close

Вход

Забыли?

вход по аккаунту

?

Biomarker epidemiology of cerebral palsy.

код для вставкиСкачать
EDITORIALS
Alpha-Synuclein in
Parkinson’s Disease: Light
from Two New Angles
Those of us not addicted to querying PubMed for
“synuclein” and “parkin” may consider news of two
more mutations at one of the nine known Parkinson’s
disease (PD)-related Mendelian gene loci a minor matter. But the reports of new ␣-synuclein mutations by
Farrer et al1and Zarranz et al2 in this issue of Annals
reconfirm the central role of this protein in the pathogenesis of PD and the other “␣-synucleinopathies” and
shed light on the mechanism(s) by which ␣-synuclein
dysfunction could lead to cell death. The former report
demonstrates the toxicity of excessive ␣-synuclein expression in the human brain. The latter provides a new
example of a qualitative defect in that protein. The existence of two very different kinds of PD-causing,
dominantly-acting ␣-synuclein mutations helps us understand PD in its common, “sporadic” form.
Insoluble aggregates of ␣-synuclein form in the cytoplasm of neurons or glia in PD, multiple system atrophy (MSA), dementia with Lewy bodies (DLB) and
a few other disorders. Although Lewy bodies (LBs), the
best-organized form of such aggregates, were first described in 1912, their major chemical component remained obscure until 1996. At that time, a wholegenome search via linkage analysis of the Contursi
kindred, a large Italian family with autosomaldominant PD,3 revealed a point mutation in the
␣-synuclein gene at what was thereupon called the
PARK1 locus.4,5
In short order, anti-␣-synuclein immunostaining of
LBs in sporadic PD and glial cytoplasmic inclusions of
MSA proved positive.6,7 The same point mutation was
found in association with early-onset PD in several
Greek families who shared haplotypes (and therefore
probably a common ancestry) with the Contursi
kindred.5,8-10 In 1998, ␣-synuclein gene sequencing in
a German family with autosomal dominant PD yielded
a second PARK1 point mutation11 and now a similar
approach in a Spanish family by Zarranz et al2 has revealed yet a third. Very recently, an American family of
mixed northern European origin with autosomal dominant, young-onset PD was found to harbor a triplication of the ␣-synuclein gene12 and a similar triplication
in a Swedish-American family is reported by Farrer et
al in the present issue of Annals.1 Additionally, a polymorphic marker in the promoter region of ␣-synuclein
has also been associated with sporadic PD by compar-
ing polymorphic allele frequencies in patients and controls.13
In the PD population, ␣-synuclein mutations are far
less common than mutations in the other two genes
whose PD-related mutations have been identified,
namely parkin (PARK2),14 an enzyme in the ubiquitin/proteasome system, and DJ-1 (PARK7),15 possibly part of the cell’s oxidative stress response. But a
central role for ␣-synuclein in all PD is suggested by a)
the abundance of ␣-synuclein in LBs; b) the observation that ␣-synuclein aggregation can result from an
oxidative cellular milieu, as occurs in PD, as well as
from many suspected environmental contributors to
PD such as some pesticides and heavy metals; and c)
the fact that over-expression of ␣-synuclein in various
animal models recapitulates much of the PD phenotype.
The original Contursi/Greek ␣-synuclein mutation
produces an alanine-to-threonine substitution at amino
acid position 53,5 while the German mutation produces alanine-to-proline change at position 30.11 The
mutation now reported by Zarranz et al2 results in a
more significant glutamic acid-to-lysine substitution at
position 46. Each lies in (or, for A53T, among) the six
tightly spaced 11-amino acid imperfect repeats near the
conserved N-terminus of the 140-amino acid
␣-synuclein protein. All three reported ␣-synuclein
point mutations are dominant, suggesting that they
cause PD via a toxic gain-of-function rather than a loss
of function.
The new mutation described by Zarranz et al2 is
the first of the three to substitute a basic residue for
an acidic one. As such, it represents a more drastic
molecular change for ␣-synuclein than the two previously identified point mutations. The glutamic acidto-lysine substitution could change the physicochemical and molecular properties of this protein in two
ways. First, this change from a negatively to a positively charged residue would probably change the polarity of the protein. This would affect its ability to
interact with lipids, thereby modulating the interaction of ␣-synuclein with membrane phospholipids
and perhaps changing vesicular processes including
trafficking and transmitter release. The importance of
this set of actions has recently been demonstrated in a
yeast model, where genes for lipid and vesicle metabolism are overrepresented among those that enhance
the toxicity of ␣-synuclein.16 Second, the introduction of a lysine residue in particular could provide an
additional site for potential covalent modifications by
ubiquitin or by the small ubiquitin-related modifier.
These post-translational modifications could have implications for the clearance or stability of the protein,
its tendency to aggregate, its interactions with other
proteins or its intracellular distribution.17-20
The six 11-amino acid repeats in ␣-synuclein assume
© 2004 American Neurological Association
Published by Wiley-Liss, Inc., through Wiley Subscription Services
153
no secondary structure in the dissolved state, but they
probably form ␣-helices when bound to lipids.21 When
the helices are disrupted by mutations, the protein misfolds, allowing it to aggregate and form fibrils.22 The
aggregates may impair the function of the proteasome,
thereby reducing the cell’s ability to dispose of misfolded proteins, probably including ␣-synuclein itself.23,24
An earlier stage of aggregation called protoaggregates
or oligomers appears to disrupt cell membranes, including those of dopamine vesicles and mitochondria.25 The mechanism by which this occurs is unclear,
but the protoaggregates exhibit pore-like activity in the
manner of some bacterial toxins.26 Pores in mitochondria would not only degrade their transmembrane potential, but would also liberate cytochrome C, a proapoptotic signal, into the cytoplasm. Pores in
dopamine vesicles would liberate dopamine, the metabolism of which increases cytoplasmic reactive oxygen
species.27 Dopamine may also inhibit the maturation
of the toxic protoaggregates into presumably harmless
mature aggregates and LBs.28 This may help explain
the relative selectivity of PD for dopaminergic neurons.
One important factor promoting the aggregation of
␣-synuclein is its concentration. Such a mechanism operates in cultured neuronal cells that over-express that
protein29 and in transgenic animal models30,31 and
most recently, in yeast32 The neurons in the patients
reported by Farrer et al1appear to be doing the same,
driven by the heterozygotic triplication of the region
that includes the ␣-synuclein gene. The neurodegeneration associated with ␣-synuclein gene triplication essentially mirrors the form of Alzheimer’s disease seen in
most individuals with trisomy 21, in which there is
triplication of the gene for amyloid precursor protein.
