Insights gained from large international real-world cohorts demonstrate that early efficacious treatment is crucial for the long-term outcome of MS patients. However, there is increasing evidence of substantial neuronal damage already occurring in presymptomatic patients (e.g., in patients with abnormalities in magnetic resonance imaging (MRI) without clinical symptoms, the so-called radiologically isolated syndrome) and even in a prodromal phase that precedes the detection of first abnormalities in MRI. For example, increased neurofilament light chain (NfL) levels, a biomarker of neuronal damage, have been detected in blood samples obtained from seemingly healthy US military personnel up to 6 years before they presented with the first clinical episode of MS . Moreover, large-scale cognitive testing of more than 20,000 individuals revealed that men later receiving a diagnosis of MS had lower cognitive scores than healthy controls up to 2 years before their first clinical event . These observations highlight that delaying treatment initiation until clinical disease onset might be too late for preventing long-term progression of physical and cognitive impairment. Thus, strategies that enable the identification of individuals at risk and of patients with presymptomatic MS along with the initiation of preventive measures (e.g., modification of known risk factors like smoking and obesity, disease-specific education, and early detection examinations) might be a key to overcoming MS progression.
To date, studies by the International Multiple Sclerosis Genetics Consortium (IMSGC), an international research collaboration aiming to identify the genetic basis of MS and its disease course, have identified 233 independent genome-wide significant associations with MS susceptibility by leveraging genotype data from more than 48,000 MS patients and almost 70,000 controls . Of note, many of these associations would not have been detected in smaller-scope studies due to minor contributions of individual variants to the overall genetic risk. There have already been attempts, for example, through the development of polygenic risk scores, to leverage the knowledge of these genetic risk variants in order to identify persons at risk to develop MS. In addition, the clinical implementation of new biomarkers such as serum NfL  may be feasible in the near future. With regard to enabling an earlier diagnosis, two recent studies conducted in large national registries provide interesting insights into how the population-wide screening of electronic health records could be used to identify MS patients before they perceive signs of neurological deficits. The first is a matched cohort study that used data linked from health administrative and clinical databases from four Canadian provinces and included 14,428 MS patients and 72,059 matched controls. The authors observed a steadily increasing annual healthcare use between 5 years and 1 year before the first demyelinating event . In a second population-based observational study, the occurrence of a variety of clinical disturbances with particular attention to autonomic symptoms, psychiatric conditions, cognitive impairment, fatigue, and pain was compared between 10,204 patients who would later receive a diagnosis of MS or clinically isolated syndrome (i.e., a clinical episode suggestive of MS but not fulfilling the diagnostic criteria of dissemination in time and space) and 39,448 controls. Remarkably, MS patients had a significantly higher risk of presenting with symptoms like gastrointestinal disturbances, anxiety and mood disorders, fatigue, and pain up to 10 years prior to the first mention of an MS diagnosis in their healthcare records. The authors suggested that the integration of these symptoms into the diagnostic procedure might aid in earlier diagnosis .
Findings from these real-world cohort studies have considerably contributed to our understanding of MS disease course as they have led to the identification of a presymptomatic phase (the MS prodrome) and have highlighted the importance of timely preventive measures. Moreover, they indicate potential strategies for the early identification of persons at risk.