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Volume 4, Issue 5


Epigenetic drugs in Alzheimer’s disease

Mar Cuadrado-Tejedor
  • Corresponding author
  • Cell and Molecular Neuropharmacology, Neurosciences Division, Center for Applied Medical Research, CIMA, University of Navarra, Av. Pio XII 55, E-31008 Pamplona, Spain
  • Department of Anatomy, School of Medicine, University of Navarra, Pamplona, Spain
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Julen Oyarzabal
  • Small Molecule Discovery Platform, Center for Applied Medical Research, CIMA, University of Navarra, Av. Pio XII 55, E-31008 Pamplona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ María Pascual Lucas
  • Cell and Molecular Neuropharmacology, Neurosciences Division, Center for Applied Medical Research, CIMA, University of Navarra, Av. Pio XII 55, E-31008 Pamplona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Rafael Franco
  • Cell and Molecular Neuropharmacology, Neurosciences Division, Center for Applied Medical Research, CIMA, University of Navarra, Av. Pio XII 55, E-31008 Pamplona, Spain
  • Department of Biochemistry and Molecular Biology, Universitat de Barcelona, Barcelona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Ana García-Osta
  • Cell and Molecular Neuropharmacology, Neurosciences Division, Center for Applied Medical Research, CIMA, University of Navarra, Av. Pio XII 55, E-31008 Pamplona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2013-07-27 | DOI: https://doi.org/10.1515/bmc-2013-0012


Epigenetic processes, such as DNA methylation and histone acetylation, regulate the genome-environment interactions that may play important roles in a wide range of brain disorders, including Alzheimer’s disease (AD). Indeed, the role of epigenetic machinery in learning and memory processes is well documented. In this review, we will focus on the most recent literature on tools that target epigenetic mechanisms, particularly on histone acetylation, and we will discuss the use of chemical probes to validate these targets in therapeutic strategies for AD.

Keywords: amyloid; histone acetylation; memory; tau phosphorylation


Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterised by memory loss and cognitive impairment, which is the most common form of dementia in the elderly, with over 35 million cases worldwide (1). Pathologically, AD is characterised by the presence of extracellular plaques of aggregated amyloid-β peptide in the brain and intracellular neurofibrillary tangles that mainly contain hyperphosphorylated tau protein. These pathological features are associated with neuronal dysfunction that ultimately leads to neuronal loss, as observed in the atrophic brain of AD patients. No effective treatment for AD exists, and the effectiveness of current FDA-approved AD treatments that target cholinergic and glutamatergic neurotransmission to improve symptoms is debatable. Thus, it is critical to develop new disease management/treatment strategies, particularly given the increasing prevalence of AD among an ageing population. The search for effective AD management strategies has largely centred on the amyloid-β (Aβ) hypothesis, focusing mainly on reducing the number of senile plaques. This approach has had little success to date and there is a growing belief that current AD treatments are prescribed far too late to significantly slow disease progression or delay the onset of the most severe symptoms. The continued failure of these therapies indicates that new alternatives, non-amyloid-based strategies, must be considered to restore memory function in AD.

Sporadic or late-onset forms AD are associated with ageing and they represent the majority of AD cases (90–95%), with familial forms associated with mutations in amyloid precursor protein (APP) or presenilin (PS1 and PS2) genes accounting for the remaining 5% (2). The majority of AD cases are thus of a multifactorial nature, and they are likely to involve complex gene-gene and gene-environment interactions (3). In line with this, environmental factors are now thought to epigenetically modify the expression of genes that contribute to the pathogenesis of AD through different mechanisms. Moreover, as epigenetic processes are involved in both ageing and cognitive functions (4, 5), and gene transcription and protein synthesis are required for the formation of new synapses associated with memory formation (6), it is possible that memory deficits in AD result from altered chromatin plasticity mediated by epigenetic mechanisms, such as histone acetylation. Epigenetic processes are dynamic and can be manipulated by both environmental factors and pharmacological tools. Moreover, gene expression can be modulated by epigenetic events, including histone modifications and DNA methylation, or epigenetic modifiers such as microRNAs and long non-coding RNAs, either individually or in combination. Here, we discuss the literature on DNA methylation and microRNAs in the context of age-associated neurodegeneration and AD. Specifically, we focus on histone acetylation, which is the most studied marker of epigenetic changes in AD. Finally, we review the most recent literature on epigenetic drugs that may be relevant to develop novel therapeutic strategies to treat AD.

Epigenetics in Alzheimer’s disease: therapeutic approaches

DNA methylation

In differentiated cells DNA methylation is a more stable epigenetic marker than histone modifications. DNA methyltransferases (DNMTs) are enzymes that establish and maintain DNA methylation, catalysing the transfer of a methyl group from S-adenosyl-methionine to cytosine residues within CpG-rich regions of the genome. DNMT1 is expressed strongly in neurons and it acts as a maintenance methyltransferase, whereas DNMT3a and DNMT3b act as de novo methyltransferases (7, 8).

Approximately 70% of CpG dinucleotides within the human genome are methylated. Methylated cytosine residues impair the transcription machinery and they are usually associated with the silencing of gene expression (9). DNA methylation in the brain is a reversible and dynamic process, and it is altered during physiological processes such as memory acquisition. Furthermore, given its reversible and dynamic nature, DNA methylation can be modified pharmacologically [review in (10)]. However, before using DNA methylation as a therapeutic option it is important to understand the alterations in DNA methylation involved in a given disease.

Some AD-related genes, such as the APP gene, undergo methylation in AD patients (11). Age-linked decreases in methylcytosine levels have been reported in the APP promoter, which has a guanine-cytosine (GC) content of 72% (12). DNA methylation also mediates the expression of β-secretase (BACE) and presenilin 1 (PS1) genes, secretases involved in Aβ production, and consequently, this manifestation influences amyloid levels (13). A decrease in methylcytosine and DNMT1 immunoreactivity was recently reported in AD patients, suggesting that the loss of DNA methylation promotes aberrant APP expression, which in turn contributes to AD pathology (14). An inverse correlation between methylcytosine levels and neurofibrillary tangles has also been reported in neurons, suggesting that DNA methylation is attenuated in AD (14). Moreover, twin studies of late-onset-AD revealed significantly lower levels of DNA methylation in the neuronal nuclei of the temporal neocortex of the AD twin. These findings are consistent with the hypothesis that epigenetic mechanisms, at the molecular level, mediate the effects of life events on AD risk, and they provide a potential explanation for AD discordance despite genetic similarities (15). However, a study using a quantitative assay to measure DNA cytosine methylation reported no significant differences in the relative methylation of CCGG sites in brain DNA from 44 AD patients compared with 20 controls (16). By contrast, the expression of a variety of epigenetic markers is reduced in neurons within layer II of the entorhinal cortex, both in AD patients and APP transgenic mice (14).

Vitamin B12 and folate play important roles in DNA methylation as both coenzymes are required for the synthesis of methionine and S-adenosyl-methionine from homocysteine. S-adenosyl-methionine is a methyl donor required for the maintenance of DNA methylation. A lack of dietary vitamin B12 and folate enhances homocysteine and DNA hypomethylation in both rats and humans (17, 18), and deficiency in these nutrients during pregnancy increases the risk of neural tube defects (e.g., spina bifida) due to aberrant DNA methylation (19). Epidemiological studies also indicate that low folate and high homocysteine levels are risk factors for cognitive decline or AD in later life (20, 21). Folate levels are decreased in the CSF of AD patients (22), and the age-associated decrease in APP promoter methylation (12) has been linked to decreases in folate and vitamin B12 levels. In line with these findings, folate deprivation in vitro induces DNA hypomethylation that promotes the expression of BACE and PS1 (13), while vitamin B deprivation accelerates the progression of Alzheimer’s-like features in APP transgenic mice (23).

An attempt to improve the status of overall one-carbon metabolism by dietary vitamin B supplementation had no positive effects in AD patients (24, 25). However, dietary supplementation with a cocktail of folate, vitamin B6, S-adenosylmethione, N-acetyl cysteine and acetyl-l-carnitine has been shown to improve memory and the performance of daily activities in AD patients (26).

Therapeutic approaches that target DNA methylation have been applied to cancer and other diseases but, to date, they have not been extended to the treatment of neurological disorders. It was originally thought that the pattern of DNA methylation remained stable and that de novo methylation did not occur in fully differentiated cells like neurons, and thus, that DNA methylation inhibitors would have no impact on the brain [reviewed in (27)]. However, it now appears that a balance exists between methylation and demethylation in postmitotic cells, including neurons. Therefore, the development of small-molecule DNMT inhibitors that interact directly with DNMTs and that are not incorporated into DNA, such as the classic inhibitor 5-AZA, could have significant potential as modulators of DNA methylation, even in neurons.

