Interferon-Induced Transmembrane Protein-3 Rs12252-G Variant Increases COVID-19 Mortality Potential in Egyptian Population

Abstract

Coronavirus disease 2019 (COVID-19) represented an international health risk. Variants of the interferon-induced transmembrane protein-3 (IFITM3) gene can increase the risk of developing severe viral infections. This cross-sectional study investigated the association between IFITM3 rs12252A>G single nucleotide polymorphism (SNP) and COVID-19 severity and mortality in 100 Egyptian patients. All participants were subjected to serum interleukin-6 (IL-6) determination by ELISA and IFITM3 rs12252 genotyping by real-time polymerase chain reaction. Of all participants, 85.0% had the IFITM3 rs12252 homozygous AA genotype, whereas 15.0% had the heterozygous AG genotype. None of our participants had the homozygous GG genotype. The IFITM3 rs12252A allele was found in 92.5% and the G allele in only 7.5%. There was no significant association (p > 0.05) between the IFITM3 rs12252 SNP and COVID-19 severity, intensive care unit (ICU) admission, or IL-6 serum levels. The heterozygous AG genotype frequency showed a significant increase among participants who died (32.0%) compared with those who had been cured (9.3%). The mutant G allele was associated with patients' death. Its frequency among cured participants was 8.5%, whereas in those who died was 24.2% (p = 0.024) with 3.429 odds ratio [95% confidence interval: 1.1–10.4]. In conclusion, this study revealed a significant association between the G allele variant of IFITM3 rs12252 and COVID-19 mortality. However, results were unable to establish a significant link between rs12252 polymorphism, disease severity, ICU admission, or serum IL-6 levels.

Introduction

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-caused coronavirus disease 2019 (COVID-19), which first emerged in Wuhan, China, in December 2019, posed a serious health threat throughout the world (Zhang et al., 2020). The World Health Organization reports show that as of May 11, 2023, Egypt had reported a cumulative total of 516,023 confirmed COVID-19 cases, including 24,830 deaths, and a total of 112,284,725 vaccine doses had been administered (World Health Organization, 2023). Individuals with COVID-19 experience varying degrees of illness severity.

The majority have no or minor symptoms, and a significant portion is severe cases who experience pneumonia, respiratory difficulty, multiorgan failure, and even death (Taha et al., 2022). Interleukin-6 (IL-6) levels are increased in severe COVID-19 patients. They are usually associated with the uncontrolled release of other cytokines, cytokine storms, which lead to an increase in alveolar-capillary gas exchange and a decrease in pulmonary tissue oxygenation, thus causing rapid worsening of COVID-19 infection and high mortality (Liu et al., 2020). Even without evident risk factors, some COVID-19 patients can rapidly progress. Therefore, other factors, such as host genetic variability, may contribute to disease severity (Taha et al., 2021).

The human interferon-induced transmembrane proteins (IFITMs) are a family of five members, three of which (IFITM1–3) play a role in the innate immune response against microbe infection (Cuesta-Llavona et al., 2021). They are evolutionarily conserved viral restriction proteins that inhibit the infection by enveloped RNA viruses (Bailey et al., 2014). Their restrictive property depends on their localization to plasma (increased infection) and endosomal membranes (reduced infection), constituting the leading portals of viral entry into cells (Cuesta-Llavona et al., 2021; Weston et al., 2014).

Owing to their role in infection, IFITM gene variants are potential modifiers of viral infection risk and disease severity (Gholami et al., 2023; Gholami et al., 2022; Zhao et al., 2019). The human chromosome 11 encodes the 15-kDa protein IFITM3 induced by cytokines such as IL-6 and interferons (Wang et al., 2021). The A > G polymorphism of the IFITM3 rs12252 locus causes aberrant splicing of IFITM3 mRNA and transform IFITM3 protein from an inhibitor to an enhancer of viral entry into cells in vitro (Shan et al., 2017; Shi et al., 2021).

However, the functional effect of IFITM3 rs12252 single nucleotide polymorphism (SNP) remains controversial. Thus, this study aims to determine the frequency of the IFITM3 rs12252 SNP in a cohort of COVID-19 Egyptian patients and its impact on disease severity and outcome, as well as its influence on IL-6 serum levels.

Methodology

Ethics

The ethical committee of the Faculty of Medicine at Ain Shams University approved the study (FMASU MS 506/2021), and before the study began, each participant (or relatives of severely ill or critical patients) provided written informed consent. All information was kept strictly confidential and used for research purposes only. Participants had the option to leave the study at any time.

