• Alzheimer's disease;
  • epigenetics;
  • histone-acetylation;
  • memory;
  • neurodegeneration;
  • non-coding RNA


  1. Top of page
  2. Abstract
  3. Memory formation via gene expression control
  4. Histone-modifications in memory formation
  5. Histone-modifications in Alzheimer's disease
  6. DNA-methylation in Alzheimer's disease
  7. Non-coding RNA in Alzheimer's disease
  8. How much Lamarck is in our memories?
  9. Conflict of interest
  10. References

Recent data support the view that epigenetic processes play a role in memory consolidation and help to transmit acquired memories even across generations in a Lamarckian manner. Drugs that target the epigenetic machinery were found to enhance memory function in rodents and ameliorate disease phenotypes in models for brain diseases such as Alzheimer's disease, Chorea Huntington, Depression or Schizophrenia. In this review, I will give an overview on the current knowledge of epigenetic processes in memory function and brain disease with a focus on Morbus Alzheimer as the most common neurodegenerative disease. I will address the question whether an epigenetic therapy could indeed be a suitable therapeutic avenue to treat brain diseases and discuss the necessary steps that should help to take neuroepigenetic research to the next level.

Memory formation via gene expression control

  1. Top of page
  2. Abstract
  3. Memory formation via gene expression control
  4. Histone-modifications in memory formation
  5. Histone-modifications in Alzheimer's disease
  6. DNA-methylation in Alzheimer's disease
  7. Non-coding RNA in Alzheimer's disease
  8. How much Lamarck is in our memories?
  9. Conflict of interest
  10. References

The human brain has about 100 billion neurons that are interconnected via synapses, and this is believed to provide the basis for the encoding, consolidation and retrieval of memories. How the brain achieves such miraculous tasks is one of the greatest remaining mysteries of our time. While various cellular mechanisms have been linked to memory function, an often cited view suggests that de novo protein synthesis is an absolute requirement for the consolidation of long-term memories; hence, tightly regulated gene expression must be a key component of memory formation. The idea that de novo protein synthesis is a requirement for memory formation is based on studies in which inhibitors of mRNA translation were found to impair memory formation in a time-dependent manner, indicating that at least two different phases of memory consolidation exist: an early phase that is de novo protein synthesis independent and a later phase that critically depends on protein synthesis (Flexner et al, 1962; Flexner et al, 1963; Davis & Squire, 1984; Igaz et al, 2002). The same principle has then been demonstrated for synaptic plasticity. For example, long-term potentiation (LTP), which is often referred to as the molecular correlate of learning and memory, can also be distinguished into an early phase (E-LTP) and late phase (L-LTP). Notably, L-LTP but not E-LTP can be blocked by de novo protein synthesis inhibitors (Frey & Morris, 1998). It was also shown that the induction of L-LTP induced molecular events that appear to trigger de novo protein synthesis and gene expression programs that can transform E-LTP into L-LTP (Frey & Morris, 1998). Those data led to the hypothesis of synaptic tagging and capturing (Box 1), which was also confirmed on the behavioral level (Moncada et al, 2011). However, pharmacological inhibition of protein synthesis was also found to cause an accumulation of mRNA transcripts which eventually leads to a super-induction of gene expression (Tronson et al, 2009), suggesting that the amnestic effect of de novo protein synthesis inhibitors is—at least in part—due to the induction of transcriptional noise. Despite such different views on the interplay and importance of synaptic events and learning-induced differential gene expression followed by de novo protein synthesis, it is obvious that a tightly controlled gene expression program provides the basis for memory encoding. This view is further supported by the fact that de-regulated gene expression is seen in brain diseases linked to memory impairment (Lu et al, 2004; Liang et al, 2010; Ginsberg et al, 2010; Twine et al, 2011; Blalock et al, 2011; Kim et al, 2012a; Arefin et al, 2012; Caldeira et al, 2013; Mills et al, 2013). To understand the mechanisms that orchestrate gene expression programs in brain cells is thus of utmost importance.

Box 1.

Braak & Braak staging

Is a histological method that used staining for neurofibrillary tangels to define the degree of AD pathology in a post-mortem brain. It ranges from stage I (early stage) to stage VI (Severe stage).


DNA samples obtained after chromatin immunoprecipitation (ChIP) are not used to study selected genes via qPCR but are subjected to massive parallel sequencing. Albeit this method yields genome-wide maps of a given chromatin mark, data analysis requires intensive bioinformatic analysis. ChIP-Seq is routinely used in other research areas (Wang et al, 2008b), but has not been applied extensively to the learning and memory field.


The term epigenetics has been introduced by Conrad Waddington to describe heritable changes of a phenotype that do not depend on altered DNA-sequence (Holliday, 1994). Especially in the neurosciences, it is now more generally used to describe processes that are mediated via the epigenetic machinery (Stilling & Fischer, 2011). Thus, when neuroscientists nowadays refer to epigenetics, they discuss processes that involve histone-modifications, DNA-methylation as well as the more recently discovered DNA-hydroxymethylation and often also the action of non-coding RNAs (Fig 1).

Environmental enrichment

Environmental enrichment is a behavioral method consisting of cognitive and physical exercise (Nithianantharajah & Hannan, 2006) that can ameliorate cognitive disease phenotypes in mice and humans (Pajonk et al, 2010) but is mechanistically poorly understood.

Synaptic tagging and capturing hypothesis

This theory suggests how activity initiates transient synaptic changes that mark a given synapse for subsequent protein synthesis-dependent long-lasting plasticity changes.

TAU pathology

The TAU protein is encoded by the mapt gene (microtubule-associated protein tau). It is natively unfolded and best studied for its role in the regulation of microtubule stability. During AD pathogenesis, TAU is hyper-phosphorylated at multiple sites, which leads to the deregulation of cellular homeostasis. Hyper-phosphorylated TAU protein eventually aggregates into intracellular neurofibrillary tangles (NFTs) that are—next to amyloid plaques—a key hallmark of AD. The distribution of NFTs in the brain is an important diagnostic tool for the Braak & Braak staging.

Writers, erasers, readers

Writers and erasers add and remove epigenetic marks. Readers, as the name suggest, read the epigenetic code for example by binding to specific epigenetic modifications which initiates subsequent events that control gene expression. A well-studied example are methylated-DNA-binding enzymes (MDB) such as MeCP2 (Na et al, 2013).

In addition to the activity of transcription factors, epigenetic (Box 1) mechanisms are key processes that control gene expression at a systems level (Allis et al, 2007) via DNA or nucleosome modifications.

Nucleosomes consist of the four core histones (H) around which 147 bp of DNA is wrapped. The histone tails are subjected to post-translational modifications including acetylation, methylation, phosphorylated, ubiquitination, sumoylation or ADP-ribosylation (Vaquero et al, 2003). This is mediated by the counteracting activities of enzymes, so-called writers and erasers (Box 1). For example, histone-acetylation and histone-methylation are mediated by histone acetyltransferases (HAT) and histone-deacetylases (HDAC) or histone-methyltransferases (HMTs) and histone-demethylases (HDM). Such modifications affect the direct interaction of the DNA with histones and thereby alter the chromatin state (Bannister & Kouzarides, 2011).

The activity of such enzymes is also believed to gives rise to a combinatorial pattern of chromatin-modifications, the so-called the histone-code, that is recognized by protein complexes that either activate or repress gene expression (Strahl & Allis, 2000). Methylation of DNA at the C-5 atom of cytosine is probably the best-studied epigenetic modification and is mediated by DNA-methyltransferases. DNA-methylation occurs often in cytosine-guanine-rich regions of the genome (CpG islands) and is generally associated with gene silencing. It is mediated by the action of DNA-methyltransferases (DNMTs). Although there is by now clear evidence that DNA-methylation can be dynamic, the precise mechanisms how DNA is de-methylated are still not well understood. Recently, it has been discovered that cytosine can also be hydroxymethylated which occurs predominantly in brain tissue (Kriaucionis & Heintz, 2009) and is a critical step in the demethylation of DNA (Guibert & Weber, 2013). In addition to coding RNAs, the majority of the transcriptome consists of non-coding RNA species of various sizes. Best studied are a group of small non-coding RNAs, the micro RNAs (miRs) that are 19–22 nt long non-coding RNAs that catalyze gene silencing by binding to a target messenger RNA that induces either its degradation or inhibition of protein translation thereby regulating protein homeostasis (Im & Kenny, 2012). Although such non-coding RNAs are not considered to be part of classical epigenetic mechanisms, there is evidence that they mediate epigenetic gene expression (Rassoulzadegan et al, 2006; Fatica & Bozzoni, 2013). Thus, this review will also discuss the role of non-coding RNAs in brain plasticity (Fig 1).

Figure 1. Epigenetic and non-coding RNA mechanisms

(1) DNA is wrapped around the nucleosome which consists of the four core histones (H). Histone tails are subjected to post-translational modification including acetylation and methylation, which give rise to the “histone-code” that affects gene expression. Histone acetylation and methylation are regulated by the counteracting activity of histone acetyltransferases (HATs) and histone-deacetylases (HDACs) or histone-methyltransferases (HMTs) and histone-demethylases (HDMs), respectively. (2) Methylation of DNA at the C-5 atom of cytosine is mediated by DNA-methyltransferases and often occurs in cytosine-guanine-rich regions of the genome (CpG islands). DNA-methylation is generally associated with gene silencing. DNA-hydroxymethylation is mediated by ten-eleven translocation proteins and also regulates gene expression. (3) Non-coding RNAs affect gene expression and protein function. The best-studied non-coding RNAs are micro RNAs (miRs) that catalyze gene silencing or inhibition of protein translation. These processes are key regulators of genome–environment interactions and provide to a cell the molecular tools to transform the variable combinations of genetic and environmental factors into long-term adaptive changes. There is now emerging evidence that the epigenome also regulates the consolidation of processed information into long-term memories.

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The emerging field of neuroepigenetics investigates the above-mentioned epigenetic processes in the context of neuronal plasticity, memory function and brain diseases. In the following, I will discuss the current knowledge on neuroepigenetics with a focus on brain plasticity that will be contrasted by the current knowledge on epigenetics in brain disease such as Alzheimer disease (AD).

Histone-modifications in memory formation

  1. Top of page
  2. Abstract
  3. Memory formation via gene expression control
  4. Histone-modifications in memory formation
  5. Histone-modifications in Alzheimer's disease
  6. DNA-methylation in Alzheimer's disease
  7. Non-coding RNA in Alzheimer's disease
  8. How much Lamarck is in our memories?
  9. Conflict of interest
  10. References


Already in 1979, it was found that acetylation of histones is altered when rats undergo memory consolidation (Schmitt & Matthies, 1979). Such studies were later confirmed showing that specific forms of learning correlate with increased HAT activity (Swank & Sweatt, 2001) and histone-acetylation (Levenson et al, 2004). While Schmitt and Matthies used C14-labeled acetate to study histone-acetylation (Schmitt & Matthies, 1979), these later studies used immunoblotting to detect bulk levels of histone-modifications. The mechanistic insight from such early observations is limited since they do allow to identify the genomic regions in which altered histone-acetylation takes place. The functional relevance of histone-acetylation for memory formation was first demonstrated via genetic mouse models in which the activity of the HAT CREB-binding protein (CBP/KAT3A) was reduced (Alarcon et al, 2004; Korzus et al, 2004). These mutant mice displayed impaired memory consolidation (Fig 2), a finding that has been reproduced in various mouse models in which CBP activity was altered (Wood et al, 2005; Wood et al, 2006; Chen et al, 2010a; Barrett et al, 2011). In addition, it was found that pharmacological inhibition of HDACs in the hippocampus enhances the consolidation of associative memories in rodents (Levenson et al, 2004; Fischer et al, 2007; Stefanko et al, 2009; Federman et al, 2009). Subsequent studies started to explore the role of specific histone-modifications and the function of the corresponding enzymes in greater detail. Insight into the role of specific modifications is still limited which is also due to the fact that most studies investigate bulk histone-modifications. To overcome this issue, researchers have started to perform chromatin immunoprecipitation (ChIP) followed by qPCR analysis to study the chromatin architecture of selected genes. Surprisingly, data in which ChIP-qPCR for specific histone-modifications was analyzed during memory formation are sparse, and at least in the brain, there is also evidence that transient changes in gene expression do not always correlate with altered histone-modifications at differentially expressed genes (Kenney et al, 2012). Such data suggest that the effect of HATs and HDACs in memory formation may involve also other mechanisms than the regulation of gene expression. The current state of the art method to study chromatin marks across the entire genome is ChIP followed by next-generation sequencing (ChIP-Seq, Box 1). A recent study performed a genome-wide analysis of H4K5ac via ChIP-sequencing and found that H4K5ac correlates with learning-induced gene expression (Park et al, 2013). This study used however a fear conditioning protocol for associative learning (Fig 2) in which mice received re-conditioning on consecutive days. It thus appears that gene expression and histone-acetylation at the corresponding genes correlate best in response to rather severe stimuli, as observed in disease situations or in the case of mutant mice that lack specific enzymes of the epigenetic machinery (Peleg et al, 2010; Kerimoglu et al, 2013). Due to decreased costs and better bioinformatic tools, the genome-wide analysis of histone-acetylation using ChIP-Seq is likely to become a standard procedure also in the neurosciences, which will allow for more mechanistic insight in the future.

