Comparison of Gene Polymorphisms of ACE1 and ACE2 and the Level of Total ACE Activity in the Blood of Afghans and Iranians with COVID-19 and Its Relationship with Disease Severity

Abstract

Field evidence indicates differences in the rate and severity of COVID-19 infection among Afghans and Iranians, potentially influenced by individual genomic variances. Therefore, investigating the potential causes of these disparities holds significant clinical importance. This study aims to explore and compare variations in the genes encoding angiotensin-converting enzyme 1 (ACE1) and angiotensin-converting enzyme 2 (ACE2), along with total ACE activity levels in the blood of Afghans and Iranians with COVID-19, to assess any potential correlation with disease severity. In this case–control study, 124 Afghans and 124 Iranians with COVID-19 residing in Rafsanjan city, Iran, were examined. Blood samples were collected from all subjects, and serum was isolated for measuring total ACE activity using the kinetic method. DNA extraction was performed using the salting-out method, and gene polymorphisms of ACE1 and ACE2 were determined through polymerase chain reaction (PCR) and PCR–restriction fragment length polymorphism techniques. The DD genotype and D allele, as well as the GG genotype and G allele, were more prevalent among individuals with severe COVID-19 cases compared with those with mild symptoms, indicating an increased risk of severe infection. Although the Iranian group exhibited higher levels of these genetic components, along with longer hospital stays, intensive care unit admissions, and mortality rates than the Afghan group, the differences were not statistically significant. Furthermore, individuals with the DD genotype displayed double the total ACE activity levels compared with those with the II genotype, with the ID genotype falling in between. The presence of the DD genotype and D allele, as well as the GG genotype and G allele, likely serves as a significant risk factor for COVID-19 susceptibility, potentially heightening the risk of severe infection among Iranians compared with Afghans.

Introduction

In December 2019, Wuhan, China, witnessed a surge in unexplained cases of pneumonia. Subsequent investigations in the following month involved the collection of throat swab samples from patients, leading to the identification of a novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for the outbreak of coronavirus disease 2019 (COVID-19) (Hui et al., 2020; Koksoy Vayisoglu et al., 2024). As the COVID-19 pandemic spread globally, certain countries reported higher infection and mortality rates. While increased diagnostic testing may contribute to higher case numbers, elevated death tolls in these nations point to additional underlying factors (Pearce et al., 2020; Siddiqui et al., 2021, 2024).

Various health, social, economic, and genetic factors can influence disease prevalence and mortality rates (Singu et al., 2020; Swann and Martins, 2023; Hesami et al., 2016). Iran stands among the top 10 countries worldwide in hosting a significant number of refugees, with Afghan immigrants comprising a substantial portion of this demographic (Hosseini Divkolaye and Burkle, 2017). Disparities in health, social, and economic conditions exist among individuals in Iran, including Afghan immigrants who often face unfavorable circumstances (Pourhossein et al., 2015; Abdollahi et al., 2015; Omidvar et al., 2013). Given these disparities, Afghan immigrants might be more susceptible to COVID-19. However, empirical data from Rafsanjan city in Iran indicate lower infection rates and mortality among Afghan immigrants compared with Iranians, suggesting potential genomic differences as a contributing factor (Sripichai and Fucharoen, 2007).

Previous research has highlighted the crucial role of angiotensin-converting enzyme 1 (ACE1) and angiotensin-converting enzyme 2 (ACE2) genes in determining susceptibility to COVID-19, with genetic variations influencing the risk of viral infection (Delanghe et al., 2020; Möhlendick et al., 2021; Sabater Molina et al., 2022). ACE2, a membrane-bound zinc-containing metalloenzyme, plays a pivotal role in the renin–angiotensin–aldosterone system (RAAS) by regulating blood pressure through the conversion of angiotensin 1 to angiotensin 1–9 and angiotensin 2 to angiotensin 1–7 (Bourgonje et al., 2020). As the primary receptor for SARS-CoV-2, ACE2 is expressed in various tissues and is essential for viral entry (Wong, 2016). The ACE2 gene, located on the X chromosome with a length of 39.98 kb at Xp22, harbors a single nucleotide polymorphism G8790A (rs2285666) in intron 3, resulting in three genotypes (GG, AA, and GA) (Luo et al., 2019; Liu et al., 2005).