Study design and participants

This cross-sectional study was performed in the period from September 2021 to March 2022 in the Clinical Pathology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt. The study included 100 confirmed COVID-19 adult Egyptian patients (age ≥18 years) with no previous history of COVID-19 infection nor prior vaccination recruited from Al-Obour Quarantine Hospital. Participants with immunological disorders and other active infections, and those receiving radiotherapy or chemotherapy, taking drugs that affect lymphocytic count, for example, azathioprine, carbamazepine, corticosteroids, opioids, interferons, methotrexate, and pregnant females were omitted from the study.

Diagnosis of COVID-19 was confirmed in all participants by reverse transcription polymerase chain reaction (RT-PCR) through the VIASURE detection system (Bio-Rad) using nasopharyngeal swabs in accordance with WHO guidelines (World Health Organization, 2021). Patients were categorized into three groups: mild (44%), moderate (19%), and severe (37%; severe group included severe and critical cases), according to their disease severity following the Consensus Report of Ain Shams University Hospital Strategy for managing adult COVID-19 patients (Abdelfattah et al., 2020).

Clinical evaluation and data collection

All participants underwent full medical history taking, clinical examination, and radiological evaluation using computed tomography (CT)-scan (CTAWP92544; Siemens Scope, Germany). On admission laboratory data were collected from participants' medical records, including complete blood count, C-reactive protein (CRP), ferritin, and D-dimer.

Blood collection

Four milliliters of venous blood were collected from each participant under complete aseptic precautions divided into two vacutainer tubes; tri-potassium ethylene diamine tetraacetate “k3 EDTA” vacutainer for IFITM3 rs12252 genotyping by real-time PCR and a plain tube containing gel and clot activator for serum separation by centrifugation at 3,000 RPM for 10 min after complete blood clotting for serum IL-6 level determination. All samples were kept at −80°C till the time of analysis.

Serum IL-6 assay

Levels of IL-6 in patients' sera were determined using a quantitative human ELISA kit (Cat. No. CSB-E04638h; Cusabio Technology LLC). The optical density of each well was read using a microplate reader (Thermo Fisher Scientific). The reader was set at 450 nm with a correction wavelength of 620 nm. The kit minimum detectable level of human IL-6 is 2.453 pg/mL with a detection range from 7.8 to 500 pg/mL.

Genotyping of IFITM3 rs12252

Genotyping of IFITM3 (rs12252) SNP was performed by TaqMan real-time PCR. Genomic DNA from EDTA samples was extracted using the whole blood genomic DNA purification QIAamp DNA Mini Kit (QIAGEN, Germany). Then, amplification of the extracted DNA using TaqMan universal master mix and ready-made TaqMan SNP genotyping assay kit for IFITM3 rs12252 SNP (Thermo Fisher Scientific) was done according to the manufacturer's specifications. The primers' sequence was: forward primer 5′-GCATCTCATAGTTGGGGGGCTGGCC-3′; reverse primer: 5′-CTGTTGACAGGAGAGAAGAAGGTTT-3′.

Each reaction mixture (20 μL) contained 2 μL genomic extracted DNA, 10 μL TaqMan genotyping PCR master mix, 1 μL 20 × working stock of SNP genotyping assay and 7 μL DNase-free water. Real-time PCR was performed using Step One thermal cycler (step I version; Applied Biosystems) with the following cycling conditions: polymerase activation at 95°C for 10 min, followed by 40 cycles each of denaturation at 95°C for 15 sec, and annealing/extension at 60°C for 60 sec.

Finally, allelic discrimination was done using Applied Biosystem, step I version software, which demonstrated a scatterplot of allele A (wild allele; VIC dye) versus allele G (mutant allele; FAM dye). A significant increase in VIC dye fluorescence only indicates homozygosity for the A-allele, whereas significant increase in FAM dye fluorescence only indicates homozygosity for the G-allele, and significant increase in both VIC and FAM dye fluorescence indicates AG heterozygosity.

Statistical methodology

Data were analyzed using SPSS 20. For descriptive statistics, parametric quantitative data used mean ± standard deviation (SD), whereas nonparametric quantitative data used median and interquartile range (IQR). Frequency and percentage were employed for qualitative data. The chi-square test, independent t-test, Mann–Whitney U test, and Kruskal–Wallis test were used to compare data. Odds ratios (ORs) and 95% confidence intervals (CIs) were utilized to identify risk factors using regression analysis. Significant p-values were <0.05.

Results

This cross-sectional study included 100 confirmed COVID-19 participants; half were males, and the other half were females. Their age ranged from 29 to 88 years, with a mean ± SD of 61.16 ± 13.18 years. Most of the participants (85%) had risk factors; the most predominant were hypertension (63.0%) and diabetes mellitus (51.0%). Bilateral ground-glass opacity (GGO) was the most common CT scan finding (91.0%). Of all participants, 49.0% were admitted to the intensive care unit (ICU), and 25.0% had died. The median (IQR) IL-6 was 20 (12.5–30) pg/mL. Table 1 demonstrates the demographic, clinical, and laboratory data of all participants.

