Establishing Biomarkers and Clinical Endpoints in Myotonic Dystrophy Type 1 (END-DM1) Extension (END-EXT)
Study Overview
Status
Status
Conditions
Conditions
Detailed Description
The goal of this observational study is to characterize long-term disease progression over at least 4 years in at least 1,000 adults with myotonic dystrophy type 1 (DM1).
The main questions this study aims to answer are:
- How do clinical measures, such as walking speed, hand function, and muscle strength, change over a multi-year period in people with DM1?
- Can long-term changes in slowly progressive measures, like heart rhythms (ECG) and lung function (FVC), be accurately captured and used as biomarkers for the disease over time?
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Jennifer Raymond
- Phone Number: 804-828-6318
- Email: Jennifer.raymond@vcuhealth.org
Study Contact Backup
- Name: Ruby Langeslay
- Phone Number: 804-828-6318
- Email: Ruby.langeslay@vcuhealth.org
Study Locations
-
-
Virginia
-
Richmond, Virginia, United States, 23298
- Recruiting
- Virginia Commonwealth University
-
Principal Investigator:
- Nicholas Johnson, MD
-
Contact:
- Jennifer Raymond
- Phone Number: 804-828-6318
- Email: Jennifer.raymond@vcuhealth.org
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Age 18 to 70 years (inclusive)
- Written, voluntary informed consent must be obtained prior to any study procedures. In cases where a Legally Authorized Representative (LAR) provides consent, verbal assent will be obtained from the subject, as determined by the investigator and documented directly on the consent form. Capacity to consent will be determined by the neurologist at the Baseline visit and will be signed off on the Inclusion/Exclusion checklist.
- Clinical diagnosis of DM1 based on research criteria or positive genetic test. The research criteria for clinical diagnosis of DM1 require myotonia, muscle weakness in a characteristic distribution, and history of similar findings in a first degree relative. Genetic testing confirmed the diagnosis of DM1 in > 99% of individuals who satisfied these criteria. OR A diagnosis of CDM, which is defined as children having symptoms of myotonic dystrophy in the newborn period (<30 days), such as hypotonia, feeding or respiratory difficulty, requiring hospitalization to a ward or to the neonatal intensive care unit for 3 days or more; and a genetic test suspicious of an expanded trinucleotide (CTG) repeat in the DMPK gene in the child or first degree relative. An expanded CTG repeat size in the child is considered greater than 200 repeats or E1-E4 classification (E1= 200-500, E2=500-1,000, E3=1,000-1,500, E4>1,500)
Exclusion Criteria:
- Symptomatic renal or liver disease, uncontrolled diabetes or thyroid disorder, or active malignancy other than in situ skin cancer.
- Current alcohol or substance use disorder.
- Concurrent pregnancy or planned pregnancy during the course of the study.
- Concurrent medical condition that would, in the opinion of the investigator or clinical evaluator. compromise performance on study measures.
- Use of mexiletine or other anti-myotonia agents within 72 hours of any study visit.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
|---|
|
Myotonic Dystrophy Type 1 (DM1) Longitudinal Cohort
Participants with a clinical or genetic diagnosis of myotonic dystrophy type 1 (DM1) or congenital myotonic dystrophy (CDM).
This cohort includes individuals transitioning from the parent study, Establishing Biomarkers and Clinical Endpoints in Myotonic Dystrophy Type 1 (END-DM1; NCT03981575), as well as newly enrolled participants.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Characterize the long-term disease progression- 10 meter walk/run
Time Frame: Baseline (0 months), every 12 months over four years
|
The 10-meter walk test (10MWT) is used in research to reliably measure gait speed, assessing functional mobility and detecting changes in walking performance over time.
It is a highly reliable, quick, and cost-effective tool. .
It is favored for its simplicity, speed, and ability to predict functional independence.
A "good" score varies by age/condition, with healthy adults averaging over 1.2-1.4
m/s.
|
Baseline (0 months), every 12 months over four years
|
|
Characterize the long-term disease progression- vHOT
Time Frame: Baseline (0 months), every 12 months over four years
|
The Video Hand Opening Time (vHOT) is used in research as a practical, low-cost, and reliable quantitative tool to measure handgrip myotonia (delayed muscle relaxation) in Myotonic Dystrophy Type 1 (DM1) patients.
It is particularly valuable for multicenter clinical trials because it allows for blinded, objective assessment of therapeutic responses.
A "good" (healthy) score is generally as close to zero as possible.
|
Baseline (0 months), every 12 months over four years
|
|
Characterize the long-term disease progression- grip strength
Time Frame: Baseline (0 months), every 12 months over four years
|
Grip strength is used in research as a reliable, low-cost biomarker for overall muscle strength, aging, and mortality risk.
A good score varies by age and sex, with healthy young adults often averaging over 40-45 kg (males) and 25-30kg (females).
|
Baseline (0 months), every 12 months over four years
|
|
Characterize the long-term disease progression- ECG
Time Frame: Baseline (0 months), every 12 months over four years
|
Electrocardiograms (ECGs/EKGs) are used in research for their non-invasive, cost-effective ability to track heart rhythm, diagnose cardiac conditions, and assess cardiovascular disease risk.
In research, a "good" ECG score indicates normal sinus rhythm and intervals, such as a PR interval of 120-200 milliseconds and an RR interval of 0.6-1.2
seconds.
|
Baseline (0 months), every 12 months over four years
|
|
Characterize the long-term disease progression- FVC
Time Frame: Baseline (0 months), every 12 months over four years
|
Forced Vital Capacity (FVC) is crucial in research for diagnosing and tracking restrictive lung diseases (e.g., pulmonary fibrosis), assessing disease progression, and measuring treatment efficacy in clinical trials.