Several other factors, including post-translational
modifications, appear to be important to ␣-synuclein
aggregation. Chronic action of environmental toxins or
excessive endogenous production of oxidants from dopamine metabolism may cause slow accumulation of
oxidative stress. This causes post-translational modification in ␣-synuclein such as tyrosine nitration, methionine oxidation and dopamine adduct formation.19,28,33 Each of these can cause oligomerization of
the protein. Alternatively, phosphorylation or aberrant
cleavage of ␣-synuclein may promote its aggregation.18
Mutations in some of the many genes with weak but
statistically significant non-Mendelian associations with
Fig. A proposed model of the pathogenetic cascade in PD. UPS: ubiquitin proteasome system; ROS: reactive oxygen species.
154
Annals of Neurology
Vol 55
No 2
February 2004
sporadic PD may impair the ubiquitin-proteasome system, which disposes of misfolded or otherwise dysfunctional proteins. 34 This seems to be the mechanism of
the autosomal recessive mutations in the parkin gene.
Aggregation of tau protein and ␣-synuclein induce
each other35 and a weak association of a tau haplotype
with PD has been reported by several groups.36 Crosslinking of ␣-synuclein via transglutamination, possibly
genetically determined, also promotes aggregation.37
These observations prompt a hypothesis of PD
pathogenesis (Figure) that posits a vicious cycle: First,
␣-synuclein aggregation results from its misfolding,
over-expression, or insufficient disposal. The last defect
may result either from genetically determined dysfunction in the ubiquitin-proteasome system or from the
action of toxins, possibly augmented by subtle genetic
defects in detoxification mechanisms. Next, aggregates
in the early, oligomeric stage of development damage
vital cell membranes, including vesicular lipid membranes, causing accumulation of reactive oxygen species,38,39 promoting further ␣-synuclein aggregation.
When several of these factors occur in mild form in
the same individual, the PD vicious cycle could be
bootstrapped into action. Although many of these etiologic factors are genetic, their combination would be
relatively rare. Many of them, as errors of hypofunction, probably act recessively. This would create what
appears to be a sporadic disease pattern.
One task for the immediate future is to sort out the
relative importance of these factors in human sporadic
PD. Novel PD-associated loci are being identified by
the four genome scans now in progress using coaffected sibling pairs.40 – 42 We also await the cloning
of the remaining known Mendelian genes (PARK 3, 6,
8, 9 and 10). These investigations may clarify details of
the present hypothesis of the pathogenesis of sporadic
PD or point to even more plausible ones. The goal, of
course, is identification of new mechanisms that may
offer novel opportunities for PD prophylaxis. The observations of Farrer et al and Zarranz et al serve as
models for this approach.
The authors gratefully acknowledge the support of a center grant
from the American Parkinson’s Disease Association and an endowment from the family of William Dow Lovett.
Lawrence I. Golbe, MD and
M. Maral Mouradian, MD
Department of Neurology
UMDNJ-Robert Wood Johnson Medical School
New Brunswick, NJ
DOI: 10.1002/ana.20036
References
1. Farrer M, Kachergus J, Forno L, et al. Comparison of kindreds
with familial parkinsonism and ␣-synuclein genomic multiplications. Ann Neural 2004;55:174 –179.
2. Zarranz J, Alegre J, Gomez-Esteban J, et al. The new mutation,
E46K, of a ␣-synuclein causes Parkinson and lewy body dementia. Ann Neurol 2004;55:164 –173.
3. Golbe LI, Di Iorio G, Bonavita V, Miller DC, Duvoisin RC. A
large kindred with autosomal dominant Parkinson’s disease.
Ann Neurol 1990;27:276-282.
4. Polymeropoulos MH, Higgins JJ, Golbe LI, et al. A gene for
Parkinson’s disease maps to 4q21–q23. Science 1996;274:11971199.
5. Polymeropoulos MH, Lavedan C, Leroy E, et al. Mutation in
alpha synuclein identified in families with Parkinson’s disease.
Science 1997;276:2045-2047.
6. Spillantini MG, Schmidt ML, Lee VM, Trojanowski JQ, Jakes
R, Goedert M. Alpha-synuclein in Lewy bodies. Nature 1997;
388:839-840.
7. Baba M, Nakajo S, Tu PH, et al. Aggregation of alphasynuclein in Lewy bodies of sporadic Parkinson’s disease
and dementia with Lewy bodies. Am J Pathol 1998;152:879884.
8. Markopoulou K, Wszolek ZK, Pfeiffer RF. Reduced expression
of the G209A alpha-synuclein allele in familial Parkinsonism.
Ann Neurol 1999;46:374-381.
9. Athanassiadou A, Voutsinas G, Psiouri L, et al. Genetic analysis
of families with Parkinson disease that carry the Ala53Thr mutation in the gene encoding alpha-synuclein. Am J Hum Genet
1999;65:555-558.
10. Spira PJ, Sharpe DM, Halliday G, Cavanagh J, Nicholson GA.
Clinical and pathological features of a Parkinsonian syndrome
in a family with an Ala53Thr alpha-synuclein mutation. Ann
Neurol 2001;49:313-319.
11. Krüger R, Kuhn W, Müller T, et al. Ala30Pro mutation in the
gene encoding alpha-synuclein in Parkinson’s disease. Nat
Genet 1998;18:106-108.
12. Singleton AB, Farrer M, Johnson J, et al. Alpha-synuclein locus triplication causes Parkinson’s disease. Science 2003:302:
841.
13. Farrer M, Maraganore DM, Lockhart P, et al. Alpha-synuclein
gene haplotypes are associated with Parkinson’s disease. Hum
Mol Genet 2001;10:1847-1851.
14. Lücking CB, Durr A, Bonifati V, et al. Association between
early-onset Parkinson’s disease and mutations in the parkin
gene. French Parkinson’s Disease Genetics Study Group.
N Engl J Med 2000;342:1560-1567.
15. Bonifati V, Rizzu P, Squitieri F, et al. DJ-1( PARK7), a novel
gene for autosomal recessive, early onset parkinsonism. Neurol
Sci 2003;24:159-160.
16. Willingham S, Fleming Outeiro T, DeVit MJ, Lindquist S,
Muchowski PJ. Yeast genes that enhance the toxicity of a mutant huntingtin fragment or ␣-synuclein. Science 2003;302:
1769-1772.
17. Takahashi T, Yamashita H, Nakamura T, Nagano Y, Nakamura
S. Tyrosine 125 of ␣-synuclein plays a critical role for dimerization following nitrative stress. Brain Res 2002;938:73-80.
18. Takahashi M, Kanuka H, Fujiwara H, et al. Phosphorylation of
alpha-synuclein characteristic of synucleinopathy lesions is recapitulated in alpha-synuclein transgenic Drosophila. Neurosci
Lett 2003;336:155-158.
