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      Antibody development after COVID-19 vaccination in patients with autoimmune diseases in the Netherlands: a substudy of data from two prospective cohort studies

      research-article
      , BSc a , * , , PhD b , , BSc a , , BSc a , , PhD d , , MD b , g , , MD g , , MD g , , PhD h , , MSc b , , MSc b , , PhD c , , Prof, PhD e , , PhD g , , PhD g , , Prof, PhD j , , Prof, PhD i , , Prof, PhD b , k , , PhD j , , Prof, PhD d , , Prof, PhD f , j , , Prof, PhD a , j , , PhD b , l , , PhD a , j
      The Lancet. Rheumatology
      Published by Elsevier Ltd.

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          Abstract

          Background

          Data are scarce on immunogenicity of COVID-19 vaccines in patients with autoimmune diseases, who are often treated with immunosuppressive drugs. We aimed to investigate the effect of different immunosuppressive drugs on antibody development after COVID-19 vaccination in patients with autoimmune diseases.

          Methods

          In this study, we used serum samples collected from patients with autoimmune diseases and healthy controls who were included in two ongoing prospective cohort studies in the Netherlands. Participants were eligible for inclusion in this substudy if they had been vaccinated with any COVID-19 vaccine via the Dutch national vaccine programme, which at the time was prioritising vaccination of older individuals. Samples were collected after the first or second COVID-19 vaccination. No serial samples were collected. Seroconversion rates and IgG antibody titres against the receptor-binding domain of the SARS-CoV-2 spike protein were measured. Logistic and linear regression analyses were used to investigate the association between medication use at the time of vaccination and at least until sampling, seroconversion rates, and IgG antibody titres. The studies from which data were collected are registered on the Netherlands Trial Register, Trial ID NL8513, and ClinicalTrials.org, NCT04498286.

          Findings

          Between April 26, 2020, and March 1, 2021, 3682 patients with rheumatic diseases, 546 patients with multiple sclerosis, and 1147 healthy controls were recruited to participate in the two prospective cohort studies. Samples were collected from patients with autoimmune diseases (n=632) and healthy controls (n=289) after their first (507 patients and 239 controls) or second (125 patients and 50 controls) COVID-19 vaccination. The mean age of both patients and controls was 63 years (SD 11), and 423 (67%) of 632 patients with autoimmune diseases and 195 (67%) of 289 controls were female. Among participants without previous SARS-CoV-2 infection, seroconversion after first vaccination were significantly lower in patients than in controls (210 [49%] of 432 patients vs 154 [73%] of 210 controls; adjusted odds ratio 0·33 [95% CI 0·23–0·48]; p<0·0001), mainly due to lower seroconversion in patients treated with methotrexate or anti-CD20 therapies. After the second vaccination, seroconversion exceeded 80% in all patient treatment subgroups, except among those treated with anti-CD20 therapies (three [43%] of seven patients). We observed no difference in seroconversion and IgG antibody titres between patients with a previous SARS-CoV-2 infection who had received a single vaccine dose (72 [96%] of 75 patients, median IgG titre 127 AU/mL [IQR 27–300]) and patients without a previous SARS-CoV-2 infection who had received two vaccine doses (97 [92%] of 106 patients, median IgG titre 49 AU/mL [17–134]).

          Interpretation

          Our data suggest that seroconversion after a first COVID-19 vaccination is delayed in older patients on specific immunosuppressive drugs, but that second or repeated exposure to SARS-CoV-2, either via infection or vaccination, improves humoral immunity in patients treated with immunosuppressive drugs. Therefore, delayed second dosing of COVID-19 vaccines should be avoided in patients receiving immunosuppressive drugs. Future studies that include younger patients need to be done to confirm the generalisability of our results.

          Funding

          ZonMw, Reade Foundation, and MS Center Amsterdam.

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          Most cited references29

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          Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine

          Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the resulting coronavirus disease 2019 (Covid-19) have afflicted tens of millions of people in a worldwide pandemic. Safe and effective vaccines are needed urgently. Methods In an ongoing multinational, placebo-controlled, observer-blinded, pivotal efficacy trial, we randomly assigned persons 16 years of age or older in a 1:1 ratio to receive two doses, 21 days apart, of either placebo or the BNT162b2 vaccine candidate (30 μg per dose). BNT162b2 is a lipid nanoparticle–formulated, nucleoside-modified RNA vaccine that encodes a prefusion stabilized, membrane-anchored SARS-CoV-2 full-length spike protein. The primary end points were efficacy of the vaccine against laboratory-confirmed Covid-19 and safety. Results A total of 43,548 participants underwent randomization, of whom 43,448 received injections: 21,720 with BNT162b2 and 21,728 with placebo. There were 8 cases of Covid-19 with onset at least 7 days after the second dose among participants assigned to receive BNT162b2 and 162 cases among those assigned to placebo; BNT162b2 was 95% effective in preventing Covid-19 (95% credible interval, 90.3 to 97.6). Similar vaccine efficacy (generally 90 to 100%) was observed across subgroups defined by age, sex, race, ethnicity, baseline body-mass index, and the presence of coexisting conditions. Among 10 cases of severe Covid-19 with onset after the first dose, 9 occurred in placebo recipients and 1 in a BNT162b2 recipient. The safety profile of BNT162b2 was characterized by short-term, mild-to-moderate pain at the injection site, fatigue, and headache. The incidence of serious adverse events was low and was similar in the vaccine and placebo groups. Conclusions A two-dose regimen of BNT162b2 conferred 95% protection against Covid-19 in persons 16 years of age or older. Safety over a median of 2 months was similar to that of other viral vaccines. (Funded by BioNTech and Pfizer; ClinicalTrials.gov number, NCT04368728.)
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            Characteristics associated with hospitalisation for COVID-19 in people with rheumatic disease: data from the COVID-19 Global Rheumatology Alliance physician-reported registry

