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The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, United Kingdom
Center for Translational Science, Division of Biostatistics and Study Methodology, Children's National Health System, Washington, DC, United StatesPediatrics, Epidemiology and Biostatistics, George Washington University, Washington, DC, United States
Centro de Investigación Biomédica en Red en Enfermedades Raras (CIBERER), Barcelona, SpainNeuromuscular Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, United Kingdom
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, United Kingdom
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, United Kingdom
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, United Kingdom
Charite Muscle Research Unit, Experimental and Clinical Research Center, a Joint Cooperation of the Charité Medical Faculty and the Max Delbrück Center for Molecular Medicine, Berlin, Germany
Department of Neurology Children's National Health System, Washington, DC, United StatesNational Institutes of Health (NINDS), Bethesda, MD, United States
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, United Kingdom
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, United Kingdom
Initial diagnosis does not predict subsequent pattern of muscle weakness in dysferlinopathy.
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Pattern of weakness is an overlapping continuum that does not form two distinct subgroups.
•
MM is a more common diagnosis in Japan than in Europe or the USA, but patients are not weaker distally.
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Patients should not be split into MM and LGMDR2 subgroups for clinical trials.
Abstract
This study aims to determine clinically relevant phenotypic differences between the two most common phenotypic classifications in dysferlinopathy, limb girdle muscular dystrophy R2 (LGMDR2) and Miyoshi myopathy (MMD1). LGMDR2 and MMD1 are reported to involve different muscles, with LGMDR2 showing predominant limb girdle weakness and MMD1 showing predominant distal lower limb weakness. We used heatmaps, regression analysis and principle component analysis of functional and Magnetic Resonance Imaging data to perform a cross-sectional review of the pattern of muscle involvement in 168 patients from the Jain Foundation's international Clinical Outcomes Study for Dysferlinopathy. We demonstrated that there is no clinically relevant difference in proximal vs distal involvement between diagnosis. There is a continuum of distal involvement at any given degree of proximal involvement and patients do not fall into discrete distally or proximally affected groups. There appeared to be geographical preference for a particular diagnosis, with MMD1 being more common in Japan and LGMDR2 in Europe and the USA. We conclude that the dysferlinopathies do not form two distinct phenotypic groups and therefore should not be split into separate cohorts of LGMDR2 and MM for the purposes of clinical management, enrolment in clinical trials or access to subsequent treatments.
Dysferlinopathy is an autosomal recessively inherited form of muscular dystrophy, which predominantly affects skeletal muscle, resulting in progressive weakness and muscle wasting.
Several clinical phenotypes are associated with mutations in the DYSF gene, most commonly limb girdle muscular dystrophy R2 (LGMDR2) and Miyoshi myopathy type 1 (MMD1). LGMDR2 describes a phenotype with predominant proximal lower and upper limb weakness at presentation [
229th ENMC international workshop: limb girdle muscular dystrophies - Nomenclature and reformed classification Naarden, the Netherlands, 17-19 March 2017.
Autosomal recessive distal muscular dystrophy as a new type of progressive muscular dystrophy: seventeen cases in eight families including an autopsied case.
]. Patients with the same DYSF mutations, including full siblings, have been described with clinically different patterns of weakness and ascribed different phenotypic diagnoses [
]. However, doubt about the presence of two truly distinct diagnosis was raised when pattern of muscle involvement on lower limb MRI was shown not to differ between LGMDR2 and MMD1 [
]. Multiple clinical diagnoses creates difficulties for trial design and therapy licencing. Pharmaceutical companies want to develop therapies for as many patients as possible, which is particularly important in a rare disease like dysferlinopathy. Regulators want to know if results from a trial involving LGMDR2 patients are applicable to patients with MMD1.
Here we compare the demographic, MRI, functional and genetic differences between 168 genetically confirmed dysferlinopathy patients with a clinical diagnosis of LGMDR2 or MMD1 to determine if they are distinct clinical phenotypes.
2. Methods
We analysed data from 168 patients with genetically confirmed dysferlinopathy enrolled in the Jain Foundation's 3-year longitudinal Clinical Outcomes Study for Dysferlinopathy (COS). This study received ethical approval in all participating countries. Participants attended 15 international sites for six evaluations (screening, baseline, 6 months, 12 months, 24 months, 36 months) between November 2012 and March 2018. Visits involved medical review, functional assessments and T1 weighted MRI of the lower limb muscles. The study protocol, patient demographics and genetic information, baseline results and a review of functional progression have been previously published [
Individual centres identified patients with dysferlinopathy from clinic lists to invite for screening. At study enrolment, 209 patients were screened and 197 met the inclusion criteria. Diagnostic inclusion criteria were the presence of a) two (predicted) pathogenic mutations in the DYSF gene, b) one (predicted) pathogenic mutation and absent dysferlin on muscle immunoblot or c), one (predicted) pathogenic mutation and dysferlin protein level ≤20% of normal level determined by blood monocyte testing. Patients also needed to be ≥ 10 years of age, able to perform study assessments, attend appointments and provide informed consent. Exclusion criteria were the presence of significant co-morbidity (in the opinion of the consenting clinician) or anticipated medical intervention which might interfere with ability to attend the assessments. Genetic and protein expression information are shown in supplementary Tables 1 and 2 and in Fig. 1.
Fig. 1Lollipop chart showing the location of pathogenic mutations in dysferlin exons. The chart separates mutations in LGMDR2 patients (top row), MMD1 patients (second row) and then shows those mutations that occur in both groups of patients (bottom row). The height of the bar corresponds to mutation frequency. Black circles denote truncating mutations and green circles denote missense mutations. This figure was generated using the open source ‘mutation mapper’ at https://www.cbioportal.org/mutation_mapper.
Of these 197, all 10 patients from one site have been excluded from further analysis due to incomplete longitudinal data. One further patient became ineligible, after further genetic analysis identified a collagen VI related myopathy.
Patients’ current clinical diagnosis was reported by the assessing clinician at screening either from reference to clinical notes (sites seeing local patients) or from patient self-report of the diagnosis given by their usual clinician (out of area patients). Of the 186 patients, 18 did not report a diagnosis of MMD1 or LGMDR2 – but rather proximodistal dysferlinopathy, asymptomatic hyperCKaemia, pseudometabolic dysferlinopathy or paravertebral muscular dystrophy. They were therefore excluded from this analysis, leaving 168 patients who had a baseline assessment. Of these, five further patients dropped out before year 2 and three missed the visit window, giving 160 (95%) with a 36-month assessment.
