Functional Genomics meets neurodegenerative disorders

Progress in Neurobiology 76 (2005) 169–188 www.elsevier.com/locate/pneurobio

Functional Genomics meets neurodegenerative disorders Part II: Application and data integration Frederic Hoerndli a,1, Della C. David a,b,1, Ju¨rgen Go¨tz a,b,c,* b

a Division of Psychiatry Research, University of Zurich, 8008 Zurich, Switzerland Brain and Mind Research Institute, University of Sydney, 100 Mallett St., Camperdown, NSW 2050, Australia c The Medical Foundation, University of Sydney, Camperdown, Sydney, NSW 2050, Australia

Received 3 March 2005; received in revised form 14 July 2005; accepted 19 July 2005

Abstract The transcriptomic and proteomic techniques presented in part I (Functional Genomics meets neurodegenerative disorders. Part I: Transcriptomic and proteomic technology) of this back-to-back review have been applied to a range of neurodegenerative disorders, including Huntington’s disease (HD), Prion diseases (PrD), Creutzfeldt–Jakob disease, amyotrophic lateral sclerosis (ALS), Alzheimer’s disease (AD), frontotemporal dementia (FTD) and Parkinson’s disease (PD). Samples have been derived either from human brain and cerebrospinal fluid, tissue culture cells or brains and spinal cord of experimental animal models. With the availability of huge data sets it will firstly be a major challenge to extract meaningful information and secondly, not to obtain contradicting results when data are collected in parallel from the same source of biological specimen using different techniques. Reliability of the data highly depends on proper normalization and validation both of which are discussed together with an outlook on developments that can be anticipated in the future and are expected to fuel the field. The new insight undoubtedly will lead to a redefinition and subdivision of disease entities based on biochemical criteria rather than the clinical presentation. This will have important implications for treatment strategies. # 2005 Elsevier Ltd. All rights reserved. Keywords: Huntington’s disease; Alzheimer’s disease; Biochemical

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Overview of human neurodegenerative disorders . . . . . . . Application of functional genomics to human brain tissue 3.1. Amyotrophic lateral sclerosis . . . . . . . . . . . . . . . . 3.2. Alzheimer’s disease and frontotemporal dementia . 3.3. From Alzheimer’s disease to Parkinson’s disease . . 3.4. From humans to non-human primates . . . . . . . . . .

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DOI of original article: 10.1016/j.pneurobio.2005.07.001 Abbreviations: AD, Alzheimer’s disease; ALS, amyotrophic lateral sclerosis; CSF, cerebrospinal fluid; ESI, electrospray ionization; EST, expressed sequence tags; FTD, frontotemporal dementia; HPLC, high-pressure liquid chromatography; HD, Huntington’s disease; ICAT, isotope coded affinity tag; LC, liquid chromatography; LCM, laser capture microdissection; MALDI, matrix-assisted laser desorption ionization; MS, mass spectrometry; NFT, neurofibrillary tangle; PD, Parkinson’s disease; PrD, prion diseases; qRT-PCR, quantitative reverse transcriptase PCR; SAGE, serial analysis of gene expression; SNP, single nucleotide polymorphisms; SOD, superoxide dismutase; 2D PAGE, two-dimensional polyacrylamide gel electrophoresis * Corresponding author. Tel.: +61 2 9036 0799; fax: +61 2 9351 0652. E-mail address: [email protected] (J. Go¨tz). 1 Shared authorship. 0301-0082/$ – see front matter # 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.pneurobio.2005.07.002

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Application of functional genomics to animal models . . 4.1. Wild-type mice . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Amyotrophic lateral sclerosis . . . . . . . . . . . . . . . 4.3. Alzheimer’s disease and frontotemporal dementia 4.4. Parkinson’s disease . . . . . . . . . . . . . . . . . . . . . . Application of functional genomics to tissue culture . . . 5.1. Amyotrophic lateral sclerosis . . . . . . . . . . . . . . . 5.2. Parkinson’s disease . . . . . . . . . . . . . . . . . . . . . . 5.3. Alzheimer’s disease and frontotemporal dementia Integration of data and future perspectives . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1. Introduction The fields of neuroscience in general and neurodegenerative disorders in particular are particularly well suited for an application of the new transcriptomic and proteomic technologies introduced in part I of this back-to-back review as neuronal signaling is complex and cellular responses are diverse. Also, even minor changes in gene expression in distinct brain regions can have profound consequences for the activity of the brain. Gene and protein expression are not static, and learning and adaptation require a rapid turnover in gene and protein expression in brain as compared to peripheral tissues. This means that the temporal and regional expression pattern of any gene or protein has to be taken into account. However, many key gene products relevant for neuronal function such as receptors for neurotransmitters or kinases are present at levels 100–1000-times lower compared to cellular constituents, such as structural proteins. To gain insight into pathogenic mechanisms, Functional Genomics is increasingly being applied to a range of neurodegenerative disorders. In addition to human cerebrospinal fluid (CSF) and brain tissue, cell culture and animal models have been investigated. Compared to human brain, tissue cells have the advantage of being highly homogeneous. Moreover, they can be easily treated pharmacologically, and offer the distinct possibility of obtaining datasets for different time-points. Experimental animal models that model selected aspects of the disease allow monitoring disease progression with time. Moreover, the animal models described here are generally inbred, whereas humans are not. In any case, the screening approaches inevitably produce huge datasets of often only subtle differences between diseased and normal samples. Therefore, they require an appropriate normalization followed by functional validation. Cluster analysis helps to decipher common schemes. Finally, we will present an outlook and discuss which developments can be anticipated for the future and how they are expected to fuel the field.

2. Overview of human neurodegenerative disorders Huntington’s disease (HD), Prion diseases (PrD), Creutzfeldt–Jakob disease, amyotrophic lateral sclerosis

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(ALS), Alzheimer’s disease (AD), frontotemporal dementia (FTD) and Parkinson’s disease (PD) are among the most important human neurodegenerative disorders (Kurosinski et al., 2002). HD is an autosomal dominant neurodegenerative disorder affecting one in 10,000 individuals. It is caused by an insertion of multiple CAG repeats in the huntingtin gene. This results in an amino-terminal polyglutamine (polyQ) expansion of the large protein huntingtin, similar to other polyQ-related neurodegenerative disorders. The polyQ expansion causes a conformational change resulting in protein aggregates in dendrites and nuclei. Selective loss of neurons is observed mostly in the striatum and cerebral cortex (Trottier et al., 1995). The function of normal huntingtin and the mechanism whereby its mutant form mediates neurodegeneration remain unclear (Young, 2003). The duration of adult-onset HD generally ranges from 15 to 25 years and that of early-onset HD from 10 to 15 years. Clinical features include slowness, clumsiness, rigidity, loss of motor skills, thick speech and drooling. Prion diseases are neurodegenerative disorders that include scrapie in sheep, bovine spongiform encephalopathy (BSE) in cattle, Creutzfeldt–Jakob disease (CJD), Gerstmann–Stra¨ussler–Scheinker disease (GSS), fatal familial insomnia (FFI), Kuru and most recently variant CJD (vCJD) in humans. The central feature of prion diseases is the posttranslational conversion of a normal host-encoded, glycosylphosphatidylinositol (GPI)-anchored glycoprotein, the cellular prion protein (PrPC), to an abnormal isoform, designated PrPSc (Wadsworth et al., 2003; Flechsig and Weissmann, 2004). Creutzfeldt–Jakob disease (CJD) is the most common form of human prion diseases. The majority of cases are sporadic (85%) at a rate of roughly one case per million population per year across the world, between 10 and 15% are familial and the remainder are iatrogenic (Brown et al., 1987; Collinge, 1997). The aetiology of sporadic CJD is unknown, although hypotheses include somatic mutations in the gene encoding the prion protein, or the spontaneous conversion of PrPC into PrPSc as a rare stochastic event. Patients are usually between 50 and 75 years of age. Typical clinical features include a rapidly progressive dementia, myoclonus and a characteristic electroencephalographic pattern (Terzano et al., 1995). Neuropathological examination reveals cortical

