Abstract
Objectives
To determine whether blood group influences development of cerebral venous thrombosis (CVT) after administration of the coronavirus disease 2019 (COVID-19) AstraZeneca ChAdOx1-S vaccine.
Design
A case–control study. Univariate and multivariate logistic regression was used to determine the association between blood type and COVID-19 vaccination status.
Setting
Vaccinated and unvaccinated patients recruited from the international Bio-Repository to Establish the Aetiology of Sinovenous Thrombosis study and the Cerebral Venous Sinus Thrombosis With Thrombocytopenia Syndrome Study Group.
Participants
All patients were of European descent and age and sex matched. Cases (n = 82) were patients ≥18 years old who suffered a CVT within 28 days of a first dose of ChAdOx1-S vaccine. Controls (n = 441) were unvaccinated CVT patients ≥18 years old. All patients were of European descent.
Main outcome measures
Frequency of blood type and ABO allele distribution by vaccination status.
Results
Blood group O was found to be more prevalent among CVT patients with vaccine-induced thrombotic thrombocytopenia (VITT-CVT) after ChAdOx1-S vaccination compared with unvaccinated CVT cases (43% vs. 17%, respectively, p < 0.001). Blood group A was less prevalent, though still high, in the vaccinated group compared with the unvaccinated group (47% vs. 71%, respectively, p < 0.001). No significant differences were observed in the VITT-CVT non-ChAdOx1-S vaccine group and unvaccinated pre-COVID-19 CVT group for blood group.
Conclusions
Blood group O is more prevalent among patients with VITT-CVT after ChAdOx1-S vaccination compared with unvaccinated cases, independent of well-established CVT risk factors. A larger dataset may be able to determine whether those of blood groups B and/or AB may be safely vaccinated with the low cost, readily available and easily transported ChAdOx1-S rather than adopting a complete ban.
Keywords: ChAdOx1-S COVID-19 vaccine, Oxford-AstraZeneca, cerebral venous thrombosis, blood group
Introduction
Cerebral venous thrombosis (CVT) has been associated with the ChAdOx1-S (Oxford-AstraZeneca) coronavirus disease 2019 (COVID-19) vaccine,1–3 leading many countries to limit its use in younger individuals, despite its high efficacy, cost-effectiveness and ease of handling. Identifying individuals most likely at risk of this rare adverse event would allow a more targeted restriction of this inexpensive vaccine. After administration of ChAdOx1-S, CVT has been reported within 28 days of vaccination and associated with a distinct clinical profile (which includes thrombosis with thrombocytopenia syndrome) and high mortality rate. 4 Most of these CVT cases after vector-based COVID-19 vaccination are due to vaccine-induced thrombotic thrombocytopenia (VITT), 5 often with a poorer outcome. 6
Recent studies have examined the relationship of blood group with COVID-19. 7 A genome-wide association study (GWAS) of COVID-19 patients showed that individuals with blood group A had a higher risk of severe disease (odds ratio [OR] = 1.45), while individuals with B or O blood groups were less represented among COVID-19 patients. 8 In addition, critically ill COVID-19 patients with blood groups A and AB were more likely to require mechanical ventilation and prolonged intensive care compared with patients with blood groups B or O. 8 We reported the first GWAS in patients with CVT 9 finding that non-O blood group is associated with a 3-fold (p = 10−16) increase of CVT compared with individuals with blood type O.
With increasing evidence that onset and outcome after CVT is associated with blood group, we sought to determine whether blood group influences development of CVT after AstraZeneca ChAdOx1-S vaccination.
Methods
All 82 patients who suffered their first VITT-CVT (47 of which were defined using the international classification of Definite or Probable) 5 within 28 days of a first dose of ChAdOx1-S vaccine from the Cerebral Venous Sinus Thrombosis with Thrombocytopenia Syndrome Study Group, 4 and 441 pre-COVID-19 unvaccinated patients with CVT from the Bio-Repository to Establish the Aetiology of Sinovenous Thrombosis (BEAST) study were recruited. The BEAST consortium, located in nine research centres (Belgium, Finland, Italy, the Netherlands, Portugal, Sweden, France, UK and USA), was established to analyse the epidemiology and genetics of CVT.9,10 Diagnoses were imaging confirmed using computed tomography/venography, magnetic resonance or conventional angiogram. Both cohorts are described in detail elsewhere4,9,10 but briefly, all patients were of European descent and age and sex matched (Table 1).
