Predictive MRI Biomarkers in MS—A Critical Review

2.5-Year changes of connectivity dynamism are relevant for physical and cognitive deterioration in multiple sclerosis

BACKGROUND

In MS, functional connectivity (FC) dynamism may influence disease evolution.

OBJECTIVES

The objective is to assess time-varying functional connectivity (TVFC) changes over time at 2.5-year follow-up in MS patients according to physical and cognitive worsening.

METHODS

We collected 3T magnetic resonance imaging (MRI) for TVFC assessment (performed using sliding-window analysis of centrality) and clinical evaluations at baseline and 2.5-year follow-up from 28 healthy controls and 129 MS patients. Of these, 79 underwent baseline and follow-up neuropsychological assessment. At 2.5 years, physical/cognitive worsening was defined according to disability/neuropsychological score changes.

RESULTS

At follow-up, 25/129 (19.3%) MS patients worsened physically and 14/79 (17.7%) worsened cognitively. At baseline, MS patients showed reduced TVFC versus controls. At 2.5-year follow-up, no TVFC changes were detected in controls. Conversely, TVFC decreased over time in parieto-temporal regions in stable MS patients and in default-mode network in worsened MS. In physically worsened MS, basal ganglia TVFC reductions were also found. Reduced TVFC over time in the putamen in physically worsened and reduced TVFC in the precuneus in cognitively worsened were significant versus stable MS.

DISCUSSION

At 2.5-year follow-up, default-mode network TVFC reductions were found in worsening MS. Moreover, reduced deep gray matter TVFC characterized physically worsened patients, whereas precuneus involvement characterized cognitively worsened MS patients.

Prognostic relevance of MRI in early relapsing multiple sclerosis: ready to guide treatment decision making?

Magnetic resonance imaging (MRI) of the brain and spinal cord plays a crucial role in the diagnosis and monitoring of multiple sclerosis (MS). There is conclusive evidence that brain and spinal cord MRI findings in early disease stages also provide relevant insight into individual prognosis. This includes prediction of disease activity and disease progression, the accumulation of long-term disability and the conversion to secondary progressive MS. The extent to which these MRI findings should influence treatment decisions remains a subject of ongoing discussion. The aim of this review is to present and discuss the current knowledge and scientific evidence regarding the utility of MRI at early MS disease stages for prognostic classification of individual patients. In addition, we discuss the current evidence regarding the use of MRI in order to predict treatment response. Finally, we propose a potential approach as to how MRI data may be categorized and integrated into early clinical decision making.

Should autologous hematopoietic stem cell transplantation be offered as a first-line disease modifying therapy to patients with multiple sclerosis?

In multiple sclerosis (MS), progression independent of new focal inflammation may commence shortly after disease onset, and it is increasingly revealed that the risk of disability accrual is reduced by early use of high-efficacy disease-modifying therapies (HE-DMTs). People with aggressive MS may therefore benefit from early treatment with autologous haematopoietic stem cell transplantation (AHSCT), a procedure inducing maximal immunosuppression followed by immune reconstitution, demonstrated to be superior to DMTs in one randomized clinical trial. However, in current practice prior failure to HE-DMTs is typically required to establish the indication for AHSCT. In the present article, the available evidence on the potential role of AHSCT as first-line treatment in aggressive MS and the rationale for its early use will be summarized. Proposed definitions of aggressive MS that could help identifying MS patients eligible for early treatment with AHSCT will also be discussed.

Serum Neurofilaments and OCT Metrics Predict EDSS-Plus Score Progression in Early Relapse-Remitting Multiple Sclerosis

(1) Background: Early disability accrual in RRMS patients is frequent and is associated with worse long-term prognosis. Correctly identifying the patients that present a high risk of early disability progression is of utmost importance, and may be aided by the use of predictive biomarkers. (2) Methods: We performed a prospective cohort study that included newly diagnosed RRMS patients, with a minimum follow-up period of one year. Biomarker samples were collected at baseline, 3-, 6- and 12-month follow-ups. Disability progression was measured using the EDSS-plus score. (3) Results: A logistic regression model based on baseline and 6-month follow-up sNfL z-scores, RNFL and GCL-IPL thickness and BREMSO score was statistically significant, with χ2(4) = 19.542, p < 0.0001, R2 = 0.791. The model correctly classified 89.1% of cases, with a sensitivity of 80%, a specificity of 93.5%, a positive predictive value of 85.7% and a negative predictive value of 90.62%. (4) Conclusions: Serum biomarkers (adjusted sNfL z-scores at baseline and 6 months) combined with OCT metrics (RNFL and GCL-IPL layer thickness) and the clinical score BREMSO can accurately predict early disability progression using the EDSS-plus score for newly diagnosed RRMS patients.

