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letter
. 2022 May 31:keac323. doi: 10.1093/rheumatology/keac323

Risk of systemic vasculitis following mRNA COVID-19 vaccination: a pharmacovigilance study

Camille Mettler 1,2, Benjamin Terrier 3,4, Jean-Marc Treluyer 5,6,1, Laurent Chouchana 7,1,
PMCID: PMC9213846  PMID: 35640943

Rheumatology key message.

  • Compared with influenza vaccines, systemic vasculitis reporting is not increased with mRNA COVID-19 vaccines, except eventually for Behçet’s syndrome.

Dear Editor, Sporadic cases of systemic vasculitis following coronavirus disease 2019 (COVID-19) vaccination were anecdotally reported in the literature [1, 2], raising the question of the association between vasculitis onset and vaccination during the COVID-19 pandemic. We recently showed that GCA and PMR may be associated with COVID-19 vaccines, although risk of reporting these entities appears lower than with influenza vaccines [3]. Here we aimed to assess a potential safety signal for the different types of systemic vasculitis following mRNA COVID-19 vaccination.

We used VigiBase (https://www.who-umc.org/vigibase/vigibase/), the World Health Organization (WHO) global individual case safety report database that contains spontaneous reports of suspected adverse drug reactions collected by national drug authorities in >130 countries. This large database is powerful for signal detection based on disproportionality analyses [4, 5]. This pharmacovigilance statistical approach is similar to a case–control study nested in a large cohort [4] and estimates whether an adverse event is differentially reported for a specific drug compared with other drugs. The association between an specific adverse event (i.e. a type of vasculitis) and a specific drug (i.e. mRNA COVID-19 vaccines) was expressed using the reporting odds ratio (ROR) and its 95% CI, which corresponds to the exposure odds among reported cases divided by the exposure odds among reported non-cases. To limit indication and reporting bias, comparators were influenza vaccines. A lower boundary 95% CI >1 is deemed significant, as for OR interpretation, and supports a potential safety signal. This study adhered to the Declaration of Helsinki.

Of the 2 499 457 spontaneous reports with mRNA COVID-19 vaccines (i.e. elasomeran/mRNA-1273 and tozinameran/BNT162b2) in VigiBase through 31 March 2022, we identified 2125 (8.5/10 000 reports) vasculitis cases; 61% were women, with median age of 58 years [interquartile range (IQR) 38–72].

Overall, mRNA COVID-19 vaccines were associated with increased reporting in Behçet’s syndrome [ROR 1.7 (95% CI 1.4, 2.1)], GCA [ROR 4.5 (95% CI 4.0, 5.0)], microscopic polyangiitis [ROR 2.6 (95% CI 1.8, 3.7)], livedoid vasculopathy [ROR 4.1 (95% CI 2.5, 6.5)] and urticarial vasculitis [ROR 3.0 (95% CI 2.4, 3.7)] (Table 1). None of the other vasculitis types were associated with increased reporting following mRNA COVID-19 vaccines, especially eosinophilic granulomatosis with polyangiitis, Henoch-Schönlein purpura (i.e. IgA vasculitis) or polyarteritis nodosa. When compared with the use of influenza vaccines, we found a disproportionate reporting with mRNA COVID-19 vaccines only for Behçet’s syndrome [ROR 4.2 (95% CI 1.3, 13.2)], in a similar manner between elasomeran and tozinameran [ROR 1.7 (95% CI 1.0, 2.9)]. Among the 93 Behçet’s syndrome cases, 76 (82%) were women, with a median age of 37 years (IQR 30–43). Differences in systemic vasculitis risk may exist between elasomeran and tozinameran but require further study.

Table 1.

