| Literature DB >> 35453660 |
Ni Tien1,2, Yu-Chang Chang1,2, Po-Ku Chen3,4,5, Hui-Ju Lin1,2, Shih-Hsin Chang3,4,6, Joung-Liang Lan3,4,7, Po-Ren Hsueh1,2,8, Ching-Kun Chang3,4, Der-Yuan Chen3,4,5,7.
Abstract
Patients with immune-mediated inflammatory diseases (IMID) were seldom enrolled in the studies of SARS-CoV-2 vaccines, and real-world data regarding the immunogenicity of different types of vaccines is limited. We aimed to assess the immunogenicity and safety of three types of vaccines (AZD1222, mRNA-1273, and BNT162b2) in 253 patients with IMID and 30 healthcare workers (HCWs). Plasma levels of IgG-antibody against SARS-CoV-2 targeting the receptor-binding domain of spike protein (anti-S/RBD-IgG) were determined by chemiluminescent immunoassay 3-4 weeks after the first-dose and second-dose vaccination. The positive rate and titers of anti-S/RBD-IgG were significantly higher in mRNA-1273 or BNT162b2 than in the AZD1222 vaccine. Immunogenicity was augmented after the second dose of any vaccine type in all IMID patients, suggesting that these patients should complete the vaccination series. Anti-S/RBD-IgG titers after first-dose vaccination were significantly lower in RA patients than pSS patients, but there was no significant difference after second-dose vaccination among five groups of IMID patients. The positive rate and titers of anti-S/RBD-IgG were significantly lower in patients receiving abatacept/rituximab therapy than in those receiving other DMARDs. All three SARS-CoV-2 vaccines showed acceptable safety profiles, and the common AEs were injection site reactions. We identified SLE as a significant predictor of increased autoimmunity and would like to promote awareness of the possibility of autoimmunity following vaccination.Entities:
Keywords: SARS-CoV-2 vaccines; immune-mediated inflammatory diseases; immunogenicity; immunosuppressive therapy; safety
Year: 2022 PMID: 35453660 PMCID: PMC9025718 DOI: 10.3390/biomedicines10040911
Source DB: PubMed Journal: Biomedicines ISSN: 2227-9059
Figure 1Study design workflow. IMID: immune-mediated inflammatory diseases immune-mediated inflammatory diseases; SLE: systemic lupus erythematosus; pSS: primary Sjögren’s syndrome; RA: rheumatoid arthritis; PsA: psoriatic arthritis; AOSD: adult-onset Still’s disease; HCWs: health-care workers; Anti-S/RBD-IgG Ab: IgG antibody against SARS-CoV-2 IgG antibody against SARS-CoV-2 specific for the receptor-binding domain (RBD) of the spike-1 (S1) protein.
Demographic data, laboratory findings, the used medications, and the presence of comorbidities in patients with SLE, pSS, RA, SpA, and AOSD, and the healthcare workers (HCWs).
