Angiotensin-Converting Enzyme 1 (ACE1) gene polymorphisms in pediatric patients with COVID-19: impact on disease severity and outcomes

Abstract

Background

Angiotensin-converting enzyme 1 (ACE1) gene polymorphisms have been suggested to influence susceptibility to and severity of coronavirus disease 2019 (COVID-19) through dysregulation of the renin–angiotensin system. Despite considerable research on COVID-19, the influence of genetic factors, particularly polymorphisms in the ACE gene, on disease severity in pediatric populations remains inadequately understood. Therefore, the present study aimed to investigate the association of ACE1 insertion/deletion (I/D) polymorphism and ACE1 variants rs4341 and rs4343 with clinical manifestations, laboratory findings, and disease severity in hospitalized children with COVID-19.

Methods

This study included 100 hospitalized pediatric patients with confirmed COVID-19 infection. Demographic characteristics, including age and sex, clinical manifestations, comorbidities, disease severity, laboratory findings, ICU hospitalization, and mortality outcomes were recorded. Genotyping of the ACE1 I/D polymorphism was performed using PCR-based methods, while rs4341 (C/G) and rs4343 (A/G) polymorphisms were analyzed using PCR-restriction fragment length polymorphism (PCR-RFLP) assays.

Results

Among the 100 enrolled patients, 76% had mild/moderate disease and 24% had severe disease. The ACE1 D/D genotype was identified in 76% of patients, whereas the ACE1 I/I genotype was detected in only 3% of cases. In the analysis of the rs4341 polymorphism, among 77 successfully genotyped patients, the C/C genotype was predominant and identified in 56 out of 77 (73.7%) individuals, while the C/G genotype was observed in 20 out of 77 (26.3%) patients. Severe disease was observed in 34 out of 56 (61%) individuals carrying the rs4341 C/C genotype compared with 8 out of 20 (40%) individuals with the C/G genotype; however, the difference was not statistically significant (P = 0.12). Patients carrying the rs4343 A/A genotype exhibited significantly higher white blood cell counts [8.2 (5.7–11.9) ×10⁹ cells/L vs. 5.5 (4.2–7.8) ×10⁹ cells/L, P = 0.008], platelet counts [269 (220.2–332) ×10⁹ cells/L vs. 206 (161.5–300) ×10⁹ cells/L, P = 0.041], and lactate dehydrogenase levels [555.5 (494.8–601.7) U/L vs. 461 (403–593.7) U/L, P = 0.011] compared with rs4343 A/G carriers.

Conclusion

In conclusion, although the ACE1 D/D genotype was highly prevalent among pediatric COVID-19 patients, it was not significantly associated with disease severity or ICU hospitalization. Similarly, no significant associations were identified between rs4341 or rs4343 polymorphisms and overall clinical outcomes. However, rs4343 variants were associated with differences in laboratory parameters, including WBC count, platelet count, and LDH levels, suggesting a possible role in host inflammatory responses during SARS-CoV-2 infection. These findings should be interpreted cautiously due to the relatively small sample size and lack of a healthy control group.

Introduction

The COVID-19 pandemic caused by the novel coronavirus, SARS-CoV-2, has posed challenges to global public health systems. While the disease is often considered less severe in children and young individuals, a subset of pediatric patients undergoes a more complex clinical course, highlighting the need for a better understanding of the factors influencing disease severity [1–3].

Despite extensive research on COVID-19, there remains a significant gap in our understanding of how genetic factors influence disease severity, particularly in pediatric populations [4]. Several factors contribute to the variable presentation and progression of COVID-19, including lymphopenia, T-cell exhaustion, cytokine release syndrome, and the expression of Angiotensin-Converting Enzyme (ACE) receptors in various organs [5–7]. Among these factors, genetic polymorphisms in the ACE gene have garnered attention due to their involvement in the renin-angiotensin system, which plays a crucial role in COVID-19 pathogenesis [8–10].

Polymorphisms in the angiotensin-converting enzyme 1 (ACE1) gene have attracted considerable attention due to their role in the renin–angiotensin system (RAS). ACE1 and ACE2 are key components of the RAS and are involved in the regulation of blood pressure, inflammation, and fluid–electrolyte balance. SARS-CoV-2 enters host cells through binding of its spike protein to the ACE2 receptor expressed on the surface of various human tissues. While ACE2 exerts protective vasodilatory and anti-inflammatory effects, ACE1 promotes the conversion of angiotensin I to angiotensin II, which is associated with vasoconstriction, inflammation, and increased vascular permeability. Therefore, disruption of the ACE1/ACE2 balance may contribute to the pathogenesis and severity of COVID-19 [11–13].

