DDR
DRUG DEVELOPMENT RESEARCH 75 : 366–371 (2014)
Research Overview
Microarray Gene and miRNA Expression Studies: Looking for New Therapeutic Targets for Frontotemporal Lobar Degeneration Elena Milanesi1* and Andrea Pilotto2,3 1 Faculty of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel 2 Department of Neurodegeneration, University of Tübingen, Tübingen, 72074, Germany 3 Centre for Ageing Brain and Neurodegenerative Disorders, University of Brescia, Brescia, 25123, Italy
Strategy, Management and Health Policy Enabling Technology, Genomics, Proteomics
Preclinical Research
Preclinical Development Toxicology, Formulation Drug Delivery, Pharmacokinetics
Clinical Development Phases I-III Regulatory, Quality, Manufacturing
Postmarketing Phase IV
ABSTRACT Frontotemporal lobar degeneration (FTLD) encompasses a spectrum of neurodegenerative disorders characterized by behavioral, executive and language impairment, with a common overlap with parkinsonism and motor-neuron disease. Despite an increased understanding of its genetic background and molecular pathophysiology, FTLD is still an orphan disorder and there are currently no effective therapies available. In this brief overview we report the results obtained by several high-throughput and bioinformatic studies aimed at discovering impairment in the transcriptional profiles in brain and peripheral tissues from FTLD patients and in animal models. Taken together, all these results provide an interesting but still fragmentary list of genes and miRNAs whose role in FTLD should be thoroughly investigated. Drug Dev Res 75 : 366–371, 2014. © 2014 Wiley Periodicals, Inc. Key words: frontotemporal degeneration; microarray; gene expression analyses; genetics; therapy; drug targets
INTRODUCTION
Genomics, proteomics and metabolomics have profoundly changed the traditional approaches to drug discovery and development. In many fields of medical science, such as in oncology, potential drug targets are increasingly being identified combining highthroughput sequencing, microarray gene expression, microRNA (miRNA) studies and recently next generation sequencing (NGS) data [Koboldt et al., 2013]. Given its strong genetic background, frontotemporal lobar degeneration (FTLD) probably represents one of the best models for translational research in neurodegenerative disease. However, despite the large amount of genetic, proteomic, clinical and pathological data available, only few targets have so far been identified and reached the evaluation in clinical setting [Miller et al., 2014]. In this brief overview we summarize published gene expression/miRNA studies con© 2014 Wiley Periodicals, Inc.
ducted in preclinical FTLD models, on post-mortem human brain tissues and in vivo, with the aim to highlight the most promising discoveries in FTLD research, underlining the importance of bioinformatics as an ultimate strategy in translational research. FTLD OVERVIEW: CLINICAL, GENETICS AND NEUROPATHOLOGY
Frontotemporal dementia (FTD) refers to a group of clinically heterogeneous disorders characterized by *Correspondence to: Elena Milanesi, Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel. E-mail: [email protected] Published online in Wiley Online Library (wileyonlinelibrary .com). DOI: 10.1002/ddr.21224
EXPRESSION STUDIES IN FRONTOTEMPORAL DEMENTIA
the progressive involvement of frontal and temporal lobes in the clinicopathological spectrum of FTLD [Kertesz et al., 2005; Seelaar et al., 2011]. The clinical presentation includes behavioral changes, executive dysfunction and language impairment with a possible overlap with motor-neuron disease (MND) and parkinsonism [Seltman and Matthews, 2012; Armstrong et al., 2013; Hardy and Rogaeva, 2013; Sreedharan and Brown, 2013]. Three distinct clinical subtypes of FTLD have been defined: the behavioral variant (bvFTD) [Capell et al., 2011; Rascovsky and Grossman, 2014], the agrammatic (avPPA) and the semantic (svPPA) variants of primary progressive aphasia. Specific protein aggregation drives neuropathology FTLD subclassification [Sieben et al., 2012]. Ubiquitin/transactive response DNA-binding protein 43 kDa (TDP-43)-positive (FTLD-U/FTLD-TDP) and Tau-positive (FTLDTAU) inclusions accounted for more than 80% of cases, followed by fused in sarcoma (FUS)-positive