COVID-19 Vaccine Boosters in People With Multiple Sclerosis: Improved SARS-CoV-2 Cross-Variant Antibody Response and Prediction of Protection.

IF 7.8 1区 医学 Q1 CLINICAL NEUROLOGY
Avani Yeola, Samuel Houston, Anupriya Aggarwal, Rashmi Gamage, Vicki E Maltby, Marzena J Fabis-Pedrini, Linh Le-Kavanagh, Vera Merheb, Kristy Nguyen, Fiona X Z Lee, Susan Walters, Marinda Taha, Annmaree O'Connell, Vilija G Jokubaitis, Angie Roldan, Mastura Monif, Helmut Butzkueven, Sandeep Sampangi, Louise Rath, Katherine Fazzolari, Todd A Hardy, Heidi N Beadnall, Michael H Barnett, Allan G Kermode, Christopher Dwyer, Tomas Kalincik, Simon A Broadley, Stuart G Turville, Stephen W Reddel, Sudarshini Ramanathan, Jeannette Lechner-Scott, Anneke Van Der Walt, Fabienne Brilot
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引用次数: 0

Abstract

Background and objectives: Although disease-modifying therapies (DMTs) may suppress coronavirus disease 2019 (COVID-19) vaccine responses in people with multiple sclerosis (pwMS), limited data are available on the cumulative effect of additional boosters. Maturation of Spike immunoglobulin G (IgG) to target a greater diversity of SARS-CoV-2 variants, especially past the BA.1 variant, has not been reported. In addition, the prediction of variant-specific protection, given that Spike antibody testing is not performed routinely, remains a challenge. We, therefore, evaluated whether additional vaccine doses improved the breadth of cross-variant recognition to target emerging SARS-CoV-2 variants. Machine learning-based models were designed to predict variant-specific protection status.

Methods: In a prospective observational cohort (n = 442), Spike IgG titers and live virus neutralization against D614, BA.1, BA.2, BA.5, XBB.1.1, XBB.1.5, and EG.5.1 variants were determined in 1,011 serum samples (0-12 months after 2-4 doses). Predictive protection models were developed by K-fold cross-validation on training and test data sets (random split 70:30).

Results: After primary vaccination, pwMS on immunosuppressive disease-modifying therapy (IMM-DMT) had 10-fold and 7.2-fold lower D614 Spike IgG titers than pwMS on low-efficacy (LE)-DMT and cladribine (p < 0.01). After 4 doses, pwMS on IMM-DMT had significantly lower Spike IgG titers, compared with pwMS on low-efficacy disease-modifying therapy, for D614 (p < 0.05), as well as BA.1, BA.2, BA.5, XBB.1, XBB.1.5, and EG.5.1(p < 0.01). The breadth of Spike IgG to recognize variants other than the cognate antigen increased after 4 doses of all DMTs. Although pwMS on IMM-DMT displayed reduced cross-variant recognition, a fourth dose resulted in a 2-4-fold increase in protection against newer variants and a reduction in two-thirds of pwMS without protective Spike IgG (p < 0.0001). Tixagevimab and cilgavimab did not induce additional cross-variant protection. Variant-specific predictive models of vaccine protection were influenced by treatment, time since primary vaccination, and age, with high sensitivity (99.4%, 95% CI 96.8-99.99) and specificity (72.0%, 95% CI 50.6-87.9) for XBB.1.5/EG.5.1 variants.

Discussion: Despite not eliciting adequate antibody response in pwMS on IMM-DMT, COVID-19 boosters improve the breadth of the humoral response against SARS-CoV-2 emerging variants. Vaccine protection can be predicted by statistical modeling.

多发性硬化症患者的COVID-19疫苗增强剂:改善SARS-CoV-2交叉变异抗体反应和预测保护作用
背景和目的:虽然疾病修饰疗法(dmt)可能会抑制多发性硬化症(pwMS)患者的2019冠状病毒病(COVID-19)疫苗反应,但关于额外增强剂的累积效应的数据有限。刺突免疫球蛋白G (IgG)成熟以靶向更多样化的SARS-CoV-2变体,特别是经过BA.1变体,尚未报道。此外,鉴于Spike抗体检测没有常规进行,预测变异特异性保护仍然是一个挑战。因此,我们评估了额外的疫苗剂量是否提高了针对新出现的SARS-CoV-2变体的交叉变体识别的广度。设计了基于机器学习的模型来预测特定变体的保护状态。方法:在前瞻性观察队列(n = 442)中,检测1011份血清样本(2-4次给药后0-12个月)的Spike IgG滴度和针对D614、BA.1、BA.2、BA.5、XBB.1.1、XBB.1.5和EG.5.1变体的活病毒中和作用。对训练和测试数据集(随机分割70:30)进行K-fold交叉验证,建立预测保护模型。结果:初次接种后,免疫抑制疾病改善疗法(IMM-DMT)组的D614 Spike IgG滴度分别比低效(LE)-DMT组和克拉德里平组低10倍和7.2倍(p < 0.01)。4次给药后,IMM-DMT治疗的pwMS对D614、BA.1、BA.2、BA.5、XBB.1、XBB.1.5和EG.5.1的Spike IgG滴度显著低于低疗效改善治疗的pwMS (p < 0.05) (p < 0.01)。所有DMTs 4次剂量后,Spike IgG识别同源抗原以外的变异的宽度增加。虽然IMM-DMT上的pwMS显示出交叉变异识别降低,但第四次剂量导致对新变异的保护增加2-4倍,并且在没有保护性Spike IgG的情况下减少了三分之二的pwMS (p < 0.0001)。替昔格韦单抗和西加维单抗没有诱导额外的交叉变异保护。疫苗保护的变异特异性预测模型受治疗、初次接种后的时间和年龄的影响,对XBB.1.5/EG.5.1变异具有高敏感性(99.4%,95% CI 96.5 -99.99)和特异性(72.0%,95% CI 50.6-87.9)。讨论:尽管在IMM-DMT的pwMS中没有引起足够的抗体反应,但COVID-19增强剂提高了针对SARS-CoV-2新变体的体液反应的广度。疫苗保护可以通过统计建模来预测。
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来源期刊
CiteScore
15.60
自引率
2.30%
发文量
219
审稿时长
8 weeks
期刊介绍: Neurology Neuroimmunology & Neuroinflammation is an official journal of the American Academy of Neurology. Neurology: Neuroimmunology & Neuroinflammation will be the premier peer-reviewed journal in neuroimmunology and neuroinflammation. This journal publishes rigorously peer-reviewed open-access reports of original research and in-depth reviews of topics in neuroimmunology & neuroinflammation, affecting the full range of neurologic diseases including (but not limited to) Alzheimer's disease, Parkinson's disease, ALS, tauopathy, and stroke; multiple sclerosis and NMO; inflammatory peripheral nerve and muscle disease, Guillain-Barré and myasthenia gravis; nervous system infection; paraneoplastic syndromes, noninfectious encephalitides and other antibody-mediated disorders; and psychiatric and neurodevelopmental disorders. Clinical trials, instructive case reports, and small case series will also be featured.
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