| Characteristics | SLE | pSS | RA | SpA | AOSD | HCWs |
|---|---|---|---|---|---|---|
| Age at study entry, years | 44.6 ± 14.3 | 61.2 ± 12.2 ***,# | 61.2 ± 12.9 ***,#,$ | 50.0 ± 16.6 | 49.9 ± 15.2 | 44.1 ± 15.4 |
| Female proportion, | 35 (97.2%) | 56 (93.3%) | 94 (85.5%) | 11 (47.8%) | 19 (79.2%) | 23 (76.7%) |
| BMI, kg/m2 | 22.7 ± 3.8 | 23.1 ± 3.4 | 23.2 ± 3.5 | 24.2 ± 4.2 | 24.0 ± 4.6 | 24.6 ± 7.0 |
| SARS-CoV-2 vaccine type | ||||||
| AZD1222/ChAdOx1 | 14 (38.9%) | 33 (55.0%) | 36 (32.7%) | 7 (30.4%) | 9 (37.5%) | 14 (46.7%) |
| The mRNA-1273 | 14 (38.9%) | 26 (43.3%) | 56 (50.9%) | 9 (39.2%) | 9 (37.5%) | 15 (50.0%) |
| BNT162b2 | 8 (22.2%) | 1 (1.7%) | 18 (16.4%) | 7 (30.4%) | 6 (25.0%) | 1 (3.3%) |
| Seropositive rate, | 16 (44.4%) | 31 (51.7%) | 41 (37.3%) | 11 (47.8%) | 14 (58.3%) | 9 (30.0%) |
| Anti-S/RBD-IgG, AU/mL, after 1st-dose vaccine | 12.8 | 21.5 | 6.1 | 26.8 | 20.7 | 21.4 |
| Seropositive rate, | 29 (80.6%) | 47 (78.3%) | 81 (73.6%) | 21 (91.3%) | 19 (79.2%) | 26 (86.7%) |
| Anti-S/RBD-IgG, AU/mL, after 2nd dose-vaccine | 50.3 | 46.5 | 29.8 | 69.5 | 44.2 | 54.0 |
| The used | ||||||
| Prednisolone ≤ 15 mg/day | 30 (83.3%) | 10 (16.7%) | 58 (52.7%) | 5 (21.7%) | 15 (62.5%) | NA |
| Prednisolone >15 mg/day | 4 (11.1%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (4.2%) | NA |
| The used csDMARDs | ||||||
| Methotrexate | 0 (0%) | 0 (0.0%) | 24 (21.8%) | 2 (8.7%) | 10 (41.7%) | NA |
| Hydroxychloroquine | 34 (94.4%) | 55 (91.7%) | 50 (45.5%) | 0 (0.0%) | 19 (79.2%) | NA |
| Azathioprine | 14 (38.9%) | 1 (1.7%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | NA |
| Cyclosporine | 5 (13.9%) | 1 (1.7%) | 2 (1.8%) | 0 (0.0%) | 2 (8.3%) | NA |
| MMF ≤ 2 gm/day | 12 (33.3%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | NA |
| MMF >2 gm/day | 3 (8.3%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | NA |
| The used biologics | ||||||
| TNF-α inhibitors | 0 (0.0%) | 0 (0.0%) | 35 (31.8%) | 13 (56.5%) | 0 (0.0%) | NA |
| IL-6R inhibitor | 0 (0.0%) | 0 (0.0%) | 23 (20.9%) | 0 (0.0%) | 4 (16.7%) | NA |
| Abatacept | 1 (2.7%) | 0 (0.0%) | 11 (10.0%) | 0 (0.0%) | 1 (4.2%) | NA |
| Rituximab | 1 (2.7%) | 1 (1.7%) | 5 (4.5%) | 0 (0.0%) | 0 (0.0%) | NA |
| The used JAKi | 0 (0.0%) | 0 (0.0%) | 38 (34.5%) | 1 (4.3%) | 0 (0.0%) | NA |
| Comorbidities | ||||||
| Hypertension | 11 (30.6%) | 10 (16.7%) | 21 (19.1%) | 4 (17.4%) | 3 (12.5%) | 0 (0.0%) |
| Diabetes mellitus | 3 (8.3%) | 5 (8.3%) | 10 (9.1%) | 1 (4.3%) | 1 (4.2%) | 0 (0.0%) |
| Current smoker | 2 (5.6%) | 4 (6.7%) | 8 (7.3%) | 1 (4.3%) | 1 (4.2%) | 0 (0.0%) |
Data were expressed as mean ± SD, number (%), or median (25th–75th quartile range). NA: not applicable; SLE: systemic lupus erythematosus; pSS: primary Sjögren’s syndrome; RA: rheumatoid arthritis; SpA: spondyloarthropathies; AOSD: adult-onset Still’s disease; BMI: body mass index; csDMARDs: conventional synthetic disease-modifying anti-rheumatic drugs; TNF-α: tumor necrosis factor-α; IL-6: Interleukin-6; JAKi: Janus kinase inhibitors; † p < 0.05, †† p < 0.01, ††† p < 0.001, vs. after first dose or at baseline, as determined by Wilcoxon matched-pairs signed-rank test; *** p < 0.001, vs. HCWs group, as determined by Kruskal-Wallis test using a post hoc Dunn’s test; # p < 0.05, vs. AOSD group, as determined by Kruskal-Wallis test using a post hoc Dunn’s test; $ p < 0.05 vs. SPA group, as determined by Kruskal-Wallis test using a post hoc Dunn’s test; §§ p < 0.01 vs. RA group, as determined by Kruskal-Wallis test using a post hoc Dunn’s test.