Figure 2. Analyzing memory function in rodents

This image illustrates three commonly used tests to study memory formation in rodents. (A) The Morris water maze Test measures spatial reference memory that is highly hippocampus-dependent. A mouse or rat is placed in a pool that contains opaque water and an escape platform that is located underneath the water surface. During the training, the rodent learns to locate the hidden platform based on spatial orientation. Such memory is normally acquired gradually throughout multiple training sessions on subsequent days (e.g., 10 days of training). (B) The Pavlovian fear conditioning is used to assess associative memory. The rodent is allowed to explore the test box representing a novel context for about 3 min before it receives a mild electric foot shock. When placed back into the context 24 h later, the animal shows freezing, inborn behavior that rodents express in response to threatening situations. The amount of freezing is quantified and reflects learning ability. In contrast to the water maze, fear conditioning is successfully acquired after a single training session, and memory can be tested even 1 year later. (C) In the novel object recognition paradigm, the animal is habituated to the test arena and eventually presented with two objects that it explores equally. After a delay that can vary from minutes (short-term memory) to 24 h (long-term memory), the animal is re-exposed to the arena that now contains one novel object. Based on the previous training session, the animal remembers the object that has already been explored and will show a preference for the novel object. (D) To elucidate the mechanisms that underlie memory consolidation, a suitable approach is to subject animals to a training session and isolate afterward at distinct time points tissue for molecular analysis. Especially paradigms such as fear conditioning are often used since memory is acquired within a distinct time window after a single training session allowing for a “molecular snapshot” of memory consolidation. Based on such results, hypothesis can be formed and suitable gain- and loss-of-function mouse models are generated that are then again tested for memory function.

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At the same time, there is already substantial data showing that the enzymes regulating histone-modifications are essential for memory function. Especially the role of HDCAs in the adult brain has gained much attention since they have emerged as promising drug targets for brain diseases (Fischer et al, 2010).

The 11 mammalian HDACs belong to an ancient protein family and require a Zn2+ ion as cofactor (de Ruijter et al, 2003; Gregoretti et al, 2004; Table 1). Under naïve conditions, all HDAC genes are expressed within the adult rodent brain (Broide et al, 2007). Mice that lack HDAC1 or overexpress it in all neurons from early developmental stages on show no impairments in contextual fear learning or spatial memory formation (Guan et al, 2009; Fig 2), suggesting that HDAC1 has no obvious role at least in the above-mentioned types of memory function. HDAC1 was however found to be essential for fear extinction learning, a process that is important for the treatment of neuropsychiatric diseases associated with aversive behaviors as they occur in post-traumatic stress disorder (Bahari-Javan et al, 2012). Here, the induction of immediate early genes was suppressed via HDAC1-mediated de-acetylation of H3K9 and subsequent H3K9 tri-methylation (Bahari-Javan et al, 2012). Although HDAC1 and HDAC2 are close homologues that derived from gene duplications, their roles in memory function differ. Overexpression of HDAC2 in neurons impaired contextual fear learning and spatial memory formation in mice, while deletion of HDAC2 in neurons from early developmental stages on improved memory function and synaptic plasticity (Guan et al, 2009). Notably, enhanced learning behavior in HDAC2 knockout mice correlated with increased hippocampal H4K12 acetylation, while H3K14 acetylation was not affected. Although the authors measured bulk changes, these data are interesting taking into account that genome-wide analysis of chromatin in the aging hippocampus suggested a key role for H4K12 acetylation in age-associated memory impairment (Peleg et al, 2010). On the structural level, loss of HDAC2 increased the number of synapses (Guan et al, 2009) which is in line with a role of HDAC2—but also HDAC1—in synapse formation during development (Akhtar et al, 2009). Loss of HDAC2 was also found to improve fear extinction learning (Morris et al, 2013) which is opposite to the function of HDAC1 (Bahari-Javan et al, 2012). HDAC2 was found to bind promoter regions of genes linked to memory formation, but the precise mechanisms by which HDAC2 acts as a memory repressor are not well understood (Guan et al, 2009). One study showed that HDAC2 is essential for the survival of adult born neurons in the dentate gyrus (Jawerka et al, 2010). Since adult neurogenesis has been linked to memory function, it is clear that the role of HDAC2 in the adult brain awaits a more detailed analysis. An important next step would be to understand the role of HDAC1 and 2 in a cell-type-specific manner. A recent study suggests that HDAC2 is produced in many neuronal cell types and in oligodendrocytes, but not in astro- or microglia (Yao et al, 2013). Similar to the data available for HDAC2, mice that lack HDAC3 in the adult hippocampus show improved object recognition memory (McQuown et al, 2011; Fig 2), but the underlying mechanisms are not understood. The function of HDAC8 in adult brain has not been addressed in detail, but a recent study found that an HDAC inhibitor with some selectivity toward HDAC8 improves memory function in rats (Yang et al, 2013). In conclusion, it appears that the class I HDACs act as molecular inhibitors of memory formation.

Table 1. HDACs in the adult brain
 ProteinSubcellular localizationPotential function in memory formation
  1. This table illustrates the current classification of the 11 mammalian HDACs and points to their role in memory formation (for further information see text).

CLASS IHDAC1Mainly nuclear, cyoplasmatic in response to axonal damageRegulates fear extinction
HDAC2Mainly nuclearNegative regulator of memory formation mice
HDAC3Nuclear/cytoplasmaticNegative regulator of memory formation mice
HDAC8Mainly nuclearUnclear
CLASS IIHDAC4Cytoplasmatic/nuclear/SynapticRequired for memory formation in mice
HDAC5Cytoplasmatic/nuclearRequired for memory formation in mice
HDAC6Cytoplasmatic/centrosomalNot required for memory formation in mice but inhibition reinstates memory function in Alzheimer disease mouse models
CLASS IVHDAC11Cytoplasmatic/nuclearUnclear

As for the class II HDACs (Table 1), HDAC4 is known to shuttle between the cytoplasm and the nucleus of cultured hippocampal neurons in response to Calcium signaling and CamKII activity (Chawla et al, 2003; Backs et al, 2006). In an C. elegans model, deletion of HDAC4 gene increases long-term memory for thermosensation in an CamKII-dependent manner (Wang et al, 2011). Specific expression of mammalian HDAC4 in the nucleus was able to revert this phenotype, suggesting that nuclear export of HDAC4 is a critical process for memory formation. In line with these data, cytoplasmatic expression of HDAC4 increased memory formation in wild-type worms (Wang et al, 2011), suggesting that during learning, HDAC4 regulates counteracting molecular processes in the nucleus and the cytoplasm. In contrast to such findings, a recent study suggests that HDAC4 is essential for memory function in mammalian systems. Mice that lack HDAC4 in the adult forebrain exhibit impaired hippocampus-dependent memory formation and plasticity (Kim et al, 2012b). These data are in line with findings showing that haploinsufficiency of HDAC4 is linked to mental retardation in humans (Williams et al, 2010). Another study confirmed that lack of HDAC4 in the adult brain results in impaired memory function and synaptic plasticity in mice and could identify synaptic plasticity genes that are regulated by nuclear HDAC4 (Sando et al, 2012). Loss of HDAC5 in the nucleus accumbens renders mice hypersensitive to chronic cocaine (Renthal et al, 2007), while 2-month-old mice that lack HDAC5 from the adult forebrain show no changes in hippocampus-dependent memory formation (Kim et al, 2012b). A role of HDAC5 in memory formation may not only be brain region but also age-related. To this end, 10-month-old mice that lack HDAC5 show hippocampus-dependent memory disturbances (Agis-Balboa et al, 2013). HDAC6 has a unique position in the HDAC family in that its main targets are cytoplasmatic proteins such as tubulin or heat-shock protein 90 (Govindarajan et al, 2013). As will be discussed below, HDAC6 is emerging as promising drug target in neurodegenerative diseases. However, loss of HDAC6 in mice has no overt phenotype and does not impact on memory formation (Govindarajan et al, 2013). The role of the remaining zinc-dependent HDACs in the adult brain has not been investigated in great detail.

Compared to the increasing numbers of studies that investigate the role of HDACs in memory formation, there are comparatively little data on the role of HATs. The mammalian genome encodes for at least 18 HATs that are subdivided into the GNAT (Gcn5 N-acetyltransferases) family, the MYST (MOZ, Ybf2/Sas3, Sas2, TIP60) family, the p300/CBP family and several other HATs that cannot be grouped into a certain family (Lee & Workman, 2007; Allis et al, 2007). The best-studied HATs belong to the p300/CBP family. Multiple studies demonstrated a role for CBP/KAT3A in memory consolidation (Alarcon et al, 2004; Korzus et al, 2004; Wood et al, 2005; Wood et al, 2006; Chen et al, 2010a; Barrett et al, 2011), though it does not seem to be essential for all types of memory and especially for the highly hippocampus-dependent Morris water maze test, existing data are conflicting (Josselyn, 2005).

However, overexpression of a dominant negative form of P300/KAT3B in the mouse brain impairs memory consolidation (Oliveira et al, 2007), and similar data were observed for mice that lack one allele of PCAF/KAT2B (Maurice et al, 2008), but mechanistic insight is limited at present. There is evidence that CBP mediates its role in brain plasticity via histone-acetylation-dependent gene expression (Vecsey et al, 2007), and one study provided evidence that the role of CBP/KAT3A during learning critically depends on its ability to induce the expression of nuclear receptor 4a1 (Nr4a1; McNulty et al, 2012). However, detailed genome-wide analysis of transcriptional networks associated with CBP function in the adult brain is sparse and gene array approaches thus far linked CBP function to calcium signaling, transcription and synaptic plasticity (Chen et al, 2010a) and de-regulated gene expression in response to environmental enrichment training (Lopez-Atalaya et al, 2011).

In conclusion, there is substantial evidence that HATs and HDACs are critical for memory formation. Based on their general role in the regulation of cellular processes, it is tempting to speculate that they coordinate gene expression programs linked to long-term memory consolidation, but a major effort in future research will be to understand the mechanisms by which HATs and HDACs regulate plasticity in specific brain cells.