19. Giasson BI, Duda JE, Murray IV, et al. Oxidative damage
linked to neurodegeneration by selective ␣-synuclein nitration
in synucleinopathy lesions. Science 2000;290:985-989.
Golbe and Mouradian: Alpha-synuclein in PD
155
20. Schwartz DC, Hochstrasser M. A superfamily of protein tags:
ubiquitin, SUMO and related modifiers. Trends Biochem Sci.
2003;28:321-328.
21. Chandra S, Chen X, Rizo J, Jahn R, Sudhof TC. A broken
alpha-helix in folded alpha-synuclein. J Biol Chem 2003;278:
15313-15318.
22. Takeda A, Mallory M, Sundsmo M, Honer W, Hansen L,
Masliah E. Abnormal accumulation of NACP/␣-synuclein in
neurodegenerative disorders. Am J Pathol 1998;152:367-372.
23. Bence NF, Sampat RM, Kopito RR. Impairment of the
ubiquitin-proteasome system by protein aggregation. Science
2001;292:1552-1555.
24. Tanaka Y, Engelender S, Igarashi S, Rao RK, Wanner T, Tanzi
RE, et al. Inducible expression of mutant alpha-synuclein decreases proteasome activity and increases sensitivity to
mitochondria-dependent apoptosis. Hum Mol Genet 2001;10:
919-926.
25. Conway KA, Lee SJ, Rochet JC, Ding TT, Williamson RE,
Lansbury PT Jr. Acceleration of oligomerization, not fibrillization, is a shared property of both alpha-synuclein mutations
linked to early-onset Parkinson’s disease: implications for
pathogenesis and therapy. Proc Natl Acad Sci USA 2000;97:
571-576.
26. Lashuel HA, Petre BM, Wall J, Simon M, Nowak RJ, Walz T,
Lansbury PT Jr. Alpha-synuclein, especially the Parkinson’s
disease-associated mutants, forms pore-like annular and tubular
protofibrils. J Mol Biol 2002;322:1089-1102.
27. Volles MJ, Lee SJ, Rochet JC, et al. How do ␣-synuclein aggregates damage dopaminergic neurons? Biochemistry 2001;40:
7812-7819.
28. Conway KA, Rochet JC, Bieganski RM, Lansbury PT Jr. Kinetic stabilization of the alpha-synuclein protofibril by a
dopamine-alpha-synuclein adduct. Science 2001;294:13461349.
29. Tofaris GK, Layfield R, Spillantini MG. Alpha-synuclein metabolism and aggregation is linked to ubiquitin-independent
degradation by the proteasome. FEBS Lett 2001;509:22-26.
30. Masliah E, Rockenstein E, Veinbergs I, et al. Dopaminergic loss
and inclusion body formation in alpha-synuclein mice: implications for neurodegenerative disorders. Science 2000;287:
1265-1269.
31. Feany MB, Bender WW. A Drosophila model of Parkinson’s
disease. Nature 2000;404:394-398.
32. Fleming Outeiro T, Lindquist S. Yeast cells provide insight into
alpha-synuclein biology and pathobiology. Science 2003;302:
1772-1775.
33. Yamin G, Glaser CB, Uversky VN, Fink AL. Certain metals
trigger fibrillation of methionine-oxidized alpha-synuclein.
J Biol Chem 2003;278:27630-27635.
34. Bennett MC, Bishop JF, Lang Y, Chock PB, Chase TN,
Mouradian MM. Degradation of alpha-synuclein by proteasome. J Biol Chem 1999;274:33855-33858.
35. Giasson BI, Forman MS, Higuchi M, et al. Initiation and synergistic fibrillization of tau and alpha-synuclein. Science 2003;
300:636-640.
36. Golbe LI, Lazzarini AM, Spychala JR, et al. The tau A0 allele
in Parkinson’s disease. Movement Disorders 2001;16:442-447.
37. Junn E, Ronchetti RD, Quezado MM, Kim SY, Mouradian
MM. Tissue transglutaminase-induced aggregation of alphasynuclein: Implications for Lewy body formation in Parkinson’s
disease and dementia with Lewy bodies. Proc Natl Acad Sci
USA 2003;100:2047-2052.
38. Kanda S, Bishop JF, Eglitis MA, Yang Y, Mouradian MM. Enhanced vulnerability to oxidative stress by alpha-synuclein mutations and C-terminal truncation. Neuroscience. 2000;97:279284.
156
39. Junn E, Mouradian MM. Human alpha-synuclein overexpression increases intracellular reactive oxygen species levels
and susceptibility to dopamine. Neurosci Lett 2002 Mar 8;320:
146-150.
40. DeStefano AL, Golbe LI, Mark MH, et al. Genome-wide scan
for Parkinson’s disease: the GenePD Study. Neurology 2001;
57: 1124-1126.
41. Pankratz N, Nichols WC, Uniacke SK, et al. Genome screen to
identify susceptibility genes for Parkinson disease in a sample
without parkin mutations. Am J Hum Genet 2002;71:124-135.
42. Scott WK, Nance MA, Watts RL, et al. Complete genomic
screen in Parkinson disease: evidence for multiple genes. JAMA
2001;286:2239-2244.
Dissecting the Relative
Influences of Genes and
The Environment in
Alzheimer’s Disease
Imagine the surprise for Antipholus and Dromio, one
of the mixed-up pair of twins in Shakespeare’s Comedy of Errors, when they meet after being separated
most of their lives, never even knowing they were
each part of a twin pair. Despite paths that had
crossed and re-crossed and the fact that friends, servants and lovers frequently mistook one for the other,
the twins lead separate but parallel lives until they
meet in a collision of mistaken identities. Of course
the Comedy ends with feasting, rejoicing and marriage
with the double set of twins together for the first time
as adults.
Twins has proven useful in studies of the genetic
influences on behavior and disease, and has enabled
investigators to begin to understand how life style and
environment might interact with these influences. In
the study by Pedersen et al in this issue,1 a large cohort of Swedish twins between the ages of 52 and 98
years were queried for incident Alzheimer’s disease,
which was found to be concordant in 5 (32%) of 26
monozygotic twin pairs compared to 2 (8.7%) of 44
dizygotic twin pairs. The authors report that the heritability of Alzheimer’s disease was similar among
twin pairs regardless of age, but seemed to decrease
with increasing age. More importantly the authors
suggest that that environmental factors may also have
an important role in the case of late life dementia.
These results differ from that of Silverman et al,2 who
found that relatives of patients with very late onset of
Alzheimer’s disease had a substantially lower risk of
© 2004 American Neurological Association
Published by Wiley-Liss, Inc., through Wiley Subscription Services
dementia than relatives of patients with earlier-onset
disease.