We used Wilcoxon rank sum testing to compare mean age of onset of muscle weakness (patient reported) and duration of symptoms and Chi-squared testing for comparing gender, previous steroid use, teenage exercise level and specific sports performed between groups.
We categorised teenage exercise levels into high and low, based on the metabolic equivalents and frequency of the exercise reported by patients, as previously described [
]. High levels of exercise describe ‘moderate activity multiple times per week or vigorous activity at least weekly’, with low levels as less than this.
To compare the pattern of muscle involvement between LGMDR2 and MMD1, we used assessments that graded functional ability or pathology in various muscle groups; North Star assessment for limb girdle type muscular dystrophies (NSAD), manual muscle testing (MMT) scores and Mercuri scores from T1 MRI. NSAD scores were taken from the year 2 study visit. MRI and MMT results were from the baseline assessment as this visit had the most complete assessments. Semiquantitative assessment of MRIs were performed by a blinded neurologist (RF-T) and radiologist (JL), who independently evaluated axial T1-weighted sequences with the Lamminen-Mercuri visual scale, as previously reported [
]. Patients with missing data were excluded from the analysis of the scale for which they did not have data. When the scales were combined, only patients with data from all of the scales were included in the comparison. Numbers of patients with complete data for each assessment are detailed below.
2.1 NSAD score
The NSAD score is a dysferlinopathy specific functional scale of motor performance, developed using RASCH analysis, which demonstrates measurable change over one year in Dysferlinopathy [
]. The scale comprises 29 tasks involving both upper and lower limbs, testing proximal and distal muscle function. Patients can score 0, 1 or 2 in each domain of the scale, corresponding to ‘unable to perform task’, ‘modified method, but achieves task independent of physical assistance from another’ and ‘able to perform task’. Score declines as functional abilities are lost. As the scale was developed using the first assessments in the natural history study, direct measurements using the new scale were not performed until the year 2 visit. The NSAD scores used in this analysis are therefore from the year 2 visit.
To compare the order in which functional abilities were impacted, we ordered NSAD items by the cohorts mean score for each item. Items with the lowest score were those that fewest patients could complete. Thus, the order demonstrated the average sequence in which the ability to perform an item were lost. All item scores of each patient with LGMDR2 were compared to those with MMD1 using a heatmap (Fig. 2a). Mean item scores for LGMDR2 and MMD1 patients were compared using linear regression (Fig. 2b). Points above the regression line represent preserved ability to complete these items, relative to other items, in MMD1 compared to LGMDR2. The standardised residual for each item was calculated using the R Function “rstandard()”.
Fig. 2Functional ability on the NSAD score compared by clinical diagnosis. A: Heatmap of individual patients NSAD scores, split by clinical diagnosis of LGMDR2 or MMD1 (n = 130). B: Scatter plot with linear regression line of the mean score on each component of the NSAD assessment for patients with a clinical diagnosis of LGMDR2 compared to patients with a clinical diagnosis of MMD1 (n = 130).
The MMT score is a clinical measurement of strength widely used in general clinical practice. We used an 11 point conversion of the 5 point MRC scale (0, 1, 2, 3−, 3, 3+, 4−, 4, 4+, 5−, and 5) [
]. We ordered each movement by the mean MMT scores achieved by the cohort, as done for NSAD scores, and compared scores of each individual patient using a heatmap (Fig. 3a). Mean muscle MMT scores for LGMDR2 and MMD1 patients were compared using linear regression (Fig. 3b).
Fig. 3Pattern of weakness assessed by the MMT score compared by clinical diagnosis. A: Heatmap of individual patients MMT scores, split by clinical diagnosis of LGMDR2 or MMD1, (n = 143). B: Scatter plot with linear regression line of the mean score for each movement tested by MMT for patients with a clinical diagnosis of LGMDR2 compared to patients with a clinical diagnosis of MMD1 (n = 143). C: Scatter plot with linear regression line of mean distal MMT score against mean proximal MMT score for each individual patient (n = 143).
Repeating the methods above, a heatmap was created for Mercuri MRI scores (Fig. 4a) and linear regression performed comparing the mean Mercuri score for each muscle between the two diagnoses (Fig. 4b). Mercuri scoring of the MRIs was performed manually with visual inspection of the muscle image [
Fig. 4Pattern of weakness assessed by Mercuri scoring of leg T1W MRI compared by clinical diagnosis. A: Heatmap of individual patients Mercuri MRI scores, split by clinical diagnosis of LGMDR2 or MMD1 (n = 59). B: Scatter plot with linear regression line of mean Mercuri score for each leg muscle for patients with a clinical diagnosis of LGMDR2 compared to patients with a clinical diagnosis of MMD1 (n = 59). C: Scatter plot with linear regression line of Mean Mercuri grading for each distal muscle against mean Mercuri grading for each proximal muscle (n = 59).
To assess for subgroups of distally or proximally affected patients irrespective of clinical diagnosis, we compared proximal and distal MMT and Mercuri scores. The mean MMT score of distal muscles was plotted against the mean MMT score of proximal muscles for each individual to create a distal: proximal scatter plot (Fig. 3c). This method was repeated for Mercuri MRI scores (Fig. 4c). All muscle groups listed in the heat maps were used. ‘Proximal’ muscles were those above, or working across, the knee or elbow and ‘distal’ muscles were below the knee or elbow, working across the ankle or wrist.
As mean values were not normally distributed, the median MMT ratio was calculated for LGMDR2 and for MMD1 and compared using a Wilcoxon signed rank test. The Spearman's correlation coefficient between distal and proximal muscle groups for LGMDR2 and for MMD1 was compared using z-scores for a two tailed test, after a Fisher z transformation. Power calculation demonstrated 87% power to detect a difference in median distal:proximal MMT score ratio of >0.2.
