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# 2002 Oxford University Press
Human Molecular Genetics, 2002, Vol. 11, No. 11
1343–1350
Molecular pathophysiology in Tay–Sachs and
Sandhoff diseases as revealed by gene expression
profiling
Rachel Myerowitz1,2, Douglas Lawson1, Hiroki Mizukami2, Yide Mi2, Cynthia J. Tifft2,3 and
Richard L. Proia2,*
1
Department of Biology, St Mary’s College of Maryland, St Mary’s City, MD 20686, USA, 2Genetics of Development
and Disease Branch, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health,
Bethesda, MD 20892, USA and 3Department of Medical Genetics, Children’s National Medical Center, Washington,
DC 20010, USA
Received February 7, 2002; Revised and Accepted March 19, 2002
Tay–Sachs and Sandhoff diseases are lysosomal storage disorders characterized by the absence of
b-hexosaminidase activity and the accumulation of GM2 ganglioside in neurons. In each disorder, a virtually
identical course of neurodegeneration begins in infancy and leads to demise generally by 4–6 years of age.
Through serial analysis of gene expression (SAGE), we determined gene expression profiles in cerebral
cortex from a Tay–Sachs patient, a Sandhoff disease patient and a pediatric control. Examination of genes
that showed altered expression in both patients revealed molecular details of the pathophysiology of the
disorders relating to neuronal dysfunction and loss. A large fraction of the elevated genes in the patients
could be attributed to activated macrophages/microglia and astrocytes, and included class II histocompatability antigens, the pro-inflammatory cytokine osteopontin, complement components, proteinases and
inhibitors, galectins, osteonectin/SPARC, and prostaglandin D2 synthase. The results are consistent with a
model of neurodegeneration that includes inflammation as a factor leading to the precipitous loss of neurons
in individuals with these disorders.
INTRODUCTION
Lysosomal storage diseases are a group of inherited disorders
that result from defective acid hydrolase function. Tay–Sachs
and Sandhoff diseases are examples of such disorders, and
represent members of a subcategory called the GM2 gangliosidoses that are so named because GM2 ganglioside
accumulates in cells owing to its impaired degradation
(reviewed in 1). The absence of b-hexosaminidase A in Tay–
Sachs disease and of b-hexosaminidase A and B in Sandhoff
disease are the primary enzyme deficiencies. Since only
b-hexosaminidase A is able to degrade GM2 ganglioside, the
substrate accumulates similarly in each disease. Affected
individuals with either disease exhibit a virtually identical
clinical course of neurodegeneration leading to death in early
childhood. Apoptosis of neurons is demonstrable in patient
samples and in mouse models (2,3). While it is clear that a
primary insult to neurons is the accumulation of ganglioside
substrates, the exact molecular mechanisms that translate the
primary insult into neuronal cell death remain to be determined.
One alluring approach to gain insight into pathophysiology is
to generate gene expression profiles of the central nervous
system (CNS) in patients affected with these disorders (4).
Such profiles would reveal how gene expression in the diseased
state differed from that of the normal. Subsequent scrutiny of
those genes exhibiting altered expression could be a wellspring
for hypotheses regarding the pathways leading to the observed
neurodegeneration. Advances, including serial analysis of gene
expression (SAGE) (5) and microarray analysis (6), have made
the undertaking of such studies feasible and are being used in
the study of neurodegenerative diseases (4). In an earlier study
on a mouse model of Sandhoff disease, we applied microarray
analysis to monitor changes in gene expression. An extensive
upregulation of genes related to an inflammatory process
dominated by activated microglia was found in the disease
model (3). Moreover, activation of microglia was found to
precede massive neuronal death, suggesting that an inflammatory process may participate in neurodegeneration.
In the present study, we have utilized the SAGE methodology
in which 10 base tags obtained from the 30 end of each gene
*To whom correspondence should be addressed at: Building 10, Room 9N-314, National Institutes of Health, 10 Center DR MSC 1821, Bethesda,
MD 20892-1821, USA. Tel: þ 1 301 496 4391; Fax: þ 1 301 496 0839; Email: [email protected]
1344
Human Molecular Genetics, 2002, Vol. 11, No. 11
transcript are concatenated and sequenced to develop gene
expression profiles for the GM2 gangliosidoses. This method,
in principle, can provide both a qualitative and a quantitative
profile of all the genes expressed in the tissues. Genes of
known function, unknown function (expressed sequence tags,
ESTs) and sequences yet to be identified as protein coding
(novel genes) are included in SAGE analysis. The data thus
generated can serve as a reference of the expressed genes in
these diseased states. The gene expression profiles that we have
obtained provide molecular details of the pathophysiology and
demonstrate an intense inflammatory process that may be
directly involved in the neurodegenerative process.
