Natural history study and statistical modeling of disease progression in a preclinical model of myotubular myopathy.

Generating reliable preclinical data in animal models of disease is essential in therapy development. Here, we performed statistical analysis and joint longitudinal-survival modeling of the progressive phenotype observed in Mtm1-/y mice, a reliable model for myotubular myopathy. Analysis of historical data was used to generate a model for phenotype progression, which was then confirmed with phenotypic data from a new colony of mice derived via in vitro fertilization in an independent animal house, highlighting the reproducibility of disease phenotype in Mtm1-/y mice. These combined data were used to refine the phenotypic parameters analyzed in these mice and improve the model generated for expected disease progression. The disease progression model was then used to test the therapeutic efficacy of Dnm2 targeting. Dnm2 reduction by antisense oligonucleotides blocked or postponed disease development, and resulted in a significant dose-dependent improvement outside the expected disease progression in untreated Mtm1-/y mice. This provides an example of optimizing disease analysis and testing therapeutic efficacy in a preclinical model, which can be applied by scientists testing therapeutic approaches using neuromuscular disease models in different laboratories. This article has an associated First Person interview with the joint first authors of the paper.

Hierarchical Bayesian modelling of disease progression to inform clinical trial design in centronuclear myopathy.

BACKGROUND: Centronuclear myopathies are severe rare congenital diseases. The clinical variability and genetic heterogeneity of these myopathies result in major challenges in clinical trial design. Alternative strategies to large placebo-controlled trials that have been used in other rare diseases (e.g., the use of surrogate markers or of historical controls) have limitations that Bayesian statistics may address. Here we present a Bayesian model that uses each patient's own natural history study data to predict progression in the absence of treatment. This prospective multicentre natural history evaluated 4-year follow-up data from 59 patients carrying mutations in the MTM1 or DNM2 genes. METHODS: Our approach focused on evaluation of forced expiratory volume in 1 s (FEV1) in 6- to 18-year-old children. A patient was defined as a responder if an improvement was observed after treatment and the predictive probability of such improvement in absence of intervention was less than 0.01. An FEV1 response was considered clinically relevant if it corresponded to an increase of more than 8%. RESULTS: The key endpoint of a clinical trial using this model is the rate of response. The power of the study is based on the posterior probability that the rate of response observed is greater than the rate of response that would be observed in the absence of treatment predicted based on the individual patient's previous natural history. In order to appropriately control for Type 1 error, the threshold probability by which the difference in response rates exceeds zero was adapted to 91%, ensuring a 5% overall Type 1 error rate for the trial. CONCLUSIONS: Bayesian statistical analysis of natural history data allowed us to reliably simulate the evolution of symptoms for individual patients over time and to probabilistically compare these simulated trajectories to actual observed post-treatment outcomes. The proposed model adequately predicted the natural evolution of patients over the duration of the study and will facilitate a sufficiently powerful trial design that can cope with the disease's rarity. Further research and ongoing dialog with regulatory authorities are needed to allow for more applications of Bayesian statistics in orphan disease research.

Myostatin: a Circulating Biomarker Correlating with Disease in Myotubular Myopathy Mice and Patients.

Myotubular myopathy, also called X-linked centronuclear myopathy (XL-CNM), is a severe congenital disease targeted for therapeutic trials. To date, biomarkers to monitor disease progression and therapy efficacy are lacking. The Mtm1 -/y mouse is a faithful model for XL-CNM, due to myotubularin 1 (MTM1) loss-of-function mutations. Using both an unbiased approach (RNA sequencing [RNA-seq]) and a directed approach (qRT-PCR and protein level), we identified decreased Mstn levels in Mtm1 -/y muscle, leading to low levels of myostatin in muscle and plasma. Myostatin (Mstn or growth differentiation factor 8 [Gdf8]) is a protein released by myocytes and inhibiting muscle growth and differentiation. Decreasing Dnm2 by genetic cross with Dnm2 +/- mice or by antisense oligonucleotides blocked or postponed disease progression and resulted in an increase in circulating myostatin. In addition, plasma myostatin levels inversely correlated with disease severity and with Dnm2 mRNA levels in muscles. Altered Mstn levels were associated with a generalized disruption of the myostatin pathway. Importantly, in two different forms of CNMs we identified reduced circulating myostatin levels in plasma from patients. This provides evidence of a blood-based biomarker that may be used to monitor disease state in XL-CNM mice and patients and supports monitoring circulating myostatin during clinical trials for myotubular myopathy.