ACE1 is a widely distributed protein and another component of the RAAS that controls blood pressure by converting angiotensin 1 to angiotensin 2 and angiotensin 1–9 to angiotensin 1–7 (Wong, 2016; Riordan, 2003). The ACE1 gene is encoded by a gene with a size of 21 kb located on chromosome 17 (17q23) (Sayed-Tabatabaei et al., 2006). The ACE1 gene possesses a polymorphism of a 287 bp Alu repeat sequence in intron 16 (rs4646994), which can be either deleted (D) or inserted (I) and results in three genotypes—homozygous II, homozygous DD, or heterozygous ID (Sayed-Tabatabaei et al., 2006; Gard, 2010).

ACE1 and ACE2 are the two key modulators of RAAS. When one is downregulated, the other is up-regulated (Koka et al., 2008; Zheng and Cao, 2020). The binding of SARS-CoV-2 to ACE2 leads to exhaustion and downregulation of ACE2 (Silhol et al., 2020; Gemmati et al., 2020), resulting in upregulation of ACE1 and increased production of angiotensin 2 (Silhol et al., 2020). Experimental and clinical studies show that angiotensin 2 can lead to acute lung and tissue damage through different mechanisms (Zheng and Cao, 2020).

This study aimed to determine and compare gene polymorphisms of ACE1 and ACE2 and the level of total ACE activity in the blood of Afghans and Iranians with COVID-19 living in Rafsanjan and its relationship with disease severity.

Methods

Study setting and subjects

This case–control study investigated 124 Afghans and 124 Iranians with COVID-19. Adult Afghans and Iranians aged between 18 and 65 living in Rafsanjan city, Iran, who tested positive for COVID-19 using the reverse transcription–polymerase chain reaction (RT-PCR) technique on pharynx and nasal samples, were included. Pregnant women, individuals with underlying conditions (such as hypertension, cardiovascular, lung, and liver diseases), as well as those who smoked cigarettes, used opium, or certain drugs were excluded.

The patients were categorized based on disease severity into mild and severe cases. Severe cases were defined according to the guidelines set by Lin and Li (2020) and Saleh et al. (2022), which include symptoms such as a respiratory rate exceeding 30 cycles/min, SaO₂ below 93%, PaO₂/FiO₂ less than 300 mm Hg, respiratory failure, multiple organ failure, and shock.

Following positive RT-PCR results, 62 Afghans with mild symptoms, 62 Afghans with severe symptoms, 62 Iranians with mild symptoms, and 62 Iranians with severe symptoms were randomly selected for the study. Groups were matched for age and gender to account for their impact on study outcomes.

All subjects were provided with relevant study information and signed consent forms. Subsequently, clinical data from their medical records were collected and recorded in a registry.

Sampling and measurement of total ACE activity

Four milliliters of venous blood was collected from each eligible subject. Serum was separated from a portion of the blood, and the level of total ACE activity was measured using the total ACE activity measurement kit (Biorex Fars Company) and the kinetic method.

DNA extraction

DNA extraction from blood lymphocytes was performed using the DNA extraction kit (Karmania Pars Gene Company) and the salting-out method. The concentration and quality of extracted DNA were assessed using nanodrop and electrophoresis on a 1% agarose gel.

Primer design

Primers for amplifying fragments of the ACE1 and ACE2 genes were designed based on information from the National Center for Biotechnology Information (NCBI) database and Vector NTI software. The primer sequences are presented in Table 1. All primers were validated using NCBI Primer-Blast.

Table 1.

Sequence of Primers Designed to Amplify Fragments of ACE1 and ACE2 Genes

Polymorphism	Primers	PCR product
ACE1 intron 16 ID (rs4646994)	F-5′CTGGAGACCACTCCCATCCTTTCT3′	Depends on genotype
	R-5′GATGTGGCCATCACATTCGTCAGAT3′
ACE2 intron 3 G8790A (rs2285666)	F-5′-CATGTGGTCAAAAGGATATCT-3′	466 bp
	R-5′-AAAGTAAGGTTGGCAGACAT-3′

ACE1, angiotensin-converting enzyme 1; ACE2, angiotensin-converting enzyme 2; PCR, polymerase chain reaction.

Genotyping of ACE1 and ACE2 polymorphisms

In this phase, PCR was employed to amplify target fragments associated with intron 16 of the ACE1 gene, which features a deletion/insertion polymorphism (rs4646994) (Saadat et al., 2010), as well as a 466 bp fragment linked to intron 3 of the ACE2 gene, containing the single nucleotide polymorphism G8790A (rs2285666) (Pinheiro et al., 2019). The amplification process utilized a premix kit (Pars Tous Company) according to the manufacturer’s protocol.