The ACE1 insertion/deletion (I/D) polymorphism is one of the most widely studied human genetic variants. The ACE D allele is associated with increased ACE-1 activity and reduced ACE-2 levels, leading to elevated angiotensin II production, enhanced microvascular permeability, and pulmonary edema. These effects may contribute to disease severity and poorer outcomes in respiratory conditions such as acute respiratory distress syndrome (ARDS) [13, 14].

On the other hand, rs4343 is a functional polymorphism located in exon 17 of the ACE1 gene. This variant has been linked to changes in ACE-1 enzyme activity and circulating serum levels, suggesting that certain genotypes may influence susceptibility to COVID-19 and the severity of the disease [15].

Genetic polymorphisms in the ACE1 gene, including rs4343, rs4341, and the ACE I/D polymorphism, have been demonstrated to influence ACE levels and activity [16–18]. The presence of certain alleles or genotypes in these polymorphisms may lead to altered ACE enzyme activity and levels, potentially influencing physiological processes and disease susceptibility, including conditions such as hypertension and cardiovascular diseases [16].

Despite growing interest in the genetic underpinnings of COVID-19 severity, conflicting findings regarding the association between ACE polymorphisms and disease outcomes have emerged [16–20]. Therefore, a comprehensive investigation into the relationship between ACE polymorphisms and COVID-19 severity is warranted to elucidate their role in disease susceptibility and progression. Understanding the genetic factors underlying COVID-19 severity is crucial for identifying individuals at higher risk and developing targeted interventions. While much research has focused on adult populations, there remains a significant gap in our understanding of how genetic polymorphisms, particularly in the ACE1 gene, influence disease severity in children.

Therefore, the present study aimed to investigate the association of ACE1 I/D polymorphism and ACE1 variants rs4341 and rs4343 with clinical manifestations, laboratory findings, and disease severity in hospitalized children with COVID-19.

Materials and methods

This descriptive cross-sectional study was conducted from December 2021 to March 2022. This study included SARS-CoV-2-positive cases from patients referred to the Children’s Medical Center (CMC), a leading referral hospital in Iran. With nearly 20 specialty and sub-specialty wards and a monthly turnover rate exceeding 35,000 outpatients and 2500 inpatients, CMC offers high-quality, specialized therapeutic services to neonates, infants, and children nationwide.

All methods were performed in accordance with the relevant guidelines and regulations, and written informed consent was obtained from all participants or their legal guardians before the collection of blood samples for this study.

All patients presented with symptoms. Symptomatic cases were characterized by the presence of fever, and/or respiratory signs, and/or diarrhea, and/or vomiting, and/or abdominal pain.

SARS- CoV-2 diagnosis

Nasal or pharyngeal swabs were collected from all participants and promptly transported to the medical molecular laboratory at the study hospitals. The presence of SARS-CoV-2 was determined using real-time transcription PCR [21].

The severity of COVID-19 was categorized into mild/moderate and severe. The severity of pediatric COVID-19 was assessed according to the World Health Organization (WHO) clinical management guidelines [22]. Severity was defined based on the following criteria: oxygen saturation (SpO2) below 93%, partial pressure of oxygen (PaO2) less than 60 mmHg, partial pressure of carbon dioxide (PaCO2) exceeding 50 mmHg, Age-specific tachypnea thresholds were defined as follows: respiratory rate ≥ 60 breaths/min for children < 2 months, ≥ 50 breaths/min for children aged 2–11 months, ≥ 40 breaths/min for children aged 1–5 years, and > 30 breaths/min for children older than 5 years. Additionally, respiratory failure requiring respiratory support, development of septic shock, or critical organ failure necessitating intensive care unit care were also considered indicative of severe disease [21, 23].

Data collection

Data collection for eligible patients involved gathering a comprehensive set of variables. This included demographic information such as the patients’ sex and age, alongside documentation of presenting symptoms. Information on pre-existing comorbid conditions was also collected. Additionally, the severity of the disease was assessed and recorded. Laboratory parameters, ICU hospitalization, and mortality outcomes were tracked as part of the data collection process.