To assess for site specific differences in muscle involvement, the mean MMT and MRI Mercuri score distal: proximal ratios were compared between patients from Tokyo (high number of MMD1 patients) and Newcastle (high number of LGMDR2 patients) using a scatter plot and Spearman's correlation (Fig. 6a and b) in the same way as for comparing clinical diagnosis.
Post-hoc power calculations, to assess the ability to detect differences between MMD1 and LGMD groups, were performed using an online tool [
]. This was completed for NSAD scores, MMT scores and MRI both individually and with all three assessments combined. PCA is a statistical analysis and data visualisation tool for comparing multiple variables [
]. It takes all of the variables for each individual and positions that individual on a 2D chart of principal components, in a way that maximises the variation between individuals. This means that each variable becomes a vector along which individuals are positioned. In this way, groups of individuals with distinct characteristics are separated – for example if MMD1 patients had a weaker soleus muscle relative to the rectus femoris than LGMDR2 patients, then MMD1 and LGMDR2 would form two distinct groups on the PCA, without the programmer needing to know which variable would pick out the differences.
2.6 Data availability statement
Anonymised aggregate data will be provided on reasonable request. Requests should be made to the clinical outcomes study steering committee by contacting the corresponding author.
3. Results
3.1 Demographics
At baseline, the cohort consisted of 114 patients with a clinical diagnosis of LGMDR2 and 54 patients with MMD1 (Table 1). Age at symptom onset and at assessment did not differ between clinical diagnoses (p > 0.05). Median symptom duration was higher in MMD1 patients than in LGMDR2 patients (p = 0.048). Gender, proportion of non-ambulant patients, previous steroid treatment and teenage exercise intensity did not differ between clinical diagnoses (p > 0.05).
Symptom duration differs between groups (p = 0.048 on Wilcoxon rank sum test). Gender, previous steroid treatment and teenage activity category not significantly different on Chi squared testing.
(range)
14 yrs (1–51)
20 yrs (4–45)
Male: female
45:69
30:24
Ambulant
86 (75%)
37(69%)
Previous steroid treatment
38 (33%)
26 (48%)
active teenage lifestyle (cat 2/3)
74 (65%)
35 (65%)
Ethnicity
White (%)
79 (69%)
38 (70%)
Asian (%)
21 (18%)
11 (20%)
Black (%)
3 (3%)
0 (0%)
Hispanic (%)
9 (8%)
2 (4%)
Mixed race (%)
2 (2%)
0 (0%)
Other (%)
0 (0%)
3 (6%)
Patient location
Europe (%)
65 (57%)
27 (50%)
Spain (Barcelona, Seville)
9 (5, 4)
6 (0, 6)
Italy (Padova)
7
8
Germany (Berlin, Munich)
11 (4, 7)
2 (0, 2)
France (Paris)
4
6
UK (Newcastle)
34
5
USA (Charlotte, Columbus, Stanford, St Louis, Washington DC) (%)
Using Chi squared test patients were more likely to have a MMD1 diagnosis in Japan than in Europe (p = 0.01) or US sites (p = 0.02).
(Tokyo) (%)
4 (4%)
9 (17%)
No difference in age symptom onset or age at assessment on Wilcoxon rank sum test.
Symptom duration differs between groups (p = 0.048 on Wilcoxon rank sum test).Gender, previous steroid treatment and teenage activity category not significantly different on Chi squared testing.
Using Chi squared test patients were more likely to have a MMD1 diagnosis in Japan than in Europe (p = 0.01) or US sites (p = 0.02).
LGMDR2 and MMD1 occurred in patients with the same genotype, with 12 patients showing the same pair of mutations as a patient with the other clinical diagnosis (supplementary Table 1 and 2). Discordant phenotypes for the same genotype did not segregate based on gender, ethnicity, location or teenage exercise level. There were 12 pairs of siblings, who all shared their sibling's diagnosis.
Patients with both LGMDR2 and MMD1 displayed a range of missense, non-sense and splice site mutations throughout the length of the DYSF gene. Neither group displayed a mutational hotspot (Fig. 1).
3.3 NSAD sequence
NSAD scores were available for 130 patients at visit 5 (86 LGMDR2 and 44 MMD1). Scores were generally lower for the MMD1 patients (Fig. 2b), suggesting a weaker cohort. The sequence in which functional abilities were lost was variable between patients but similar between LGMDR2 and MMD1 (Fig. 2a and 1b). The most common ability to be lost was standing on tiptoes for both clinical diagnoses (Fig. 2b). In general, distal functions appeared below the regression line, suggesting they were more impaired in MMD1 than LGMDR2 patients for a given overall score, although standardised residuals for all items were small (<1.5).
3.4 MMT sequence
Complete MMT scores were available for 143 patients at baseline (visit 2) (95 LGMDR2 and 48 MMD1. Scores were generally lower for the MMD1 patients (Fig. 3b). The sequence in which MMT scores deteriorated was variable between patients (Fig. 3a) but similar between LGMDR2 and MMD1 (Fig. 3b). Distal lower limb movements appeared slightly more affected in MMD1, (below the regression line in Fig. 3b), particularly ankle plantar flexion (knee flexed), which showed the largest residual. Proximal lower limb movements were involved slightly more prominently in LGMDR2, with hip extension having the largest residual. Upper limb movements were generally less affected in both groups of patients and did not appear to separate by diagnosis. Overall, while the ratio of mean distal: proximal involvement did vary between patients (Fig. 3c) it did not vary by diagnosis, with no significant difference between median distal: proximal ratios (LGMDR2 = 1.06, MMD1 = 0.97, p = 0.1) and no difference between regression coefficient (p = 0.10) (Fig. 3c). Sample size was adequate to detect a true difference in ratio of greater than 0.18. These ratios did not highlight discrete groups of distally or proximally affected patients, irrespective of diagnosis (Fig. 3c).