Table 1.

Demographic, Clinical, Radiological, and Laboratory Data of All Participants (n = 100)

Parameter	n = 100
Age, years
Mean ± SD	61.16 ± 13.18
Range	29–88
Gender, n (%)
Female	50 (50.0)
Male	50 (50.0)
Risk factor, n (%)
No	15 (15.0)
Yes	85 (85.0)
Hypertension	63 (63.0)
Diabetes mellitus	51 (51.0)
Ischemic heart disease	13 (13.0)
Chronic kidney disease	7 (7.0)
Obesity	6 (6.0)
Smoking	4 (4.0)
Acute kidney injury	4 (4.0)
Cancer	4 (4.0)
Asthma	3 (3.0)
COPD	2 (2.0)
CT scan, n (%)
Free	7 (7.0)
Uni-GGO	1 (1.0)
Bi-GGO	91 (91.0)
Lung collapse	1 (1.0)
ICU admission, n (%)
No	51 (51.0)
Yes	49 (49.0)
Fate, n (%)
Cured	75 (75.0)
Died	25 (25.0)
Case severity, n (%)
Mild	44 (44.0)
Moderate	19 (19.0)
Severe	37 (37.0)
Total leukocytic count, × 10⁹/L RR: 4–10
Median (IQR)	9.5 (7.05–13)
Range	3–438
Lymphocytes, × 10⁹/L RR: 1–3
Median (IQR)	0.9 (0.64–1.35)
Range	0.1–171
Hemoglobin, g/dL RR male: 13–17, RR female: 12–16
Mean ± SD	11.75 ± 2.10
Range	5.9–15.5
Platelets, × 10⁹/L RR: 150–410
Median (IQR)	232.5 (161.5–300)
Range	28–1,331 RR: 150–410
Ferritin, ng/mL RR male: 24–336, RR female: 11–307
Median (IQR)	415 (239–1,100)
Range	10–10,000
D-dimer, mg/L RR: <0.5
Median (IQR)	395.5 (7.5–1124.5)
Range	0.08–4,000
CRP, mg/L RR: <6
Median (IQR)	30 (11.6–75)
Range	0.2–200
O₂ SAT, % RR: 95
Mean ± SD	90.60 ± 8.42
Range	50–99
IL-6, pg/mL RR: 0–43.5
Median (IQR)	20 (12.5–30)
Range	0–462.5
Genotype, n (%)
AA	85 (85.0)
AG	15 (15.0)
GG	0.0 (0.0)
Allele, n (%)
A	185 (92.5)
G	15 (7.5)

COPD, chronic obstructive pulmonary disease; CRP, C-reactive protein; CT, computed tomography; GGO, ground-glass opacities; ICU, intensive care unit; IL-6, interleukin-6; IQR, interquartile range; RR, reference range; SAT, saturation; SD, standard deviation.

Regarding the IFITM3 rs12252 genotypes, 85.0% of all participants had the homozygous AA genotype, whereas 15.0% had the heterozygous AG genotype. None of our participants had the homozygous GG genotype. Furthermore, the A allele was found in 92.5% of all participants and the G allele in only 7.5% (Table 1).

Regarding COVID-19 severity, comparative statistics revealed that bilateral GGO and lung collapse in chest CT-scan, ICU admission, and patients' fatalities were all associated with severe COVID-19 cases. As for the laboratory findings, levels of Total leucocyte count (p = 0.036), serum ferritin (p < 0.001), D-dimer (p < 0.001), and CRP (p < 0.001) showed a significant increase with the severe disease. In contrast, levels of hemoglobin (p < 0.001) and O₂ saturation (p < 0.001) showed a significant decrease. In contrast, disease severity had no significant associations (p > 0.05) to levels of lymphocytes, platelets or IL-6. Regarding the IFITM3 rs12252 genotype and allele expression, there was no significant association (p > 0.05) with COVID-19 severity (Table 2).

Table 2.