Table 1.
Characteristics of vaccinated and unvaccinated patients with CVT.
|
Vaccinated (n = 82) |
Unvaccinated (n = 441) | p-Value | |
|---|---|---|---|
| Age in years at CVT (SD) | 47.8 (15.1) | 47.4 (15.4) | 0.83 |
| Women (n/%) | 57 (69.5) | 305 (69.2) | 0.99 |
| COVID-19 vaccination (n/%) | |||
| First (1st) | |||
| ChAdOx1-S vaccine | 59 (72.0) | 0 (0) | – |
| Non-ChAdOx1-S vaccine a | 23 (28.0) | 0 (0) | – |
| Second (2nd) | |||
| None | 67 (81.7) | 0 (0) | – |
| ChAdOx1-S vaccine | 2 (2.4) | 0 (0) | – |
| Non-ChAdOx1-S vaccine b | 13 (15.9) | 0 (0) | – |
| Third (3rd) | |||
| None | 81 (99) | 0 (0) | – |
| ChAdOx1-S vaccine | 0 (0) | 0 (0) | – |
| Non-ChAdOx1-S vaccine c | 1 (1) | 0 (0) | – |
| VITT (n/%) for ChAdOx1-S vaccine | |||
| Definite | 38 (64.4) | 0 (0) | – |
| Probable | 9 (15.3) | 0 (0) | – |
| Possible | 5 (8.5) | 0 (0) | – |
| Unlikely | 7 (11.9) | 0 (0) | – |
| VITT (n/%) for Non-ChAdOx1-S vaccine | |||
| Definite | 4 (17.4) | 0 (0) | – |
| Probable | 0 (0) | 0 (0) | – |
| Possible | 3 (13.0) | 0 (0) | – |
| Unlikely | 16 (69.6) | 0 (0) | – |
n: sample size; SD: standard deviation; VITT: vaccine-induced immune thrombocytopenia and thrombosis.
a Pfizer/BioNTech (12), Moderna (2), Johnson & Johnson (5), Sinovac (1), Other (3). b Pfizer/BioNTech (8), Moderna (2), Johnson & Johnson (0), Sinovac (0), Other (3). c Pfizer/BioNTech (1), Moderna (0), Johnson & Johnson (0), Sinovac (0), Other (0)
Vaccinated patients were free of these CVT risk factors: anticoagulant, antiphospholipid antibodies, Protein-C deficiency, Protein-S deficiency, antithrombin deficiency, Factor-V Leiden and factor VIII (FVIII), except one patient with prothrombin G20210A and one patient with lupus anticoagulant. Unvaccinated patients with CVT from the BEAST study were also free of those risk factors.
All recruits were aged ≥18 years with patient or relative informed written consent. Age was documented at time of CVT diagnosis.
Both studies received all ethical and consent standards set by local Institutional Review Boards at each of the participating sites.
Statistical methods
Matching of vaccinated and unvaccinated patients was performed using the frequency matching approach. First, we calculated the distribution (frequency table) of the matching characteristics among the vaccinated patients. Characteristics were categorised as follows: age: ≤33 years, >33 and ≤43 years, >43 and ≤51 years, >51 and ≤62 years, >62 years and gender (men, women). For each category of the matching characteristic, we selected an unvaccinated patient from the BEAST study. If the unvaccinated patients matched on the age and sex category, the matching was considered successful and removed from the unvaccinated patient list. An iterative approach was applied if matching failed. Sample size was thus maximised using this iterative strategy until all categories were matched.