Insight into Early Diagnosis of Multiple Sclerosis by Targeting Prognostic Biomarkers

Multiple sclerosis (MS) is a central nervous system (CNS) immune-mediated disease that mainly strikes young adults and leaves them disabled. MS is an autoimmune illness that causes the immune system to attack the brain and spinal cord. The myelin sheaths, which insulate the nerve fibers, are harmed by our own immune cells, and this interferes with brain signal transmission. Numbness, tingling, mood swings, memory problems, exhaustion, agony, vision problems, and/or paralysis are just a few of the symptoms. Despite technological advancements and significant research efforts in recent years, diagnosing MS can still be difficult. Each patient's MS is distinct due to a heterogeneous and complex pathophysiology with diverse types of disease courses. There is a pressing need to identify markers that will allow for more rapid and accurate diagnosis and prognosis assessments to choose the best course of treatment for each MS patient. The cerebrospinal fluid (CSF) is an excellent source of particular indicators associated with MS pathology. CSF contains molecules that represent pathological processes such as inflammation, cellular damage, and loss of blood-brain barrier integrity. Oligoclonal bands, neurofilaments, MS-specific miRNA, lncRNA, IgG-index, and anti-aquaporin 4 antibodies are all clinically utilised indicators for CSF in MS diagnosis. In recent years, a slew of new possible biomarkers have been presented. In this review, we look at what we know about CSF molecular markers and how they can aid in the diagnosis and differentiation of different MS forms and treatment options, and monitoring and predicting disease progression, therapy response, and consequences during such opportunistic infections.

Serum and CSF Biomarkers Predict Active Early Cognitive Decline Rather Than Established Cognitive Impairment at the Moment of RRMS Diagnosis

(1) Background: Cognitive impairment (CI) begins early in the evolution of multiple sclerosis (MS) but may only become obvious in the later stages of the disease. Little data is available regarding predictive biomarkers for early, active cognitive decline in relapse remitting MS (RRMS) patients. (2) Methods: 50 RRMS patients in the first 6 months following diagnosis were included. The minimum follow-up was one year. Biomarker samples were collected at baseline, 3-, 6- and 12-month follow-up. Cognitive performance was assessed at baseline and 12-month follow-up; (3) Results: Statistically significant differences were found for patients undergoing active cognitive decline for sNfL z-scores at baseline and 3 months, CSF NfL baseline values, CSF Aβ42 and the Bremso score as well. The logistic regression model based on these 5 variables was statistically significant, χ2(4) = 22.335, p < 0.0001, R2 = 0.671, with a sensitivity of 57.1%, specificity of 97.4%, a positive predictive value of 80% and a negative predictive value of 92.6%. (4) Conclusions: Our study shows that serum biomarkers (adjusted sNfL z-scores at baseline and 3 months) and CSF biomarkers (CSF NfL baseline values, CSF Aβ42), combined with a clinical score (BREMSO), can accurately predict an early cognitive decline for RRMS patients at the moment of diagnosis.

Neurodegeneration in Multiple Sclerosis: The Role of Nrf2-Dependent Pathways

Multiple sclerosis (MS) encompasses a chronic, irreversible, and predominantly immune-mediated disease of the central nervous system that leads to axonal degeneration, neuronal death, and several neurological symptoms. Although various immune therapies have reduced relapse rates and the severity of symptoms in relapsing-remitting MS, there is still no cure for this devastating disease. In this brief review, we discuss the role of mitochondria dysfunction in the progression of MS, focused on the possible role of Nrf2 signaling in orchestrating the impairment of critical cellular and molecular aspects such as reactive oxygen species (ROS) management, under neuroinflammation and neurodegeneration in MS. In this scenario, we propose a new potential downstream signaling of Nrf2 pathway, namely the opening of hemichannels and pannexons. These large-pore channels are known to modulate glial/neuronal function and ROS production as they are permeable to extracellular Ca²⁺ and release potentially harmful transmitters to the synaptic cleft. In this way, the Nrf2 dysfunction impairs not only the bioenergetics and metabolic properties of glial cells but also the proper antioxidant defense and energy supply that they provide to neurons.