Comparison of Demographic, Clinical, Radiological, and Laboratory Data of All Participants (n = 100) as Regards COVID-19 Severity

	Case severity			p
	Mild	Moderate	Severe
	n = 44	n = 19	n = 37
Age, n (%)
Age ≤60	22 (50.0)	6 (31.6)	10 (27.0)	0.256
Age 61–69	15 (34.1)	8 (42.1)	16 (43.2)
Age >69	7 (15.9)	5 (26.3)	11 (29.7)
Gender, n (%)
Female	18 (40.9)	12 (63.2)	20 (54.1)	0.222
Male	26 (59.1)	7 (36.8)	17 (45.9)	0.222
Total leukocytic count, × 10⁹/L
Median (IQR)	8.9 (6.8–11)	8.57 (6.2–16.2)	10.5 (8.57–18)	0.036
Range	3–22	4–438	4.3–40	0.036
Lymphocytes, × 10⁹/L
Median (IQR)	1.1 (0.65–1.6)	1 (0.7–2)	0.8 (0.6–1)	0.094
Range	0.1–3	0.4–171	0.3–7	0.094
Hemoglobin, g/dL
Mean ± SD	12.59 ± 2.06	11.75 ± 1.68	10.75 ± 1.94	<0.001
Range	6.9–15.5	8.3–15.1	5.9–14.7	<0.001
Platelets, × 10⁹/L
Median (IQR)	250 (196.5–300.5)	239 (163–269)	200 (154–275)	0.191
Range	28–1,331	133–356	70–600	0.191
Ferritin, ng/mL
Median (IQR)	300 (210–420)	255 (150–1,200)	998 (487–1,699)	<0.001
Range	10–1,300	74–10,000	190–5,000	<0.001
D-dimer, mg/L
Median (IQR)	158 (0.55–450)	440 (210–1,000)	766 (391–1,500)	<0.001
Range	0.08–3,614	0.5–4,000	0.6–3,540	<0.001
CRP, mg/L
Median (IQR)	20.9 (6.5–34)	30 (10–64)	79 (27–100)	<0.001
Range	0.9–152	0.2–100	4–200	<0.001
O₂ SAT, %
Mean ± SD	96.48 ± 1.55	92.53 ± 6.11	82.62 ± 7.99	<0.001
Range	90–99	75–99	50–92	<0.001
IL-6, pg/mL
Median (IQR)	13 (12.5–25)	20 (12.5–30)	20 (10–50)	0.839
Range	5–275	0–100	0–462.5	0.839
CT scan, n (%)
Free	7 (15.9)	0 (0.0)	0 (0.0)	0.019
Uni-GGO	1 (2.3)	0 (0.0)	0 (0.0)
Bi-GGO	36 (81.8)	18 (94.7)	37 (100.0)
Lung collapse	0 (0.0)	1 (5.3)	0 (0.0)
ICU, n (%)
No	38 (86.4)	13 (68.4)	0 (0.0)	<0.001
Yes	6 (13.6)	6 (31.6)	37 (100.0)	<0.001
Fate, n (%)
Cured	41 (93.2)	18 (94.7)	16 (43.2)	<0.001
Died	3 (6.8)	1 (5.3)	21 (56.8)	<0.001
Genotype, n (%)
AA	40 (90.9)	16 (84.2)	29 (78.4)	0.288
AG	4 (9.1)	3 (15.8)	8 (21.6)	0.288
Allele, n (%)
A	84 (95.5)	35 (92.1)	66 (89.2)	0.400
G	4 (4.5)	3 (7.9)	8 (10.8)	0.400

	Post hoc analysis
	Mild vs. moderate	Mild vs. severe	Moderate vs. severe
Total leukocytic count	0.753	0.007	0.253
Hemoglobin	0.121	<0.001	0.074
Ferritin	0.893	<0.001	0.003
D-dimer	0.030	<0.001	0.087
CRP	0.323	<0.001	0.003
O₂ SAT	0.012	<0.001	<0.001
CT scan	0.110	0.049	0.576
ICU	0.096	<0.001	<0.001
Fate	0.816	<0.001	<0.001

Bold p-values indicate statistical significance.

When patients were subdivided based on IFITM3 rs12252 genotyping, both subgroups (AA and AG genotype subgroups) were compared for risk factors, clinical characteristics, laboratory data, and patients' outcome, only patients' outcome showed a significant difference, where most of the homozygous AA genotype participants had been cured (80.0%), whereas most of those with the heterozygous AG genotype had died (53.3%; p = 0.006) (Table 3).

Table 3.

Comparison of Demographic, Clinical, Radiological, and Laboratory Data of All Participants (n = 100) as Regards IFITM3 rs12252 AA and AG Genotypes