3.5 MRI sequence
A complete set of Mercuri scores for thigh and lower leg muscles (whole leg) was available for 59 patients (39 LGMD and 20 MMD1) and for lower leg muscles for 131 patients (84 LGMDR2 and 47 MMD1) at their baseline visit. Mercuri scores across all muscles were generally lower for the MMD1 patients (Fig. 4b). Heatmaps and regression showed a variable pattern of muscle involvement between patients (whole leg – Fig. 4a, lower leg – Fig. 5), but the sequence of severity of involvement was similar between LGMDR2 and MMD1 (whole leg - Fig. 4b). The largest standardised residuals were seen for the gastrocnemius medialis muscle, being more prominently involved in LGMDR2 than MMD1, and for the adductor longus muscle, being more prominently involved in MMD1 than in LGMDR2. The ratio of mean distal: proximal involvement did vary between patients (Fig. 4c), but not by diagnosis, with no difference between median distal: proximal ratio (LGMDR2 = 1.08, MMD1 = 1.04, p = 0.97) and no difference between regression coefficient (p = 0.59) (Fig. 4c). Sample size was adequate to detect a true difference in ratio of greater than 0.37. These ratios did not highlight discrete groups of distally or proximally affected patients, irrespective of diagnosis (Fig. 4c).
Fig. 5Heatmap of the lower leg T1W MRI Mercuri scores (n = 131) by clinical diagnosis.
A greater proportion of Japanese patients had a diagnosis of MMD1 (64%) than Europeans (30%, true difference on chi-squared p = 0.01) or Americans (32%, p = 0.02). In comparing patients from Tokyo (high proportion of MMD1) and Newcastle (high proportion of LGMDR2), there was no difference in regression coefficients for distal: proximal MMT (p = 0.87) and Mercuri MRI (p = 0.56) scores (Fig. 6a and b). In Newcastle, all patients with an MMD1 diagnosis showed relative distal weakness on MMT distal: proximal ratio, while the pattern was more varied in LGMDR2 patients (Fig. 6a). In Tokyo, all patients with an LGMDR2 diagnosis showed relative proximal weakness on MMT distal: proximal ratio, while the pattern was more varied in MMD1 patients (Fig. 6a). On MRI, patients distal: proximal ratio of Mercuri scores did not group by diagnosis at either site (Figure b). PCA analysis of NSAD score, MMT score and MRI did not split Tokyo and Newcastle patients into distinct groups (Fig. 7b)
Fig. 6Comparison of distal vs proximal weakness in Newcastle and Tokyo. A: Mean distal MMT score against mean proximal MMT score for each individual patient in Newcastle (n = 30) and Tokyo (n = 12). There was no significant difference between Spearman's R coefficient (p = 0.87). B: Mean distal Mercuri score against mean proximal Mercuri score for each individual patient in Newcastle (n = 26) and Tokyo (n = 11). There was no significant difference between Spearman's R coefficient (p = 0.56).
Fig. 7Principal component analysis of assessments between a. diagnosis and b. study site. A: Principle component analysis (PCA) of NSAD, MMT scores and lower leg Mercuri MRI score showing no difference in weighting of principle components between diagnoses. B: Principle component analysis (PCA) of NSAD, MMT scores and lower leg Mercuri MRI score showing no difference in weighting of principle components between Newcastle and Tokyo.
LGMDR2 and MMD1 patients did not separate into distinct groups based on PCA analysis of NSAD score, MMT score or MRI analysis when each scoring systems was assessed individually (data not shown) or when combined (Fig. 7a).
4. Discussion
We have demonstrated that MMT scores, the NSAD and the pattern of muscle involvement on MRI were similar between the two most common clinical diagnoses in dysferlinopathy - MMD1 and LGMDR2.
Distal involvement was common to both diagnoses, even in patients with otherwise mild functional impairment, with difficulty standing on tiptoes being the most commonly affected function in both LGMDR2 and MMD1. Although MMD1 patients showed a slightly more distal phenotype, with ankle plantar flexion (knee flexed) and some distal NSAD functions being more prominently involved than in LGMDR2, these differences were not statistically significant and there was a high degree of overlap in pattern of weakness between both diagnoses. Upper limb involvement, as measured by MMT scores and functional elements, was less common in both diagnosis and distal upper limb weakness was not more common in either group.
In addition to the overlap between groups, some patients with an MMD1 diagnosis displayed an LMGDR2 phenotype, with striking preservation of distal strength but marked proximal weakness and vice versa for LGMDR2 patients displaying an MMD1 phenotype. This suggests either that phenotypes were variable and have changed since the time of diagnosis, or that factors other than pattern of weakness influenced the diagnosis.
One potential factor influencing diagnosis is a sites’ previous experience. A clinical diagnosis of MMD1 was more common in Japan while a diagnosis of LGMDR2 was more common in Europe and the United States; however, we found no purely ethnic variation in diagnosis prevalence, no distinct patterns of weakness on PCA and no variation in the degree of distal muscle involvement between sites. Only those Tokyo patients with markedly greater proximal than distal weakness had an LGMDR2 diagnosis, while patients in Newcastle only had an MMD1 diagnosis if they were particularly weak distally. We speculate that this may be explained by a geographical preference for diagnosis. Japanese sites may be more likely to diagnose MMD1 as the default, unless presentation is strikingly different, due to site experience, as MMD1 was first described in a Japanese cohort [
Autosomal recessive distal muscular dystrophy as a new type of progressive muscular dystrophy: seventeen cases in eight families including an autopsied case.
]. However, we did not assess what the pattern of weakness was at initial presentation. It remains possible that a true difference in pattern of presentation exists, but this study was not close enough to the time of diagnosis, and that MMD1 and LGMDR2 were both described in the geographic locations where each presentation was more common.
A potential weakness in this study is the wide range of age and disease severity of patients when they were assessed. MMD1 patients had generally had symptoms for longer, were slightly weaker than the LGMDR2 patients and may have presented later initially if they only had mild calf weakness. In addition, because the NSAD assessment was developed and validated during COS, the most complete scores were from the year 2 (5th) visit, adding a further 2 years to each individual's disease progression at the point of assessment. The variation between individuals was greatest in less affected patients, so it is possible that a larger cohort of minimally affected patients would demonstrate true phenotypic differences. However, in this cohort, even amongst the mildly affected patients, the pattern of muscle involvement varied and overlapped between diagnostic groups. Even if there were a difference early in the disease course, it seems that the clinical diagnoses given at presentation does not continue to best describe the phenotype of a dysferlinopathy patient several years into their disease.