While neither study suggests that genetic influences
are unimportant in assessing disease risk in late life,
both place greater emphasis on the potential contributions from the environment. Studies of heritability provide an estimate of the degree to which the variability
in the phenotype is related to genetic variation, but it
is difficult to separate shared genetic from shared environmental influences. Siblings, especially twins, share
their childhood environment in addition to their genetic background. Because heritability depends on all
contributing genetic and environmental components, a
change in any one factor can influence the estimate.
Thus, heritability estimates such as those by Pedersen
are likely to be reasonable approximations of the genetic
variance in the risk of Alzheimer’s disease, but they
cannot apportion the degree of gene-environmental
interaction.
Is there sufficient evidence to support the hypothesis
that Alzheimer’s disease in the very old is the result of
both genetic and environmental influences? There are
essentially two ways to analyze this proposition: a posteriori, examining the facts and experience to date, and
a priori, reviewing the supporting data and not worrying about the facts.
The last two decades of research have shown that
variant alleles in four genes are firmly associated with
Alzheimer’s disease.3 Each of these genes have diverse
functions elsewhere, but in this disease they are involved either in the production, processing or clearance of amyloid ␤ peptide, ultimately deposited in
brain in the form of neuritic plaques. Studies of large
multi-generational families with an autosomal dominant pattern of Alzheimer’s disease beginning as early
as the third decade of life led to the discovery of mutations in the amyloid precursor protein, presenilin 1
and presenilin 2. Family studies also led to the identification of APOE as a “susceptibility” gene because
possession of a single ε4 allele, present in approximately 25% of the population, is associated with a
two- to three-fold increased in disease risk, while having two copies is associated with a five-fold increase.
Unlike the early onset mutations, the APOE-ε4 allele
is not fully penetrant, and the population attributable
risk has been estimated at 20%.4 Still APOE-ε4 remains one of the most important risk factors for the
Alzheimer’s disease.
Additional loci on chromosomes 9q, 10q, 12p and
20p have been linked to Alzheimer’s disease.5,6 Several
candidate genes at these sites have been given intense
scrutiny including alpha-2-macroglobulin,7 the lowdensity lipoprotein receptor-related protein;8 insulin
degrading enzyme,9 ␣⫺T catenin 10and glutathione
S-transferase, omega-1,11 but remain unconfirmed by
other investigators. Blacker et al 6reported in a recent
genome scan that as many as 12 additional loci might
considered suggestive for linkage to Alzheimer’s disease.
The a posteriori conclusion here is that given enough
time and resources, additional genes will eventually be
identified.
Over nearly the same period no specific environmental toxin has found to be associated with Alzheimer disease. While depression, smoking, traumatic head injury
and cardiovascular-related disorders such as hypertension, myocardial infarct, hypercholesterolemia and
stroke have been associated with Alzheimer’s disease it
remains unclear whether these are true antecedents or
simply comorbidities.12 Variation in socioeconomic
factors such as literacy, educational achievement and
the type of early home environment have been associated with Alzheimer disease,13,14 but the mechanism
by which these factors are related to disease remain uncertain. The use of estrogen, anti-inflammatory drugs,
the consumption of wine and devoting time to complex physical and mental activities have been related to
decreased risk.15-20 The initial trials of estrogens and
anti-inflammatory ages have been discouraging. The a
priori conclusion here is that some of these environmental or non-genetic factors might be related to Alzheimer’s disease, but there is little more than circumstantial evidences to support these associations.
Near the end of the Comedy, Antipholus’s aging
mother laments her loss of memory, vision and hearing, but she is convinced that he must be her true son.
So it is with epidemiological studies of diseases in latelife, recall of past exposures are often difficult and have
to cover a lifetime. If Alzheimer’s disease has a long
prodrome as is suspected by many, traditional epidemiological approaches may not work. The recent interest in developing antecedent biomarkers for Alzheimer’s disease should provide a way to increase validity
and reduce bias in the assessment of risk factors because direct measurements lessen the possibility of exposure misclassification. However, not all risk factors
are measurable in biological samples from humans.
Nonetheless, the effects of these each of these risk factors may become clearer once we have a better understanding of the genetic influences on Alzheimer’s disease in late life. As the players discover in Comedy, relat
ionships are much easier to understand once the genetic identities are worked out.
Richard Mayeux, MD, MSc
Gertrude H. Sergievsky Center and the Taub Institute
for Research on Alzheimer’s Disease and the Aging
Brain at Columbia University College of Physicians
and Surgeons
New York, NY
Golbe and Mouradian: Alpha-synuclein in PD
157
References
1. Pedersen NL, Gatz M, Berg S, Johansson B. How heritable is
Alzheimer’s disease late in life? Findings from Swedish Twins.
Ann Neurol 2004;55:180 –185.
2. Silverman JM, Smith CJ, Marin DB, et al. Familial patterns of
risk in very late-onset Alzheimer disease. Arch Gen Psychiatry
2003;60:190-197.
3. St George-Hyslop PH. Molecular genetics of Alzheimer’s disease. Biol Psychiatry 2000;47:183-199.
4. Slooter AJ, Cruts M, Kalmijn S, et al. Risk estimates of dementia by apolipoprotein E genotypes from a population-based incidence study: the Rotterdam Study. Arch Neurol 1998;55:964968.
5. Farrer LA, Bowirrat A, Friedland RP, et al. Identification of
multiple loci for Alzheimer disease in a consanguineous IsraeliArab community. Hum Mol Genet 2003;12:415-422.
6. Blacker D, Bertram L, Saunders AJ, et al. Results of a highresolution genome screen of 437 Alzheimer’s Disease families.
Hum Mol Genet 2003;12:23-32.
7. Blacker D, Wilcox MA, Laird NM, et al. Alpha-2 macroglobulin is genetically associated with Alzheimer disease. Nat Genet
1998;19:357-360.
8. Wavrant-DeVrieze F, Perez-Tur J, Lambert JC, et al. Association
between the low density lipoprotein receptor-related protein
(LRP) and Alzheimer’s disease. Neurosci Lett 1997;227:68-70.
9. Edland SD, Wavrant-De Vriese F, Compton D, et al. Insulin
degrading enzyme (IDE) genetic variants and risk of Alzheimer’s disease: evidence of effect modification by apolipoprotein
E (APOE). Neurosci Lett 2003;345:21-24.
10. Ertekin-Taner N, Ronald J, Asahara H, et al. Fine mapping of
the alpha-T catenin gene to a quantitative trait locus on chromosome 10 in late-onset Alzheimer’s disease pedigrees. Hum
Mol Genet 2003;12:3133-3143.
11. Li YJ, Oliveira SA, Xu P, et al. Glutathione S-transferase
omega-1 modifiesage-at-onset of Alzheimer disease and Parkinson disease. Hum Mol Genet 2003;12:3259-3267.