The PCR reaction was prepared with a total volume of 20 μL, consisting of 10 μL of 2X Taq premix, 1 μL of forward primer (10 μM), 1 μL of reverse primer (10 μM), and 8 μL of template DNA. The cycling conditions included an initial denaturation step at 94°C for 4 min, followed by 32 cycles of 30 sec at 94°C, 30 sec at 69°C (for ACE1) or 51°C (for ACE2), and 30 sec at 72°C, concluding with a final extension step at 72°C for 5 min.

To determine the genotype for the ACE2 gene polymorphism, enzymatic digestion via restriction fragment length polymorphism was performed using the AluI restriction enzyme (Thermo Scientific Company), which recognizes an AG/CT cutting site. For this procedure, 18 μL of nuclease-free water, 2 μL of 10× buffer, and 1 μL (10 U/μL) of AluI were added to 10 μL of PCR products. The mixture was gently vortexed and incubated at 37°C for 16 h to facilitate enzymatic digestion. Following digestion, the reaction was inactivated by incubating at 65°C for 20 min.

To assess genotypes for the ACE1 and ACE2 gene polymorphisms, 6 μL of PCR products mixed with loading buffer and 3 μL of a 100 bp marker combined with another 3 μL of diluted loading buffer were loaded onto a 2% agarose gel containing Green Viewer DNA dye. The gel was then placed in a gel dock device for observation and photography. The quality of electrophoresis was confirmed by the presence of sharp bands without smearing and the absence of contamination in the no-DNA control sample. To ensure accuracy, 10% of the samples were randomly selected for repeat genotyping.

For ACE1 gene polymorphism, a 490 bp segment indicates the I allele, while a 190 bp segment indicates the D allele associated with the deletion/insertion polymorphism in intron 16 (rs4646994) of the ACE1 gene. For ACE2 gene polymorphism, fragments measuring 185 bp and 281 bp represent the A allele, while a fragment of 466 bp represents the G allele for the single nucleotide polymorphism G8790A located in the fourth base of intron 3 (rs2285666) of the ACE2 gene.

Statistical analysis

A priori power analysis was conducted to determine the required sample size. Continuous variables were presented as mean ± standard deviation, while categorical variables were expressed as count and percentage. Data analysis involved independent t-tests, chi-square tests (χ ²), Fisher’s exact test, analysis of variance test, and/or logistic regression test. All statistical analyses were conducted using SPSS software (version 18.0, SPSS Inc.). Results with a p-value <0.05 were considered significant.

Sample size

A priori power analysis was conducted to determine the required sample size. The following formula was used to estimate the sample size for each group: $n = \frac{{{2 (Z}_{1 - \frac{α}{2}} + Z_{1 - β})}^{2} \bar{P} (1 - \bar{P})}{{(P_{1} - P_{2})}^{2}}$

In this formula, n represents the required sample size for each group. Z denotes the confidence coefficient at a 95% confidence level and an 85% statistical power. P_1 and P_2 are estimates of the proportions of individuals with mild and severe COVID-19, set at 25% and 44%, respectively (Yamamoto et al., 2020). Based on this analysis, the required sample size for each group was determined to be at least 113 participants. However, accounting for a 10% dropout rate, the estimated sample size was adjusted to 124 participants per group.

Results

The mean levels of white blood cells, erythrocyte sedimentation rate (ESR), C-reactive protein, lactate dehydrogenase, and creatine phosphokinase were significantly higher in the severe group compared with the mild group. However, there was no significant difference in the mean total ACE activity between the two groups (Table 2).

Table 2.

Demographic Information, Laboratory Findings, and Total ACE Activity in Mild and Severe Groups

Variables	Mild (N = 124)	Severe (N = 124)	p
Age (years)	45.45 ± 14.39	46.29 ± 14.12	0.644
Sex			1.00
Male (N, %)	60 (48.4%)	60 (48.4%)
Female (N, %)	64 (51.6%)	64 (51.6%)
WBC (10³/µL)	6.42 ± 2.74	7.71 ± 3.63	0.002^**
Platelet (10³/µL)	208.08 ± 84.73	196.59 ± 101.13	0.333
ESR (mm/h)	28.77 ± 15.85	34.45 ± 23.58	0.027^*
CRP (mg/L)	27.09 ± 30.73	57.56 ± 51.31	<0.001^***
LDH (U/L)	592.69 ± 211.49	717.03 ± 229.82	<0.001^***
CPK (U/L)	124.56 ± 116.84	164.91 ± 157.76	0.023^*
ACE (U/L)	64.39 ± 26.85	61.97 ± 29.15	0.496

p: analysis with independent t-test or Pearson chi-square test (χ ²).