	IFITM3 genotype		p
	AA	AG
	n = 85	n = 15
Risk factor, n (%)
No	13 (15.3)	2 (13.3)	0.845
Yes	72 (84.7)	13 (86.7)	0.845
Hypertension	53 (62.4)	10 (66.7)	0.750
Diabetes mellitus	45 (52.9)	6 (40.0)	0.355
Ischemic heart disease	12 (14.1)	1 (6.7)	0.429
Chronic kidney disease	5 (5.9)	2 (13.3)	0.297
Obesity	4 (4.7)	2 (13.3)	0.195
Smoking	2 (2.4)	2 (13.3)	0.045
Acute kidney injury	4 (4.7)	0 (0.0)	0.391
Cancer	3 (3.5)	0 (0.0)	0.460
Asthma	2 (2.4)	1 (6.7)	0.367
COPD	2 (2.4)	0 (0.0)	0.548
Total leukocytic count, × 10⁹/L
Median (IQR)	9.5 (7–13)	9.5 (7.9–14.9)	0.946
Range	3.7–438	3–20	0.946
Lymphocytes, × 10⁹/L
Median (IQR)	0.9 (0.7–1.5)	0.8 (0.6–1.2)	0.670
Range	0.1–171	0.4–2.4	0.670
Hemoglobin, g/dL
Mean ± SD	11.74 ± 2.13	11.78 ± 1.97	0.951
Range	5.9–15.5	9–15.1	0.951
Platelets, × 10⁹/L
Median (IQR)	233 (174–298)	200 (154–300)	0.757
Range	28–1,331	100–358	0.757
Ferritin, ng/mL
Median (IQR)	387 (222–1,000)	487 (300–1,200)	0.472
Range	10–10,000	230–2,100	0.472
D-dimer, mg/L
Median (IQR)	400 (5–1,099)	366 (20–1,200)	0.938
Range	0.08–4,000	0.5–3,614	0.938
CRP, mg/L
Median (IQR)	29 (10–75)	34 (29–66)	0.252
Range	0.2–200	11.6–200	0.252
IL-6, pg/mL
Median (IQR)	20 (12.5–30)	20 (10–100)	0.447
Range	0–275	5–462.5	0.447
O₂ SAT, %
Mean ± SD	91.06 ± 8.50	88.00 ± 7.70	0.196
Range	50–99	70–98	0.196
CT scan, n (%)
Free	7 (8.2)	0 (0.0)	0.627
Uni-GGO	1 (1.2)	0 (0.0)
Bi-GGO	76 (89.4)	15 (100.0)
Lung collapse	1 (1.2)	0 (0.0)
ICU, n (%)
No	46 (54.1)	5 (33.3)	0.138
Yes	39 (45.9)	10 (66.7)	0.138
Fate, n (%)
Cured	68 (80.0)	7 (46.7)	0.006
Died	17 (20.0)	8 (53.3)	0.006
Case severity, n (%)
Mild	40 (47.1)	4 (26.7)	0.288
Moderate	16 (18.8)	3 (20.0)
Severe	29 (34.1)	8 (53.3)

Bold p-value indicates statistical significance.

Furthermore, upon revisiting relation of the studied genetic variants to patients' fatalities by dividing them according to outcome, the IFITM3 rs12252 genotype AG, and the allele G were found to be more frequent among the dead patients' subgroup when compared with the cured one (p = 0.006 with an OR of 4.571, 95% CI: 1.4–14.3 for AG genotype frequency, and p = 0.024 with an OR of 3.429, 95% CI: 1.1–10.4 for the G allele frequency) (Table 4).

Table 4.

Relation of IFITM3 (rs12252) Genotype and Allele Frequencies to Patients' Outcome

	Fate		p	OR (95% CI)
	Cured	Died
	n = 75	n = 25
Genotype, n (%)
AA	68 (90.7)	17 (68.0)	0.006	4.571 (1.455–14.368)
AG	7 (9.3)	8 (32.0)	0.006	4.571 (1.455–14.368)
Allele, n (%)
A	143 (95.3)	42 (84.0)	0.024	3.429 (1.129–10.412)
G	7 (4.70)	8 (16.0)	0.024	3.429 (1.129–10.412)

Bold p-values indicate statistical significance.

CI, confidence interval; OR, odds ratio.

Discussion

Early detection of COVID-19 risk factors would be highly beneficial to define the disease's clinical and epidemiological features more precisely and enable appropriate supportive care and timely admission to the ICU if necessary (Alghamdi et al., 2021). Host-genetic variables may affect COVID-19 phenotypes (Wu et al., 2020). Studies on COVID-19 etiology found numerous gene susceptibility variants with different levels of significance (Novelli et al., 2020; Torre-Fuentes et al., 2021). The IFITM3 rs12252 minor allele (C in minus or G in plus-strand orientation) reduces the expression of IFITM3 protein (Allen et al., 2017), weakens its antiviral activity (Jia et al., 2012), and alters its cellular localization (Chesarino et al., 2014; Jia et al., 2012).

This study found that the frequency of the IFITM3 rs12252-G allele was 13%, which is closer to the frequency in the Saudi population (9%) studied by Alghamdi et al. (2021) and the European population (4%) but much lower than the frequencies found in East Asia (53%) and the entire world population (24%) according to the 1000 genome project (Schönfelder et al., 2021).

