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Imaging stroke recovery Lessons from prozac.

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EDITORIALS
Microarrays, Markers of
Disease, and the Myth of
“Nonhypothesis-Driven”
Research
The article by Tang and colleagues1 in this issue of the
Annals reports that differences in gene expression patterns in blood mononuclear leukocytes, measured with
DNA microarrays, can distinguish a variety of experimental cerebral disorders. This is an important contribution because of the potential for applying genomic
and proteomic technology to identifying peripheral
markers of neurological disease. While a handful of articles have characterized gene expression patterns in the
brain in neurological disorders, this is the first to demonstrate the feasibility of using microarray data for
neurological differential diagnosis. Moreover, because
distinct patterns of altered gene expression were detectable in blood, this approach could lead to minimally
invasive diagnosis of neurological disorders.
DNA microarrays, or gene chips, consist of hundreds or thousands of DNA fragments spotted onto a
glass slide or other support, and provide a means for
comparing the profiles of messenger RNA (mRNA) expression in two tissue samples. This is accomplished by
labeling mRNA from the two samples with different
fluorescent dyes and measuring their relative binding to
each spot on the array. Like any other investigative
method, DNA microarrays have strengths and weaknesses. A major strength is the ability to monitor the
expression of thousands of genes simultaneously, and
thereby to profile changes in their expression associated
with a biological or pathological process. However, because gene-chip microarrays measure mRNA abundance, they identify only alterations in gene transcription and cannot detect whether changes in the level or
function of proteins occur as well. These and other issues surrounding the use of DNA microarrays in neurobiological research are discussed in detail in an excellent recent review.2
Two of the principal uses of DNA microarrays are
for fingerprinting biological or pathological processes
and for discovering new genes involved in these processes. An example of the former is the finding by
Tang and colleagues that disorders such as cerebral
ischemia, intracerebral hemorrhage, seizures, hypoglycemia, and hypoxia produce distinct gene-expression
profiles in blood leukocytes. This suggests that genechip technology could be useful as a minimally invasive
approach for differential diagnosis. In addition, there is
the prospect for improved understanding of pathogen-
esis and perhaps, as a result, new treatments. Thus, recent studies published in the Annals of Neurology have
used microarrays to identify changes in the expression
of genes not previously implicated in multiple sclerosis3
and Alzheimer’s disease.4 When microarrays are used
for fingerprinting, reproducibility is critical; for discovering clinically relevant genes, however, it is most important that observed changes in gene transcription are
accompanied by changes in protein expression and associated biological effects. In short, assessing the validity and value of microarray results requires that the experimental context be considered.
This brings up a criticism of microarray studies that
has achieved some currency, namely, that such studies
are by their nature “nonhypothesis-driven.” The implication seems to be that if one tests 10,000 genes seriatim for disease-related changes in expression, this represents 10,000 hypothesis-driven experiments, but if all
the genes are tested simultaneously on a single chip,
the hypotheses are somehow annulled. The clear hypothesis of Tang and colleagues—that “the gene expression profile in white blood cells could be used as a
fingerprint of different disease states”—was tested and
affirmed.
Microarray technology is starting to be used for additional applications, such as protein arrays to detect
protein–protein interactions5 and even arrays of living
cells.6 We do not yet know how clinically useful any of
these so-called massively parallel approaches will prove
to be, but the study by Tang and colleagues augurs
well. As microarray technology develops, it will be important that disdain for “nonhypothesis-driven” research does not prevent its potential benefits from being realized.
David A. Greenberg, MD, PhD
Buck Institute for Age Research
Novato, CA
References
1. Tang Y, Lu A, Aronow BJ, Sharp FR. Blood genomic responses
differ after stroke, seizures, hypoglycemia and hypoxia: blood
genomic fingerprints of disease. Ann Neurol 2001;50:699 –707.
2. Greenberg SA. DNA microarray gene expression analysis technology and its application to neurological disorders. Neurology
2001;57:755–761.
3. Whitney LW, Becker KG, Tresser NJ, et al. Analysis of gene
expression in multiple sclerosis lesions using cDNA microarrays.
Ann Neurol 1999;46:425– 428.
4. Ginsberg SD, Hemby SE, Lee VM, et al. Expression profile of
transcripts in Alzheimer’s disease tangle-bearing CA1 neurons.
Ann Neurol 2000;48:77– 87.
5. MacBeath G, Schreiber SL. Printing proteins as microarrays for
high-throughput function determination. Science 2000;289:
1760 –1763.
6. Ziauddin J, Sabatini DM. Microarrays of cells expressing defined
cDNAs. Nature 2001;411:107–110.
© 2001 Wiley-Liss, Inc.
