Introduction
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a member of the family of Coronaviridae, is responsible for coronavirus disease 2019 (COVID-19). The most common symptoms are fever, cough, and dyspnea [1]. Despite intensive research, it remains to be unraveled why some individuals get infected while others remain uninfected under similar conditions (e.g. medical history or exposure to SARS-CoV-2). In addition, it is unclear why the course of the disease differs drastically between different subjects with similar preconditions ranging from mild symptoms to death with an overall fatality rate of around 2% (25 January 2021) and an in-hospital mortality ranging from 28 to 72% [2,3]. The main risk factors discussed for infection and severity are older age, male gender, obesity, and a variety of disorders such as hypertension, diabetes, and coronary heart disease, to name but a few [1,2,4].
Virus entry into host cells depends on binding of the viral spike (S) protein to membrane-bound angiotensin-converting enzyme II (ACE2) [5], which is localized on, for example, oral mucosa, respiratory tract, and heart cells [6,7]. Its main physiological function is the degradation of angiotensin II (Ang II) to angiotensin 1–7 (Ang 1–7) which activates the vasorelaxant mas-related G-protein coupled receptor [8]. Many authors have postulated that single-nucleotide polymorphisms (SNPs) in the gene ACE2 (Xp22.2) could affect its expression and also the binding affinity of SARS-CoV-2, thereby influencing the susceptibility for SARS-CoV-2 infection and severity of COVID-19 [9–12]. The best characterized SNP in ACE2 is a splice region variant (rs2285666, G>A, Intron 3/4). Several studies have shown associations with hypertension, coronary heart disease, and diabetes combined with cerebral stroke [13–15]. Interestingly, the A-allele is associated with increased serum levels of ACE2 in healthy controls, subjects with diabetes, and patients with diabetes along with cerebral stroke [13]. Although it is unknown whether the increased serum ACE2 levels associated with the A-allele actually also reflect increased membrane-bound ACE2 in, for example, the lung or other tissues, this polymorphism appears to be an attractive candidate associated with an altered susceptibility for infection or course of COVID-19 given the fact that ACE2 functions as a cellular ‘receptor’ for virus entry.
Another frequently discussed gene is ACE (17q23.3) coding for angiotensin-converting enzyme (ACE), usually cleaving angiotensin I (Ang I) to Ang II, which activates the angiotensin II receptor type 1 (AT1R) mediating vasoconstrictive, pro-inflammatory, and -fibrotic effects [8]. A deletion/insertion (D/I) of an Alu repeat (rs1799752, Intron 16) in the gene ACE may also play a role in COVID-19 [11]. ACE rs1799752 D-allele carriers show significantly higher ACE serum levels than carriers of the I-variant [16]. While the D-allele is associated with an increased risk for, for example, myocardial infarction or left ventricular hypertrophy [17,18], it is also a risk factor for the development and progression of acute respiratory distress syndrome (ARDS) and SARS [19–22]. Recently, Yamamoto et al. demonstrated in an in-silico study, that ACE rs1799752 II genotype is negatively correlated with number of SARS-CoV-2 cases and deaths in East Asia [23]. In a first case-control study, encompassing 204 SARS-CoV-positive patients, the ACE rs1799752 DD genotype was associated with a higher risk for severe COVID-19 [24].
Thus, those variants in the genes ACE2 and ACE are good candidates in genetic association studies trying to learn more about the genetic causes of susceptibility for infection with SARS-CoV-2 and the severity of COVID-19.
Methods
Study participants and recruitment
The study was conducted following the approval of the ethics committees of the Medical Faculties of the University of Duisburg-Essen (20-9230-BO), Ruhr-University Bochum (20-6886), and RWTH Aachen University (206/09) and in cooperation with the West German Biobank (WBE; 20-WBE-088) and the RWTH centralized Biomaterial Bank (RWTH cBMB; 31-2020). Written informed consent was obtained from the study patients.
Enrolment from the respective hospitals or centers (Essen, Aachen, Herne, or Mettmann) started on 11 March 2020 and ended on 30 September 2020. Patients were initially recruited upon presentation with COVID-19 typical symptoms, that is, fever, cough, and dyspnea, or who were admitted to the hospital/center with already confirmed SARS-CoV-2 infection. We included 297 SARS-CoV-2-positive patients. Follow-up was completed on 31 October 2020, at which time all patients either were discharged from the hospitals as ‘cured’ or had a fatal outcome of the disease. We also studied 253 SARS-CoV-2-negative patients, who presented with COVID-19 typical symptoms but were tested SARS-CoV-2-negative by real-time reverse-transcription-PCR (RT-PCR). Those patients were hospitalized at the University Hospital Essen or treated as outpatients, due to other medical conditions. SARS-CoV-2 positivity or negativity was determined as described below. Samples from 200 anonymous blood donors collected before the COVID-19 pandemic served as a reference cohort.
