Editor’s summary: The autoimmune disease multiple sclerosis (MS) is a highly heterogeneous disease with many different treatment options. However, it is not clear whether certain features of MS are associated with distinct immune signatures or would benefit from particular therapies. Here, Gross et al. used peripheral blood mononuclear cells and serum collected from two independent cohorts of patients with MS to identify three endophenotypes of the disease. These peripheral blood immune signatures distinguished patients with distinct clinical disease trajectories and efficacy of interferon-β treatment. These data suggest that peripheral blood analysis could be used to guide personalized treatment regimens for patients with MS.

Abstract:  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.