Although not forming distinct groups, a wide range in pattern of muscle involvement is evident and suggests there may be multiple, rather than a single, genetic or environmental disease modifying factors [
]. The variation is not explained by the underlying dysferlin mutations, as patients in this (and previous) studies with the same dysferlin genotype have different clinical diagnoses and patterns of weakness [
]. Ethnicity also does not seem to influence diagnostic prevalence. We also reviewed exercise intensity and type, which are known to vary culturally, [
] but did not identify any association with clinical diagnosis. This suggests that pattern of weakness is not related to demographic factors, such that these findings should be generalizable to the wider population of patients with dysferlinopathy.
The patient population with dysferlinopathy demonstrate variation in rates of disease progression and the degree of distal:proximal muscle involvement, particularly early in the disease. Developing interventional therapies for such a heterogenous cohort is complex and there are incentives to form smaller, more homogeneous cohorts of patients. However, for several reasons, we argue that a patient's clinical diagnosis should not be the element used to create cohorts for clinical trials:
(1)
Diagnostic criteria for each diagnosis are not clearly defined allowing individual and regional variation in ascribing diagnosis.
(2)
There is significant phenotypic overlap between clinical diagnostic groups even in early stages.
(3)
Validated, dysferlinopathy specific, outcome measures (the NSAD) are available that incorporate both distal and proximal muscle functions to allow progression to be monitored across the spectrum of disease.
(4)
Outcome measures including the NSAD, 10 m walk and timed up and go show no difference in rate of progression over three years between patients with MMD1 and LGMDR2 [
These points suggest that combining the clinical diagnoses of MMD1 or LGMDR2 into a common unified group of ‘dysferlinopathies’, is important for clinical trials in order to prevent potential detrimental artificial distinctions and the risk oftreatments being developed with and for one specific group and not the other, when both could benefit.
Mutations in the DYSF gene are associated with multiple different clinical diagnoses, including LGMDR2 and MMD1. We have shown that pattern of weakness did not separate patients into distinct clinical entities, with significant functional overlap between and within diagnostic groups. Initial clinical diagnosis was not a reliable predictor of future pattern of weakness, functional ability or rate of deterioration. Therefore, for the purposes of monitoring and the evaluation of therapeutic interventions, we recommend that patients with dysferlinopathy be considered as a single cohort, rather than being separated based on initial clinical diagnosis.
Declaration of Competing Interest
None.
Acknowledgments
This study has only been possible thanks to the international collaboration of several specialised centres promoted by the Jain Foundation. The Jain COS consortium would like to thank the study participants and their families for their invaluable contribution and would also like to acknowledge the ongoing support the Jain Foundation provides in the development, management, and analysis of this Study. The Jain Foundation, based in Seattle, USA, is entirely focused on LGMD2B/dysferlinopathy/Miyoshi Myopathy. The foundation does not solicit funding from patients, but instead funds research and clinical studies worldwide with the goal of finding treatments for dysferlinopathy. Please visit www.jain-foundation.org for more information about the foundation and if you are a patient suffering from dysferlinopathy, please consider enrolling into their interactive dysferlinopathy registry that seeks to build a strong, engaged, and supportive community ([email protected]).
Statistical analysis
Statistics conducted by Dr Ursula Moore, academic affiliation 1.
Statistical approach advised by Dr Heather Gordish Dressman, academic affiliation 2 and 3.
Study funding
The estimated $4 million USD needed to fund this study was provided by the Jain Foundation.
Volker Straub was supported by an MRC strategic award to establish an International Centre for Genomic Medicine in Neuromuscular Diseases (ICGNMD) MR/S005021/1
Study sponsorship and author disclosures
The estimated $4 million USD needed to fund this study was provided by the Jain Foundation.
Volker Straub was supported by an MRC strategic award to establish an International Centre for Genomic Medicine in Neuromuscular Diseases (ICGNMD) MR/S005021/1
As detailed below individuals disclosure interests outside the scope of this work and the grant from the Jain Foundation. As a natural history study, there are no products that are being tested in this study. Therefore in the view of the corresponding author and consortium lead there are no conflicts of interest relevant to this work.
Ursula Moore reports the grant from the Jain Foundation
Heather Gordish reports the grant from the Jain Foundation
Jordi Díaz-Manera reports no disclosures
Meredith K. James reports the grant from the Jain Foundation
Anna G. Mayhew reports no disclosures
Michela Guglieri reports the grant from the Jain Foundation
Roberto Ferenandez Torron reports no disclosures
Laura E. Rufibach works for the Jain Foundation
Jia Feng reports no disclosures
Andrew M. Blamire reports the grant from the Jain Foundation
Pierre G. Carlier MD reports no disclosures
Simone Spuler reports no disclosures
John W. Day reports the grant from the Jain Foundation, personal fees from Biogen, Ionis, Avexis, Roche, Sarepta, Sanofi, Genzyme, Scholar Rock, Pfizer plus patents from Athena Diagnostics.
Kristi J. Jones reports no disclosures
Diana X. Bharucha-Goebel reports membership of the Gene Therapy Network (Avexis)
Emmanuelle Salort-Campana reports no disclosures
Alan Pestronk reports the grant from the Jain Foundation
Sabine Krause reports no disclosures
Olivia Schreiber-Katz reports grants from the German Neuromuscular Society (DGM e.V.) and from the Young Faculty Program of Hannover Medical School; personal fees and non-financial support from Biogen GmbH, outside the submitted work.
Maggie C. Walter reports advisory board membership for Avexis, Biogen, Novartis, Roche, Santhera, Sarepta, PTC Therapeutics, Ultragenyx, Wave Sciences, plus personal fees from Novartis, Biogen, Ultragenyx, Santhera, PTC Therapeutics, Ask Bio, Audentes Therapeutics, Fulcrum Therapeutics, GIG Consul, Guidepoint Global, Novartis, PTC, Gruenthal Pharma,
Carmen Paradas reports no disclosures
Tanya Stojkovic reports no disclosures
Madoka Mori-Yoshimura reports no disclosures
Elena Bravver deceased
Elena Pegoraro reports grants, personal fees and non financial support from Santhera, personal fees and nonfinancial support from Sarepta, Personal fees and non financial support from PTC pharmaceuticals all outside this submitted work.
Linda Pax Lowes reports no disclosures
Jerry R. Mendell reports no disclosures
Kate Bushby reports no disclosures
Volker Straub reports the Jain Foundation grant and other grants and personal fees from Sarepta Therapeutics.