695
Epilepsy After Head Injury:
The Impact of Impact
A bone of the skull of a 12-year old youth had been
broken and depressed by a fall and by negligence
had not been restored . . . . Consequently in his
18th year the youth suffered from epilepsy because of oppression of the brain.
—Duretus, (1527–1586)1
But the secret I was seeking eluded me as it has
eluded others before me and since that time: What
is it that corrupts the nerve cells of the remaining
gray matter from their true function while scars
form and wounds heal, changing the orderly formation and conduction of nervous impulse into
disorderly mass discharges?
—Wilder Penfield2
Although head injury accounts for a relatively small
proportion of the causes of epilepsy overall, the risk of
epilepsy in patients who have suffered from severe head
trauma is remarkably high. For example, soldiers with
penetrating missile injuries of the brain have a 30 to
50% incidence of epilepsy,3 and civilian patients with
trauma-induced loss of consciousness, prolonged amnesia, and subdural hematomas or brain contusion have
at least a 12-fold increased risk of developing epilepsy
within the next 10 years compared with the general
population.4 At the other end of the scale, epidemiological studies suggest that there is minimal risk of epilepsy after concussive head injury in which the loss of
consciousness or amnesia is less than 30 minutes.4
Nonetheless, many epileptologists can offer compelling
anecdotes about previously healthy patients who have
focal complex seizures immediately after relatively minor head injury, and who subsequently develop classic
features of temporal lobe epilepsy.
The clear link between head injury and epilepsy presents an opportunity for achieving a thus-far unattained goal: the prevention of epilepsy in an at-risk
population. Conceptually, antiepileptogenesis strategies
are the ultimate goal of epilepsy therapeutics, and the
high incidence of head injury in an adult population
and the predictability of subsequent epilepsy have led
to a number of large-scale clinical trials looking at the
potential benefits of anticonvulsant therapy in preventing post-traumatic epilepsy. Unfortunately, the results
of these trials have been disappointing—a recent metaanalysis concluded that although anticonvulsants prevent seizures in the first week after injury, they do not
prevent the development of epilepsy.5 The need to prevent epilepsy in a high-risk population and the current
lack of any effective treatment is magnified by our limited understanding of the basic, underlying mecha-
696
© 2001 Wiley-Liss, Inc.
nisms of trauma-induced epileptogenesis. This is not
for want of experimental models or intensive research
on head injury itself–the literature is replete with studies of the structural, biochemical, and overall functional consequences of traumatic brain injury.6 However, relatively little effort has been focused on the
effects of trauma on network excitability.
In 1992, my colleagues and I made the fortuitous discovery that experimental fluid-percussion injury (FPI) in
the rat causes a selective loss of hilar interneurons in the
dentate gyrus.7 Our observation grew from the work of
Robert Sloviter, who had shown that a similar pattern of
cell loss could be induced by pure electrical activation of
the main afferent input into the dentate gyrus, and predicted that the selective loss of cells led to a pathological
disinhibition of the dentate granule cells.8 In both models, the pattern of injury is strikingly similar to that seen
in many cases of human temporal lobe epilepsy.9
Prompted by Sloviter’s work, we found that the immediate cell loss induced by the injury was associated with
abnormal hyperexcitability of the dentate granule cells 1
week later, and we proposed this as a potential mechanism of trauma-induced epileptogenesis. The model
turns out to be far from perfect, since the animals fail to
develop clinically evident, spontaneous seizures. Nonetheless, the fact that a single, isolated, 25msec impact to
the dura could lead to a prolonged defect in network
excitability at some distance from the injury provided at
least a new system for studying the electrophysiological
consequences of head trauma. Over the next few years,
additional studies both verified the pattern of selective
cell loss and provided a more sophisticated analysis of
the short-term abnormalities of excitability.10 –12 However, until now, studies of the long-term electrophysiological effects of FPI have been lacking.
In this issue of Annals, Soltesz and colleagues provide
us with some initial information about the persistent
changes in network properties of the hippocampal formation following FPI in the rodent.13 Using
hippocampal-entorhinal cortical slices prepared acutely
from animals sacrificed at various times after FPI, they
found that the evoked population spike amplitude of
dentate granule cells in response to perforant path stimulation, which was abnormally elevated 1 week after injury, had returned to control levels 1 and 3 months
later. However, studies of tetanic stimulation of the
Schaeffer collaterals (the main input to CA1 pyramidal
cells) 3 months after FPI revealed a significant decrease
in the threshold for the generation of self-sustaining epileptiform activity compared with control slices (ie, abnormal hyperexcitability). Somewhat surprisingly, they
also observed a long-lasting increase in the frequency of
spontaneous inhibitory postsynaptic currents in dentate
granule cells after FPI, an increase that appeared to be a
consequence of enhanced excitatory drive onto inhibitory interneurons within the circuit. The finding of en-
hanced inhibition and hyperexcitability in an epileptogenic process may seem paradoxical but is hardly
unprecedented, and, as the authors mention in their discussion, there are a number of theories and supportive
evidence to suggest a causal link between the two.