Non-coding RNAs

Non-coding RNAs (ncRNAs) regulate chromatin architecture and gene expression, and they have recently been attributed a role in AD as they participate in important functions in brain development and cognition. Differences in miRNA expression profiles have been demonstrated between sporadic AD patients and age-matched controls [reviewed in (28)], although it remains to be determined whether these changes are a cause or consequence of the disease process. The regulation of APP expression through its 3’UTR is influenced by several miRNA-binding sites, cis-acting regulatory elements and binding proteins, and single-nucleotide polymorphisms (SNPs). The levels of miRNA-101, which negatively regulates APP, are reduced in the cortex of AD patients’ brains (29, 30). BACE1 β-secretase mRNA expression is regulated by both miRNAs (miRNA-107) and long ncRNAs, such as BACE1-antisense (BACE1-AS) (29). BACE1-AS improves BACE stability and it is upregulated in AD brains (31). Systemic injection of targeted exosomes was recently used successfully to deliver siRNAs that silence BACE1 expression in the mouse brain (32). Although the efficacy of RNA interference in the central nervous system (CNS) must still be determined, recent findings point to non-coding RNAs as a new class of potential drug targets in neurodegenerative diseases. However, before investigating the therapeutic potential of miRNAs, it is necessary to develop new delivery methods to ensure stable expression and minimal toxicity, particularly for chronic treatment regimens such as those required for neurodegenerative disorders.

Histone modifications

Histones are basic proteins that regulate chromatin compaction and that undergo post-translational epigenetic modifications via acetylation, methylation, phosphorylation, ubiquitination or sumoylation. Histone acetylation and phosphorylation have been linked to transcriptional activation, while trimethylation of histone-3K4 is associated with gene silencing. In this section we will focus on histone acetylation, as this is the most extensively studied epigenetic modification in AD.

Histone acetylation is controlled by the opposing actions of two different types of enzyme that modulate gene expression: HATs and HDACs (33–35). Histone acetylation results in a less tightly packaged chromatin structure that is associated with transcriptional activation, as well as learning and memory processes (36). Increases in histone acetylation have been described following exposure to different learning paradigms (37–41) and HDAC inhibition enhances hippocampus-dependent memory formation (33, 37, 42, 43). Moreover, dysregulation of histone acetylation has been described in the brains of cognitively impaired AD mouse models (44, 45) and human AD patients (19).

Histone deacetylases

The induction of histone acetylation following the inhibition of histone deacetylases (HDACs) has been proposed as a potential therapeutic strategy to treat memory decline in AD (46, 47), as successfully demonstrated in several AD mouse models (44, 48–52). However, it remains unclear which HDAC subtypes are involved in the pathophysiology of AD. HDAC enzymes are divided into four classes: class I consists of HDAC1, 2, 3 and 8; class II is divided into two subclasses, class IIa (HDAC4, 5, 7 and 9) and class IIb (HDAC6 and 10); class III is composed of a group of proteins known as sirtuins (1–7); and the sole member of class IV is HDAC11. The function of class I and II HDACs in the nervous system has been the subject of much research (53) and most HDAC inhibitors tested in AD mouse models target both classes (Table 1 summarises the different HDAC inhibitors tested in AD to date and their selectivity for different classes of HDACs).

Table 1

HDAC inhibitors tested in AD.

Class I and class II HDACs

Although the distribution of individual HDACs in the CNS is not well defined and their role in memory varies, it is clear that class I HDACs do influence memory processes. Moreover, both HDAC2 and HDAC3 have been shown to regulate learning and memory. Indeed, memory functions are enhanced when mice lack HDAC2 and HDAC3 in the hippocampus, while those that lack HDAC1 have no obvious phenotype (54, 55), although a recent study implicated HDAC1 in the extinction of contextual fear memories (56). No role has been demonstrated for HDAC8 in learning and memory. Concerning the class IIa HDACs, Agis-Balboa et al. (57) showed that impaired spatial memory formation was evident in HDAC5-/- mice although inhibition of HDAC5 failed to improve memory deficits or pathogenesis in a mouse model of amyloid pathology. In contrast, no changes in learning and memory in HDAC5-/- mice have been reported by other authors, despite defining spatial memory, impairment in conditional brain-specific HDAC4 knockout mice was encountered (58). No causative role in cognition has been described for other HDACs, although inhibition of HDAC6, a class IIb HDAC, ameliorates cognitive deficits in a mouse model of AD (59). HDAC6 is a unique member of the HDAC family that acts on cytoplasmic non-histone substrates, primarily α-tubulin (60), and has been implicated in cytoskeletal stability and intracellular transport (61).

There are higher levels of HDAC2, but not HDAC1 or HDAC3, in the hippocampus of AD mouse models and in the hippocampus and entorhinal cortex of AD patients (62). There is also more HDAC6 expression levels in postmortem tissue samples from AD patients (63), consistent with the decreased tubulin acetylation concentration observed in neurons from the brains of AD patients (64). These findings indicate that HDAC2 is one of the main targets of pan-HDAC inhibitors to counteract cognitive decline in AD, although effects on non-histone proteins such as α-tubulin via HDAC6 inhibition may also be involved. Many HDAC inhibitors tested in AD transgenic mice are non-selective and ameliorate or even reverse memory deficits in multiple AD mouse models, including sodium butyrate (NaBu), sodium phenylbutyrate (PBA), valproate and tricostatin A (see Table 1 for details) (44, 49, 51, 52, 65).

The influence of HDAC inhibition on spatial and contextual fear memory was first tested effectively in a mouse model of AD (Tg2576) using PBA, a pan-HDAC inhibitor (HDACi) that specifically inhibits class I and IIb HDACs and that also acts as a chemical chaperone (44, 49). Both chaperone activity and HDAC6 inhibition may be at least partially involved in memory restoration in PBA-treated Tg2576 mice. However, the fact that similar effects are observed in different AD mouse models (Table 1) treated with NaBu, Ms-275 or valproate (19, 51, 52, 65, 66), specific inhibitors of class I HDACs, strongly suggests that the inhibition of class I HDACs, and more specifically the HDAC2 that is upregulated in AD, are involved in the recovery of memory. Thus, although amyloid-β and pTau may not be affected by HDAC2 inhibition, restoring the transcription of plasticity-related genes appears to ameliorate the symptoms of dementia, even after disease onset in AD patients.

It should be noted that although AD is a multifaceted disorder in which memory decline is the main symptom, the aggregation of misfolded proteins such as amyloid-β and pTau ultimately leads to the loss of neurons, the main cause of AD pathology. The effect of HDACis on amyloid and/or pTau pathology has been addressed in different studies using a variety of in vivo and in vitro models of AD (see Table 1 for details). Beneficial effects have been observed with non-selective HDACis (targeting class I and II HDACs) that decrease the levels of both pTau and amyloid-β levels in different models of AD such as PBA and valproate (44, 49, 50, 65, 67, 68). In vitro assays provide better opportunities to elucidate the mechanism of action of different drugs. In a recent study, we compared the effects of PBA (which inhibits class I and IIb HDACs) with those of NaBu (a selective inhibitor of class I HDACs) in primary cultures of neurons from Tg2576 mice. Decreased levels of Aβ42 and its precursor C99 were observed in the conditioned media from PBA-treated but not NaBu-treated neurons (68). As NaBu selectively inhibits class I HDACs, these findings suggest that amyloid pathology is ameliorated by the inhibition of class IIb HDACs (including HDAC6 and HDAC10) but not class I HDACs. While the chemical chaperone activity of PBA may influence the amyloid pathology (68), a recent study reported that a mercaptoacetamide-based class II HDACi diminished Aβ levels in vitro and in vivo by modulating APP processing (69). Thus, class II HDAC inhibitors, particularly those that target class IIb HDACs like PBA, may also modulate amyloid pathology and should be considered as potential novel agents to treat AD.

Interestingly, both PBA and valproate modulate GSK3β activity and reduce tau hyperphosphorylation, the latter representing another key event in AD pathogenesis (44, 49, 67, 68). Both of these compounds produce chaperone-like effects, reducing endoplasmic reticulum stress (49, 67, 68). Although the role of HDAC inhibition on tau phosphorylation remains unclear, as tau phosphorylation was significantly decreased in primary cultures of neurons of Tg2576 mice exposed to either PBA or NaBu (a selective class I HDACi) for 3 days (68), the modulation of tau phosphorylation through the inhibition of class I HDACs cannot be ruled out. Decreased pTau levels have also been reported in 3xTgAD mice treated with selective inhibitors of class II HDACs (69). HDAC6 (class IIb) mediates microtubule stability by increasing α-tubulin acetylation, a mechanism potentially involved in the decrease in tau phosphorylation detected following exposure to pan-HDACis that target this enzyme. It is important to emphasise that tau interacts with HDAC6, inhibiting its deacetylase activity and leading to increases in tubulin acetylation (70). However, treatment with tubacin (a selective HDAC6 inhibitor) does not impair this interaction but attenuates tau phosphorylation (63). Taken together, these findings point to HDAC6 as a promising therapeutic target in AD.