SARS-CoV-2 in vitro diagnostic test
Nasopharyngeal swabs were collected and SARS-CoV-2 RNA positivity was determined by qualitative RT-PCR with in vitro diagnostic kits according to manufacturers’ instructions. Patients were classified as SARS-CoV-2-positive with at least one positive RT-PCR test result and as SARS-CoV-2-negative with exclusively negative RT-PCR test results and no COVID-’typical’ or COVID-’possible’ chest computed tomography (CT) result (see below).
Chest computed tomography
A diagnostic chest CT scan was performed with default settings for thoracic routine when patients presented with clinical signs indicating an infection of the lower respiratory tract defined as dyspnea, tachypnea (breathing rate > 25), cough, a decreased oxygen saturation (<92%), or crackles [25]. All images were performed in one of the three CT systems (Somatoform Force, Somatom Definition AS+, Somatom Definition Flash; Siemens Healthineers, Erlangen, Germany). All CT examinations were re-evaluated especially for this study by a board-certified senior radiologist blinded for SARS-CoV-2 RT-PCR test results. Diagnosis of SARS-CoV-2 pneumonia was established as follows: multifocal bilateral distribution of ground-glass opacity with/without consolidations in lung regions close to visceral pleural surfaces (including fissures) or signs of ARDS [1,26]. SARS-CoV-2 RT-PCR-negative patients, who presented any of these features (‘typical’) or atypical CT results, which could be related to COVID-19 pneumonia (‘possible’) were excluded from the study (N = 69) since sensitivity of chest CT was found to be superior to RT-PCR [27]. The results of chest CT scans from SARS-CoV-2-positive patients served as internal quality control (N = 182).
Demographics, clinical characteristics, and outcome of the patients
Demographics, clinical characteristics, and outcomes were obtained from the electronic patient records. For each patient’s age, sex, medical history, medication of angiotensin-converting-enzyme inhibitors (ACEi), and angiotensin II receptor blockers (ARBs), initial symptoms (fever, cough, and dyspnea [1]), and outcome were collected. Medical history was classified based on the European Centre of Disease Prevention and Control (ECDC) [28] as cardiovascular system (e.g. myocardial infarction, coronary heart disease, but not arterial hypertension), arterial hypertension, or diabetes. Clinical outcome was defined as follows according to the criteria of the ECDC – ‘mild’: outpatients; ‘hospitalized’: inpatients; ‘severe’: hospitalized patients admitted to an ICU or became dependent on mechanical ventilation, or both; ‘fatal’ all cases of COVID-19-related deaths during the hospital stay. In contrast to the ECDC classification, where patients are counted up to three times, every patient only counted once according to the worst clinical outcome observed during the hospital stay in our study. The main group ‘moderate’ consisted of the subgroups ‘mild’ and ‘hospitalized’, whereas the main group ‘serious’ consisted of the subgroups ‘severe’ and ‘fatal’.
Genotyping of ACE2 and ACE
PCR was performed with 100 ng genomic DNA and 30 µL Taq DNA-Polymerase 2x Master Mix Red (Ampliqon, Odense, Denmark) with the following conditions: initial denaturation 95°C for 5 min; 38 cycles with denaturation 95°C for 30 s, annealing temperature (Tm) °C for 30 s and elongation 72°C for 30 s each; final elongation 72°C for 10 min. Oligonucleotide sequences and Tm for the respective polymorphisms can be found in Supplemental Digital Content 1, https://links.lww.com/FPC/B393. Genotyping was performed for ACE2 rs2285666 and ACE rs1799752 by Pyrosequencing according to the manufacturers’ instructions (Qiagen, Hilden, Germany). For ACE2 coding region polymorphisms (amino acids 1-62, MAF ≥ 0.005, Supplemental Digital Content 2, Supplemental Digital Content 1, https://links.lww.com/FPC/B393) only previously identified SNPs with potential functional impact on SARS-CoV-2 binding were analyzed by Sanger sequencing [9,10].
Statistical analyses
Correlations of demographics and clinical characteristics with SARS-CoV-2 infection risk were analyzed by Fisher’s exact test. Differences between age groups in SARS-CoV-2-positive and SARS-CoV-2-negative patients were estimated by Mann–Whitney test.
Hardy–Weinberg equilibrium (HWE) for ACE was calculated using Pearson’s χ2 goodness of fit test and samples were considered as deviant from HWE at a significance level of P < 0.05. HWE for X-chromosomal ACE2 was tested with the R-script ‘HWadmiX’ [29].
