Keypoint.
The risk of contracting SARS‐CoV‐2 was slightly higher for individuals with blood group A versus O but did not differ between blood groups A1 versus A2. With much higher epitope density of blood group A1, this suggests that the A epitope itself does not facilitate viral entry.
Information on the impact of ABO blood group (BG) on SARS‐CoV‐2 infections is conflicting [1, 2, 3, 4]. To identify risk factors for severe COVID‐19 courses, we performed a cross‐sectional study in volunteers between 18 and 61 years of age registered with DKMS for stem cell donation approved by the institutional review board of the Technische Universität Dresden. All participants provided explicit consent that COVID‐19‐specific data were linked to genotype data in the donor registry file. Patient‐reported data on swabs, risk factors, symptoms and treatment of COVID‐19 were collected with a health questionnaire and linked to existing data on ABO and Rhesus [5]. ABO genotype data were grouped into ABO BG phenotypes by assuming dominant expression for A1 over A2 and BG A or B over BG O. Severe respiratory tract infections (RTIs) were defined by the combination of at least fever and cough, dyspnoea and cough, dyspnoea and fever, or dyspnoea and myalgia. This group included patients with respiratory hospitalization, defined by inpatient care with supplemental oxygen or mechanical ventilation or hospitalization for dyspnoea or cough. We fitted multivariable logistic regression models for the risk of contracting SARS‐CoV‐2, risk of severe respiratory infection and risk of hospitalization. All models were adjusted for age, sex, BMI, diabetes mellitus, arterial hypertension and smoking status. Age, BMI and month of positive test were modelled as categorical variables.
Amongst 125 125 participants tested for SARS‐CoV‐2 with ABO genotypes available (102 426 at allele‐level resolution), 6257 tested virus‐positive. A patient flow chart and characteristics are shown in Figure S1 and Table S1. Overall, 11.9% of SARS‐CoV‐2‐positive participants reported asymptomatic courses, 59.5% reported mild/moderate symptoms, 25% reported severe respiratory tract infections, and 3.6% reported hospitalization for respiratory tract infections.
We found that BG A was a risk factor for contracting SARS‐CoV‐2 compared with BG O (adjusted OR 1.15; 95% CI 1.08–1.22, P < 0.001) (Figure S2, Panels A + C). Based on similar observations in previous studies, the hypothesis had been raised that A epitopes facilitate virus entry [2, 3, 4]. Individuals with BG A1 have a higher glycosyltransferase activity and thus expose more than fourfold higher numbers of A epitopes compared with individuals with BG A2 [6]. Therefore, we tested whether individuals with A1 phenotype have a greater risk of infection compared with individuals with A2 phenotype. Participants with A1 and A2 phenotypes, however, showed comparable rates of infections (adjusted OR 1.03; 95% CI 0.93–1.15, P = 0.58) (Figure S2). Our data therefore argue against the hypothesis that A epitopes facilitate SARS‐CoV‐2 entry into cells. Participants with BG AB (adjusted OR 1.19; 95% CI 1.06–1.35, P = 0.004) had significantly more infections as well, but no difference was found for participants with BG B phenotype compared with BG O. Exploratory analyses of ABO genotypes showed that participants who were homozygous for BG B had the lowest odds ratio and participants who were homozygous for A2 had the highest odds ratio for positive tests (Table 1 and Table S2).
Table 1.