Finally, given that neuronal loss is one of the key features of AD in the human brain, the neuroprotection putatively offered by HDACis suggests they have additional relevant properties. VPA is neuroprotective in several models of neurodegenerative diseases [reviewed in (71)] and long-term treatment with PBA but not NaBu prevents neuronal loss in the CA1 hippocampal layer of TghAPPWT mice (68). The multimodal action of PBA and VPA, as pan-HDACis and chemical chaperones, may contribute to this effect (68, 71). Thus, the evidence available suggests that HDAC inhibition is a promising and novel strategy for AD therapy, acting through a multi-target mechanism that involves epigenetic regulation, chromatin remodeling (promoting memory restoration) and regulation of proteostasis (affecting signalling cascades triggered by Aβ and pTau: Figure 1).

Scheme showing potential benefits obtained by modifying histones and α-tubulin acetylation in AD. HDAC, histone deacetylase; HAT, histone acetyltransferase; Ac, Acetylation;  activation;  inhibition.
Figure 1

Scheme showing potential benefits obtained by modifying histones and α-tubulin acetylation in AD. HDAC, histone deacetylase; HAT, histone acetyltransferase; Ac, Acetylation;



Class III HDACs, also known as sirtuins, have attracted considerable attention over the last decade because of their role as epigenetic regulators of ageing. Unlike other classes of HDACs, sirtuins do not require zinc as a co-factor but they are dependent on NAD+ for catalysis (72). SIRT1 is the best characterised sirtuin, and it is necessary to maintain synaptic plasticity, learning and memory. Pharmacological regulation of SIRT1 can effectively reverse the ageing process and lower the incidence of age-related complications in rodent models. Indeed, recent studies have demonstrated the therapeutic potential of dietary compounds that increase the activity of SIRT1, including resveratrol, leptin and curcumin [reviewed in (73)]. In the inducible p25 transgenic mouse, increased SIRT1 activity caused by lentiviral overexpression of SIRT1 or resveratrol treatment protects against hippocampal neurodegeneration, and prevents learning and memory deficits (74). Moreover, SIRT1 is decreased in the parietal cortex of AD patients, an alteration that may be associated with their amyloid-β and pTau accumulation (75). By contrast, the role of sirtuins in ameliorating AD-like symptoms in animal models remains controversial. Overexpression of SIRT1 is reported to reduce Aβ production and amyloid burden in a mouse model of AD (76), and several studies have provided evidence of anti-amyloidogenic properties of the SIRT1 activators resveratrol or curcumin [reviewed in (77)]. However, nicotinamide, a competitive sirtuin inhibitor, restores cognition and decreases tau phosphorylation in the 3xTgAD mouse model without affecting amyloid levels (78), indicating that the decrease in tau phosphorylation may be related to SIRT2 inhibition given that it has been shown to act as an α-deacetylase (79). Thus, activation of SIRT1 and inhibition of SIRT2 by distinct mechanisms appears to modulate AD-like features (amyloid-β and pTau) in mouse models of this disease (80).

Histone acetyltransferases (HAT)

The use of pan-HDAC inhibitors is limited by their toxicity, although an alternative means of restoring the transcriptional balance and protein acetylation would be to use histone acetyltransferase (HAT) activators. Thus, stimulation of acetyltransferase activity is another potential tool to treat neurodegenerative diseases and the specificity in restoring chromatin may be enhanced by targeting HATs than by inhibiting HDACs (81).

HATs involved in memory formation include p300, the cAMP-response element binding protein (CBP), and the p300/CBP-associated factor (PACAF). The intrinsic HAT activity of P300 and CBP, and their recruitment of the basal transcriptional machinery to the promoter indicates that these genes regulate gene expression directly. CBP loss of function has been reported in several diseases characterised by neurological deficits, including Rubinstein-Taybi syndrome and polyglutamine-related pathologies (e.g., Huntington’s disease) (82, 83). Morris water maze training induces CBP, p300 and PCAF mRNA expression in the rat hippocampus, supporting the important role of these HATs in memory processing [reviewed in (81)]. Furthermore, CBP overexpression restores memory function in 3xTg-AD triple transgenic mice (84).

Together, these data suggest that targeting these HATs (CBP, p300 and PCAF) is a more specific means of enhancing memory than the use of the currently available non-selective HDAC inhibitors (see Figure 1). Nonetheless, the HAT activators described to date exhibit poor solubility and membrane permeability, and they are therefore unsuitable candidates to treat neurodegenerative and/or neurological disorders. The best characterised HAT activator is N-(4-chloro-3-trifluoromethyl-phenyl)-2-ethoxy-6-pentadecyl-benzamide (CTPB) (85), a small-molecule modulator of the p300 histone acetyltransferase that induces structural alterations in p300 acetyltransferase. However, CTPB is cell impermeable and must be bound to carbon spheres (CSP) if it is to be used in cell systems, in which it promotes p300 autoacetylation and transcription (86). Furthermore, intra-peritoneal injection of CSP-CTPB induces hyperacetylation of histone 3 in the mouse brain, indicating its ability to cross the blood-brain barrier (BBB) (86). A recent patent application covers the use of HAT activators to enhance learning and memory, as well as cognition, and to treat neurodegenerative disorders and diseases involving accumulation of the amyloid-beta peptide and tau protein (87).

By contrast, there is evidence that HAT inhibition is beneficial in models of AD. While the p300 inhibitor, C646, reduces levels of acetylated and phosphorylated tau in vitro (88), gallic acid and/or curcumin, two polyphenol HAT inhibitors, activate SIRT1 (89) and ameliorate amyloid pathology by alleviating inflammatory progression (90–92). By modulating different signalling pathways, such as those dependent on NF-kappaB and mitogen-activated protein kinase, polyphenols exert antioxidant and anti-inflammatory effects that may be beneficial in neurodegenerative disorders such as AD [reviewed in (89)].

Epigenetics: chemical tools

A lack of mechanistic rigour in the selection and validation of therapeutic targets has contributed to a crisis in drug discovery. It is essential for chemical probes to be used to investigate the relationship between such targets and the biological processes involved in disease pathogenesis to achieve rigorous preclinical target validation (93). Medicinal chemistry can provide selective chemical probes to assess target engagement, the corresponding functional pharmacology, and the relevant phenotypes when targets have not yet been validated for clinical applications.

As illustrated above, certain epigenetic processes are promising targets for the treatment of AD, although the identification and validation of these targets requires an investment of time, resources and money before any drug discovery programmes can be launched. Therefore, the development of selective chemical probes and relevant assays is critical to ensure the success of this strategy and to develop new AD therapies. In this section we will discuss some the most important epigenetic-based chemical tools.

DNA methylation inhibitors

Many DNMT inhibitors have been described to date, compounds that can be divided into two families: nucleoside analogues that have been studied for many years; and non-nucleoside inhibitors whose structure varies according to their inhibitory mechanism. While nucleoside-like inhibitors have been approved by the FDA, their lack of specificity and strong secondary effects highlight the urgent need for more selective, novel DNMT inhibitors.

In recent years, non-nucleoside molecules have emerged as potential candidates to be used in the CNS, as their mechanism of action does not rely on their incorporation into DNA (94). Several novel DNMT inhibitors of different origins and structures have been described in recent years. Curcumin derivatives are particularly potent, and they have been shown to inhibit the bacterial C5 DNA methyltransferase M. SssI [1] (95) and its derivatives with an IC50 of ∼30 nm (Figure 2). RG-108 [2] (96), a compound identified through virtual screening, inhibits M. SssI and human DNA methylation in HCT116 and NALM6 (leukaemia) cells at 100 μm (Figure 2). After bisulfite conversion of the genome of RG108-treated cells, demethylation of gene promoters could be detected by sequencing after treatment. Moreover, unlike other DNMT inhibitors, RG108 is neither genotoxic nor cytotoxic (94, 96). Finally, by competing with S-adenosylmethionine (SAM) in the methylation reaction and acting as a competitive inhibitor of the SAM co-factor, SGI-1027 [3] (97) mediates the selective degradation of DNMT1, producing few or no effects on DNMT3A and DNMT3B (Figure 2). Because of the highly conserved I and X motifs involved in the recognition of the SAM co-factor (94, 97), all DNMTs are inhibited by SGI-1027 with a comparable IC50 (6–13 μm).

Non-nucleoside inhibitors of DNMTs. (A) Curcumin, (B) RG-108 and (C) SGI-1027.
Figure 2

Non-nucleoside inhibitors of DNMTs. (A) Curcumin, (B) RG-108 and (C) SGI-1027.