Histone-methylation in memory formation

In addition to acetylation, histone proteins can be methylated, phosphorylated, ubiquitinated, sumoylated, biotinylated or ADP-ribosylated (Vaquero et al, 2003). While histone-phosphorylation and histone 1 ADP-ribosylation has been linked to memory training (Chwang et al, 2006; Fontán-Lozano et al, 2010), the best studied histone-modification in the brain next to acetylation is histone-methylation. Similar to histone-acetylation, it is regulated by the counteracting activity of HMTs and HMDs. However, in contrast to acetylation, the lysine residues of histones can be either mono-, di- or tri-methylated which is catalyzed by specific enzymes. As such there are more HMTs and HDMs than there are HATs and HDACs, and their general role has been discussed in a number of recent review articles (Shi, 2007; Shi & Whetstine, 2007; Badeaux & Shi, 2013). Early studies found that histone-methylation is implicated with neuronal plasticity and memory formation. Especially H3K4-trimethylation (H3K4me3), a mark for active gene promoters, has been studied. For example, H3K4me3 correlates with the expression of glutamate receptors in the human brain (Stadler et al, 2005). Moreover, bulk levels of hippocampal H3K4me3 were found to increase in response to fear conditioning training (Gupta et al, 2010). H3K4me3 is regulated by at least 10 different enzymes that catalyze mono-, di and tri-methylation (Badeaux & Shi, 2013). Mice that lack one allele of the H3K4 HMT Mll1/KMT2A display impaired memory formation (Gupta et al, 2010). A recent study also demonstrated a role for the H3K4 specific HMT Mll2/KMT2B in memory function. Mice that lack KMT2B in the dorsal dentate gyrus of hippocampal region show memory impairment that is linked to deregulation of learning-relevant genes (Kerimoglu et al, 2013). Loss of KMT2B not only affected H3K4me3 at the promoter regions of learning-regulated genes but also reduced H3K9 acetylation, while H4K16 acetylation and H3K4me1 was unaffected at the same gene promoters (Kerimoglu et al, 2013). Such data further confirm the view that histone-methylation and histone-acetylation are tightly linked, and also demonstrate the need to better understand the protein complexes that regulate chromatin plasticity in the adult brain. Other H3K4 HMTs or HDMs have not been tested for a role in memory formation, but an inhibitor of the H3K4 HMD LSD1/KDM1a was found to impair memory formation when injected to mice (Neelamegam et al, 2012). These data would suggest that increased H3K4me3 in the brain causes cognitive impairments, which is in contrast to the data obtained from the knockout studies of H3K4 HMTs KMT2A and KMT2B. However, at present, it is unclear which gene expression programs are controlled by H3K4me3 and which HTMs and HDMs are indeed involved in the regulation of such learning-relevant genes. Moreover, LSD1/KDM1a also affects H3K9 methylation. H3K9 methylation is linked to heterochromatin formation and gene silencing. Interestingly, the H3K9 di-methylation-specific HMT G9a/KMT1C was found to play a key role in neuronal integrity. In fact, mice that lack G9a/KMT1C in the adult forebrain develop mental retardation-like phenotypes (Schaefer et al, 2009). However, loss of G9a/KMT1C in the nucleus accumbens increases cocaine-induced neuronal plasticity (Maze et al, 2010), and yet another study found that pharmacological inhibition of G9a in the entorhinal cortex facilitated memory function, while administration of the same inhibitor into the hippocampus resulted in impaired memory function in mice (Gupta-Agarwal et al, 2012). A critical role for G9a/KMT1C in memory formation is also supported from studies in Drosophila, where loss of G9a/KMT1C impaired memory formation (Kramer et al, 2011). Another H3K9 methyltransferase is SETDB1/KMT1E. Increased expression of SETDB1/KMT1E in the forebrain of mice reduced depressive-like behavior via a mechanism that involved regulation of NMDA receptor subunit 2B (Jiang et al, 2010). As for the HDMs, there are even less data investigating the role of such enzymes in memory formation. Recent studies could link mutations in JARID1C/KDM5C, an H3K4 demethylase, to short-term memory deficits in female humans (Simensen et al, 2012) and to mental retardation (Rujirabanjerd et al, 2012). As for the H3K9 demethylases, JMJD2A/KDM4A was found in a complex with HDAC1 and protein phosphatase 1 (PP1) which was required for memory formation (Koshibu et al, 2009). In conclusion, the current data suggest that histone-methylation, as well as the activity of HMTs and HDMs, plays a role in memory formation, but a clear picture is not yet emerging.

Histone-modifications in Alzheimer's disease

  1. Top of page
  2. Abstract
  3. Memory formation via gene expression control
  4. Histone-modifications in memory formation
  5. Histone-modifications in Alzheimer's disease
  6. DNA-methylation in Alzheimer's disease
  7. Non-coding RNA in Alzheimer's disease
  8. How much Lamarck is in our memories?
  9. Conflict of interest
  10. References

An increasing number of studies show that targeting the epigenetic machinery in neurodegenerative diseases could be a novel and promising therapeutic avenue (Fischer et al, 2010). Especially, inhibitors of HDAC proteins have gained much attention in brain disorders such as AD (Sananbenesi & Fischer, 2009). AD is a debilitating disease that arises on the pathological background of amyloid-beta plaques, neurofibrillary tangles and severe neuronal loss, eventually leading to dementia (Haass & Selkoe, 2007). About 5% of all AD cases are caused by mutations in genes that regulate processing of the amyloid precursor protein (Haass & Selkoe, 2007). More common is however the late onset form (loAD) of AD that comprises 95% of all cases and is driven by variable combinations of genetic and environmental risk factors (Sananbenesi & Fischer, 2009; Goate & Hardy, 2012). Despite intensive research and increasing molecular insight to the patho-mechanisms underlying loAD, no effective therapy is currently available (Mangialasche et al, 2010).

The therapeutic potential of HDAC inhibitors in AD was first tested in a mouse model that overexpresses the p25 protein—a pathological activator of cyclin-dependent kinase 5—in a region and time-restricted manner (Fischer et al, 2007). Inducible over-expression of p25 causes amyloid and tau pathology, severe neurodegeneration and memory impairment (Cruz et al, 2003; Fischer et al, 2005; Cruz et al, 2006). Intra-peritoneal (ip) administration of the HDAC inhibitor sodium butyrate for 4 weeks was able to reinstate learning behavior and synaptic plasticity in this mouse model even after the onset of severe synaptic and neuronal loss (Fischer et al, 2007). In this experimental setting, the rational to apply an HDAC inhibitor to an AD mouse model was based on the hypothesis that environmental enrichment (EE, Box 1) is mediated via changes in neuronal histone-acetylation (Fischer et al, 2007; Sananbenesi & Fischer, 2009).

The therapeutic effect of HDAC inhibitors in AD was also observed in mouse models for amyloid deposition. HDAC inhibitors such as trichostatin A, phenylbutyrate, valproate, sodiumbutyrate or suberoylanilide hydroxamic acid (SAHA, Vorinostat) have been administered mainly via i.p. injections to APP/PS1, Tg2576 and APPPS1-21 mice (Francis et al, 2009; Ricobaraza et al, 2009; Ricobaraza et al, 2010; Kilgore et al, 2010; Govindarajan et al, 2011). All these studies found that HDAC inhibitors improved memory function, and in some cases, increased bulk levels of histone-acetylation in brain regions were observed. One study also investigated hippocampal spine density and found it to be enhanced after phenylbutyrate treatment (Ricobaraza et al, 2010), while another studies observed a reduction in pathological phospho-Tau levels (Ricobaraza et al, 2009) or a reinstatement of gene expression (Govindarajan et al, 2011). The work of Govindarajan et al is of note since the HDAC inhibitor sodiumbutyrate was only applied after the onset of severe AD pathology and was still able to improve memory function. Equally important is the fact that none of the above studies could demonstrate an effect of HDAC inhibitor treatment on amyloid pathology itself. Since all of the above-described HDAC inhibitors show different pharmacological profiles and affect multiple HDAC proteins, it is still possible that other HDAC inhibitors may alter amyloid pathology, probably via regulation of genes linked to APP processing or clearance mechanisms. In line with this view, a recent study found that orally administered MS-275 (Entinostat), a class I HDAC inhibitor that shows selectivity toward HDAC1 (Hu et al, 2003; Khan et al, 2008; Bahari-Javan et al, 2012), improved dysregulated nesting behavior in APPPS1-21 mice and reduced neuroinflammation and also amyloid plaque deposition (Zhang & Schluesener, 2013). Another study found that a new class II HDAC inhibitor lowered Aß40, Aß42 and Thr181 phospho-TAU levels and improved memory function when administered for 4 weeks to 3xTG AD mice (Sung et al, 2013).

It has to be mentioned that one recent study reported that the HDAC inhibitor SAHA facilitates hippocampal long-term potentiation (LTP) in wild-type mice but failed to improve cognitive function in Tg2567 mouse model for Alzheimer's disease (Hanson et al, 2013). As an explanation the authors demonstrate poor brain availability of SAHA after i.p. injection. This could explain why improved memory function was observed in the same mouse model when phenylbutyrate was administered (Ricobaraza et al, 2009) and the fact that SAHA could rescue age-associated memory impairment in mice when injected directly into the hippocampus (Peleg et al, 2010). However, the same dose of SAHA that was used in the Hansson et al study was found effective in APP/PS1delta9 mice when administered i.p. for only 3 weeks (Kilgore et al, 2010) and the discrepancy for these data is not clear at present.

Importantly, most of the data on HDAC inhibitors in AD were obtained using mouse models that recapitulate amyloid deposition and are based on the rare familial form of AD. Thus, it is interesting to note that a number of studies found that HDAC inhibitors also improve memory function in aged rodents (Fontán-Lozano et al, 2008; Peleg et al, 2010; Reolon et al, 2011).

A role for histone-acetylation and the zinc-dependent HDACs in models for TAU pathology (Box 1) has not been investigated in detail. I predict that this will be a very interesting line of future research, taking into account that reduction of TAU expression has emerged as a promising therapeutic strategy in AD (Roberson et al, 2007) and findings showing that the epigenetic state of the mapt gene (which encodes the TAU protein) as well as the app gene (which encodes APP) is altered in human AD brains (Iwata et al, 2013). Furthermore, the function of TAU itself was found to be regulated via acetylation. TAU acetylation was found to inhibit the turnover of phosphorylated TAU species via a mechanism that involves the HAT p300/KAT3B and the class III HDAC SIRT1 (Min et al, 2010), indicating that increased TAU acetylation contributes to disease pathogenesis. In contrast to this view, recent studies suggest that targeting TAU acetylation or related processes could be a beneficial strategy to treat AD. For example, TAU interacts with HDAC6 (Ding et al, 2008; Perez et al, 2009) which has been linked to Tau clearance (Cook et al, 2012). It was furthermore shown that HDAC6-mediated loss of Tau acetylation renders the protein vulnerable to toxic phosphorylation events (Cook et al, 2013). Further evidence that inhibition of HDAC6 might attenuate TAU pathology in AD stems from a Drosophila model (Xiong et al, 2013). Here, hyper-phosphorylated Tau protein resulted in microtubule instability and neurodegeneration which was rescued by knock-down of HDAC6 (Xiong et al, 2013). Such findings are supported by recent data showing loss of HDAC6 rescues memory function in a mouse model for Alzheimer's disease (Govindarajan et al, 2013).

In conclusion, there is substantial evidence that HDAC inhibitor treatment can improve memory function in mouse models for AD even at an advanced stage of pathology. This phenomenon is mechanistically however not well understood.

Two questions need to be addressed in future research: (i) Via which cellular mechanisms do HDAC inhibitors ameliorate AD-related cognitive decline? and (ii) through which specific HDAC proteins do HDAC inhibitors mediate their therapeutic effects? Obviously, these questions are closely linked to research that aims to better understand the role of HATs and HDACs during memory formation. It is also critical to elucidate the question whether targeting the epigenome is symptomatic or whether indeed disease-causing epigenetic mechanisms are affected by therapeutic strategies such as HDAC inhibitors.

