Heterogeneity in multiple sclerosis. Insights from imaging, immunology and genetics

Background: Multiple sclerosis is an autoimmune disease in which disease heterogeneity is poorly understood. Improving our understanding of pathways that determine inter-patient variation generates new insights that can advance the therapeutic landscape with tailored treatment options.
Objective: By focusing on imaging, immunology and genetics, we aim to unravel how patients differ from one another and how mechanistically different treatments can target similar pathways.
Results: Using flow cytometry, we found that carrying the CD40 risk allele that increases susceptibility to multiple sclerosis lowers the cell-surface expression of CD40 in all tested B cell subsets. Moreover, the CD40 risk allele resulted in lower total CD40 expression but with an increased proportion of alternative splice-forms leading to decoy receptors. In addition, the CD40 risk allele was associated with decreased levels of IL-10. Intriguingly, the CD40 risk allele conveys protection to other antibody-driven autoimmune diseases. Furthermore, we showed that the magnetization transfer ratio (MTR, a semi-quantitative measure for myelin content) and volumetric brain MRI traits are primarily influenced by unidentified patient-specific factors. Variation over time and demographical variables such as age, gender and disease duration explained much less of the observed variance. Along this line, also the genetic risk score of multiple sclerosis susceptibility variants was not convincingly associated with MTR or volumetric indices. The latter implies that susceptibility and heterogeneity are not driven by the same genetic factors. Conversely, we identified two independent novel associations (rs6982453; rs3729856) on chr8p23 near FDFT1 and CTSB with susceptibility to demyelination across three tissues (lower peak height MTR in normal-appering white matter, normal-appearing grey matter and lesions). In addition, we looked at how two different multiple sclerosis treatments induce similar peripheral B cell changes. Both interferon-beta (IFNB) and fingolimod induce B cell-activating factor (BAFF) without affecting the proportion of the antagonizing spliceform. Importantly, BAFF-induced BAFF receptor signalling might redirect the B cell compartment towards a more immature state. This is the only known shared mechanism across IFNB, fingolimod and many other established multiple sclerosis treatments. Although suggested by multiple sclerosis animal models, BAFF-induced IL-10 signalling, CD40-induced IL-10 signalling and IL-35 were not involved in the IFNB- or fingolimod-induced regulatory immune state.
Conclusion: Our data emphasize that multiple sclerosis patients differ in remyelinating potential as well as genetic and immunological composition. Baseline differences likely shape the response to treatment and different treatments ultimately target the same pathways. Understanding these processes allows evolving towards heterogeneity-based patient management.