The IFITM3 rs12252-G allele was associated with the clinical expression and outcomes of various viral diseases, ranging from nothing in Europeans to severity and mortality in East Asians (Alghamdi et al., 2021). Data from previous studies have demonstrated an association between IFITM3 rs12252 homozygosity of the minor allele and the seriousness of some viral infections (Yu et al., 2023) such as HIV (Zhang et al., 2015), enterovirus (Li et al., 2021), cytomegalovirus (Wang et al., 2021), and influenza (Zhang et al., 2013).

This study has revealed no association between IFITM3 rs12252 SNP and COVID-19 severity. Contrary to what we found, among the few studies concerning the association between IFITM3 rs12252 SNP and COVID-19, a recent study on a small cohort of Chinese individuals by Zhang et al. (2020) documented a significant association between IFITM3 rs12252 SNP and COVID-19 severity suggesting a prominent role of IFITM3 in the pathogenesis of COVID-19.

The frequency of the IFITM3 rs12252 homozygous mutant CC genotype was 35% of their included patients; this genotype was associated with COVID-19 severity (OR = 6.37), where two of their three dead patients had the CC genotype. In addition, a study by Xu et al. (2022) on a Chinese cohort of COVID-19 demonstrated that the IFITM3 rs12252 CC genotype was associated with SARS-CoV-2 infection risk, suggesting that COVID-19 patients with IFITM3 rs12252 minor allele may benefit from early medical intervention.

Similarly, in a cohort of Caucasian COVID-19 patients, Gomez et al. (2021) found that the IFITM3 rs12252 minor allele was significantly more frequent in the COVID-19 participants than in the controls. They found the IFITM3 rs12252 CC genotype in only 1% of their included patients (3/311), and none of the controls had this genotype. They also reported that the IFITM3 rs12252-C allele was associated with a significantly (p = 0.01) increased risk of hospitalization due to COVID-19 by 2.02 times. In contrast, similar to our data, Schönfelder et al. (2021) could not find any association between IFITIM3 rs12252 SNP and COVID-19 susceptibility or severity in a German cohort.

Notably, Zhao (2020) stated that the clinical relevance of the IFITM3 rs12252-C allele for severe COVID-19 might be population dependent. The IFITM3 rs12252 GG genotype was not detected in our included subjects. The lack of an association between the IFITM3 rs12252 SNP and COVID-19 severity in our study raises the possibility that this polymorphism would only affect COVID-19 pathogenesis if the patient had the GG homozygous genotype, a question that needs to be answered by further investigations.

The IFITM3 rs12252-G allele was significantly associated with COVID-19 mortality in this study. Patients with this mutant allele had a 3.4 times more chance of disease mortality than those without that allele. We also found the IFITM3 rs12252 heterozygous AG genotype in only 9.3% of the cured and 32% of dead patients, with 4.571 times more chance of disease mortality than those without the AG genotype. In concordance with our study, Alghamdi et al. (2021) have shown that the IFITM3 rs12252-G allele presence nearly doubled the odds of dying from COVID-19.

Despite the association with mortality, our study has demonstrated no association of IFITM3 rs12252 AG genotype to ICU admission, which concords with the Saudi study by Alghamdi et al. (2021). In line with our findings. A study in Iran by Ahmadi et al. (2022) reported that the IFITM3 rs12252-C allele frequency was significantly higher in dead COVID-19 patients than in those improved, and the IFITM3 rs12252 CC genotype was significantly related to COVID-19 mortality. Partially consistent with our results, a study on a Spanish cohort by Cuesta-Llavona et al. (2021) reported a higher frequency of IFITM3 rs12252-G allele among their included COVID-19 patients with OR of 1.51, but this allele was not associated with ICU admission or death.

The pathogenicity of the IFITM3 rs12252 minor allele relationship with COVID-19 morbidity and mortality is not fully understood. The AG genotype could increase mortality induced by the presence of the SARS-CoV-2 virus but not comorbidities (Alghamdi et al., 2021). The limited sample size could explain the discrepancy between our study and other studies, only 100 patients were included in our study, and the significant observations may be unpredictable.

In this study, we observed higher circulating IL-6 levels in patients with the IFITM3 rs12252 AG genotype IFITM3 compared with the IFITM3 rs12252 AA genotype patients. However, the difference did not reach a statistical significance, possibly due to the limited number of studied patients. However, this might raise the suspicion of a dysregulated immune response in patients carrying the IFITM3 variant. More research is required to identify the pathogenic mechanisms interacting in those with the G allele IFITM3 variation.