RESULTS
Generation of SAGE data
SAGE libraries were constructed from mRNAs isolated from
cerebral cortex tissue samples derived from a normal child, a
child with Tay–Sachs disease and a child with Sandhoff
disease. A total of 107 976 tags were generated; 34 137 from
normal, 38 940 from Tay–Sachs and 34 899 from Sandhoff
tissues (Table 1). Sequence analysis showed that between 39%
and 47% of the tags in each of the libraries were unique and
corresponded to known genes, ESTs or potentially novel
transcripts. Disregard for sequence tags that matched to more
than one gene in each SAGE library allowed us to discern that
at most 9231 genes were represented in the pediatric control,
11 679 in the Tay–Sachs and 11 111 in the Sandhoff. While the
majority of these corresponded to a sequence in GenBank,
approximately 30% in either the Tay–Sachs or Sandhoff
libraries did not match any GenBank entry and constitute a
cadre of potentially novel transcripts awaiting characterization.
Comparison of gene expression profiles in normal and GM2
gangliosidosis cerebral cortex tissues
Results summarized in Table 2 show that of the 11 679 genes
and novel tags expressed in the Tay–Sachs SAGE library, 631
(5.4%) showed differential expression at a statistically
significant level (P < 0.05). About an equivalent number were
elevated in expression as were depressed, and 10% of these
showed a 10-fold or greater differential expression when
compared with the pediatric normal. Of the 16 transcripts in the
Tay–Sachs library displaying the highest fold elevation of
expression (between 30 and 100), 9 belong to the novel tag
category. Similar results were obtained with the Sandhoff
library: 4.9% of the expressed genes and novel tags showed
significant differential expression, with an approximately equal
number elevated as depressed. To increase the probability of
focusing on genes related to the pathophysiology of the GM2
gangliosidoses rather than individual variation, we confined our
scrutiny to those genes whose expression was altered in both
the Tay–Sachs and Sandhoff disease patients relative to the
normal individual. Of the gene tags displaying differential
expression, 111 elevated and 232 depressed were in common to
both patients. This represents more than 50% of genes
displaying differential expression in each of the disease
libraries. These gene expression profiles can be found in the
Supplementary Material. Those genes with elevated expression
in the patients that could be functionally classified are listed
in Table 3. Assignation of genes to a particular functional
category is indicated by its color code. A category containing
the largest fraction of the overexpressed genes included those
associated with inflammation and injury responses. Many of
these genes were associated with activated macrophages/
microglia and astrocytes, the cell types that mediate inflammation and injury responses in the CNS. Genes that have been
reported to be expressed by activated macrophages include
cartilage gp-39 (7), galectin 3 (8), glycoprotein nmb (9,10),
HLA-DR (7) and the complement component 1q b chain
(11,12) (Table 3). A tag corresponding to CD68 (13), a classic
macrophage marker, was also elevated in both disease libraries
(Tay–Sachs, 13; Sandhoff, 4; normal, 0). The expression of two
genes characteristic of activated astrocytes – glial fibrillary
acidic protein (GFAP) and vimentin (14) – were both very
highly elevated. Other genes elevated in both disease libraries
and generally associated with astrocytes included aB-crystallin
(15), apoliprotein E (15,16), calcyclin (17) and the gap junction
protein, connexin 43 (14). Elevated genes related to inflammatory responses and reported to be expressed by activated glia
were prostoglandin D2 synthase (18), clusterin (12), cathepsin
B (7) and the proinflammatory cytokine, osteopontin (19).
Osteonectin (SPARC), a gene found to be upregulated in
astrocytes after neural damage was also elevated in both
patients (20,21).
In the category related to stress/apoptosis, several heat-shock
proteins and the ubiquitin-conjugating enzyme E2H were
elevated. Also of potential interest was the elevation of deathassociated protein 6 (DAXX), encoding a protein that
associates with the Fas receptor to mediate activation of Jun
N-terminal kinase (JNK) and programmed cell death induced
by Fas (22).
Other functional categories included genes involved in
protein synthesis, cytoskeleton, signaling/gene expression and
metabolism/housekeeping. A neuron-specific gene significantly
elevated in both patients was growth-associated protein 43
Table 2. Summary of differentially expressed genes in Tay–Sachs and Sandhoff
diseases compared with pediatric normala
Table 1. Summary of SAGE analysis
Tissue sample
Total tags
Distinct tags
Genesa
Novel tags
Normal
Tay–Sachs
Sandhoff
34 137
38 940
34 899
13 290
17 290
16 419
5731
7312
7249
3500
4367
3862
Tissue sample
Known genes
ESTs
Novel tags
Elevatedb
Depressedb
Tay–Sachs
Sandhoff
516
437
39
42
84
50
314
252
317
273
a
P < 0.05.
Does not include 8 genes in Tay–Sachs disease and 4 genes in Sandhoff disease
with multiple tags that display both elevation and depression relative to normal.
b
a
As defined by matches to GenBank entries.