12. Mayeux R. Epidemiology of neurodegeneration. Ann Rev Neurosci 2003;26:81-104.
13. Stern Y, Gurland B, Tatemichi TK, et al. Influence of education and occupation on the incidence of Alzheimer’s disease.
Jama 1994;271:1004-1010.
14. Friedland RP, Fritsch T, Smyth KA, et al. Patients with Alzheimer’s disease have reduced activities in midlife compared
with healthy control-group members. Proc Natl Acad Sci U S A
2001;98:3440-3445.
15. Tang M-X, Jacobs D, Stern Y, et al. Effect of oestrogen during
menopause on risk and age-at-onset of Alzheimer’s disease. Lancet 1996;348:429 – 432.
16. Yaffe K, Haan M, Byers A, et al. Estrogen use, APOE, and
cognitive decline: evidence of gene-environment interaction.
Neurology 2000;54:1949-1954.
17. Stewart WF, Kawas C, Corrada M, Metter EJ. Risk of Alzheimer’s disease and duration of NSAID use. Neurology 1997;48:
626-632.
18. Orgogozo JM, Dartigues JF, Lafont S, et al. Wine consumption and dementia in the elderly: a prospective community
study in the Bordeaux area. Rev Neurol (Paris) 1997;153:185192.
19. Laurin D, Verreault R, Lindsay J, et al. Physical activity and
risk of cognitive impairment and dementia in elderly persons.
Arch Neurol 2001;58:498-504.
20. in ’t Veld BA, Ruitenberg A, Hofman A, et al. Nonsteroidal
antiinflammatory drugs and the risk of Alzheimer’s disease.
New England Journal of Medicine 2001;345:1515-1521.
DOI: 10.1002/ana.20037
158
Biomarker Epidemiology of
Cerebral Palsy
Once upon a time, epidemiologists and basic scientists
did not talk to one another. Recently, however, they
have come together to foster the field that is now called
biomarker epidemiology. Whereas the emphasis previously had been on identifying exposures and/or outcomes by interview or review of records, now the exposures and/or outcomes are identified with the tools
of the (molecular) biologist. Equally, if not more important, biomarker epidemiologists also want to generate and evaluate hypotheses about the intermediate
steps leading from the exposure to the disorder they
study. In essence, biomarker epidemiologists fully disagree with the view that “epidemiological methods
identify causes, but not mechanism of disease.”1
Advances in clinical proteomics,2 also known as disease proteomics,3 offer the hope that progress in identifying and subsequently measuring more proteins in
smaller amounts of body fluid will result in improved
epidemiological studies of neurological disorders. The
simultaneous evaluation of many proteins is needed for
an understanding of interprotein relationships, especially in light of known “context specificity.”
The article in this issue by Kaukola and colleagues4
is the latest example of a biomarker epidemiology study
that evaluates the link between 78 biomarkers (cytokines, chemokines, and growth factors) measured in venous cord blood and cerebral palsy risk. It differs from
previous studies in several ways. First, it is the first article to our knowledge that reports on biomarker differences between cerebral palsy cases and controls in
both preterm and term children. Second, it includes
many biomarkers not included in previous studies.
Third, it describes results from biomarker measurements using a laboratory technique (a multiplexed microarray sandwich-immunoassay involving rolling circle
signal amplification) that is different from those used
in previous studies of cord and neonatal blood samples.
Despite its novelty, the article has major limitations
that prompt us to advise caution in drawing inferences
from its findings. First, it is a rather small study with
low power, comparing essentially 10 preterm and 9
term children with cerebral palsy to 19 gestational agematched controls. Matching for gestational age, although crucial, does not necessarily suffice as a strategy
to render groups comparable. Moreover, the study design, with more variables (78 biomarkers) than subjects, violates a basic axiom of epidemiology. The low
power is such a limiting factor that we prefer to view
the study more as a venture in hypothesis generation
© 2004 American Neurological Association
Published by Wiley-Liss, Inc., through Wiley Subscription Services
than in hypothesis testing. This is all the more appropriate because many of the 75 biomarkers had not
been evaluated at all or minimally in biomarker studies
of cerebral palsy. Second, it looks at median serum
concentrations of biomarkers, thereby ignoring the
possibility that what is most informative is the proportion of children in the highest or lowest quantile (eg,
quartile or decile) of each biomarker’s concentration
distribution.
Third, the authors do not display the data for all
biomarkers that they measured, so that we do not
know how the distributions of some biomarkers differed between cases and controls. Fourth, probably because of small size, the study does not allow for multivariable analytic approaches, which are the only
current techniques of adjusting for distortions by potential confounding factors.
Before offering additional comments about what this
study found and did not find, we provide some background about biomarker epidemiological studies of
neonatal brain damage and cerebral palsy. Although
some children with sonographic evidence of white matter damage do not develop cerebral palsy, and some
children who develop cerebral palsy do not have sonographic evidence of white matter damage,5 much of the
literature supports the view that an appreciable proportion of cerebral palsy, in preterm infants at least, reflects white matter damage. Perhaps the association between white matter damage and cerebral palsy will be
more apparent with the increased use of early magnetic
resonance imaging.6
Inflammation
What may be the earliest biomarker study of white
matter damage in newborns documented that infants
who died with white matter damage were much more
likely than their peers to have gram-negative bacteria in
cardiac blood at the time of autopsy.7,8 No bacteria
were seen in the brains of any of the infants who died
with white matter damage. These and related observations led to the speculation that a circulating product
of infection such as endotoxin (lipopolysaccharide)
might contribute to neonatal white matter damage.
They also led to the hypothesis that remote infection
(ie, outside the central nervous system) can lead to cerebral white matter damage.9
Subsequently, the focus shifted from infection to inflammation,10,11 and enough evidence became available
to bolster our suggestion that intrauterine infection
might initiate an inflammatory response in the placenta, the systemic circulation, and the brain of preterm newborns, eventually leading to brain white matter damage.12 A host of observations now support the
infection-inflammation-brain damage link.13–16
An infant is at increased risk of white matter damage
and/or cerebral palsy if (1) there has been exposure to
chorioamnionitis,15,17 (2) the blood vessels of the chorionic plate of the placenta or the umbilical cord are
inflamed,18,19 (3) the concentrations of proinflammatory cytokines are increased in amniotic fluid,19,20 umbilical cord blood21–23 or postnatal blood obtained for
state-mandated newborn screening,24 (4) the concentration of a cellular marker of antigen exposure
(CD45RO⫹ T lymphocytes) is increased in umbilical
cord blood.22
These findings have led to two important inferences.
First, the inflammatory phenomena and presumably
the processes leading to white matter damage begin in
utero. Second, the likelihood of brain damage is increased if the fetus responds to an inflammatory stimulus.