Impact of ABO genotypes and phenotypes
| Genotype | Contracting SARS‐CoV‐2 | Evaluable a infections | Severe respiratory tract infections | Respiratory hospitalizations | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Tests (%) | Cases | OR (95% CI) | P | N | N | OR (95% CI) | P | N | OR (95% CI) | P | |||
| O + O | 40 975 (40.0) | 1916 | 1 | 1653 | 398 | 1 | 55 | 1 | |||||
| B + O | 10 997 (10.7) | 533 | 1.05 (0.94–1.16) | 0.392 | 443 | 138 | 1.45 (1.14–1.83) | 0.002 | 30 | 2.16 (1.36–3.45) | 0.001 | ||
| B + B | 869 (0.8) | 37 | 0.95 (0.68–1.34) | 0.784 | 33 | 6 | 0.71 (0.29–1.77) | 0.467 | 1 | 0.79 (0.10–6.07) | 0.817 | ||
| B + A1 | 4072 (4.0) | 215 | 1.17 (1.01–1.36) | 0.042 | 186 | 53 | 1.29 (0.92–1.83) | 0.140 | 6 | 1.01 (0.42–2.39) | 0.987 | ||
| B + A2 | 1298 (1.3) | 70 | 1.29 (1.00–1.66) | 0.052 | 59 | 17 | 1.30 (0.73–2.33) | 0.377 | 0 | ‐ | – | ||
| A1 + O | 27 251 (26.6) | 1462 | 1.15 (1.07–1.23) | <.001 | 1229 | 316 | 1.09 (0.92–1.30) | 0.311 | 36 | 0.89 (0.58–1.37) | 0.589 | ||
| A1 + A1 | 4612 (4.5) | 214 | 0.99 (0.85–1.15) | 0.860 | 187 | 54 | 1.26 (0.90–1.77) | 0.180 | 5 | 0.78 (0.31–1.99) | 0.604 | ||
| A1 + A2 | 3031 (3.0) | 169 | 1.22 (1.03–1.44) | 0.023 | 150 | 35 | 0.90 (0.60–1.34) | 0.611 | 5 | 0.99 (0.39–2.55) | 0.990 | ||
| A2 + O | 8714 (8.5) | 470 | 1.16 (1.04–1.29) | 0.008 | 407 | 112 | 1.23 (0.96–1.58) | 0.101 | 12 | 0.92 (0.48–1.74) | 0.785 | ||
| A2 + A2 | 523 (0.5) | 30 | 1.32 (0.90–1.95) | 0.157 | 28 | 10 | 1.93 (0.87–4.27) | 0.107 | 0 | ‐ | ‐ | ||
CI, confidence interval; N, number of cases; OR, odds ratio; P, P value.
Odds ratios were calculated in a multivariable logistic regression model containing information on age, sex, BMI, diabetes mellitus, arterial hypertension, smoking status and month of testing.
Infections reported for the months January to July, excluding August and September.
Genetic variance in ABO genes has been associated with the risk for venous thromboembolism, stroke, coronary artery disease and acute respiratory distress syndrome regardless of COVID‐19 [7, 8, 9]. Glycosylation patterns may impact on the clearance of plasma proteins (e.g. of the von Willebrand factor) and thus impact on end‐stage coagulation and thrombosis [10]. In our study, however, BG A did not show an impact on COVID‐19 severity. Blood group B was associated with a higher risk of severe RTI (OR 1.24; 95% CI 1.01–1.53, P = 0.038) and respiratory hospitalizations (OR 1.78; 95% CI 1.18–2.68, P = 0.006) compared with BG O (Figure S2, Panels B + D). Exploratory analyses of the genotype compositions of BG B, however, did not reveal a pattern suggesting causality (Table 1), and BG B has not been described consistently as risk factor for severe COVID‐19 courses [2, 4]. Therefore, we interpret this association as incidental finding. Rhesus BG did not have an impact on any clinical end‐point (Table S2).
In conclusion, we confirm that individuals with BG A have a greater risk of infection compared with individuals with BG O. The observation of comparable risks of contracting SARS‐CoV‐2 amongst individuals with A1 versus A2 together with the knowledge of a more than fourfold higher epitope density for A1 versus A2 suggests that the A epitope itself, for example by modifying the ACE protein, does not facilitate viral entry. This leaves alternative hypotheses of absorbing anti‐A antibodies or genetic linkage as possible explanations for the higher risk of contracting SARS‐CoV‐2 for individuals with BG A compared with BG O. In line with others, we did not find a consistent impact of ABO BG on the severity of COVID‐19.