This study had certain limitations, being a single-center study with a relatively small sample size, including only COVID-19 patients with no controls, and lacking the follow-up of the recovered and discharged patients. Further multicenter studies with larger sample sizes, including controls to assess the frequency of the SNP among healthy individuals and follow-up of the recovered discharged patients to assess post-COVID-19 complications, are recommended. In addition, a validation experiment is required through Sanger DNA sequencing.

Conclusion

This study revealed a significant association between the IFITM3 rs12252-G allele and COVID-19 mortality. However, no significant association was found between IFITM3 rs12252 SNP and ICU admission, COVID-19 severity, or IL-6 serum levels. It is recommended that additional research on a larger cohort is to be done to confirm our results.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Funding Information

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References

Abdelfattah

, Ahmed

, El-Zahapy

, et al. Hospital Response to COVID-19 A Consensus Report on Ain Shams University Hospital Strategy. ScienceOpen Preprints, 2020; doi: 10.14293/S2199-1006.1.SOR-.PPD4QZX.v1

Ahmadi

, Afifipour

, Sakhaee

, et al. Impact of interferon-induced transmembrane protein 3 gene rs12252 polymorphism on COVID-19 mortality. Cytokine, 2022; 157:155957; doi: 10.1016/j.cyto.2022.155957

Alghamdi

, Alaamery

, Barhoumi

, et al. Interferon-induced transmembrane protein-3 genetic variant rs12252 is associated with COVID-19 mortality. Genomics, 2021; 113(4):1733–1741; doi: 10.1016/j.ygeno.2021.04.002

Allen

, Randolph

, Bhangale

, et al. SNP-mediated disruption of CTCF binding at the IFITM3 promoter is associated with risk of severe influenza in humans. Nat Med, 2017; 23(8):975–983; doi: 10.1038/nm.4370

Bailey

, Zhong

, Huang

, et al. IFITM-family proteins: The cell's first line of antiviral defense. Annu Rev Virol, 2014; 1:261–283; doi: 10.1146/annurev-virology-031413-085537

Chesarino

, McMichael

, Hach

, et al. Phosphorylation of the antiviral protein interferon-inducible transmembrane protein 3 (IFITM3) dually regulates its endocytosis and ubiquitination. J Biol Chem, 2014; 289(17):11986–11992; doi: 10.1074/jbc.M114.557694

Cuesta-Llavona

, Albaiceta

, García-Clemente

, et al. Association between the interferon-induced transmembrane protein 3 gene (IFITM3) rs34481144/rs12252 haplotypes and COVID-19. Curr Res Virol Sci, 2021; 2:100016; doi: 10.1016/j.crviro.2021.100016

Gholami

, Sakhaee

, Mirzaei Gheinari

, et al. Interferon-induced transmembrane protein 3 rs34481144 C/T genotype and clinical parameters related to progression of COVID-19. J Immunol Res, 2023; 2023:2345062; doi: 10.1155/2023/2345062

Gholami

, Sakhaee

, Sotoodehnejadnematalahi

, et al. Increased risk of COVID-19 mortality rate in IFITM3 rs6598045 G allele carriers infected by SARS-CoV-2 delta variant. Hum Genomics, 2022; 16(1):60; doi: 10.1186/s40246-022-00434-8

10.

Gómez

, Albaiceta

, Cuesta-Llavona

, et al. The interferon-induced transmembrane protein 3 gene (IFITM3) rs12252 C variant is associated with COVID-19. Cytokine, 2021; 137:155354; doi: 10.1016/j.cyto.2020.155354

11.

Jia

, Pan

, Ding

, et al. The N-terminal region of IFITM3 modulates its antiviral activity by regulating IFITM3 cellular localization. J Virol, 2012; 86(24):13697–13707; doi: 10.1128/JVI.01828-12

12.

, Li

, Deng

, et al. DNA methylation and SNP in IFITM3 are correlated with hand, foot and mouth disease caused by enterovirus 71. Int J Infect Dis, 2021; 105:199–208; doi: 10.1016/j.ijid.2021.02.049

13.

Liu

, Li

, Zhou

, et al. Can we use interleukin-6 (IL-6) blockade for coronavirus disease 2019 (COVID-19)-induced cytokine release syndrome (CRS)?. J Autoimmun, 2020; 111:102452; doi: 10.1016/j.jaut.2020.102452

14.

Novelli

, Biancolella

, Borgiani

, et al. Analysis of ACE2 genetic variants in 131 Italian SARS-CoV-2-positive patients. Hum Genomics, 2020; 14(1):29; doi: 10.1186/s40246-020-00279-z

15.

Schönfelder

, Breuckmann

, Elsner

, et al. The influence of IFITM3 polymorphisms on susceptibility to SARS-CoV-2 infection and severity of COVID-19. Cytokine, 2021; 142:155492; doi: 10.1016/j.cyto.2021.155492

16.

