Wearable full-body motion tracking of activities of daily living predicts disease trajectory in Duchenne muscular dystrophy

Artificial intelligence has the potential to revolutionize healthcare, yet clinical trials in neurological diseases continue to rely on subjective, semiquantitative and motivation-dependent endpoints for drug development. To overcome this limitation, we collected a digital readout of whole-body movement behavior of patients with Duchenne muscular dystrophy (DMD) (n = 21) and age-matched controls (n = 17). Movement behavior was assessed while the participant engaged in everyday activities using a 17-sensor bodysuit during three clinical visits over the course of 12 months. We first defined new movement behavioral fingerprints capable of distinguishing DMD from controls. Then, we used machine learning algorithms that combined the behavioral fingerprints to make cross-sectional and longitudinal disease course predictions, which outperformed predictions derived from currently used clinical assessments. Finally, using Bayesian optimization, we constructed a behavioral biomarker, termed the KineDMD ethomic biomarker, which is derived from daily-life behavioral data and whose value progresses with age in an S-shaped sigmoid curve form. The biomarker developed in this study, derived from digital readouts of daily-life movement behavior, can predict disease progression in patients with muscular dystrophy and can potentially track the response to therapy

A wearable motion capture suit and machine learning predict disease progression in Friedreich's ataxia

Friedreich's ataxia (FA) is caused by a variant of the Frataxin (FXN) gene, leading to its downregulation and progressively impaired cardiac and neurological function. Current gold-standard clinical scales use simplistic behavioral assessments, which require 18- to 24-month-long trials to determine if therapies are beneficial. Here we captured full-body movement kinematics from patients with wearable sensors, enabling us to define digital behavioral features based on the data from nine FA patients (six females and three males) and nine age- and sex-matched controls, who performed the 8-m walk (8-MW) test and 9-hole peg test (9 HPT). We used machine learning to combine these features to longitudinally predict the clinical scores of the FA patients, and compared these with two standard clinical assessments, Spinocerebellar Ataxia Functional Index (SCAFI) and Scale for the Assessment and Rating of Ataxia (SARA). The digital behavioral features enabled longitudinal predictions of personal SARA and SCAFI scores 9 months into the future and were 1.7 and 4 times more precise than longitudinal predictions using only SARA and SCAFI scores, respectively. Unlike the two clinical scales, the digital behavioral features accurately predicted FXN gene expression levels for each FA patient in a cross-sectional manner. Our work demonstrates how data-derived wearable biomarkers can track personal disease trajectories and indicates the potential of such biomarkers for substantially reducing the duration or size of clinical trials testing disease-modifying therapies and for enabling behavioral transcriptomics

Long-term natural history data in Duchenne muscular dystrophy ambulant patients with mutations amenable to skip exons 44, 45, 51 and 53

The aim of this international collaborative effort was to report 36-month longitudinal changes using the 6MWT in ambulant patients affected by Duchenne muscular dystrophy amenable to skip exons 44, 45, 51 or 53

Machine learning in clinical and epidemiological research: isn't it time for biostatisticians to work on it?

In recent years, there has been a widespread cross-fertilization between Medical Statistics and Machine Learning (ML) techniques

Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy

The North Star ambulatory assessment (NSAA) is a functional motor outcome measure in Duchenne muscular dystrophy (DMD), widely used in clinical trials and natural history studies, as well as in clinical practice. However, little has been reported on the minimal clinically important difference (MCID) of the NSAA. The lack of established MCID estimates for NSAA presents challenges in interpreting the significance of the results of this outcome measure in clinical trials, natural history studies and clinical practice. Combining statistical approaches and patient perspectives, this study estimated MCID for NSAA using distribution-based estimates of 1/3 standard deviation (SD) and standard error of measurement (SEM), an anchor-based approach, with six-minute walk distance (6MWD) as the anchor, and evaluation of patient and parent perception using participant-tailored questionnaires. The MCID for NSAA in boys with DMD aged 7 to 10 years based on 1/3 SD ranged from 2.3-2.9 points, and that on SEM ranged from 2.9-3.5 points. Anchored on the 6MWD, the MCID for NSAA was estimated as 3.5 points. When the impact on functional abilities was considered using participant response questionnaires, patients and parent perceived a complete loss of function in a single item or deterioration of function in one to two items of the assessment as an important change. Our study examines MCID estimates for total NSAA scores using multiple approaches, including the impact of patient and parent perspective on within scale changes in items based on complete loss of function and deterioration of function, and provides new insight on evaluation of differences in these widely used outcome measure in DMD

Downregulation of miRNA-29, -23 and -21 in urine of Duchenne muscular dystrophy patients