Conflict of interest statement
All authors have completed the Unified Competing Interest form (available on request from the corresponding author) and declare no support from any organization for the submitted work, no financial relationships with any organizations that might have an interest in the submitted work in the previous three years and no other relationships or activities that could appear to have influenced the submitted work.
Funding statement
DKMS initiated and conducted this study. The Federal Ministry of Education and Research (BMBF) supported the study by a research grant (COVID‐19 call (202), reference number 01KI20177).
Transparency declaration
The corresponding author (JS) declares that this manuscript is an honest, accurate and transparent account of the study being reported. No important aspects of the study have been omitted, and there were no discrepancies from the study as planned and registered.
Author contribution
Johannes Schetelig: Conceptualization (lead); Data curation (lead); Formal analysis (lead); Funding acquisition (lead); Investigation (lead); Methodology (lead); Project administration (lead); Supervision (lead); Writing‐original draft (lead). Henning Baldauf: Conceptualization (equal); Formal analysis (lead); Investigation (equal); Methodology (equal); Resources (equal); Validation (equal); Writing‐review & editing (equal). Sarah Wendler: Investigation (equal); Resources (equal); Writing‐review & editing (equal). Falk Heidenreich: Investigation (equal); Methodology (equal); Resources (equal); Writing‐review & editing (equal). Ruben Real: Investigation (equal); Methodology (equal); Resources (equal); Writing‐review & editing (equal). Martin Kolditz: Data curation (equal); Writing‐review & editing (equal). Andrea Rosner: Data curation (equal); Writing‐review & editing (equal). Alexander Dalpke: Data curation (equal); Writing‐review & editing (equal). Katja De With: Data curation (equal); Writing‐review & editing (equal). Vinzenz Lange: Data curation (equal); Methodology (equal); Writing‐review & editing (equal). Jan Markert: Methodology (equal); Resources (equal); Validation (equal); Writing‐review & editing (equal). Ralf Barth: Conceptualization (equal); Methodology (equal); Resources (equal); Software (equal); Validation (equal); Writing‐review & editing (equal). Carolin Bunzel: Conceptualization (equal); Methodology (equal); Resources (equal); Writing‐review & editing (equal). Dennis Endert: Conceptualization (equal); Methodology (equal); Resources (equal); Validation (equal); Writing‐review & editing (equal). Jan A. Hofmann: Conceptualization (equal); Methodology (equal); Resources (equal); Validation (equal); Writing‐review & editing (equal). Jürgen Sauter: Conceptualization (equal); Formal analysis (equal); Methodology (equal); Resources (equal); Validation (equal); Writing‐review & editing (equal). Stefanie N. Bernas: Conceptualization (equal); Investigation (equal); Methodology (equal); Project administration (supporting); Resources (equal); Validation (equal); Writing‐review & editing (equal). Alexander H. Schmidt: Conceptualization (equal); Data curation (equal); Methodology (equal); Project administration (lead); Supervision (lead); Writing‐review & editing (equal).
Data availability statement
De‐identified analysis of data of this study may be shared under the following conditions. Applicants have to guarantee full compliance with the European General Data Protection Regulation. Researchers have to submit a study protocol, which has been approved by their local institutional review board together with a curriculum vitae. Project proposals will be reviewed formally for compliance, feasibility, scientific merit and potential clinical impact. Data will only be shared after a mutually agreed data transfer agreement had been signed.
Supporting information
Figure S1. Flow chart.
Figure S2. Rates of positive SARS‐CoV‐2 tests and severe respiratory tract infection by ABO blood group genotype and phenotype.
Table S1. Characteristics of SARS‐CoV‐2 positive and negative participants.
Table S2. Risk of infection, severe respiratory tract infection, and respiratory hospitalization by ABO genotype including rare variants and Rhesus genotype.