Significance at the 0.05 level.

Significance at the 0.01 level.

***

Significance at the 0.001 level.

ACE, angiotensin-converting enzyme; CPK, creatine phosphokinase; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; LDH, lactate dehydrogenase; WBC, white blood cell.

After electrophoresis, the 490 bp fragment represented the I allele, and the 190 bp fragment represented the D allele for the deletion and insertion polymorphism (rs4646994) of the ACE1 gene (Fig. 1). Additionally, fragments 185 and 281 bp represented the A allele, while the 466 bp fragment represented the G allele for single nucleotide polymorphism G8790A (rs2285666) of the ACE2 gene (Fig. 2).

FIG. 1.

Electrophoresis pattern of ACE1 gene PCR products on 2% agarose gel. ACE1, angiotensin-converting enzyme 1; PCR, polymerase chain reaction.

FIG. 2.

Electrophoresis pattern of ACE2 gene enzymatic digestion products on 2% agarose gel. ACE2, angiotensin-converting enzyme 2.

Further statistical analysis from Table 3 indicated significant differences between the mild and severe groups in terms of the II, ID, and DD genotypes associated with the deletion and insertion polymorphism of the ACE1 gene. Notably, 44.4% of individuals in the severe group had the DD genotype compared with only 28.2% in the mild group (p = 0.024). Individuals with the DD genotype were found to have a 2.39-fold increased risk of developing severe COVID-19 compared with those with the II genotype. Similarly, significant disparities were observed between the mild and severe groups concerning the I and D alleles related to the ACE1 gene polymorphism (64.5% vs. 52.4%, respectively; p = 0.006), with individuals carrying the D allele having a 1.65-fold higher risk of developing severe COVID-19.

Table 3.

Frequency of Genotypes and Alleles of ACE1 and ACE2 Gene Polymorphism in Mild and Severe Groups

Variables	Mild (N = 124)	Severe (N = 124)	χ ²	p¹	OR (95% CI)	p²
II (N, %)	29 (23.4%)	19 (15.3%)			1 (reference)	—
ID (N, %)	60 (48.4%)	50 (40.3%)	7.43	0.024^*	1.27 (0.63–2.53)	0.494
DD (N, %)	35 (28.2%)	55 (44.4%)			2.39 (1.17–4.91)	0.017^*
I (N, %)	118 (47.6%)	88 (35.5%)	7.47	0.006^**	1 (Reference)	—
D (N, %)	130 (52.4%)	160 (64.5%)			1.65 (1.15–2.36)	0.006^**
Female
AA (N, %)	2 (3.1%)	2 (3.1%)			1 (Reference)	—
GA (N, %)	25 (39.1%)	12 (18.8%)	6.51	0.039^*	0.48 (0.06–3.83)	0.489
GG (N, %)	37 (57.8%)	50 (78.1%)			1.35 (0.18–10.04)	0.769
A (N, %)	29 (22.7%)	16 (12.5%)	4.55	0.033^*	1 (Reference)	—
G (N, %)	99 (77.3%)	112 (87.5%)			2.05 (1.05–3.99)	0.035^*
Male
A (N, %)	22 (36.7%)	12 (20.0%)	4.10	0.043^*	1 (Reference)	—
G (N, %)	38 (63.3%)	48 (80.0%)			2.31 (1.01–5.26)	0.045^*

p ¹: Analysis with Pearson chi-square test (χ ²).

p ²: Analysis with logistic regression test.

Significance at the 0.05 level.

Significance at the 0.01 level.

CI, confidence interval; OR, odds ratio.

Regarding the single nucleotide polymorphism G8790A of the ACE2 gene, a significant difference was noted in the frequency of AA, GA, and GG genotypes between mild and severe women (78.1% in the severe group vs. 57.8% in the mild group; p = 0.039). Individuals with the GG genotype had a 1.35-fold increased likelihood of experiencing a severe course of COVID-19 compared with those with the AA genotype.

Additionally, there was a significant discrepancy in the frequency of A and G alleles related to the single nucleotide polymorphism G8790A of the ACE2 gene between mild and severe women, with the G allele being significantly more prevalent in severe cases compared with mild cases (87.5% vs. 77.3%, respectively; p = 0.033). Individuals with the G allele had a 2.05-fold higher chance of developing severe COVID-19 compared with those with the A allele.