Most known non-nucleoside inhibitors are compounds with demonstrated biological activity against targets other than DNMTs, although none have yet entered clinical development (94). Thus, further studies will be necessary to identify novel, selective (in terms of off-target promiscuity and isoform selectivity) and potent non-nucleoside DNMT inhibitors in order to validate DNMTs as therapeutic targets.

HDAC inhibitors

A large set of HDAC inhibitors have already been tested in AD mouse models (Table 1) and in vitro biochemical profiling has demonstrated that these compounds display distinct selectivity for different HDAC classes. For example, SAHA [4] targets class I and IIb HDACs (IC50 of 30–410 nm for all isoforms), MS-275 [5] is a selective class I inhibitor that targets HDAC1, HDAC2 and HDAC3 (IC50<370 nm) and W2 [6] is a selective class IIb inhibitor with an IC50 for HDAC6 of 21 nm (>1.5 log units difference compared to the next most active isoforms: HDAC5 and HDAC11) (50). These inhibitors display a common pharmacophore that consists of a chelator (zinc-binding group, ZBG), a linker domain and a surface recognition domain (Figure 3). While the zinc-binding domain is critical for the catalytic activity, different structural motifs may confer selectivity to specific classes of HDACs.

The three key pharmacophore features of inhibitors of class I and II HDACs. (A) SAHA (also known as Vorinostat or Zolinza®, approved by the FDA); (B) MS-275; and (C) W2. Structures are colour-coded according to the features of each region.
Figure 3

The three key pharmacophore features of inhibitors of class I and II HDACs.

(A) SAHA (also known as Vorinostat or Zolinza®, approved by the FDA); (B) MS-275; and (C) W2. Structures are colour-coded according to the features of each region.

Assessing the activity of these compounds in vivo may allow us to elucidate the optimal means to treat AD, although given that it is most likely that chronic treatment will be necessary, greater selectivity may be required in order to determine the specific effects of each isoform, in terms of both efficacy and safety. A new generation of selective chemical probes will therefore be required to minimise the polypharmacology (unwanted off-target effects) of HDACs, and to identify and validate the most relevant HDAC isoform(s) for AD treatment. Potent HDAC6 inhibitors have recently been described (98–100) that have a selectivity ∼2 log units better than the next most active isoforms, such as tubastatin A [7] (Figure 4). The selectivity of tubastatin A is attributed to the specific interactions between the unique capping motif and the surface topology of HDAC6. Moreover, tubastatin A [7] has recently been used as a chemical probe, and in this way HDAC6 was shown to be a unique potential therapeutic target for AD and related neurodegenerative tauopathies (101).

TFMO-compound 1 is a selective inhibitor of class IIa HDACs, with a novel zinc-binding mode of action [8] (Figure 4) that circumvents the selectivity and pharmacologic liabilities of hydroxamates (102). These cell-active chemical probes are important tools in the HDAC inhibitor field, and they help precisely define class IIa HDAC catalytic and/or acetyl-lysine activity.

HAT activators

A recent patent describes compound I [9] as a HAT activator (Figure 5) and in vitro assays show this molecule to target CBP with an EC50 of 2.75 μm. Compound I [9] is over 1 log unit more selective than PCAF and GCN5, and it does not inhibit any of the HDACs tested (10 isoforms assayed from classes I, IIa, IIb and III) (87). Given its pharmacokinetic profile and ability to cross the BBB, together with its pharmacological activity in vivo (increasing histone 3 acetylation levels in the hippocampus) and lack of toxicity after chronic treatment (87), compound I [9] appears to represent an important pharmacological tool for use in vivo, promising to be exceedingly useful for validating HAT targets (in this case CBP) in AD mouse models. However, further work is required to elucidate the role of each HAT in AD, for which more potent and selective chemical probes will be required.

HAT activators.
Figure 5

HAT activators.


In conclusion, an increasing number of chemical tools have emerged that may aid the validation of epigenetic targets. However, careful characterisation of chemical probes is essential to ensure that accurate biological conclusions are reached. A new generation of selective chemical probes will be required to unequivocally validate targets, thereby facilitating the development of potent and selective compounds with minimal unwanted off-target effects. The generation of information relevant to human disease requires chemical probes with optimised pharmacokinetics that are capable of crossing the BBB and that meet the current critical safety criteria. These probes will be essential pharmacological tools for in vivo target validation in the search for AD pharmacotherapies.


  • 1.

    Selkoe DJ. Preventing Alzheimer’s disease. Science 2012; 337: 1488–92.Google Scholar

  • 2.

    Ertekin-Taner N. Genetics of Alzheimer’s disease: a centennial review. Neurol Clin 2007; 25: 611–67, v.CrossrefGoogle Scholar

  • 3.

    Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE. Systematic meta–analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet 2007; 39: 17–23.CrossrefGoogle Scholar

  • 4.

    Rodriguez-Rodero S, Fernandez-Morera J, Fernandez AF, Menendez-Torre E, Fraga MF. Epigenetic regulation of aging. Discov Med 2010; 10: 225–33.Google Scholar

  • 5.

    Reichenberg, A, Mill J, MacCabe JH. Epigenetics, genomic mutations and cognitive function. Cogn Neuropsychiatry 2009; 14: 377–90.CrossrefGoogle Scholar

  • 6.

    Alberini CM. Mechanisms of memory stabilization: are consolidation and reconsolidation similar or distinct processes? Trends Neurosci 2005; 28: 51–6.CrossrefGoogle Scholar

  • 7.

    Inano K, Suetake I, Ueda T, Miyake Y, Nakamura M, Okada M, Tajima S. Maintenance-type DNA methyltransferase is highly expressed in post-mitotic neurons and localized in the cytoplasmic compartment. J Biochem 2000; 128: 315–21.CrossrefGoogle Scholar

  • 8.

    Hsieh CL. Evidence that protein binding specifies sites of DNA demethylation. Mol Cell Biol 1999; 19: 46–56.Google Scholar

  • 9.

    Razin A, Riggs AD. DNA methylation and gene function. Science 1980; 210: 604–10.Google Scholar

  • 10.

    Day JJ, Sweatt JD. DNA methylation and memory formation. Nat Neurosci 2010; 13: 1319–23.CrossrefGoogle Scholar

  • 11.

    Yoshikai S, Sasaki H, Doh–ura K, Furuya H, Sakaki Y. Genomic organization of the human-amyloid beta-protein precursor gene. Gene 1991; 102: 291–2.CrossrefGoogle Scholar

  • 12.

    Tohgi H, Utsugisawa K, Nagane Y, Yoshimura M, Ukitsu M, Genda Y. Decrease with age in methylcytosines in the promoter region of receptor for advanced glycated end products (RAGE) gene in autopsy human cortex. Brain Res Mol Brain Res 1999; 65: 124–8.CrossrefGoogle Scholar

  • 13.

    Fuso A, Seminara L, Cavallaro RA, D’Anselmi F, Scarpa S. S-adenosylmethionine/homocysteine cycle alterations modify DNA methylation status with consequent deregulation of PS1 and BACE and beta-amyloid production. Mol Cell Neurosci 2005; 28: 195–204.Google Scholar

  • 14.

    Mastroeni D, Grover A, Delvaux E, Whiteside C, Coleman PD, Rogers J. Epigenetic changes in Alzheimer’s disease: decrements in DNA methylation. Neurobiol Aging 2010; 31: 2025–37.CrossrefGoogle Scholar

  • 15.

    Mastroeni D, McKee A, Grover A, Rogers J, Coleman PD. Epigenetic differences in cortical neurons from a pair of monozygotic twins discordant for Alzheimer’s disease. PLoS One 2009; 4: e6617.CrossrefGoogle Scholar

  • 16.

    Schwob NG, Nalbantoglu J, Hastings KE, Mikkelsen T, Cashman NR. DNA cytosine methylation in brain of patients with Alzheimer’s disease. Ann Neurol 1990; 28: 91–4.CrossrefGoogle Scholar

  • 17.

    Fuso A, Nicolia V, Pasqualato A, Fiorenza MT, Cavallaro RA, Scarpa S. Changes in Presenilin 1 gene methylation pattern in diet-induced B vitamin deficiency. Neurobiol Aging 2011; 32: 187–99.Google Scholar

  • 18.

    Selhub J. Folate, vitamin B12 and vitamin B6 and one carbon metabolism. J Nutr Health Aging 2002; 6: 39–42.Google Scholar

  • 19.

    Chang H, Zhang T, Zhang Z, Bao R, Fu C, Wang Z, Bao Y, Li Y, Wu L, Zheng X, Wu J. Tissue-specific distribution of aberrant DNA methylation associated with maternal low-folate status in human neural tube defects. J Nutr Biochem 2011; 22: 1172–7.CrossrefGoogle Scholar

  • 20.