For genetic association, we calculated odds ratio (OR) and 95% confidence interval (CI) by Fisher’s exact test using Baptista-Pike method for OR, respectively. P-values are reported two-sided and values of < 0.05 were considered significant.
Multivariable analysis was performed to estimate independence of the variables age, sex, medical history, medication, and ACE rs1799752 or ACE2 rs2285666 genotypes by logistic regression (likelihood ratio test, backward).
Results
Demographics, clinical characteristics, and outcome of the patients
From March 11, 2020, to October 31, 2020, we enrolled and studied 297 SARS-CoV-2-positive and 253 SARS-CoV-2-negative patients to determine the associations of SNPs in the genes ACE2 and ACE with susceptibility for SARS-CoV-2 infection and severity of COVID-19.
SARS-CoV-2-positive and SARS-CoV-2-negative patients had similar demographics and clinical characteristics (Table 1). Considering cardiovascular diseases except for hypertension, we observed a significantly higher prevalence in the SARS-CoV-2-negative patients (48.2% vs. 36.1%, P = 0.01). There were no differences regarding ACEi or ARBs medication in both groups. Cough and dyspnea were the most frequent initial symptoms in the SARS-CoV-2-positive group (P < 0.0001 and P = 0.03, respectively). We found significantly more SARS-CoV-2-positive patients than SARS-CoV-2-negative patients in the ‘serious’ group (‘severe’ plus ‘fatal’; P = 0.001). Comparing the ‘moderate’ and the ‘serious’ groups, we found a significant association for the severity of COVID-19 with age (P = 0.02), male sex (OR: 2.25, 95% CI, 1.32–3.84, P = 0.003), and cardiovascular disease (OR: 1.84, 95% CI, 1.10–3.08, P = 0.02) (Table 2).
Table 1 - Demographics, clinical characteristics, and outcome of the patients
| Characteristics |
All patients
(N = 550) |
SARS-CoV-
2-positive
(N = 297) |
SARS-CoV-
2-negative
(N = 253) |
P |
| Median age (range) – yrs. |
62.0 (18–99) |
60.0 (18–99) |
63.0 (22–97) |
0.17 |
| Male sex – no. (%) |
323 (58.7) |
176 (59.3) |
147 (58.1) |
0.79 |
| Medical history – no. (%) |
| Cardiovascular systema |
225 (41.7) |
104 (36.1) |
121 (48.2) |
0.01 |
| Arterial hypertension |
266 (49.3) |
133 (46.2) |
133 (52.8) |
0.14 |
| Diabetes |
138 (25.6) |
66 (22.9) |
72 (28.7) |
0.14 |
| Medication – no. (%)b |
| ACEi |
129 (23.9) |
61 (21.2) |
68 (27.1) |
0.13 |
| ARBs |
85 (15.8) |
44 (15.3) |
41 (16.3) |
0.81 |
| Initial symptoms – no. (%) |
| Fever |
224 (46.7) |
107 (46.1) |
117 (47.2) |
0.85 |
| Cough |
164 (34.2) |
103 (44.4) |
61 (24.6) |
<0.0001 |
| Dyspnea |
185 (38.5) |
101 (43.5) |
84 (33.9) |
0.03 |
| Outcome – no. (%)c |
| Moderate – |
Mild |
67 (12.1) |
30 (10.1) |
37 (14.6) |
0.12 |
| Hospitalized |
347 (63.1) |
177 (59.6) |
170 (67.2) |
0.07 |
| Serious – |
Severe |
66 (12.0) |
44 (14.8) |
22 (8.7) |
0.03 |
| Fatal |
70 (12.7) |
46 (15.5) |
24 (9.5) |
0.04 |
ECDC, European Centre of Disease Prevention and Control; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
aCardiovascular system: e.g. myocardial infarction, coronary heart disease but not arterial hypertension.
bOnly angiotensin-converting-enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARBs) were analyzed.
cClassification according to the COVID-19 surveillance report of the ECDC: category ‘mild’ is a case that has not been reported as hospitalized or dead. Whereas a ‘severe’ case has been admitted to intensive care and/or required respiratory support.