A recent review concludes “in very premature infants, the association of infection with cerebral palsy
has been less consistent and, when present, less strong”
than in term newborns.25 Although it may still be true
that the pathomechanisms differ between preterm and
term infants, the absence of an association in some
samples of preterm infants also might have methodological reasons.26 For example, failure to perceive an
association between biomarkers of inflammation and
cerebral palsy in preterm infants in two recent published studies27,28 might be caused in part by the exclusion of infants at highest risk of antenatal infection
(birth within 3 hours of admission) as well as exclusion
of those who might have been at lowest risk (preeclampsia).
Another possibility is that the inflammatory process
leading to preterm labor and cerebral white matter
damage might subside within days of delivery. Indeed,
the high concentrations of inflammatory cytokines in
cord blood can fall within days of delivery.29 Thus,
examining blood obtained days after birth might fail to
identify the inflammatory processes that were at their
peak before delivery. They might be expected, however, to identify some of the antiinflammatory processes that are responses to circulating inflammatory
proteins and neonatal inflammatory processes that are
independent of antenatal exposures. Thus, we consider
repeated biomarker assessments an integral part of future research.
Because inflammatory biomarker patterns in the
uterine cavity differ appreciably between preterm and
term labor,30 the inflammation–brain damage link in
preterm newborns might differ from that in term newborns. This possibility prompted Kaukola and colleagues to evaluate preterm newborns separately from
term newborns.4
Kaukola and colleagues found that of the 78 biomarkers evaluated in 10 preterm case–control pairs, only
five had median values that differed between cerebral
cases and their gestational age-matched controls. The
umbilical venous blood concentrations of the four that
Dammann and Leviton: Biomarker Epidemiology
159
can be viewed as markers of inflammatory processes
tended to be lower in the cerebral palsy cases. An additional, and probably equally important, point is what
the investigators did not find. They did not find appreciable differences between cases and controls in the
distribution of the “classic” proinflammatory cytokines
that have played a prominent role in previous reports
(eg, interleukin [IL]–1␤, tumor necrosis factor–␣,
interleukin-6, among others). These findings must be
viewed with great caution in light of the very low
power of the study (see above), but they do suggest a
lack of support for hypotheses that rely on systemic
inflammation as one of the driving forces leading to
brain damage manifested as congenital motor handicap.
Compared with their controls, the nine children
born at term who developed cerebral palsy tended to
have higher median cord blood concentrations of 15
biomarkers. Most have inflammatory or antiinflammatory properties, providing some support for the hypothesis that brain damage in term born children who
develop cerebral palsy is preceded or accompanied by
inflammatory phenomena. This interpretation lends itself toward a perception of inflammatory phenomena
as biomarkers of exposure. On the other hand,
Kaukola and colleagues carefully discuss the possibility
that some of the proteins elevated in cerebral palsy
cases might be biomarkers of outcome, that is, brain
damage.31
Developmental Regulation
Morphological and physiological processes that vary
with gestational age are considered “developmentally
regulated.” Investigators seek to understand how each
protein that might be involved in promoting or preventing white matter damage and cerebral palsy varies
with gestational age. An underlying assumption is that
some of the unusually high risk in preterm newborns
reflects developmentally regulated phenomena. This assumption has taken form as two hypotheses.
In Kaukola and colleagues’ study, 11 biomarkers
correlated with the length of gestation, both in cases
and controls. Venous cord blood concentrations of
IL-6, IL-8, and a plasminogen activator receptor declined with increasing gestational age, providing some
support for the hypothesis that preterm newborns have
less immunomodulating capability than their gestationally older and more mature peers.32,33 So too are the
observations that the venous blood concentrations of
the immunomodulators transforming growth factor–␤1
and leukemia inhibitory factor increase with gestational
age. What is less easily integrated into this “immunomodulating” hypothesis is the observation that concentrations of tumor necrosis factor–␣ also tended to increase with gestational age.
The “paucity-of-protectors” hypothesis is based on
160
Annals of Neurology
Vol 55
No 2
February 2004
the observation that infants born much before term
have lower blood levels of proteins needed for extrauterine well-being.34 Many of these molecules are provided by the mother or by the placenta before the third
trimester, when the fetus begins to produce these substances in sufficient amounts. Included among these
developmentally regulated proteins are growth factors
and hormones that promote oligodendrocyte survival
and maturation. This led to the inference that preterm
newborns are more vulnerable to cerebral white matter
damage and cerebral palsy, in part because they do not
have adequate amounts of proteins that ensure the
well-being of oligodendrocytes and their precursors,35
and that low circulating concentrations of these growth
factors and hormones indicate heightened risk of white
matter damage and cerebral palsy. Indeed, preterm
newborns with the lowest blood levels of thyroxine are
at increased risk of cerebral white matter damage18 and
cerebral palsy.36 To date, clinical trials of thyroxine
supplementation have not been encouraging.37
In the study by Kaukola and colleagues, brainderived neurotrophic factor is the clearest example of a
growth factor with neurotrophic properties whose concentration in venous blood increases with increasing
gestational age. This example of developmental regulation can be viewed as support for the hypothesis that
infants born much before term might be especially vulnerable because of their lack of protectors.
We are pleased with the authors’ preparation of their
Figure 2. Perhaps they and others will try to fit lines
for predicted values of the biomarkers based on their
gestational age–related data. More studies of developmental regulation of biomarkers are needed in the future to adjust for gestational age–specific biomarker
distributions in comparative studies.
Olaf Dammann1,2 and Alan Leviton2
1
Perinatal Infectious Disease Epidemiology Unit,
Department of Obstetrics, Prenatal Medicine, and
Gynecology Department of Pediatric Pulmonology and
Neonatology
Hannover Medical School
Hannover, Germany
2
Neuroepidemiology Unit
Department of Neurology
Children’s Hospital and Harvard Medical School
Boston, MA
References
1. Perry IJ. Risk factor epidemiology. Lancet 1997;350:1256.
2. Tyers M, Mann M. From genomics to proteomics. Nature
2003;422:193–197.
3. Petricoin EF, Zoon KC, Kohn EC, et al. Clinical proteomics:
translating benchside promise into bedside reality. Nat Rev
Drug Discov 2002;1:683– 695.
4. Kaukola T, Satyaraj E, Patel DD, et al. Cerebral palsy is characterized by protein mediators in cord serum. Ann Neurol
2004;55:136 –194.
5. Holling EE, Leviton A. Characteristics of cranial ultrasound
white matter echolucencies that predict disability: a review. Dev
Med Child Neurol 1999;41:136 –139.
6. Inder TE, Anderson NJ, Spencer C, et al. White matter injury
in the premature infant: a comparison between serial cranial
sonographic and MR findings at term. AJNR Am J Neuroradiol
2003;24:805– 809.