Human Molecular Genetics, 2002, Vol. 11, No. 11
1345
Table 3. Classified genes elevated in both Tay–Sachs and Sandhoff diseases
(GAP43), a phosphoprotein expressed in the elongating
terminals of neurites (23). However, GAP43 appeared to be
unique as a gene with specific neuronal expression that was
elevated in the patients’ libraries. A number of tags with
specific neuron expression appeared to be significantly
depressed in the patients’ gene profiles (Table 2 in Supplementary Material). These included neuronal-specific enolase
(NSE, enolase 2) (24), b-synuclein (25), neuronal pentraxin
receptor (26), metabotropic glutamate receptor 3 (27), neurogranin (28), complexin 1 (29) and hippocalcin (30). The myelin
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Human Molecular Genetics, 2002, Vol. 11, No. 11
Figure 1. Histologic analysis of neurons, microglia and astrocytes. Sections of cerebral cortex from control (A, D, G, J), the Tay–Sachs patient (B, E, H, K) and
the Sandhoff patient (C, F, I, L) were immunostained with antibody to neuronal-specific enolase (NSE) to detect neurons, glial fibrillary acidic protein (GFAP) to
detect astrocytes and CD68 to detect microglia/macrophages. Staining with antibody to phosphotyrosine was used to detect activated microglia/macrophages. Note
the low density of neurons and the enlarged astrocytes and microglia/macrophages in the patients’ sections. Bar ¼ 50 mm.
Figure 2. Confirmation of SAGE by immunostaining of cerebral cortex sections. Sections of cerebral cortex from control (A, D, G, J, M), the Tay–Sachs patient (B,
E, H, K, N) and the Sandhoff patient (C, F, I, L, O) were immunostained with antibody to cathepsin B, aB-crystallin, ferritin, osteopontin and GAP43.
Bars ¼ 50 mm.
Human Molecular Genetics, 2002, Vol. 11, No. 11
basic protein gene, expressed by oligodendrocytes, was also
significantly depressed in the patients’ SAGE libraries.
Confirmation of SAGE data
To confirm the results of our SAGE library data, we checked
the expression of several genes through immunohistochemical
staining of paraffin-embedded sections of cortex (Fig. 1).
Antibody to NSE, a gene found to have decreased expression in
the Tay–Sachs and Sandhoff SAGE libraries, demonstrated
less intense staining in the patients’ sections compared with
the control (Fig. 1A–C). The patients’ sections appeared to
contain fewer neurons, and those that were present had an
altered, swollen morphology. Immunostaining for glial fibrillary acidic protein (GFAP) showed astrocytes that were clearly
enlarged in the patients’ sections, characteristic of an activated
state (31) (Fig. 1D–F). CD68 immunostaining indicated a
significantly elevated number of microglia in the patients’
sections (P < 0.001) (Fig. 1G–I). The patients’ microglia
were amoeboid with minimal processes, a morphology
associated with their activation (32). Their activation was
confirmed by intense staining with antibody to phosphotyrosine
(Fig. 1J–L) (3).
The protein products of several other genes with altered
expression were assessed by immunostaining. Cathepsin B
expression was elevated in the patients’ sections, and appeared
to be expressed by the amoeboid microglia (Fig. 2A–C).
Staining with aB-crystallin was more intense in the patients’
sections than in the control, consistent with the SAGE results,
and appeared to be localized to the enlarged astrocytes and
neurons (Fig. 2D–F). Ferritin immunostaining was also
enhanced in patients’ samples, as predicted from the elevated
expression of ferritin heavy- and light-chain genes (Table 3),
and appeared to be localized to amoeboid microglia as well as
other cell types (Fig. 2G–I). Osteopontin was found to be
highly overexpressed in the patients’ sections (Fig. 2J–L).
Double immunostaining revealed that the majority of osteopontin expression was confined to microglia (not shown).
GAP43, a neuron-specific gene, was more intensely expressed
in patients’ sections and appeared in a punctuate pattern
(Fig. 2M–O).
DISCUSSION
Both Tay–Sachs and Sandhoff diseases are characterized by a
deficiency of b-hexosaminidases that results in the accumulation of GM2 ganglioside in lysosomes. As a consequence of
a similar biochemical defect, the two diseases are virtually
indistinguishable in their neurodegenerative courses.
Although much is known about the enzymology and
molecular genetics of these diseases (1), there is considerably
less information regarding how the primary cellular insult –
lipid storage – leads to massive neuronal cell death and what
cellular and molecular mechanisms participate in this process.
We hypothesized that gene expression profiles of cerebral
tissue from patients with the GM2 gangliosidoses could
provide clues that would prove valuable in elucidating the
pathological mechanisms operating in these diseases. Toward
that goal, we employed the SAGE methodology to obtain
global gene expression profiles for cerebral cortex tissue from
1347
a Tay–Sachs and a Sandhoff disease patient. We confined our
attention to those genes with significantly elevated or
decreased expression in both the Tay–Sachs and Sandhoff
disease patients to focus our attention on genes mostly likely
to be relevant to the neurodegenerative process rather than
individual variation.