    Fischer P, Zehetmayer S, Jungwirth S, Weissgram S, Krampla W, Hinterberger M, Torma S, Rainer M, Huber K, Hoenigschnabl S, Gelpi E, Bauer K, Leitha T, Bauer P, Tragl KH. Risk factors for Alzheimer dementia in a community-based birth cohort at the age of 75 years. Dement Geriatr Cogn Disord 2008; 25: 501–7.CrossrefGoogle Scholar

  • 21.

    Seshadri S, Beiser A, Selhub J, Jacques PF, Rosenberg IH, D’Agostino RB, Wilson PW, Wolf PA. Plasma homocysteine as a risk factor for dementia and Alzheimer’s disease. N Engl J Med 2002; 346: 476–83.Google Scholar

  • 22.

    Serot JM, Christmann D, Dubost T, Bene MC, Faure GC. CSF-folate levels are decreased in late-onset AD patients. J Neural Transm 2001; 108: 93–9.CrossrefGoogle Scholar

  • 23.

    Fuso A, Nicolia V, Cavallaro RA, Ricceri L, D’Anselmi F, Coluccia P, Calamandrei G, Scarpa S. B-vitamin deprivation induces hyperhomocysteinemia and brain S-adenosylhomocysteine, depletes brain S-adenosylmethionine, and enhances PS1 and BACE expression and amyloid-beta deposition in mice. Mol Cell Neurosci 2008; 37: 731–46.Google Scholar

  • 24.

    Aisen PS, Egelko S, Andrews H, Diaz-Arrastia R, Weiner M, DeCarli C, Jagust W, Miller JW, Green R, Bell K, Sano M. A pilot study of vitamins to lower plasma homocysteine levels in Alzheimer disease. Am J Geriatr Psychiatry 2003; 11: 246–9.CrossrefGoogle Scholar

  • 25.

    Aisen PS, Schneider LS, Sano M, Diaz-Arrastia R, van Dyck CH, Weiner MF, Bottiglieri T, Jin S, Stokes KT, Thomas RG, Thal LJ; Alzheimer Disease Cooperative Study. High-dose B vitamin supplementation and cognitive decline in Alzheimer disease: a randomized controlled trial. J Am Med Assoc 2008; 300: 1774–83.Google Scholar

  • 26.

    Chan A, Paskavitz J, Remington R, Rasmussen S, Shea TB. Efficacy of a vitamin/nutriceutical formulation for early-stage Alzheimer’s disease: a 1-year, open-label pilot study with a 16-month caregiver extension. Am J Alzheimers Dis Other Demen 2008; 23: 571–85.Google Scholar

  • 27.

    Szyf M. DNA methylation and demethylation probed by small molecules. Biochim Biophys Acta 2010; 1799: 750–9.Google Scholar

  • 28.

    Schonrock N, Gotz J. Decoding the non-coding RNAs in Alzheimer’s disease. Cell Mol Life Sci 2012; 69: 3543–59.CrossrefGoogle Scholar

  • 29.

    Hébert SS, Horré K, Nicolaï L, Papadopoulou AS, Mandemakers W, Silahtaroglu AN, Kauppinen S, Delacourte A, De Strooper B. Loss of microRNA cluster miR-29a/b-1 in sporadic Alzheimer’s disease correlates with increased BACE1/beta-secretase expression. Proc Natl Acad Sci USA 2008; 105: 6415–20.Google Scholar

  • 30.

    Vilardo E, Barbato C, Ciotti M, Cogoni C, Ruberti F. MicroRNA-101 regulates amyloid precursor protein expression in hippocampal neurons. J Biol Chem 2010; 285: 18344–51.Google Scholar

  • 31.

    Faghihi MA, Modarresi F, Khalil AM, Wood DE, Sahagan BG, Morgan TE, Finch CE, St Laurent G 3rd, Kenny PJ, Wahlestedt C. Expression of a noncoding RNA is elevated in Alzheimer’s disease and drives rapid feed-forward regulation of beta-secretase. Nat Med 2008; 14: 723–30.CrossrefGoogle Scholar

  • 32.

    Alvarez-Erviti L, Seow Y, Yin H, Betts C, Lakhal S, Wood MJ. Delivery of siRNA to the mouse brain by systemic injection of targeted exosomes. Nat Biotechnol 2011; 29: 341–5.CrossrefGoogle Scholar

  • 33.

    Guan Z, Giustetto M, Lomvardas S, Kim JH, Miniaci MC, Schwartz JH, Thanos D, Kandel ER. Integration of long-term-memory-related synaptic plasticity involves bidirectional regulation of gene expression and chromatin structure. Cell 2002; 111: 483–93.CrossrefGoogle Scholar

  • 34.

    Soejima H, Joh K, Mukai T, Gene silencing in DNA damage repair. Cell Mol Life Sci 2004; 61: 2168–72.Google Scholar

  • 35.

    Clayton AL, Hazzalin CA, Mahadevan LC. Enhanced histone acetylation and transcription: a dynamic perspective. Mol Cell 2006; 23: 289–96.CrossrefGoogle Scholar

  • 36.

    Peleg S, Sananbenesi F, Zovoilis A, Burkhardt S, Bahari-Javan S, Agis-Balboa RC, Cota P, Wittnam JL, Gogol-Doering A, Opitz L, Salinas-Riester G, Dettenhofer M, Kang H, Farinelli L, Chen W, Fischer A. Altered histone acetylation is associated with age–dependent memory impairment in mice. Science 2010; 328: 753–6.Google Scholar

  • 37.

    Levenson JM, O’Riordan KJ, Brown KD, Trinh MA, Molfese DL, Sweatt JD. Regulation of histone acetylation during memory formation in the hippocampus. J Biol Chem 2004; 279: 40545–59.Google Scholar

  • 38.

    Martin KC, Sun YE. To learn better, keep the HAT on. Neuron 2004; 42: 879–81.CrossrefGoogle Scholar

  • 39.

    Chwang WB, O’Riordan KJ, Levenson JM, Sweatt JD. ERK/MAPK regulates hippocampal histone phosphorylation following contextual fear conditioning. Learn Mem 2006; 13: 322–8.CrossrefGoogle Scholar

  • 40.

    Chwang WB, Arthur JS, Schumacher A, Sweatt JD. The nuclear kinase mitogen- and stress-activated protein kinase 1 regulates hippocampal chromatin remodeling in memory formation. J Neurosci 2007; 27: 12732–42.CrossrefGoogle Scholar

  • 41.

    Fischer A, Sananbenesi F, Wang X, Dobbin M, Tsai LH. Recovery of learning and memory is associated with chromatin remodelling. Nature 2007; 447: 178–82.Google Scholar

  • 42.

    Vecsey CG, Hawk JD, Lattal KM, Stein JM, Fabian SA, Attner MA, Cabrera SM, McDonough CB, Brindle PK, Abel T, Wood MA. Histone deacetylase inhibitors enhance memory and synaptic plasticity via CREB:CBP-dependent transcriptional activation. J Neurosci 2007; 27: 6128–40.CrossrefGoogle Scholar

  • 43.

    Wood MA, Hawk JD, Abel T. Combinatorial chromatin modifications and memory storage: a code for memory? Learn Mem 2006; 13: 241–4.CrossrefGoogle Scholar

  • 44.

    Ricobaraza A, Cuadrado-Tejedor M, Pérez-Mediavilla A, Frechilla D, Del Río J, García-Osta A. Phenylbutyrate ameliorates cognitive deficit and reduces tau pathology in an Alzheimer’s disease mouse model. Neuropsychopharmacology 2009; 34: 1721–32.CrossrefGoogle Scholar

  • 45.

    Francis YI, Fa M, Ashraf H, Zhang H, Staniszewski A, Latchman DS, Arancio O. Dysregulation of histone acetylation in the APP/PS1 mouse model of Alzheimer’s disease. J Alzheimers Dis 2009; 18: 131–9.Google Scholar

  • 46.

    Abel C, Allegri RF, Garau L, Genovese O, Mangone CA. Treatment of Alzheimer’s disease cognitive symptoms. Vertex 2008; 19(Suppl): 39–47.Google Scholar

  • 47.

    Fischer A, Sananbenesi F, Mungenast A, Tsai LH. Targeting the correct HDAC(s) to treat cognitive disorders. Trends Pharmacol Sci 2010; 31: 605–17.CrossrefGoogle Scholar

  • 48.

    Ricobaraza A, Cuadrado-Tejedor M, Garcia-Osta A. Long-term phenylbutyrate administration prevents memory deficits in Tg2576 mice by decreasing Abeta. Front Biosci (Elite Ed) 2011; 3: 1375–84.Google Scholar

  • 49.