Similarly, in men, there was a significant difference in the frequency of A and G alleles related to the single nucleotide polymorphism G8790A of the ACE2 gene between mild and severe cases. The frequency of the G allele was significantly higher in severe cases compared with mild cases (80.0% vs. 63.3%, respectively; p = 0.043), with individuals carrying the G allele having a 2.31-fold increased risk of developing severe COVID-19 compared with those with the A allele as reference.

The observed frequency did not differ significantly from the expected frequency in the Hardy–Weinberg equation (p > 0.05) (Table 4). The distribution of genotypes related to the deletion and insertion polymorphism of the ACE1 gene in both the mild (χ ² = 0.11, p = 0.738) and severe groups (χ ² = 1.77, p = 0.183), as well as the distribution of genotypes related to the single nucleotide polymorphism G8790A of the ACE2 gene in mild (χ ² = 0.84, p = 0.359) and severe women (χ ² = 1.30, p = 0.253), was in Hardy–Weinberg equilibrium.

Table 4.

Test for Hardy-Weinberg Equilibrium for Distribution of Genotypes in Mild and Severe Groups

Genotypes	Obs.	Exp.	χ ²	p
Mild (N = 124)			0.11	0.738
II (N, %)	29	28.1
ID (N, %)	60	61.8
DD (N, %)	35	34.1
Severe (N = 124)			1.77	0.183
II (N, %)	19	15.6
ID (N, %)	50	56.8
DD (N, %)	55	51.6
Mild—women (N = 64)			0.84	0.359
AA (N, %)	2	3.3
GA (N, %)	25	22.4
GG (N, %)	37	38.3
Severe—women (N = 64)			1.30	0.253
AA (N, %)	2	1.0
GA (N, %)	12	14.0
GG (N, %)	50	49.0

p: analysis with Pearson chi-square test (χ ²).

There was no significant difference in the mean level of total ACE activity between Afghan and Iranian groups (Table 5). Additionally, the frequency of ground-glass opacity, consolidation, pleural effusion, as well as the mean length of stay in the hospital and intensive care unit (ICU), and mortality in the Iranian group were higher than in the Afghan group, but these differences were not statistically significant.

Table 5.

Demographic Information, Total ACE Activity, Chest CT Scan Findings, and Outcomes of COVID-19 in Afghan and Iranian Groups

Variables	Afghans (N = 124)	Iranians (N = 124)	p
Age (years)	46.08 ± 14.56	45.66 ± 13.95	0.817
Sex			1.00
Male (N, %)	60 (48.4%)	60 (48.4%)
Female (N, %)	64 (51.6%)	64 (51.6%)
ACE (U/L)	61.09 ± 27.68	65.27 ± 28.26	0.240
Variables	Severe Afghans (N = 62)	Severe Iranians (N = 62)	p
Ground-glass opacity (N, %)	42 (67.7%)	51 (82.3%)	0.062
Consolidation (N, %)	28 (45.2%)	32 (51.6%)	0.472
Pleural effusion (N, %)	3 (4.8%)	4 (6.5%)	0.990
Hospital (day)	6.09 ± 3.32	6.74 ± 4.89	0.392
ICU (day)	1.37 ± 3.23	1.91 ± 4.66	0.448
Death (N, %)	4 (6.5%)	8 (13.0%)	0.224

p: analysis with independent t-test or Pearson chi square test (χ ²) or Fisher’s exact test.

CT, computed tomography; ICU, intensive care unit.

The frequency of the DD genotype and D allele, as well as the frequency of the GG genotype and G allele in the Iranian group, was higher than in the Afghan group, but these differences were not statistically significant (Table 6).

Table 6.

Frequency of Genotypes and Alleles of ACE1 and ACE2 Gene Polymorphism in Afghan and Iranian Groups

Variables	Afghans (N = 124)	Iranians (N = 124)	χ ²	p¹
II (N, %)	25 (20.2%)	23 (18.5%)	0.29	0.862
ID (N, %)	56 (45.2%)	54 (43.5%)
DD (N, %)	43 (34.6%)	47 (38.0%)
I (N, %)	106 (42.7%)	100 (40.3%)	0.29	0.585
D (N, %)	142 (57.3%)	148 (59.7%)
Female
AA (N, %)	2 (3.1%)	2 (3.1%)	0.34	0.841
GA (N, %)	20 (31.3%)	17 (26.6%)
GG (N, %)	42 (65.6%)	45 (70.3%)
A (N, %)	24 (18.8%)	21 (16.4%)	0.24	0.622
G (N, %)	104 (81.2%)	107 (83.6%)
Male
A (N, %)	19 (31.7%)	15 (25.0%)	0.65	0.418
G (N, %)	41 (68.3%)	45 (75.0%)

p: analysis with Pearson chi-square test (χ ²).