Descriptive statistics summarised data using mean with standard deviation or median with interquartile range for continuous variables, and proportion for categorical variables. For single factor analysis, chi-square (or Fisher’s exact test, where appropriate) was used for categorical variables, and independent t-test (or Mann-Whitney U test, where appropriate) for continuous variables. Univariate and multivariate logistic regression estimated the associations of covariates (confounding variables) with COVID-19 vaccination status. The reliability (goodness of fit) of each model was quantified using the Hosmer and Lemeshow test. 11 Models were evaluated using Akaike's Information Criterion and the likelihood ratio chi-square test. 12 ABO alleles distribution for vaccinated patients and unvaccinated patients was estimated by the Expectation-Maximization-algorithm from blood type distribution.13,14 A permutation test assessed significant differences in ABO allele frequencies between vaccinated and unvaccinated patients. Rather than using a correction for multiple testing at global significance level, the statistical significance threshold for individual association testing was established at P<0.01. 15
Results
A total of 82 CVT vaccinated patients and 441 non-vaccinated patients of European descent were enrolled in the study to assess whether certain ABO blood type group was more likely to be associated with development of CVT after the COVID-19 ChAdOx1-S vaccination. Of those, 47 patients were defined using the international classification for CVT post vaccination of Definite or Probable within 28 days of a first dose of ChAdOx1-S. The demographic characteristics of CVT individuals with COVID-19 vaccine and non-COVID-19 vaccine are presented in Table 1. Patients were appropriately age and sex matched. Importantly, there were no differences between VITT-CVT non-ChAdOx1-S vaccine group and unvaccinated pre-COVID-19 CVT group for well-established risk factors for CVT including lupus anticoagulant, antiphospholipid antibodies, Protein-C deficiency, Protein-S deficiency, antithrombin deficiency, factor VIII (FVIII), Factor-V Leiden and prothrombin G20210A.
Blood type distribution of VITT-CVT (Definite or Probable) vaccinated and unvaccinated groups are presented in Table 2. Blood group O was more prevalent in the VITT-CVT group than in the unvaccinated pre-COVID-19 CVT group (43% vs. 17%, respectively, p < 0.001, Figure 1). Blood group A was less prevalent, though still high, in the vaccinated compared with the unvaccinated group (47% vs. 71%, respectively, p < 0.001), as described in our previous GWAS. 9 In an unadjusted model, the presence of blood group O was three-times more likely in the VITT-CVT Definite or Probable vaccinated group (OR = 3.83, 95% confidence interval (CI): 1.98–7.41, p < 0.001) compared with those with blood group A.
Table 2.
Blood type distribution between the vaccinated group (analysis restricted to VITT-CVT defined as Definite or Probable 5 ) and the unvaccinated group.
|
Vaccinated(n = 47) |
Unvaccinated (n = 441) |
Overallp-Value |
|
|---|---|---|---|
| Blood type (n/%) for ChAdOx1-S vaccine a | |||
| O | 20 (42.6) | 74 (16.8) | <0.001 |
| A | 22 (46.8) | 312 (70.7) | |
| B | 2 (4.3) | 39 (8.8) | |
| AB | 3 (6.4) | 16 (3.6) | |
n: sample size.
Analysis includes only VITT defined as Definite or Probable. 5
Figure 1.
Blood type distribution between vaccinated group for ChAdOx1-S vaccine (analysis restricted to VITT-CVT defined as Definite or Probable5) and unvaccinated group.
For the non-ChAdOx1-S vaccine group and unvaccinated pre-COVID-19 CVT, there was no significant difference between ABO blood groups between vaccine and unvaccinated patients. There was no significant difference in ABO blood groups between the 7 (Definite, Probable, Possible) non-ChAdOx1-S vaccinated and the 441 unvaccinated patients (p = 0.34). Similarly, when analysis is confined to only the Definite group (n = 4) there was no difference between vaccinated and unvaccinated patients, blood group O compared to Non-O (p = 0.52).
Multivariate analysis with well-established CVT risk factors lupus anticoagulant, antiphospholipid antibodies, Protein-C deficiency, Protein-S deficiency, antithrombin deficiency, factor VIII (FVIII), Factor-V Leiden (FAK-tur five LIDE-n) and prothrombin G20210A (Factor II mutation) produced similar results. The presence of blood group O was three-times more likely in the VITT-CVT Definite or Probable vaccinated group (OR = 3.45, 95% CI: 1.75–6.75, p < 0.001) compared with those with blood group A.
