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Metachromatic leukodystrophy (MLD) is a rare neurodegenerative disorder. Emerging therapies are most effective in the presymptomatic phase, and thus defining this window is critical. We hypothesize that early development delay may precede developmental plateau. With the advent of presymptomatic screening platforms and transformative therapies, it is essential to define the onset of neurologic disease. The specific ages of gain and loss of developmental milestones were captured from the medical records of individuals affected by MLD. Milestone acquisition was characterized as: on target (obtained before the age limit of 90th percentile plus 2 standard deviations compared to a normative dataset), delayed (obtained after 90th percentile plus 2 standard deviations), or plateau (skills never gained). Regression was defined as the age at which skills were lost. LI-MLD was defined by age at onset before 2.5 years. Across an international cohort, 351 subjects were included (n = 194 LI-MLD subcohort). The median age at presentation of the LI-MLD cohort was 1.4 years (25th–75th %ile: 1.0–1.5). Within the LI-MLD cohort, 75/194 (39%) had developmental delay (or plateau) prior to MLD clinical presentation. Among the LI-MLD cohort with a minimum of 1.5 years of follow-up (n = 187), 73 (39.0%) subjects never attained independent ambulation. Within LI-MLD + delay subcohort, the median time between first missed milestone target to MLD decline was 0.60 years (maximum distance from delay to onset: 1.9 years). Early developmental delay precedes regression in a subset of children affected by LI-MLD, defining the onset of neurologic dysfunction earlier than previously appreciated. The use of realworld data prior to diagnosis revealed an early deviation from typical development. Close monitoring for early developmental delay in presymptomatic individuals may help in earlier diagnosis with important consequences for treatment decisions. [ABSTRACT FROM AUTHOR]

Growing interest in therapeutic development for rare diseases necessitate a systematic approach to the collection and curation of natural history data that can be applied consistently across this group of heterogenous rare diseases. In this study, we discuss the challenges facing natural history studies for leukodystrophies and detail a novel standardized approach to creating a longitudinal natural history study using existing medical records. Prospective studies are uniquely challenging for rare diseases. Delays in diagnosis and overall rarity limit the timely collection of natural history data. When feasible, prospective studies are often cross-sectional rather than longitudinal and are unlikely to capture pre- or early- symptomatic disease trajectories, limiting their utility in characterizing the full natural history of the disease. Therapeutic development in leukodystrophies is subject to these same obstacles. The Global Leukodystrophy Initiative Clinical Trials Network (GLIA-CTN) comprises of a network of research institutions across the United States, supported by a multi-center biorepository protocol, to map the longitudinal clinical course of disease across leukodystrophies. As part of GLIA-CTN, we developed Standard Operating Procedures (SOPs) that delineated all study processes related to staff training, source documentation, and data sharing. Additionally, the SOP detailed the standardized approach to data extraction including diagnosis, clinical presentation, and medical events, such as age at gastrostomy tube placement. The key variables for extraction were selected through face validity, and common electronic case report forms (eCRF) across leukodystrophies were created to collect analyzable data. To enhance the depth of the data, clinical notes are extracted into "original" and "imputed" encounters, with imputed encounter referring to a historic event (e.g., loss of ambulation 3 months prior). Retrospective Functional Assessments were assigned by child neurologists, using a blinded dual-rater approach and score discrepancies were adjudicated by a third rater. Upon completion of extraction, data source verification is performed. Data missingness was evaluated using statistics. The proposed methodology will enable us to leverage existing medical records to address the persistent gap in natural history data within this unique disease group, allow for assessment of clinical trajectory both pre- and post-formal diagnosis, and promote recruitment of larger cohorts. [ABSTRACT FROM AUTHOR]