The best evidence that altered histone-acetylation is mechanistically linked to memory decline stems from a study in which age-associated memory impairment was investigated in mice (Peleg et al, 2010). Here, the onset of cognitive decline during aging was linked to deregulated acetylation of H4K12 (H4K12ac). While memory training induced a transient increase in various histone-acetylation marks in the hippocampus of young and aged mice, H4K12ac did not respond anymore to such a stimulus in old animals. ChIP-Seq was combined with transcriptome analysis, and the data suggest that H4K12ac is critical for the initiation of a learning-induced gene expression program via mechanisms that involved transcriptional elongation (Peleg et al, 2010). Intrahippocampal injection of SAHA to aged mice was able to partially restore H4K12ac-linked gene expression and memory function (Peleg et al, 2010).

Several HDAC proteins have been linked to cognitive decline. For example, HDAC1 has been implicated with AD, but the current data do not yet allow for a conclusion if inhibition of HDAC1 would be detrimental or beneficial for AD pathology. Recent data suggest that HDAC1 activity contributes to AD pathology since it appears to be a critical mediator of genome stability. Loss of HDAC1 has been linked to DNA damage (Kim et al, 2008; Wang et al, 2013; Dobbin et al, 2013), which represents most likely a loss of nuclear HDAC1 function. Such data suggest that future therapeutic approaches using HDAC inhibitors should avoid targeting HDAC1. However, it was found that in response to axonal damage, which is also a hallmark of AD, HDAC1 is exported from the nucleus to the cytoplasm where it dysregulates mitochondrial transport. In this context, inhibition of HDAC1 was beneficial and could reinstate axonal transport (Kim et al, 2010). In contrast, the role of HDAC2 is better understood. HDAC2 expression was found to increase in AD patients and in AD mouse models. Reducing HDAC2 levels in AD mouse models via siRNA approaches was able to reinstate memory function (Gräff et al, 2012).

As for the class II HDACs, it was shown that loss of HDAC5 accelerated memory decline in APPPS1-21 mice (Agis-Balboa et al, 2013). A recent study found that HDAC5 plays a role in axonal regeneration (Cho et al, 2013). Upon axonal damage HDAC5 is transported out of the nucleus which allows the expression of genes that orchestrate a neuronal regeneration program. The only other HDAC that has been studied for its role in AD is HDAC6, which is elevated in post-mortem brain tissue from AD patients (Ding et al, 2008). Reducing HDAC6 levels in mice rescues memory impairment in an AD mouse model via a mechanism that involves mitochondrial transport (Govindarajan et al, 2013).

In summary, the knowledge of HDAC proteins in learning and brain diseases has significantly increased in the last 5 years. It is however obvious that more research is needed. For example, HDACs mediate their biological function as components of larger complexes that include transcription factors and other proteins, offering another layer for pharmacological interventions. The question how chromatin-modifying enzymes act in the context of protein complexes in the adult brain will be an interesting question for future research.

Taking into account that deregulated acetylation of histone and non-histone proteins is implicated with memory decline and AD, in addition to the role of HDACs, it is important to elucidate the role of HATs in brain diseases. Most of the current knowledge is focused on CBP/KAT3A. Mutations in CBP cause Rubinstein–Taybi syndrome (RTS, see Box 1), and there is some evidence that CBP is implicated in AD pathogenesis, since it was found that phosho-levels of CBP/KAT3A are down-regulated in a mouse model for amyloid deposition. Overexpression of CBP/KAT3A ameliorated memory impairment in this model (Caccamo et al, 2010). Further evidence stems from findings suggesting that CBP/KAT3A and the close homologue P300/KAT3B are activated by wild-type presenilin 1, but not by the AD-associated presenilin 1 mutant protein (Francis et al, 2007).

Whether CBP/KAT3A or P300/KAT3B control gene expression programs that might mirror the deregulation seen in AD has not been addressed in detail, but novel computational approaches might help to shed light on such questions (Poirel et al, 2013). Data for other HATs in neurodegenerative disease are sparse. Loss of PCAF/KAT2B was found to ameliorate the phenotypes induced by the injection of amyloid-beta peptides injected into lateral ventricles (Duclot et al, 2010). Moreover, TIP60/KAT5 activity can rescue amyloid-beta-induced neurotoxicity (Pirooznia et al, 2012) and axonal transport deficits in a Drosophila model (Johnson et al, 2013). There is evidence that TIP60/KAT5 mediates such effects by regulating gene expression, especially of genes linked to apoptotic cell death (Pirooznia et al, 2012) and axonal transport (Johnson et al, 2013). However, unbiased approaches to decipher the gene expression program controlled by TIP60/KAT5 in the adult brain are missing. A direct link of TIP60/KAT5 to AD pathogenesis is suggested by findings showing that TIP60/KAT5 regulates gene expression in a complex with the amyloid precursor protein intracellular domain (AICD; Cao et al, 2004; Müller et al, 2013). Moreover, TIP60/KAT5 plays a critical role in orchestrating the cellular response to DNA damage (Kaidi & Jackson, 2013) which is emerging as another critical player in AD pathogenesis (Mao & Reddy, 2011; Herrup et al, 2013). There is also evidence that TIP60 mediates microtubule-acetylation (Sarthi & Elefant, 2011), suggesting that it might act as a counterplayer of HDAC6, which has however not been tested so far.

While the role of HATs in neurodegenerative disease is only emerging and from a pharmacological point of view it might be easier to inhibit rather than to activate an enzyme, there is an increasing body of literature pointing to the potential of HAT activators as a therapeutic avenue in brain diseases (Selvi et al, 2010; Schneider et al, 2013). A recent study employed a novel HAT activator and found that this compound crosses the blood–brain barrier, increased neuronal plasticity and memory function in wild-type mice (Chatterjee et al, 2013). It will be interesting to see how such a compound may affect pathology in mouse models of AD.

In conclusion, the recent literature suggests that it is important to further understand the counteracting roles of HATs and HDACs in AD pathogenesis before such findings can be translated into therapeutic approaches. With respect to other histone-modifications, increased histone-phosphorylation was observed in post-mortem tissue from AD patients (Rao et al, 2012), but in general little is known on other histone-modifications and their corresponding enzymes in AD or other brain diseases (Box 2).

Box 2.

Histone-modifying enzymes in other neurodegenerative diseases

A number of chromatin-modifying enzymes have been linked to other neurodegenerative diseases than AD, of which the most important ones are briefly mentioned here. For more information on the role of such enzymes in psychiatric diseases, the reader is referred to some recent review articles on this topic (Labrie et al, 2012; Jakovcevski & Akbarian, 2012; Mahgoub & Monteggia, 2013).


A recent study found that HDAC1 levels are increased in mouse models for Chorea Huntington and in CK-p25 mice and showed that elevated HDAC1 induces neuronal cell death in a HDAC3-dependent manner (Bardai et al, 2012). However, the same study provides evidence that HDAC1 promotes cell survival via interaction with histone deacetylase-related protein (HDRP), suggesting that rather than inhibiting HDAC1 activity it could be a suitable therapeutic approach to block HDAC1–HDAC3 interactions. Nevertheless, a recent study employed the HDAC1/HDAC3 inhibitors 4b and 136 and found that these compounds were able to ameliorate disease phenotypes in drosophila and mouse models for Huntington's disease (Jia et al, 2012). Taking also into account that HDAC1 is required for specific forms of learning (Bahari-Javan et al, 2012; Jakovcevski et al, 2013) and is deregulated in schizophrenia patients (Sharma et al, 2008) suggests that more research is needed to evaluate the potential of this HDAC as a drug target in brain diseases.


Genome-wide association studies identified HDAC9 as a genetic risk factor for ischemic stroke (Traylor et al, 2012; Markus et al, 2013). Moreover, hemizygous loss of HDAC9 has been linked to schizophrenia (Lang et al, 2011). Another study found that an intronic single nucleotide polymorphism in the HDAC9 genes was linked to male-pattern baldness (Brockschmidt et al, 2011), which is undeniably a disease of the head, but clearly more research on HDAC9 is needed to evaluate its role in memory function and brain diseases. An issue not discussed yet is alternative splicing. It is thus interesting to note that histone-deactylase-related protein (HDR) is an alternative splice version of the HDAC9 gene that gives rise to a truncated HDAC9 protein linked to neuroprotection (Zhang et al, 2008).

HDAC10 and HDAC11

These HDACs have not been linked to a neurodegenerative diseases yet, but there are in general only very little data available for these enzymes. An interesting observation was made in mice subjected to caloric restriction, which is known to improve synaptic plasticity and learning in mice. Fasting led to a down-regulation of the hdac10 and hdac11 genes in the hypothalamus (Funato et al, 2011). Similar explorative studies reported increased levels of HDAC11 in the cingulate cortex and the striatum of mice after cocaine self administration (Host et al, 2011) and in the cortex of mice in a ischemic stroke model (Chen et al, 2012).


Rubinstein–Taybi syndrome (RTS) is an autosomal dominantly inherited form of mental retardation that affects 1 in 125,000 individuals (Petrij et al, 1995; Oike et al, 1999). It is caused by mutations in CBP/KAT3A and in line with these data, mice that lack CBP show RTS-like phenotypes (Bourtchouladze et al, 2003) which can partially be restored by administration of an HDAC inhibitor (Alarcon et al, 2004).

CREB-binding protein/KAT3A also appears to play a role in the pathogenesis of Huntington's disease (HD), where it was found that mutant Huntingtin protein interacts with CBP/KAT3A and thereby deregulates gene expression (Steffan et al, 2000; Steffan et al, 2001; Cong et al, 2005; Jiang et al, 2006). Although CBP/KAT3A and P300/KAT3B are close homologues, the available data suggest that P300/KAT3B does not bind to mutant huntingtin (Cong et al, 2005).

In line with impaired CBP/KAT3A function in HD, decreased histone-acetylation and corresponding gene expression were found in HD patients and in HD mouse models (Sadri-Vakili et al, 2007; McFarland et al, 2012; Yeh et al, 2013). Mice that lack CBP/KAT3A show accelerated pathology when crossed to a Huntington's disease model (Klevytska et al, 2010), while loss of CBP/KAT3A by itself does not cause neuronal cell death (Valor et al, 2011). Moreover, administration of sodiumbutyrate or suberoylanilide hydroxamic acid, phenylbutyrate or sodium butyrate ameliorated disease phenotypes in a mouse model for HD (Hockly et al, 2003; Ferrante et al, 2003; Gardian et al, 2005). Data from a C. elegans model suggest that especially inhibition of HDAC3 might counteract the loss of CBP/KAT3A in the presence of mutant huntingtin (Bates et al, 2006).


Mutations in Mll2/Mll4/KMT2D have been linked to Kabuki syndrome, a rare disease that is accompanied by cognitive impairment (Ng et al, 2010). Aberrant H3K4me3 was also observed in post-mortem human brain tissue from autistic individuals (Shulha et al, 2012a).

DNA-methylation in memory formation

The best-studied epigenetic modification is DNA-methylation. There is evidence that DNA-methylation is dynamically regulated during memory formation. For example, neuronal activity altered the DNA-methylation in granule neurons of the dentate gyrus (Guo et al, 2011). Moreover, fear conditioning training in mice induced hippocampal expression of DNMT3a and DNMT3b which correlated with increased DNA-methylation of the PP1 and the reeling gene within 1 h after memory training (Miller & Sweatt, 2007). Administration of DNA-methylation inhibitors such as 5-deoxycytidine (5-aza) or zebularine into the hippocampus impaired associative learning and the regulation of PP1 and reeling genes upon memory training (Miller & Sweatt, 2007). Later studies confirmed these findings used enzymatic DNMT inhibitors rather than the base analogs 5-aza or zebularine (Lubin et al, 2008).