Decreased expression of neuron-specific genes was characteristic of both patient libraries. Immunostaining with NSE, a
gene specifically depressed in the patient libraries, confirmed a
decreased density of neurons in the disease samples. These
findings underscore the neuronal loss that occurs during the
disease process. Apoptosis of neurons has been demonstrated
in both Tay–Sachs and Sandhoff disease patients and in mouse
models, and is thought to be the cause of the precipitous
neuronal loss (2,3). Of potential relevance to the neuronal cell
death in the disorders is the elevated expression of cathepsin B,
a lysosomal protease that has been shown to be released by
activated microglia and to directly cause neuronal apoptosis
(33). In Alzheimer’s disease, high levels of cathepsin B are in
senile plaques (34). Prostoglandin D2 synthase, elevated in both
patients’ SAGE libraries, has also been demonstrated to
directly induce apoptosis in neuronal cells (35).
The elevation of GAP43 expression in the patients may be
indicative of dysfunction or damage to neurons during the
pathogenesis of disorder. GAP43 is a phosphoprotein that
promotes neurite formation and is expressed during axonal
growth and regeneration (23,36). A characteristic feature in the
GM2 gangliosidoses is the presence of ‘meganeurites’ – areas
of swollen neuronal processes with abnormally high densities
of neurites (37). An elevation of GAP43 expression provides
a molecular explanation for this enhanced neuritogenesis, a
process that has been suggested to cause neuronal dysfunction
in the GM2 gangliosidoses (37). Abnormal neurite sprouting
attributed to GAP43 expression has also been found in
Alzheimer disease neurons (38). In addition, increased
expression of GAP43 has been observed in neurons in
amyotropic lateral sclerosis patients (39).
Inflammation is believed to be a central factor causing
neuronal cell death in a number of neurodegenerative disorders,
including Alzheimer disease, Parkinson disease, amyotropic
lateral sclerosis and HIV dementia (40,41). We previously
provided evidence that inflammation contributes to the
neurodegeneration in the GM2 gangliosidoses using a mouse
model of Sandhoff disease (3). Through cDNA microarray
analysis, we found that a large fraction of overexpressed genes
in the CNS from the disease-model mice were related to an
inflammatory process. Our results with SAGE show a
remarkably similar profile of increased expression of inflammatory genes. Elevated genes in common between the mouse
and human gene profiles included class II histocompatability
antigens, the pro-inflammatory cytokine osteopontin, complement components, proteinases and inhibitors, galectin-3, and
prostaglandin D2 synthase. Both activated macrophages/
microglia and activated astrocytes are known mediate inflammatory responses in the CNS (40,42). In the SAGE study, the
gene profiles indicated that both cell types were activated in the
patients.
In addition to mediating inflammation, astrocytes along with
microglia respond to neuronal damage by a process of reactive
gliosis where the cells proliferate and migrate to sites of
1348
Human Molecular Genetics, 2002, Vol. 11, No. 11
Figure 3. A proposed model for the pathophysiology of the GM2 gangliosidoses.
damage to preserve tissue integrity (14,32). The elevated
expression of genes concerned with protein synthesis and the
cytoskeleton may be associated with the increased proliferative
and migratory activity of the glia. The heightened expression
gene encoding osteonectin (SPARC), an extracellular matrix
protein involved in tissue remodeling, is likely related to an
injury response in the patients (20,43).
The results obtained by SAGE allow new detail to be added
to our previous understanding of the pathophysiology of the
GM2 gangliosidoses. A proposed model is shown in Fig. 3.
Neuronal storage of ganglioside, due to the b-hexosaminidase
deficiency, is the primary insult in these diseases, and leads to
neuronal dysfunction and damage. The molecular events
involved in these early processes are still poorly understood.
The overexpression of GAP43 and the formation of ectopic
dendrites may be one of these events (37), but has not yet been
determined experimentally. Both microglia and astrocytes
become activated by sensing neuronal damage (14,32) or
through their own accumulation of glycolipid, which may
activate cells directly (44). The activated microglia and
astrocytes express inflammatory proteins, including cytokines,
proteases and complement proteins, and monocytes are
recruited from the blood (45). The inflammatory milieu in
the CNS causes an additional insult to the already compromised neurons, leading to a phase of rapid neuronal apoptosis.
Demyelination, prominent in the disorders, occurs as a result of
the loss of axons (46). The severe neuronal cell death also
triggers reactive gliosis and may induce the expression of genes
related to tissue remodeling such as osteonectin/SPARC.