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spongiform changes, hence the term spongiform encephalopathy. ALS or Lou Gehrig’s disease is a neurodegenerative disorder with unknown etiology, which is characterized by degeneration of motor neurons in the motor cortex, brain stem and spinal cord. This results in progressive muscle wasting and weakness, and death usually results from respiratory failure within 3–5 years after onset. Ten percent of cases are estimated to be familial and of these, 2–3% are caused by mutations in the gene encoding Cu/Zn superoxide dismutase1 (SOD1), producing a toxic gain of function rather than a loss of (catalytic) function (Rosen et al., 1993). Among others, protein misfolding and aggregation are implicated as a pathogenic mechanism. Some SOD1 mutations result in destabilization of normal dimers of the enzyme and foster aggregation, forming amyloid structures or pores depending on the conditions, not unlike familial amyloid polyneuropathy (Koo et al., 1999; Hough et al., 2004). AD is the most common neurodegenerative disorder worldwide. Histo-pathologically, AD is characterized by extracellular b-amyloid-containing plaques (consisting mainly of aggregated Ab peptide derived by proteolysis of the amyloid precursor protein APP), intracellular neurofibrillary tangles (NFTs), reduced synaptic density and neuronal loss in selected brain areas (Gotz, 2001; Gotz et al., 2004b). The most severe neuropathological changes occur in the hippocampal formation, the association cortices and subcortical structures including the amygdala and the nucleus basalis of Meynert (Arnold et al., 1991). In earlyonset familial AD (FAD), mutations have been identified in three genes: in the APP gene itself, and in the presenilin 1 (PS1) and presenilin 2 (PS2) genes. These mutations account for less than 1% of the total number of AD cases (Delacourte et al., 2002). Mutations in the APP gene are estimated to account for up to 5% of FAD. Twin studies support the notion that 70–80% of the risk to develop sporadic AD is determined by genetic factors (Gatz et al., 1997). NFT are also abundant, in the absence of plaques, in additional neurodegenerative diseases such as Pick’s disease (PiD), progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), argyrophilic grain disease (AgD) and frontotemporal dementia (FTD) including the familial form of frontotemporal dementia with Parkinsonism linked to chromosome 17 (FTDP-17) (Gotz, 2001; Lee et al., 2001). In familial AD, no mutations have been identified in the tau gene. However, in FTDP-17, exonic and intronic mutations were identified in the tau gene that were linked to the disease (Hutton et al., 1998; Poorkaj et al., 1998; Spillantini et al., 1998). In contrast to AD, which is characterized predominantly by memory loss, FTD is mainly initiated with behavioral impairment (e.g., disinhibition, loss of personal and social awareness), followed by affective symptoms, speech disorder and memory problems. Neuroradiological examination reveals an often symmetrical atrophy of the frontal and temporal lobes (Bird et al., 1999; Murrell et al., 1999; van Swieten et al., 1999). In many cases, additional

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degenerative changes are observed in subcortical brain regions, such as the substantia nigra, leading to Parkinsonian symptoms (Wszolek et al., 1992). Next to AD, PD is the second most prevalent neurodegenerative disease and the most common neurodegenerative movement disorder (Olanow and Tatton, 1999). Clinical manifestations of PD include postural instability, bradykinesia, resting tremor and rigidity. Neuropathologically, the disease is characterized by the selective degeneration of dopaminergic neurons in the substantia nigra. One important feature of PD is the presence of cytoplasmic inclusions of fibrillar, misfolded proteins, termed Lewy bodies, in affected brain areas. The major proteinaceous constituent of these is asynuclein. Mutations in at least four genes have been linked to PD. These include a-synuclein (PARK1), the E3 ligase parkin (PARK2), DJ-1 (PARK7) and PTEN-induced kinase 1 (PINK1, also known as PARK6) (Polymeropoulos et al., 1997; Kitada et al., 1998; Bonifati et al., 2003). 95% of PD cases are sporadic and possibly related to altered metal homeostasis and mitochondrial dysfunction (Betarbet et al., 2000; Hardy et al., 2003; Kaur et al., 2003). There is increasing evidence of an overlap of the neurodegenerative disorders outlined above, with a contribution of environmental, epigenetic and genetic factors (Kurosinski et al., 2002). Lewy bodies (LBs), for example, are also abundant in dementia with Lewy bodies (DLB) and the LB variant of AD (Hansen et al., 1990). The availability of a-synuclein-specific antibodies provided a new tool for the identification of LBs in brains from cases of sporadic and familial AD, Down’s syndrome and the parkinsonismdementia complex of Guam. In one study, for example, LBs were detected in the amygdala of more than half of all familial AD cases, and some LBs colocalized with taupositive NFTs (Lippa et al., 1998). In addition to an overlap of the histopathological features, common themes are emerging. For example, oxidative stress in the mitochondria is very likely associated with the pathogenesis of AD, PD, PrD, as well as aging itself (Lopez and Melov, 2002). Mechanisms discussed for the etiology of AD and PD include, in addition to mitochondrial dysfunction, altered metal homeostasis and energy deficits. In general, lowering the burden of protein aggregation, oxidative stress, mitochondrial injury, inflammatory response and heavy metal accumulation in the brain so as to re-establish neurotransmission and block excitotoxicity may prove beneficial in the treatment of several neurodegenerative diseases (Bossy-Wetzel et al., 2004). In the following paragraph application of transcriptomics and proteomics to the disorders mentioned above are presented. As these techniques have only recently been significantly improved and, due to the set-up of Functional Genomics centers, have only lately been made available to researchers with limited technical expertise, for some disease entities there is either no or only very limited data available.

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3. Application of functional genomics to human brain tissue 3.1. Amyotrophic lateral sclerosis Although ALS was described more than 130 years ago, the mechanism underlying the characteristic selective degeneration and death of motor neurons in this disease has remained a mystery. Moreover, there is no effective remedy for this progressive, fatal disorder (Bruijn et al., 2004). Few Functional Genomics studies have been performed with human ALS samples and little is known about global gene expression patterns. At the proteome level, examination of CSF in ALS by routine techniques did not reveal any specific changes (Strong, 2002). In an attempt to obtain a diagnostic pattern, CSF from patients and healthy controls was analyzed by online capillary LC-FTICR MS. Only a small volume of 16 ml CSF was required for one LC experiment and typically around 4000 peptides were detected in one single run. To evaluate the FTICR MS dataset, the peptide patterns of CSF spiked in vitro with the biomarker myoglobin were compared with control CSF. The patterns were clearly separated and the tryptic peptides of the biomarker were successfully selected as characteristic peaks. Therefore, the method was applied to compare mass chromatograms of CSF from 12 ALS patients and 10 matched healthy controls. When samples from ALS patients were compared with healthy controls, no single biomarker could be identified from the list of characteristic peaks. However, four out of five test samples were correctly classified based on their characteristic pattern (Ramstrom et al., 2004). It remains to be seen whether the diagnostic predictability can be further improved. By using the Kinetworks multi-immunoblotting technique to evaluate the expression of 78 protein kinases, 24 protein phosphatases and the phosphorylation states of 31 phosphoproteins in thoracic spinal cord tissue from control subjects and sporadic ALS (SALS) patients, elevated expression and/ or activation of many protein kinases was found in the SALS samples. These included different PKC isoforms and GSK3a/ b, which may augment neuronal death in ALS, and CaMKK, PKBa, Rsk1, S6K and SAPK, which may be a response to neuronal injury that potentially can mitigate cell death (Hu et al., 2003). As the human cellular signaling network includes genes for just around 500 kinases and 150 phosphatases (Manning et al., 2002; Forrest et al., 2003; Wang et al., 2003; Alonso et al., 2004), developing a blot with antibodies directed against all kinases and phosphatases and their activated forms (by using phosphorylation-dependent antibodies) is likely to be a fruitful approach. To determine global gene expression patterns, highdensity gene discovery arrays (GDA human version 1.2) containing 18,400 non-redundant EST cDNAs pooled from different tissue libraries were used to monitor gene expression in lumbar spinal cord from ALS cases compared with controls. Quantitative filter analysis revealed differ-

ential expression of cDNAs normalized to internal standards. These candidates have been further investigated and their expression in spinal cord characterized in a panel of ALS and control subjects. Significant differential expression was obtained for 14 genes, 13 being elevated (up to six-fold) and one decreased (by 80%) in ALS. Among those elevated in ALS were thioredoxin and GFAP. The other differentially regulated transcripts confirmed in the expression studies are involved in antioxidant systems, neuroinflammation, the regulation of motor neuron function, lipid metabolism, protease inhibition and protection against apoptosis (Malaspina et al., 2001). In another study, Affymetrix microarrays were used to compare expression levels of approximately 6800 genes in post-mortem spinal cord gray matter obtained from individuals with ALS as well as normal individuals. Interestingly, it was possible to distinguish familial ALS (FALS) from sporadic ALS (SALS) gene expression profiles. Characterization of the specific genes significantly altered in ALS uncovered a pro-inflammatory terminal state. Moreover, alterations in genes involved in mitochondrial function, oxidative stress, excitotoxicity, apoptosis, cytoskeletal architecture, RNA transcription and translation, proteasomal function, and growth and signaling were found (Dangond et al., 2004). A related microarray study of SALS samples revealed similar categories as genes associated with the ubiquitin-proteasome system, oxidative toxicity, transcription, neuronal differentiation and inflammation were identified (Ishigaki et al., 2002). These findings are interesting in the light of previous knowledge of the disease. The discovery of mutations in Cu/ Zn superoxide dismutase (SOD) immediately prompted hypotheses that toxicity is caused by oxidative damage and aberrant chemistry of the active copper and zinc sites of the misfolded enzyme (Beckman et al., 1993). There is also evidence that mitchondria may be primary targets for SOD1 mutant-mediated damage, based on studies in transgenic animals (Dal Canto and Gurney, 1994; Wong et al., 1995; Kong and Xu, 1998). Despite these findings, the evidence that mitochondria are important targets for damage common to SOD1 mutants with different biochemical characters remains contradictory. Mitochondrial pathology has not been found in other rodent models that develop motor neuron disease from expression of lower levels of the same mutants or in any of the models that develop motor neuron disease from expression of mutants without dismutase activity (Bruijn et al., 2004). The finding that SOD1 mutants impair slow axonal transport months prior to disease onset led to the conclusion that diminished transport correlated with the development of motor neuron disease (Williamson et al., 1998). Furthermore, in ALS tissues, there is strong activation and proliferation of microglia in regions of motor neuron loss (Kawamata et al., 1992; Ince et al., 1996). Based on previous promising studies in mice the anti-inflammatory drugs minocylcine and celecoxib are currently studied in human clinical trials (Bruijn et al., 2004). Despite the