Nevertheless, the fact that a base analog such as 5-aza, which has to be incorporated into DNA in order to affect DNA-methylation, impairs memory function is fascinating considering that DNA in post-mitotic neurons normally does not undergo replication. It cannot be excluded that such drugs unspecifically impair memory formation by mechanisms other than DNA-methylation. Moreover, the hippocampus undergoes adult neurogenesis. However, such newborn neurons normally need to mature at least for 2 weeks before they contribute to plasticity and memory function, which is too long to explain the immediate effect of 5-aza and zebularine when injected into the hippocampus (Ge et al, 2005; Agis-Balboa et al, 2011). Thus, these data indicate that DNA in post-mitotic neurons might be less stable than generally assumed and base pair analogs can integrate to DNA during DNA repair. In fact, neurons are particular sensitive to reactive oxygen species, and it is estimated that each neuron has to repair at least 40,000 single- and double-strand breaks every day (Martin, 2008). Moreover, a recent study found that neuronal activity induces DNA damage in the hippocampus and cortex of mice, which is rapidly repaired. The authors hypothesize that DNA double-strand breaks occur in response to relevant stimuli and contribute to neuronal plasticity, possibly by facilitating chromatin changes at dynamically regulated genes (Suberbielle et al, 2013). Since stimulus-induced DNA damage occurred rapidly within 2 h after a stimulus, such a process could explain indeed how 5-Aza or zebularine would impact on memory formation and DNA-methylation in neurons.

In any case, there is now convincing evidence that DNA-methylation in the adult brain is quite dynamic. For example, DNA-methylation was linked to bdnf expression within 2 h after memory training, while no difference in DNA-methylation was detectable 24 h later (Lubin et al, 2008). Pharmacological inhibition of DNA-methylation also affects reward learning in the ventral tegmental area (Day et al, 2013), and there is also evidence that during memory formation, DNA-methylation and histone-acetylation are linked (Miller et al, 2008). A role for DNA-methylation in memory formation has also been suggested using genetic approaches. Mice that lack DNMT1 and DNMT3a from the adult forebrain show impaired memory formation, while mice lacking only DNMT1 or DNMT3a did not show any memory deficits (Feng et al, 2010). Notably, DNMT3a is expressed from different promoters giving rise to the two variants DNMT3a1 and DNMT3a2, which lacks 219 amino acids at the N-terminus (Chen et al, 2002). DNMT3a2 was found to be an immediate early gene that is generally decreased in the hippocampus of 18-month-old mice (Oliveira et al, 2012). Increasing the expression of DNMT3a2 in the hippocampus of cognitively impaired aged mice rescued memory function (Oliveira et al, 2012). While this confirms a role of DNA-methylation in memory formation, the precise role of DNMTs in learning and memory needs to be further investigated.

It was recently found that DNA is not only methylated but can be hydroxymethylated (5hmC) and that this process is particularly prominent in brain tissue (Kriaucionis & Heintz, 2009). Hydroxymethylation of DNA is mediated by the ten-eleven translocation (TET) proteins TET1, TET2 and TET3 that convert 5-methylcytosine to 5-hydroxymethylcytosine and further to 5-formylcytosine and 5-carboxylcytosine and thereby eventually mediate active DNA-demethylation (Pastor et al, 2013). All TET proteins are expressed in the adult brain (Kriaucionis & Heintz, 2009; Szulwach et al, 2011). A recent study found that constitutive deletion of TET1 results in a minor decrease of bulk 5 hydroxy-methylation in the adult brain. Mice that lack TET1 are viable and able to form new memories. However, fear extinction learning was impaired in TET1 knockout mice which correlated with the hyper-methylation of selected genes such as Npas4 (Rudenko et al, 2013). In a similar study, viral-mediated overexpression of TET1 in the hippocampus impaired associated learning measured by contextual fear conditioning. Interestingly, overexpression of a catalytical inactive TET1 mutant had the same effect (Kaas et al, 2013). Neither of these two studies investigated 5-hydroxymethylation at target genes, and although 5-hydroxymethylation of DNA has been implicated with active and inactive DNA-demethylation, 5-hydroxymethylcytosine appears to be more than a simple intermediate in DNA-demethylation. For example, a recent study found a number of proteins that distinctly bind either 5-methyl- or 5-hydroxy-methylcytosine (Spruijt et al, 2013). It will be critical for future research to generate genome-wide data for the methylation and hydroxyl-methylation of DNA during brain plasticity to further understand the role of this novel epigenetic mark.

DNA-methylation in Alzheimer's disease

  1. Top of page
  2. Abstract
  3. Memory formation via gene expression control
  4. Histone-modifications in memory formation
  5. Histone-modifications in Alzheimer's disease
  6. DNA-methylation in Alzheimer's disease
  7. Non-coding RNA in Alzheimer's disease
  8. How much Lamarck is in our memories?
  9. Conflict of interest
  10. References

There are a number of studies that have investigated DNA-methylation in post-mortem tissue from AD patients and in corresponding mouse models (Coppieters & Dragunow, 2011) using a variety of approaches such as measurement of global DNA-methylation (Mastroeni et al, 2009), PCR arrays (Siegmund et al, 2007; Silva et al, 2008), bisulfide sequencing (Brohede et al, 2010) or methylated DNA immunoprecipitation (Agbemenyah et al, 2013) of target genes linked to AD pathogenesis including the mapt gene coding for TAU and the genes for app or presenilin's (Fuso et al, 2012a; Iwata et al, 2013). Also genome-wide approaches using array technology have been used to study DNA-methylation in AD (Bakulski et al, 2012). Most but not all studies (Barrachina & Ferrer, 2009) found differences between controls and AD patients or AD models. Generally the current picture suggests that AD correlates with hypomethylation of target genes. Interestingly, AD-related changes in DNA-methylation also occur within non-coding regions such as transposable elements (Bollati et al, 2011).

It cannot be excluded that genetic risk may explain part of the DNA-methylation changes observed in AD. However, genes linked to DNA-methylation were not found in GWAS studies. Two functional polymorphisms within the promoter of DNMT3B have been investigated, but no altered risk for sporadic AD was detected (Coppedè et al, 2012). On the other hand, there is substantial evidence that environmental factors such as diet impact on DNA-methylation. This is explained by the fact that s-adenosylmethionine (SAM) is the major methyl-donor for DNA-methylation and SAM production within the methionine-homocysteine cycle is strongly affected by dietary factors such as folate or vitamine B12. Indeed, folate deficiency in late life has been associated with an increased risk to develop AD, and AD patients with low baseline folate levels appear to benefit from vitamin B treatment (Hinterberger & Fischer, 2013). Such findings have to be however interpreted with care due to differences in clinical trial design and the fact that not all studies observed improvement in cognitive function (Dangour et al, 2010; Hinterberger & Fischer, 2013). However, research in animal models supports a key role of methionine-homocysteine metabolism in AD. For example, a diet rich in folic acid ensures high level of the methyl-donor SAM. In fact, it was found that a folic acid-rich diet could further ameliorate disease pathology in a mouse model for amyloid pathology that was treated with memantine (Chen et al, 2010b) or in mice that suffer from memory impairment due to vitamin deficiency (Fuso et al, 2012b). Thus, there is a picture emerging in which dietary factors impact on epigenetic mechanisms such as DNA-methylation, altering the risk of AD. This also implies that not everybody would benefit from a corresponding therapeutic approach, but that such knowledge has to be transformed into suitable biomarker signatures that would then allow to stratify patients for specific treatments. It will also be interesting to see how diet affects other epigenetic mechanisms.

The role of DNA-hydroxymethylation in AD has not been addressed in great detail by now. There is evidence from immunohistochemical analysis that DNA-hydroxymethylation changes in the mouse hippocampus in response to age or amyloid pathology (Chouliaras et al, 2012; van den Hove et al, 2012), but clearly more research in this direction is needed.

Non-coding RNAs in memory formation

Next-generation sequencing approaches have identified non-coding RNAs that represent a novel mechanism to orchestrate gene expression programs. Such RNAs are currently distinguished on the basis of their length in that RNAs below 200 bases are considered small non-coding RNAs, while RNAs above 200 bases are referred to as long non-coding RNAs. One of the best-studied small non-coding RNAs is microRNAs (miRs).

A role for miRs in the nervous system is recently emerging as a number of studies found that miRs are critical regulators of synaptic plasticity (Schratt et al, 2006; Karr et al, 2009; Schratt, 2009; Siegel et al, 2009; Rajasethupathy et al, 2009; Edbauer et al, 2010; Impey et al, 2010; Fiore et al, 2011; Lippi et al, 2011; Im & Kenny, 2012; Saba et al, 2012; Lee et al, 2012a). Moreover, in vivo manipulation of miRs leads to changes in memory consolidation. For example, in an Aplysia model, miR124 controls serotonin-induced synaptic plasticity and memory formation via the regulation of CREB (Rajasethupathy et al, 2009). In the mouse brain, miR134 was found to control CREB levels, and increased expression of miR134 causes memory impairment (Gao et al, 2010). Loss of miR-processing protein DICER in the developing neocortex of mice leads to lethality soon after birth (De Pietri Tonelli et al, 2008). When DICER was deleted from excitatory forebrain neurons of the adult mouse brain, animals initially exhibited enhanced memory formation and hippocampal synaptic plasticity but eventually developed severe neurodegenerative phenotypes (Konopka et al, 2010). Such data suggest that miRs may represent a molecular brake to memory formation processes, which is critical for neuronal homeostasis. This view is supported by a study that identified the microRNAome of the mouse hippocampus via next-generation sequencing and correlated the expression of miRNAs to the expression of learning-induced genes (Zovoilis et al, 2011). MiR34c was one of the miRs increased following learning and the induction of gene expression, and it was subsequently shown that chronic elevation of miR34c in the mouse hippocampus impairs memory formation, while inhibition of miR34c enhances learning and memory (Zovoilis et al, 2011). This finding is also interesting since miR34c levels are elevated in the hippocampus of AD patients and in mouse models for amyloid deposition (Zovoilis et al, 2011). Similar findings were obtained for miR206 (Lee et al, 2012b). In vivo manipulation of miR34c, miR128, mir182 or miR132 were also found to be essential for the stress-induced plasticity, cued fear conditioning or recognition learning in mice (Haramati et al, 2011; Lin et al, 2011; Scott et al, 2012).

In addition to micro RNAs, a number of other small and long non-coding RNAs such as endogenous small interfering (endo-si)RNAs, PIWI-interacting (pi)RNAs or long intergenic non-coding (linc)RNAs have been identified and the diversity of such RNAs appears to be particularly prominent in the brain (Qureshi & Mehler, 2012). There is at present very limited knowledge on the role of such non-coding RNAs in the adult brain. One interesting finding is that piRNAs, which were originally thought to be only present in germ cells, regulate learning in an Aplysia model (Rajasethupathy et al, 2012) and might be important regulators of brain plasticity that counteract the function of miRs (Landry et al, 2013). Tsx is a long non-coding RNA that has been linked to germ cell function, but interestingly mice that lack Tsx show enhanced short-term memory function (Anguera et al, 2011).

In conclusion, non-coding RNAs are a fascinating new research area in the neurosciences that may help to further understand how the brain orchestrates gene expression during memory formation.

Non-coding RNA in Alzheimer's disease

  1. Top of page
  2. Abstract
  3. Memory formation via gene expression control
  4. Histone-modifications in memory formation
  5. Histone-modifications in Alzheimer's disease
  6. DNA-methylation in Alzheimer's disease
  7. Non-coding RNA in Alzheimer's disease
  8. How much Lamarck is in our memories?
  9. Conflict of interest
  10. References

The best-studied non-coding RNAs in brain disease are miRs that have gained increasing interested as potential biomarker and novel therapeutic strategies. A number of studies identified miRs that are up or down-regulated in post-mortem brain tissue from AD patients or in AD mouse models. While most of these studies are descriptive, there is also evidence that miRs deregulated in AD are mechanistically linked to the pathogenesis. For example, there is now substantial evidence that the miR29 cluster is down-regulated in AD brains (Hébert et al, 2008). The beta-secretase BACE1 is a direct target of miR29 and thus decreased miR29 levels lead to elevated BACE1 levels that promotes amyloid pathology (Hébert et al, 2008). Interestingly, other miRs that target BACE1 such as miR107, miR298, miR328 have also been linked to AD (Wang et al, 2008a; Boissonneault et al, 2009; Nelson & Wang, 2010). Moreover, SNPs located within miR29 binding sites of the bace1 gene correlated with sporadic AD (Bettens et al, 2009). Notably, such SNPs were also found for the app gene (Bettens et al, 2009) and also other miRs such as miR16 and miR101 were linked to app expression (Vilardo et al, 2010; Long & Lahiri, 2011; Liu et al, 2012a,b). However, since one miR targets multiple mRNAs, it will be important to further understand the role of the gene expression and protein networks controlled by individual miRs.