inclusions (FTLD-FUS) [Josephs et al., 2011; Chare et al., 2014]. FTLD is the second most common cause of early-onset dementia but in late-life its prevalence is probably higher than previously reported [Borroni et al., 2010; Bernardi et al., 2012]. Forty to fifty percent of patients show a positive family history of dementia [Rademakers and Rovelet-Lecrux, 2009; Chare et al., 2014] and mutations in several genes have been identified in autosomal dominant FTLD. The great majority of FTLD-TDP monogenic cases have been associated with granulin (GRN) mutations and C9orf72 expansion [DeJesus-Hernandez et al., 2011; Renton et al., 2011]. Microtubule-associated protein tau (MAPT) and FUS genes mutations have been linked to FTLDTAU and FTLD-FUS, respectively [Spillantini et al., 1998]. FTLD-TDP RNA Expression Analyses Inclusion of TDP-43, a nuclear riboprotein involved in transcriptional splicing regulator [Buratti et al., 2010] defined FTLD-TDP, the only subtype associated with MND [Neumann et al., 2006]. TDP-43 pathology is characterized by hyperphosphorylation, ubiquitination, and depletion of nuclear TDP-43, as well as cytoplasmic inclusions containing truncated TDP-43 [Neumann et al., 2006; Mackenzie et al., 2010]. This raises the question of whether loss of a nuclear function or gain of toxic cytoplasmic function could be the primary causes of TDP-43 pathology [Buratti et al., 2010]. The same authors reported that in TDP-43 knockdown cells, let-7b and miR-663 expression levels were down- and upregulated, respectively, and that both miRNAs were able to bind directly TDP-43 in different positions. Using microarray
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approach the authors also identified several candidate transcripts whose expression levels were affected by these TDP-43–miRNA interactions. The list of altered cellular transcripts in TDP-43 knockdown experiments that represent putative miR-663 targets included EPHX1, CDA, AAMP [Buratti et al., 2010]. The first microarray-based gene expression study on post-mortem FTLD-TDP brain tissues was reported in 2007 [Mishra et al., 2007]. This work showed a threefold higher Dynein axonemal light intermediate chain 1 (DNALI1) and myeloid differentiation primary response gene 88 (MYD88) expression in FTLD-U compared with FTLD-MND and controls. Moreover, annexin A2 (ANXA2) expression was 11.3-fold higher in FTLD-U than FTLD-MND and 2.3-fold higher than controls. Chen-Plotkin et al. [2008] compared gene expression profiles of prefrontal cortex between 17 FTLD-U and 11 control brain samples. Sorting the identified genes by fold-change (FC) ID4, ABCA8, KLF4, ECM2, AQP1, SLC14A1, C4A/C4B, OMD, DCN and ANGPT1 were the top 10 upregulated genes, whereas NPTX2, EGR4, EGR3, HS35T2, SV2C, HTR2A, NRN1, GREM2, ARC and VGF were the top 10 downregulated. In the same study comparison of the gene expression profile of FTD progranulin mutation carriers (GRN+) with noncarriers (GRN−) and healthy controls identified 657 genes that were differentially expressed when comparing GRN-FTLD with controls, whereas comparing GRN-FTLD-U with controls identified only 147 genes as modulated (FC cutoff set by 2 and P = 0.001). Progranulin and TDP-43 The genetic association between TDP-43 pathology and progranulin has only recently been explained at the molecular level [Zhang et al., 2007; Kumar-Singh, 2011]. GRN mutations lead to severe PGRN haploinsufficiency, mostly due to out-of-frame insertions or deletions, splice site, or nonsense mutations that introduce a premature termination codon. This results in the degradation of the mutant messenger RNA via nonsense-mediated decay [Cruts et al., 2006; van der Zee et al., 2007; Gijselinck et al., 2008] or affects transport and stability of progranulin [Kleinberger et al., 2013]. Decreased progranulin can lead to pathological processing of TDP-43 by caspase 3, probably contributing to the first steps of TDP-43 pathology. However, Colombrita et al. [2012] demonstrated that TDP-43 activity also regulates progranulin expression. The group applied RNA immunoprecipitation and chip analysis to define the mRNAs associated with TDP-43. Bioinformatic analyses identified several targets regulated by TDP-43 activity, including progranulin. Given Drug Dev. Res.