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suggestion that trophic factors may be important in ALS, human trials with neurotrophic factors have been disappointing (Bruijn et al., 2004). Furthermore, in a large European study, which had been designed to determine whether alterations in the vascular endothelial cell growth factor (VEGF) gene may be linked to human ALS, three single nucleotide polymorphisms in the promoter region of the VEGF gene were identified, implicating VEGF as a risk factor in the disease (Lambrechts et al., 2003). In familial ALS, the disease results from an acquired toxicity of mutant SOD1 that affects both neurons and glial cells. The exact nature of this toxicity is uncertain, but in neurons it likely disrupts several basic cellular functions including protein breakdown by the ubiquitin-proteasome system, slow anterograde transport, fast retrograde axonal transport, calcium homeostasis, mitochondrial function and maintenance of the cytoskeletal architecture (Bruijn et al., 2004). The transcriptomic studies described above strengthen the previous findings of a role for oxidative damage and mitochondrial dysfunction, neuroinflammation, the proteasome system, growth control and the cytoskeleton, and further point at genes involved in transcriptional control and neuronal differentiation. 3.2. Alzheimer’s disease and frontotemporal dementia Although the application of transcriptomics and proteomics to AD has only recently been initiated, a relatively large body of data is available for this important disorder (Butterfield et al., 2003). One of the first studies determined the expression profile of human AD brain in an effort to analyze mRNAs sequestered in plaques (Ginsberg et al., 1999). In the light of the current interest in intracellular Ab, it was interesting to find that the plaques sequestered mainly neuronal mRNAs. Switching from plaques to NFT, the gene expression profile was established of individually isolated specific NFT-bearing hippocampal CA1 neurons in AD and compared with non-NFT bearing neurons in control brains (Ginsberg et al., 2000). Here, cDNA microarray analysis was followed by reverse Northern blot analysis of 120 selected mRNAs on custom-made cDNA arrays. Relative to normal CA1 neurons, those harboring NFTs in AD brains showed significant reductions in several classes of mRNAs that are known to encode proteins implicated in AD neuropathology, including phosphatases, kinases (such as the focal adhesion kinase, FAK), cytoskeletal proteins, synaptic proteins, glutamate receptors and dopamine receptors. Interestingly, three times as many down-regulated genes were found compared to upregulated genes. The categories that have been identified are meaningful. For example, hippocampal dopamine receptors have been shown to correlate with memory functions in AD (Kemppainen et al., 2003). Of the differentially expressed genes, FAK is particularly attractive as it is found in the innerperipheral membrane cortex with the ‘‘cortex’’ being defined as the plasma membrane and its associated protein

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components, representing a complex three-dimensional molecular machinery, which is involved in the translation of extracellular cues into morphological changes mediated by intracellular processes. Interestingly, FAK is localized to this ‘‘cortex’’ promoting cytoskeletal fluidity and linking actin to the plasma membrane. Moreover, it is rapidly phosphorylated in primary cortical cultures in response to Ab treatment (Williamson et al., 2002). As in the screen, cathepsin D mRNA was upregulated in NFT-bearing CA1 neurons in AD brains; an immunohistochemical analysis was performed confirming abundant cathepsin D immunoreactivity in the same population of NFT-bearing CA1 neurons. Thus, the profile of mRNAs that are differentially expressed by NFT-bearing CA1 neurons may represent a molecular fingerprint of these neurons (Ginsberg et al., 2000). When the CA1 region of six control and six AD subjects was looked at, in an Affymetrix analysis of over 10,000 genes, up-regulation of oxidative stress-related, apoptosisrelated and pro-inflammatory signaling genes was found. In contrast, genes encoding transcription and neurotrophic factors were down-regulated. The maximal-fold differences were 4.8-fold increases for DAXX, an apoptotic mediator, and 4.8-fold decreases for a brain-enriched form of metallothionein involved in metal metabolism. The data support the hypothesis of widespread transcriptional alterations, misregulation of RNAs involved in metal ion homeostasis, transcription factor signaling deficits, decreases in neurotrophic support and activated apoptotic and neuroinflammatory signaling in the moderately affected hippocampal CA1 region (Colangelo et al., 2002). Again, the categories are meaningful and it is reasonable to follow up on selected candidates. Some of the categories are targeted by current treatment strategies aimed to combat AD (discussed in Gotz et al. (2004b)). In a related study, brain areas with and without an AD pathology were compared in nine controls and six AD cases. One hundred and eighteen of the 7050 sequences on a broadly representative cDNA microarray were differentially expressed in the amygdala and cingulate cortex, two regions affected early on in AD. The 31 up-regulated genes have roles in chronic inflammation, cell adhesion, cell proliferation and protein synthesis, whereas the 87 down-regulated genes have roles in signal transduction, energy metabolism, stress response, synaptic vesicle synthesis and function, calcium binding and the cytoskeleton. These results can be reconciled with several concepts of AD such as the amyloid cascade hypothesis, mitotic failure and oxidative stress (Gotz et al., 2004a). This is also true for our own transcriptomic and proteomic approaches (see below). In addition to the known genes, approximately 10 genes of unknown function were found correlating with the pathology (Loring et al., 2001). In AD brain, degeneration of cholinergic basal forebrain neurons correlates with disease duration and the degree of cognitive impairment (Davies and Maloney, 1976;

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Whitehouse et al., 1982; Mufson et al., 1989). These types of neurons provide the major source of cholinergic innervation to the cerebral cortex and hippocampus and play a key role in memory and attention. To obtain single basal forebrain neurons, basal forebrain tissue was obtained, fixed and stained with acridine orange to confirm the presence of RNA (Mufson et al., 2002). Then, sections were immunostained with an antibody specific for p75, followed by individual aspiration of identified neurons. RNA was amplified from single cells and custom array technology was used to examine the expression of functional classes of mRNAs in anterior nucleus basalis (NB) neurons from normal aged and AD subjects. mRNAs encoding neurotrophin receptors, synaptic proteins, protein phosphatases and amyloid-related proteins were evaluated. Whereas trkB and trkC mRNAs were selectively downregulated in NB neurons, p75NTR mRNA levels remained stable in end stage AD. TrkA mRNA was reduced by approximately 28%, but did not reach statistical significance. There was a down-regulation of synaptophysin, synaptotagmin and protein phosphatases PP1a and PP1b mRNAs in AD. No differences were found for the structural Aa and Ab and the catalytic subunit Ca of PP2A, contradicting previous findings based on in situ hybridization analysis (Vogelsberg-Ragaglia et al., 2001). In contrast, a selective up-regulation of cathepsin D mRNAwas found in NB neurons in AD brain confirming previous studies (Ginsberg et al., 2000; Mufson et al., 2002). (For single-cell gene expression analysis and its implications for neurodegenerative and neuropsychiatric disorders see: Ginsberg et al., (2004)). A few studies have also focused on early changes associated with mild cognitive impairment. In one microarray analysis of a small group of brain samples from cases with moderate dementia, several changes in genes involved in neurotransmitter regulation were observed in the superior temporal gyrus. Down-regulation was found for genes encoding synaptic vesicle proteins such as synapsin IIa, and genes involved in cytoskeletal mobility, protein metabolism and fatty acid metabolism (Pasinetti, 2001). A follow-up study using proteomics confirmed many of the changes in proteins with synaptic activities (Pasinetti and Ho, 2001). Proteomics was also used to analyze six regions of the human brain, three as representations of neurodegeneration in AD (hippocampus, temporal cortex and entorhinal cortex), and three comparison regions that are relatively spared in AD (cerebellum, cingulated gyrus and sensorimotor cortex) (Schonberger et al., 2001). 2D gel electrophoresis and trypsin digestion of Coomassie-stained gels was followed by reversed phase HPLC and aminoterminal peptide sequencing. By this approach, 411 proteins were identified that were differentially expressed between one or more cerebral regions from AD and non-AD brains. The molecular identity of 37 proteins with significantly altered expression was determined. Key functional groups of these proteins included synaptic transmission, stress response,

