Relapses are a characteristic clinical feature of multiple sclerosis (MS), but an appreciation of factors that cause them remains elusive. In this study, we have examined seasonal variation of relapse in a large population-based MS cohort and correlated observed patterns with age, sex, disease course, and climatic factors. Relapse data were recorded prospectively in 2076 patients between 2005 and 2014. 3902 events were recorded in 1158 patients (range 0–24). There was significant seasonal variation in relapse rates (p < 0.0001) and this was associated with monthly hours of sunshine (odds ratio OR 1.08, p = 0.02). Relapse rates were highest in patients under the age of 30 (OR 1.42, p = 0.0005) and decreased with age. There was no evidence of different relapse rates for males compared to females (OR 0.90, p = 0.19). Identification of potentially modifiable environmental factors associated with temporal variation in relapse rates may allow alteration of risk on a population basis and alteration of outcome of established disease once established. Future epidemiological studies should examine dynamic environmental factors with serial prospective measurements and biological sampling. Significant seasonal differences in relapse rates highlight the importance of environmental factors in disease expression and should be taken into account when planning clinical trials in which relapse frequency is an outcome. In addition, identification of potentially modifiable factors associated with this variation may offer unique opportunities for alteration of risk of relapse and long-term outcome on a population level, and suggest putative biological mechanisms for relapse initiation.

Background and purpose: Structural magnetic resonance techniques have been widely applied in neurological disorders to better understand tissue changes, probing characteristics such as volume, iron deposition and diffusion. Dystonia is a hyperkinetic movement disorder, resulting in abnormal postures and pain. Its pathophysiology is poorly understood, with normal routine clinical imaging in idiopathic forms. More advanced tools provide an opportunity to identify smaller scale structural changes which may underpin pathophysiology. This review aims to provide an overview of methodological approaches undertaken in structural brain imaging of dystonia cohorts, and to identify commonly identified pathways, networks or regions that are implicated in pathogenesis.Methods: Structural magnetic resonance imaging studies of idiopathic and genetic forms of dystonia were systematically reviewed. Adhering to strict inclusion and exclusion criteria, PubMed and Embase databases were searched up to January 2022, with studies reviewed for methodological quality and key findings. Results:Seventy-seven studies were included, involving 1945 participants. The majority of studies employed diffusion tensor imaging (DTI) (n = 45) or volumetric analyses (n = 37), with frequently implicated areas of abnormality in the brainstem, cerebellum, basal ganglia and sensorimotor cortex and their interconnecting white matter pathways. Genotypic and motor phenotypic variation emerged, for example fewer cerebellothalamic tractography streamlines in genetic forms than idiopathic and higher grey matter volumes in task-specific than non-task-specific dystonias.Discussion: Work to date suggests microstructural brain changes in those diagnosed with dystonia, although the underlying nature of these changes remains undetermined.Employment of techniques such as multiple diffusion weightings or multi-exponential relaxometry has the potential to enhance understanding of these differences.

This study demonstrated that static (fasting) and dynamic (AUC, 2-hour) C-peptide measurements predict T2DM resolution 6 months following bariatric surgery. This work provides insight into C-peptide dynamics as a predictor of response to bariatric surgery.