The laboratory findings included various parameters such as white blood cell count (WBC), neutrophil, and lymphocyte counts, platelet count, C-reactive protein (CRP) levels, erythrocyte sedimentation rates (ESR), d-dimer (D-dimer) levels, blood urea nitrogen (BUN) levels, serum creatinine levels, liver enzyme levels, fibrinogen levels, ferritin levels, lactate dehydrogenase (LDH) levels, creatine phosphokinase(CPK) levels, procalcitonin levels, prothrombin time (PT), partial thromboplastin time (PTT), and CK-MB levels. All tests were interpreted according to the respective laboratory reference values [24].

ACE I/D polymorphism

Genomic DNA extraction was performed using the DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany).

The ACE I/D polymorphism was determined using conventional PCR with primers flanking the insertion/deletion region in intron 16 of the ACE1 gene, as previously described [25].

The ACE I/D polymorphism located in intron 16 of the ACE1 gene was determined using conventional PCR using the insertion-specific forward primer INSERT-F (5′-TTTGAGACGGAGTCTCGCTC-3′) and INSERT-R (5′-GATGTGGCCATCACATTCGTCAGAT-3′). This assay selectively amplified the insertion allele and produced a 408 bp fragment in samples carrying the I allele. Furthermore, deletion-specific PCR was carried out using DELETE-F (5′-CCTGCTGCCTATACAGTCACTT-3′) and DELETE-R (5′-TCTGGTAGGGGTTTGAATGC-3′) primers, generating a 129 bp fragment specific for the D allele.

PCR-RFLP genotyping

Genotyping of the rs4341 and rs4343 polymorphisms was performed using the PCR-restriction fragment length polymorphism (PCR-RFLP) method. For rs4341 (C/G), a 200 bp fragment was amplified using the forward primer rs4341F (5′-CGCCAATTTTATTCCAGCTC-3′) and reverse primer rs4341R (5′-TCGGGTAAAACTGGAGGATG-3′). The amplified products were digested with the BsmI restriction enzyme and analyzed by agarose gel electrophoresis. Fragment sizes of 200 bp represented one allele, whereas fragments of 123 and 77 bp represented the alternative allele.

For rs4343 (A/G), PCR amplification was performed using the same primer pair under identical PCR conditions. The resulting 200 bp PCR products were digested with the BtsCI restriction enzyme. Following electrophoresis, fragment patterns of 180 and 20 bp or 116, 64, and 20 bp were used to determine genotypes. Digested products were visualized under ultraviolet illumination after gel electrophoresis [25].

Statistical analysis

Descriptive statistics were used to summarize the demographic and clinical characteristics of the study participants. Continuous variables were presented as mean ± standard deviation (SD) or median with interquartile range (IQR) depending on the distribution, while categorical variables were expressed as frequencies and percentages. The chi-square test was employed to assess the association between categorical variables. All statistical analyses were performed with SPSS 16.0 (SPSS, Inc.). P < 0.05 was considered to indicate a statistically significant difference.

Results

A total of 100 patients were included in the study, including 76 patients with mild/moderate disease and 24 with severe disease. The demographic characteristics revealed a balanced gender distribution, with 52% of the patients being female and 48% male. The mean age of the patients was 5.9 ± 5.0 years. A significant majority (67%) reported a family history of COVID-19, while 31% had underlying health conditions. ICU admission was required for 8% of subjects, with 13% needing oxygen therapy. Unfortunately, a 2% mortality rate was observed. Male sex was more frequent among severe cases compared with mild/moderate patients (n = 16, 67% vs. n = 32, 42%), although the difference was not statistically significant (P = 0.06).

Cough was the most common clinical manifestation and was reported in 39 (51%) patients with mild/moderate disease and 17 out of 23 (74%) severe cases (P = 0.092). Gastrointestinal symptoms including vomiting (37% vs. 21%), abdominal pain (9% vs. 12.5%), and diarrhea (20% vs. 8%), were observed in both groups without significant differences.

Respiratory manifestations were significantly more common among severe patients. Respiratory distress was present in 8 out of 23 (35%) severe cases compared with 2 out of 76 (3%) mild/moderate cases (P < 0.0001). Similarly, tachypnea was significantly more frequent in severe disease (42% vs. 8%, P < 0.0001). Chest pain was also more commonly observed among severe patients (17% vs. 4%), although this difference did not reach statistical significance (P = 0.055).