A number of genes elevated in GM2 gangliosidosis patients
have been described as elevated in Alzheimer disease and other
neurodegenerative disorders (19,47–51). The molecular similarities between the disorders of diverse etiology suggest
common mechanisms for neurodegeneration, regardless of
the nature of the primary insult. In many of these disorders,
inflammation has been implicated as a central mechanism
leading to neurodegeneration.
In addition to establishing molecular details of the pathophysiology of neurodegeneration in the GM2 gangliosidoses,
the gene profiles can provide potential markers for monitoring
the clinical progression of the disorders. The ability to
assess the neurodegenerative course would be critical for the
development of therapies for these disorders.
MATERIALS AND METHODS
Tissue samples
Samples of cerebral cortex from a 2-year-old male suffering
from Sandhoff disease (#2081) (frozen < 24 hours postmortem) and from a normal 9-month-old male who died in
an accident (#2844) (frozen 20 hours postmortem) were
provided by the University of Miami Brain and Tissue Bank
for Developmental Disorders. This represents a joint effort of
the University of Miami and the University of Maryland
Brain and Tissue Banks through NICHD Contract N01-HD8-3284. The Tay–Sachs cerebral cortex sample was frozen
1.5 hours following the death of a 32-month-old male and
was obtained from the Children’s National Medical Center,
Washington, DC. A recent study has indicated that there was
little degradation in human brain RNA up to 96 hours
postmortem (52).
RNA isolation
Total cellular RNA from 5 g of each cerebral cortex sample was
isolated using Trizol reagent (Gibco BRL). Poly(A) RNA was
then purified from total RNA using the Oligotex (Quiagen) spin
column protocol.
Construction and sequencing of SAGE libraries
The SAGE method was performed essentially as previously
described (5) and is accessible on the SAGE Home Page
Human Molecular Genetics, 2002, Vol. 11, No. 11
(www.sagenet.org/). Briefly, 5 mm of poly(A) RNA isolated
from the Tay–Sachs and Sandhoff cerebral cortex samples
was converted to double-stranded DNA using a cDNA
synthesis kit (Gibco BRL) according to the protocol described
by the manufacturer, except that a poly(A) biotinylated
primer, 50 -T18 biotin, was used in the synthesis. The cDNA
was cleaved with NlaIII (anchoring enzyme) and the resulting
30 -terminal cDNA fragments were bound to streptavidincoated beads (Dynal). These bound fragments were divided
into two pools. Each was ligated to one of two types of
linkers that contained a BsmFI (New England Biolabs)
restriction site. The ligations were followed by digestion with
BsmF1 (tagging enzyme) to release 14 bp sequence tags from
the streptavidin-bead-bound cDNAs. Following fill-in of the
SAGE tag overhangs with Klenow, the two pools of tags were
ligated to each other to form ditags still bound to the linkers.
The ditags were amplified via PCR, and the products were
isolated from a 12% polyacrylamide gel and treated with
NlaIII to produce 24 bp ditags freed of linkers. Following
isolation via a 12% acrylamide gel, the 24 bp ditags were
concatenated using T4 ligase (Gibco BRL) and the concatenates were purified on an 8% acrylamide gel. Concatenates migrating on the gel in the 400–800 bp range were
isolated and ligated into the SphI site of pZero vector
(Invitrogen). Transfection of one-sixth of this ligation mixture
into ElectroMAXDH10B (Gibco BRL) via electroporation
yielded about 500 colonies. The colonies were screened for
inserts via PCR utilizing M13F and M13R as primers. Several
hundred colonies displaying inserts greater than 400 bases in
size were selected for sequencing via the ABI Prism Big Dye
Terminator Cycle Sequencing Ready Reaction Kit (PE
Biosystems), with 7 21M13 serving as the primer, and were
analyzed on an ABI Prism 377 automated sequencer. This
analysis was done to assess the fitness of the libraries. Highthroughput sequencing was subsequently performed on
minipreps of the pZero plasmids containing ditag concatenated inserts by the NIH Intramural Sequencing Center
(NISC). The pediatric normal SAGE library was constructed
using the I-SAGE Kit (Invitrogen).
Data analysis and comparison of SAGE libraries
Tag sequences and their count in the libraries were organized
and tallied via eSAGE software developed by Margulies and
Innis (52). In order to eliminate the potential PCR bias in
amplification of ditags during the SAGE protocol, we counted
any ditag that was found more than one time in any given
library only once for that library. Library comparisons were
performed using eSAGE 2000 software. This software
compared the relative abundance of each tag between a disease
and the control library and produced a P-value for each
comparison. Only tags that had P < 0.05 were considered
statistically significant. Tags that matched to more than one
gene were considered ambiguous and excluded from the
analysis. Matching tags to specific genes in GenBank was
achieved by comparing tags for each library with a SAGE tag
to a Unigene map that had been downloaded from the NCBI
SAGE website. The classification of function of individual
genes was based in part on information obtained from the
1349
OMIM (www.ncbi.nlm.nih.gov/OMIM/) and LocusLink
(www.ncbi.nlm.nih.gov/LocusLink/) databases.