The demographic characteristics of vaccinated patients VITT-CVT defined as Definite or Probable and unvaccinated patients with CVT are presented in Table 3. No significant difference was observed in age and sex between them. More than 80% of the vaccinated VITT-CVT patients were classified as Definite.
Table 3.
Characteristics of vaccinated VITT-CVT patients defined as Definite or Probable and unvaccinated patients with CVT.
|
Vaccinated(n = 47) |
Unvaccinated (n = 441) | p-Value | |
|---|---|---|---|
| Age in years at CVT (SD) | 46.2 (14.7) | 47.4 (15.4) | 0.60 |
| Female (n/%) | 37 (78.7) | 305 (69.2) | 0.23 |
| COVID-19 vaccination (n/%) | |||
| First (1st) | |||
| ChAdOx1-S vaccine | 47 (100.0) | 0 (0) | – |
| Non-ChAdOx1-S vaccine a | 0 (0) | 0 (0) | – |
| Second (2nd) | |||
| None | 44 (93.6) | 0 (0) | – |
| ChAdOx1-S vaccine | 1 (2.1) | 0 (0) | – |
| Non-ChAdOx1-S vaccine b | 2 (4.3) | 0 (0) | – |
| Third (3rd) | |||
| None | 47 (100.0) | 0 (0) | – |
| ChAdOx1-S vaccine | 0 (0) | 0 (0) | – |
| Non-ChAdOx1-S vaccine c | 0 (0) | 0 (0) | – |
| VITT (n/%) for ChAdOx1-S vaccine | |||
| Definite | 38 (80.9) | 0 (0) | – |
| Probable | 9 (19.1) | 0 (0) | – |
n: sample size; SD: standard deviation; VITT: vaccine-induced immune thrombocytopenia and thrombosis.
a Pfizer/BioNTech (0), Moderna (0), Johnson & Johnson (0), Sinovac (0), Other (0). b Pfizer/BioNTech (2), Moderna (0), Johnson & Johnson (0), Sinovac (0), Other (0). c Pfizer/BioNTech (0), Moderna (0), Johnson & Johnson (0), Sinovac (0), Other (0).
Further, to test whether ABO allele frequencies associated with ChAdOx1-S vaccination, the blood type allele distribution status among VITT-CVT patients defined as Definite or Probable is presented in Figure 2. ABO allele distribution can be more powerful and informative because it essentially doubles the sample size of the studied population. 16 ChAdOx1-S vaccinated patients had 20.5% (95% CI: 43.3–63.8, p < 0.001) higher frequency of O allele compared with unvaccinated patients. Conversely, unvaccinated patients had higher frequency of the A allele 19.3% (95%CI: 8.8–29.8, p < 0.001) compared with vaccinated patients (Figure 2).
Figure 2.
ABO allele distribution between ChAdOx1-S vaccinated and unvaccinated groups (analysis restricted to VITT-CVT defined as Definite or Probable5).
Discussion
We show that blood group O is more prevalent among patients with VITT-CVT after ChAdOx1-S (Oxford-AstraZeneca) vaccination compared with unvaccinated cases in a well-characterised CVT population. The most common ABO allele among vaccinated patients was O, present in 63% (95% CI: 53–74) followed by allele-A present in 31% (95% CI: 22–41). Converse results were observed in the unvaccinated group with the most common ABO allele-A present in 50% (95% CI: 47–54) followed by the O-allele in 43% (95% CI: 40–47). Although our study is small, VITT-CVT post COVID-19 vaccination is rare and we present one of the largest cohorts recruited via two international ongoing studies.