lipid transport, glycolysis and, interestingly, roles in the pathogenesis of diabetes. Concerning the latter, there are reports that diabetes mellitus is associated with an increased risk of developing AD but this issue has not been finally settled (Messier, 2003; Arvanitakis et al., 2004). In another post-mortem proteomic study, differentially expressed proteins were identified in the temporal lobe in AD, with a balance towards down-regulation. Five protein spots were significantly increased, 28 spots were significantly decreased and seven spots were specifically detected in AD. Two spots among those significantly increased and one spot among those significantly decreased were identified as GFAP-related (Tsuji and Shimohama, 2001). GFAP has been previously associated with disease. The pathological hallmark of a rare disorder of the central nervous system of unknown etiology termed Alexander’s disease is the socalled Rosenthal fibers, which are cytoplasmic inclusions in astrocytes that contain GFAP in association with small heatshock proteins (Brenner et al., 2001; Kurosinski and Gotz, 2002). In a follow-up proteomics study, AD and control brains were compared using nanoESI-MS and MS/MS utilizing a Qq-TOF mass spectrometer, and 35 proteins from over 100 protein spots on a 2D gel were identified. In the temporal lobe of AD brain, G protein b subunit, 60 kDa heat shock protein and internexin were decreased, whereas mitochondrial ATP synthase a subunit and calpain were increased. The degree of the increases and decreases, however, was not reported (Tsuji et al., 2002). Oxidative modification has long been implicated in the pathogenesis of AD and related neurodegenerative disorders. These modifications may promote the formation of cross-linked protein aggregates, making them resistant to removal by proteinases. Increased production of reactive oxygen species (ROS) and increased oxidative modification of brain proteins are also important in AD pathogenesis (Hensley et al., 1995; Markesbery, 1997). Carbonyl formation is an important marker of protein oxidation, and carbonyl derivatives are formed by ROS-mediated oxidation of side-chains of some amino acid residues. Carbonyl groups may also be introduced into proteins by glycation and reaction with lipid peroxidation products. Protein carbonyls are increased in AD, and there is a brain regional correspondence between protein carbonyl formation and histopathological markers in AD (Hensley et al., 1995). To address protein carbonyl formation at the cellular level and to obtain information about individual protein targets, proteins from different brain regions of six AD patients and six healthy controls were separated by 2D gel electrophoresis, and the positions of some selected proteins were identified using specific antibodies, followed by immunoblot analysis for protein carbonyls (oxyblots). These studies demonstrated the presence of protein carbonyl immunoreactivity in b-tubulin, b-actin and creatine kinase BB in AD and control brain extracts. Interestingly, protein carbonyls were undetectable in spots matching GFAP and tau isoforms. Specific protein carbonyl levels in b-actin and

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creatine kinase BB were significantly higher in AD than in control brain extract, whereas b-tubulin did not demonstrate a significant increase in specific protein carbonyl content. The authors concluded that oxidative stress-induced injury may involve the selective modification of different intracellular proteins, including key enzymes and structural proteins, which precedes and may lead to the neurofibrillary degeneration of neurons in the AD brain (Aksenov et al., 2001). To circumvent the limitations of oxyblots, which are laborious, requires the availability of specific antibodies, and, most importantly, a reasonable guess as to the identity of the protein; a proteomic approach was used to identify specifically oxidized proteins in AD, by coupling 2D fingerprinting with immunological detection of carbonyls and identification of proteins by MALDI-TOF MS. Increased oxidation was detected in AD brains for creatine kinase BB, glutamine synthase and ubiquitin carboxyterminal hydrolase L-1 (Castegna et al., 2002a). In a followup study of the same group, additional increases were reported in protein oxidation of dihydropyriminidase-related protein 2 (DRP-2), a protein involved in axonal growth and guidance, and the cytosolic enzyme a-enolase involved in the glycolytic pathway (Castegna et al., 2002b). Interestingly, in fetal Down’s syndrome brain, the level of DRP-2 is decreased (Weitzdoerfer et al., 2001), suggesting a crucial role of this protein in promoting correct synaptogenesis and neuronal differentiation and migration, processes that are abnormal in Down’s syndrome. As only a few proteins were found to exhibit increased protein carbonyl content in AD, this raises the possibility of new roles of protein oxidation in neurodegeneration in AD. It is plausible that decreased activity of oxidized enzymes might impair the metabolic pathway in which they are involved, from which cell abnormalities may result (Castegna et al., 2002b). In a related study, again, significant changes in the amount of protein-bound carbonyls were found only for a few proteins, with five increases and one decrease in AD brains. In that particular study, only the molecular weight was given and the identity of these proteins was not determined (Korolainen et al., 2002). In addition to oxidation, nitration of tyrosine has been associated with several neurodegenerative diseases, such as ALS, PD and AD. Increased levels of nitrated proteins have been reported in AD brain and CSF, demonstrating the potential involvement of reactive nitrogen species (RNS) in neurodegeneration. Reaction of NO with O2
leads to formation of peroxynitrite ONOO
, which, following protonation, generates cytotoxic species that oxidize and nitrate proteins. Several findings suggest an important role of protein nitration in modulating the activity of key enzymes in neurodegenerative disorders. By MALDI-TOF MS and LC-MS/MS of nitrotyrosine-reactive preactive protein spots separated by 2D gel electrophoresis, six targets of protein nitration were identified in AD brain. These included g-enolase, b-actin, L-lactate dehydrogenase,

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triosephosphate isomerase and human neuropeptide h3. The enolases are involved in glycolysis, L-lactate dehydrogenase in energy metabolism and b-actin is part of the cytoskeleton (Castegna et al., 2003). When assessing the functional categories, which are differentially regulated as determined by both transcriptomic and proteomic approaches, some categories reoccur in almost every study. These are functions associated with the synapse as a subcellular site affected early on in the degenerative process of AD. Then, categories associated with oxidative and other forms of stress, and mitochondrial functions are often found. As these have been implicated in the etiology of PD, this suggests a potential pathogenic overlap between AD and PD. Finally, as a third category, genes and proteins involved in all forms of metabolic functions, including energy metabolism, are generally found to be differentially regulated in AD samples. This asks, as a logical next step, for a careful metabolomic analysis of AD samples. It is expected that such an analysis would provide insight into the role of environmental factors in sporadic AD. A major research area in AD, in addition to dissecting pathogenic mechanisms, is the development of diagnostic tools. Accurate clinical diagnosis of AD remains a challenge (Gotz, 2001). To assist in the early diagnosis of AD and other neurodegenerative diseases, there are increasing efforts to identify biomarkers in the CSF or elsewhere in the periphery. One early report identified variations in a-2FS haptoglobin in the CSF between AD and schizophrenia patients by analyzing silver stained 2D gels using immunoblotting (Johnson et al., 1992). For example, to identify new potential biological markers, a number of 2D PAGE protein spots in a human CSF pool were analyzed using aminoterminal sequencing, MALDI-MS and nanoLC-ESI-TOF-MS with MS/MS switching. The spots included the complement C3 a-chain, complement factor B, cystatin C, calgranulin A, the hemoglobin b-chain and b2-microglobulin (Raymackers et al., 2000). In a related study, CSF from AD patients with confirmed post-mortem pathology was compared with specimens from healthy controls. Following 2D gel electrophoresis, nine molecular markers were identified that were found to be segregating diseased cases from normal controls; however, the markers were not further identified (Choe et al., 2002). Another group obtained CSF from 15 AD patients and 12 controls and used a mini-gel technology in a 2D electrophoresis procedure, sensitive SYPRO Ruby staining and MALDI-TOF- and ESI-QTOF-MS/MS. They found that the levels of six proteins and their isoforms, including proapolipoprotein, apolipoprotein E, b2-microglobulin, retinol-binding protein, transthyretin and ubiquitin, were significantly altered in CSF of AD patients. The most prominently altered proteins were the apolipoproteins, especially proapolipoprotein (Davidsson et al., 2002b). To obtain diagnostic markers with a high selectivity and specificity, a comparative proteomic analysis of CSF proteins was employed for studies of the pathophysiological mechanisms in FTD. 2D gel electrophoresis and MS were

