COVID patients had pre-existing liver comorbidities, 14-53% had alterations in levels of AST and ALT as the disease progressed.

Liver dysfunction is found to be more prevalent in severe than in mild cases of COVID (Zhang et al. 2020). In our study elevations of total bilirubin occurred in 12.7%, AST in 65.8 %, ALT in 44.3 %, ALP in 9.4% and GGT in 51.7% of COVID positive patients.  Hypoproteinemia and hypoalbuminaemia was observed in 23.5% of the patients. Chen et al. (2020) reported an increase in ALT by 28%, AST by 35%, bilirubin by 18% and decrease in albumin by 98%.  Zhang et al reported elevation of GGT by 54% (Chen et al. 2020; Zhang et al. 2020).

Inflammatory cytokines are known to play a role in inducing acute kidney injury and glomerulopathy.  Endothelial injury and cardiovascular instability occurring in severely infected COVID patients may cause renal impairment resulting in cardio renal syndrome (Gonza´lez-Cuadrado et al. 1997; Sanz et al. 2011; Lin et al. 2020; Fan et al. 2020). Previous studies have reported expression of angiotensin converting enzyme 2 (ACE-II) receptors in human kidneys thus indicating a potential pathway for COVID-19 infection (Lin et al. 2020; Fan et al. 2020).

Acute kidney injury is considered to be an independent predictor of covid-19 in-hospital mortality (Cheng et al. 2020; Carriazo et al. 2020).  Hassan Mohammed et al during their analysis of urea and creatinine levels both at the onset of disease and later during the clinical course showed that impaired kidney function is seen in COVID-19 patients contributing to morbidity and mortality (Mahmoudi et al. 2020).

In our study, elevations of urea levels occurred in 18.4%, creatinine in 14.3% and BUN in 18.4% was found in COVID positive patients. Huang et al. (2020); Chen et al. (2020) have reported creatinine elevations in 10% and 3% of their COVID study group respectively.  An increase in BUN beyond the normal range was seen in 6% of the study group analysed by Chen et al.  Henry et al in their meta-analysis on biochemical abnormalities also identified derangements in kidney function in patients with severe and fatal COVID-19 patients (Henry et al. 2020).

Initial evidence from COVID studies have indicated the presence of electrolyte abnormalities (Guan et al. 2020; Huang et al. 2020).  Identification of such alterations help not only in effective patient management but also help to understand key pathophysiological mechanisms of the disease process. Among the COVID patients of our study, the incidence of hyponatremia and hypokalemia was found to be 7.6% and 9.7% respectively. Fall in serum chloride and bicarbonate levels below the reference range was noted in 9.7% and 19.3% respectively (Lippi et al. 2020).

The abnormalities in serum electrolyte levels were found to be more prevalent among the positive patients compared to those who had tested negative. Results of a pooled analysis conducted by Lippe et al. (2020) to identify the most commonly encountered electrolyte abnormalities in COVID patients indicates COVID-19 severity to be associated with lowered serum concentrations of sodium, potassium and calcium. Binding of the virus to its host receptor namely angiotensin converting enzyme-2 may cause increased renal loss of potassium leading onto hypokalemia. Electrolyte status among COVID patients also varies highly (Lippe et al. 2020; Huang et al. 2020).

Studies with larger number of COVID positive samples analysed at different stages of progression of the disease will help to clearly establish the clinical significance and to initiate the appropriate interventions. The major limitation of our study is its retrospective cross-sectional nature and the non-availability of correlation with the clinical aspects of COVID patients.  Analysis of a larger sample size sourced from multiple centres with clinical outcome can help in a better understanding of the clinical utility of these parameters.

The findings of the present study indicate that males were more commonly affected by COVID-19 than females.  The maximum numbers of positive cases were found in the age group of more than 60 years. Among the 149 positive cases, 84 (56.4%) were found to have ferritin levels <500 ng/ml and 65 (43.6%) had ferritin levels >500 ng/ml. We reported significant increase in serum ferritin levels in severe positive samples (1449.84 ± 249.47) compared to mild positive samples (230.04 ± 17.41).

We observed significant increase in the levels of lactate dehydrogenase, urea, creatinine, BUN, total bilirubin, direct bilirubin, indirect bilirubin, AG ratio, alanine transaminase and gamma glutamyl transferase and significant decrease in the levels of chloride, total protein, albumin in severe positive (ferritin levels >500 ng/ml) compared to mild positive (ferritin levels <500 ng/ml).  The significant alterations in various biochemical parameters among the COVID-19 patients suggests the importance of initial assessment and monitoring of these laboratory parameters in risk assessment.

Conflict of interests: Authors declare no conflicts of interests to disclose.

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