Shan

, Zhao

, Shan

, et al. Histone demethylase LSD1 restricts influenza A virus infection by erasing IFITM3-K88 monomethylation. PLoS Pathog, 2017; 13(12):e1006773. [Erratum in: PLoS Pathog 2018; 14 (4):e1007037. Erratum in: PLoS Pathog 2021; 17(2):e1009359]; doi: 10.1371/journal.ppat.1006773

17.

Shi

, Kenney

, Kudryashova

, et al. Opposing activities of IFITM proteins in SARS-CoV-2 infection. EMBO J, 2021; 40(3):e106501; doi: 10.15252/embj.2020106501

18.

Taha

, Shata

, Baioumy

, et al. Toll-like receptor 4 polymorphisms (896A/G and 1196C/T) as an indicator of COVID-19 severity in a convenience sample of Egyptian patients. J Inflamm Res, 2021; 14:6293–6303; doi: 10.2147/JIR.S343246

19.

Taha

, Shata

, El-Sehsah

, et al. Comparison of COVID-19 characteristics in Egyptian patients according to their Toll-Like Receptor-4 (Asp299Gly) polymorphism. Infez Med, 2022; 30(1):96–103; doi: 10.53854/liim-3001-11

20.

Torre-Fuentes

, Matías-Guiu

, Hernández-Lorenzo

, et al. ACE2, TMPRSS2, and Furin variants and SARS-CoV-2 infection in Madrid, Spain. J Med Virol, 2021; 93(2):863–869; doi: 10.1002/jmv.26319

21.

Wang

, Wang

, Li

, et al. Molecular characterization, expression and functional analysis of yak IFITM3 gene. Int J Biol Macromol, 2021; 184:349–357; doi: 10.1016/j.ijbiomac.2021.06.057

22.

Wang

, Luo

, Guan

, et al. HCMV infection and IFITM3 rs12252 are associated with Rasmussen's encephalitis disease progression. Ann Clin Transl Neurol, 2021; 8(3):558–570; doi: 10.1002/acn3.51289

23.

Weston

, Czieso

, White

, et al. A membrane topology model for human interferon inducible transmembrane protein 1. PLoS One, 2014; 9(8):e104341; doi: 10.1371/journal.pone.0104341

24.

World Health Organization. Coronavirus disease (COVID-19) Weekly Epidemiological Update and Weekly Operational Update; 2021. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports [Last accessed November 22, 2021 ].

25.

World Health Organization. WHO Coronavirus (COVID-19) Dashboard; 2023. Available from: https://covid19.who.int/ [Last accessed: May 13, 2023 ].

26.

, Spence

, Das

, et al. Site-specific photo-crosslinking proteomics reveal regulation of IFITM3 trafficking and turnover by VCP/p97 ATPase. Cell Chem Biol, 2020; 27(5):571–585.e6; doi: 10.1016/j.chembiol.2020.03.004

27.

, Wang

, Zhao

, et al. IFITM3 inhibits SARS-CoV-2 infection and is associated with COVID-19 susceptibility. Viruses, 2022; 14(11):2553; doi: 10.3390/v14112553

28.

, Wang

, Li

, et al. IFITM3 rs12252 polymorphism and coronavirus disease 2019 severity: A meta-analysis. Exp Ther Med, 2023; 25(4):158; doi: 10.3892/etm.2023.11857

29.

Zhang

, Makvandi-Nejad

, Qin

, et al. Interferon-induced transmembrane protein-3 rs12252-C is associated with rapid progression of acute HIV-1 infection in Chinese MSM cohort. AIDS, 2015; 29(8):889–894; doi: 10.1097/QAD.0000000000000632

30.

Zhang

, Qin

, Zhao

, et al. Interferon-induced transmembrane protein 3 genetic variant rs12252-C associated with disease severity in coronavirus disease 2019. J Infect Dis, 2020; 222(1):34–37; doi: 10.1093/infdis/jiaa224

31.

Zhang

, Zhao

, Li

, et al. Interferon-induced transmembrane protein-3 genetic variant rs12252-C is associated with severe influenza in Chinese individuals. Nat Commun, 2013; 4:1418; doi: 10.1038/ncomms2433

32.

Zhao

. Interferon-induced transmembrane protein 3 related to coronavirus disease 2019. J Infect Dis, 2020; 222(8):1413; doi: 10.1093/infdis/jiaa454

33.

Zhao

, Li

, Winkler

, et al. IFITM genes, variants, and their roles in the control and pathogenesis of viral infections. Front Microbiol, 2019; 9:3228; doi: 10.3389/fmicb.2018.03228