Background: Previous studies evidenced a link between metabolic dysregulation, inflammation, and neurodegeneration in multiple sclerosis (MS). Objectives: To explore whether increased adipocyte mass expressed as body mass index (BMI) and increased serum lipids influence cerebrospinal fluid (CSF) inflammation and disease severity. Methods: In this cross-sectional study, 140 consecutive relapsing-remitting (RR)-MS patients underwent clinical assessment, BMI evaluation, magnetic resonance imaging scan, and blood and CSF collection before any specific drug treatment. The CSF levels of the following cytokines, adipocytokines, and inflammatory factors were measured: interleukin (IL)-6, IL-13, granulocyte macrophage colony-stimulating factor, leptin, ghrelin, osteoprotegerin, osteopontin, plasminogen activator inhibitor-1, resistin, and Annexin A1. Serum levels of triglycerides, total cholesterol (TC), and high-density lipoprotein cholesterol (HDL-C) were assessed. Results: A positive correlation emerged between BMI and Expanded Disability Status Scale score. Obese RR-MS patients showed higher clinical disability, increased CSF levels of the proinflammatory molecules IL-6 and leptin, and reduced concentrations of the anti-inflammatory cytokine IL-13. Moreover, both the serum levels of triglycerides and TC/HDL-C ratio showed a positive correlation with IL-6 CSF concentrations. Conclusion: Obesity and altered lipid profile are associated with exacerbated central inflammation and higher clinical disability in RR-MS at the time of diagnosis. Increased adipocytokines and lipids can mediate the negative impact of high adiposity on RR-MS course.

Delayed diagnosis and treatment initiation are associated with higher CSF levels of IL-6 and IL-8 in RR-MS, leading to worsening disease course and poor response to treatments.

Studies of brain network connectivity improved understanding on brain changes and adaptation in response to different pathologies. Synaptic plasticity, the ability of neurons to modify their connections, is involved in brain network remodeling following different types of brain damage (e.g., vascular, neurodegenerative, inflammatory). Although synaptic plasticity mechanisms have been extensively elucidated, how neural plasticity can shape network organization is far from being completely understood. Similarities existing between synaptic plasticity and principles governing brain network organization could be helpful to define brain network properties and reorganization profiles after damage. In this review, we discuss how different forms of synaptic plasticity, including homeostatic and anti-homeostatic mechanisms, could be directly involved in generating specific brain network characteristics. We propose that long-term potentiation could represent the neurophysiological basis for the formation of highly connected nodes (hubs). Conversely, homeostatic plasticity may contribute to stabilize network activity preventing poor and excessive connectivity in the peripheral nodes. In addition, synaptic plasticity dysfunction may drive brain network disruption in neuropsychiatric conditions such as Alzheimer’s disease and schizophrenia. Optimal network architecture, characterized by efficient information processing and resilience, and reorganization after damage strictly depend on the balance between these forms of plasticity.

The endocannabinoid system (ECS) has been recently recognized as a prominent promoter of the emotional homeostasis, mediating the effects of different environmental signals including rewarding and stressing stimuli. The ECS modulates the rewarding effects of environmental stimuli, influencing synaptic transmission in the dopaminergic projections to the limbic system, and mediates the neurophysiological and behavioral consequences of stress. Notably, the individual psychosocial context is another key element modulating the activity of the ECS. Finally, inflammation represents an additional factor that could alter the cannabinoid signaling in the CNS inducing a “sickness behavior,” characterized by anxiety, anhedonia, and depressive symptoms. The complex influences of the ECS on both the environmental and internal stimuli processing, make the cannabinoid-based drugs an appealing option to treat different psychiatric conditions. Although ample experimental evidence shows beneficial effects of ECS modulation on mood, scarce clinical indication limits the use of cannabis-based treatments. To better define the possible clinical indications of cannabinoid-based drugs in psychiatry, a number of issues should be better addressed, including genetic variability and psychosocial factors possibly affecting the individual response. In particular, better knowledge of the multifaceted effects of cannabinoids could help to understand how to boost their therapeutic use in anxiety and depression treatment.