Systemic vasculitis cases reported in the WHO global safety database with mRNA COVID-19 vaccines and their reporting ORs

Types of vasculitis N observed a
N expected N reaction Disproportionality analysis, ROR (95% CI)
mRNA COVID-19 vaccines Elasomeran Tozinameran mRNA COVID-19 vaccines vs any drugs mRNA COVID-19 vaccines vs influenza vaccines Tozinameran vs elasomeran
ANCA-associated vasculitis 229 41 188 255 3064 0.9 (0.8, 1.0) 0.4 (0.3, 0.4) 1.8 (1.3, 2.5)
ANCA-positive vasculitis 68 14 54 75 905 0.9 (0.7, 1.1) 0.3 (0.2, 0.5) 1.5 (0.8, 2.7)
Eosinophilic granulomatosis with polyangiitis 54 11 43 106 1274 0.5 (0.4, 0.6) 0.4 (0.2, 0.7) 1.5 (0.8, 2.9)
Granulomatosis with polyangiitis 82 16 66 64 770 1.3 (1.0, 1.7) 0.3 (0.2, 0.4) 1.6 (0.9, 2.7)
Microscopic polyangiitis 34 3 31 15 180 2.6 (1.8, 3.7) 0.5 (0.2, 0.9) 4.0 (1.2, 13.0)
Behçet’s syndrome 93 17 76 57 690 1.7 (1.4, 2.1) 4.2 (1.3, 13.2) 1.7 (1.0, 2.9)
Central nervous system vasculitis 47 6 41 47 568 1.0 (0.7, 1.3) 0.6 (0.3, 1.3) 2.6 (1.1, 6.2)
Cryoglobulinaemic vasculitis 38 1 37 33 401 1.2 (0.8, 1.6) 0.6 (0.3, 1.2) c
Cutaneous vasculitisb 740 135 605 742 8921 1.0 (0.9, 1.1) 0.5 (0.4, 0.5) 1.7 (1.4, 2.1)
Giant cell arteritis 501 99 402 144 1736 4.5 (4.0, 5.0) 0.7 (0.6, 0.9) 1.6 (1.3, 1.9)
Henoch, Schönlein purpura 256 51 205 370 4447 0.7 (0.6, 0.8) 0.1 (0.1, 0.1) 1.5 (1.1, 2.1)
Kawasaki’s disease 45 1 44 118 1421 0.4 (0.3, 0.5) 0.1 (0.1, 0.1) c
Liveloid vasculopathy 24 6 18 7 89 4.1 (2.5, 6.5) c 1.2 (0.5, 2.9)
Polyarteritis nodosa 24 5 19 64 774 0.4 (0.2, 0.5) 0.3 (0.1, 0.5) 1.5 (0.5, 3.9)
Takayasu’s arteritis 9 0 9 17 201 0.5 (0.3, 1.0) c c
Urticarial vasculitis and hypocomplementemic urticarial vasculitis syndrome 93 19 74 37 439 3.0 (2.4, 3.7) 1.1 (0.6, 2.1) 1.5 (0.9, 2.5)

The specific types of vasculitis were identified using the ad hoc preferred terms from the Medical Dictionary for Regulatory Activities (MedDRA; https://www.meddra.org/). ROR (95% CI) were calculated as adbc(adbc. e±1.961a+1b+1c+1d), where a is the number of cases reported with RNA-based COVID-19 vaccines, b is the number of non-cases (i.e. all other adverse drug reaction reports) reported with RNA-based COVID-19 vaccines, c is the number of cases reported with all other drugs and d is the number of non-cases reported with all other drugs. The threshold for signal detection is defined as an ROR lower boundary 95% CI ≥1 and the number of cases ≥3. Significant associations (adverse event–drug combination) are presented in bold. Nexpected is the expected number of case reports based on the number of case reports for the drug and for the specific reaction, calculated as (Ndrug × Nreaction)/Ntotal, with Ntotal being the total number of reports in the database with any drugs (i.e. 30 031 000 reports) and Ndrug being the number of reports for the drug, regardless the type of reaction (i.e. 2 499 457 reports with elasomeran or tozinameran); Nreaction is the number of reports for the reaction (i.e. cases), regardless of drug.

a

The sum of Nobserved is greater than the number of cases, as one case may refer to more than one type of vasculitis.

b

Refers to hypersensitivity vasculitis, palpable purpura, vasculitic rash and vasculitic ulcer.

c

ROR not provided because insufficient cases were observed with the studied drugs.