    Ricobaraza A, Cuadrado-Tejedor M, Marco S, Perez-Otano I, Garcia-Osta A. Phenylbutyrate rescues dendritic spine loss associated with memory deficits in a mouse model of Alzheimer disease. Hippocampus 2012; 22: 1040–50.CrossrefGoogle Scholar

  • 50.

    Cuadrado-Tejedor M, Garcia-Osta A, Ricobaraza A, Oyarzabal J, Franco R. Defining the mechanism of action of 4-phenylbutyrate to develop a small-molecule-based therapy for Alzheimer’s disease. Curr Med Chem 2011; 18: 5545–53.Google Scholar

  • 51.

    Kilgore M, Miller CA, Fass DM, Hennig KM, Haggarty SJ, Sweatt JD, Rumbaugh G. Inhibitors of class 1 histone deacetylases reverse contextual memory deficits in a mouse model of Alzheimer’s disease. Neuropsychopharmacology 2010; 35: 870–80.CrossrefGoogle Scholar

  • 52.

    Govindarajan N, Agis-Balboa RC, Walter J, Sananbenesi F, Fischer A. Sodium butyrate improves memory function in an Alzheimer’s disease mouse model when administered at an advanced stage of disease progression. J Alzheimers Dis 2011; 26: 187–97.Google Scholar

  • 53.

    Abel T, Zukin RS. Epigenetic targets of HDAC inhibition in neurodegenerative and psychiatric disorders. Curr Opin Pharmacol 2008; 8: 57–64.CrossrefGoogle Scholar

  • 54.

    Guan JS, Haggarty SJ, Giacometti E, Dannenberg JH, Joseph N, Gao J, Nieland TJ, Zhou Y, Wang X, Mazitschek R, Bradner JE, DePinho RA, Jaenisch R, Tsai LH. HDAC2 negatively regulates memory formation and synaptic plasticity. Nature 2009; 459: 55–60.Google Scholar

  • 55.

    McQuown SC, Wood MA. HDAC3 and the molecular brake pad hypothesis. Neurobiol Learn Mem 2011; 96: 27–34.CrossrefGoogle Scholar

  • 56.

    Bahari-Javan S, Maddalena A, Kerimoglu C, Wittnam J, Held T, Bähr M, Burkhardt S, Delalle I, Kügler S, Fischer A, Sananbenesi F. HDAC1 regulates fear extinction in mice. J Neurosci 2012; 32: 5062–73.CrossrefGoogle Scholar

  • 57.

    Agis-Balboa RC, Pavelka Z, Kerimoglu C, Fischer A. Loss of HDAC5 impairs memory function: implications for Alzheimer’s disease. J Alzheimers Dis 2013; 33: 35–44.Google Scholar

  • 58.

    Kim MS, Akhtar MW, Adachi M, Mahgoub M, Bassel-Duby R, Kavalali ET, Olson EN, Monteggia LM. An essential role for histone deacetylase 4 in synaptic plasticity and memory formation. J Neurosci 2012; 32: 10879–86.CrossrefGoogle Scholar

  • 59.

    Govindarajan N, Rao P, Burkhardt S, Sananbenesi F, Schlüter OM, Bradke F, Lu J, Fischer A. Reducing HDAC6 ameliorates cognitive deficits in a mouse model for Alzheimer’s disease. EMBO Mol Med 2013; 5: 52–63.Google Scholar

  • 60.

    Haggarty SJ, Koeller KM, Wong JC, Grozinger CM, Schreiber SL. Domain-selective small-molecule inhibitor of histone deacetylase 6 (HDAC6)-mediated tubulin deacetylation. Proc Natl Acad Sci USA 2003; 100: 4389–94.CrossrefGoogle Scholar

  • 61.

    Valenzuela-Fernandez A, Cabrero JR, Serrador JM, Sanchez-Madrid F. HDAC6: a key regulator of cytoskeleton, cell migration and cell–cell interactions. Trends Cell Biol 2008; 18: 291–7.Google Scholar

  • 62.

    Gräff J, Rei D, Guan JS, Wang WY, Seo J, Hennig KM, Nieland TJ, Fass DM, Kao PF, Kahn M, Su SC, Samiei A, Joseph N, Haggarty SJ, Delalle I, Tsai LH. An epigenetic blockade of cognitive functions in the neurodegenerating brain. Nature 2012; 483: 222–6.Google Scholar

  • 63.

    Ding H, Dolan PJ, Johnson GV. Histone deacetylase 6 interacts with the microtubule-associated protein tau. J Neurochem 2008; 106: 2119–30.Google Scholar

  • 64.

    Hempen B, Brion JP. Reduction of acetylated alpha-tubulin immunoreactivity in neurofibrillary tangle-bearing neurons in Alzheimer’s disease. J Neuropathol Exp Neurol 1996; 55: 964–72.CrossrefGoogle Scholar

  • 65.

    Qing H, He G, Ly PT, Fox CJ, Staufenbiel M, Cai F, Zhang Z, Wei S, Sun X, Chen CH, Zhou W, Wang K, Song W. Valproic acid inhibits Abeta production, neuritic plaque formation, and behavioral deficits in Alzheimer’s disease mouse models. J Exp Med 2008; 205: 2781–9.CrossrefGoogle Scholar

  • 66.

    Zhang ZY, Schluesener HJ. Oral administration of histone deacetylase inhibitor MS–275 ameliorates neuroinflammation and cerebral amyloidosis and improves behavior in a mouse model. J Neuropathol Exp Neurol 2013; 72: 178–85.CrossrefGoogle Scholar

  • 67.

    Hu JP, Xie JW, Wang CY, Wang T, Wang X, Wang SL, Teng WP, Wang ZY. Valproate reduces tau phosphorylation via cyclin-dependent kinase 5 and glycogen synthase kinase 3 signaling pathways. Brain Res Bull 2011; 85: 194–200.CrossrefGoogle Scholar

  • 68.

    Cuadrado-Tejedor M, Ricobaraza AL, Torrijo R, Franco R, Garcia-Osta A. Phenylbutyrate is a multifaceted drug that exerts neuroprotective effects and reverses the Alzheimer s disease-like phenotype of a commonly used mouse model. Curr Pharm Des 2013; 10: 390–405.Google Scholar

  • 69.

    Sung YM, Lee T, Yoon H, DiBattista AM, Song JM, Sohn Y, Moffat EI, Turner RS, Jung M, Kim J, Hoe HS. Mercaptoacetamide-based class II HDAC inhibitor lowers Abeta levels and improves learning and memory in a mouse model of Alzheimer’s disease. Exp Neurol 2013; 239: 192–201.CrossrefGoogle Scholar

  • 70.

    Perez M, Santa-Maria I, Gomez de Barreda E, Zhu X, Cuadros R, Cabrero JR, Sanchez-Madrid F, Dawson HN, Vitek MP, Perry G, Smith MA, Avila J. Tau–an inhibitor of deacetylase HDAC6 function. J Neurochem 2009; 109: 1756–66.Google Scholar

  • 71.

    Monti B, Polazzi E, Contestabile A. Biochemical, molecular and epigenetic mechanisms of valproic acid neuroprotection. Curr Mol Pharmacol 2009; 2: 95–109.CrossrefGoogle Scholar

  • 72.

    Haberland M, Montgomery RL, Olson EN. The many roles of histone deacetylases in development and physiology: implications for disease and therapy. Nat Rev Genet 2009; 10: 32–42.CrossrefGoogle Scholar

  • 73.

    Guarente L. Sirtuins in aging and disease. Cold Spring Harb Symp Quant Biol 2007; 72: 483–8.CrossrefGoogle Scholar

  • 74.

    Kim D, Nguyen MD, Dobbin MM, Fischer A, Sananbenesi F, Rodgers JT, Delalle I, Baur JA, Sui G, Armour SM, Puigserver P, Sinclair DA, Tsai LH. SIRT1 deacetylase protects against neurodegeneration in models for Alzheimer’s disease and amyotrophic lateral sclerosis. Embo J 2007; 26: 3169–79.CrossrefGoogle Scholar

  • 75.

    Julien C, Tremblay C, Emond V, Lebbadi M, Salem N Jr, Bennett DA, Calon F. Sirtuin 1 reduction parallels the accumulation of tau in Alzheimer disease. J Neuropathol Exp Neurol 2009; 68: 48–58.CrossrefGoogle Scholar

  • 76.

    Donmez, G. The effects of SIRT1 on Alzheimer’s disease models. Int J Alzheimers Dis 2012; 2012: 509529.Google Scholar

  • 77.

    Vingtdeux V, Dreses-Werringloer U, Zhao H, Davies P, Marambaud P. Therapeutic potential of resveratrol in Alzheimer’s disease. BMC Neurosci 2008; 9(Suppl 2): S6.CrossrefGoogle Scholar

  • 78.