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the haploinsufficiency mechanism, GRN is presently considered a particularly interesting gene for drug targeting and restoring PGRN levels as a promising therapeutic approach. Looking for compounds capable to selectively increase PGRN levels, Capell et al. [2011] identified several known drugs, including amiodarone for clinical trials. However, in monogenic GRNmutated patients, amiodarone was ineffective in a pilot trial [Alberici et al., 2014]. In fetal progenitor cells, Rosen et al. [2011] found the WNT1 signaling pathway was strongly associated with progranulin neuronal deficiency. This result was confirmed by gene expression data from frontal cortex samples of GRN-mutated FTLD patients. Moreover, in human post-mortem brain, a microarray-based screen of more than 800 miRNAs identified the miRNA-132 cluster as the top miRNAs differentiating FTLD-TDP and healthy controls and showed that its target, TMEM106B, was overexpressed in association with increased intracellular progranulin [Chen-Plotkin et al., 2012]. Using miRNA array profiling in FTLD-TDP frontal cortex tissues of patients with and without GRN mutations, Kocerha et al. [2011] identified 20 miRNAs differentially expressed compared with healthy controls. The confirmation in real-time polymerase chain reaction (PCR) validated miR-922, miR-516a-3p, miR-571, miR-548b-5p and miR-548c-5p differential expression. Interestingly, among the different targets of these miRNAs, brain angiogenesis inhibitor 3 (BAI3) was identified as a key synaptic player. As part of the effort to identify genes involved in FTLD onset, a microarray gene expression analysis was carried out on leukocytes of presymptomatic and symptomatic FTLD GRN mutation carriers. This study identified significant differences in expression levels of genes involved in inflammatory processes, when moving from preclinical to clinical stages of GRN-disease. In particular, beyond a normal expression of TARDBP, TMEM106B and WNT1, a significant alteration of leukocyte LY6G6F and TMEM40 expression was found when disease was overt, as compared with preclinical stages and healthy condition. These abnormalities were specific for GRN mutations and not detected in sporadic FTLD patients. Moreover, TMEM40 and LY6G6F mutations have been associated with different gray matter damage in vivo [Milanesi et al., 2013]. In order to identify possible genetic modulators of phenotype presentation, a microarray analysis was performed on the same peripheral tissue in an enlarged cohort of GRN mutation carriers. Interestingly, the expression levels of RAP1GAP were higher in avPPA as compared with bvFTD patients, but the identification of the molecular link between RAP1GAP and progranulin has not yet been identified [Bonvicini et al., 2014]. Drug Dev. Res.
C9orf72 Expansion and TDP-43 The recent discovery of C9orf72 expansion as the most common genetic cause of FTD, FTD- MND and pure MND has revolutionized the understanding of FTD-TDP pathology. The mechanisms by which the expanded repeats cause neurodegeneration are unknown; RNA-mediated toxicity, loss of the C9orf72 gene function or a combination of the two were proposed [Gendron et al., 2014]. Lagier-Tourenne et al. [2013] identified a nuclear RNA foci containing an hexanucleotide expansion (GGGGCC) in several types of patient cells, including white blood cells, fibroblasts, glia and neuronal cells. RNA foci were specific of C9orf72 mutation, being excluded in other forms of MND, neurodegenerative disease and controls. Moreover, in the same study genome-wide RNA profiling identified an RNA signature in fibroblasts from patients with C9orf72 expansion. Antisense oligonucleotides (ASOs) targeting sense strand repeat-containing RNAs did not correct this signature, a failure that may be explained, at least in part, by the discovery of abundant RNA foci with C9orf72 repeats transcribed in the antisense (GGCCCC) direction, which are not affected by sense strand-targeting ASOs [Lagier-Tourenne et al., 2013]. Taken together these findings support a therapeutic approach by ASO administration raising the potential importance of targeting expanded RNAs transcribed in both directions. Given the C9orf72 MND overlap, it will be pivotal to integrate C9orf72 amyotrophic lateral sclerosis (ALS) and FTD animal models and findings from clinical samples in order to further understand the mechanisms linked to this genetic variation. FTLD-TAU, MAPT Mutations and RNA Expression Analyses Tau protein is the first known and best studied contributor to FTLD. The identification of mutations within MAPT gene, encoding for tau protein, has provided compelling evidence for its causative role in the disease. FTLD-TAU has a deep clinical and neuropathological overlap with parkinsonism, especially with progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). In addition, tau inclusions are also present in other neurodegenerative diseases such as Alzheimer’s disease [Dickson et al., 2011]. Tauopathies are subclassified according to the predominant species of tau that accumulates in brain tissues with respect to alternative splicing of MAPT, with tau proteins containing three (3R) or four repeats (4R) of ∼32 amino acids in the microtubule binding domain. In the rarer Pick’s disease (PiD), with a circumscribed lobar atrophy, 3R tau predominates,
EXPRESSION STUDIES IN FRONTOTEMPORAL DEMENTIA