The observed frequency did not differ significantly from the expected frequency in the Hardy–Weinberg equation (p > 0.05) (Table 7). The distribution of genotypes related to the deletion and insertion polymorphism of the ACE1 gene in both the Afghan (χ ² = 0.74, p = 0.389) and Iranian groups (χ ² = 1.12, p = 0.289), as well as the distribution of genotypes related to the single nucleotide polymorphism G8790A of the ACE2 gene in Afghan (χ ² = 0.04, p = 0.837) and Iranian women (χ ² = 0.06, p = 0.800), was in Hardy–Weinberg equilibrium.

Table 7.

Test for Hardy–Weinberg Equilibrium for Distribution of Genotypes in Afghan and Iranian Groups

Genotypes	Obs.	Exp.	χ ²	p
Afghan (N = 124)			0.74	0.389
II (N, %)	25	22.7
ID (N, %)	56	60.7
DD (N, %)	43	40.6
Iranian (N = 124)			1.12	0.289
II (N, %)	23	20.2
ID (N, %)	54	59.7
DD (N, %)	47	44.1
Afghan—women (N = 64)			0.04	0.837
AA (N, %)	2	2.2
GA (N, %)	20	19.5
GG (N, %)	42	42.3
Iranian—women (N = 64)			0.06	0.800
AA (N, %)	2	1.7
GA (N, %)	17	17.6
GG (N, %)	45	44.7

p: analysis with Pearson chi square test (χ ²).

The mean age and ESR in individuals with DD, ID, and II genotypes differed significantly (Table 8). Specifically, the mean age and ESR in individuals with the ID genotype were significantly higher than those with II and DD genotypes. Moreover, the mean total ACE activity in individuals with DD, ID, and II genotypes showed a significant difference, with the level of total ACE activity being approximately twice as high in individuals with the DD genotype compared with those with II genotype, while individuals with ID genotype had intermediate levels between these two values.

Table 8.

Demographic Information, Laboratory Findings, Total ACE Activity, Chest CT Scan Findings, and Outcomes of COVID-19 in II, ID, and DD Groups

Variables	II (N = 48)	ID (N = 110)	DD (N = 90)	p II × ID × DD
Age (years)	39.35 ± 13.76	50.99 ± 12.55	43.08 ± 14.36	<0.001^***
Sex				0.607
Male (N, %)	21 (43.8%)	52 (47.3%)	47 (52.2%)
Female (N, %)	27 (56.2%)	58 (52.7%)	43 (47.8%)
WBC (10³/µL)	7.26 ± 3.73	6.99 ± 3.02	7.06 ± 3.35	0.893
Platelet (10³/µL)	219.25 ± 112.47	204.24 ± 91.36	190.98 ± 83.41	0.229
ESR (mm/h)	28.58 ± 22.21	35.45 ± 20.19	28.54 ± 18.59	0.028^*
CRP (mg/L)	35.22 ± 29.68	46.17 ± 52.67	41.42 ± 40.99	0.361
LDH (U/L)	611.12 ± 238.02	656.51 ± 195.68	676.16 ± 259.37	0.283
CPK (U/L)	151.87 ± 165.95	135.136 ± 123.87	152.67 ± 144.41	0.629
ACE (U/L)	43.44 ± 17.14	56.48 ± 20.11	81.90 ± 30.07	<0.001^***

Variables	II (N = 19)	ID (N = 50)	DD (N = 55)	PII × ID × DD
Ground-glass opacity (N, %)	11 (57.9%)	40 (80.0%)	42 (76.4%)	0.158
Consolidation (N, %)	6 (31.6%)	30 (60.0%)	24 (43.6%)	0.069
Pleural effusion (N, %)	0 (0.0%)	5 (10.0%)	2 (3.6%)	0.270
Hospital (day)	5.63 ± 3.05	6.30 ± 4.56	6.80 ± 4.16	0.560
ICU (day)	1.47 ± 3.16	1.60 ± 4.95	1.74 ± 3.31	0.964
Death (N, %)	1 (5.3%)	4 (8.0%)	7 (12.7%)	0.652

p: analysis with ANOVA test or independent t-test or Pearson chi-square test (χ ²) or Fisher’s exact test.

Significance at the 0.05 level.

***

Significance at the 0.001 level.

ANOVA, analysis of variance.