Figure 2Comparisons of anti-S/RBD-IgG positive rates and titers among different groups. Comparisons of anti-S/RBD-IgG positive rates (A) and titers (B) among three different types of SARS-CoV-2 vaccines. (C) Comparisons of anti-S/RBD-IgG positive rates and titers among the different groups of participants. (D) Comparisons of the anti-S/RBD-IgG positive rates and titers among the immunosuppressants, csDMARDs, bDMARDs, and tsDMARDs. The horizontal line within each figure indicates the cut-off value for positive anti-S/RBD-IgG. ** p < 0.01, *** p < 0.001, vs. after first dose or at baseline, as determined by Wilcoxon matched-pairs signed-rank test. # p <0.05, ### p < 0.001, vs. AZD1222 vaccine, as determined by Kruskal-Wallis test using a post hoc Dunn’s test in (B). ## p < 0.01, vs. pSS group, as determined by Kruskal-Wallis test using a post hoc Dunn’s test in (C). # p < 0.01, vs. ABT/RTX therapy, as determined by Kruskal-Wallis test using a post hoc Dunn’s test in (D). SLE: systemic lupus erythematosus; pSS: primary Sjögren’s syndrome; RA: rheumatoid arthritis (RA); SpA: spondyloarthropathies; AOSD: adult-onset Still’s disease; csDMARDs: conventional synthetic disease-modifying antirheumatic drugs; bDMARDs: biological DMARDs; tsDMARDs: targeted synthetic DMARDs; TNFi: tumor necrosis factor inhibitors; TCZ: tocilizumab; ABT: abatacept; RTX: rituximab; JAKi: Janus kinase inhibitors; MTX: methotrexate; MMF: mycophenolate.
Logistic regression analysis for predicting the lack of immunogenicity.
| Baseline Variables | Univariate Model | Multivariate Model | ||||||
|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | |||||
| Age at entry, years | 1.03 | (1.01- | 1.05) | 0.012 | ||||
| Gender | ||||||||
| Male | ref. | |||||||
| Female | 0.36 | (0.17- | 0.75) | 0.007 | 0.34 | (0.14- | 0.80) | 0.014 |
| Disease groups | 0.97 | (0.74- | 1.27) | 0.837 | ||||
| CKD | 5.64 | (2.46- | 12.95) | 0.001 | ||||
| The estimated GFR | 0.98 | (0.97- | 0.99) | 0.001 | ||||
| BMI, kg/m2 | 1.02 | (0.94- | 1.11) | 0.593 | ||||
| The used medications | ||||||||
| TNF-α inhibitors | 0.70 | (0.27- | 1.77) | 0.445 | ||||
| Tocilizumab | 1.27 | (0.48- | 3.39) | 0.633 | ||||
| ABT/RTX | 2.98 | (1.06- | 8.42) | 0.039 | 4.19 | (1.25- | 14.09) | 0.021 |
| JAK inhibitors | 0.51 | (0.19- | 1.37) | 0.178 | ||||
| Methotrexate | 1.21 | (0.53- | 2.74) | 0.655 | ||||
| Mycophenolate | 2.03 | (0.71- | 5.76) | 0.183 | ||||
| Corticosteroids | 0.89 | (0.49- | 1.62) | 0.771 | ||||
| Type of vaccines | ||||||||
| AZ12222 | 5.29 | (2.80- | 10.00) | 0.001 | 7.21 | (1.96- | 26.57) | 0.003 |
| mRNA-1273 | 0.38 | (0.20- | 0.72) | 0.003 | ||||
| BNT162b2 | 0.20 | (0.06- | 0.68) | 0.01 | ||||
OR: odds ratio; 95% CI: 95% confidence interval; CKD: chronic kidney disease; GFR: glomerular filtration rate; BMI: body mass index; TNF: tumor necrosis factor; ABT/RTX: abatacept/rituximab; JAK: Janus kinase. Variables in multivariate model: age, gender, CKD, GFR, ABT/RTX, AZ12222, RNA-1273, BNT162b1.