AIM: To study the signature of 87 urinary miRNAs in Duchenne muscular dystrophy (DMD) patients, select the most dysregulated and determine statistically significant differences in their expression between controls, ambulant (A) and nonambulant (NA) DMD patients, and patients on different corticosteroid regimens. Patients/materials & methods: Urine was collected from control (n = 20), A (n = 31) and NA (n = 23) DMD patients. miRNA expression was measured by reverse transcription-quantitative PCR. RESULTS: miR-29c-3p was significantly downregulated in A DMD patients while miR-23b-3p and miR-21-5p were significantly downregulated in NA DMD patients compared with age-matched controls. CONCLUSION: miR-29c-3p, miR-23b-3p and miR-21-5p are promising novel noninvasive biomarkers for DMD, and miR-29c-3p levels are differentially affected by different steroid regimens, supporting the antifibrotic effect of steroid therapy

Biochemical characterization of patients with in-frame or out-of-frame DMD deletions pertinent to Exon 44 or 45 skipping

Importance: In Duchenne muscular dystrophy (DMD), the reading frame of an out-of-frame DMD deletion can be repaired by antisense oligonucleotide (AO)–mediated exon skipping. This creates a shorter dystrophin protein, similar to those expressed in the milder Becker muscular dystrophy (BMD). The skipping of some exons may be more efficacious than others. Patients with exon 44 or 45 skippable deletions (AOs in clinical development) have a less predictable phenotype than those skippable for exon 51, a group in advanced clinical trials. A way to predict the potential of AOs is the study of patients with BMD who have deletions that naturally mimic those that would be achieved by exon skipping. Objective: To quantify dystrophin messenger RNA (mRNA) and protein expression in patients with DMD deletions treatable by, or mimicking, exon 44 or 45 skipping. Design, Setting, and Participants: Retrospective study of nondystrophic controls (n = 2), patients with DMD (n = 5), patients with intermediate muscular dystrophy (n = 3), and patients with BMD (n = 13) at 4 university-based academic centers and pediatric hospitals. Biochemical analysis of existing muscle biopsies was correlated with the severity of the skeletal muscle phenotype. Main Outcomes and Measures: Dystrophin mRNA and protein expression. Results: Patients with DMD who have out-of-frame deletions skippable for exon 44 or 45 had an elevated number of revertant and trace dystrophin expression (approximately 19% of control, using quantitative immunohistochemistry) with 4 of 9 patients presenting with an intermediate muscular dystrophy phenotype (3 patients) or a BMD-like phenotype (1 patient). Corresponding in-frame deletions presented with predominantly mild BMD phenotypes and lower dystrophin levels (approximately 42% of control) than patients with BMD modeling exon 51 skipping (approximately 80% of control). All 12 patients with in-frame deletions had a stable transcript compared with 2 of 9 patients with out-of-frame deletions (who had intermediate muscular dystrophy and BMD phenotypes). Conclusions and Relevance: Exon 44 or 45 skipping will likely yield lower levels of dystrophin than exon 51 skipping, although the resulting protein is functional enough to often maintain a mild BMD phenotype. Dystrophin transcript stability is an important indicator of dystrophin expression, and transcript instability in DMD compared with BMD should be explored as a potential biomarker of response to AOs. This study is beneficial for the planning, execution, and analysis of clinical trials for exon

T Cell Responses to Dystrophin in a Natural History Study of Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is caused by the lack of dystrophin, but many patients have rare revertant fibres that express dystrophin. The skeletal muscle pathology of DMD patients includes immune cell infiltration and inflammatory cascades. There are several strategies to restore dystrophin in skeletal muscles of patients, including exon skipping and gene therapy. There is some evidence that dystrophin restoration leads to a reduction in immune cells, but dystrophin epitopes expressed in revertant fibres or following genome editing, cell therapy or microdystrophin delivery after AAV gene therapy may elicit T cell production in patients. This may affect the efficacy of the therapeutic intervention, and potentially lead to serious adverse events. To confirm and extend previous studies, we performed annual Enzyme- Linked Immunospot interferon-gamma assays on peripheral blood mononuclear cells from 77 paediatric boys with DMD recruited into a natural history study, 69 of whom (89.6%) were treated with corticosteroids. T cell responses to dystrophin were quantified using a total of 368 peptides spanning the entire dystrophin protein, organized into nine peptide pools. Peptide mapping pools were used to further localize the immune response in one positive patient. Six (7.8%) patients had a T cell-mediated immune response to dystrophin at at least one timepoint. All patients that had a positive result had been treated with corticosteroids, either prednisolone or prednisone. Our results show that ~8% of DMD individuals in our cohort have a pre-existing T cell-mediated immune response to dystrophin despite steroid treatment. Although these responses are relatively low-level, this information should be considered as a useful immunological baseline before undertaking clinical trials and future DMD studies. We further highlight the importance for a robust, reproducible standard operating procedure for collecting, storing and shipping samples from multiple centres to minimise the number of inconclusive data