Discussion

A recent analysis by Henry et al. of 52 American patients with COVID-19 found no correlation between serum ACE activity and the severity of the infection. These findings align with the current study’s results, which highlight differences in total ACE activity between mild and severe cases, as well as between Afghan and Iranian groups. The results indicated that individuals with the DD genotype exhibited approximately twice the total ACE activity compared with those with the II genotype. Those with the ID genotype had activity levels that fell between the DD and II genotypes (Henry et al., 2021). In a similar study, Papadopoulou et al. evaluated the relationship between deletion and insertion polymorphisms related to the ACE1 gene and ACE serum activity in 81 Greek patients with COVID-19. They found that ACE activity was highest in the DD genotype, intermediate in the ID genotype, and lowest in the II genotype (Papadopoulou et al., 2022).

Moreover, a recent study by El-Sayed Marei et al. highlighted that the DD genotype was significantly more prevalent in severe COVID-19 cases compared with mild cases, reinforcing the association between ACE1 polymorphisms and disease severity (El-Sayed Marei et al., 2023). Their findings suggest that both the DD genotype and D allele, as well as the GG genotype and G allele, are significantly more common in the severe group than in the mild group. Additionally, the presence of these genotypes and alleles increases the risk of experiencing a more severe COVID-19 infection.

Our results indicated a higher prevalence of the DD genotype and D allele, as well as the GG genotype and G allele, in the Iranian group, potentially making them more susceptible to serious COVID-19 infections compared with the Afghan population. However, no significant differences were observed between the two groups regarding ground-glass opacity, consolidation, pleural effusion, length of hospital or ICU stays, or mortality rates. A study conducted by El-Sayed Marei et al. also found a significant association between the ACE1 DD genotype and increased severity of COVID-19 symptoms among Egyptian patients (El-Sayed Marei et al., 2023). Further studies with larger sample sizes are recommended to explore this issue in greater depth.

Verma et al. investigated the association between deletion and insertion polymorphisms of the ACE1 gene and COVID-19 severity in a study involving 269 Indian patients in July 2021. Their results suggested that the frequency of the DD genotype and D allele was significantly associated with a higher likelihood of severe COVID-19 infections.[36] In October 2021, Möhlendick et al. assessed the potential link between a variation in the ACE2 gene (G8790A polymorphism) and more severe symptoms of COVID-19 in 297 German patients. Their findings indicated that possessing a GG genotype or G allele slightly increased the risk of experiencing extreme COVID-19 illness by nearly threefold (Möhlendick et al., 2021).

In comparison to the findings of the current study, research by Aladag et al. in September 2021 explored the relationship between ACE1 gene deletion and insertion polymorphisms and COVID-19 severity in 112 Turkish individuals. They found that the ID genotype was associated with a higher likelihood of severe COVID-19 infection (Aladag et al., 2021). Additionally, Mahmood et al. conducted a study in February 2022 to investigate the potential link between ACE1 gene deletion and insertion polymorphisms, as well as the ACE2 gene G8790A polymorphism, and the severity of COVID-19 among 99 Iraqi patients. They concluded that there was no significant relationship between these genetic variations and COVID-19 severity (Mahmood et al., 2022). This inconsistency may be due to variations in population genetics or differing environmental factors influencing disease outcomes across regions. The discrepancies in these findings could also be attributed to differences in genetic makeup, sample sizes, and criteria for categorizing patients.

Furthermore, Tekcan et al. investigated the associations among ACE ID polymorphisms alongside MTHFR C677T and MIF-173GC variants concerning clinical outcomes in Turkish patients with COVID-19. Their results indicated that individuals with the DD genotype had a higher prevalence among those requiring intensive care compared to hospitalized or outpatient groups, suggesting that these genetic markers may significantly influence disease severity. Additionally, they found that the MTHFR C677T CT genotype T allele and MIF-173GC CC genotype C allele were more prevalent in intensive care patients, indicating a multifactorial genetic predisposition affecting COVID-19 morbidity (Tekcan et al., 2023).

Regarding the impact of deletion and insertion polymorphisms of the ACE1 gene and the single nucleotide polymorphism G8790A of the ACE2 gene on susceptibility to COVID-19, it is noteworthy that although these variations are located in non-coding regions,[23,26] they are associated with changes in ACE1 and ACE2 levels (Tiret et al., 1992; Pinheiro et al., 2019; Wu et al., 2017). The presence of the DD genotype and D allele is linked to increased serum levels of ACE1 (Faridzadeh et al., 2022), resulting in elevated production of angiotensin II (Wong, 2016; Riordan, 2003). The DD genotype of the ACE1 gene has been associated with more severe outcomes in patients with COVID-19 due to several interrelated mechanisms involving the renin–angiotensin system. Specifically, the ACE1 DD genotype contributes to worse outcomes in patients with COVID-19 through mechanisms involving increased ACE activity, reduced ACE2 levels, and heightened susceptibility to acute respiratory complications (Jukic et al., 2023).