The adverse effects of vaccination with AZD1222, mRNA-1273, or BNT162b2 in patients with immune-mediated inflammatory diseases.
| Adverse Events (AEs) | AZD1222 ( | mRNA-1273 ( | BNT162b2 ( | |||
|---|---|---|---|---|---|---|
| Injection site pain/skin rash | ||||||
| Grade 1 or 2 | 9 (10.0%) | 1.0 (0.7–1.5) | 16 (13.7%) | 1.0 (0.8–1.4) | 8 (17.4%) | 1.0 (1.0–1.3) |
| Grade 3 | 2 (2.2%) | 1.8 (1.6–2.0) | 3 (2.6%) | 1.5 (1.3–1.5) | 2 (4.3%) | 1.8 (1.6–1.9) |
| Grade 4 | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |||
| Flu-like symptoms a | ||||||
| Grade 1 or 2 | 3 (3.3%) | 1.0 (0.8–1.3) | 6 (5.1%) | 0.9 (0.7–1.0) | 2 (4.3%) | 0.9 (0.9–1.0) |
| Grade 3 | 1 (1.1%) | 1.5 | 0 (0.0%) | 0 (0.0%) | ||
| Grade 4 | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |||
| Cardiovascular symptoms e | ||||||
| Grade 1 or 2 | 1 (1.1%) | 2.5 | 6 (5.1%) | 2.0 (1.6–2.4) | 2 (4.3%) | 2.3 (2.1–2.4) |
| Grade 3 | 0 (0.0%) | 2 (1.7%) | 2.8 (2.7–2.9) | 1 (2.2%) | 3.0 | |
| Grade 4 | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |||
| VITT f | ||||||
| Grade 1 or 2 | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |||
| Grade 3 | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |||
| Grade 4 | 1 (1.1%) | 14.0 | 0 (0.0%) | 0 (0.0%) | ||
VITT: vaccine-induced thrombosis and thrombocytopenia; a the presence of fever, chills, general malaise, muscle pain, or other flu-like symptoms; b the presence of rash, itching, urticaria, angioedema, or even anaphylaxis that occurred within 2 h postvaccination; c the presence of vomiting, diarrhea, or abdominal pain.; d the presence of peripheral neuropathy, myopathy, seizure, or even ischemic stroke.; e the presence of palpitation, precordial tightness, myocarditis/pericarditis, venous thromboembolism, pulmonary embolism, or even acute myocardial infarction; f the presence of thrombocytopenia, vascular thrombosis, or the relevant symptoms.
Logistic regression analysis for predicting the occurrence of adverse events.
