CTG repeat expansions in DMPK cause myotonic dystrophy (DM1) with a continuum of severity and ages of onset. Congenital DM1 (CDM1), the most severe form, presents distinct clinical features, large expansions, and almost exclusive maternal transmission. The correlation between CDM1 and expansion size is not absolute, suggesting contributions of other factors. We determined CpG methylation flanking the CTG repeat in 79 blood samples from 20 CDM1-affected individuals; 21, 27, and 11 individuals with DM1 but not CDM1 (henceforth non-CDM1) with maternal, paternal, and unknown inheritance; and collections of maternally and paternally derived chorionic villus samples (7 CVSs) and human embryonic stem cells (4 hESCs). All but two CDM1-affected individuals showed high levels of methylation upstream and downstream of the repeat, greater than non-CDM1 individuals (p = 7.04958 × 10). Most non-CDM1 individuals were devoid of methylation, where one in six showed downstream methylation. Only two non-CDM1 individuals showed upstream methylation, and these were maternally derived childhood onset, suggesting a continuum of methylation with age of onset. Only maternally derived hESCs and CVSs showed upstream methylation. In contrast, paternally derived samples (27 blood samples, 3 CVSs, and 2 hESCs) never showed upstream methylation. CTG tract length did not strictly correlate with CDM1 or methylation. Thus, methylation patterns flanking the CTG repeat are stronger indicators of CDM1 than repeat size. Spermatogonia with upstream methylation may not survive due to methylation-induced reduced expression of the adjacent SIX5, thereby protecting DM1-affected fathers from having CDM1-affected children. Thus, DMPK methylation may account for the maternal bias for CDM1 transmission, larger maternal CTG expansions, age of onset, and clinical continuum, and may serve as a diagnostic indicator.

Digital health metrics promise to advance the understanding of impaired body functions, for example in neurological disorders. However, their clinical integration is challenged by an insufficient validation of the many existing and often abstract metrics. Here, we propose a data-driven framework to select and validate a clinically relevant core set of digital health metrics extracted from a technology-aided assessment. As an exemplary use-case, the framework is applied to the Virtual Peg Insertion Test (VPIT), a technology-aided assessment of upper limb sensorimotor impairments. The framework builds on a use-case-specific pathophysiological motivation of metrics, models demographic confounds, and evaluates the most important clinimetric properties (discriminant validity, structural validity, reliability, measurement error, learning effects). Applied to 77 metrics of the VPIT collected from 120 neurologically intact and 89 affected individuals, the framework allowed selecting 10 clinically relevant core metrics. These assessed the severity of multiple sensorimotor impairments in a valid, reliable, and informative manner. These metrics provided added clinical value by detecting impairments in neurological subjects that did not show any deficits according to conventional scales, and by covering sensorimotor impairments of the arm and hand with a single assessment. The proposed framework provides a transparent, step-by-step selection procedure based on clinically relevant evidence. This creates an interesting alternative to established selection algorithms that optimize mathematical loss functions and are not always intuitive to retrace. This could help addressing the insufficient clinical integration of digital health metrics. For the VPIT, it allowed establishing validated core metrics, paving the way for their integration into neurorehabilitation trials.

Purpose of reviewMyotonic dystrophy type 1 (DM1) is a severe, progressive genetic disease that affects between 1 in 3,000 and 8,000 individuals globally. No evidence-based guideline exists to inform the care of these patients, and most do not have access to multidisciplinary care centers staffed by experienced professionals, creating a clinical care deficit.Recent findingsThe Myotonic Dystrophy Foundation (MDF) recruited 66 international clinicians experienced in DM1 patient care to develop consensus-based care recommendations. MDF created a 2-step methodology for the project using elements of the Single Text Procedure and the Nominal Group Technique. The process generated a 4-page Quick Reference Guide and a comprehensive, 55-page document that provides clinical care recommendations for 19 discrete body systems and/or care considerations.SummaryThe resulting recommendations are intended to help standardize and elevate care for this patient population and reduce variability in clinical trial and study environments.

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