Here we used the WHO global safety database to assess potential safety signals for the different types of systemic vasculitis following the use of mRNA COVID-19 vaccines. We found an increased reporting of Behçet’s syndrome, microscopic polyangiitis, livedoid vasculopathy and urticarial vasculitis and, as previously reported, GCA following mRNA COVID-19 vaccination. These findings suggest a potential safety signal for these entities. It should be noted that we previously showed the relative risk for GCA or PMR reporting was reduced with COVID-19 vaccines when the comparator was influenza vaccines [3]. Here, for all vasculitis types except Behçet’s syndrome, we did not find increased reporting when compared with influenza vaccines. Behçet’s syndrome cases were in the range of the expected epidemiology of this disease. Although significant, these results should be interpreted with caution considering the small number of cases in the comparator group. Environmental factors and infections are likely to play a role in the onset of systemic vasculitis and vaccination could act as an inflammatory trigger, as already suspected in previous studies [6]. Our analysis has limitations such as a underreporting and heterogeneous causality assessment among reports. Also, it highlights the importance of using a relevant comparator for the interpretation of these real-life data.

Overall, our study did not suggest a specific vasculitis risk with mRNA COVID-19 vaccines compared with influenza vaccines, except eventually for Behçet’s syndrome. Further analyses are needed to confirm this safety signal and vaccine causality. Nevertheless, mRNA COVID-19 vaccine benefits dramatically outweigh this potential risk, which appears very rare relative to the billions of doses administered so far.

Acknowledgements

The authors would like to thank all the healthcare workers and the French Pharmacovigilance Network involved in the large immunization campaign and its safety. VigiBase is a fully anonymized database of spontaneous reports from the WHO and access is granted for national or regional pharmacovigilance centres such as our team. The information within VigiBase comes from a variety of sources and the probability that the suspected adverse effect is drug related is not the same in all cases. The present analysis does not represent the opinion of the Uppsala Monitoring Centre or the WHO and only reflects the authors opinion. This study adhered to the Declaration of Helsinki. L.C., C.M. and B.T. were responsible for the concept and design; the acquisition, analysis or interpretation of data and drafting of the manuscript. All authors critically reviewed the manuscript. L.C. and C.M. were responsible for the statistical analysis. L.C. was responsible for administrative, technical and material support. L.C. and B.T. were responsible for supervision.

Funding: No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this article.

Disclosure statement: B.T. received consulting fees and/or grants from Roche/Chugai, AstraZeneca, GlaxoSmithKline, Bristol-Myers Squibb, Eli Lilly, Vifor Pharma, LFB, Grifols and Terumo Blood and Cell Technologies. C.M., J.-M.T. and L.C. report no conflicts of interest.

Data availability statement

Data are available upon reasonable request by any qualified researchers who engage in rigorous, independent scientific research, and will be provided following review and approval of a research proposal and Statistical Analysis Plan (SAP) and execution of a Data Sharing Agreement (DSA). All data relevant to the study are included in the article.

Contributor Information

Camille Mettler, Assistance Publique-Hôpitaux de Paris, Département de Pharmacologie, Centre Régional de Pharmacovigilance, Hôpital Cochin; Assistance Publique-Hôpitaux de Paris, Département de Médecine Interne, Centre de Référence National pour les maladies auto-immunes systémiques rares, Hôpital Cochin.

Benjamin Terrier, Assistance Publique-Hôpitaux de Paris, Département de Médecine Interne, Centre de Référence National pour les maladies auto-immunes systémiques rares, Hôpital Cochin; Université Paris, Paris, France.

Jean-Marc Treluyer, Assistance Publique-Hôpitaux de Paris, Département de Pharmacologie, Centre Régional de Pharmacovigilance, Hôpital Cochin; Université Paris, Paris, France.

Laurent Chouchana, Assistance Publique-Hôpitaux de Paris, Département de Pharmacologie, Centre Régional de Pharmacovigilance, Hôpital Cochin.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data are available upon reasonable request by any qualified researchers who engage in rigorous, independent scientific research, and will be provided following review and approval of a research proposal and Statistical Analysis Plan (SAP) and execution of a Data Sharing Agreement (DSA). All data relevant to the study are included in the article.


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