There is increasing evidence for the involvement of blood group in CVT, 9 either in terms of onset or outcome. We present data suggesting that blood group may also be involved in the development of CVT after vaccination. This finding not only may suggest an aetiological mechanism for CVT after a vector-based vaccine but may help to identify those more likely to be at risk. According to the European Medicines Agency,17,18 after the ChAdOx1-S vaccination, young people with wild type blood group O may experience immunosenescence, a negative immunological response that can result in blood abnormalities resembling disseminated intravascular coagulation. Blood group antigens play a direct role in infection through various mechanisms. Anti-A antibodies were protective against intracellular uptake of severe acute respiratory syndrome coronavirus 1.19,20 Blood group A with anti-A antibodies inhibited interaction between angiotensin converting enzyme-2-dependent cellular adhesion to angiotensin converting enzyme-2-expressing cells. 19
Although we show a lower prevalence of blood group A for patients with VITT-CVT after ChAdOx1-S vaccination compared with unvaccinated cases and no significant differences observed for other known risk factors for CVT, our result must be interpreted with caution as the number of patients from the vaccinated group with ChAdOx1-S was limited. However, as CVT is a rare disorder, and vaccination-associated CVT is even rarer, our data present one of the largest such studies to-date. The population we recruited in both groups was well characterised using internationally agreed criteria for CVT and for vaccine-associated CVT. Other limitations include the possibility of the presence of specific confounders, namely, genetic or environmental factors that may have a role in modifying the vaccination effect. Additionally, side effects of ChAdOx1-S vaccination must be confronted knowing the vast number of doses that were administered over a short time.
Conclusions
We document high prevalence of blood group O in patients with VITT-CVT after ChAdOx1-S Oxford-AstraZeneca vaccination. As ChAdOx1-S is the predominant vaccine of choice globally due to its ease of transportation and low cost, larger studies are urgently required to determine whether a complete ban on its use in young individuals with any blood group is too restrictive.
Summary box
What is known?
COVID-19 patients with blood group A tend to have a higher risk of severe disease, while individuals with B or O blood groups are less represented among COVID-19 patients.
CVT after administration of ChAdOx1-S (Oxford-AstraZeneca) has been associated within 28 days of vaccination.
What is the question?
This study aimed to determine whether blood group influences development of CVT after ChAdOx1-S vaccination.
What was found?
In this case–control study of 523 CVT patients from two international collaborative groups, we found that blood group O was more prevalent in the VITT-CVT group than in the unvaccinated pre-COVID-19 CVT group (43% vs. 17%, respectively, p < 0.001).
Blood group A was less prevalent, though still high, in the vaccinated group compared with the unvaccinated group (47% vs. 71%, respectively, p < 0.001)
Multivariate analysis with well-established CVT risk factors showed similar results.
What is the implication for practice now?
This study suggests that those with blood group O are more likely to be exposed to VITT-CVT after ChAdOx1-S vaccination regardless of well-established CVT risk factors such as gender.
These results may lead governments to question whether ChAdOx1-S (Oxford-AstraZeneca) vaccine should be outright banned despite its high efficacy, cost-effectiveness and ease of handling.
Those with non-O blood group may be suitable for the AstraZeneca COVID-19 vaccine, although larger studies are required to confirm our findings.
