Biomarker combinations from different modalities predict early disability accumulation in multiple sclerosis.

IF 5.9 2区 医学 Q1 IMMUNOLOGY Frontiers in Immunology Pub Date : 2025-01-31 eCollection Date: 2025-01-01 DOI:10.3389/fimmu.2025.1532660
Vinzenz Fleischer, Tobias Brummer, Muthuraman Muthuraman, Falk Steffen, Milena Heldt, Maria Protopapa, Muriel Schraad, Gabriel Gonzalez-Escamilla, Sergiu Groppa, Stefan Bittner, Frauke Zipp
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Abstract

Objective: Establishing biomarkers to predict multiple sclerosis (MS) disability accrual has been challenging using a single biomarker approach, likely due to the complex interplay of neuroinflammation and neurodegeneration. Here, we aimed to investigate the prognostic value of single and multimodal biomarker combinations to predict four-year disability progression in patients with MS.

Methods: In total, 111 MS patients were followed up for four years to track disability accumulation based on the Expanded Disability Status Scale (EDSS). Three clinically relevant modalities (MRI, OCT and blood serum) served as sources of potential predictors for disease worsening. Two key measures from each modality were determined and related to subsequent disability progression: lesion volume (LV), gray matter volume (GMV), retinal nerve fiber layer, ganglion cell-inner plexiform layer, serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein. First, receiver operator characteristic (ROC) analyses were performed to identify the discriminative power of individual biomarkers and their combinations. Second, we applied structural equation modeling (SEM) to the single biomarkers in order to determine their causal inter-relationships.

Results: Baseline GMV on its own allowed identification of subsequent EDSS progression based on ROC analysis. All other individual baseline biomarkers were unable to discriminate between progressive and non-progressive patients on their own. When comparing all possible biomarker combinations, the tripartite combination of MRI, OCT and blood biomarkers achieved the highest discriminative accuracy. Finally, predictive causal modeling identified that LV mediates significant parts of the effect of GMV and sNfL on disability progression.

Conclusion: Multimodal biomarkers, i.e. different major surrogates for pathology derived from MRI, OCT and blood, inform about different parts of the disease pathology leading to clinical progression.

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不同方式的生物标志物组合预测多发性硬化症的早期残疾积累。
目的:建立生物标志物来预测多发性硬化症(MS)残疾累积一直是一个挑战,使用单一的生物标志物方法,可能是由于神经炎症和神经变性的复杂相互作用。在这里,我们的目的是研究单一和多模式生物标志物组合在预测MS患者4年残疾进展方面的预后价值。方法:总共有111名MS患者进行了4年的随访,根据扩展残疾状态量表(EDSS)跟踪残疾积累。三种临床相关模式(MRI、OCT和血清)是疾病恶化的潜在预测因素。从每种模式中确定了与随后的残疾进展相关的两个关键指标:病变体积(LV)、灰质体积(GMV)、视网膜神经纤维层、神经节细胞-内丛状层、血清神经丝轻链(sNfL)和血清胶质纤维酸性蛋白。首先,进行受试者操作特征(ROC)分析,以确定个体生物标志物及其组合的鉴别能力。其次,我们将结构方程模型(SEM)应用于单个生物标志物,以确定它们之间的因果关系。结果:基线GMV本身可以根据ROC分析识别随后的EDSS进展。所有其他个体基线生物标志物本身无法区分进展性和非进展性患者。在比较所有可能的生物标志物组合时,MRI、OCT和血液生物标志物的三方组合获得了最高的判别准确性。最后,预测因果模型发现,LV介导了GMV和sNfL对残疾进展的重要影响。结论:多模式生物标志物,即来自MRI、OCT和血液的不同主要病理学替代物,可告知导致临床进展的疾病病理的不同部分。
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来源期刊
CiteScore
9.80
自引率
11.00%
发文量
7153
审稿时长
14 weeks
期刊介绍: Frontiers in Immunology is a leading journal in its field, publishing rigorously peer-reviewed research across basic, translational and clinical immunology. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide. Frontiers in Immunology is the official Journal of the International Union of Immunological Societies (IUIS). Encompassing the entire field of Immunology, this journal welcomes papers that investigate basic mechanisms of immune system development and function, with a particular emphasis given to the description of the clinical and immunological phenotype of human immune disorders, and on the definition of their molecular basis.
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