Table 2 - Association of demographics and clinical characteristics of SARS-CoV-2-positive patients with COVID-19 severity
| Characteristics |
Moderatea (N = 207) |
Seriousa (N = 90) |
OR (95% CI) |
P |
| Median age (range) – yrs. |
58.0 (18–94) |
64.0 (26–99) |
NA |
0.02 |
| Male sex – no. (%) |
111 (53.6) |
65 (72.2) |
2.25 (1.32–3.84) |
0.003 |
| Medical history – no. (%) |
| Cardiovascular systemb |
63 (31.7) |
41 (46.1) |
1.84 (1.10–3.08) |
0.02 |
| Arterial hypertension |
89 (44.7) |
44 (49.4) |
1.21 (0.73–1.99) |
0.52 |
| Diabetes |
43 (21.6) |
23 (25.8) |
1.26 (0.71–2.26) |
0.45 |
| Medication – no. (%)c |
| ACEi |
37 (18.6) |
24 (27.0) |
1.62 (0.90–2.91) |
0.12 |
| ARBs |
31 (15.6) |
13 (14.6) |
0.93 (0.46–1.87) |
0.86 |
OR, odds ratio; CI, confidence interval; P, P value as calculated for estimation of significant differences (P < 0.05) of the patients` age, sex, medical history or medication, and COVID-19 severity; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
aThe group ‘moderate’ consisted of the subgroups ‘mild’ and ‘hospitalized’, whereas the group ‘serious’ consisted of the subgroups ‘severe’ and ‘fatal’.
bCardiovascular system: e.g. myocardial infarction, coronary heart disease but not arterial hypertension.
cOnly angiotensin-converting-enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARBs) were analyzed.
Association of ACE2 and ACE genotypes with susceptibility for SARS-CoV-2 infection and severity of COVID-19
For ACE2 rs2285666, we found 77.4% GG, 13.5% GA, and 9.1% AA genotype carriers in SARS-CoV-2-positive patients, with a minor allele frequency (MAF) of 0.16 for the A-allele. Genotypes were compatible with HWE (P = 0.53). The genotypes in SARS-CoV-2-negative patients were distributed as follows: 70.4% GG, 13.8% GA, and 15.8% AA (Table 3). The A-allele had a MAF of 0.23. There was no deviation from HWE (P = 0.65). Interestingly, we noticed that the genotype distribution of our reference cohort fitted in the middle between SARS-CoV-2 infected and non-infected patients (MAF = 0.18; HWE P = 0.97). We observed 1.91-fold (95% CI, 1.13–3.24, P = 0.02) and 1.88-fold (95% CI, 1.12–3.16; P = 0.02) increased susceptibility for SARS-CoV-2 infection for ACE2 rs2285666 GG genotypes or G-allele carriers, respectively (Table 4).
Table 3 - Genotype distributions of
ACE2 and
ACE single-nucleotide polymorphisms in SARS-CoV-2-positive, SARS-CoV-2-negative patients and reference group
|
SARS-CoV-2-positive |
SARS-CoV-2-negative |
Reference group |
| GroupaSubgroup |
|
Moderate |
Serious |
All(N = 253) no. (%) |
All(N = 200) no. (%) |
| All(N = 297) no. (%) |
Mild(N = 30) no. (%) |
Hospitalized(N = 177) no. (%) |
Severe(N = 44) no. (%) |
Fatal(N = 46) no. (%) |
| ACE2 rs2285666 GG |
230 (77.4) |
19 (63.3) |
131 (74.0) |
39 (88.6) |
41 (89.1) |
178 (70.4) |
150 (75.0) |
| ACE2 rs2285666 GA |
40 (13.5) |
8 (26.7) |
26 (14.7) |
2 (4.6) |
4 (8.7) |
35 (13.8) |
29 (14.5) |
| ACE2 rs2285666 AA |
27 (9.1) |
3 (10.0) |
20 (11.3) |
3 (6.8) |
1 (2.2) |
40 (15.8) |
21 (10.5) |
| minor allele frequency |
0.16 |
0.23 |
0.19 |
0.09 |
0.07 |
0.23 |
0.18 |
| ACE rs1799752 DD |
105 (35.4) |
9 (30.0) |
65 (36.7) |
21 (47.7) |
10 (21.7) |
77 (30.4) |
55 (27.5) |
| ACE rs1799752 DI |
126 (42.4) |
12(40.0) |
74 (41.8) |
17 (38.6) |
23 (50.0) |
118 (46.6) |
95 (47.5) |
| ACE rs1799752 II |
66 (22.2) |
9 (30.0) |
38 (21.5) |
6 (13.6) |
13 (28.3) |
58 (22.9) |
50 (25.0) |
| minor allele frequency |
0.43 |
0.50 |
0.42 |
0.33 |
0.53 |
0.46 |
0.49 |
ECDC, European Centre of Disease Prevention and Control; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
aFor clinical outcome we defined four subgroups (‘mild’, ‘hospitalized’, ‘severe’, and ‘fatal’) to classify our patient cohort according to the criteria of the ECDC. Patients in the ‘mild’ group consisted of outpatients. The ‘hospitalized’ group encompassed patients, who stayed in the hospital as inpatients. The ‘severe’ group comprised of hospitalized patients admitted to an ICU and/or became dependent on mechanical ventilation. The ‘fatal’ group counted all cases of death during the hospital stay. The group ‘moderate’ consisted of the subgroups ‘mild’ and ‘hospitalized’, whereas the group ‘serious’ consisted of the subgroups ‘severe’ and ‘fatal’.