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used for clinical screening of CSF proteins in 15 FTD patients compared to 12 controls. Six proteins were significantly altered in FTD compared to controls, including granin-like neuroendocrine precursor (proSAAS), pigment-epithelium derived factor (PEDF), retinol-binding protein (RBP), apoE, haptoglobin and albumin. The levels of ProSAAS, PEDF and RBP have not been shown earlier to be involved in the FTD pathology. Compared with the proteomic analysis of CSF obtained from AD patients, ApoE seemed to be influenced to a lesser degree in FTD compared to AD. Several proteins involved in FTD pathology were not influenced in the CSF of AD patients, and vice versa, establishing differences in the pathophysiological mechanisms between FTD and AD (Davidsson et al., 2002a). These types of direct proteomic comparisons between AD and other neurodegenerative disorders in easily obtainable patient samples are likely to have significant implications for the diagnosis and the development of specific medication in the future. 3.3. From Alzheimer’s disease to Parkinson’s disease Oxidative stress is an important factor that has been implicated in the pathogenesis of a number of neurodegenerative disorders. Post-mortem analyzes revealed that the overall level of oxidative damage to proteins, lipids and DNA is elevated in both AD and PD brains (Giasson et al., 2002; Jenner, 2003). In addition to oxidative stress, ubiquitin-proteasome dysfunction has been implicated in the pathogenesis of AD and PD, but the interplay between these two processes is not understood. To investigate alterations in protein expression associated with AD and PD, a comparative 2D gel electrophoresis was performed with the gels being stained with SYPRO Ruby, and three different spots showed differential expression between AD, PD and controls. Quantification of the intensities of these spots revealed that, in AD, the protein levels of all three spots were decreased by approximately 50% compared with agematched controls. In PD, the level of spot #1 was decreased by 30%, whereas the levels of spots #2 and #3 were virtually unaltered. These spots turned out to be DNP-reactive and therefore exhibited a high degree of oxidation (oxyblot). They were sequenced by a combination of MALDI-TOF MS and HPLC-ESI MS/MS. Three human brain UCH-L1 (ubiquitin carboxyl-terminal hydrolase L1) isoforms were identified, a full-length form and two amino-terminally truncated forms. The proteomic analysis revealed that the full-length UCH-L1 is a major target of oxidative damage in both AD and PD brains. Furthermore, immunohistochemical studies showed prominent UCH-L1 immunostaining associated with NFTs, and levels of soluble UCH-L1 protein inversely proportional to NFT numbers in AD brains. Together, these results provide evidence supporting a direct link between oxidative damage to the neuronal ubiquitination/de-ubiquitination machinery and the pathogenesis of both sporadic AD and PD (Choi et al., 2004).

To identify candidate genes for PD, SAGE and genetic linkage analysis were combined. SAGE was applied to two normal substantia nigras and adjacent midbrain tissue. Over 3700 transcripts were identified. The three most abundant SAGE tags did not correspond to any known genes or ESTs. Then, high-throughput bioinformatics was used to map the genes corresponding to these tags, and 402 substantia nigra genes were identified that lay within five large genomic linkage regions, previously identified in 174 multiplex PD families. These novel genes are likely to represent candidates for PD susceptibility alleles and await further genomic analyzes (Hauser et al., 2003). In general, identifying subregion-specific mRNAs is likely to assist in understanding selective vulnerability, which characterizes all neurodegenerative disorders in humans. 3.4. From humans to non-human primates Compared to neurodegenerative diseases with marked changes in brain structure, neuropsychiatric diseases with more subtle changes in neurochemistry pose a particular challenge to Functional Genomics. Using high throughput approaches, however, consistent patterns of gene expression changes were revealed even in disorders such as schizophrenia, where disregulation of genes involved in synaptic function and metabolism is seen in prefrontal cortex of postmortem brain samples from affected individuals (Lewis et al., 2003; Vawter et al., 2004). In addition to humans, Affymetrix screening has been applied to non-human primates. Analysis of prefrontal cortices of human, chimpanzee, macaque and marmoset by a qualitative (present or not detected) and quantitative (expression level) measure indicated that many genes known to be involved in human neurological disorders were present and regulated in non-human primates (Marvanova et al., 2003). This implies that the aged non-human primate brain may be a feasible model for neurodegenerative disorders (Schultz et al., 2000). In general, however, experimental models such as the mouse are more practical for experimental manipulation (Gotz et al., 2004b).

4. Application of functional genomics to animal models 4.1. Wild-type mice In this chapter, we will first discuss efforts to identify subregion- or cell type-specific transcripts in non-transgenic mice. In contrast to human brain, distinct brain regions of experimental animals can be easily dissected to perform a neuroanatomical profiling, without a considerable postmortem delay. When this approach was applied using an 11,000-gene array, a series of genes specific for subregions of the hippocampus (CA1, CA3 and DG) was defined and

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confirmed by qRT-PCR. The Trp6 gene, for example, was localized specifically to the dentate gyrus and confirmed by in situ hybridization analysis, whereas Testican localized specifically to CA3 pyramidal neurons. The maximal difference observed was 7.6-fold (Zhao et al., 2001). This fold difference is higher than in studies using total brain of transgenic compared with control brain indicating that zooming in into specific brain areas is advantageous (Chen et al., 2004). Affymetrix chips were also used to assess gene expression differences in wild-type strains in response to seizures and in different brain regions, with subsequent validation by Northern blotting and qRT-PCR (Sandberg et al., 2000). Expression profiles of cortex, cerebellum and midbrain within the same strain revealed, on average, a relatively small number of genes (less than 1%) with clear differences. In that particular study, 23 genes were uniquely expressed in the cerebellum but not detectable in other brain areas. Vice versa, 28 genes were excluded from the cerebellum but expressed in other brain areas. In contrast to the cerebellum, the structures of the medial temporal lobe (hippocampus, amygdala and entorhinal cortex) showed extremely similar expression profiles. Only eight genes were unique to one of the three regions. Of the seven genes present in the hippocampus and not in the amygdala or the entorhinal cortex, six were also expressed outside of the medial temporal lobe. Remarkably, there was only one gene uniquely expressed in the amygdala and not in the entorhinal cortex. These findings would suggest that forebrain structures, despite some functional differences, are highly similar at the molecular level. Finally, the midbrain was interesting in that, although 10 genes were uniquely expressed, no genes were exclusively absent (Sandberg et al., 2000). In a related study, a microarray analysis of differential gene expression among five selected brain regions, including the amygdala, cerebellum, hippocampus, olfactory bulb and periaqueductal gray, was combined with in situ hybridization. On average, 0.3% of the 34,000 genes assessed were highly enriched in each of the five regions, relative to the others. In situ hybridization performed on a subset of amygdala-enriched genes confirmed in most cases the overall region-specificity predicted by the microarray data and identified additional sites of brain expression not examined on the microarrays. Strikingly, the majority of these genes exhibited boundaries of expression within the amygdala corresponding to cytoarchitectonically defined subnuclei. These results define a unique set of molecular markers for amygdaloid subnuclei and provide tools to genetically dissect their functional roles in different emotional behaviors (Zirlinger et al., 2001). A role for different amygdaloid subnuclei has been shown in fear conditioning and conditioned taste aversion (CTA) (Welzl et al., 2001; Bahar et al., 2003). Interestingly, the outcome of fear conditioning and CTA tests in P301L mutant tau transgenic mice is correlated with the distribution of tau

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aggregates in amygdaloid subnuclei (Pennanen et al., 2004). As NFT formation is prominent in the amygdala of P301L tau mutant mice (Gotz et al., 2001b; Lewis et al., 2001), it will be interesting to identify amygdaloid genes that confer an increased susceptibility to develop NFT. Another interesting aspect is the differences in inbred strains that are routinely used to generate either transgenic or knockout mice. The C57BL/6 and hybrid strains derived thereof are widely used to produce transgenic mice by pronuclear injections whereas 129Sv is the genotype of most embryonic stem cell lines used for production of knockout mice. Some strains are preferentially used for behavioral studies (Pennanen et al., 2004, 2005), whereas others are used for seizure studies (Mohajeri et al., 2004). Thus, it is interesting to note that many genes are differentially expressed between the 129SvEv and C57BL/6 mouse strains, both at baseline and in response to seizure. A total of 73 genes was differentially expressed in at least one brain region between the two strains. A subset of these genes was confirmed by Northern blotting and qRT-PCR. When the expression profiles of hippocampus and cerebellum were determined in the two strains 1 h after seizure induction using pentylenetetrazol, it could be shown that the C57BL/6 mice had a significantly greater overall transcriptional response to seizure induction (with 49 genes being induced in C57BL/6 hippocampus compared with 12 in 129SvEv) (Sandberg et al., 2000). This means that the genetic background has to be considered when a phenotype is interpreted. It also implies that crossing of the transgene or a null mutation onto a different genetic background might either enhance or ameliorate the phenotype in which case it might be worthwhile to identify the modifier genes. To identify memory-related genes, wild-type mice that had undergone a standard Morris water maze paradigm were analyzed with Affymetrix chips. Twelve hundred neurobiologically relevant genes were simultaneously profiled and, among others, 140 hippocampal memory-related genes including glutamate receptors, ion channels and trafficking proteins were identified (Cavallaro et al., 2002). This information will be important in efforts understanding and distinguishing memory impairment in normal aging and neurodegenerative disorders (Morrison and Hof, 1997). 4.2. Amyotrophic lateral sclerosis Only a few transgenic or knockout strains as models for ALS have been subjected to transcriptomic and proteomic analyzes so far. These include transgenic mice overexpressing mutant SOD, a murine model of ALS (Yoshihara et al., 2002). Using Kinetworks multi-immunoblotting analysis of brain and spinal cord tissue, the expression of 78 protein kinases, 24 protein phosphatases and 31 phosphoproteins was investigated. Significant differences were found in the expression of kinases, phosphatases and the phosphorylation of their substrates between mutant and control tissue; however, the expression and phosphorylation