| Baseline Variables | Univariate Model | Multivariate Model | ||||||
|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | |||||
| Age at entry, years | 1.00 | (0.97- | 1.01) | 0.268 | ||||
| Gender | ||||||||
| Male | ref. | |||||||
| Female | 1.56 | (0.65- | 3.74) | 0.319 | ||||
| Disease groups | 0.86 | (0.66- | 1.11) | 0.247 | ||||
| CKD | 0.85 | (0.33- | 2.20) | 0.734 | ||||
| The estimated GFR | 1.00 | (0.99- | 1.02) | 0.507 | ||||
| BMI, kg/m2 | 1.04 | (0.96- | 1.12) | 0.304 | ||||
| The used medications | ||||||||
| TNF-α inhibitors | 0.062 | (0.01- | 0.47) | 0.007 | 0.07 | (0.01- | 0.53) | 0.010 |
| Tocilizumab | 0.82 | (0.29- | 2.32) | 0.713 | ||||
| ABT/RTX | 0.68 | (0.19- | 2.47) | 0.559 | ||||
| JAK inhibitors | 2.39 | (1.15- | 4.95) | 0.020 | ||||
| Methotrexate | 1.19 | (0.54- | 2.63) | 0.667 | ||||
| Mycophenolate | 1.28 | (0.43- | 3.78) | 0.657 | ||||
| Corticosteroids | 1.45 | (0.82- | 2.57) | 0.205 | ||||
| Type of vaccines | ||||||||
| AZ12222 | 1.38 | (0.77- | 2.48) | 0.277 | ||||
| mRNA-1273 | 0.83 | (0.47- | 1.48) | 0.534 | ||||
| BNT162b2 | 0.81 | (0.38- | 1.79) | 0.584 | ||||
OR: odds ratio; 95% CI: 95% confidence interval; CKD: chronic kidney disease; GFR: glomerular filtration rate; BMI: body mass index; TNF: tumor necrosis factor; ABT/RTX: abatacept/rituximab; JAK: Janus kinase. Variables in multivariate model: TNFi, JAKi.
Logistic regression analysis for predicting an augmented titer of ANA.
| Baseline Variables | Univariate Model | Multivariate Model | ||||||
|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | |||||
| Age at entry, years | 1.00 | (0.98- | 1.02) | 0.707 | ||||
| Gender | ||||||||
| Male | ref. | |||||||
| Female | 2.53 | (1.00- | 6.41) | 0.05 | ||||
| Disease groups | ||||||||
| Systemic lupus erythematosus | 7.93 | (2.75- | 22.84) | 0.001 | 11.63 | (2.41- | 56.06) | 0.002 |
| Primary Sjögren’s syndrome | 0.63 | (0.32- | 1.24) | 0.182 | ||||
| Rheumatoid arthritis | 1.22 | (0.69- | 2.14) | 0.490 | ||||
| Spondyloarthropathies | 0.33 | (0.94- | 1.16) | 0.084 | ||||
| Adult-onset Still’s disease | 0.35 | (0.10- | 1.25) | 0.106 | ||||
| CKD | 0.50 | (0.18- | 1.40) | 0.189 | ||||
| The estimated GFR | 1.00 | (1.00 - | 1.02) | 0.199 | ||||
| BMI, kg/m2 | 0.95 | (0.88- | 1.03) | 0.186 | ||||
| The used medications | ||||||||
| TNF-α inhibitors | 1.26 | (0.61- | 2.60) | 0.536 | ||||
| Tocilizumab | 0.79 | (0.30- | 2.11) | 0.639 | ||||
| ABT/RTX | 1.32 | (0.46- | 3.79) | 0.606 | ||||
| JAK inhibitors | 0.47 | (0.19- | 1.12) | 0.090 | ||||
| Methotrexate | 1.09 | (0.50- | 2.40) | 0.827 | ||||
| Mycophenolate | 4.62 | (1.11- | 19.02) | 0.034 | ||||
| Corticosteroids | 1.03 | (0.59- | 1.81) | 0.919 | ||||
| Type of vaccines | ||||||||
| AZ12222 | 0.95 | (0.53- | 1.70) | 0.853 | ||||
| mRNA-1273 | 1.12 | (0.64- | 1.97) | 0.687 | ||||
| BNT162b2 | 0.88 | (0.40- | 1.96) | 0.756 | ||||
ANA: antinuclear antibodies; OR: odds ratio; 95% CI: 95% confidence interval; CKD: chronic kidney disease; GFR: glomerular filtration rate; BMI: body mass index; TNF: tumor necrosis factor; ABT/RTX: abatacept/rituximab; JAK: Janus kinase. Variables in multivariate model: gender, SLE, MMF.