Other manifestations, including myalgia, conjunctivitis, skin rash, and seizure did not differ significantly between the groups. Detailed clinical characteristics are presented in Table 1.

Table 1.

Comparison of symptoms between patients with mild/moderate and severe COVID-19

Variable	Mild/moderate (n = 76)		Severe (n = 24)		P value
	n	%	n	%
Sex (male)	32	42	16	67	0.06
Symptom
Cough	39	51	17 out of 23	74	0.092
Vomiting	28	37	5	21	0.146
Abdominal pain	7	9	3	12.5	0.699
Diarrhea	15	20	2	8	0.349
Chest pain	3	4	7	17	0.055
Skin rash	2 out of 75	3	1	4	0.569
Respiratory distress	2	3	8 out of 23	35	< 0.0001
Myalgia	5	7	4	17	0.212
Tachypnea	6	8	10	42	< 0.0001
Conjunctivitis	2	3	2	8	0.243
Seizure	2	3	3	12.5	0.088

Among the 100 analyzed cases, the ACE1 I/I genotype was identified in only 3% of patients. None of these individuals required ICU hospitalization, ventilator support, or intubation, and no cases of asthma, immune deficiency, or mortality were observed in this group. In contrast, the ACE1 D/D genotype was detected in 76% of patients. In the remaining samples, no definitive ACE1 genotype could be determined because neither insertion-specific nor deletion-specific PCR amplification produced reproducible bands. These unresolved cases were most likely attributable to technical limitations, including low DNA quality or concentration. Therefore, these samples were excluded from subsequent genotype analyses.

In the analysis of the rs4341 polymorphism, among 77 cases, the C/C genotype was predominant, found in 56 individuals (73.7%), while the C/G genotype was observed in 20 individuals (26.3%). Among individuals with the rs4341 C/C genotype, 61% (n = 34) experienced severe outcomes, while 40% of those with the C/G genotype (n = 8) showed severe disease, however, the difference was not significant (P = 0.12). Mortality was observed in 4.3% of individuals with the rs4341 C/C genotype, while there were no deaths among individuals with the rs4341 C/G genotype.

Regarding the rs4343 polymorphism, among 97 cases, the A/G genotype was predominant, observed in 64 individuals (66.0%), while the A/A genotype was present in 33 individuals (34.0%).

No statistically significant association was found between rs4341 or rs4343 genotypes and patient sex (Fig. 1). Likewise, no significant differences were observed when assessing the relationship between these polymorphisms and patient age or their potential impact on COVID-19 clinical outcomes.

Fig. 1.

Demographic and clinical outcomes in COVID-19 patients with ACE1 I/I, ACE1 D/D, rs4341 and rs4343 polymorphisms

Clinical characteristics and outcomes according to ACE1 polymorphisms are summarized in Fig. 1. Among patients carrying the rs4343 A/G genotype, severe disease was observed in 13 out of 64 (20%) cases, while ICU hospitalization occurred in 4 cases (6%). Underlying diseases were present in 18 (28%) patients, whereas asthma, ventilator requirement, immunodeficiency, intubation, and mortality were infrequent, occurring in 2–5% of cases. Patients with the rs4343 A/A genotype showed relatively higher frequencies of severe disease (9 out of 33, 27%) and ICU hospitalization (n = 3, 9%) compared with rs4343 A/G carriers. Similarly, underlying diseases were reported in 10 (30%) of individuals with rs4343 A/A variant. Among rs4341 genotypes, severe disease and ICU hospitalization were observed in only 1 out of 20 (5%) patients carrying the rs4341 C/G genotype, with no cases of ventilator requirement, immunodeficiency, intubation, or mortality. In contrast, rs4341 C/C carriers demonstrated higher proportions of severe disease (14 out of 56, 25%), ICU hospitalization (n = 4, 7%), underlying diseases (n = 18, 32%), and mortality (n = 2, 4%). Regarding ACE1 I/I, severe disease was identified in 1 out of 3 (33%) individuals, while no ICU hospitalization, ventilator requirement, immunodeficiency, intubation, or mortality was observed in this group. Patients with the ACE1 D/D exhibited relatively higher frequencies of severe disease (16 out of 76, 21%), ICU hospitalization (n = 6, 8%), ventilator requirement (n = 2, 3%), immunodeficiency (n = 3, 4%), intubation (n = 2, 3%), and mortality (n = 1, 2%).