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differences between mSOD and control mice were dissimilar to those seen for patients with sporadic ALS and healthy controls (Hu et al., 2003). Furthermore, using cDNA microarrays (Atlas Glass microarrays; Clontech), 30 elevated and 7 decreased genes were identified in the spinal cords of G93A mice (Yoshihara et al., 2002). Genes related to an inflammatory process, such as the tumor necrosis factor-a gene were up-regulated, resulting from glial activation, together with an altered apoptosis-related gene expression as shown for caspase-1. The increased expression of the inflammation- and apoptosis-related genes occurred at 11 weeks of age in the presymptomatic stage prior to motor neuron death suggesting that an inflammatory response is an important component of neurodegeneration in ALS (Yoshihara et al., 2002). A role for inflammation- and apoptosis-related genes has also been revealed by studies using human tissue (see above). Inducing brain inflammation in these transgenic models pharmacologically or by lesioning, crossing the transgenic mice with transgenic models of brain inflammation (Wyss-Coray and Mucke, 2002), or treating the mice with anti-inflammatory drugs will clarify the relative contribution of inflammation to ALS. 4.3. Alzheimer’s disease and frontotemporal dementia A whole range of transgenic animal models has been developed for AD and FTD in the course of the last years (Gotz, 2001; Gotz et al., 2004b). These model aspects of the key histopathologic features of these diseases, namely b-amyloid plaques and NFT, but do not display massive neurodegeneration. The histopathologic features have been correlated with distinct behavioral impairments (Gotz et al., 2004b). Until today, only a few transgenic strains have been analyzed by Functional Genomics. These include an amyloid precursor protein and presenilin-1 (APP/PS1) double transgenic mouse strain, which develops memory deficits as Ab deposits accumulate. Gene expression was profiled by competitive hybridization of RNA derived from Ab-containing areas (hippocampus and cortex) and Ab-free areas (cerebellum, striatum and brainstem) to Unigene Lifearray microarrays (Incyte Genomics Ltd.) and confirmed by qRT-PCR. At an age when these animals developed cognitive dysfunction, they showed reduced mRNA expression of several genes essential for long-term potentiation (LTP) and memory formation (Arc, Zif268, NR2B, GluR1, Homer-1a, Nur77/TR3). These changes were maximally twofold and appeared to be related to Ab deposition, because mRNA expression was unchanged in the regions that did not accumulate Ab. Interestingly, these changes occurred without apparent changes in synaptic structure, because a number of presynaptic marker mRNAs (such as growth-associated protein-43, synapsin, synaptophysin, synaptopodin, synaptotagmin and syntaxin) remained stable. The data suggest that the memory loss in APP/PS1 transgenic mice may model the early memory

dysfunction in AD before synapses and neurons degenerate (Dickey et al., 2003). To address the role of the environment on Ab peptide levels and amyloid deposits, APP/PS1 mutant double transgenic mice with a high plaque load in the hippocampus and cortex were exposed either to an ‘‘enriched environment’’ or raised under ‘‘standard housing’’ conditions (Lazarov et al., 2005). The enriched environment was composed of large cages, running wheels, colored tunnels, toys and chewable material. It was found that the enriched environment led to reduced Ab deposition and reduced Ab levels. This is different from a previous report using a different APP/PS1 transgenic mouse strain (Jankowsky et al., 2003), and the critical differences in the experimental approaches have been thoroughly discussed (Lazarov et al., 2005). In the mice with the reduced Ab levels (Lazarov et al., 2005), the Ab-degrading enzyme, neprilysin, revealed an elevated activity suggesting that reductions in Ab levels in enriched mice might, at least in part, be the consequence of elevated neprilysin activity. However, as it is equally conceivable that additional mechanisms might be operative influencing Ab production and/or deposition, a transcriptomic analysis using Affymetrix microarrays was performed. A 3-month time point was chosen to uncover transcriptomic changes preceding Ab deposition. The majority of genes identified as differentially expressed (and mainly increased in the enriched environment) were related to early transcriptome activation, and these encoded poly-peptides involved a variety of processes associated with learning and memory, vasculogenesis, neurogenesis and cell survival pathways (Lazarov et al., 2005). Consistent with earlier studies that suggest exercise induces angiogenesis in the CNS following environmental enrichment (Black et al., 1990; Isaacs et al., 1992; Swain et al., 2003), elevated expression of the mRNA encoding the zinc finger transcription factor EGR-1 was observed. The authors of the study offer the suggestion that modifications of the blood–brain barrier and associated factors may have a profound impact on Ab clearance (Shibata et al., 2000; Lazarov et al., 2005). P301L mutant tau transgenic mice are a model of NFT formation, the second histopathological hallmark of AD (Lewis et al., 2000; Gotz et al., 2001a,b). Using UniGem mouse microarray chips (Incyte Inc.), inflammation mediators and apoptosis inhibitors were found to be downregulated (Ho et al., 2001). A second P301L mutant mouse line was analyzed using Affymetrix microarrays (Chen et al., 2004). By a stringent analysis, a single up-regulated gene, glyoxalase I, was identified. This enzyme plays a critical role in the detoxification of dicarbonyl compounds and thereby reduces the formation of advanced glycation end products. Levels of glyoxalase I mRNA and protein were significantly elevated in P301L brains, as shown by Northern and Western blot analysis, respectively. Moreover, a glyoxalase I-specific antiserum revealed many intensely stained flame-shaped neurons in AD brain compared with brains from non-

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demented controls suggesting a previously unidentified role for glyoxalase I in neurodegenerative disease (Chen et al., 2004). In addition to a transcriptomic approach, a proteomic approach was applied to P301L transgenic brain followed by a functional analysis. Mainly mitochondrial proteins, antioxidant enzymes and synaptic proteins were identified as modified in the proteome pattern of P301L tau mice. Furthermore, a functional analysis demonstrated a mitochondrial dysfunction in these mice demonstrating the validity of the proteomic approach (David et al., 2005). Specifically, proteomics identified mainly metabolic related proteins including mitochondrial respiratory chain complex components, antioxidant enzymes and synaptic proteins as modified in the proteome pattern of P301L tau mice. Functional analysis demonstrated a mitochondrial dysfunction in P301L tau mice together with reduced NADHubiquinone oxidoreductase activity and, with age, impaired mitochondrial respiration and ATP synthesis. Mitochondrial dysfunction was associated with higher levels of reactive oxygen species in aged transgenic mice. Increased tau pathology as in aged homozygous P301L tau mice revealed modified lipid peroxidation levels and the up-regulation of antioxidant enzymes in response to oxidative stress. As the proteomics comparison of the P301L tau and wild-type control mice revealed a significant decrease of two spots identified as the complex V component ATP synthase D chain, complex V levels were analyzed in human FTDP-17 patient brains carrying the P301L tau mutation. A significant decrease in complex V levels was found in all P301L brain samples compared to control brains confirming the proteomics observation made in the P301L tau transgenic mice and suggesting that the P301L mutant tau pathology potentially causes a specific mitochondrial dysfunction in humans as well as in mice. Furthermore, P301L tau transgenic mitochondria displayed increased vulnerability towards Ab peptide insult, suggesting a synergistic action of tau and Ab pathology on the mitochondria. Taken together, it was concluded that tau pathology involves a mitochondrial and oxidative stress disorder possibly distinct from that caused by Ab (David et al., 2005). Exposing the P301L mice to oxidative stress or mitochondrial toxins may determine whether oxidative stress and mitochondrial dysfunction are merely consequences of tau aggregation, or whether they can also enhance the tau pathology, arguing in favor of synergistic actions. 4.4. Parkinson’s disease The etiology of PD is still unknown, although clinical and experimental evidence implicates the involvement of mitochondrial dysfunction (Kosel et al., 1999; Beal, 2003) and oxidative stress (Jenner and Olanow, 1996; Zhang et al., 2000). Analysis of mitochondria isolated from idiopathic PD patients showed an inhibited capacity of NADH-ubiquinone reductase, part of the complex I of the