Understanding these genetic factors is essential for identifying at-risk populations and tailoring treatment strategies to improve COVID-19 management. The elevated levels of ACE1 in individuals with the DD genotype can be attributed to the genetic characteristics of the ACE ID polymorphism. Individuals with the DD genotype exhibit higher ACE1 levels due to genetic predisposition, leading to increased production of angiotensin II. This elevation is associated with greater inflammatory responses and worse clinical outcomes in diseases such as COVID-19, underscoring the importance of genetic factors in disease severity and management (Boraey et al., 2024).

Conversely, recent evidence suggests that lower levels of ACE2 associated with GG genotypes may contribute to heightened inflammatory responses during SARS-CoV-2 infection (Najafi and Mahdavi, 2023; Faridzadeh et al., 2022). The presence of the GG genotype and G allele may be linked to decreased ACE2 levels, resulting in the upregulation of ACE1 and increased production of angiotensin II (Banu et al., 2020; Pinheiro et al., 2019). Moreover, the binding of SARS-CoV-2 to ACE2 can lead to its exhaustion and downregulation, further promoting ACE1 upregulation and elevating angiotensin II production (Silhol et al., 2020; Banu et al., 2020). Consequently, the presence of these genotypes or alleles in conjunction with COVID-19 infection may lead to excessive production of ACE1 and angiotensin II, potentially exacerbating the severity of the disease (Sarangarajan et al., 2021).

In this study, we examined two distinct populations—Iranians and Afghans—in a small town, revealing that certain genotypes and genetic alleles can predispose individuals to severe cases of COVID-19, even across different ethnic groups. Populations with a higher frequency of these genotypes and alleles may experience greater disease severity despite similar living conditions and better health, social, and economic circumstances. This underscores the significance of genetic differences in disease severity.

The differential susceptibility of Iranians and Afghans to COVID-19 likely results from a complex interplay of genetic factors—such as ACE1 and ACE2 polymorphisms—alongside environmental influences and access to health care. Understanding these molecular mechanisms sheds light on how different populations respond to viral infections such as COVID-19 and emphasizes the need for personalized approaches in disease management. Further research is essential to comprehensively elucidate these relationships.

While this study has focused on specific genetic factors related to COVID-19, future research should also explore other known polymorphisms within genes associated with immune responses to viral infections. Additionally, it is crucial to consider environmental factors such as socioeconomic status and comorbidities across larger and more diverse populations. Exploring these elements will enhance our understanding of COVID-19 susceptibility and severity.

Conclusion

The DD and GG genotypes, along with the D and G alleles, may serve as potential risk factors for susceptibility to COVID-19. This may indicate a higher risk for severe symptoms among the Iranian population compared to the Afghan population. Further research with larger sample sizes and diverse racial populations is warranted to gain a comprehensive understanding of the genetic factors influencing COVID-19 outcomes.

Footnotes

Acknowledgments

The authors take this opportunity to thank the Department of Clinical Biochemistry, Faculty of Medicine, Rafsanjan University of Medical Sciences, Rafsanjan, Iran for their financial support. The authors also gratefully acknowledge the cooperation of all Iranian and Afghan patients, without whom this investigation would not have been possible.

Authors’ Contributions

All authors read and approved the final article. All authors take responsibility for the integrity of the data and the accuracy of the data analysis.

Ethical Considerations

The ethics committee of Rafsanjan University of Medical Sciences approved this study (code: IR.RUMS.REC.1400.247), adhering to the standards outlined in the Declaration of Helsinki. Prior to participation, all volunteers provided written consent, and confidentiality of obtained information was ensured. This research did not interfere with ongoing medical services and treatments provided in health care facilities.

Consent for Publication

By submitting this document, the authors declare their consent for the final accepted version of the article to be considered for publication.

Data Availability

The data used in this study are available from the corresponding author upon request.

Author Disclosure Statement

The authors of this study declare no conflict of interest.

Funding Information

Thanks to financial support, guidance, and advice from Rafsanjan University of Medical Sciences. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report (grant number: 40047/1/20/31).

Supplementary Material

Supplementary Data S1

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