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, UK
conception and design of the study, acquisition and analysis of data, preparation of the manuscript
Heather Gordish
Centre for translational science, division of biostatistics and study methodology, children's national health system, washington, dc, usa,
Review and design of statistical analysis for the study, drafting
Jordi Diaz-Manera
Neuromuscular Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau,
Conception and design of the study, acquisition and analysis of data, drafting
Meredith K. James
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, UK
Conception and design of the study, acquisition and analysis of data, drafting
Anna G. Mayhew
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, UK
Conception and design of the study, acquisition and analysis of data, drafting
Michela Gulgieri
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, UK
Acquisition and analysis of data, drafting
Roberto Fernandez Torron
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, UK
Acquisition and analysis of data
Laura E. Rufibach
6 The Jain Foundation, Seattle, Washington, USA
Conception and design of the study, acquisition and analysis of data, drafting
Jia Feng
Centre for translational science, division of biostatistics and study methodology, children's national health system, washington, dc, usa,
Acquisition and analysis of data
Andrew M. Blamire
Magnetic Resonance Centre, Translational and Clinical Research Institute, Newcastle University, UK
Conception and design of the study, drafting
Pierre G. Carlier
AIM & CEA NMR Laboratory, Institute of Myology, Pitié-Salpêtrière University Hospital, 47–83, Paris, France
Conception and design of the study, drafting
Simone Spuler
Charite Muscle Research Unit, Experimental and Clinical Research Centre, a joint cooperation of the Charité Medical Faculty and the Max Delbrück Centre for Molecular Medicine, Berlin, Germany
Acquisition and analysis of data, drafting
John W. Day
Department of Neurology and Neurological Sciences, Stanford University School of Medicine; Stanford, CA, USA
Acquisition and analysis of data, drafting
Kristi J. Jones
The Children's Hospital at Westmead, and The University of Sydney, Australia.
Acquisition and analysis of data, drafting
Diana X. Bharucha-Goebel
Department of Neurology Children's National Health System, Washington, DC, USA
Acquisition and analysis of data, drafting
Emmanuelle Salort- Campana
Service des maladies neuromusculaire et de la SLA, Hôpital de La Timone, Marseille, France
Acquisition and analysis of data, drafting
Alan Pestronk
Department of Neurology Washington University School of Medicine, St. Louis, MO, USA
Acquisition and analysis of data, drafting
Maggie C. Walter
Friedrich-Baur-Institute, Dept. of Neurology, Ludwig-Maximilians-University of Munich, Germany
Acquisition and analysis of data, drafting
Carmen Paradas
Neuromuscular Unit, Department of Neurology, Hospital U. Virgen del Rocío/Instituto de Biomedicina de Sevilla, Sevilla, Spain
Acquisition and analysis of data, drafting
Tanya Stojkovic
Centre de référence des maladies neuromusculaires, Institut de Myologie, AP-HP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
Acquisition and analysis of data, drafting
Madoka Mori-Yoshimura
Department of Neurology, National Centre Hospital, National Centre of Neurology and Psychiatry Tokyo, Japan
Acquisition and analysis of data, drafting
Elena Bravver
Neuroscience Institute, Carolinas Neuromuscular/ALS-MDA Centre, Carolinas HealthCare System, Charlotte, NC, USA.
Acquisition and analysis of data, drafting
Elena Pegoraro
Department of Neuroscience, University of Padova, Italy
Acquisition and analysis of data, drafting
Linda Pax Lowes
The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio USA
Acquisition and analysis of data, drafting
Jerry R. Mendell
The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio USA
Acquisition and analysis of data, drafting
Kate Bushby
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, UK
Study design, acquisition and analysis of data, drafting
Volker Straub
The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Central Parkway, Newcastle upon Tyne, UK
Conception and design of the study, acquisition and analysis of data, drafting, final sign off, corresponding author
Appendix 2 Coinvestigators - The Jain COS Consortium
We acknowledge the work of the following members of the Consortium who have contributed to the collection of the data, but do not qualify for authorship on this paper.
Tabled
1
Name
Location
Role
Contribution
Marni Jacobs
Children's National Medical Centre Washington DC, USA
Study Statistician
Oversight of data management Data Management and Training
Adrienne Arrieta MS
Children's National Medical Centre Washington DC,
Lead Data Management Expert
Data Base development and training
Esther Hwang
Jain Foundation, Seattle, USA-
Patient Advocate
Development of study questionnaires Recruitment,
Elaine Lee PhD
Jain Foundation, Seattle, USA-,
Patient Advocate
Development of study questionnaires Recruitment
Isabel Illa MD
Hospital de la Santa Creu i Sant Pau/ CIBERER, Barcelona, Spain
Director of the Neuromuscular Unit
Study Design
Eduard Gallardo MD
Hospital de la Santa Creu i Sant Pau/ CIBERER, Barcelona, Spain
Consultant Scientist
Confirmation of Eligibility using monocyte assay
Izaskun Belmonte Jimeno PT
Servei de Medicina F ísica i Rehabilitació, Hospital de la Santa Creu i Sant Pau
Physiotherapist
Acquisition of physiotherapy data
Elena Montiel- Morillo
Servei de Medicina F ísica i Rehabilitació, Hospital de la Santa Creu i Sant Pau
Physiotherapist
Acquisition of physiotherapy data
Irene Pedrosa- Hernandez
Servei de Medicina F ísica i Rehabilitació, Hospital de la Santa Creu i Sant Pau
Physiotherapist
Acquisition of physiotherapy data
Jaume LLauger Rossello
Radiology department, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain,
Radiologist
Collection and Analysis of MRI data
Bruce Harwick
Department of Radiology, CMC Mercy Charlotte, Carolinas Healthcare System Neurosciences Institute, Charlotte, NC, USA
NMR Technologist
MRI Data Acquistion
Jackie Sykes RN, BSN
Carolinas HealthCare System, Charlotte, NC,
Study Coordinator
Study Coordination and Data Management
Susan Sparks
Carolinas HealthCare System, Charlotte, NC,
Neurologist
Recruiting PI and PI for first three visits.