    Green KN, Steffan JS, Martinez-Coria H, Sun X, Schreiber SS, Thompson LM, LaFerla FM. Nicotinamide restores cognition in Alzheimer’s disease transgenic mice via a mechanism involving sirtuin inhibition and selective reduction of Thr231-phosphotau. J Neurosci 2008; 28: 11500–10.Google Scholar

  • 79.

    North BJ, Marshall BL, Borra MT, Denu JM, Verdin E. The human Sir2 ortholog, SIRT2, is an NAD+-dependent tubulin deacetylase. Mol Cell 2003; 11: 437–44.Google Scholar

  • 80.

    Qin W, Yang T, Ho L, Zhao Z, Wang J, Chen L, Zhao W, Thiyagarajan M, MacGrogan D, Rodgers JT, Puigserver P, Sadoshima J, Deng H, Pedrini S, Gandy S, Sauve AA, Pasinetti GM. Neuronal SIRT1 activation as a novel mechanism underlying the prevention of Alzheimer disease amyloid neuropathology by calorie restriction. J Biol Chem 2006; 281: 21745–54.Google Scholar

  • 81.

    Selvi BR, Cassel JC, Kundu TK, Boutillier AL. Tuning acetylation levels with HAT activators: therapeutic strategy in neurodegenerative diseases. Biochim Biophys Acta 2010; 1799: 840–53.Google Scholar

  • 82.

    Murata T, Kurokawa R, Krones A, Tatsumi K, Ishii M, Taki T, Masuno M, Ohashi H, Yanagisawa M, Rosenfeld MG, Glass CK, Hayashi Y. Defect of histone acetyltransferase activity of the nuclear transcriptional coactivator CBP in Rubinstein-Taybi syndrome. Hum Mol Genet 2001; 10: 1071–6.CrossrefGoogle Scholar

  • 83.

    Giralt A, Puigdellívol M, Carretón O, Paoletti P, Valero J, Parra-Damas A, Saura CA, Alberch J, Ginés S. Long-term memory deficits in Huntington’s disease are associated with reduced CBP histone acetylase activity. Hum Mol Genet 2012; 21: 1203–16.CrossrefGoogle Scholar

  • 84.

    Caccamo A, Maldonado MA, Bokov AF, Majumder S, Oddo S. CBP gene transfer increases BDNF levels and ameliorates learning and memory deficits in a mouse model of Alzheimer’s disease. Proc Natl Acad Sci USA 2010; 107: 22687–92.CrossrefGoogle Scholar

  • 85.

    Balasubramanyam K, Swaminathan V, Ranganathan A, Kundu TK. Small molecule modulators of histone acetyltransferase p300. J Biol Chem 2003; 278: 19134–40.Google Scholar

  • 86.

    Elvi BR, Jagadeesan D, Suma BS, Nagashankar G, Arif M, Balasubramanyam K, Eswaramoorthy M, Kundu TK. Intrinsically fluorescent carbon nanospheres as a nuclear targeting vector: delivery of membrane–impermeable molecule to modulate gene expression in vivo. Nano Lett 2008; 8: 3182–8.Google Scholar

  • 87.

    Uses of histone acetyltransferase activators. WO2012/171008A1. 2012.Google Scholar

  • 88.

    Min SW, Cho SH, Zhou Y, Schroeder S, Haroutunian V, Seeley WW, Huang EJ, Shen Y, Masliah E, Mukherjee C, Meyers D, Cole PA, Ott M, Gan L. Acetylation of tau inhibits its degradation and contributes to tauopathy. Neuron 2010; 67: 953–66.CrossrefGoogle Scholar

  • 89.

    Chung S, Yao H, Caito S, Hwang JW, Arunachalam G, Rahman I. Regulation of SIRT1 in cellular functions: role of polyphenols. Arch Biochem Biophys 2010; 501: 79–90.Google Scholar

  • 90.

    Kim MJ, Seong AR, Yoo JY, Jin CH, Lee YH, Kim YJ, Lee J, Jun WJ, Yoon HG. Gallic acid, a histone acetyltransferase inhibitor, suppresses beta-amyloid neurotoxicity by inhibiting microglial-mediated neuroinflammation. Mol Nutr Food Res 2011; 55: 1798–808.CrossrefGoogle Scholar

  • 91.

    Begum AN, Jones MR, Lim GP, Morihara T, Kim P, Heath DD, Rock CL, Pruitt MA, Yang F, Hudspeth B, Hu S, Faull KF, Teter B, Cole GM, Frautschy SA. Curcumin structure-function, bioavailability, and efficacy in models of neuroinflammation and Alzheimer’s disease. J Pharmacol Exp Ther 2008; 326: 196–208.Google Scholar

  • 92.

    Hamaguchi T, Ono K, Yamada M. REVIEW: curcumin and Alzheimer’s disease. CNS Neurosci Ther 2010; 16: 285–97.CrossrefGoogle Scholar

  • 93.

    Editorial. Stay on target. Nat Chem Biol 2013; 9: 193.Google Scholar

  • 94.

    Gros C, Fahy J, Halby L, Dufau I, Erdmann A, Gregoire JM, Ausseil F, Vispé S, Arimondo PB. DNA methylation inhibitors in cancer: recent and future approaches. Biochimie 2012; 94: 2280–96.CrossrefPubMedGoogle Scholar

  • 95.

    Liu Z, Xie Z, Jones W, Pavlovicz RE, Liu S, Yu J, Li PK, Lin J, Fuchs JR, Marcucci G, Li C, Chan KK. Curcumin is a potent DNA hypomethylation agent. Bioorg Med Chem Lett 2009; 19: 706–9.CrossrefGoogle Scholar

  • 96.

    Stresemann C, Brueckner B, Musch T, Stopper H, Lyko F. Functional diversity of DNA methyltransferase inhibitors in human cancer cell lines. Cancer Res 2006; 66: 2794–800.CrossrefGoogle Scholar

  • 97.

    Datta J, Ghoshal K, Denny WA, Gamage SA, Brooke DG, Phiasivongsa P, Redkar S, Jacob ST. A new class of quinoline-based DNA hypomethylating agents reactivates tumor suppressor genes by blocking DNA methyltransferase 1 activity and inducing its degradation. Cancer Res 2009; 69: 4277–85.CrossrefGoogle Scholar

  • 98.

    Butler KV, Kalin J, Brochier C, Vistoli G, Langley B, Kozikowski AP. Rational design and simple chemistry yield a superior, neuroprotective HDAC6 inhibitor, tubastatin A. J Am Chem Soc 2010; 132: 10842–6.Google Scholar

  • 99.

    Histone Deacetylase Inhibitors. WO 2012/117421A1. 2012.Google Scholar

  • 100.

    Wagner FF, Olson DE, Gale JP, Kaya T, Weïwer M, Aidoud N, Thomas M, Davoine EL, Lemercier BC, Zhang YL, Holson EB. Potent and selective inhibition of histone deacetylase 6 (HDAC6) does not require a surface-binding motif. J Med Chem 2013. [Epub ahead of print]CrossrefGoogle Scholar

  • 101.

    Xiong Y, Zhao K, Wu J, Xu Z, Jin S, Zhang YQ. HDAC6 mutations rescue human tau-induced microtubule defects in Drosophila. Proc Natl Acad Sci USA 2013; 110: 4604–9.CrossrefGoogle Scholar

  • 102.

    Lobera M, Madauss KP, Pohlhaus DT, Wright QG, Trocha M, Schmidt DR, Baloglu E, Trump RP, Head MS, Hofmann GA, Murray-Thompson M, Schwartz B,Chakravorty S, Wu Z, Mander PK, Kruidenier L, Reid RA, Burkhart W, Turunen BJ, Rong JX, Wagner C, Moyer MB, Wells C, Hong X, Moore JT, Williams JD, Soler D, Ghosh S, Nolan MA. Selective class IIa histone deacetylase inhibition via a nonchelating zinc–binding group. Nat Chem Biol 2013; 9: 319–25.CrossrefGoogle Scholar

  • 103.

    Wiley JC, Pettan-Brewer C, Ladiges WC. Phenylbutyric acid reduces amyloid plaques and rescues cognitive behavior in AD transgenic mice. Aging Cell 2011; 10: 418–28.CrossrefGoogle Scholar

  • 104.

    Fass DM, Shah R, Ghosh B, Hennig K, Norton S, Zhao WN, Reis SA, Klein PS, Mazitschek R, Maglathlin RL, Lewis TA, Haggarty SJ. Effect of inhibiting histone deacetylase with short-chain carboxylic acids and their hydroxamic acid analogs on vertebrate development and neuronal chromatin. ACS Med Chem Lett 2010; 2: 39–42.Google Scholar

  • 105.