7. Leviton A, Gilles FH. An epidemiologic study of perinatal telencephalic leucoencephalopathy in an autopsy population.
J Neurol Sci 1973;18:53– 66.
8. Leviton A, Gilles F, Neff R, et al. Multivariate analysis of risk
of perinatal telencephalic leucoencephalopathy. Am J Epidemiol
1976;104:621– 626.
9. Dammann O, Leviton A. Infection remote from the brain, neonatal white matter damage, and cerebral palsy in the preterm
infant. Semin Pediatr Neurol 1998;5:190 –201.
10. Adinolfi M. Infectious diseases in pregnancy, cytokines and
neurological impairment: an hypothesis. Dev Med Child Neurol 1993;35:549 –553.
11. Leviton A. Preterm birth and cerebral palsy: is tumor necrosis
factor the missing link? Dev Med Child Neurol 1993;35:
553–558.
12. Dammann O, Leviton A. Maternal intrauterine infection, cytokines, and brain damage in the preterm newborn. Pediatr Res
1997;42:1– 8.
13. Dammann O, Leviton A. Role of the fetus in perinatal infection
and neonatal brain damage. Curr Opin Pediatr 2000;12:99 –104.
14. Toti P, De Felice C. Chorioamnionitis and fetal/neonatal brain
injury. Biol Neonate 2001;79:201–204.
15. Wu YW. Systematic review of chorioamnionitis and cerebral
palsy. Ment Retard Dev Disabil Res Rev 2002;8:25–29.
16. Willoughby RE Jr, Nelson KB. Chorioamnionitis and brain injury. Clin Perinatol 2002;29:603– 621.
17. Jacobsson B, Hagberg G, Hagberg B, et al. Cerebral palsy in preterm infants: a population-based case-control study of antenatal
and intrapartal risk factors. Acta Paediatr 2002;91:946 –951.
18. Leviton A, Paneth N, Reuss ML, et al. Maternal infection, fetal
inflammatory response, and brain damage in very low birthweight infants. Pediatric Res 1999;46:566 –575.
19. Yoon BH, Romero R, Park JS, et al. Fetal exposure to an intraamniotic inflammation and the development of cerebral palsy at
the age of three years. Am J Obstet Gynecol 2000;182:
675– 681.
20. Yoon BH, Jun JK, Romero R, et al. Amniotic fluid inflammatory cytokines (interleukin-6, interleukin- 1beta, and tumor necrosis factor-alpha), neonatal brain white matter lesions, and cerebral palsy. Am J Obstet Gynecol 1997;177:19 –26.
21. Yoon BH, Romero R, Yang SH, et al. Interleukin-6 concentrations in umbilical cord plasma are elevated in neonates with
white matter lesions associated with periventricular leukomalacia. Am J Obstet Gynecol 1996;174:1433–1440.
22. Duggan PJ, Maalouf EF, Watts TL, et al. Intrauterine T-cell
activation and increased proinflammatory cytokine concentrations in preterm infants with cerebral lesions. Lancet 2001;358:
1699 –1700.
23. Minagawa K, Tsuji Y, Ueda H, et al. Possible correlation between high levels of IL-18 in the cord blood of pre-term infants
and neonatal development of periventricular leukomalacia and
cerebral palsy. Cytokine 2002;17:164 –170.
24. Nelson KB, Dambrosia JM, Grether JK, et al. Neonatal cytokines and coagulation factors in children with cerebral palsy.
Ann Neurol 1998;44:665– 675.
25. Nelson KB. Can we prevent cerebral palsy? N Engl J Med
2003;349:1765–1769.
26. Hagberg H. No correlation between cerebral palsy and cytokines in postnatal blood of preterms. Pediatr Res 2003;53:
544 –545.
27. Grether JK, Nelson KB, Walsh E, et al. Intrauterine exposure
to infection and risk of cerebral palsy in very preterm infants.
Arch Pediatr Adolesc Med 2003;157:26 –32.
28. Nelson KB, Grether JK, Dambrosia JM, et al. Neonatal cytokines and cerebral palsy in very preterm infants. Pediatr Res
2003;53:600 – 607.
29. Dammann O, Phillips TM, Allred EN, et al. Mediators of fetal
inflammation in extremely low gestational age newborns. Cytokine 2001;13:234 –239.
30. Maymon E, Ghezzi F, Edwin SS, et al. The tumor necrosis
factor alpha and its soluble receptor profile in term and preterm
parturition. Am J Obstet Gynecol 1999;181:1142–1148.
31. Leviton A, Dammann O. Brain damage markers in children.
Neurobiological and clinical aspects. Acta Paediatr 2002;91:
9 –13.
32. Atici A, Satar M, Alparslan N. Serum interleukin-1beta in neonatal sepsis. Acta Paediatr 1996;85:371–374.
33. Berner R, Niemeyer CM, Leititis JU, et al. Plasma levels and
gene expression of granulocyte colony-stimulating factor, tumor
necrosis factor-alpha, interleukin (IL)-1beta, IL-6, IL-8, and
soluble intercellular adhesion molecule-1 in neonatal early onset
sepsis. Pediatr Res 1998;44:469 – 477.
34. Reuss ML, Paneth N, Lorenz JM, et al. Correlates of low thyroxine values at newborn screening among infants born before
32 weeks gestation. Early Hum Dev 1997;47:223–233.
35. Dammann O, Leviton A. Brain damage in preterm newborns:
might enhancement of developmentally-regulated endogenous
protection open a door for prevention? Pediatrics 1999;104:
541–550.
36. Reuss ML, Paneth N, Pinto-Martin JA, et al. The relation of
transient hypothyroxinemia in preterm infants to neurologic development at two years of age. N Engl J Med 1996;334:
821– 827.
37. van Wassenaer AG, Briet JM, van Baar A, et al. Free thyroxine
levels during the first weeks of life and neurodevelopmental
outcome until the age of 5 years in very preterm infants. Pediatrics 2002;110:534 –539.