Immunohistochemistry
Antibodies were from the following sources: ferritin, NSE,
CD68 and GFAP from DAKO (Carpinteria, CA), phosphotyrosine from Santa Cruz Biotechnology Inc. (Santa Cruz, CA),
cathepsin B from Oncogene Research Products (Cambridge,
MA), GAP43 from Sigma (St Louis, MO), Osteopontin from
IBL (Fujioka-shi, Gunnma, Japan) and aB-crystallin from
Stressgen (Victoria, British Columbia). Antibodies to CD68
and GFAP were conjugated to peroxidase. For immunostaining,
paraffin sections were deparaffinized and rehydrated; in some
cases, antigen retrieval was accomplished by trypsin and
microwave treatment. Sections were incubated with primary
antibodies overnight at 4 C. When appropriate, the washed
sections were incubated with labeled polymer peroxidaseconjugated mouse and rabbit secondary antibodies (DAKO
Corp., Carpenteria, CA). The peroxidase reaction was
visualized by diaminobenzidine and hydrogen peroxide.
SUPPLEMENTARY MATERIAL
For Supplementary Material, please refer to HMG Online.
ACKNOWLEDGEMENTS
We thank Jennifer Rhode for assistance with statistical analysis,
Aaron Norton for help with data analysis and Mitch Gutshall for
preliminary sequencing. We are grateful to Jeff Touchman and
Gerard Bouffardat at NISC for the high-throughput sequencing
of the SAGE libraries. This research was funded in part by a
grant to R.M. from the Mathew Forbes Romer Foundation, an
Affiliate of National Tay–Sachs and Allied Diseases Association, and the Evan Lee Ungerleider Foundation, National
Tay–Sachs and Allied Diseases Association NY Area.
REFERENCES
1. Gravel, R.A., Kabak, M.M., Proia, R.L., Sandhoff, K., Suzuki, K. and
Suzuki, K. (2001) The GM2 gangliosidoses. In Scriver, C.R., Beaudet, A.L.,
Valle, D., Sly, W.S., Childs, B., Kinzler, K.W. and Vogelstein, B. (eds), The
Metabolic and Molecular Basis of Inherited Disease. McGraw-Hill, New
York, pp. 3827–3876.
2. Huang, J.Q., Trasler, J.M., Igdoura, S., Michaud, J., Hanal, N. and
Gravel, R.A. (1997) Apoptotic cell death in mouse models of GM2
gangliosidosis and observations on human Tay–Sachs and Sandhoff
diseases. Hum. Mol. Genet., 6, 1879–1885.
3. Wada, R., Tifft, C.J. and Proia, R.L. (2000) Microglial activation
precedes acute neurodegeneration in Sandhoff disease and is suppressed
by bone marrow transplantation. Proc. Natl Acad. Sci. USA, 97,
10954–10959.
4. Colantuoni, C., Purcell, A.E., Bouton, C.M. and Pevsner, J. (2000) High
throughput analysis of gene expression in the human brain. J. Neurosci.
Res., 59, 1–10.
5. Velculescu, V.E., Zhang, L., Vogelstein, B. and Kinzler, K.W. (1995) Serial
analysis of gene expression. Science, 270, 484–487.
6. Schena, M., Shalon, D., Davis, R.W. and Brown, P.O. (1995) Quantitative
monitoring of gene expression patterns with a complementary DNA
microarray. Science, 270, 467–470.
1350
Human Molecular Genetics, 2002, Vol. 11, No. 11
7. Suzuki, T., Hashimoto, S., Toyoda, N., Nagai, S., Yamazaki, N.,
Dong, H.Y., Sakai, J., Yamashita, T., Nukiwa, T. and Matsushima, K.
(2000) Comprehensive gene expression profile of LPS-stimulated human
monocytes by SAGE. Blood, 96, 2584–2591.
8. Pesheva, P., Urschel, S., Frei, K. and Probstmeier, R. (1998) Murine
microglial cells express functionally active galectin-3 in vitro. J. Neurosci.
Res., 51, 49–57.
9. Hashimoto, S., Suzuki, T., Dong, H.Y., Yamazaki, N. and Matsushima, K.
(1999) Serial analysis of gene expression in human monocytes and
macrophages. Blood, 94, 837–844.
10. Moran, M.T., Schofield, J.P., Hayman, A.R., Shi, G.P., Young, E. and
Cox, T.M. (2000) Pathologic gene expression in Gaucher disease:
up-regulation of cysteine proteinases including osteoclastic cathepsin K.
Blood, 96, 1969–1978.
11. Haga, S., Aizawa, T., Ishii, T. and Ikeda, K. (1996) Complement gene
expression in mouse microglia and astrocytes in culture: comparisons with
mouse peritoneal macrophages. Neurosci. Lett., 216, 191–194.