Table 4 - Association of
ACE2 rs228566 and
ACE rs1799752 with SARS-CoV-2 infection risk
| ACE2, rs2285666 G>A |
G vs. A |
GG + GA vs. AA |
GG vs. AA |
| OR (95% CI), P value |
1.57 (1.03–2.41), P = 0.04 |
1.88 (1.12–3.16), P = 0.02 |
1.91 (1.13–3.24), P = 0.02 |
| ACE, rs1799752 D/I |
D vs. I |
DD + DI vs. II |
DD vs. II |
| OR (95% CI), P value |
1.12 (0.80–1.57), P = 0.65 |
1.04 (0.70–1.55), P = 0.92 |
1.20 (0.76–1.90), P = 0.48 |
CI, confidence interval; D, deletion; I, insertion; OR, odds ratio; P, P value as calculated for estimation of significant differences (P < 0.05) of the patients’ genotypes and SARS-CoV-2 infection risk; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
We noted an almost linear decrease of the MAF of the A-allele from the ‘mild’ (23%), over the ‘hospitalized’ (19%) to the ‘severe’ (9%) and the ‘fatal’ (7%) group in SARS-CoV-2-positive patients. We found a three-fold increased risk for ACE2 rs2285666 GG genotype carriers to develop a ‘serious’, rather than a ‘moderate’ course of infection (OR: 3.04, 95% CI, 1.47–6.27, P = 0.002). We observed an almost three-fold increased fatality risk for ACE2 rs2285666 GG genotype carriers comparing patients from the ‘fatal’ group (N = 46, 15.5%) to all other SARS-CoV-2-positive patients (OR: 2.69, 95% CI, 1.02–7.11, P = 0.05). Remarkably, only one of the patients in the ‘fatal’ group carried the ACE2 AA genotype. Although limited by a small number of patients with ‘mild’ course of disease (N = 30), we found a trend for association with a two-fold increased risk for hospitalization (groups: ‘hospitalized’, ‘severe’ and ‘fatal’) for ACE2 rs2285666 GG genotype carriers (OR: 2.18, 95% CI, 0.98–4.85, P = 0.06).
A coding region variant in the gene ACE2 was only observed in three SARS-CoV-2-negative and in one SARS-CoV-2-positive patient (rs4646116, c.77A>G, p.K26R, MAF = 0.006).
In SARS-CoV-2-positive and SARS-CoV-2-negative patients, the ACE rs1799752 genotypes were equally distributed (Table 3). There was no deviation from HWE in SARS-CoV-2 negative patients (P = 0.32), but genotypes in the SARS-CoV-2-positives were deviant from HWE (P = 0.02). No significant association for the D/I variant with susceptibility for SARS-CoV-2 infection or course of COVID-19 was observed (Table 4).
A multivariable logistic regression showed that the ACE2 rs2285666 G-allele (OR: 3.75, 95% CI, 1.23–11.47, P = 0.02), male sex (OR: 2.75, 95% CI, 1.57–4.80, P = 0.00002), and cardiovascular disease (OR: 1.79, 95% CI, 1.06–3.05, P = 0.03) remained as independent significant predictors for ‘serious’ course of COVID-19.
Discussion
Influence of demographics, medical history, and medication on SARS-CoV-2 infection risk and COVID-19 severity
We found a similar prevalence of distribution of medical history and in-hospital mortality as observed in a recent large-scale observational study with 10.021 German hospitalized COVID-19 patients [2], suggesting our study cohort may be representative for hospitalized patients. We could not find associations between sex, age, medical history, or ACEi/ARBs medication and SARS-CoV-2 infection risk, which might be related to our highly selected cohort with SARS-CoV-2-negative patients, who presented at our hospital for other severe medical conditions than COVID-19. This may as well explain the higher prevalence of patients with cardiovascular diseases in the SARS-CoV-2-negative group. Considering only the SARS-CoV-2-positive patients, we could find a significantly higher risk for COVID-19 severity in male patients or those with cardiovascular diseases confirming the data from recent observational studies [4,30].