No significant differences in symptoms were observed between individuals with ACE1 D/D, ACE1 I/I, rs4341, and rs4343 polymorphisms (Table 2).

Table 2.

Frequency of symptoms in COVID-19 patients with ACE1 I/D, rs4341, and rs4343 polymorphisms

Variant	cough	sore throat	conjunctivitis	edema	tachypnea	chest pain	vomiting	abdominal pain	diarrhea	distress	myalgia	rash	seizure
	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)
ACE1 I/I	1 (33)	0	1 (33)	1 (33)	0	0	1 (33)	0	0	0	0	1 (33)	0
ACE1 D/D	49 (64.5)	7 (9)	1 (1)	0	13 (17)	7 (9)	27 (35.5)	8 (10.5)	14 (18)	6 (8)	8 (10.5)	2 (3)	2 (3)
rs4341 C/C	34 (62)	6 (11)	2 (4)	1 (2)	8 (14)	6 (11)	19 (34)	6 (11)	10 (18)	8 (14.6)	7 (12.5)	3 (5.5)	4 (7)
rs4341 C/G	8 (40)	2 (10)	1 (5)	0	5 (25)	0	8 (40)	2 (10)	4 (20)	1 (5)	0	0	0
rs4343 A/G	37 (58)	4 (6)	1 (2)	0	11 (17)	3 (5)	24 (37.5)	8 (25)	11 (17)	5 (8)	6 (9)	1 (2)	1 (2)
rs4343 A/A	17 (53)	4 (12)	3 (9)	1 (3)	5 (15)	4 (12)	8 (24)	2 (6)	6 (18)	5 (15)	3 (9)	2 (6)	3 (9)

Table 3 summarizes the laboratory findings of COVID-19 patients according to ACE1 D/D, rs4341, and rs4343 polymorphisms. Due to the very small number of individuals carrying the ACE1 I/I genotype (n = 3), statistical analysis comparing ACE1 I/I with ACE1 D/D genotypes was not performed.

Table 3.

Laboratory findings in COVID-19 patients with ACE1 D/D, rs4341, and rs4343 polymorphisms