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mitochondrial electron transport chain, and increased production of reactive oxygen species (ROS) (Schapira, 1998). Similar changes have been seen in autopsy cases of patients with presymptomatic PD, suggesting that mitochondrial dysfunction and oxidative stress precede clinical manifestations (Dexter et al., 1994). In addition to the more prevalent idiopathic forms, a subset of PD patients exhibits familial inheritance patterns. Loss-of-function mutations in parkin are the predominant cause of familial Parkinson’s disease. Parkin has been shown to function as an E3 ubiquitin ligase. Loss of parkin function, therefore, has been hypothesized to cause nigral degeneration via an aberrant accumulation of its substrates. Surprisingly, parkin
/
mice exhibit nigrostriatal deficits in the absence of nigral degeneration (Goldberg et al., 2003). Therefore, a proteomic approach was employed to determine whether loss of parkin function results in alterations in abundance and the modification of proteins in the ventral midbrain of parkin
/
mice. 2D gel electrophoresis followed by a combination of MALDI-TOF and LC-ESI-MS revealed decreased abundance of a number of proteins involved in mitochondrial function or oxidative stress. Consistent with reductions in several subunits of complexes I and IV, functional assays showed reductions in the respiratory capacity of striatal mitochondria isolated from parkin
/
mice. Interestingly, electron microscopic analysis revealed no gross morphological abnormalities in striatal mitochondria of parkin
/
mice. Accompanying these deficits in mitochondrial function, parkin
/
mice also exhibited decreased levels of proteins involved in protection from oxidative stress, decreased serum antioxidant capacity and increased protein and lipid peroxidation (Palacino et al., 2004). As discussed above, similar findings were subsequently reported in P301L tau mutant mice modeling the tau pathology of AD (David et al., 2005). Additional initiatives of applying proteomics to PD have been reviewed recently, but await publication (Zhang and Goodlett, 2004).

5. Application of functional genomics to tissue culture 5.1. Amyotrophic lateral sclerosis Despite their limitation, tissue culture systems are useful, in particular when combined with transgenic models. Until today, however, only a few tissue culture systems modeling selected aspects of the human pathology have been analyzed using Functional Genomics. As motor neurons are degenerating in ALS, a tissue culture system was established by stable transfection of the motor neuron-like cell line NSC34 with wild-type, G93A or G37R mutant human SOD1, and analyzed by 2D gel electrophoresis followed by MALDI-TOF MS. The seven up-regulated proteins were identified as argininosuccinate synthase, argininosuccinate lyase, neuronal nitric-oxide synthase, RNA-binding motif

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protein 3, peroxiredoxin I, proteasome subunit b5 and glutathione S-transferase (GST) a2. The seven downregulated proteins were GST Mu 1, GST Mu 2, GST Mu 5, a hypothetical GST Mu, GST Pi B, leukotriene B(4) 12-hydroxydehydrogenase and proteasome subunit b5i (LMP7). Remarkably, in a proteomic study of P301L tau transgenic mice as a model for the tau pathology of AD of these proteins, GST Mu 1 and GST P2 were identified as down-regulated spots (David et al., 2005) pointing at common pathogenic mechanisms in ALS and AD. The proteomic study of the ALS cell lines was followed by functional assays. GST assays, for example, demonstrated a significant reduction in the total GST activity of cells expressing mutant human SOD1. Proteasome assays demonstrated significant reductions in chymotrypsin-like, trypsin-like and post-glutamylhydrolase proteasome activities. Subsequent LMD of spinal cord motor neurons from human ALS cases, in conjunction with RT-PCR, confirmed decreased levels of mRNAs encoding GST Mu 1, leukotriene B(4) 12-hydroxydehydrogenase and LMP7. Together, these combined approaches provide evidence for an involvement of alterations in antioxidant defenses, proteasome function and nitric oxide metabolism in the pathophysiology of ALS (Allen et al., 2003). In a related study, proteomics was used to identify mitochondrial proteins that are altered in the NSC34 cells in the presence of the G93A mutant form of SOD1. Four hundred seventy unique proteins were identified in the mitochondrial fraction collectively. 2D gel electrophoresis was used subsequently to analyze the differences between the mitochondrial proteomes of NSC34 cells expressing wild-type and G93A SOD1. Nine and 36 protein spots displayed elevated and suppressed abundance, respectively, in G93A expressing cells. The 45 spots were identified by RP-LC-MS/MS. They included proteins involved in mitochondrial membrane transport, apoptosis, the respiratory chain and molecular chaperones. In particular, alterations in the post-translational modifications of voltage dependent anion channel 2 (VDAC2) were found with relevance in regulating mitochondrial membrane permeability and activation of apoptotic signals (Fukada et al., 2004). Together, these studies demonstrate the potential of using specific model cell lines. Genetic manipulation of the identified candidates will provide further insight into the pathogenesis of ALS. 5.2. Parkinson’s disease a-Synuclein is the major filamentous constituent of the Lewy bodies in PD. To identify the proteins associated with soluble a-synuclein that might promote its aggregation, MES cells (a rat mesencephalic/neuroblastoma hybrid cell line) were exposed to rotenone, a pesticide that inhibits mitochondrial complex I, produces parkinsonism in animals and induces Lewy body-like inclusions in the dopaminergic neurons. More than 250 proteins associated with a-

synuclein soluble in the detergent NP-40 were identified. For that, duplicate gels were run with one gel being blotted and probed with an anti-a-synuclein antibody, while the other gel was stained with Coomassie Blue. Stained gel sections corresponding to a-synuclein-immunoreactive bands in immunoblot analyzes were cut, digested and analyzed by LC-MS/MS spectrometry. In addition, ICAT was applied. At least 51 proteins displayed significant differences in their relative abundance in a-synuclein complexes under conditions where rotenone was cytotoxic and induced formation of a-synuclein immunoreactive cytoplasmic inclusions. These included the heat shock protein (hsp) 70. When hsp70 was overexpressed in MES cells, not only were the cells protected from rotenonemediated cytotoxicity but also a-synuclein aggregation was decreased. Furthermore, the protection afforded by hsp70 transfection appeared to be related to suppression of rotenone-induced oxidative stress as well as mitochondrial and proteasomal dysfunction (Zhou et al., 2004). A protective role for hsp70 is supported by in vivo studies. When a-synuclein transgenic mice were bred with hsp70overexpressing mice, this led to a significant reduction in both the high molecular weight and detergent-insoluble asynuclein species (Klucken et al., 2004). The patho-cascades of PD and AD may overlap as a significant percentage of patients have clinical and pathological features of both diseases (Kurosinski et al., 2002). Therefore, drugs aimed at blocking the accumulation of Ab, a-synuclein or tau might benefit a broader spectrum of neurodegenerative disorders than previously anticipated. Proteomic analyzes will identify genes and proteins, which are involved in the patho-cascade of PD and AD. Eventually this may help in determining whether the two pathologies are only overlapping, or, what seems more likely, synergistic. 5.3. Alzheimer’s disease and frontotemporal dementia The human neuroblastoma cell line SH-SY5Y is widely used in AD research (Hamdane et al., 2003; Ruiz-Leon and Pascual, 2003; Uemura et al., 2003; Frasca et al., 2004). It can be neuronally differentiated by the sequential treatment with retinoic acid and brain-derived neurotrophic factor (BDNF). SH-SY5Y cells can be transplanted into mouse brain where they persist for a couple of days. Moreover, they anatomically integrate into organotypic hippocampal slices where they express synaptic markers and fire action potentials after 20 days in culture (Gotz et al., 2004a). To model the Ab42-mediated tau pathology in AD, human SHSY5Y neuroblastoma cells were transfected with wild-type and mutant tau constructs, neuronally differentiated and treated with fibrillar preparations of Ab42. This treatment caused a reduced solubility of tau, along with the formation of PHF-like tau filaments (Ferrari et al., 2003). To identify differentially regulated genes, a transcriptomic approach can be envisaged. However, as differences in gene regulation to

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be assessed by RNA screening methods (e.g., SAGE, Affymetrix GeneChips) can be very subtle, these techniques require stable reference genes for accurate normalization. Expression of housekeeping genes, which are routinely used for normalization, can vary significantly depending on the tissue, and experimental test. Therefore, stable reference genes were identified for fibrillar Ab42 peptidetreated, human tau-expressing SH-SY5Y neuroblastoma cells. By selecting genes exhibiting potential normalization characteristics from public databases a custom-made microarray was created that allowed the identification of reference genes for low, intermediate and abundant mRNAs. A subset of these candidates was subjected to qRT-PCR and analyzed with the geNorm software. GAPD, M-RIP and POLR2F were identified as stable and usable reference genes irrespective of the differentiation status and Ab42 treatment (Hoerndli et al., 2004). Following the identification of reference genes, this new normalization was applied to identify differentially expressed genes in Ab42-treated, P301L tau transfected SH-SY5Y cells as outlined below.