Scott Holsten
Carolinas HealthCare System, Charlotte, NC,
Physiotherapist
Acquisition of physiotherapy data
Lindsay Alfano
Nationwide Children's Hospital, Columbus, OH,
Physiotherapist
Acquisition of physiotherapy data
Brent Yetter, MS
Nationwide Children's Hospital, Columbus, OH,
Study Coordinator
Study Coordination and Data Management
Mark Smith MS, DABMP RT(MR)
Department of Radiology, Nationwide Children's Hospital, Columbus, OH, USA,
MRI Technologist
MRI Data Acquisition
Bernard Lapeyssonie PT
Neuromuscular and ALS Centre, La Timone Hospital, Aix-Marseille Université, Marseille,
Physiotherapist
Acquisition of physiotherapy data
Bruno Vandevelde
Neuromuscular and ALS Centre, La Timone Hospital, Aix-Marseille Université, Marseille,
Physiotherapist
Acquisition of physiotherapy data
David Bendahan PhD
Centre de Résonance, MagnétiqueBiologique et Médicale, UMR CNRS 7339, Marseille, France,
MRI Lead
MRI Technologist
Yann Le Fur PhD
Aix-Marseille Université, Marseille, France,
MRI Technologist
MRI Data Acquisition
Attarian Shahram, MD, PhD
Neuromuscular and ALS Centre, La Timone Hospital, Aix-Marseille Université, Marseille,
Study Doctor
Medical History, Medical and Physical Examination
Testot-Ferry Albane, CRA
Neuromuscular and ALS Centre, La Timone Hospital, Aix-Marseille Université, Marseille,
Study Coordinator
Study Coordination and Data Management
Eva M. Coppenrath MD,
Department of Clinical Radiology, Ludwig-Maximilians-University Munich, Germany,
Radiologist
MRI Data Acquisition
Simone Thiele
Ludwig-Maximilians-University Munich, Germany,
Physiotherapist
Acquisition of physiotherapy data
Sabine Krause
Ludwig-Maximilians-University Munich, Germany,
Study Doctor
Medical History, Medical and Physical Examination
Olivia Schreiber- Katz
Ludwig-Maximilians-University Munich, Germany,
Study Doctor
Medical History, Medical and Physical Examination
Elizabeth Harris MD
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne, UK
Study Doctor
Medical History, Medical and Physical Examination
Michela Guglieri MD
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne,
Study Doctor
Medical History, Medical and Physical Examination
Teresinha Evangelista MD
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne,
Study Doctor
Medical History, Medical and Physical Examination
Alex Murphy MD
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne,
Study Doctor
Medical History, Medical and Physical Examination
Michelle Eagle PhD
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne,
Physiotherapist
Study Design, Acquisition of physiotherapy data
Heather Hilsden
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne,
Project Manager
Coordination of whole study
Robert Muni Lofra
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne,
Physiotherapist
Acquisition of physiotherapy data
Dionne Moat BSc
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne,
Physiotherapist
Acquisition of physiotherapy data
Jassi Amritpal Singh Sodhi BSc
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne,
Physiotherapist
Acquisition of physiotherapy data
Helen Sutherland
The John Walton Muscular Dystrophy Research Centre, Newcastle upon Tyne,
Clinical Trial and Data Manager
Study Coordination and Data Management
Tim Hodgson MClinRES,
Magnetic Resonance Centre, Newcastle University, UK,
Radiologist
MRI Data Acquisition
Fiona E. Smith
Magnetic Resonance Centre, Newcastle University, UK,
NMR Scientist
MRI analysis and Training
Ian Wilson
Magnetic Resonance Centre, Newcastle University, UK,
NMR Scientist
MRI analysis
Dorothy Wallace BSc,
Magnetic Resonance Centre, Institute for Cellular Medicine, Newcastle University, UK,
Radiologist
MRI Data Acquisition
Louise Ward DCR,
Magnetic Resonance Centre, Institute for Cellular Medicine, Newcastle University, UK
Radiologist
MRI Data Acquisition
Debra Galley
Magnetic Resonance Centre, Newcastle University,
Radiology Assistant
MRI Data Acquisition
Chiara Calore
University of Padova, Padova, Italy,
Study Doctor
Medical History, Medical and Physical Examination
Claudio Semplicini
University of Padova,
Sub PI
Acquisition of physiotherapy data Medical History, Medical and Physical Examination
Luca Bello
University of Padova, Padova, Italy,
Sub PI
Acquisition of physiotherapy data Medical History, Medical and Physical Examination
Roberto Stramare MD
Radiology Unit, Department of Medicine, University of Padova, Padova, Italy,
Radiologist
MRI Data Acquisition
Alessandro Rampado MRT
Radiology Unit, Department of Medicine, University of Padova, Padova, Italy,
Radiologist
MRI Data Acquisition
Aurelie Canal
Institut de Myologie, Paris,
Physiotherapist
Acquisition of physiotherapy data
Jean Yves Hogrel
Institut de Myologie, Paris,
Research Scientist
Supervision of Physiotherapy and Study Coordination
Suna Turk MSc
AIM & CEA NMR Laboratory, Institute of Myology, Pitié-Salpêtrière University Hospital, 47–83, Paris, France,
Radiologist
MRI Data Acquisition
Harmen Reyngoudt
AIM & CEA NMR Laboratory, Institute of Myology, Pitié-Salpêtrière University Hospital, 47–83, Paris, France,
NMR Scientist
MRI Training and analysis
Ericky Caldas
AIM & CEA NMR Laboratory, Institute of Myology, Pitié-Salpêtrière University Hospital, 47–83, Paris, France
NMR Scientist
MRI Training and analysis
Cyrille Theis
Institut de Myologie, Paris
Radiologist
MRI Data Acquisition
Oumar Diabaté
Institut de Myologie, Paris,
Study Coordinator
Study Coordination and Data Management
Matthew Harms
Washington University, St. Louis, MO, USA, Co PI
Co PI, Study Doctor
Recruitment, Medical History, Medical and Physical Examination
Julaine M. Florence
Washington University, St Louis, MO, USA,
Physiotherapist
Acquisition of physiotherapy data
Catherine Siener
Washington University, St Louis, MO, USA,
Physiotherapist
