Heterogeneity in the Multiple Sclerosis Prodrome and Impact on Disease Progression
Summary: Neurodegenerative diseases, such as Parkinson’s, can start years before clinical diagnosis and are often preceded by a range of health issues. For example, individuals with Parkinson’s may experience depression and constipation years before the classic symptoms, such as motor deficiencies, are detected. These early symptoms are collectively known as the “prodrome”. This study aims to advance our understanding of the multiple sclerosis (MS) prodrome by enhancing our capacity to identify personal predictors of the MS prodrome across diverse groups and understand the relationship of these features with subsequent MS disability outcomes. This knowledge will help facilitate more timely recognition of individuals at risk of MS onset, and those at risk of worse disability outcomes, thereby improving diagnosis and management of MS.
Project Description: Dr. Helen Tremlett (University of British Columbia) and team have identified and described an MS prodromal period for at least five years prior to MS symptom onset. Prior studies from Dr. Tremlett have shown that in this prodromal period, people with MS have higher rates of hospital and physician visits, an increase in prescription drugs, and experience a number of non-specific health issues (i.e. pain, sleep disorders, anaemia, fatigue, mood and anxiety disorders, and migraine headaches). This study aims to further our understanding of the prodromal period by identifying predictors of MS across different groups of people in the years before clinical MS diagnosis and understanding how these factors impact disease progression. The study will examine a cohort of over 250,000 people using health administrative databases, patient registries and other databases in three regions—two in Canada (Ontario and British Columbia) and one in Sweden—and assess health and workplace data (i.e. healthcare use, physician and emergency room visits, prescription drugs, workplace absences), in relation to key sociodemographic factors (i.e. biological sex, socioeconomic status, and birth country/immigration status). The researchers will utilize advanced machine learning techniques to identify predictors of MS at the individual level that differentiate MS cases from those without MS. These patterns will also be assessed over time to establish the duration of the prodrome. Finally, the researchers will investigate health care use patterns, specific conditions (e.g. psychiatric) as well as overall burden and how they are associated with future disability progression and how they differ by disease course (e.g. primary progressive MS versus relapsing-remitting MS).
Potential Impact: A greater understanding of the early prodromal features and predictors of disability progression will facilitate more timely recognition of individuals ‘at-risk’ of MS, and those ‘at- risk’ of worse outcomes. In the longer-term, insights from this research could be used to help with earlier diagnosis and treatment of MS and provide opportunities to prevent disability progression.
Project Status: In progress
Funding Partner(s): National MS Society (US)