    Khan N, Jeffers M, Kumar S, Hackett C, Boldog F, Khramtsov N, Qian X, Mills E, Berghs SC, Carey N, Finn PW, Collins LS, Tumber A, Ritchie JW, Jensen PB, Lichenstein HS, Sehested M. Determination of the class and isoform selectivity of small-molecule histone deacetylase inhibitors. Biochem J 2008; 409: 581–9.Google Scholar

About the article

Mar Cuadrado-Tejedor

Mar Cuadrado-Tejedor got her PhD at the Anatomy Department, School of Medicine, at University of Navarra, Spain (March, 2003). After finishing her PhD she joined the Neuroscience Department at University of Navarra as a post-doctoral student (April 2003–September 2005). Assistant Professor (2003–2008) at the Department of Anatomy at School of Medicine at University of Navarra and Associate Professor of the same Department from 2008 to the present date. In September 2005 she joined the Center for Applied Medical Research (CIMA), University of Navarra as staff researcher in the laboratory of Cellular and Molecular Neuropharmacology: behaviour research that aims to study the molecular basis of dementia in Alzheimer’s disease. She is co-inventor of two patents and author of 23 publications.

Julen Oyarzabal

Julen Oyarzabal got his PhD at the Pharmaceutical and Organic Chemistry Department, School of Pharmacy, Universidad del País Vasco. After finishing his PhD in 1998, he moved to the University of California, San Francisco (USA); and later, he joined the University of Southampton (UK), where he worked in computational chemistry. In November 2001 he joined Johnson & Johnson Pharmaceutical R&D in Toledo (Spain) where he led several projects, from molecular design perspective, in the CNS therapeutic area – as senior scientist. In October 2006, after leaving J&J, he joined the Spanish National Cancer Research Centre (CNIO) at the Experimental Therapeutics programme where he set up and led the Computational Medicinal Chemistry Section as well as medicinal chemistry projects. Then, after 4 years, in September 2010 he left CNIO and joined the Center for Applied Medical Research (CIMA), University of Navarra, to set up and lead the small-molecule discovery platform: chemical biology and medicinal chemistry. He is co-inventor of 14 published patents.

María Pascual Lucas

María Pascual-Lucas is a PhD student in the Neuroscience program at University of Navarra. She received her Licentiate Degree in Biotechnology from University of Salamanca (Spain), and a Master’s Degree in Neuroscience and Cognition from Univerity of Navarra (Spain). Her research interests include understanding the role of insulin-like growth factors in AD.

Rafael Franco

Rafael Franco Fernández received his PhD in Biochemistry from the University of Barcelona. He is an expert in G-protein-coupled receptors and in signalling in the CNS via adenosine, dopamine and cannabinoid receptors and receptor heteromers. After 30 years in the University of Barcelona, as full Professor since 1996, and founder and director of the laboratory of Molecular Neurobiology of the University of Barcelona, he moved to Pamplona in October 2009 to head the Cell and Molecular Neuropharmacology laboratory at CIMA. The h index of Dr. Franco is 42, resulting from the interest raised by his more than 250 publications in prestigious journals such as: Nature Chem Biol, Nature Methods, Proc Natl Acad Sci, J Neurosc, Mol Cell Biol, J Biol Chem, etc.

Ana García-Osta

Ana Garcia-Osta got her PhD at the Pharmacology Department, School of Medicine, at University of Navarra, Spain (March, 1999). In October 2001 she moved to the Department of Neuroscience at Mont Sinai School of Medicine, New York (USA) and was there until June 2006. In March 2007 she joined the Center for Applied Medical Research (CIMA), University of Navarra as staff researcher in the laboratory of Cellular and Molecular Neuropharmacology: behaviour research that aims to study the molecular basis of dementia in Alzheimer’s disease. She is co-inventor of four patents and author of 24 publications.

Corresponding author: Mar Cuadrado-Tejedor, Cell and Molecular Neuropharmacology, Neurosciences Division, Center for Applied Medical Research, CIMA, University of Navarra, Av. Pio XII 55, E-31008 Pamplona, Spain; and Department of Anatomy, School of Medicine, University of Navarra, Pamplona, Spain, e-mail:

Received: 2013-05-13

Accepted: 2013-06-24

Published Online: 2013-07-27

Published in Print: 2013-10-01

Citation Information: BioMolecular Concepts, Volume 4, Issue 5, Pages 433–445, ISSN (Online) 1868-503X, ISSN (Print) 1868-5021, DOI: https://doi.org/10.1515/bmc-2013-0012.

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Obdulia Rabal, Juan A. Sánchez-Arias, Mar Cuadrado-Tejedor, Irene de Miguel, Marta Pérez-González, Carolina García-Barroso, Ana Ugarte, Ander Estella-Hermoso de Mendoza, Elena Sáez, Maria Espelosin, Susana Ursua, Haizhong Tan, Wei Wu, Musheng Xu, Antonio Pineda-Lucena, Ana Garcia-Osta, and Julen Oyarzabal
ACS Chemical Neuroscience, 2019
Chendhore S. Veerappan, Sama Sleiman, and Giovanni Coppola
Neurotherapeutics, 2013, Volume 10, Number 4, Page 709
Hui Liu and Weidong Le
Translational Neurodegeneration, 2014, Volume 3, Number 1
Obdulia Rabal, Juan A. Sánchez-Arias, Mar Cuadrado-Tejedor, Irene de Miguel, Marta Pérez-González, Carolina García-Barroso, Ana Ugarte, Ander Estella-Hermoso de Mendoza, Elena Sáez, Maria Espelosin, Susana Ursua, Tan Haizhong, Wu Wei, Xu Musheng, Ana Garcia-Osta, and Julen Oyarzabal
ACS Chemical Neuroscience, 2018
Xiaolei Liu, Bin Jiao, and Lu Shen
Frontiers in Genetics, 2018, Volume 9
Oscar Teijido and Ramón Cacabelos
International Journal of Molecular Sciences, 2018, Volume 19, Number 10, Page 3199
Obdulia Rabal, Juan A. Sánchez-Arias, Mar Cuadrado-Tejedor, Irene de Miguel, Marta Pérez-González, Carolina García-Barroso, Ana Ugarte, Ander Estella-Hermoso de Mendoza, Elena Sáez, Maria Espelosin, Susana Ursua, Tan Haizhong, Wu Wei, Xu Musheng, Ana Garcia-Osta, and Julen Oyarzabal
European Journal of Medicinal Chemistry, 2018, Volume 150, Page 506
Jaeyoon Chung, Xiaoling Zhang, Mariet Allen, Xue Wang, Yiyi Ma, Gary Beecham, Thomas J. Montine, Steven G. Younkin, Dennis W. Dickson, Todd E. Golde, Nathan D. Price, Nilüfer Ertekin-Taner, Kathryn L. Lunetta, Jesse Mez, Richard Mayeux, Jonathan L. Haines, Margaret A. Pericak-Vance, Gerard Schellenberg, Gyungah R. Jun, and Lindsay A. Farrer
Alzheimer's Research & Therapy, 2018, Volume 10, Number 1
Paulami Chatterjee, Debjani Roy, and Nitin Rathi
Journal of Alzheimer's Disease, 2017, Volume 61, Number 1, Page 53
Gemma Navarro, Nuria Franco, Eva Martínez-Pinilla, and Rafael Franco
Frontiers in Genetics, 2017, Volume 8
Shuang-shuang Yang, Rui Zhang, Gang Wang, and Yong-fang Zhang
Translational Neurodegeneration, 2017, Volume 6, Number 1
Juan A. Sánchez-Arias, Obdulia Rabal, Mar Cuadrado-Tejedor, Irene de Miguel, Marta Pérez-González, Ana Ugarte, Elena Sáez, Maria Espelosin, Susana Ursua, Tan Haizhong, Wu Wei, Xu Musheng, Ana Garcia-Osta, and Julen Oyarzabal
ACS Chemical Neuroscience, 2017, Volume 8, Number 3, Page 638
Obdulia Rabal, Juan A. Sánchez-Arias, Mar Cuadrado-Tejedor, Irene de Miguel, Marta Pérez-González, Carolina García-Barroso, Ana Ugarte, Ander Estella-Hermoso de Mendoza, Elena Sáez, Maria Espelosin, Susana Ursua, Tan Haizhong, Wu Wei, Xu Musheng, Ana Garcia-Osta, and Julen Oyarzabal
Journal of Medicinal Chemistry, 2016, Volume 59, Number 19, Page 8967
Rosalina Fonseca
Neurobiology of Learning and Memory, 2016, Volume 133, Page 182
Mar Cuadrado-Tejedor and Ana García-Osta
Frontiers in Neurology, 2014, Volume 5
Ramón Cacabelos and Clara Torrellas
Expert Opinion on Drug Discovery, 2014, Volume 9, Number 9, Page 1059

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