Footnotes
ORCID iD: Gie Ken-Dror https://orcid.org/0000-0003-3747-7112
Contributor Information
on behalf of the international Bio-Repository to Establish the Aetiology of Sinovenous Thrombosis (BEAST) collaborators and Cerebral Venous Sinus Thrombosis With Thrombocytopenia Syndrome Study Group:
Anita van de Munckhof, Katarzyna Krzywicka, Mayte Sánchez van Kammen, Abdoreza Ghoreishi, Afshin Borhani-Haghighi, Alberto Negro, Albrecht Günther, Alvaro Cervera, Anil Man Tuladhar, Annemie Devroye, Annerose Mengel, Avinash Aujayeb, Barbara Casolla, Beng Lim Alvin Chew, Carla Zanferrari, Carlos Garcia-Esperon, Christoph M. Wahl, Daniel Guisado Alonso, David Bougon, Domenico Sergio Zimatore, Dominik Michalski, Dylan Blacquiere, Elias Johansson, Elisa Cuadrado-Godia, Emmanuel de Maistre, Espen Saxhaug Kristoffersen, Fabrice Bonneville, Fabrizio Giammello, Florindo D'Onofrio, Francesco Grillo, Georgios Tsivgoulis, Igor Sibon, Jaime Masjuan, Jiangang Duan, Jim Burrow, Johann Pelz, Joshua Mbroh, Karl Ng, Katia Garambois, Kevin Lagarde, Sylvain Lanthier, María Hernández Pérez, Aarti R Sharma, Shyam S Sharma, Mar Morín, Marco Petruzzellis, Maria Sofia Cotelli, Marialuisa Zedde, Marta Carvalho, Matthias Wittstock, Mehrdad Roozbeh, Miguel Miranda, Miriam Wronski, Mona Skjelland, Monica Bandettini di Poggio, Mostafa Almasi-Dooghaee, Nicolas Raposo, Nima Fadakar, Nyika Kruyt, Paolo Candelaresi, Ricardo Vieira, Roberto Acampora, Robin Lemmens, Rolf Kern, Seán Murphy, Simon Nagel, Sini Hiltunen, Sophie Chatterton, Theodoros Karapanayiotides, Thomas Cox, Thomas Gattringer, Thomas Geeraerts, Thorsten Bartsch, Zahra Mirzaasgari, Bentalhoda Ziaadini, Zohreh Zamani, Thalia S Field, Charlotte Cordonnier, Timothy J Kleinig, Jukka Putaala, Sven Poli, Adrian Scutelnic, Mirjam R Heldner, Erik Lindgren, Turgut Tatlisumak, Katarina Jood, Marcel Arnold, Diana Aguiar de Sousa, Jose M Ferro, and Jonathan M Coutinho
Declarations
Competing Interests
None declared.
Funding
BEAST was funded, in part, by grants awarded to PS from The Stroke Association (UK) and the Dowager Countess Eleanor Peel Trust (UK). PS was funded by a Dept of Health (UK) Senior Fellowship at Imperial College London for part of this study. The cohort of 231 French cases was constituted during a hospital protocol of clinical research approved by the French Ministry of Health; biological collection was kept and managed by the INSERM CIC-CRB 1404, F-76000 Rouen, France. The controls from Belgium were genotyped as part of the SIGN study. Robin Lemmens (RL) is a senior clinical investigator of FWO Flanders. Turgut Tatlisumak (TT) is the recipient of funding from the Sigrid Juselius Foundation (FIN), Helsinki University Central Hospital (FIN), Sahlgrenska University Hospital (SWE) and University of Gothenburg (SWE). Swedish Research Council (2018-02543) and the Swedish Heart and Lung Foundation (20190203). JMC has received funding from the Dutch Thrombosis Foundation. This material is the result of work supported with resources and the use of facilities at the VA Maryland Health Care System, Baltimore, Maryland USA and was also supported, in part, by the National Institutes of Health (U01NS069208, R01NS105150, R01NS100178). The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.
Ethics approval
The study was approved by the British Repository of DNA in Stroke (BRAINS) Committee (04/Q0401/40) and all patients gave written informed consent.
Guarantor
PS.
Contributorship
PS conceived the idea and supervised the study. GKD undertook the primary analysis and wrote the first draft of the article. All authors and collaborators contributed to the final article.
Acknowledgements
We are grateful to the patients without whom this work would not have been possible.
Bio-Repository to Establish the Aetiology of Sinovenous Thrombosis (BEAST) collaborators: Gie Ken-Dror, Ida Martinelli, Elvira Grandone, Sini Hiltunen, Erik Lindgren, Maurizio Margaglione, Veronique Le Cam Duchez, Aude Bagan Triquenot, Marialuisa Zedde, Michelangelo Mancuso, Ynte M Ruigrok, Brad Worrall, Jennifer J Majersik, Tiina M. Metso, Jukka Putaala, Elena Haapaniemi, Susanna M. Zuurbier, Matthijs C. Brouwer, Maria Abbattista, Paolo Bucciarelli, Robin Lemmens, Emanuela Pappalardo, Paolo Costa, Marina Colombi, Diana Aguiar de Sousa, Sofia Rodrigues, Patrícia Canhão, Aleksander Tkach, Rosa Santacroce, Giovanni Favuzzi, Antonio Arauz, Donatella Colaizzo, Kostas Spengos, Amanda Hodge, Reina Ditta, Alessandro Pezzini, Jonathan M. Coutinho, Vincent Thijs, Katarina Jood, Turgut Tatlisumak, José M. Ferro, and Pankaj Sharma; on behalf of the International Stroke Genetics Consortium (ISGC) & Bio-Repository to Establish the Aetiology of Sinovenous Thrombosis (BEAST) collaborators.
