| Literature DB >> 28424654 |
Elizabeth A Mills1, Ali Mirza2, Yang Mao-Draayer2,3.
Abstract
The autoimmune disease multiple sclerosis (MS) is characterized by relapses in the majority of patients. A definitive clinical diagnosis of relapse in MS can be complicated by the presence of an infection or comorbid disorder. In this mini-review, we describe efforts to develop enhanced imaging techniques and biomarker detection as future tools for relapse validation. There is emerging evidence of roles for meningeal inflammation, sex hormones, comorbid metabolic or mood disorders, and a dysregulated immune profile in the manifestation and severity of relapse. Specific subsets of immune cells likely drive the pathophysiology of relapse, and identification of a patient's unique immunological signature of relapse may help guide future diagnosis and treatment. Finally, these studies highlight the diversity in terms of relapse presentation, immunological signature, and response in patients with MS, indicating that going forward the best approach to assessment and treatment of relapse will be multifactorial and highly personalized.Entities:
Keywords: biomarker; comorbidity; cortical lesion; estrogen; pseudo-relapse
Year: 2017 PMID: 28424654 PMCID: PMC5372802 DOI: 10.3389/fneur.2017.00116
Source DB: PubMed Journal: Front Neurol ISSN: 1664-2295 Impact factor: 4.003
Figure 1Emerging methods to validate and monitor treatment for multiple sclerosis (MS) relapse. This schematic provides an outline of how currently available and emerging tools could be used to help validate the diagnosis of MS relapse, as determined through a physical exam. Assessment scales are currently the easiest, but subject to patient biases, and advanced imaging techniques the most reliable, but least accessible. Biomarkers are emerging as a new avenue to bridge this divide, but still require further clinical validation. Diagnosis can be confounded by comorbid disorders, the presence of which can also impact treatment decisions. If patients are diagnosed with a true relapse, the choice of treatment will depend on severity, and effectiveness can be monitored using the relapse validation tools.