White Blood Cell count (× 109 cells per L)	ACE1 D/D	rs4341 C/C	rs4341 C/G	rs4343 A/G	rs4343 A/A
	5.6 (4.2–7.7)	5.93 (4.2–9.3)	6 (4.8-9)	5.5 (4.2–7.8)	8.2 (5.7–11.9)
Platelet count (× 109 cells per L)	216 (169–299)	232 (169.5–300)	267 (172–344)	206 (161.5–300)	269 (220.2–332)
Neutrophil count (× 109 cells per L)	2.7 (1.4–4.3)	2.7 (1.4–5.1)	2.75 (1.6–4.7)	2.4 (1.2–3.9)	4.3 (2.6–7.7)
Lymphocyte count (× 109 cells per L)	2.2 (1.3–3.2)	2.3 (1.3–3.2)	2.6 (1.8–3.9)	2.2 (1.2–3.2)	2.3 (1.7–3.6)
Ferritin (ng/mL)	112.0 (54.0–215.0)	133.5 (63.25-240.25)	81.5 (49-214.25)	97 (53.2–229)	136 (54–231)
D-dimer (ng/mL)	356 (200–606)	347 (200–603)	480 (200–697)	377 (200-625.5)	337 (200–565)
Fibrinogen (mg/dL)	340 (279.8–406.3)	355 (243.75–437.5)	309 (279.75-366.25)	310 (260–396)	360 (275–455)
C-reactive protein level (mg/L)	5 (2.0–27.5)	6 (2–30)	9 (2–56)	4 (2–17)	7 (1-35.5)
Erythrocyte sedimentation rate (mm/hr)	15 (10.5–30.5)	15 (10.5–31.5)	21 (11–30)	14 (9.5–29.5)	21 (11–32)
Aspartate aminotransferase (U/L)	35 (26–52.8)	34.5 (26-53.75)	29.5 (25-51.75)	34 (25-53.2)	32 (21.5–49.5)
Alanine transaminase (U/L)	22 (17–53.8)	24.5 (17.75-62)	21.5 (16.25–31.75)	22 (16.7–52.2)	23 (14.5–45.5)
Procalcitonin (ng/mL)	0.11 (0.1–0.2)	0.14 (0.06–0.26)	0.13 (0.06–0.3)	0.13 (0.06–0.23)	0.07 (0.4 − 0.3)
Prothrombin Time (seconds)	15 (13.7–16.6)	15 (13.4–16.6)	15.1 (14-16.6)	15 (14-16.2)	15 (13.5–16.9)
Partial Thromboplastin Time (seconds)	38 (33–42.8)	36.5 (33–43)	38 (32–42)	38 (32.2–42.7)	38 (33-41.5)
Blood Urea Nitrogen (mg/dL)	10 (8–14)	11 (7–14)	10 (7.25–12.75)	10 (8–14)	11(7.2–13.7)
Creatinine (mg/dL)	0.6 (0.4–0.7)	0.6 (0.4–0.7)	0.5 (0.4–0.6)	0.6 (0.4–0.7)	0.6 (0.5–0.7)
Creatine Kinase (U/L)	94 (60.3–132)	93 (57–163)	105 (53.5-132.5)	94 (70–135)	89.5 (43.7-146.2)
Lactate dehydrogenase (U/L)	493.5 (410.8–598.8)	537 (433-623.25)	461 (432-561.5)	461 (403-593.7)	555 (494.7-601.7)
Creatine Kinase-MB (U/L)	23 (17.5–34)	23 (18.5–36)	16 (20-20.25)	21 (17–32)	21.5 (15.7–36)
CD4 T cell count (cells/µL)	39.0 (31–48)	38 (28.5–48.5)	40 (34–53)	39 (31.2–48.7)	36.5 (25-42.7)
CD8 T cell count (cells/µL)	25 (18.5–32)	28 (19.5–32)	20 (17–27)	25 (20-32.7)	24.5 (18-31.7)

Significant differences were observed among rs4343 genotypes with respect to platelet count, WBC count, and LDH levels. Individuals carrying the rs4343 A/A genotype exhibited significantly higher platelet counts [269 (220.2–332) ×10⁹ cells/L] compared with those carrying the rs4343 A/G genotype [206 (161.5–300) ×10⁹ cells/L; P = 0.041]. Similarly, WBC counts were significantly elevated in rs4343 A/A carriers [8.2 (5.7–11.9) ×10⁹ cells/L] compared with rs4343 A/G individuals [5.5 (4.2–7.8) ×10⁹ cells/L; P = 0.008]. In addition, LDH levels were significantly higher in patients with the rs4343 A/A genotype [555.5 (494.8–601.7) U/L] than in those carrying the rs4343 A/G genotype [461 (403–593.7) U/L; P = 0.011]. No statistically significant differences were observed for the remaining laboratory parameters among the evaluated genotypes.

Discussion

The polymorphic nature of the ACE1 gene has attracted considerable attention regarding its potential role in susceptibility to and severity of COVID-19. Since the renin–angiotensin system is involved in inflammation, vascular permeability, and pulmonary injury, genetic variations affecting ACE1 activity may influence the host response to SARS-CoV-2 infection [11, 12, 15, 20, 26]. However, previous studies investigating ACE1 polymorphisms in COVID-19 have reported inconsistent findings across different ethnic populations and age groups, and limited data are available in hospitalized pediatric patients.

In the present study, the ACE1 deletion genotype was highly prevalent among hospitalized pediatric COVID-19 patients, accounting for 76% of cases. Patients carrying the ACE1 D/D genotype demonstrated relatively higher frequencies of severe clinical outcomes, including ICU hospitalization, ventilator requirement, and intubation, compared with individuals carrying the ACE1 I/I genotype. Although the low frequency of the ACE1 I/I genotype limited statistical comparisons, none of the individuals with this genotype required ICU admission or ventilatory support. These findings are in agreement with previous reports suggesting that the ACE1 D allele may contribute to enhanced disease severity through increased ACE activity and elevated angiotensin II production, resulting in enhanced inflammatory responses and pulmonary damage [14, 20, 27, 28]. Previous studies have reported that the ACE1 (rs4646994) D/D genotype is associated with increased susceptibility to COVID-19 in Asian populations, increasing the risk by approximately 1.7-fold, while no significant association has been observed in Western populations [12].