Cerebral Venous Sinus Thrombosis with Thrombocytopenia Syndrome Study Group collaborators: Anita van de Munckhof, Katarzyna Krzywicka, Mayte Sánchez van Kammen, Abdoreza Ghoreishi, Afshin Borhani-Haghighi, Alberto Negro, Albrecht Günther, Alvaro Cervera, Anil Man Tuladhar, Annemie Devroye, Annerose Mengel, Avinash Aujayeb, Barbara Casolla, Beng Lim Alvin Chew, Carla Zanferrari, Carlos Garcia-Esperon, Christoph M. Wahl, Daniel Guisado Alonso, David Bougon, Domenico Sergio Zimatore, Dominik Michalski, Dylan Blacquiere; Elias Johansson, Elisa Cuadrado-Godia, Emmanuel de Maistre, Espen Saxhaug Kristoffersen, Fabrice Bonneville, Fabrizio Giammello, Florindo D'Onofrio, Francesco Grillo, Georgios Tsivgoulis, Igor Sibon, Jaime Masjuan, Jiangang Duan, Jim Burrow, Johann Pelz, Joshua Mbroh, Karl Ng, Katia Garambois, Kevin Lagarde, Sylvain Lanthier, María Hernández Pérez, Aarti R Sharma, Shyam S Sharma, Mar Morín, Marco Petruzzellis, Maria Sofia Cotelli, Marialuisa Zedde, Marta Carvalho, Matthias Wittstock, Mehrdad Roozbeh, Miguel Miranda, Miriam Wronski, Mona Skjelland, Monica Bandettini di Poggio, Mostafa Almasi-Dooghaee, Nicolas Raposo, Nima Fadakar, Nyika Kruyt, Paolo Candelaresi, Ricardo Vieira, Roberto Acampora, Robin Lemmens, Rolf Kern, Seán Murphy, Simon Nagel, Sini Hiltunen, Sophie Chatterton, Theodoros Karapanayiotides, Thomas Cox, Thomas Gattringer, Thomas Geeraerts, Thorsten Bartsch, Zahra Mirzaasgari, Bentalhoda Ziaadini, Zohreh Zamani, Thalia S Field, Charlotte Cordonnier, Timothy J Kleinig, Jukka Putaala, Sven Poli, Adrian Scutelnic, Mirjam R Heldner, Erik Lindgren, Turgut Tatlisumak, Katarina Jood, Marcel Arnold, Diana Aguiar de Sousa, Jose M Ferro, Jonathan M Coutinho.
Provenance
Not commissioned; peer-reviewed by Julie Morris and Carmel Curtis.