Schetelig J, Baldauf H, Wendler S, Heidenreich F, Real R, Kolditz M, Rosner A, Dalpke A, de With K, Lange V, Markert J, Barth R, Bunzel C, Endert D, Hofmann JA, Sauter J, Bernas SN, Schmidt AH (1From the DKMS, Stem Cell Donor Registry, Clinical Trials Unit, Dresden, Germany). 2Department of Internal Medicine I, University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany). 3Division of Pulmonology, Department of Internal Medicine I, University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany). 4Division of Transfusion Medicine, Department of Internal Medicine I, University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany). 5Institute of Medical Microbiology and Hygiene, Institute of Virology, TU Dresden, Dresden, Germany). 6Division of Infectious Diseases, TU Dresden, Dresden, Germany). 7DKMS Life Science Lab, Stem Cell Donor Registry, Dresden, Germany). 8DKMS, Tübingen, Germany). Blood group A epitopes do not facilitate entry of SARS‐CoV‐2 (Letter to the Editor). J Intern Med. 2021;290:223–226. 10.1111/joim.13256
References
- 1. Zhang J, Pellicori P, Schutte R, Cleland JG. The association between blood groups and COVID‐19 infection: a study from the UK Biobank. J Int Med 2021. [DOI] [PubMed] [Google Scholar]
- 2. 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(16): 1522–1534. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Barnkob MB, Pottegård A, Støvring H, Haunstrup TM, Homburg K, Larsen R, et al. Reduced prevalence of SARS‐CoV‐2 infection in ABO blood group O. Blood Adv 2020; 4: 4990–3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Golinelli D, Boetto E, Maietti E, Fantini MP. The association between ABO blood group and SARS‐CoV‐2 infection: a meta‐analysis. PLoS One 2020; 15: e0239508. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Lang K, Wagner I, Schöne B, Schöfl G, Birkner K, Hofmann JA, et al. ABO allele‐level frequency estimation based on population‐scale genotyping by next generation sequencing. BMC Genom 2016; 20(17): 374. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Cooling L. Technical manual 18th Edition. In: Fung MK, Grossmann BJ, Hillyer CD, Westhoff CM, eds. Technical manual. Bethesda, MD: American Association of Blood Banks (ABB), 2014. [Google Scholar]
- 7. Dentali F, Sironi AP, Ageno W, Turato S, Bonfanti C, Frattini F, et al. Non‐O blood type is the commonest genetic risk factor for VTE: results from a meta‐analysis of the literature. Semin Thromb Hemost. 2012; 38(5): 535–48. [DOI] [PubMed] [Google Scholar]
- 8. Dichgans M, Malik R, König IR, Rosand J, Clarke R, Gretarsdottir S, et al. Shared genetic susceptibility to ischemic stroke and coronary artery disease: a genome‐wide analysis of common variants. Stroke 2014; 45(1): 24–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Reilly JP, Meyer NJ, Shashaty MG, Anderson BJ, Ittner C, Dunn TG, et al. The ABO Histo‐Blood Group, endothelial activation, and acute respiratory distress syndrome risk in critical illness. J Clin Invest 2020; 131: e139700. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Suhre K, Arnold M, Bhagwat AM, Cotton RJ, Engelke R, Raffler J, et al. Connecting genetic risk to disease end points through the human blood plasma proteome. Nat Commun. 2017; 27(8): 14357. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1. Flow chart.
Figure S2. Rates of positive SARS‐CoV‐2 tests and severe respiratory tract infection by ABO blood group genotype and phenotype.
Table S1. Characteristics of SARS‐CoV‐2 positive and negative participants.
Table S2. Risk of infection, severe respiratory tract infection, and respiratory hospitalization by ABO genotype including rare variants and Rhesus genotype.
Data Availability Statement
De‐identified analysis of data of this study may be shared under the following conditions. Applicants have to guarantee full compliance with the European General Data Protection Regulation. Researchers have to submit a study protocol, which has been approved by their local institutional review board together with a curriculum vitae. Project proposals will be reviewed formally for compliance, feasibility, scientific merit and potential clinical impact. Data will only be shared after a mutually agreed data transfer agreement had been signed.