A "good" or normal FVC is typically 80% or higher of the predicted value, based on a patient's age, height, sex, and ethnicity.
|
Baseline (0 months), every 12 months over four years
|
|
Characterize the long-term disease progression- DM1-Activ-c
Time Frame: Baseline (0 months), every 12 months over four years
|
The DM1-Activ-c (25-item) is a validated, Rasch-built, patient-reported outcome measure designed specifically to assess daily activity and participation in Myotonic Dystrophy Type 1 (DM1) patients.
It is used in research for its high sensitivity to disease progression and therapeutic changes (responsiveness), making it a reliable primary endpoint for clinical trials to measure patient improvement.
The DM1-Activ-c is scored on a scale from 0 to 100, where higher scores indicate better functional ability.
|
Baseline (0 months), every 12 months over four years
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Nicholas Johnson, MD, Virginia Commonwealth University
Publications and helpful links
General Publications
- Guyatt GH, Osoba D, Wu AW, Wyrwich KW, Norman GR; Clinical Significance Consensus Meeting Group. Methods to explain the clinical significance of health status measures. Mayo Clin Proc. 2002 Apr;77(4):371-83. doi: 10.4065/77.4.371.
- Jaeschke R, Singer J, Guyatt GH. Measurement of health status. Ascertaining the minimal clinically important difference. Control Clin Trials. 1989 Dec;10(4):407-15. doi: 10.1016/0197-2456(89)90005-6.
- Mathai SC, Puhan MA, Lam D, Wise RA. The minimal important difference in the 6-minute walk test for patients with pulmonary arterial hypertension. Am J Respir Crit Care Med. 2012 Sep 1;186(5):428-33. doi: 10.1164/rccm.201203-0480OC. Epub 2012 Jun 21.
- Goldman A, Ramsay M, Jenkins T. Ethnicity and myotonic dystrophy: a possible explanation for its absence in sub-Saharan Africa. Ann Hum Genet. 1996 Jan;60(1):57-65. doi: 10.1111/j.1469-1809.1996.tb01172.x.
- Griggs RC, Wood DS. Criteria for establishing the validity of genetic recombination in myotonic dystrophy. Neurology. 1989 Mar;39(3):420-1. doi: 10.1212/wnl.39.3.420. No abstract available.
- Personius KE, Pandya S, King WM, Tawil R, McDermott MP. Facioscapulohumeral dystrophy natural history study: standardization of testing procedures and reliability of measurements. The FSH DY Group. Phys Ther. 1994 Mar;74(3):253-63. doi: 10.1093/ptj/74.3.253.
- Thornton CA, Johnson K, Moxley RT 3rd. Myotonic dystrophy patients have larger CTG expansions in skeletal muscle than in leukocytes. Ann Neurol. 1994 Jan;35(1):104-7. doi: 10.1002/ana.410350116.
- Braida C, Stefanatos RK, Adam B, Mahajan N, Smeets HJ, Niel F, Goizet C, Arveiler B, Koenig M, Lagier-Tourenne C, Mandel JL, Faber CG, de Die-Smulders CE, Spaans F, Monckton DG. Variant CCG and GGC repeats within the CTG expansion dramatically modify mutational dynamics and likely contribute toward unusual symptoms in some myotonic dystrophy type 1 patients. Hum Mol Genet. 2010 Apr 15;19(8):1399-412. doi: 10.1093/hmg/ddq015. Epub 2010 Jan 15.
- Guyatt G, Walter S, Norman G. Measuring change over time: assessing the usefulness of evaluative instruments. J Chronic Dis. 1987;40(2):171-8. doi: 10.1016/0021-9681(87)90069-5.
- Wyrwich KW, Tierney WM, Wolinsky FD. Further evidence supporting an SEM-based criterion for identifying meaningful intra-individual changes in health-related quality of life. J Clin Epidemiol. 1999 Sep;52(9):861-73. doi: 10.1016/s0895-4356(99)00071-2.
- Teng S, Wang B, Yang F, Yi X, Zhang X, Sun Y. MediDRNet: Tackling category imbalance in diabetic retinopathy classification with dual-branch learning and prototypical contrastive learning. Comput Methods Programs Biomed. 2024 Aug;253:108230. doi: 10.1016/j.cmpb.2024.108230. Epub 2024 May 17.
- Liu P, Liu Y, Liu H, Xiong L, Mei C, Yuan L. A Random Forest Algorithm for Assessing Risk Factors Associated With Chronic Kidney Disease: Observational Study. Asian Pac Isl Nurs J. 2024 Jun 3;8:e48378. doi: 10.2196/48378.
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
- Neurologic Manifestations
- Musculoskeletal Diseases
- Nervous System Diseases
- Muscular Diseases
- Neuromuscular Manifestations
- Genetic Diseases, Inborn
- Neurodegenerative Diseases
- Heredodegenerative Disorders, Nervous System
- Muscular Disorders, Atrophic
- Myotonic Disorders
- Congenital, Hereditary, and Neonatal Diseases and Abnormalities
- Pathological Conditions, Signs and Symptoms
- Signs and Symptoms
- Muscular Dystrophies
- Myotonic Dystrophy
- Myotonia
- Neuromuscular Diseases
Other Study ID Numbers
Other Study ID Numbers
- HM300000528 END-EXT
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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