Muscular Dystrophy Surveillance, Tracking, and Research Network pilot: Population-based surveillance of major muscular dystrophies at four U.S. sites, 2007-2011

Genetic Patterns of Selected Muscular Dystrophies in the Muscular Dystrophy Surveillance, Tracking, and Research Network

Background and Objectives

To report the genetic etiologies of Emery-Dreifuss muscular dystrophy (EDMD), limb-girdle muscular dystrophy (LGMD), congenital muscular dystrophy (CMD), and distal muscular dystrophy (DD) in 6 geographically defined areas of the United States.

Methods

This was a cross-sectional, population-based study in which we studied the genes and variants associated with muscular dystrophy in individuals who were diagnosed with and received care for EDMD, LGMD, CMD, and DD from January 1, 2008, through December 31, 2016, in the 6 areas of the United States covered by the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet). Variants of unknown significance (VUSs) from the original genetic test reports were reanalyzed for changes in interpretation.

Results

Among 243 individuals with definite or probable muscular dystrophy, LGMD was the most common diagnosis (138 cases), followed by CMD (62 cases), DD (22 cases), and EDMD (21 cases). There was a higher proportion of male individuals compared with female individuals, which persisted after excluding X-linked genes (EMD) and autosomal genes reported to have skewed gender ratios (ANO5, CAV3, and LMNA). The most common associated genes were FKRP, CAPN3, ANO5, and DYSF. Reanalysis yielded more definitive variant interpretations for 60 of 144 VUSs, with a mean interval between the original clinical genetic test of 8.11 years for all 144 VUSs and 8.62 years for the 60 reclassified variants. Ten individuals were found to have monoallelic pathogenic variants in genes known to be primarily recessive.

Discussion

This study is distinct for being an examination of 4 types of muscular dystrophies in selected geographic areas of the United States. The striking proportion of resolved VUSs demonstrates the value of periodic re-examinations of these variants. Such re-examinations will resolve some genetic diagnostic ambiguities before initiating repeat testing or more invasive diagnostic procedures such as muscle biopsy. The presence of monoallelic pathogenic variants in recessive genes in our cohort indicates that some individuals with muscular dystrophy continue to face incomplete genetic diagnoses; further refinements in genetic knowledge and diagnostic approaches will optimize diagnostic information for these individuals.

Sources of variation in estimates of Duchenne and Becker muscular dystrophy prevalence in the United States

BACKGROUND

Direct estimates of rare disease prevalence from public health surveillance may only be available in a few catchment areas. Understanding variation among observed prevalence can inform estimates of prevalence in other locations. The Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet) conducts population-based surveillance of major muscular dystrophies in selected areas of the United States. We identified sources of variation in prevalence estimates of Duchenne and Becker muscular dystrophy (DBMD) within MD STARnet from published literature and a survey of MD STARnet investigators, then developed a logic model of the relationships between the sources of variation and estimated prevalence.

RESULTS

The 17 identified sources of variability fell into four categories: (1) inherent in surveillance systems, (2) particular to rare diseases, (3) particular to medical-records-based surveillance, and (4) resulting from extrapolation. For the sources of uncertainty measured by MD STARnet, we estimated each source's contribution to the total variance in DBMD prevalence. Based on the logic model we fit a multivariable Poisson regression model to 96 age-site-race/ethnicity strata. Age accounted for 74% of the variation between strata, surveillance site for 6%, race/ethnicity for 3%, and 17% remained unexplained.

CONCLUSION

Variation in estimates derived from a non-random sample of states or counties may not be explained by demographic differences alone. Applying these estimates to other populations requires caution.

A population-based study of mortality due to muscular dystrophies across a 36-year period in Spain

Muscular dystrophies (MD) are a group of rare hereditary degenerative diseases. Our aim was to analyze the mortality pattern in Spain from 1981 to 2016 to assess the temporal trend and discern possible geographic differences using population-based data. Annual deaths related to MD were obtained from the National Statistics Institute with codes 359.1 of the ICD-9 (1981–1998) and G71.0 of the ICD-10 (1999–2016). Age-adjusted mortality rates were calculated and changes in mortality trends were identified. The standardized mortality ratios (SMR) and their respective 95% confidence intervals were calculated by district for 1999–2016. Smoothed SMRs and posterior probability were also assessed and then mapped to look for patterns or geographic distribution. All rates were expressed per 1,000,000 inhabitants. A total of 2,512 deaths (73.8% men) were identified. The age-adjusted mortality rates varied from 0.63 (95% CI 0.40–0.95) in 1981 to 1.51 (95% CI 1.17–1.93) in 2016. MD mortality showed a significant increase of 8.81% per year (95% CI 5.0–12.7) from 1981 to 1990, remaining stable afterwards. Areas with risk of death higher than expected for Spain as a whole were identified, not showing a specific regional pattern. In conclusion, the rising trend in MD mortality might be attributable to advanced improvements in diagnostic techniques leading to a rise in prevalence. Further research on the districts with the highest mortality would be necessary.

Characteristics of Clinical Trial Participants with Duchenne Muscular Dystrophy: Data from the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet)

BACKGROUND

Therapeutic trials are critical to improving outcomes for individuals diagnosed with Duchenne muscular dystrophy (DMD). Understanding predictors of clinical trial participation could maximize enrollment.