12. Van Beek, J., Chan, P., Bernaudin, M., Petit, E., MacKenzie, E.T. and
Fontaine, M. (2000) Glial responses, clusterin, and complement in
permanent focal cerebral ischemia in the mouse. Glia, 31, 39–50.
13. Holness, C.L. and Simmons, D.L. (1993) Molecular cloning of CD68, a
human macrophage marker related to lysosomal glycoproteins. Blood, 81,
1607–1613.
14. Ridet, J.L., Malhotra, S.K., Privat, A. and Gage, F.H. (1997) Reactive
astrocytes: cellular and molecular cues to biological function. Trends
Neurosci., 20, 570–577.
15. Eddleston, M. and Mucke, L. (1993) Molecular profile of reactive
astrocytes – implications for their role in neurologic disease. Neuroscience,
54, 15–36.
16. Baskin, F., Smith, G.M., Fosmire, J.A. and Rosenberg, R.N. (1997) Altered
apolipoprotein E secretion in cytokine treated human astrocyte cultures.
J. Neurol. Sci., 148, 15–18.
17. Yamashita, N., Kosaka, K., Ilg, E.C., Schafer, B.W., Heizmann, C.W. and
Kosaka, T. (1997) Selective association of S100A6 (calcyclin)immunoreactive astrocytes with the tangential migration pathway of
subventricular zone cells in the rat. Brain Res., 778, 388–392.
18. Ishizaka, M., Ohe, Y., Senbongi, T., Wakabayashi, K. and Ishikawa, K.
(2001) Inflammatory stimuli increase prostaglandin D synthase levels in
cerebrospinal fluid of rats. Neuroreport, 12, 1161–1165.
19. Chabas, D., Baranzini, S.E., Mitchell, D., Bernard, C.C., Rittling, S.R.,
Denhardt, D.T., Sobel, R.A., Lock, C., Karpuj, M., Pedotti, R. et al. (2001)
The influence of the proinflammatory cytokine, osteopontin, on
autoimmune demyelinating disease. Science, 294, 1731–1735.
20. McKinnon, P.J. and Margolskee, R.F. (1996) SC1: a marker for astrocytes
in the adult rodent brain is upregulated during reactive astrocytosis. Brain
Res., 709, 27–36.
21. Mendis, D.B., Ivy, G.O. and Brown, I.R. (1996) SC1, a brain extracellular
matrix glycoprotein related to SPARC and follistatin, is expressed by rat
cerebellar astrocytes following injury and during development. Brain Res.,
730, 95–106.
22. Yang, X., Khosravi-Far, R., Chang, H.Y. and Baltimore, D. (1997) Daxx, a
novel Fas-binding protein that activates JNK and apoptosis. Cell, 89,
1067–1076.
23. Benowitz, L.I. and Routtenberg, A. (1997) GAP-43: an intrinsic determinant
of neuronal development and plasticity. Trends Neurosci., 20, 84–91.
24. Schmechel, D., Marangos, P.J., Zis, A.P., Brightman, M. and Goodwin, F.K.
(1978) Brain endolases as specific markers of neuronal and glial cells.
Science, 199, 313–315.
25. Lavedan, C., Leroy, E., Torres, R., Dehejia, A., Dutra, A., Buchholtz, S.,
Nussbaum, R.L. and Polymeropoulos, M.H. (1998) Genomic organization
and expression of the human beta-synuclein gene (SNCB). Genomics, 54,
173–175.
26. Dodds, D.C., Omeis, I.A., Cushman, S.J., Helms, J.A. and Perin, M.S.
(1997) Neuronal pentraxin receptor, a novel putative integral membrane
pentraxin that interacts with neuronal pentraxin 1 and 2 and taipoxinassociated calcium-binding protein 49. J. Biol. Chem., 272,
21488–21494.
27. Makoff, A., Volpe, F., Lelchuk, R., Harrington, K. and Emson, P. (1996)
Molecular characterization and localization of human metabotropic
glutamate receptor type 3. Brain Res. Mol. Brain Res., 40, 55–63.
28. Pak, J.H., Huang, F.L., Li, J., Balschun, D., Reymann, K.G., Chiang, C.,
Westphal, H. and Huang, K.P. (2000) Involvement of neurogranin in the
modulation of calcium/calmodulin-dependent protein kinase II, synaptic
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
plasticity, and spatial learning: a study with knockout mice. Proc. Natl
Acad. Sci. USA, 97, 11232–11237.
McMahon, H.T., Missler, M., Li, C. and Sudhof, T.C. (1995) Complexins:
cytosolic proteins that regulate SNAP receptor function. Cell, 83, 111–119.
Paterlini, M., Revilla, V., Grant, A.L. and Wisden, W. (2000) Expression of
the neuronal calcium sensor protein family in the rat brain. Neuroscience,
99, 205–216.