Unbiased screening approaches were employed to identify miRs that are affected by amyloid pathology. For example, treatment of hippocampal neurons with Aß42 peptides led to altered levels of 21 miRs. Cross-correlation with data from a mouse model for amyloid deposition and human brain tissue identified miR9, Mir181c, let7i, miR30c, miR148b and miR20 to be key miRs affected by amyloid (Schonrock et al, 2010). Another study could confirm elevated expression of miR146a in five different mouse models for amyloid deposition (Li et al, 2011b). Notably, miR146a was also found to be down-regulated in hippocampal neurons after Aß42 treatment in the Schonrock study (Schonrock et al, 2010)—albeit not in the APP mouse model—indicating the need to link screening approaches with subsequent mechanistic studies.

Another miR cluster that has been repeatedly linked to AD pathogenesis and age-associated memory impairment is miR34. Cortical miR34a was found to be up-regulated in a mouse model for amyloid deposition. It was furthermore shown that miR34a controls caspase activity via the expression of BCL2, thereby contributing to AD pathogenesis (Wang et al, 2009). miR34c was also identified as a key regulator of learning-induced gene expression and is increased in hippocampal tissue from AD patients and in AD mouse models (Zovoilis et al, 2011). Targeting the miR34 cluster was able the reinstate memory function in a mouse model for amyloid deposition which was linked to the regulation of the SIRT1 protein (Zovoilis et al, 2011), a class III HDAC implicated with life span and brain diseases (Donmez, 2013). Moreover, miR34a was linked to the down-regulation of TREM2 in human AD brains (Zhao et al, 2013; Alexandrov et al, 2013), a gene that has been recently identified as a risk factor for sporadic AD (Guerreiro et al, 2013), further pointing to an important role of miR34 in AD. While the above-described data suggest that elevated miR34 levels contribute to AD pathogenesis, a recent study found that inhibition of miR34a led to elevated TAU expression, suggesting that in such a context increasing rather than inhibiting miR34a should have therapeutic potential in AD (Dickson et al, 2013). Moreover, up-regulation of miR34a extends median life span in the fruit fly (Liu et al, 2012a,b), indicating that more research is needed to fully appreciate the role of this miR in the adult mammalian brain.

The use of miRs as biomarker is of particular interest in AD research because pathogenesis begins about 20 years before the onset of clinical symptoms (Bateman et al, 2012). miRs are very stable compared to other potential biomarker such as proteins or mRNAs. Thus, a number of studies started to investigate miRs in cerebrospinal fluid (CSF) or in blood samples from AD patients and animal models. For example, levels of miR34a were elevated in serum obtained from aged rats when compared to young animals (Li et al, 2011a). An early study by Cogswell et al used a TaqMan PCR array to study miRs in brain and CSF from AD patients and non-demented controls (Cogswell et al, 2008). Interestingly, among other miRs, miR34a and 29a/b levels were increased AD brain tissue. The same study also analyzed miR levels in post-mortem CSF samples from individuals with B&B stage 1 (Braak & Braak staging, Box 1) compared to B&B stage 5. Notably, no CSF changes were observed for miR34 or miR29a/b, and the overall correlation between brain and CSF changes was rather poor. Nevertheless, some interesting observations were made. For example, the miR30 cluster was increased in CSF and decreased in the hippocampus, while miR125b was increased in both, brain and CSF (Cogswell et al, 2008). Another recent study used a similar approach and investigated eight selected miRs in post-mortem human hippocampus and CSF from AD patients and controls (Müller et al, 2014). Altered levels of miR16, miR34c, miR107, miR128a and miR146a were detected in the hippocampus, which correlates well with previous studies. Analysis of CSF samples was hindered by detection limits and blood contamination, but reliable detection of lower miR146a levels in AD was reported (Müller et al, 2014). In a targeted approach, let7-b was found to be increased in the CSF from AD patients (Lehmann et al, 2012). These data indicate the changes in miR levels can be detected in CSF, but that the methodological approaches need to be improved and the presently available data should be considered as being preliminary. A recent study employed the array-based nano-string technology to study miR levels in CSF from AD patients and identified miR27-3p to be reduced in the CSF from AD patients (Sala Frigerio et al, 2013) while its levels increase in the hippocampus of individuals that suffered from AD (Lau et al, 2013). The use of next-generation sequencing to study the entire small non-coding RNAome in CSF from AD patients and controls would be another option that may allow for a complete unbiased and quantitative measurement of CSF miRs. One important issue that needs to be solved is the source of miRs detected in human CSF. For example, miRs can be bound to lipoproteins (Vickers et al, 2011) or Argonaute (Arroyo et al, 2011) but are also found in cell-derived small vesicles named exosomes or microvesicles (Valadi et al, 2007).

A few studies have analyzed miRs in blood samples from AD patients. Using micro array technology, 462 miRs were analyzed in mononuclear blood cells (MBCs) comparing AD patients to healthy controls (Schipper et al, 2007). Notably miR34a and miR181b were found to be increased in AD patients (Schipper et al, 2007), which is interesting since both have been linked to memory function or AD pathogenesis (Cogswell et al, 2008; Wang et al, 2009; Zovoilis et al, 2011; Saba et al, 2012; Zhao et al, 2013). Another miR that has been linked to AD and was found to be down-regulated in MBCs from AD patients is miR29b (Villa et al, 2013).

In comparison with the data available for micro RNAs, there is limited knowledge on the role of other non-coding RNAs in AD. But not too surprisingly, changes in lincRNAs have been observed in AD. For example, it was found that the non-coding RNA BC200, which is believed to regulate dendritic protein synthesis, is increased in AD patients, while it decreases with normal aging (Mus et al, 2007). It has to be mentioned that an early study found down-regulation of BC200 in Brodman area 22 of AD patients (Lukiw et al, 1992). Other studies found increased levels of lncRNAs that affect genes linked to amyloid metabolism (Faghihi et al, 2008; Ciarlo et al, 2013) or neurotransmission (Massone et al, 2011). Moreover, SNPs in lincRNAs have been associated with brain structure and cognitive function (Chen et al, 2013). While mechanistically little is known on the role of lncRNAs or small RNAs in AD, especially the lncRNAs might be interesting for future research, since they can modulate protein function and at the same time interact in a sequence-dependent manner with DNA or RNA.

Meeting the future in neuroepigenetics

How do chromatin plasticity and the underlying enzymatic machinery contribute to memory formation in health and disease? The current data suggest that, for example, the regulation of gene expression via histone-acetylation or DNA-methylation plays a role, but conclusive data are still lacking. Future approaches must study the genome-wide distribution of enzymes such as HATs and HDACs, as well as other regulators of chromatin structure via ChIP-sequencing, and correlate such data with gene expression, histone-modifications or DNA-methylation. While the basal level of gene expression or gene expression changes linked to chronic disease states often, but not always correlate well with the chromatin state of a given gene (Wang et al, 2008b; Peleg et al, 2010; Valor et al, 2013; Vashishtha et al, 2013; Ng et al, 2013; Lopez-Atalaya et al, 2013; Crepaldi et al, 2013), there are little genome-wide data to support the view that transient changes in gene expression as they are, for example, seen in response to memory training indeed correlate with altered histone-modifications at the corresponding genes in brain cells.

Another key issue the field needs to address in the future is cell type specificity. Most studies still investigate epigenetic processes in heterogenous brain tissue, which can be particularly misleading when interpreting data obtained from AD models or human brain tissue in which the glia/neuron ration is changed due to inflammatory processes and neuronal cell death. There are different options to overcome such problems. Cell type specificity can be obtained, for example, via established methods to isolate cells from complex tissue via fluorescence-activated cell sorting (FACS). Such approaches are especially powerful when fluorescent markers such as GFP are expressed in the cell type of interest, for example, in dopaminergic neurons, which has been successfully used to study epigenetic processes in distinct populations of brain cells (Jordi et al, 2013). A disadvantage of isolating intact cells from brain tissue via FACS is the fact that cells need to be dissociated before sorting which usually involves prolonged incubation at 37°C in the presence of proteases such as trypsin or papain. Such protocols are only successful if fresh tissue from early developmental stages is used and even here a substantial amount of cells do not survive the procedure. Taking into account that memory training was found to induce epigenetic changes already within 30–60 min (Levenson et al, 2004; Miller et al, 2007; Zovoilis et al, 2011; Peleg et al, 2010), it is difficult to judge whether results obtained by such methods truly reflect the in vivo situation. Another approach is of course to isolate cells via laser capture microdissection, which is however very time consuming.

An alternative strategy is to directly sort nuclei using endogenous marker proteins (Jiang et al, 2008). This method has the advantage that cells do not need to be dissociated during long incubation times. For example, nuclei sorting via staining for the neuronal marker protein NeuN was found suitable to study neuronal versus non-neuronal chromatin marks via ChIP-PCR or NGS analysis (Jiang et al, 2008; Shulha et al, 2012b). Advanced protocols such as the batch-isolation of tissue specific chromatin for immunoprecipitation (BiTS-ChIP) have been successfully used to isolate chromatin even from fixed nuclei thereby allowing a direct view at the chromatin at the time of tissue isolation (Bonn et al, 2012a; Bonn et al, 2012b). There is no reason to believe that such an approach should not work for brain tissue. In conjunction with next-generation sequencing technologies and advanced bioinformatics analysis, these methods will allow for an unprecedented insight to cell-type-specific chromatin dynamics in the adult brain. Machine learning approaches appear to be particularly suitable to decipher the epigenetic code from data obtained via genome-wide analysis (Bonn et al, 2012a). However, even the most sophisticated bioinformatics analysis of next-generation sequencing data will only describe epigenetic networks. In order to understand such networks, subsequent steps must involve hypothesis-driven mechanistic research (Fig 3).

Figure 3. Understanding the epigenome of learning and memory

1. Experimental approaches to test memory function in model systems should be employed to define the epigenetic landscape of memory formation. Well-studied examples are mice that are subjected to hippocampus-dependent memory training such as contextual fear conditioning. 2. In order to understand how the epigenome shapes neuronal circuitries, it will be essential to isolate distinct cell types for epigenome analysis. This could be achieved in a meaningful manner via fluorescence-activated cell sorting of nuclei that will then be subjected to epigenome profiling using next-generation sequencing (NGS) approaches. 3. Bioinformatic analysis and computational modeling will be an essential tool to understand the molecular networks linked to memory formation in health and disease. 4. This will allow researchers to formulate novel hypothesis about the underlying mechanisms that shall then be tested using suitable models systems. For example, mutant mice that lack or overexpress the hub within a given network. The effect of such manipulation and the epigenetic network can then be tested again using cell-type-specific epigenome profiling.

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How much Lamarck is in our memories?

