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Does CAG repeat number predict the rate of pathological changes in Huntington's disease.

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neurodegenerative disease.’ Following our report, Okuizumi
and his colleagues also obtained the same result in their
study of Japanese subjects with PSP and other diseases with
tau pathology, including Picks disease, corticobasal degeneration, and amyotrophic lateral sclerosis. It is possible that the
role of this polymorphism in PSP may be different between
Caucasian and Japanese populations or, alternatively, that this
polymorphism may not reflect genetic changes causal for
PSP but rather a marker for other molecular genetic risk factors within or close to the tau gene on chromosome 17.’
Although Okuizumi and his associates and our own group
obtained the same result in Japanese subjects with PSP, an
examination of the methodologies used in the two studies
raises concerns with broader implications for the field of genetics in general. When studying the genetic basis of disease,
accurate diagnosis is crucial for collecting and pooling subjects. Our selection of subjects with neurodegenerative diseases was based on pathological riter ria.',^'^ In contrast, the
subjects analyzed by Okuizumi and his colleagues were diagnosed on the basis of clinical criteria. Most of these disorders
are extremely difficult to diagnose because they have significant overlap in clinical presentation in addition to the clinical heterogeneity seen within each d i ~ o r d e r .These
~
confounding factors can lead to an error in diagnosis. This
becomes a major concern when studying rare diseases with
small sample sizes (<20). In this situation, misdiagnosis can
have a significant impact on the interpretation of the data.
The use of subjects whose clinical diagnosis has been confirmed by pathological criteria on autopsy can reduce the incidence of this type of error.5 Although pathological diagnosis is not completely error-free (there are similarities in
pathology between these neurological disorders), this type of
diagnosis is generally more reliable, because the subjects have
typically been followed clinically as well. In the absence of
more accurate diagnosis and larger sample sizes, misdiagnosis
remains a major concern in our attempts to gain insight into
these types of disease.
“Department of Pathology, Albert Einstein College of
Medicine, Bronx, N E and ?Department of Neuroscience,
Johns Hopkins University School of Medicine,
Baltimore, M D
References
1. Conrad C, Amano N, Andreadis A, et al. Differences in a dinucleotide repeat polymorphism in the tau gene between Caucasian
and Japanese populations, implication for progressive supranuclear palsy. Neurosci Lett 1998;250:135-137
2. Conrad C, Andreadis A, Trojanowski JQ, et al. Genetic evidence
for thc involvement of tau in progressive supranuclear palsy. Ann
Neurol 1997;41:277-281
3. Higgins JJ, Litvan I, Pho LT, et al. Progressive supranuclear gaze
palsy is in linkage disequilibrium with the tau and not the alphasynuclein gene. Neurology 1998;50:270-273
4. Sawa A, Amano N, Yamada N, et al. Apolipoprotein E in progressive supranuclear palsy in Japan. Mol Psychiatry 1997;2:341342
5. Feany MB, Dickson DW. Neurodegenerative disorders with extensive tau pathology: a comparative study and review. Ann Neurol 1996;40:139-148
708 Annals of Neurology
Vol 44
No 4
October 1998
Does CAG Repeat Number Predict the Rate of
Pathological Changes in Huntington’s Disease?
A. Rosenblatt, MD,* R. L. Margolis, MD,”
M. W. Becher, MD,t E. Aylward, PhD,*$
M. L. Franz, MSW,’ M. Sherr, RN, BSN,*
M. H. Abbott, MPH, RN,* K.-Y.
Liang, PhD,§
and C. A. Ross, MD, PhD*S
Penny and colleagues’ believe that neuropathological changes
in Huntington’s disease begin at birth and proceed at a con
stant rate, They infer this from the linear relationship between grade (as defined by Vonsattel and associates’) and age
(at death) and the number of CAG repeats. A clinical measure of striatal dysfunction should therefore depend only on
the repeat number and age of the individual. We replicated
their experiment and performed the clinical correlation using
the motor impairment score (MIS), the subset of the Quantified Neurologic Examination that best predicts functional
i m ~ a i r m e n t .Ninety-five
~
brains were examined. A total of
1,425 examinations with complete MIS data on 309 patients
with known CAG repeat lengths were used.
There was a high correlation ( r = 0.797) between CAG
number and gradelage, with an intercept of 35.7 repeats (Fig,
A). An analysis simply comparing the CAG number to the
reciprocal of the age of onset showed an even higher correlation ( r = 0.801), with an intercept of 36.2 repeats (see Fig,
B). As predicted, there was a slight positive correlation between MIS and age X (CAG - 35.5 repeats) ( r = 0.380),
but there was a stronger correlation between MIS and disease
duration ( Y = 0.651).
Interpreting gradelage as a constant rate makes an assumption that cannot be tested without longitudinal data. Removing grade from the analysis and substituting age of onset for
age at death (removing the effect of disease duration) actually
improves the correlation. Penny and colleagues’ interpreted
the intercept as the CAG number at which no neuropathological changes were expected. We see it as a physiological
asymptote, the repeat number at which age of onset would
exceed the human life span (see Fig, C).
Neuropathological changes in Huntington’s disease probably do not begin at birth or proceed in a linear fashion. Our
analysis shows that disease duration is a much better predictor of dysfunction than age and repeat number alone. This is
more consistent with the hypothesis that neuropathological
changes begin a few years before clinical onset and is supported by the structural neuroimaging data a~ailable.~
Data
from a recent study by our group showed no caudate or putamen volume reduction over an average of 32 months in 3
subjects with number of predicted years to onset greater than
10. Determining when neuropathological changes begin in
Huntington’s disease is important for understanding its
pathogenesis and timing therapeutic interventions.
Departments of *Psychiaty, fPatholoa, JBiostatistics, and
YNeuroscience, The Johns Hopkins Uniuersity School of
Medicine, Baltimore, MD; and $Department of Radiology,
University of Washington, Seattle, WA
This study was supported by NIH grant NS 16375 and the Washington Metro Chapter of the Huntington’s Disease Society of
America.
References
A
1. Penny JB, Vonsattel JP, MacDondd ME, et al. CAG repeat
number governs the development rate of pathology in Huntington’s disease. Ann Neurol 1997;41:689-692
2. Vonsattel JP, Myers RH, Stevens TJ, et al. Neuropathological
classification of Huntington’s disease. J Neuropathol Exp Neurol
1985;44:559-577
3. Folstein SE, Jensen B, Leigh RJ, Folstein MF. The measurement
of abnormal movement: methods developed for Huntington’s
disease. Neurobehav Toxicol Teratol 1983;5:605-609
4. Aylward EH, Codori AM, Barta P, et al. Basal ganglia volume
and proximity to onset in presymptomatic Huntington disease.
Arch Neurol 1996;53:1293-1296
90
30
0.00
05
.210
15
.I0
GradelAge
B
..
80.
70.
c
Q
.-
60.
a
6
50.
40.
30
000
04
02
06
10
08
12
1lAge of Onset
C
100
I
I
I
0
30
I
I
,
40
50
60
70
80
CAG Triplets
Fig. The relationship of C4G number to grade/age (A) is contrasted with that of CAG number to l/age o f onset (B). CAG
versus onset is shown in its more familiar form in C, with the
intercept value ?om A depicted a a ddthed line.
Annals of Neurology
Vol 44
No 4
October 1998
709
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