Where do these new findings leave us? Soltesz and
colleagues have provided unambiguous evidence for a
chronic network defect in the hippocampal formation
many months after a single episode of head trauma.
Along with the work of Prince and coworkers using a
different model of mechanical trauma (the cortical undercut model),14 we now have at least two systems for
studying epileptogenesis associated with the types of injuries seen in patients. Given the need for the development of preventative therapies, investigators may be
tempted to use these models to screen potential antiepileptogenic compounds. This would be an exceptionally risky venture, at least at the present time. The
models do not lend themselves to high through-put
drug screening, and the relationship between the abnormal network properties and the clinical phenotype
of epilepsy, particularly in humans, is uncertain at best.
Furthermore, we need to be especially selective about
the choice of interventions that are proposed for prospective clinical trials looking at head injury and the
subsequent onset of epilepsy. By their nature, these trials require large numbers of patients, prolonged periods
of observation to verify the presence or absence of a
beneficial effect, and they are too expensive to justify
an approach lacking a well-founded, rational basis.
This leaves us with only one viable option—determined and sustained efforts to identify the precise molecular, cellular, and systems events that are induced by
trauma and transform a normal neural circuit into a
seizure focus. By documenting for the first time the
long-term electrophysiological changes seen in the FPI
model, Soltesz and colleagues have made a significant
contribution toward this goal.
Daniel Lowenstein, MD
Harvard Medical School
Boston, Massachusetts
References
1. Temkin O. The falling sickness: a history of epilepsy from the
Greeks to the beginnings of modern neurology. Baltimore: The
Johns Hopkins Press, 1945.
2. Penfield W. Introduction (to the Symposium on PostTraumatic Epilepsy at the American Epilepsy Society Meeting).
Epilepsia 1961;2:109 –110.
3. Jennett B. Epilepsy after non-missile head injuries. 2nd ed.
London: William Heinemann, 1975.
4. Annegers J, Hauser W, Coan S, et al. A population based study
of seizures after traumatic brain injuries. N Engl J Med 1998;
338:20 –24.
5. Temkin N. Antiepileptogenesis and seizure prevention trials
with antiepileptic drugs: meta-analysis of controlled trials. Epilepsia 2001;42:515–524.
6. Laurer H, McIntosh T. Experimental models of brain trauma.
Curr Opin Neurol 1999;12:715–721.
7. Lowenstein D, Thomas M, Smith D, et al. Selective vulnerability of dentate hilar neurons following traumatic brain
injury: a potential mechanistic link between head trauma and
disorders of the hippocampus. J Neurosci 1992;12:
4846 – 4853.
8. Sloviter R. “Epileptic” brain damage in rats induced by sustained electrical stimulation of the perforant path. I. Acute electrophysiological and light microscopic studies. Brain Res Bull
1983;10:675– 697.
9. Margerison J, Corsellis J. Epilepsy and the temporal lobes.
Brain 1966;89:499 –530.
10. Toth Z, Hollrigel G, Gorcs T, et al. Instantaneous pertubation of interneuronal networks by a pressure wave-transient
delivered to the neocortex. J Neurosci 1997;17:8106 – 8117.
11. Santhakumar V, Bender R, Frotscher M, et al. Granule cell
hyperexcitability in the early post-traumatic rat dentate gyrus:
the ‘irritable mossy cell’ hypothesis. J Physiol (Lond) 2000;524:
117–134.
12. Coulter D, Rafiq A, Shumate M, et al. Brain injury-induced
enhanced limbic epileptogenesis: anatomical and physiological
parallels to an animal model of temporal lobe epilepsy. Epilepsy
Res 1996;26:81–91.
13. Santhakumar V, Ratzliff A, Jeng J, et al. Long-term hyperexcitability in the hippocampus after experimental head trauma.
Ann Neurol 2001;708 –717.
14. Prince D, Jacobs K, Salin P, et al. Chronic focal neocortical
epileptogenesis: does disinhibition play a role? Can J Physiol
Pharmacol 1997;75:500 –507.
Imaging Stroke Recovery:
Lessons from Prozac
The past decade has seen selected but highly significant
advances in the prevention and treatment of stroke, although stroke remains the most common cause of neurological dysfunction. The primary interest of stroke
victims, along with secondary prevention, is the opportunity for recovery of function. Fortunately, most
stroke symptoms do improve, although to varying degrees, and with variable rates. Basic research on stroke
recovery has shown that the recovery process can be
modulated through pharmacological and environmental factors. The extent to which these principles can be
successfully applied to human stroke victims could
have a major impact on the overall morbidity of stroke.