  1. Top of page
  2. Abstract
  3. Memory formation via gene expression control
  4. Histone-modifications in memory formation
  5. Histone-modifications in Alzheimer's disease
  6. DNA-methylation in Alzheimer's disease
  7. Non-coding RNA in Alzheimer's disease
  8. How much Lamarck is in our memories?
  9. Conflict of interest
  10. References

Epigenetic processes are dynamic yet persistent at the same time, and DNA does not replicate in post-mitotic neurons. Thus, there is little chance for altering the genetic code other than by transposon activity or mutations (Muotri et al, 2007), which are rare events. DNA-methylation provides another layer to encode information in DNA without changing its nucleotide sequence. Patterns of DNA-methylation can be very persistent and are maintained across generations, yet they are not irreversible, and especially in neurons there is increasing evidence showing that in some genomic regions DNA-methylation is quite dynamically regulated during memory formation. An interesting example of DNA-methylation transmitting acquired information across generations stems from studies that investigate the effect of early life stress on cognitive function. Early life stress is a prominent risk factor for neuropsychiatric diseases, and in rodents it leads to increased anxiety and depressive-like behavior that can be observed even in the offspring, albeit this second generation was never exposed to such stress (Franklin et al, 2010). This effect has been linked to altered DNA-methylation of the corticotropin-releasing factors receptor 2 in the brain and in the germ line. Another recent study investigated the consolidation of fear memories for specific odors. This type of learning correlated with neuroanatomical changes in the olfactory system and altered expression of the relevant odor-receptor (Dias & Ressler, 2013). Notably, such changes were also observed in the subsequent generation that consequently showed enhanced odor learning. Mechanistically, this phenotype was linked to altered DNA-methylation of the relevant odor-receptor (Dias & Ressler, 2013).

The same principle is true for histone-modifications that can be dynamically regulated in response to environmental stimuli, and changes in histone-modifications have been linked to the transmission of phenotypes across generations. For example, liver damage in rats initiates a hepatic wound healing program that eventually leads to changes in histone-methylation and DNA-methylation in genes linked to fibrosis (Zeybel et al, 2012). Notably such changes were also observed in sperm, and indeed the offspring of such rats could better adapt to liver damage (Zeybel et al, 2012). An interesting observation of this study was the fact that serum transfer from animals that were exposed to liver damage to a control group caused the same transgenerational phenotypes, suggesting that a factor present in blood must mediate epigenetic changes in the germ cells (Zeybel et al, 2012).

How such environmental stimuli mediate epigenetic changes in brain cells and in germ cells is however not well understood.

Similarly, non-coding RNAs are affected by learning processes but can also mediate phenotypic changes across generations. A fascinating example is paramutations that have been well studied, for example, in plants (Cuzin et al, 2008) but also occur in mammals. In mice, it was found that presence of miR 221 and miR 222 in germ cells was responsible for the transfer of a specific phenotype linked to tail color to the subsequent generation (Rassoulzadegan et al, 2006).

There are other remarkable examples in which epigenetic processes define in a stable yet reversible manner an organisms behavior (Herb et al, 2012), and although not all of the above-discussed examples are directly linked to memory formation as we understand it, such findings illustrate that epigenetic processes are in a bona fide position when it comes to long-term information storage. Namely, they allow the compromise between the competing needs for flexibility of a system to update existing memories and the necessary stability that is required to maintain a once consolidated memory trace.

In fact, there is a substantial amount of literature investigating how epigenetic processes mediate long-term memory formation in other organisms such as plants that can for example “remember” the previous winter. Vernalization describes the ability of a plant to flower in the spring depending on a cold period during the previous winter. This process critically involves histone-modifications (He et al, 2003), DNA-methylation (Bastow et al, 2004) but also the action of non-coding RNAs such as the lncRNAs coolair and coldair (Heo & Sung, 2011; He & Amasino, 2005; Swiezewski et al, 2009) that orchestrate the corresponding gene expression programs.

It is thus tempting to speculate that an epigenetic code could be part of the engram. The nature of the engram is still a mystery, but the predominant view suggests that structural changes occurring at synapses which represent specific neuronal networks recruited during memory consolidation are an essential part of it (Routtenberg, 2013). Could it be possible that part of the information processed in such networks is permanently stored within the chromatin of the corresponding cells? Although this is pure speculation, in favor of this view it was shown that formerly lost memories could be reinstated in a mouse model for severe neurodegeneration when mice received an epigenetic drug, in this case an HDAC inhibitor (Fischer et al, 2007).

It will therefore be important in future studies to investigate the mechanism by which the synapse within a particular neuronal circuitry communicates to the corresponding nucleus and to understand how the nucleus integrates such signals on the level of the chromatin. Moreover, in order to address such questions, it will be essential to study only the cells that contribute to such networks. This will also be important in the context of brain disease such as loAD that are caused by variable combinations of genetic and environmental risk factors. If the epigenome indeed serves as a molecular read out for life experience—including the exposure to AD risk factors—it might be possible to develop powerful epigenetic biomarkers and disease modifying therapies for such devastating diseases without the necessity to identify or target all possible risk factors directly (Fig 4).

Figure 4. The epigenome as a read out for life experience and disease risk

Throughout lifetime an organism is exposed to variable environmental stimuli that can initiate memory consolidation processes. On the basis of the existing data, it can be speculated that consolidation of such life experiences into memories critically involve long-term epigenetic changes. Such epigenetic signatures may even be transmitted to the next generation thereby influencing the phenotype of the coming generations. Part of such life experiences represents the interaction of genetic and non-genetic risk factors for brain diseases such as Alzheimer disease. I hypothesize that also such risk factors lead to a disease-specific epigenetic signature and a corresponding gene expression profile that may even affect disease risk in the next generation. As such epigenetic signatures may serve as bona fide biomarkers and therapeutic strategies to target, the epigenome may turn out to be more beneficial than directly targeting the multiple risk factors that are believed to contribute to disease pathogenesis.

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In conclusion, to study epigenetic processes in memory formation during health and disease is a fascinating novel area of research that still offers great challenges but also a unique chance to further understand how the brain stores information and to develop novel therapeutic approaches to treat patients in which memory function is disturbed.