Mucke, L. and Eddleston, M. (1993) Astrocytes in infectious and
immune-mediated diseases of the central nervous system. FASEB J., 7,
1226–1232.
Streit, W.J., Walter, S.A. and Pennell, N.A. (1999) Reactive microgliosis.
Prog. Neurobiol., 57, 563–581.
Kingham, P.J. and Pocock, J.M. (2001) Microglial secreted cathepsin B
induces neuronal apoptosis. J. Neurochem., 76, 1475–1484.
Cataldo, A.M. and Nixon, R.A. (1990) Enzymatically active lysosomal
proteases are associated with amyloid deposits in Alzheimer brain.
Proc. Natl Acad. Sci. USA, 87, 3861–3865.
Ragolia, L., Palaia, T., Frese, L., Fishbane, S. and Maesaka, J.K. (2001)
Prostaglandin D2 synthase induces apoptosis in PC12 neuronal cells.
Neuroreport, 12, 2623–2628.
Yankner, B.A., Benowitz, L.I., Villa-Komaroff, L. and Neve, R.L. (1990)
Transfection of PC12 cells with the human GAP-43 gene: effects on neurite
outgrowth and regeneration. Brain Res. Mol. Brain Res., 7, 39–44.
Purpura, D.P. and Suzuki, K. (1976) Distortion of neuronal geometry and
formation of aberrant synapses in neuronal storage disease. Brain Res., 116,
1–21.
Masliah, E., Mallory, M., Hansen, L., Alford, M., DeTeresa, R., Terry, R.,
Baudier, J. and Saitoh, T. (1992) Localization of amyloid precursor protein
in GAP43-immunoreactive aberrant sprouting neurites in Alzheimer’s
disease. Brain Res., 574, 312–316.
Ikemoto, A., Hirano, A. and Akiguchi, I. (1999) Increased expression of
growth-associated protein 43 on the surface of the anterior horn cells in
amyotrophic lateral sclerosis. Acta Neuropathol. (Berl.), 98, 367–373.
Gonzalez-Scarano, F. and Baltuch, G. (1999) Microglia as mediators of
inflammatory and degenerative diseases. Annu. Rev. Neurosci., 22,
219–240.
McGeer, P.L. and McGeer, E.G. (1998) Glial cell reactions in
neurodegenerative diseases: pathophysiology and therapeutic interventions.
Alzheimer Dis. Assoc. Disord., 12, S1–S6.
Aschner, M. (1998) Astrocytes as mediators of immune and inflammatory
responses in the CNS. Neurotoxicology, 19, 269–281.
Bradshaw, A.D. and Sage, E.H. (2001) SPARC, a matricellular protein that
functions in cellular differentiation and tissue response to injury. J. Clin.
Invest., 107, 1049–1054.
Pyo, H., Joe, E., Jung, S., Lee, S.H. and Jou, I. (1999) Gangliosides activate
cultured rat brain microglia. J. Biol. Chem., 274, 34584–34589.
Oya, Y., Proia, R.L., Norflus, F., Tifft, C.J., Langaman, C. and Suzuki, K.
(2000) Distribution of enzyme-bearing cells in GM2 gangliosidosis mice:
regionally specific pattern of cellular infiltration following bone marrow
transplantation. Acta Neuropathol. (Berl.), 99, 161–168.
Haberland, C., Brunngraber, E., Witting, L. and Brown, B. (1973) The
white matter in GM2 gangliosidosis. A comparative histopathological and
biochemical study. Acta Neuropathol. (Berl.), 24, 43–55.
Afagh, A., Cummings, B.J., Cribbs, D.H., Cotman, C.W. and Tenner, A.J.
(1996) Localization and cell association of C1q in Alzheimer’s disease
brain. Exp. Neurol., 138, 22–32.
McGeer, P.L., Itagaki, S., Tago, H. and McGeer, E.G. (1987) Reactive
microglia in patients with senile dementia of the Alzheimer type are
positive for the histocompatibility glycoprotein HLA-DR. Neurosci. Lett.,
79, 195–200.
Grewal, R.P., Morgan, T.E. and Finch, C.E. (1999) C1qB and clusterin
mRNA increase in association with neurodegeneration in sporadic
amyotrophic lateral sclerosis. Neurosci. Lett., 271, 65–67.
Torres-Munoz, J.E., Redondo, M., Czeisler, C., Roberts, B., Tacoronte, N.
and Petito, C.K. (2001) Upregulation of glial clusterin in brains of patients
with AIDS. Brain Res., 888, 297–301.
McHattie, S., Wells, G.A., Bee, J. and Edington, N. (1999) Clusterin
in bovine spongiform encephalopathy (BSE). J. Comp. Pathol., 121,
159–171.
Margulies, E.H. and Innis, J.W. (2000) eSAGE: managing and analysing
data generated with serial analysis of gene expression (SAGE).
Bioinformatics, 16, 650–651.