6. Integration of data and future perspectives Proteomics and transcriptomics have generated huge datasets and will continue to do so. To extract meaningful information it will be important to use an integrative approach and to assess additional information of the differentially expressed candidates, such as anatomical localization, splice variants, post-translational modifcation, biological function, role in disease and so forth. This information can be accessed by consulting websites such as http://www.rzpd.de/cards/. Integration of expression data is greatly facilitated when information about the function of the genes of interest and knowledge of the promoter elements controlling their expression is included. Comparing information from the transcriptome, proteome, anatomy and physiology is the most obvious way to integrate and verify biologically relevant information obtained from discovery-driven screening approaches. Systems biology is a new branch of biology aimed at understanding biological complexity and developing methods to integrate information obtained from different screening methods. This approach has been applied to yeast, where perturbations to critical pathway components were analyzed using transcriptomic and proteomic approaches, and databases of known physical interactions. By identifying 997 mRNAs responding to twenty systematic perturbations of the yeast galactoseutilization pathway and providing evidence that approximately 15 of 289 detected proteins are regulated posttranscriptionally, explicit physical interactions governing the cellular response to each perturbation were identified. The model was further refined through iterations of perturbation and global measurements, inciting Ideker and co-workers to bring forward hypotheses about the regulation

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of galactose utilization and physical interactions between this and a variety of other metabolic pathways (Ideker et al., 2001). However, general platforms where all this information can be directly integrated do not currently exist, with the exception of large industrial cross-related databases exploited by specific software offered by companies such as Genedata, Lion Bioscience, Ingenuity and others. In academic settings or when smaller datasets are assessed, data integration can also be done manually. An obvious first step is to check the functional annotation of the genes of interest to identify their role in putative regulation pathways (such as the MAPK pathway). Category-based analysis, such as those performed with EASE, or predetermined hierarchical gene classification as done with Genespring or other software packages (Table 1, part I of this review) assists in searching for biological themes (such as apoptosis or cell cycle) in broad screening approaches. To identify common regulatory pathways we compared transcriptomic data obtained in three experimental systems utilizing three different annotation databases. The first dataset involves the SAGE analysis of RNA extracted from pooled amygdalae of NFT-forming P301L tau transgenic mice. The second dataset used contains data from an Affymetrix screening of RNA extracted from total brain of these mice (Chen et al., 2004), and finally, we draw on Affymetrix data obtained from P301L tau-transfected human SH-SY5Y neuroblastoma cells (Ferrari et al., 2003; Hoerndli et al., 2004) (Fig. 1). The annotation and categorical analysis program EASE enables this analysis, yet it is important to keep in mind that each analysis highly depends on the database used. Databases differ in their hierarchical organization and the total number of annotated genes. Using GenMAPP pathways as an annotation database, we found that P301L cells (Affymetrix) and the P301L amygdala (SAGE) show differential regulation of genes in the two categories of electron transport chain and ribosomal proteins when compared with controls, whereas P301L amygdala (SAGE) and brain (Affymetrix) share regulated genes involved in inflammation signaling and proteasome degradation. However, when using GO biological processes as annotation database all three samples share regulated genes involved in intracellular protein transport, cell growth and development, DNA-dependent transcription, signaling in response to stress and sexual reproduction. The GO integration also suggests that P301L amygdala (SAGE) and brain (Affymetrix) specifically share genes involved in electron transport and carboxylic acid metabolism. Categories shared only by P301L brain and P301L cells (both Affymetrix datasets) include genes involved in cell cycle, phosphate metabolism and DNA metabolism. Finally, when using yet another database, KEGG, no overlap is revealed for all three samples. P301L amygdala (SAGE) and brain (Affymetrix) share no common categories, whereas analysis of P301L cells and P301L brain (both Affymetrix) reveals

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Fig. 1. Integrative comparison of SAGE and Affymetrix data obtained in three related experimental systems. To identify common regulatory pathways we compared transcriptomic data obtained in three experimental systems utilizing three different annotation databases. The first dataset involves the SAGE analysis of RNA extracted from pooled amygdalae of NFT-forming P301L tau transgenic mice (a). The second dataset used contains data from an Affymetrix screening of RNA extracted from total brain of these mice (b), and finally, we drew on Affymetrix data obtained from P301L tau-transfected human SH-SY5Y neuroblastoma cells (c). EASE (Expression Analysis Systematic Explorer) analysis of transcriptomic data from the three systems was done with three different annotation databases: GenMAPP pathways (1), KEGG pathways (2) and GO biological processes (3). (A) List of categories obtained after EASE analysis of each experimental system with each annotation database. The table lists the total number of annotated genes in each database (e), the number of annotated genes in a particular category (d), the number of genes of interest obtained in the experimental system (g), the number of genes of interest present in a particular category (b) and the name of the regulated categories (a). Colors are used to group categories according to themes. Red includes all energy metabolism-related categories; yellow all cell cycle, cellular growth, transcription and translation related categories; gray all signaling categories; pink all reproduction and infertility related categories; purple all protein degradation related categories; blue all intracellular transport related categories; orange all DNA metabolism related categories. (B) GenMAPP pathways (1) categories obtained with EASE as shown in (A). Regulated categories from three experimental conditions (a, b and c) are represented as a piece of pie (in orange) of the total number of annotated genes in the GenMAPP database (see d–f). This piece of pie is then split into specific categories using the color code described in (A). Hatched regions of the second pie represent the percentage of the number of candidate genes (b) in each category (d).

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Fig. 1. (Continued ).

shared regulated genes in categories such as neurodegenerative disorder, AD and Huntington’s disease, sorting and degradation and proteasome. On the other hand, P301L cells (Affymetrix) and amygdala datasets (SAGE) both show in common, regulated genes involved in oxidative phosphorylation and translation. The different outcome using the three databases is partly related to the fact that KEGG has less annotated genes than GenMAPP pathways and GO biological processes. Annotated genes for intracellular transport are found in only the GO database and not in the other two databases. In any case, the outcome of gene category analysis is highly dependent on the annotated database used. However, constant themes such as energy metabolism and proteasome degradation appear across all three databases, suggesting a biological role for these themes in P301L tau-related dysfunction. On the other hand, as the three annotation databases use an only partially overlapping set of categories, the finding of the categories sexual reproduction or intracellular protein transport for all three experimental systems only in the GO integration cannot be ignored. In addition to comparing the three transcriptomic datasets applying one annotation database after the other, an alternative approach is to compare the datasets obtained for one transcriptomic

analysis using all three annotation databases. For example, when assessing the P301L SAGE annotations a role for electron transport and ATP synthesis is highlighted with all three annotations databases. Another option is to run a promoter analysis. If genes that show a common regulation also participate in the same pathway or exert a similar function, and have in addition a regulatory promoter element in common, the significance of the findings is highly increased. One of the major obstacles in the application of Functional Genomics to neurodegenerative disorders is the complexity of the brain and the heterogeneity of cell types even within a relatively small brain area. With advances in the sensitivity of fluorescent detection it will eventually be possible to analyze the expression profile of single cells (Xiang et al., 2003). Whereas it is already possible to amplify RNA from single cells by PCR, this sensitivity is not yet in sight for the proteome. But still, with the further development of more sensitive mass spectrometric methods, as illustrated by the FTICR, it will be possible to use increasingly minute amounts of starting material. This will undoubtedly assist in dissecting pathogenic mechanisms by determining the proteome of dissected diseased brain tissue.

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Microarray technology will be particularly valuable in drug discovery. Similarly, in pharmacogenomics, the design of safer and more effective therapeutics targeted to specific individual phenotypes will be assisted by the microarray technology (Roses, 2000). We are on the verge of being able to identify inherited differences between individuals, which can predict each patient’s response to a medicine. Current efforts to map SNPs in the human genome, which are linked to disease, are expected to assist in the development of customized medicine (Roses, 2000). The combined application of transcriptomic and proteomic techniques to postmortem human tissue, CSF, brain tissue obtained from experimental animals and tissue culture systems will allow a better understanding of disease and assist in drug discovery programs. The major challenge for both principal techniques is to make biological sense of the vast amount of information that is generated in a typical experiment. This is further increased when combined with anatomical and imaging data. One step in the right direction is the use of software packages, such as TxtGATE, which discards technology-specific data formats and contents and converts the data into a text format including relevant literature citation, leaving the neuroscientist with the task of integrating knowledge and not simply using technology.

Acknowledgements The authors thank Dr. Peter Gehrig (Functional Genomics Center Zu¨rich) and Dr. Feng Chen (University of Zurich) for helpful suggestions and Jay Tracy for critical reading of this manuscript. We thank Drs. Dramiga, Krempel, Schro¨der and Schu¨tz (University of Cologne) for making the SAGE data available to us. This work was supported by grants from the EMDO Foundation, the Olga Mayenfisch Foundation, the Kurt und Senta Herrmann Foundation, the Swiss National Science Foundation, the University of Sydney and the Medical Foundation (University of Sydney) to J.G.

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