            Objectives COVID-19 outcomes in people with rheumatic diseases remain poorly understood. The aim was to examine demographic and clinical factors associated with COVID-19 hospitalisation status in people with rheumatic disease. Methods Case series of individuals with rheumatic disease and COVID-19 from the COVID-19 Global Rheumatology Alliance registry: 24 March 2020 to 20 April 2020. Multivariable logistic regression was used to estimate ORs and 95% CIs of hospitalisation. Age, sex, smoking status, rheumatic disease diagnosis, comorbidities and rheumatic disease medications taken immediately prior to infection were analysed. Results A total of 600 cases from 40 countries were included. Nearly half of the cases were hospitalised (277, 46%) and 55 (9%) died. In multivariable-adjusted models, prednisone dose ≥10 mg/day was associated with higher odds of hospitalisation (OR 2.05, 95% CI 1.06 to 3.96). Use of conventional disease-modifying antirheumatic drug (DMARD) alone or in combination with biologics/Janus Kinase inhibitors was not associated with hospitalisation (OR 1.23, 95% CI 0.70 to 2.17 and OR 0.74, 95% CI 0.37 to 1.46, respectively). Non-steroidal anti-inflammatory drug (NSAID) use was not associated with hospitalisation status (OR 0.64, 95% CI 0.39 to 1.06). Tumour necrosis factor inhibitor (anti-TNF) use was associated with a reduced odds of hospitalisation (OR 0.40, 95% CI 0.19 to 0.81), while no association with antimalarial use (OR 0.94, 95% CI 0.57 to 1.57) was observed. Conclusions We found that glucocorticoid exposure of ≥10 mg/day is associated with a higher odds of hospitalisation and anti-TNF with a decreased odds of hospitalisation in patients with rheumatic disease. Neither exposure to DMARDs nor NSAIDs were associated with increased odds of hospitalisation.
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              False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies.

              Procedures for controlling the false positive rate when performing many hypothesis tests are commonplace in health and medical studies. Such procedures, most notably the Bonferroni adjustment, suffer from the problem that error rate control cannot be localized to individual tests, and that these procedures do not distinguish between exploratory and/or data-driven testing vs. hypothesis-driven testing. Instead, procedures derived from limiting false discovery rates may be a more appealing method to control error rates in multiple tests. Controlling the false positive rate can lead to philosophical inconsistencies that can negatively impact the practice of reporting statistically significant findings. We demonstrate that the false discovery rate approach can overcome these inconsistencies and illustrate its benefit through an application to two recent health studies. The false discovery rate approach is more powerful than methods like the Bonferroni procedure that control false positive rates. Controlling the false discovery rate in a study that arguably consisted of scientifically driven hypotheses found nearly as many significant results as without any adjustment, whereas the Bonferroni procedure found no significant results. Although still unfamiliar to many health researchers, the use of false discovery rate control in the context of multiple testing can provide a solid basis for drawing conclusions about statistical significance. Copyright © 2014 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Lancet Rheumatol
                Lancet Rheumatol
                The Lancet. Rheumatology
                Published by Elsevier Ltd.
                2665-9913
                6 August 2021
                6 August 2021
                Affiliations
                [a ]Amsterdam Rheumatology and Immunology Center, location Reade, Department of Rheumatology, Amsterdam, Netherlands
                [b ]Department of Immunopathology, Amsterdam, Netherlands
                [c ]Department of Experimental Immunohematology, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, Amsterdam, Netherlands
                [d ]Department of Neurology, Amsterdam, Netherlands
                [e ]Department of Rheumatology and Clinical Immunology, Amsterdam, Netherlands
                [f ]Department of Epidemiology and Data Science, Vrije Universiteit, Amsterdam UMC, Amsterdam, Netherlands
                [g ]Department of Neurology and Neurophysiology, Amsterdam Neuroscience, University of Amsterdam, Amsterdam, Netherlands
                [h ]Department of Medical Microbiology and Infection Control, University of Amsterdam, Amsterdam, Netherlands
                [i ]Department of Pediatric Immunology, Rheumatology and Infectious Disease, Amsterdam UMC, location AMC, University of Amsterdam, Amsterdam, Netherlands
                [j ]Department of Rheumatology, Amsterdam Rheumatology and Immunology Center, Amsterdam, Netherlands
                [k ]Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
                [l ]Biologics Lab, Sanquin Diagnostic Services, Amsterdam, Netherlands
                Author notes
                [* ]Correspondence to: Dr Laura Boekel, Amsterdam Rheumatology and Immunology Center, location Reade, Department of Rheumatology, Amsterdam, Netherlands
                Article
                S2665-9913(21)00222-8
                10.1016/S2665-9913(21)00222-8
                8346242
                34396154
                ef7c4252-c02a-4dcc-bd26-a867248360b5
                © 2021 Published by Elsevier Ltd.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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