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Predicting Progression of the Muscular Dystrophies

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Analyze Longitudinal Cases of DMD/LGMD. Convert Data to a Physical Variable ... Early, Precipitous Involvement of Shoulder, Elbow, Hip, Knee groups. Data Generation ... – PowerPoint PPT presentation

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Title: Predicting Progression of the Muscular Dystrophies


1
Predicting Progression of the Muscular Dystrophies
  • MW Munn
  • August 2007

2
Methodology Purpose
  • Analyze Longitudinal Cases of DMD/LGMD
  • Convert Data to a Physical Variable
  • Functioning Muscle Fiber Fraction (MFF)
  • Determine MFF Time Dependence
  • Focus on Exponential Cases to Start
  • Find the Transform from MFF to MRC
  • Demonstrate Predictability
  • Predictability Reduces Statistical Needs in
    Patient s and Time Required for Trials

3
Anatomy of Duchenne Decay
  • Strength vs age
  • 3-D Format
  • Muscle group decay vs time
  • Clear Patterns revealed
  • Case Shown is Severe
  • Patterns vary predictably from less to more
    severity
  • Allows Progression Predictability
  • Reduces s Needed in Trials

Relative Strength
4
Strength Decay Distributions
Less Severe Region
More Severe Region
Early, Precipitous Involvement of Shoulder,
Elbow, Hip, Knee groups
5
Data Generation
  • Create 3 Parallel Data Sets
  • First AMS Muscle Group Score AMS Megascore
    (This is the CIDD database)
  • Second Muscle Group Conversion to MRC Scores and
    an MRC Megascore
  • Third Muscle Group Conversion to Functioning
    Muscle Fiber Fraction (MFF) and the Corresponding
    MFF Megascore
  • MFF is a true physical variable
  • Amenable to biophysical analyses predictability

6
Critical Transform Manual Strength to Functional
Fiber Fraction
  • Essential to relate qualitative to quantitative
    data
  • Permits analysis based on physical principles
  • Creates the basis for predictive capabilities
  • Beasley, WC, Quantitative Muscle Testing
    Principles and Applications to Research
  • and Clinical Studies, Arch Phys Med Rehab, 42,
    398-425, 1961
  • 2. Felice, KJ, A Longitudinal Study Comparing
    Thenar Motor Unit Number Estimates to Other
    Quantitative
  • Tests in Patients with Amyotrophic Lateral
    Sclerosis, Muscle Nerve, 20, 179 185, 1997.

7
Three Major DMD Decay Types
8
Significance of Broad Weakness Canyons
  • Presence of Canyons Indicative of Exponential
    Decay in Functioning Muscle Fiber Fraction (MFF)
  • MFF is Averaged over all Muscle Groups
  • MFF Decay Rate Correlates to Onset Age for
    CanyonUpper or Lower Body
  • Approximately 30 CIDD Cases in Class
  • Represents a DMD Decay Archetype

9
DMD Decay ArchetypeExponential
  • Canyon Decay Pattern
  • Upper and Lower body
  • Always Results in Exponential Decay
  • Canyon Onset Couples to Decay Rate
  • Involves about 30 of Patients

10
Prediction of MRC Score is Possible
  • For Cases Exponential in MFF
  • Determine the Decay Rate
  • Write the Governing Equations
  • MRC/100 1/ 1 e (t/b t - t/c ) (0.1/
    t),
  • t is the half-life of the fiber decay 0.69/a
  • MFF e -at (derived from data)
  • b 2, c 1.5 b governs slope, c governs
    breakpoint from 100
  • Predict MRC and Compare

MRC Equation is a Standard Form Richards
Sigmoid
11
Dystrophic Time EvolutionMegascoresExponential
Fiber Decay
No Measurable Strength Loss by MMT
MMT Measurable Strength Breakpoint
Anecdotal Regionfalls, runs slowly.
MVIC Measurable Here

12
Low Decay Rate Case I
MRC/100 1/ 1 e (t/2 t - t/1.5 ) (0.1/
t),
MFF e 0.1028336 t
? 0.69/0.1028336
13
Low Decay Rate Case II
MFF e 0.1079576 t
MRC/100 1/ 1 e (t/2 t - t/1.5 ) (0.1/
t),
? 0.69/0.1079576
14
High Decay Rate Case I
MRC/100 1/ 1 e (t/1.75 t - t/1.5 )
(0.1/ t),
MFF e 0.136463 t
? 0.69/0.136463
High Decay Rates Require a Systematic Decrease
in One Constant i.e. 2 ? 1.75
15
Application to LGMD Cases
  • Longitudinal Cases from Kawai et al
  • Grouping of Single Point Cases from Pollitt et
    al
  • Equations Identical to DMD
  • MRC/100 1/ 1 e (t/2 t - t/1.5 ) (0.1/
    t),
  • One parameter (t/2 ) allows the 2 to vary
    dependent on decay strength (also true for higher
    decay strengths in DMD)

Pollitt C., Anderson L. V. B., Pogue R., Davison
K., Pyle A., and Bushby K. M. D. The phenotype of
calpainopathy diagnosis based on a
multidisciplinary approach, Neuromuscular
Disorders, Vol 11, Issue 3, April 2001, Pages
287-296
16
Kawai et al LGMD2A Cases
Kawai, H, Akaike, M et al Clinical,
Pathological, and Genetic Features of Limb-Girdle
Muscular Dystrophy type 2a with New Calpain 3
Gene Mutations in Seven Patients from three
Japanese families, Muscle Nerve 21 14931501,
1998
17
Pollitt et al Sample Cases
MRC/100 1/ 1 e (t/a t - t/1.5 )
(0.1/ t),
Strength in Plots Shown in MMT Units
Varies in a predictable way dependent on the
decay strength
18
Synthesis of Physics
  • Basic Equations
  • MFF e -at (derived from data), a rate
  • MRC/100 1/ 1 e (t/2 t - t/1.5 ) (0.1/
    t),
  • t is the half-life of the fiber decay 0.69/a
  • Physical Variables Naturally Integrate in Rate
  • Body Temperature Cellular Kinetics
  • Defective DNA features Resonance Frequencies

19
Conclusion
  • Predictability Achieved For a Subset of DMD Cases
  • For Those Cases the MFF Megascore Decays
    Exponentially
  • For All LGMD Cases Investigated to Date, MFF is
    Exponential in Nature
  • LGMD Strength vs Time is Predictable with a
    Slight Modification to the DMD Equation
  • Nexts Steps
  • Expand to Non-exponential modes
  • Incorporate Ultra-high Severities
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