内表型
多发性硬化
疾病
免疫系统
医学
个性化医疗
生物信息学
生物
免疫学
内科学
认知
精神科
作者
Catharina C. Groß,Andreas Schulte‐Mecklenbeck,Olga V. Steinberg,Timo Wirth,Sarah Lauks,Stefan Bittner,Patrick Schindler,Sergio E. Baranzini,Sergiu Groppa,Judith Bellmann–Strobl,Nora Bünger,Claudia Chien,Eva Dawin,Maria Eveslage,Vinzenz Fleischer,Gabriel González‐Escamilla,Barbara Gisevius,Jürgen Haas,Martin Kerschensteiner,Lucienne Kirstein
出处
期刊:Science Translational Medicine
[American Association for the Advancement of Science (AAAS)]
日期:2024-03-27
卷期号:16 (740): eade8560-eade8560
被引量:33
标识
DOI:10.1126/scitranslmed.ade8560
摘要
One of the biggest challenges in managing multiple sclerosis is the heterogeneity of clinical manifestations and progression trajectories. It still remains to be elucidated whether this heterogeneity is reflected by discrete immune signatures in the blood as a surrogate of disease pathophysiology. Accordingly, individualized treatment selection based on immunobiological principles is still not feasible. Using two independent multicentric longitudinal cohorts of patients with early multiple sclerosis ( n = 309 discovery and n = 232 validation), we were able to identify three distinct peripheral blood immunological endophenotypes by a combination of high-dimensional flow cytometry and serum proteomics, followed by unsupervised clustering. Longitudinal clinical and paraclinical follow-up data collected for the cohorts revealed that these endophenotypes were associated with disease trajectories of inflammation versus early structural damage. Investigating the capacity of immunotherapies to normalize endophenotype-specific immune signatures revealed discrete effect sizes as illustrated by the limited effect of interferon-β on endophenotype 3–related immune signatures. Accordingly, patients who fell into endophenotype 3 subsequently treated with interferon-β exhibited higher disease progression and MRI activity over a 4-year follow-up compared with treatment with other therapies. We therefore propose that ascertaining a patient’s blood immune signature before immunomodulatory treatment initiation may facilitate prediction of clinical disease trajectories and enable personalized treatment decisions based on pathobiological principles.
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