References
- 1.Pottegard A, Lund LC, Karlstad O, Dahl J, Andersen M, Hallas J, et al. Arterial events, venous thromboembolism, thrombocytopenia, and bleeding after vaccination with Oxford-AstraZeneca ChAdOx1-S in Denmark and Norway: population based cohort study. BMJ 2021; 373: n1114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Greinacher A, Thiele T, Warkentin TE, Weisser K, Kyrle PA, Eichinger S. Thrombotic thrombocytopenia after ChAdOx1 nCov-19 vaccination. N Engl J Med 2021; 384: 2092–2101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Schultz NH, Sorvoll IH, Michelsen AE, Munthe LA, Lund-Johansen F, Ahlen MT, et al. Thrombosis and thrombocytopenia after ChAdOx1 nCoV-19 vaccination. N Engl J Med 2021; 384: 2124–2130. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Sanchez van Kammen M, Aguiar de Sousa D, Poli S, Cordonnier C, Heldner MR, van de Munckhof A, et al. Characteristics and outcomes of patients with cerebral venous sinus thrombosis in SARS-CoV-2 vaccine-induced immune thrombotic thrombocytopenia. JAMA Neurol 2021; 78: 1314–1323. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Pavord S, Scully M, Hunt BJ, Lester W, Bagot C, Craven B, et al. Clinical features of vaccine-induced immune thrombocytopenia and thrombosis. N Engl J Med 2021; 385: 1680–1689. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Perry RJ, Tamborska A, Singh B, Craven B, Marigold R, Arthur-Farraj P, et al. Cerebral venous thrombosis after vaccination against COVID-19 in the UK: a multicentre cohort study. Lancet 2021; 398: 1147–1156. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Ray JG, Schull MJ, Vermeulen MJ, Park AL. Association between ABO and Rh blood groups and SARS-CoV-2 infection or severe COVID-19 illness: a population-based cohort study. Ann Intern Med 2021; 174: 308–315. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Ellinghaus D, Degenhardt F, Bujanda L, Buti M, Albillos A, Invernizzi P, et al.; Severe Covid-19 GWAS Group. Genomewide association study of severe Covid-19 with respiratory failure. N Engl J Med 2020; 383: 1522–1534. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ken-Dror G, Cotlarciuc I, Martinelli I, Grandone E, Hiltunen S, Lindgren E, et al. Genome-wide association study identifies first locus associated with susceptibility to cerebral venous thrombosis. Ann Neurol 2021; 90: 777–788. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Cotlarciuc I, Marjot T, Khan MS, Hiltunen S, Haapaniemi E, Metso TM, et al. Towards the genetic basis of cerebral venous thrombosis – the BEAST Consortium: a study protocol. BMJ Open 2016; 6: e012351. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Hosmer DW, Lemeshow S, Sturdivant RX. ProQuest . Applied Logistic Regression. Hoboken, NJ: Wiley, 2013. [Google Scholar]
- 12.Zhou X-h, McClish DK, Obuchowski NA. Statistical Methods in Diagnostic Medicine . 2nd ed. Hoboken, NJ: Wiley, 2011. [Google Scholar]
- 13.Ken-Dror G, Hastings IM. Markov chain Monte Carlo and expectation maximization approaches for estimation of haplotype frequencies for multiply infected human blood samples. Malar J 2016; 15: 430. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.McLachlan GJ, Krishnan T. The EM Algorithm and Extensions . Hoboken, NJ: Wiley-Interscience, 2008. [Google Scholar]
- 15.Ken-Dror G, Wade C, Sharma S, Law J, Russo C, Sharma A, et al. COVID-19 outcomes in UK centre within highest health and wealth band: a prospective cohort study. BMJ Open 2020; 10: e042090. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Ken-Dror G, Humphries SE, Drenos F. The use of haplotypes in the identification of interaction between SNPs. Hum Hered 2013; 75: 44–51. [DOI] [PubMed] [Google Scholar]
- 17.Dal-Re R, Launay O. Public trust on regulatory decisions: The European Medicines Agency and the AstraZeneca COVID-19 vaccine label. Vaccine 2021; 39: 4029–4031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Krzywicka K, Heldner MR, Sanchez van Kammen M, van Haaps T, Hiltunen S, Silvis SM, et al. Post-SARS-CoV-2-vaccination cerebral venous sinus thrombosis: an analysis of cases notified to the European Medicines Agency. Eur J Neurol 2021; 28: 3656–3662. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Guillon P, Clement M, Sebille V, Rivain JG, Chou C-F, Ruvoën-Clouet N, et al. Inhibition of the interaction between the SARS-CoV spike protein and its cellular receptor by anti-histo-blood group antibodies. Glycobiology 2008; 18: 1085–1093. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Ritchie G, Harvey DJ, Feldmann F, Stroeher U, Feldmann H, Royle L, et al. Identification of N-linked carbohydrates from severe acute respiratory syndrome (SARS) spike glycoprotein. Virology 2010; 399: 257–269. [DOI] [PMC free article] [PubMed] [Google Scholar]