whereas 4R tau is characteristic of parkinsonism, CBD and PSP. Therefore, tau is a natively unfolded protein acting as microtubule assembler and stabilizer [Goode and Feinstein, 1994] and the number of repeats (3R versus 4R) can modulate its affinity for the microtubule surface. The discovery of MAPT mutations linked to FTD was an important breakthrough for understanding tau function and its role in neurodegenerative diseases. MAPT mutations can be distinguished into missense mutations affecting the normal microtubule stabilization, and intronic or coding mutations affecting the splicing of exon 10 at the mRNA level, resulting in a change in ratio of 3R to 4R tau isoforms [Goedert et al., 1989]. Thus, depending upon the specific mutation, familial FTLD-TAU presents large clinical phenotype variability and has been associated with 3R, 4R or a combination of 3R and 4R tau pathology. During the last decade, an increased understanding of how the posttranslational modifications of tau affect its function has led to a growing interest in developing drugs that target pathological tau [Brunden et al., 2010]. Prevention of mis-splicing, hyperphosphorylation, aggregation, and clearance of tau aggregates are currently promising therapeutic targets for interfering with tau-induced toxicity and neurodegeneration. Despite the increased understanding of the molecular mechanisms involved in tau pathology, only few studies have so far focused on gene expression profiling in FTLD-TAU. Bronner et al. [2009] constructed genome-wide expression profiles from snap frozen post-mortem tissues from the medial temporal lobe of patients with four tau neurodegenerative disorders (5 AD, 5 PSP, 5 PiD and 5 FTD patients) and five healthy controls. They found a set of 166 genes whose expression could discriminate between neurological disorders and normal aging; disease-specific gene sets were differentially expressed in each of the four disorders. A similar study by Hauser et al. [2005], conducted a microarray expression analysis of post-mortem substantia nigra samples from parkinsonism and controls. Due to the small sample size, including only two PSP and only one FTLD-TAU patient, the study did not find specific candidate genes for FTLD-TAU; however, it showed commonly reduced COX4I1 and ATP1B1 levels in both tauopathies. In addiction the study showed an increased expression of heat shock proteins HSPA1A and HSPA1B in Parkinson’s disease, PSP and FTLD-TAU compared with controls, indicating that this may be a common stress response to mitigate the toxic effects of a misfolded protein. Integrated microarray, qPCR, confocal microscopy and immunoblotting studies have shown that the moderately aged hTau mouse may explain the gene expression level changes found in
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human tauopathies. Specifically, progressive gene and protein level changes were identified in a vulnerable hippocampal cell type critical for learning and memory [Alldred et al., 2012].
Further Studies Kudo et al. [2010] developed an integrative approach using an animal model, postmortem human material and a combination of high-throughput microarray methods to identify novel molecular markers of ALS. They identified genes located within a linkage region associated with familial ALS/FTD. This large-scale gene and protein expression study identified distinct molecular mechanisms of TAU- and SOD1induced motor-neuron degeneration including several new ALS relevant proteins (CNGA3, CRB1, OTUB2, MMP14, SLK, DDX58, RSPO2) and putative blood biomarkers, including NEFH, PRPH and MGII. Eigenanatomy and sparse canonical correlation analysis (SCCAN) is another promising approach to identify associations between SNPs and neuroanatomical structure in neurological disease. McMillan et al. [2014] applied this method in FTLD identifying rs8070723 (in MAPT) as associated with gray matter variance in temporal cortex and rs1768208 (in MOBP), rs646776 (near SORT1) and rs5848 (in PGRN) in the midbrain and superior longitudinal fasciculus white matter variance. The recent publication of the largest genomewide association study in FTLD [Ferrari et al., 2014] suggested that immune system processes linked to 6p21.3 were potentially involved in the disease. In addition, the association of FTLD with the 11q14 locus, encompassing RAB38/CTSC genes related to lysosomal biology, provided a new perspective in FTLD pathophysiology. Functional studies will be important for confirming these observations, and for linking these genes with previously known genes implicated in FTD. The expression quantitative trait loci analyses performed on PSP represented a fine example for integrating genetics and functional analyses and should be replicated for the new genes FTLD-associated genes emerging from GWAS.
CONCLUSION
The growing interest in FTLD has led to important findings in genetics and molecular biology. Despite the improved understanding of its pathological and molecular basis; however, FTLD remains an orphan disorder with no disease-modifying therapies being available. The studies cited in this brief overview provide an interesting but fragmentary list of genes and Drug Dev. Res.
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miRNAs, the role of which in FTLD should be more thoroughly investigated, ideally with animal models. However, the integration between molecular models, in vivo analyses, and clinical genetics and molecular studies is mandatory in order to identify promising new therapeutic targets. A recent example in the field from Santiago et al. [2014] was focused on the identification new PSP biomarkers. The study integrated GWAS data cluster analyses with microarray findings obtained from blood samples, and identified PTPN1 as a novel candidate FTLD biomarker. Future steps in FTLD research will require a common platform where all genetic, clinical and gene expression data findings, obtained in brain and peripheral issues, can be shared by the research community. New genetic techniques such as NGS are promising but also need integration with clinical and molecular findings and with systems biology. Thus, bioinformatics studies and integrative database research will probably be the key for finding therapeutics for this complex CNS disorder. ACKNOWLEDGMENTS
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Drug Dev. Res.