Acquisition of physiotherapy data
Linda Schimmoeller
Washington University, St. Louis, MO, USA,
Study Coordinator
Study Coordination and Data Management
Glenn Foster rtr (mr)
Centre for clinical imaging research ccir, washington university, st louis, mo, usa,
MRI Technologist
MRI Data Acquisition
Pilar Carbonell MD
Hospital U. Virgen del Rocío/Instituto de Biomedicina de Sevilla Seville,
Study Doctor
Medical History, Medical and Physical Examination
Macarena Cabrera MD
Hospital U. Virgen del Rocío/Instituto de Biomedicina de Sevilla, Seville,
Study Doctor
Medical History, Medical and Physical Examination
Juan Bosco Mendez
Hospital U. Virgen del Rocío/Instituto de Biomedicina de Sevilla, Seville,
Rehabilitation Doctor
Acquisition of physiotherapy data
Nieves Sanchez- Aguilera Praxedes
Hospital U. Virgen del Rocío/Instituto de Biomedicina de Sevilla, Seville,
Physiotherapist
Acquisition of physiotherapy data
Yolanda Morgado MD
Hospital U. Virgen de Valme /Instituto de Biomedicina de Sevilla, Seville,
Study Doctor
Medical History, Medical and Physical Examination
Susana Rico Gala MD
Department of Radiology, Hospital U. Virgen de Valme, Sevilla, Spain,
Radiologist
MRI Data Acquisition
Jennifer Perez
Stanford University School of Medicine, Stanford,
Study Coordinator
Study Coordination and Data Management
Anne Marie Sawyer FSMRT,
Lucas Centre for Imaging, Stanford University School of Medicine; Stanford, CA, USA
MRI Lead
MRI data acquisition
Carolina Tesi-Rocha
Stanford University School of Medicine; Stanford, CA, USA
Sub- I Study Doctor
Medical History, Medical and Physical Examination
Tina Duong
Stanford University School of Medicine; Stanford, CA, USA
Physiotherapist
Training of physiotherapists and Acquisition of physiotherapy data
Richard Gee
Stanford University School of Medicine; Stanford, CA, USA
Physiotherapist
Acquisition of physiotherapy data
Nigel F Clarke MD
Institute for Neuroscience and Muscle Research, Sydney r
Original PI. Deceased.
Recruitment and Study Design
Kristy Rose
Institute for Neuroscience and Muscle Research, Sydney
Physiotherapist
Training of physiotherapists and Acquisition of physiotherapy data
Sarah Sandaradura MD
Institute for Neuroscience and Muscle Research, Sydney
Study Doctor
Acquisition of Medical History, medical and physical assessments
Roula Ghaoui MD
Institute for Neuroscience and Muscle Research, Sydney
Study Doctor
Acquisition of Medical History, medical and physical assessments
Kayla Cornett
Institute for Neuroscience and Muscle Research, Sydney
Physiotherapist
Acquisition of physiotherapy data
Claire Miller PT
Institute for Neuroscience and Muscle Research, Sydney
Physiotherapist
Acquisition of physiotherapy data
Sheryl Foster MHlthSc
Department of Radiology, Westmead Hospital; Faculty of Health Sciences, The University of Sydney, Australia
Radiologist
MRI data acquistion
Anthony Peduto MBBS
Department of Radiology, Westmead Hospital; Faculty of Health Sciences, The University of Sydney, Australia,
Radiologist
MRI data acquistion
Noriko Sato MD PhD
Department of Radiology, National Centre Hospital, National Centre of Neurology and Psychiatry, Tokyo, Japan
Radiologist
MRI data acquistion
Takeshi Tamaru MRT
Department of Radiology, National Centre Hospital, National Centre of Neurology and Psychiatry, Tokyo, Japan,
Radiologist
MRI data acquistion
Shin'ich Takeda
National Centre of Neurology and Psychiatry, Tokyo,
Director
Supervision of Site Investigators
Ai Ashida PT
National Centre of Neurology and Psychiatry, Tokyo,
Physiotherapist
Acquisition of physiotherapy data
Chikako Sakamoto PT
National Centre of Neurology and Psychiatry, Tokyo,
Physiotherapist
Acquisition of physiotherapy data
Tatayuki Tateishi
National Centre of Neurology and Psychiatry, Tokyo
Physiotherapist
Acquisition of physiotherapy data
Hiroyuki Yajima
National Centre of Neurology and Psychiatry, Tokyo,
Physiotherapist
Acquisition of physiotherapy data
Takahiro Nakayama MD PhD
Yokohama Rosai Hospital, Yokohama,
Study Advisor
Study Coordinator
Kazuhiko Segawa MD PhD
National Centre of Neurology and Psychiatry, Tokyo,
Study Doctor
Acquisition of Medical History, medical and physical assessments
Makiko Endo
National Centre of Neurology and Psychiatry, Tokyo,
Study Coordinator
Study Coordination and Data Management
Meganne E Leach, MSN, APRN
Children's National Health System, Washington,
Research Nurse
Acquisition of Medical History, medical and physical assessments
Nora Brody, PT, DPT
Children's National Health System, Washington,
Physiotherapist
Acquisition of physiotherapy data
Brittney DeWolf
Children's National Health System, Washington,
Physiotherapist
Acquisition of physiotherapy data
Allyn Toles
Children's National Health System, Washington,
Study Coordinator
Study Coordination and Data Management
Stanley T. Fricke PhD
Department of Diagnostic Imaging and Radiology, Children's National Health System, Washington DC, USA,
Radiologist
MRI data acquistion
Hansel J. Otero MD
Department of Diagnostic Imaging and Radiology, Children's National Health System, Washington DC, USA,
Radiologist
MRI data acquistion
Ulrike Grieben MD
Charite, Berlin,
Study Doctor
Acquisition of Medical History, medical and physical assessments
229th ENMC international workshop: limb girdle muscular dystrophies - Nomenclature and reformed classification Naarden, the Netherlands, 17-19 March 2017.
Autosomal recessive distal muscular dystrophy as a new type of progressive muscular dystrophy: seventeen cases in eight families including an autopsied case.
Symptom duration differs between groups (p = 0.048 on Wilcoxon rank sum test).Gender, previous steroid treatment and teenage activity category not significantly different on Chi squared testing.
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