ACE2 rs2285666 GG genotype or G-allele and risk for SARS-CoV-2 infection
Currently, a number of studies analyze the impact of genetic host factors on SARS-CoV-2 infection risk or COVID-19 severity. Notably, one such genetic factor was unraveled in a genome-wide association study to be the blood group A, with an approximately 1.45-fold increased infection risk compared to other blood groups [31]. Other authors – mainly due to hypothetical reasons – have postulated that polymorphisms in the genes encoding for important components of the renin-angiotensin system, that is, ACE or ACE2 could play a role in infection risk. In a pilot study, Novelli et al. sequenced the whole exomes of 131 hospitalized COVID-19 patients and 1000 individuals of an Italian control group and evaluated the association of ACE2 variants with COVID-19 [32]. Although ACE2 rs2285666 was observed in this study (MAF = 0.18) the allele frequency did not differ between SARS-CoV-2-positives and the control group. The comparison to a control group with uncertain SARS-CoV-2 status may be a drawback of this study. In fact, we could show the MAF of ACE2 rs2285666 from healthy blood donors collected before the COVID-19 pandemic fitted in-between infected and non-infected patients. In the comparison of SARS-CoV-2-positive to SARS-CoV-2-negative patients; however, we determined an almost two-fold increased risk for SARS-CoV-2 infection in ACE2 rs2285666 GG carriers or G-allele carriers compared to AA genotypes. The mechanism behind this finding remains elusive or even counterintuitive. If the notion is correct that the A-allele is associated with increased ACE2 serum levels or even cellular ACE2 expression [13] one would expect – if ACE2 acts as the ‘receptor’ for SARS-CoV-2 entry – an increased risk for A-allele carriers. Presently, we have no explanation for our findings. It should; however, be noted that our cohort is not representative of the general population since it consisted of a highly selected cohort of both severely sick SARS-CoV-2-positive and -negative patients entering the emergency wards of highly specialized University hospitals. In addition, while in the SARS-CoV-2-positive group the infection was clearly present as determined by RT-PCR, SARS-CoV-2-negativity may be regarded as less reliable. We cannot exclude the viral load in these subjects was too low for the detection or whether they might have had different exposure to SARS-CoV-2.
Coding region variants in the gene ACE2 seem to play a negligible role, although they might be functional [33] since those variants were too rare to contribute to infection risk. Furthermore, ACE genotype distribution was not significantly different between SARS-CoV-2-positive and -negative individuals.
ACE and ACE2 polymorphisms and severity of COVID-19
We found no effect of ACE rs1799752 D/I polymorphism on the natural course of COVID-19. This stays in contrast to a recent Spanish study by Gomez et al. who reported an increased risk for an unfavorable COVID-19 outcome in ACE DD genotype carriers [24]. The reason for this discrepancy is unclear. Moreover, since genotyping errors can be excluded we have no explanation for the observation that ACE genotypes slightly violated HWE in the SARS-CoV-2-positive but not in the SARS-CoV-2-negative group or in healthy blood donors. This could hypothetically be attributed to an unrecognized selection bias in the first-mentioned group.
On the other hand, and again in contrast to the findings of Gomez et al., we found a significant association of the ACE2 rs2285666 G-allele with a three-fold increased risk for an unfavorable COVID-19 course. Interestingly, the frequency of the A-allele decreased almost linearly from 23% in ‘mild’ disease to only 7% in the ‘fatal’ group. Despite the limited sample size, we found a significant association between COVID-19 fatality risk and GG genotype as well.
Multivariable logistic regression analysis confirmed the G-allele as an independent risk factor for a ‘serious’ course of COVID-19 besides the known risk factors male gender and cardiovascular disease.
It has been postulated that an ACE/ACE2 imbalance may play a central role in COVID-19 [34,35]. In this scenario, SARS-CoV-2 infection decreases the activity of ACE2 which typically counteracts the pro-inflammatory and -fibrotic effects of Ang II by converting it to Ang 1–7. If one accepts this theory, our findings suggesting a ‘protective’ role of the ACE2 rs2285666 A-allele would make sense: If A-allele carriers actually produce more ACE2 than those with GG genotypes, A-allele carriers could be protected at least partially against the ACE/ACE2 imbalance and potentially better deal with the detrimental effects of increased Ang II levels, which could cause severe lung and heart injury [35,36].
A word of caution is nevertheless necessary: our Caucasian study population was limited and highly selected. Therefore, our findings cannot be transferred to the general population or populations with different ethnicities. Before universally being acceptable, our findings and hypothesis require a confirmation from independent investigations.
In summary, our report appears to be the first showing that a common ACE2 polymorphism impacts the risk for SARS-CoV-2 infection and the course of COVID-19 independently from previously described risk factors.