DOI: 10.1002/ana.20014
Why Muscle Atrophy in
Acute Quadriplegic
Myopathy Is Rapid and
Severe
The article on acute quadriplegic myopathy (AQM)
from Di Giovanni and colleagues1 highlights the complexity of skeletal muscle atrophy. The authors demonstrate that rapid and severe atrophy in acute quadriplegic myopathy develops because of activation of
multiple degenerative pathways within muscle. AQM,
also called acute illness myopathy, critical illness my-
Annals of Neurology Vol 55 No 2 February 2004
161
opathy, or acute myopathy of intensive care, is a serious condition that develops in association with two of
the following three conditions: (1) treatment with a
nondepolarizing neuromuscular blocking agent, (2)
high-dose systemic glucocorticoid treatment, or (3) severe illness such as sepsis.2– 4 AQM is a syndrome with
several variations. There is profound muscle fiber atrophy, especially in fast twitch fibers, without evidence of
denervation or inflammation.3–5 Frank muscle fiber
necrosis is rare. Consequently, serum levels of muscleassociated proteins such as creatine kinase are often not
elevated. Some patients have prominent loss of myosin
and other contractile proteins.3,6 Skeletal muscle fibers
can be inexcitable because of membrane depolarizationinduced inactivation of sodium channels combined
with loss of sodium channels or altered sodium channel
gating.7,8
Prior work had shown that AQM was associated
with ubiquitin-mediated proteolysis with activation of
cytoplasmic and lysosomal-dependent proteolytic pathways.4,9 –12 Previous studies identified changes in gene
expression in animal models of AQM including suppression of skeletal muscle sodium channels8 and expression of mRNA associated with proteolytic pathways.13 However, existing data did not provide a
coherent story about what degeneration pathways were
specifically activated and how the pattern of degeneration pathway activation differed between AQM and
other conditions leading to muscle atrophy.
The authors used an elegant combination of techniques to evaluate different muscle degeneration pathways. They used microarray (genechip) technology to
analyze for patterns of activation or suppression of
genes associated with specific enzymatic pathways. Reverse transcriptase polymerase chain reaction assays
were used to validate gene expression patterns determined from genechip assays and to measure expression
of relevant genes that were not represented on the genechip. Immunoblot was used to assay for the presence
of specific proteins, and the terminal deoxynucleotidyltransferase–mediated dUTP nick end labeling
(TUNEL) technique was used to detect nuclear DNA
fragmentation in situ. Thus, the authors analyzed for
activation of specific degeneration pathways using a
cross-checking combination of nucleic acid and protein
assays. They compared biopsy specimens from patients
with AQM with biopsies from patients who had neurogenic atrophy and control patients who had asymptomatic elevation of creatine kinase. The subject groups
enabled them to determine which degeneration pathways were specifically activated in neurogenic atrophy
and AQM.
Both neurogenic atrophy and AQM were associated
with activation of the elements of the ubiquitindependent proteolysis pathway. AQM distinguished itself from neurogenic atrophy by activating several path-
162
Annals of Neurology
Vol 55
No 2
February 2004
ways associated with muscle fiber degeneration. AQM
showed stronger upregulation of ubiquitin-dependent
proteolysis, including upregulation of the ubiquitin ligase, atrogin-1. AQM also showed stronger activation
of caspase proteases. AQM activated the MAPK signaling cascade, which regulates cell growth, atrophy, and
apoptosis. The MAPK cascade was not activated in
neurogenic atrophy. AQM activated elements of the
MAPK cascade including the transforming growth factor (TGF)–␤ and RAS cascades. Some fibers in AQM
biopsy specimens showed features of apoptosis. Key elements of TGF-␤–MAPK cascade were strongly expressed in apoptotic AQM fibers and a small fraction
of TUNEL-negative AQM fibers. Neurogenic atrophy
was not associated with apoptosis or activation of the
TGF-␤–MAPK cascade.
The work of Di Giovanni and colleagues1 provides a
molecular explanation for the rapid and severe muscle
atrophy seen in AQM. AQM was associated with activation of multiple cell degeneration pathways including
the ubiquitin-dependent pathway that is also activated
in neurogenic atrophy and the TGF-␤–MAPK cascade
that was associated with apoptosis. Apoptosis was not a
prominent feature of neurogenic atrophy. Remaining
questions include (1) how does AQM activate the
TGF-␤–MAPK cascade? and (2) how can clinicians
avert the activation of muscle degeneration pathways in
patients at risk for developing AQM?
Robert L. Ruff, MD, PhD
Spinal Cord Injury and Dysfunction Service
Louis Stokes Department of Veterans Affairs Medical
Center
Departments of Neurology and Neurosciences
Case Western Reserve University School of Medicine
Cleveland, OH
References
1. Di Giovanni S, Molon A, Broccolini A, et al. Myogenic atrophy in acute quadripelgic myopathyis specifically associated
with activation pro-apoptotic TGF beta-MAPK cascade. Ann
Neurol 2004;55:195–206.
2. Ruff RL. Why do ICU patients become paralyzed? Ann Neurol
1998;43:154 –155.
3. Larsson L, Li X, Edstrom L, et al. Acute quadriplegia and loss
of muscle myosin in patients treated with nondepolarizing neuromuscular blocking agents and corticosteroids: mechanisms at
the cellular and molecular levels. Crit Care Med 2000;28:
34 – 45.
4. Lacomis D. Critical illness myopathy. Curr Rheumatol Rep
2002;4:403– 408.
5. Gutmann L, Blumenthal D, Gutmann L, Schochet SS. Acute
type II myofiber atrophy in critical illness. Neurology 1996;46:
819 – 821.
6. Sander HW, Golden M, Danon MJ. Quadriplegic areflexic
ICU illness: selective thick filament loss and normal nerve histology. Muscle Nerve 2002;26:499 –505.
7. Rich MM, Pinter MJ, Kraner SD, Barchi RL. Loss of electrical
excitability in an animal model of acute quadriplegic myopathy.
Ann Neurol 1998;43:171–179.
8. Rich MM, Kraner SD, Barchi RL. Altered gene expression in
steroid-treated denervated muscle. Neurobiol Dis 1999;6:515–522.
9. Mitch WE, Bailey JL, Wang X, et al. Evaluation of signals activating ubiquitin-proteasome proteolysis in a model of muscle
wasting. Am J Physiol 1999;276:C1132–C1138.
10. Helliwell TR, Wilkinson A, Griffiths RD. Muscle fiber atrophy
in critically ill patients is associated with loss of myosin filaments and the pressure of lysosomal enzymes and ubiquitin.
Neuropathol Appl Neurobiol 1998;24:507–515.
11. Showalter CJ, Engel AG. Acute quadriplegic myopathy: analysis
of myosin isoforms and evidence for calpain-medicated proteolysis. Muscle Nerve 1997;20:316 –322.
12. Matsumoto N, Nakamura T, Yasui Y, Torii J. Analysis of muscle proteins in acute quadriplegic myopathy. Muscle Nerve
2000;23:1270 –1276.
13. Jagoe RT, Lecker SH, Gomes M, Goldberg AL. Patterns of
gene expression in atrophying skeletal muscles: responses to
food deprivation. FASEB J 2002;16:1697–1712.
DOI: 10.1002/ana.10845
Annals of Neurology Vol 55 No 2 February 2004
163
Документ
Категория
Без категории
Просмотров
0
Размер файла
119 Кб
Теги
epidemiology, biomarkers, palsy, cerebral
1/--страниц
Пожаловаться на содержимое документа