DRUG DEVELOPMENT RESEARCH 75 : 366–371 (2014)
Research Overview
Microarray Gene and miRNA Expression Studies: Looking for New Therapeutic Targets for Frontotemporal Lobar Degeneration Elena Milanesi1* and Andrea Pilotto2,3 1 Faculty of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel 2 Department of Neurodegeneration, University of Tübingen, Tübingen, 72074, Germany 3 Centre for Ageing Brain and Neurodegenerative Disorders, University of Brescia, Brescia, 25123, Italy
Strategy, Management and Health Policy Enabling Technology, Genomics, Proteomics
Preclinical Research
Preclinical Development Toxicology, Formulation Drug Delivery, Pharmacokinetics
Clinical Development Phases I-III Regulatory, Quality, Manufacturing
Postmarketing Phase IV
ABSTRACT Frontotemporal lobar degeneration (FTLD) encompasses a spectrum of neurodegenerative disorders characterized by behavioral, executive and language impairment, with a common overlap with parkinsonism and motor-neuron disease. Despite an increased understanding of its genetic background and molecular pathophysiology, FTLD is still an orphan disorder and there are currently no effective therapies available. In this brief overview we report the results obtained by several high-throughput and bioinformatic studies aimed at discovering impairment in the transcriptional profiles in brain and peripheral tissues from FTLD patients and in animal models. Taken together, all these results provide an interesting but still fragmentary list of genes and miRNAs whose role in FTLD should be thoroughly investigated. Drug Dev Res 75 : 366–371, 2014. © 2014 Wiley Periodicals, Inc. Key words: frontotemporal degeneration; microarray; gene expression analyses; genetics; therapy; drug targets
INTRODUCTION
Genomics, proteomics and metabolomics have profoundly changed the traditional approaches to drug discovery and development. In many fields of medical science, such as in oncology, potential drug targets are increasingly being identified combining highthroughput sequencing, microarray gene expression, microRNA (miRNA) studies and recently next generation sequencing (NGS) data [Koboldt et al., 2013]. Given its strong genetic background, frontotemporal lobar degeneration (FTLD) probably represents one of the best models for translational research in neurodegenerative disease. However, despite the large amount of genetic, proteomic, clinical and pathological data available, only few targets have so far been identified and reached the evaluation in clinical setting [Miller et al., 2014]. In this brief overview we summarize published gene expression/miRNA studies con© 2014 Wiley Periodicals, Inc.
ducted in preclinical FTLD models, on post-mortem human brain tissues and in vivo, with the aim to highlight the most promising discoveries in FTLD research, underlining the importance of bioinformatics as an ultimate strategy in translational research. FTLD OVERVIEW: CLINICAL, GENETICS AND NEUROPATHOLOGY
Frontotemporal dementia (FTD) refers to a group of clinically heterogeneous disorders characterized by *Correspondence to: Elena Milanesi, Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel. E-mail: [email protected] Published online in Wiley Online Library (wileyonlinelibrary .com). DOI: 10.1002/ddr.21224
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the progressive involvement of frontal and temporal lobes in the clinicopathological spectrum of FTLD [Kertesz et al., 2005; Seelaar et al., 2011]. The clinical presentation includes behavioral changes, executive dysfunction and language impairment with a possible overlap with motor-neuron disease (MND) and parkinsonism [Seltman and Matthews, 2012; Armstrong et al., 2013; Hardy and Rogaeva, 2013; Sreedharan and Brown, 2013]. Three distinct clinical subtypes of FTLD have been defined: the behavioral variant (bvFTD) [Capell et al., 2011; Rascovsky and Grossman, 2014], the agrammatic (avPPA) and the semantic (svPPA) variants of primary progressive aphasia. Specific protein aggregation drives neuropathology FTLD subclassification [Sieben et al., 2012]. Ubiquitin/transactive response DNA-binding protein 43 kDa (TDP-43)-positive (FTLD-U/FTLD-TDP) and Tau-positive (FTLDTAU) inclusions accounted for more than 80% of cases, followed by fused in sarcoma (FUS)-positive inclusions (FTLD-FUS) [Josephs et al., 2011; Chare et al., 2014]. FTLD is the second most common cause of early-onset dementia but in late-life its prevalence is probably higher than previously reported [Borroni et al., 2010; Bernardi et al., 2012]. Forty to fifty percent of patients show a positive family history of dementia [Rademakers and Rovelet-Lecrux, 2009; Chare et al., 2014] and mutations in several genes have been identified in autosomal dominant FTLD. The great majority of FTLD-TDP monogenic cases have been associated with granulin (GRN) mutations and C9orf72 expansion [DeJesus-Hernandez et al., 2011; Renton et al., 2011]. Microtubule-associated protein tau (MAPT) and FUS genes mutations have been linked to FTLDTAU and FTLD-FUS, respectively [Spillantini et al., 1998]. FTLD-TDP RNA Expression Analyses Inclusion of TDP-43, a nuclear riboprotein involved in transcriptional splicing regulator [Buratti et al., 2010] defined FTLD-TDP, the only subtype associated with MND [Neumann et al., 2006]. TDP-43 pathology is characterized by hyperphosphorylation, ubiquitination, and depletion of nuclear TDP-43, as well as cytoplasmic inclusions containing truncated TDP-43 [Neumann et al., 2006; Mackenzie et al., 2010]. This raises the question of whether loss of a nuclear function or gain of toxic cytoplasmic function could be the primary causes of TDP-43 pathology [Buratti et al., 2010]. The same authors reported that in TDP-43 knockdown cells, let-7b and miR-663 expression levels were down- and upregulated, respectively, and that both miRNAs were able to bind directly TDP-43 in different positions. Using microarray
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approach the authors also identified several candidate transcripts whose expression levels were affected by these TDP-43–miRNA interactions. The list of altered cellular transcripts in TDP-43 knockdown experiments that represent putative miR-663 targets included EPHX1, CDA, AAMP [Buratti et al., 2010]. The first microarray-based gene expression study on post-mortem FTLD-TDP brain tissues was reported in 2007 [Mishra et al., 2007]. This work showed a threefold higher Dynein axonemal light intermediate chain 1 (DNALI1) and myeloid differentiation primary response gene 88 (MYD88) expression in FTLD-U compared with FTLD-MND and controls. Moreover, annexin A2 (ANXA2) expression was 11.3-fold higher in FTLD-U than FTLD-MND and 2.3-fold higher than controls. Chen-Plotkin et al. [2008] compared gene expression profiles of prefrontal cortex between 17 FTLD-U and 11 control brain samples. Sorting the identified genes by fold-change (FC) ID4, ABCA8, KLF4, ECM2, AQP1, SLC14A1, C4A/C4B, OMD, DCN and ANGPT1 were the top 10 upregulated genes, whereas NPTX2, EGR4, EGR3, HS35T2, SV2C, HTR2A, NRN1, GREM2, ARC and VGF were the top 10 downregulated. In the same study comparison of the gene expression profile of FTD progranulin mutation carriers (GRN+) with noncarriers (GRN−) and healthy controls identified 657 genes that were differentially expressed when comparing GRN-FTLD with controls, whereas comparing GRN-FTLD-U with controls identified only 147 genes as modulated (FC cutoff set by 2 and P = 0.001). Progranulin and TDP-43 The genetic association between TDP-43 pathology and progranulin has only recently been explained at the molecular level [Zhang et al., 2007; Kumar-Singh, 2011]. GRN mutations lead to severe PGRN haploinsufficiency, mostly due to out-of-frame insertions or deletions, splice site, or nonsense mutations that introduce a premature termination codon. This results in the degradation of the mutant messenger RNA via nonsense-mediated decay [Cruts et al., 2006; van der Zee et al., 2007; Gijselinck et al., 2008] or affects transport and stability of progranulin [Kleinberger et al., 2013]. Decreased progranulin can lead to pathological processing of TDP-43 by caspase 3, probably contributing to the first steps of TDP-43 pathology. However, Colombrita et al. [2012] demonstrated that TDP-43 activity also regulates progranulin expression. The group applied RNA immunoprecipitation and chip analysis to define the mRNAs associated with TDP-43. Bioinformatic analyses identified several targets regulated by TDP-43 activity, including progranulin. Given Drug Dev. Res.