The past decade has also seen a rapid expansion of
opportunities to examine human brain function using
noninvasive imaging, primarily with magnetic resonance. Functional magnetic resonance imaging (fMRI)
has not only reduced the cost and invasiveness of functional neuroimaging, but also has increased its sensitivity such that task-specific signal changes can typically
© 2001 Wiley-Liss, Inc.
697
be reliably observed in individual subjects. One of the
major potential clinical applications of fMRI is to gain
a better understanding of the mechanisms of functional
recovery in response to brain injury, with the hopes of
using this information to develop strategies to enhance
this process.
In the present study, Pariente and colleagues1 demonstrate that a single dose of fluoxetine increased motor performance and also produced increased fMRI activation in the ipsilesional motor cortex. While these
observations are consistent with a causal role of fluoxetine on motor cortex resulting in improved performance, it also remains possible that motor activation
increased in response to improved performance
through some other mechanism, such as attention. Attentional effects have been previously shown to alter
fMRI activation in motor areas.2 The absence of
fluoxetine-correlated changes in brain regions thought
to subserve attention does not provide much evidence
against this alternative, as the statistical approaches currently used for fMRI analysis do not well address the
issue of false-negative activation. It is also unfortunate
that motor performance and motor cortex activation
could not be assessed using identical tasks. This would
have allowed task performance to be included as a covariate in the image analysis.
The present study illustrates the challenges in determining causality based on associations between performance effects and fMRI activation. Existing data indicate that activation may increase with performance in
certain regions, at least over certain ranges, while in
other regions activation may decrease with increasing
performance. The latter response has been observed in
dorsolateral prefrontal cortex during pharmacological
modulation of working memory performance.3,4 Another factor related to performance is task difficulty,
which is a particular concern when activation in patients with deficits is compared with controls, even if
subjects in both groups perform equally.
Perhaps more convincing neuroimaging evidence of
therapeutic causality might be the recruitment of brain
regions not previously activated by the task, for example, the recruitment of homolateral brain regions or a
spatial shift in the activation centroid. Such effects
have also been observed during stroke recovery. A fundamental question concerning the specific application
of fMRI to stroke recovery is the extent to which the
normal coupling between neural function and cerebral
blood flow (CBF) is preserved, as well as the extent to
which changes in CBF with functional activation reflect neural versus vascular reorganization. In the
present study, the potential influence of this uncer-
698
Annals of Neurology
Vol 50
No 6
December 2001
tainty was minimized because fMRI was used to characterize changes in cortex in response to small subcortical infarcts, which presumably do not significantly
affect cortical CBF. Furthermore, the authors also
studied a passive control task that did not show a fluoxetine effect.
At the very least, fMRI studies such as these may be
viewed as hypothesis generating. In the present case,
the hypothesis that fluoxetine effects on motor cortex
are mediated by serotonin can be tested through further manipulations of this system. Neuroimaging
methods that measure resting CBF or metabolism
might also contribute to the characterization of pharmacological interventions by demonstrating their effects on regional activity independent of task performance. For example, an increase in resting metabolism
in motor cortex in response to fluoxetine would further
support a causal role for this therapy in motor performance. In the case of novel activations in response to
intervention or recovery, their role in task performance
can be tested using methods that inhibit the activity,
such as pharmacological manipulation or focal transcranial magnetic stimulation. At the very best, studies
such as these illustrate how functional neuroimaging
performed with careful attention to experimental design and data analysis can elucidate the mechanisms
and modulators of functional recovery in the human
brain. With improved understanding of the relationships between task difficulty, task performance, and
brain activation, such data should provide insights that
will ultimately result in opportunities to improve patients’ functional outcome from stroke and other types
of brain injury.
John A. Detre, MD
Department of Neurology
University of Pennsylvania
Philadelphia, Pennsylvania
References
1. Pariente J, Loubinoux I, Carel C, et al. Fluoxetine modulates
motor performance and cerebral activation of patients recovering
from stroke. Ann Neurol 2001;718 –729.
2. Baker JT, Donoghue JP, Sanes JN. Gaze direction modulates
finger movement activation patterns in human cerebral cortex.
J Neurosci 1999;19:10044 –10052.
3. Mehta MA, Owen AM, Sahakian BJ, et al. Methylphenidate enhances working memory by modulating discrete frontal and parietal lobe regions in the human brain. J Neurosci 2000;20:
RC65.
4. Furey ML, Pietrini P, Haxby JV. Cholinergic enhancement and
increased selectivity of perceptual processing during working
memory. Science 2000;290:2315–2319.
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