Multiple sclerosis endophenotypes identified by high-dimensional blood signatures are associated with distinct disease trajectories.
Catharina C GrossAndreas Schulte-MecklenbeckOlga V SteinbergTimo WirthSarah LauksStefan BittnerPatrick SchindlerSergio E BaranziniSergiu GroppaJudith Bellmann-StroblNora BüngerClaudia ChienEva DawinMaria EveslageVinzenz FleischerGabriel González-EscamillaBarbara GiseviusJürgen HaasMartin KerschensteinerLucienne KirsteinCatharina KorsukewitzLisa LohmannJan D LünemannFelix LuessiGerd Meyer Zu HörsteJeremias MotteTobias RuckKlemens RuprechtNicholas SchwabFalk SteffenSven Guenther MeuthFriedemann PaulBrigitte WildemannTania KümpfelRalf GoldTim HahnFrauke ZippLuisa KlotzHeinz Wiendlnull nullPublished in: Science translational medicine (2024)
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.
Keyphrases
- multiple sclerosis
- single cell
- depressive symptoms
- flow cytometry
- oxidative stress
- peripheral blood
- magnetic resonance imaging
- mass spectrometry
- machine learning
- small molecule
- dendritic cells
- combination therapy
- gene expression
- immune response
- white matter
- magnetic resonance
- electronic health record
- diffusion weighted imaging