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the haploinsufficiency mechanism, GRN is presently considered a particularly interesting gene for drug targeting and restoring PGRN levels as a promising therapeutic approach. Looking for compounds capable to selectively increase PGRN levels, Capell et al. [2011] identified several known drugs, including amiodarone for clinical trials. However, in monogenic GRNmutated patients, amiodarone was ineffective in a pilot trial [Alberici et al., 2014]. In fetal progenitor cells, Rosen et al. [2011] found the WNT1 signaling pathway was strongly associated with progranulin neuronal deficiency. This result was confirmed by gene expression data from frontal cortex samples of GRN-mutated FTLD patients. Moreover, in human post-mortem brain, a microarray-based screen of more than 800 miRNAs identified the miRNA-132 cluster as the top miRNAs differentiating FTLD-TDP and healthy controls and showed that its target, TMEM106B, was overexpressed in association with increased intracellular progranulin [Chen-Plotkin et al., 2012]. Using miRNA array profiling in FTLD-TDP frontal cortex tissues of patients with and without GRN mutations, Kocerha et al. [2011] identified 20 miRNAs differentially expressed compared with healthy controls. The confirmation in real-time polymerase chain reaction (PCR) validated miR-922, miR-516a-3p, miR-571, miR-548b-5p and miR-548c-5p differential expression. Interestingly, among the different targets of these miRNAs, brain angiogenesis inhibitor 3 (BAI3) was identified as a key synaptic player. As part of the effort to identify genes involved in FTLD onset, a microarray gene expression analysis was carried out on leukocytes of presymptomatic and symptomatic FTLD GRN mutation carriers. This study identified significant differences in expression levels of genes involved in inflammatory processes, when moving from preclinical to clinical stages of GRN-disease. In particular, beyond a normal expression of TARDBP, TMEM106B and WNT1, a significant alteration of leukocyte LY6G6F and TMEM40 expression was found when disease was overt, as compared with preclinical stages and healthy condition. These abnormalities were specific for GRN mutations and not detected in sporadic FTLD patients. Moreover, TMEM40 and LY6G6F mutations have been associated with different gray matter damage in vivo [Milanesi et al., 2013]. In order to identify possible genetic modulators of phenotype presentation, a microarray analysis was performed on the same peripheral tissue in an enlarged cohort of GRN mutation carriers. Interestingly, the expression levels of RAP1GAP were higher in avPPA as compared with bvFTD patients, but the identification of the molecular link between RAP1GAP and progranulin has not yet been identified [Bonvicini et al., 2014]. Drug Dev. Res.
C9orf72 Expansion and TDP-43 The recent discovery of C9orf72 expansion as the most common genetic cause of FTD, FTD- MND and pure MND has revolutionized the understanding of FTD-TDP pathology. The mechanisms by which the expanded repeats cause neurodegeneration are unknown; RNA-mediated toxicity, loss of the C9orf72 gene function or a combination of the two were proposed [Gendron et al., 2014]. Lagier-Tourenne et al. [2013] identified a nuclear RNA foci containing an hexanucleotide expansion (GGGGCC) in several types of patient cells, including white blood cells, fibroblasts, glia and neuronal cells. RNA foci were specific of C9orf72 mutation, being excluded in other forms of MND, neurodegenerative disease and controls. Moreover, in the same study genome-wide RNA profiling identified an RNA signature in fibroblasts from patients with C9orf72 expansion. Antisense oligonucleotides (ASOs) targeting sense strand repeat-containing RNAs did not correct this signature, a failure that may be explained, at least in part, by the discovery of abundant RNA foci with C9orf72 repeats transcribed in the antisense (GGCCCC) direction, which are not affected by sense strand-targeting ASOs [Lagier-Tourenne et al., 2013]. Taken together these findings support a therapeutic approach by ASO administration raising the potential importance of targeting expanded RNAs transcribed in both directions. Given the C9orf72 MND overlap, it will be pivotal to integrate C9orf72 amyotrophic lateral sclerosis (ALS) and FTD animal models and findings from clinical samples in order to further understand the mechanisms linked to this genetic variation. FTLD-TAU, MAPT Mutations and RNA Expression Analyses Tau protein is the first known and best studied contributor to FTLD. The identification of mutations within MAPT gene, encoding for tau protein, has provided compelling evidence for its causative role in the disease. FTLD-TAU has a deep clinical and neuropathological overlap with parkinsonism, especially with progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). In addition, tau inclusions are also present in other neurodegenerative diseases such as Alzheimer’s disease [Dickson et al., 2011]. Tauopathies are subclassified according to the predominant species of tau that accumulates in brain tissues with respect to alternative splicing of MAPT, with tau proteins containing three (3R) or four repeats (4R) of ∼32 amino acids in the microtubule binding domain. In the rarer Pick’s disease (PiD), with a circumscribed lobar atrophy, 3R tau predominates,