METHODS

Data from six sites (Colorado, Iowa, Piedmont region North Carolina, South Carolina, Utah, and western New York) of the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet) were analyzed. Clinical trial participation and individual-level clinical and sociodemographic characteristics were obtained from medical records for the 2000-2015 calendar years. County-level characteristics were determined from linkage of the most recent county of residence identified from medical records and publicly available federal datasets. Fisher's exact and Wilcoxon two-sample tests were used with statistical significance set at one-sided p-value (<0.05) based on the hypothesis that nonparticipants had fewer resources.

RESULTS

Clinical trial participation was identified among 17.9% (MD STARnet site: 3.7-27.3%) of 358 individuals with DMD. Corticosteroids, tadalafil, and ataluren (PTC124) were the most common trial medications recorded. Fewer non-Hispanic blacks or Hispanics than non-Hispanic whites participated in clinical trials. Trial participants tended to reside in counties with lower percentages of non-Hispanic blacks. Conclusion: Understanding characteristics associated with clinical trial participation is critical for identifying participation barriers and generalizability of trial results. MD STARnet is uniquely able to track clinical trial participation through surveillance and describe patterns of participation.

High throughput screening for expanded CTG repeats in myotonic dystrophy type 1 using melt curve analysis

Background

Myotonic dystrophy type 1 (DM1) is caused by CTG repeat expansions in the DMPK gene and is the most common form of muscular dystrophy. Patients can have long delays from onset to diagnosis, since clinical signs and symptoms are often nonspecific and overlapping with other disorders. Clinical genetic testing by Southern blot or triplet‐primed PCR (TP‐PCR) is technically challenging and cost prohibitive for population surveys.

Methods

Here, we present a high throughput, low‐cost screening tool for CTG repeat expansions using TP‐PCR followed by high resolution melt curve analysis with saturating concentrations of SYBR GreenER dye.

Results

We determined that multimodal melt profiles from the TP‐PCR assay are a proxy for amplicon length stoichiometry. In a screen of 10,097 newborn blood spots, melt profile analysis accurately reflected the tri‐modal distribution of common alleles from 5 to 35 CTG repeats, and identified the premutation and full expansion alleles.

Conclusion

We demonstrate that robust detection of expanded CTG repeats in a single tube can be achieved from samples derived from specimens with minimal template DNA such as dried blood spots (DBS). This technique is readily adaptable to large‐scale testing programs such as population studies and newborn screening programs.

The ties that bind: functional clusters in limb-girdle muscular dystrophy

The limb-girdle muscular dystrophies (LGMDs) are a genetically pleiomorphic class of inherited muscle diseases that are known to share phenotypic features. Selected LGMD genetic subtypes have been studied extensively in affected humans and various animal models. In some cases, these investigations have led to human clinical trials of potential disease-modifying therapies, including gene replacement strategies for individual subtypes using adeno-associated virus (AAV) vectors. The cellular localizations of most proteins associated with LGMD have been determined. However, the functions of these proteins are less uniformly characterized, thus limiting our knowledge of potential common disease mechanisms across subtype boundaries. Correspondingly, broad therapeutic strategies that could each target multiple LGMD subtypes remain less developed. We believe that three major "functional clusters" of subcellular activities relevant to LGMD merit further investigation. The best known of these is the glycosylation modifications associated with the dystroglycan complex. The other two, mechanical signaling and mitochondrial dysfunction, have been studied less systematically but are just as promising with respect to the identification of significant mechanistic subgroups of LGMD. A deeper understanding of these disease pathways could yield a new generation of precision therapies that would each be expected to treat a broader range of LGMD patients than a single subtype, thus expanding the scope of the molecular medicines that may be developed for this complex array of muscular dystrophies.

Characterization of individuals with selected muscular dystrophies from the expanded pilot of the Muscular Dystrophy Surveillance, Tracking and Research Network (MD STARnet) in the United States

INTRODUCTION

Data on muscular dystrophies (MDs), a heterogeneous group of heritable diseases hallmarked by progressive muscle deterioration, are scarce.

OBJECTIVE

We describe cross-sectional sociodemographic and clinical characteristics of individuals with congenital, distal, Emery-Dreifuss, facioscapulohumeral, limb-girdle, myotonic, or oculopharyngeal MD.

METHODS

The study was conducted in four sites (Arizona, Colorado, Iowa, and 12 western New York counties) as a pilot expansion of the Muscular Dystrophy Surveillance, Tracking and Research Network, funded by the Centers for Disease Control and Prevention. MDs were detected in healthcare facilities and administrative data sources using International Classification of Disease codes. Our sample contains 1,723 individuals with a MD diagnosis and a healthcare encounter between January 1, 2007 and December 31, 2011.

RESULTS AND CONCLUSIONS

Individuals were mostly non-Hispanic and white. Median ages ranged from 9.2 to 66.0 years. Most (98%) had health insurance. The proportion of individuals who were disabled or unable to work increased with age (range: 8.6-46.4%). People with limb-girdle MD aged ≥18 years were more likely to be nonambulatory (range: 24.5-44.7%). The percentages of individuals with documented clinical interventions during the surveillance period were low. The most common cause of death was respiratory causes (46.3-57.1%); an ICD-10 code for MD (G71.1 or G71.0) was reported for nearly one-half. Our findings show wide variability in sociodemographic and clinical characteristics across MDs.