A research study conducted among the Brazilian population revealed that there were no notable differences observed in the genotype and allele distribution of ACE polymorphism concerning the severity of COVID-19 [29].

Previous reports indicating that the G allele of the rs4343 SNP increases the severity of COVID-19 [16]. Our study revealed that individuals with the rs4343 A/G genotype exhibited higher rates of severe outcomes compared to those with the C/G genotype. However, the difference was not significant. In a study conducted by Íñiguez in Spain, it was found that the G allele of rs4341 and rs4343 was linked with severe cases of COVID-19 among hypertensive patients, regardless of gender. Furthermore, individuals with G-carrier genotypes for both polymorphisms exhibited higher mortality rates (P < 0.05) and increased severity of COVID-19 among those with dyslipidemia and type 2 diabetes [16].

In children, respiratory symptoms are the primary manifestation, followed by fever and gastrointestinal symptoms [3, 21, 30–33]. No significant differences were found in symptoms between individuals with the rs4341 and rs4343 polymorphisms. This indicates that these genetic variations may not have a substantial impact on symptoms in the examined population.

We additionally evaluated the potential role of ACE1 genetic variants, including the ACE I/D polymorphism and rs4341 and rs4343 SNPs, in disease severity and laboratory abnormalities. Although no significant associations were observed between rs4341 or rs4343 genotypes and patient sex, age, or overall COVID-19 outcome, several laboratory parameters differed according to rs4343 genotypes. Specifically, rs4343 A/A carriers exhibited significantly higher WBC counts, platelet counts, and LDH levels compared with rs4343 A/G individuals, suggesting a possible relationship between this polymorphism and inflammatory or tissue injury responses during SARS-CoV-2 infection.

The ACE1 D/D genotype was detected in the majority of patients and was associated with relatively higher frequencies of severe clinical outcomes, including ICU hospitalization, ventilator requirement, and intubation. In contrast, none of the individuals carrying the ACE1 I/I genotype required ICU admission or ventilatory support, although interpretation of this finding is limited by the very small number of ACE1 I/I cases in our study.

Several limitations should be acknowledged. First, the relatively small sample size, particularly the low frequency of certain genotypes such as ACE1 I/I, may have limited the statistical power of the analyses. Second, unresolved genotypes in a subset of samples due to unsuccessful PCR amplification may have affected genotype distribution analyses. In addition, the absence of a healthy control group limited our ability to fully evaluate the contribution of ACE1 polymorphisms to COVID-19 susceptibility and clinical outcomes. Finally, the single-population design may restrict the generalizability of our findings to other ethnic groups and geographic regions.

Conclusion

In conclusion, although the ACE1 D/D genotype was highly prevalent in our cohort, it was not significantly associated with hospitalization severity or ICU admission among pediatric COVID-19 patients. Likewise, no significant associations were identified between rs4341 or rs4343 polymorphisms and overall clinical outcomes. However, rs4343 variants were associated with differences in several laboratory parameters, including WBC count, platelet count, and LDH levels, suggesting a possible role in inflammatory responses during SARS-CoV-2 infection.

The absence of statistically significant associations may be attributable to the relatively small sample size and the low frequency of certain genotypes. Therefore, these findings should be interpreted with caution. Further large-scale multicenter studies involving ethnically diverse populations and appropriate control groups are required to better clarify the role of ACE1 polymorphisms in pediatric COVID-19 severity.

Authors’ contributions

SM1 and SM2 conceived and designed the study. RHS performed laboratory tests. SM1 and MT analyzed and interpreted the data and wrote the manuscript. RHS and BP recruited patients, collected samples, and interpreted the data. All authors approved the final version of the article for submission.

Funding

This study was supported by a grant (grant number: 1400-3-149-53254) from Tehran University of Medical Sciences to Dr. Shima Mahmoudi.

Data availability

All data from this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

This research received ethical approval from Tehran University of Medical Sciences, Tehran, Iran (IR.TUMS.CHMC.REC.1400.245). All methods were performed in accordance with the relevant guidelines and regulations and written informed consent was obtained from all participants or their legal guardians before the collection of blood samples for this study. Research conducted in compliance with the Helsinki Declaration.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.