Determinants and Biomarkers of Progression Independent of Relapses in Multiple Sclerosis

Reconciling lesions, relapses and smouldering associated worsening: A unifying model for multiple sclerosis pathogenesis

The failure of relapses and white matter lesions to properly explain long-term disability and progression in multiple sclerosis is compounded by its artificial separation into relapsing remitting, secondary progressive, and primary progressive pigeonholes. The well-known epidemiological disconnection between relapses and long-term disability progression has been rediscovered as "progression independent of relapse activity", i.e. smouldering multiple sclerosis. This smouldering associated worsening proceeds despite early and prolonged use of disease modification therapies, even those that are highly effective at preventing relapses and new/enhancing white matter lesions on MRI. We recognise that smouldering associated worsening and relapse/lesion associated worsening coexist, to varying extents. The extent of cortical demyelination has been shown to correlate significantly with the severity of diffuse injury in normal appearing white matter (post mortem histopathologically (r = 0.55; P = 0.001), and in vivo with MRI (r = -0.6874; P = 0.0006)) and does so independently of white matter lesion burden. Axon loss in the normal appearing white matter explains disability in multiple sclerosis better than focal white matter lesions do. Smouldering associated worsening typically manifests as a length-dependent central axonopathy. We propose a unifying model for multiple sclerosis pathogenesis, wherein accumulation of cortical lesion burden predisposes associated normal appearing white matter to diffuse injury, whilst also intensifying damage within white matter lesions. Our novel two-hit hypothesis implicates cortical disease as a culprit for smouldering multiple sclerosis, abetted by active focal inflammation in the white matter (and vice versa). Substantiation of the two-hit hypothesis would advance the importance of specific therapeutic intervention for (and monitoring of) cortical/meningeal inflammation in people with multiple sclerosis.

The influence of aging and the microbiome in multiple sclerosis and other neurologic diseases

The human gut microbiome is well-recognized as a key player in maintaining health. However, it is a dynamic entity that changes across the lifespan. How the microbial changes that occur in later decades of life shape host health or impact age-associated inflammatory neurological diseases such as multiple sclerosis (MS) is still unclear. Current understanding of the aging gut microbiome is largely limited to cross-sectional observational studies. Moreover, studies in humans are limited by confounding host-intrinsic and extrinsic factors that are not easily disentangled from aging. This review provides a comprehensive summary of existing literature on the aging gut microbiome and its known relationships with neurological diseases, with a specific focus on MS. We will also discuss preclinical animal models and human studies that shed light on the complex microbiota-host interactions that have the potential to influence disease pathology and progression in aging individuals. Lastly, we propose potential avenues of investigation to deconvolute features of an aging microbiota that contribute to disease, or alternatively promote health in advanced age.

Exploring miRNAs' Based Modeling Approach for Predicting PIRA in Multiple Sclerosis: A Comprehensive Analysis

The current hypothesis on the pathophysiology of multiple sclerosis (MS) suggests the involvement of both inflammatory and neurodegenerative mechanisms. Disease Modifying Therapies (DMTs) effectively decrease relapse rates, thus reducing relapse-associated disability in people with MS. In some patients, disability progression, however, is not solely linked to new lesions and clinical relapses but can manifest independently. Progression Independent of Relapse Activity (PIRA) significantly contributes to long-term disability, stressing the urge to unveil biomarkers to forecast disease progression. Twenty-five adult patients with relapsing-remitting multiple sclerosis (RRMS) were enrolled in a cohort study, according to the latest McDonald criteria, and tested before and after high-efficacy Disease Modifying Therapies (DMTs) (6-24 months). Through Agilent microarrays, we analyzed miRNA profiles from peripheral blood mononuclear cells. Multivariate logistic and linear models with interactions were generated. Robustness was assessed by randomization tests in R. A subset of miRNAs, correlated with PIRA, and the Expanded Disability Status Scale (EDSS), was selected. To refine the patient stratification connected to the disease trajectory, we computed a robust logistic classification model derived from baseline miRNA expression to predict PIRA status (AUC = 0.971). We built an optimal multilinear model by selecting four other miRNA predictors to describe EDSS changes compared to baseline. Multivariate modeling offers a promising avenue to uncover potential biomarkers essential for accurate prediction of disability progression in early MS stages. These models can provide valuable insights into developing personalized and effective treatment strategies.