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whereas 4R tau is characteristic of parkinsonism, CBD and PSP. Therefore, tau is a natively unfolded protein acting as microtubule assembler and stabilizer [Goode and Feinstein, 1994] and the number of repeats (3R versus 4R) can modulate its affinity for the microtubule surface. The discovery of MAPT mutations linked to FTD was an important breakthrough for understanding tau function and its role in neurodegenerative diseases. MAPT mutations can be distinguished into missense mutations affecting the normal microtubule stabilization, and intronic or coding mutations affecting the splicing of exon 10 at the mRNA level, resulting in a change in ratio of 3R to 4R tau isoforms [Goedert et al., 1989]. Thus, depending upon the specific mutation, familial FTLD-TAU presents large clinical phenotype variability and has been associated with 3R, 4R or a combination of 3R and 4R tau pathology. During the last decade, an increased understanding of how the posttranslational modifications of tau affect its function has led to a growing interest in developing drugs that target pathological tau [Brunden et al., 2010]. Prevention of mis-splicing, hyperphosphorylation, aggregation, and clearance of tau aggregates are currently promising therapeutic targets for interfering with tau-induced toxicity and neurodegeneration. Despite the increased understanding of the molecular mechanisms involved in tau pathology, only few studies have so far focused on gene expression profiling in FTLD-TAU. Bronner et al. [2009] constructed genome-wide expression profiles from snap frozen post-mortem tissues from the medial temporal lobe of patients with four tau neurodegenerative disorders (5 AD, 5 PSP, 5 PiD and 5 FTD patients) and five healthy controls. They found a set of 166 genes whose expression could discriminate between neurological disorders and normal aging; disease-specific gene sets were differentially expressed in each of the four disorders. A similar study by Hauser et al. [2005], conducted a microarray expression analysis of post-mortem substantia nigra samples from parkinsonism and controls. Due to the small sample size, including only two PSP and only one FTLD-TAU patient, the study did not find specific candidate genes for FTLD-TAU; however, it showed commonly reduced COX4I1 and ATP1B1 levels in both tauopathies. In addiction the study showed an increased expression of heat shock proteins HSPA1A and HSPA1B in Parkinson’s disease, PSP and FTLD-TAU compared with controls, indicating that this may be a common stress response to mitigate the toxic effects of a misfolded protein. Integrated microarray, qPCR, confocal microscopy and immunoblotting studies have shown that the moderately aged hTau mouse may explain the gene expression level changes found in
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human tauopathies. Specifically, progressive gene and protein level changes were identified in a vulnerable hippocampal cell type critical for learning and memory [Alldred et al., 2012].
Further Studies Kudo et al. [2010] developed an integrative approach using an animal model, postmortem human material and a combination of high-throughput microarray methods to identify novel molecular markers of ALS. They identified genes located within a linkage region associated with familial ALS/FTD. This large-scale gene and protein expression study identified distinct molecular mechanisms of TAU- and SOD1induced motor-neuron degeneration including several new ALS relevant proteins (CNGA3, CRB1, OTUB2, MMP14, SLK, DDX58, RSPO2) and putative blood biomarkers, including NEFH, PRPH and MGII. Eigenanatomy and sparse canonical correlation analysis (SCCAN) is another promising approach to identify associations between SNPs and neuroanatomical structure in neurological disease. McMillan et al. [2014] applied this method in FTLD identifying rs8070723 (in MAPT) as associated with gray matter variance in temporal cortex and rs1768208 (in MOBP), rs646776 (near SORT1) and rs5848 (in PGRN) in the midbrain and superior longitudinal fasciculus white matter variance. The recent publication of the largest genomewide association study in FTLD [Ferrari et al., 2014] suggested that immune system processes linked to 6p21.3 were potentially involved in the disease. In addition, the association of FTLD with the 11q14 locus, encompassing RAB38/CTSC genes related to lysosomal biology, provided a new perspective in FTLD pathophysiology. Functional studies will be important for confirming these observations, and for linking these genes with previously known genes implicated in FTD. The expression quantitative trait loci analyses performed on PSP represented a fine example for integrating genetics and functional analyses and should be replicated for the new genes FTLD-associated genes emerging from GWAS.
CONCLUSION
The growing interest in FTLD has led to important findings in genetics and molecular biology. Despite the improved understanding of its pathological and molecular basis; however, FTLD remains an orphan disorder with no disease-modifying therapies being available. The studies cited in this brief overview provide an interesting but fragmentary list of genes and Drug Dev. Res.
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miRNAs, the role of which in FTLD should be more thoroughly investigated, ideally with animal models. However, the integration between molecular models, in vivo analyses, and clinical genetics and molecular studies is mandatory in order to identify promising new therapeutic targets. A recent example in the field from Santiago et al. [2014] was focused on the identification new PSP biomarkers. The study integrated GWAS data cluster analyses with microarray findings obtained from blood samples, and identified PTPN1 as a novel candidate FTLD biomarker. Future steps in FTLD research will require a common platform where all genetic, clinical and gene expression data findings, obtained in brain and peripheral issues, can be shared by the research community. New genetic techniques such as NGS are promising but also need integration with clinical and molecular findings and with systems biology. Thus, bioinformatics studies and integrative database research will probably be the key for finding therapeutics for this complex CNS disorder. ACKNOWLEDGMENTS
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