Acknowledgements
We kindly thank Iris Manthey, Grit Müller and Stephanie Büscher for technical support (Institute of Pharmacogenetics). We thank Dr. Katharina Jockers, Tanja Lehmann and Heike Loewendick for their support regarding patient samples from the WBE (University Hospital Essen), Jennifer Wipperfürth for her help with RWTH cBMB samples (University Hospital Aachen) and Dr. Lothar Volbracht, Dr. Marc Wichert, Martina Wachsmann and Petra Kasper for their support with the samples from the central laboratory (University Hospital Essen).
Conflicts of interest
This work was supported by a grant (to Dr. Birte Möhlendick) from the Stiftung Universitätsmedizin Essen of the Medical Faculty Essen. The funder of the study had no role in study design, data collection, data analysis, data interpretation, writing of the report, or in the decision of submitting the article for publication. For the remaining authors, there are no conflicts of interest.
References
1. Wiersinga WJ, Rhodes A, Cheng AC, Peacock SJ, Prescott HC. Pathophysiology, transmission, diagnosis, and treatment of coronavirus disease 2019 (COVID-19): a review. JAMA 2020; 324:782–793.
2. Karagiannidis C, Mostert C, Hentschker C, Voshaar T, Malzahn J, Schillinger G, et al. Case characteristics, resource use, and outcomes of 10 021 patients with COVID-19 admitted to 920 German hospitals: an observational study. Lancet Respir Med 2020; 8:853–862.
3. The Johns Hopkins Coronavirus Resource Center. COVID-19 DATA IN MOTION: MONDAY, APRIL 26, 2021.
coronavirus.jhu.edu. [Accessed 25 January 2021].
4. Ko JY, Danielson ML, Town M, Derado G, Greenlund KJ, Daily Kirley P, et al. Risk factors for COVID-19-associated hospitalization: COVID-19-associated hospitalization surveillance network and behavioral risk factor surveillance system. Clin Infect Dis 2020:ciaa1419. doi: 10.1093/cid/ciaa1419
5. Hoffmann M, Kleine-Weber H, Schroeder S, Krüger N, Herrler T, Erichsen S, et al. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell 2020; 181:271–280.e8.
6. Li MY, Li L, Zhang Y, Wang XS. Expression of the SARS-CoV-2 cell receptor gene ACE2 in a wide variety of human tissues. Infect Dis Poverty 2020; 9:45.
7. Aguiar JA, Tremblay BJ, Mansfield MJ, Woody O, Lobb B, Banerjee A, et al. Gene expression and in situ protein profiling of candidate SARS-CoV-2 receptors in human airway epithelial cells and lung tissue. Eur Respir J 2020; 56:2001123.
8. Tikellis C, Thomas MC. Angiotensin-converting enzyme 2 (ACE2) Is a key modulator of the renin angiotensin system in health and disease. Int J Pept 2012; 2012:256294.
9. Darbani B. The expression and polymorphism of entry machinery for COVID-19 in human: juxtaposing population groups, gender, and different tissues. Int J Environ Res Public Health 2020; 17:E3433.
10. Devaux CA, Rolain JM, Raoult D. ACE2 receptor polymorphism: susceptibility to SARS-CoV-2, hypertension, multi-organ failure, and COVID-19 disease outcome. J Microbiol Immunol Infect 2020; 53:425–435.
11. Gemmati D, Bramanti B, Serino ML, Secchiero P, Zauli G, Tisato V. COVID-19 and individual genetic susceptibility/receptivity: role of ACE1/ACE2 genes, immunity, inflammation and coagulation. Might the double X-chromosome in females be protective against SARS-CoV-2 compared to the single X-chromosome in males? Int J Mol Sci 2020; 21:E3474.
12. Hou Y, Zhao J, Martin W, Kallianpur A, Chung MK, Jehi L, et al. New insights into genetic susceptibility of COVID-19: an ACE2 and TMPRSS2 polymorphism analysis. BMC Med 2020; 18:216.
13. Wu Y-H, Li J-Y, Wang C, Zhang L-M, Qiao H. The ACE2 G8790A polymorphism: involvement in type 2 diabetes mellitus combined with cerebral stroke. J Clin Lab Anal 2017; 31:e22033.
14. Pinheiro DS, Santos RS, Jardim PCBV, Silva EG, Reis AAS, Pedrino GR, Ulhoa CJ. The combination of ACE I/D and ACE2 G8790A polymorphisms revels susceptibility to hypertension: a genetic association study in Brazilian patients. PLoS One 2019; 14:e0221248.
15. Yang M, Zhao J, Xing L, Shi L. The association between angiotensin-converting enzyme 2 polymorphisms and essential hypertension risk: a meta-analysis involving 14,122 patients. J Renin Angiotensin Aldosterone Syst 2015; 16:1240–1244.
16. Rigat B, Hubert C, Alhenc-Gelas F, Cambien F, Corvol P, Soubrier F. An insertion/deletion polymorphism in the angiotensin I-converting enzyme gene accounting for half the variance of serum enzyme levels. J Clin Invest 1990; 86:1343–1346.
17. Schunkert H. Polymorphism of the angiotensin-converting enzyme gene and cardiovascular disease. J Mol Med (Berl) 1997; 75:867–875.
18. Cambien F. The angiotensin-converting enzyme (ACE) genetic polymorphism: its relationship with plasma ACE level and myocardial infarction. Clin Genet 1994; 46:94–101.
19. Itoyama S, Keicho N, Quy T, Phi NC, Long HT, Ha LD, et al. ACE1 polymorphism and progression of SARS. Biochem Biophys Res Commun 2004; 323:1124–1129.
20. Jerng JS, Yu CJ, Wang HC, Chen KY, Cheng SL, Yang PC. Polymorphism of the angiotensin-converting enzyme gene affects the outcome of acute respiratory distress syndrome. Crit Care Med 2006; 34:1001–1006.
21. Adamzik M, Frey U, Sixt S, Knemeyer L, Beiderlinden M, Peters J, Siffert W. ACE I/D but not AGT (-6)A/G polymorphism is a risk factor for mortality in ARDS. Eur Respir J 2007; 29:482–488.
22. Marshall RP, Webb S, Bellingan GJ, Montgomery HE, Chaudhari B, McAnulty RJ, et al. Angiotensin converting enzyme insertion/deletion polymorphism is associated with susceptibility and outcome in acute respiratory distress syndrome. Am J Respir Crit Care Med 2002; 166:646–650.
23. Yamamoto N, Ariumi Y, Nishida N, Yamamoto R, Bauer G, Gojobori T, et al. SARS-CoV-2 infections and COVID-19 mortalities strongly correlate with ACE1 I/D genotype. Gene 2020; 758:144944.
24. Gómez J, Albaiceta GM, García-Clemente M, López-Larrea C, Amado-Rodríguez L, Lopez-Alonso I, et al. Angiotensin-converting enzymes (ACE, ACE2) gene variants and COVID-19 outcome. Gene 2020; 762:145102.
25. Fistera D, Risse J, Manegold R, Pabst D, Konik M, Dolff S, et al. COVID-19 triage: who is an inpatient? The Essen triage model. Dtsch Med Wochenschr 2020; 145:e87–e92.
26. Bernheim A, Mei X, Huang M, Yang Y, Fayad ZA, Zhang N, et al. Chest CT findings in coronavirus disease-19 (COVID-19): relationship to duration of infection. Radiology 2020; 295:200463.
27. Fang L, Karakiulakis G, Roth M. Antihypertensive drugs and risk of COVID-19? – Authors’ reply. Lancet Respir Med 2020; 8:e32–e33.
28. European Center of Disease Prevention and Control. ECDC surveillance report.
covid19-surveillance-report.ecdc.europa.eu. [Accessed 15 January 2021].
29. Backenroth D, Carmi S. A test for deviations from expected genotype frequencies on the X chromosome for sex-biased admixed populations. Heredity (Edinb) 2019; 123:470–478.
30. Yang J, Zheng Y, Gou X, Pu K, Chen Z, Guo Q, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. Int J Infect Dis 2020; 94:91–95.
31. Ellinghaus D, Degenhardt F, Bujanda L, Buti M, Albillos A, Invernizzi P, et al. Genomewide Association Study of Severe Covid-19 with respiratory failure. N Engl J Med 2020; 383:1522–1534.
32. Novelli A, Biancolella M, Borgiani P, Cocciadiferro D, Colona VL, D’Apice MR, et al. Analysis of ACE2 genetic variants in 131 Italian SARS-CoV-2-positive patients. Hum Genomics 2020; 14:29.
33. Calcagnile M, Forgez P, Iannelli A, Bucci C, Alifano M, Alifano P. Molecular docking simulation reveals ACE2 polymorphisms that may increase the affinity of ACE2 with the SARS-CoV-2 spike protein. Biochimie 2021; 180:143–148.
34. Sriram K, Insel PA. A hypothesis for pathobiology and treatment of COVID-19: the centrality of ACE1/ACE2 imbalance. Br J Pharmacol 2020; 177:4825–4844.
35. Lumbers ER, Delforce SJ, Pringle KG, Smith GR. The lung, the heart, the novel coronavirus, and the renin-angiotensin system; the need for clinical trials. Front Med (Lausanne) 2020; 7:248.
36. Kuba K, Imai Y, Rao S, Gao H, Guo F, Guan B, et al. A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus-induced lung injury. Nat Med 2005; 11:875–879.