  1. Top of page
  2. Abstract
  3. Memory formation via gene expression control
  4. Histone-modifications in memory formation
  5. Histone-modifications in Alzheimer's disease
  6. DNA-methylation in Alzheimer's disease
  7. Non-coding RNA in Alzheimer's disease
  8. How much Lamarck is in our memories?
  9. Conflict of interest
  10. References
  • Agbemenyah HY, Agis-Balboa RC, Burkhardt S, Delalle I, Fischer A (2013) Insulin growth factor binding protein 7 is a novel target to treat dementia. Neurobiol Dis 25: 135143
  • Agis-Balboa RC, Arcos-Diaz DA, Wittnam J, Govindarajan N, Blom K, Burkhardt S, Haladyniak U, Agbemenyah HY, Zovoilis A, Salinas-Riester G, Opitz L, Sananbenesi F, Fischer A (2011) A hippocampal insulin-growth factor 2 pathway regulates the extinction of fear memories. EMBO J 30: 40714083
  • Agis-Balboa RC, Pavelka Z, Kerimoglu C, Fischer A (2013) Loss of HDAC5 impairs memory function: implications for Alzheimer's disease. J Alzheimers Dis 33: 3544
  • Akhtar MW, Raingo J, Nelson ED, Montgomery RL, Olson EN, Kavalali ET, Monteggia LM (2009) Histone deacetylases 1 and 2 form a developmental switch that controls excitatory synapse maturation and function. J Neurosci 29: 82888297
  • Alarcon JM, Malleret G, Touzani K, Vronskaya S, Ishii S, Kandel ER, Barco A (2004) Chromatin acetylation, memory, and LTP are impaired in CBP+/− mice: a model for the cognitive deficit in Rubinstein-Taybi syndrome and its amelioration. Neuron 42: 947959
  • Alexandrov PN, Zhao Y, Jones BM, Bhattacharjee S, Lukiw WJ (2013) Expression of the phagocytosis-essential protein TREM2 is down-regulated by an aluminum-induced miRNA-34a in a murine microglial cell line. J Inorg Biochem 128: 267269
  • Allis CD, Berger SL, Cote J, Dent S, Jenuwein T, Kouzarides T, Pillus L, Reinberg D, Shi Y, Shiekhattar R, Shilatifard A, Workman J, Zhang Y (2007) New nomenclature for chromatin-modifying enzymes. Cell 131: 633636
  • Anguera MC, Ma W, Clift D, Namekawa S, Kelleher, Lee JT, R Jr, Lee JT (2011) Tsx produces a long noncoding RNA and has general functions in the germline, stem cells, and brain. PLoS Genet 7: e1002248
  • Arefin AS, Mathieson L, Johnstone D, Berretta R, Moscato P (2012) Unveiling clusters of RNA transcript pairs associated with markers of Alzheimer's disease progression. PLoS One 7: e45535
  • Arroyo JD, Chevillet JR, Kroh EM, Ruf IK, Pritchard CC, Gibson DF, Mitchell PS, Bennett CF, Pogosova-Agadjanyan EL, Stirewalt DL, Tait JF, Tewari M (2011) Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc Natl Acad Sci USA 108: 50035008
  • Backs J, Song K, Bezprozvannaya S, Chang S, Olson EN (2006) CaM kinase II selectively signals to histone deacetylase 4 during cardiomyocyte hypertrophy. J Clin Invest 116: 18531864
  • Badeaux AI, Shi Y (2013) Emerging roles for chromatin as a signal integration and storage platform. Nat Rev Mol Cell Biol 14: 211224
  • Bahari-Javan S, Maddalena A, Kerimoglu C, Wittnam J, Held T, Bähr M, Burkhardt S, Delalle I, Kügler S, Fischer A, Sananbenesi F (2012) HDAC1 regulates fear extinction in mice. J Neurosci 32: 50625073
  • Bakulski KM, Dolinoy DC, Sartor MA, Paulson HL, Konen JR, Lieberman AP, Albin RL, Hu H, Rozek LS (2012) Genome-wide DNA methylation differences between late-onset Alzheimer's disease and cognitively normal controls in human frontal cortex. J Alzheimers Dis 29: 571588
  • Bannister AJ, Kouzarides T (2011) Regulation of chromatin by histone modifications. Cell Res 21: 381395
  • Bardai FH, Price V, Zaayman M, Wang L, D'Mello SR (2012) Histone deacetylase-1 (HDAC1) is a molecular switch between neuronal survival and death. J Biol Chem 287: 3544435453
  • Barrachina M, Ferrer I (2009) DNA methylation of Alzheimer disease and tauopathy-related genes in postmortem brain. J Neuropathol Exp Neurol 68: 880891
  • Barrett RM, Malvaez M, Kramar E, Matheos DP, Arrizon A, Cabrera SM, Lynch G, Greene RW, Wood MA (2011) Hippocampal focal knockout of CBP affects specific histone modifications, long-term potentiation, and long-term memory. Neuropsychopharmacology 36: 15451556
  • Bastow R, Mylne JS, Lister C, Lippman Z, Martienssen RA, Dean C (2004) Vernalization requires epigenetic silencing of FLC by histone methylation. Nature 427: 164167
  • Bateman RJ, Xiong C, Benzinger TL, Fagan AM, Goate A, Fox NC, Marcus DS, Cairns NJ, Xie X, Blazey TM, Holtzman DM, Santacruz A, Buckles V, Oliver A, Moulder K, Aisen PS, Ghetti B, Klunk WE, McDade E, Martins RN et al; Dominantly Inherited Alzheimer Network (2012) Clinical and biomarker changes in dominantly inherited Alzheimer's disease. N Engl J Med 367: 795804
  • Bates EA, Victor M, Jones AK, Shi Y, Hart AC (2006) Differential contributions of Caenorhabditis elegans histone deacetylases to huntingtin polyglutamine toxicity. J Neurosci 26: 28302838
  • Bettens K, Brouwers N, Engelborghs S, Van Miegroet H, De Deyn PP, Theuns J, Sleegers K, Van Broeckhoven C (2009) APP and BACE1 miRNA genetic variability has no major role in risk for Alzheimer disease. Hum Mutat 30: 12071213
  • Blalock EM, Buechel HM, Popovic J, Geddes JW, Landfield PW (2011) Microarray analyses of laser-captured hippocampus reveal distinct gray and white matter signatures associated with incipient Alzheimer's disease. J Chem Neuroanat 42: 118126
  • Boissonneault V, Plante I, Rivest S, Provost P (2009) MicroRNA-298 and microRNA-328 regulate expression of mouse beta-amyloid precursor protein-converting enzyme 1. J Biol Chem 284: 19711981
  • Bollati V, Galimberti D, Pergoli L, Dalla Valle E, Barretta F, Cortini F, Scarpini E, Bertazzi PA, Baccarelli A (2011) DNA methylation in repetitive elements and Alzheimer disease. Brain Behav Immun 25: 10781083
  • Bonn S, Zinzen RP, Girardot C, Gustafson EH, Gonzalez AP, Delhomme N, Ghavi-Helm Y, Wilczynski B, Riddell A, Furlong EEM (2012a) Tissue specific analysis of chromatin state identifies temporal signatures of enhancer activity during embryonic development. Nat Genet 44: 148156
  • Bonn S, Zinzen RP, Perez-Gonzalez A, Riddell A, Gavin AC, Furlong EE (2012b) Cell type-specific chromatin immunoprecipitation from multicellular complex samples using BiTS-ChIP. Nat Protoc 7: 978994
  • Bourtchouladze R, Lidge R, Catapano R, Stanley J, Gossweiler S, Romashko D, Scott R, Tully T (2003) A mouse model of Rubinstein-Taybi syndrome: defective long-term memory is ameliorated by inhibitors of phosphodiesterase 4. Proc Natl Acad Sci USA 100: 1051810522
  • Brockschmidt FF, Heilmann S, Ellis JA, Eigelshoven S, Hanneken S, Herold C, Moebus S, Alblas MA, Lippke B, Kluck N, Priebe L, Degenhardt FA, Jamra RA, Meesters C, Jöckel KH, Erbel R, Harrap S, Schumacher J, Fröhlich H, Kruse R et al (2011) Susceptibility variants on chromosome 7p21.1 suggest HDAC9 as a new candidate gene for male-pattern baldness. Br J Dermatol 165: 12931302
  • Brohede J, Rinde M, Winblad B, Graff C (2010) A DNA methylation study of the amyloid precursor protein gene in several brain regions from patients with familial Alzheimer disease. J Neurogenet 24: 179181
  • Broide RS, Redwine JM, Aftahi N, Young W, Bloom FE, Winrow CJ (2007) Distribution of histone deacetylases 1–11 in the rat brain. J Mol Neurosci 31: 4758
  • Caccamo A, Maldonado MA, Bokov AF, Majumder S, Oddo S (2010) 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 107: 2268722692
  • Caldeira GL, Ferreira IL, Rego AC (2013) Impaired transcription in Alzheimer's disease: key role in mitochondrial dysfunction and oxidative stress. J Alzheimers Dis 34: 115131
  • Cao L, Jiao X, Zuzga DS, Liu Y, Fong DM, Young D, During MJ (2004) VEGF links hippocampal activity with neurogenesis, learning and memory. Nat Genet 36: 827835
  • Chatterjee S, Mizar P, Cassel R, Neidl R, Selvi BR, Mohankrishna DV, Vedamurthy BM, Schneider A, Bousiges O, Mathis C, Cassel JC, Eswaramoorthy M, Kundu TK, Boutillier AL (2013) A novel activator of CBP/p300 acetyltransferases promotes neurogenesis and extends memory duration in adult mice. J Neurosci 33: 1069810712
  • Chawla S, Vanhoutte P, Arnold FJ, Huang CL, Bading H (2003) Neuronal activity-dependent nucleocytoplasmic shuttling of HDAC4 and HDAC5. J Neurochem 85: 151159
  • Chen G, Zou X, Watanabe H, van Deursen JM, Shen J (2010a) CREB binding protein is required for both short-term and long-term memory formation. J Neurosci 30: 1306613070
  • Chen G, Qiu C, Zhang Q, Liu B, Cui Q (2013) Genome-wide analysis of human SNPs at long intergenic noncoding RNAs. Hum Mutat 34: 338344
  • Chen T, Ueda Y, Xie S, Li E (2002) A novel Dnmt3a isoform produced from an alternative promoter localizes to euchromatin and its expression correlates with active de novo methylation. J Biol Chem 277: 3874638754
  • Chen TF, Huang RF, Lin SE, Lu JF, Tang MC, Chiu MJ (2010b) Folic Acid potentiates the effect of memantine on spatial learning and neuronal protection in an Alzheimer's disease transgenic model. J Alzheimers Dis 20: 607615
  • Chen YT, Zang XF, Pan J, Zhu XL, Chen F, Chen ZB, Xu Y (2012) Expression patterns of histone deacetylases in experimental stroke and potential targets for neuroprotection. Clin Exp Pharmacol Physiol 39: 751758
  • Cho Y, Sloutsky R, Naegle KM, Cavalli V (2013) Injury-induced HDAC5 nuclear export is essential for axon regeneration. Cell 155: 894908
  • Chouliaras L, van den Hove DL, Kenis G, Keitel S, Hof PR, van Os J, Steinbusch HW, Schmitz C, Rutten BP (2012) Age-related increase in levels of 5-hydroxymethylcytosine in mouse hippocampus is prevented by caloric restriction. Curr Alzheimer Res 9: 536544
  • Chwang WB, O'Riordan KJ, Levenson JM, Sweatt JD (2006) ERK/MAPK regulates hippocampal histone phosphorylation following contextual fear conditioning. Learn Mem 13: 322328
  • Ciarlo E, Massone S, Penna I, Nizzari M, Gigoni A, Dieci G, Russo C, Florio T, Cancedda R, Pagano A (2013) An intronic ncRNA-dependent regulation of SORL1 expression affecting Aβ formation is upregulated in post-mortem Alzheimer's disease brain samples. Dis Model Mech 6: 424433
  • Cogswell JP, Ward J, Taylor I, Waters M, Shi Y, Cannon B, Kelnar K, Kemppainen J, Brown D, Chen C, Prinjha RK, Richardson JC, Saunders AM, Roses AD, Richards C (2008) Identification of miRNA changes in Alzheimer's disease brain and CSF yields putative biomarkers and insights into disease pathways. J Alzheimers Dis 14: 2741
  • Cong SY, Pepers BA, Evert BO, Rubinsztein DC, Roos RA, van Ommen GJ, Dorsman JC (2005) Mutant huntingtin represses CBP, but not p300, by binding and protein degradation. Mol Cell Neurosci 30: 560571
  • Cook C, Gendron TF, Scheffel K, Carlomagno Y, Dunmore J, DeTure M, Petrucelli L (2012) Loss of HDAC6, a novel CHIP substrate, alleviates abnormal tau accumulation. Hum Mol Genet 21: 29362945
  • Cook C, Carlomagno Y, Gendron TF, Dunmore J, Scheffel K, Stetler C, Davis M, Dickson D, Jarpe M, Deture M, Petrucelli L (2013) Acetylation of the KXGS motifs in tau is a critical determinant in modulation of tau aggregation and clearance. Hum Mol Genet 23: 104116
  • Coppedè F, Zitarosa MT, Migheli F, Lo Gerfo A, Bagnoli S, Dardano A, Nacmias B, Mancuso M, Monzani F, Siciliano G, Sorbi S, Migliore L (2012) DNMT3B promoter polymorphisms and risk of late onset Alzheimer's disease. Curr Alzheimer Res 9: 550554
  • Coppieters N, Dragunow M (2011) Epigenetics in Alzheimer's disease: a focus on DNA modifications. Curr Pharm Des 17: 33983412
  • Crepaldi L, Policarpi C, Coatti A, Sherlock WT, Jongbloets BC, Down TA, Riccio A (2013) Binding of TFIIIC to sine elements controls the relocation of activity-dependent neuronal genes to transcription factories. PLoS Genet 9: e1003699
  • Cruz JC, Kim D, Moy LY, Dobbin MM, Sun X, Bronson RT, Tsai LH (2006) p25/cyclin-dependent kinase 5 induces production and intraneuronal accumulation of amyloid beta in vivo. J Neurosci 26: 1053610541
  • Cruz JC, Tseng HC, Goldman JA, Shih H, Tsai LH (2003) Aberrant Cdk5 activation by p25 triggers pathological events leading to neurodegeneration and neurofibrillary tangles. Neuron 40: 471483
  • Cuzin F, Grandjean V, Rassoulzadegan M (2008) Inherited variation at the epigenetic level: paramutation from the plant to the mouse. Curr Opin Genet Dev 18: 193196
  • Dangour AD, Whitehouse P, Rafferty K, Mitchell SA, Smith L, Hawkesworth S, Vellas B (2010) B-vitamins and fatty acids in the prevention and treatment of Alzheimer's disease and dementia: a systematic review. J Alzheimers Dis 22: 205224
  • Davis HS, Squire LR (1984) Protein synthesis and memory: a review. Psychol Bull 96: 518559
  • Day JJ, Childs D, Guzman-Karlsson MC, Kibe M, Moulden J, Song E, Tahir A, Sweatt JD (2013) DNA methylation regulates associative reward learning. Nat Neurosci 16: 14451452
  • De Pietri Tonelli D, Pulvers JN, Haffner C, Murchison EP, Hannon GJ, Huttner WB (2008) miRNAs are essential for survival and differentiation of newborn neurons but not for expansion of neural progenitors during early neurogenesis in the mouse embryonic neocortex. Development 153: 39113921
  • Dias BG, Ressler KJ (2013) Parental olfactory experience influences behavior and neural structure in subsequent generations. Nat Neurosci 17: 8996
  • Dickson JR, Kruse C, Montagna DR, Finsen B, Wolfe MS (2013) Alternative polyadenylation and miR-34 family members regulate tau expression. J Neurochem 127: 739749
  • Ding H, Dolan PJ, Johnson GV (2008) Histone deacetylase 6 interacts with the microtubule-associated protein tau. J Neurochem 106: 21192130
  • Dobbin MM, Madabhushi R, Pan L, Chen Y, Kim D, Gao J, Ahanonu B, Pao PC, Qiu Y, Zhao Y, Tsai LH (2013) SIRT1 collaborates with ATM and HDAC1 to maintain genomic stability in neurons. Nat Neurosci 16: 10081015
  • Donmez G (2013) Sirtuins as possible targets in neurodegenerative diseases. Curr Drug Targets 14: 644647
  • Duclot F, Meffre J, Jacquet C, Gongora C, Maurice T (2010) Mice knock out for the histone acetyltransferase p300/CREB binding protein-associated factor develop a resistance to amyloid toxicity. Neuroscience 167: 850863
  • Edbauer D, Neilson JR, Foster KA, Wang CF, Seeburg DP, Batterton MN, Tada T, Dolan BM, Sharp PA, Sheng M (2010) Regulation of synaptic structure and function by FMRP-associated microRNAs miR-125b and miR-132. Neuron 65: 373384
  • Faghihi MA, Modarresi F, Khalil AM, Wood DE, Sahagan BG, Morgan TE, Finch CE, St Laurent G III, Kenny PJ, Wahlestedt C (2008) Expression of a noncoding RNA is elevated in Alzheimer's disease and drives rapid feed-forward regulation of beta-secretase. Nat Med 14: 723730
  • Fatica A, Bozzoni I (2013) Long non-coding RNAs: new players in cell differentiation and development. Nat Rev Genet 15: 721.
  • Federman N, Fustiñana MS, Romano A (2009) Histone acetylation is recruited in consolidation as a molecular feature of stronger memories. Learn Mem 16: 600606
  • Feng J, Zhou Y, Campbell SL, Le T, Li E, Sweatt JD, Silva AJ, Fan G (2010) Dnmt1 and Dnmt3a maintain DNA methylation and regulate synaptic function in adult forebrain neurons. Nat Neurosci 13: 423430
  • Ferrante RJ, Kubilus JK, Lee J, Ryu H, Beesen A, Zucker B, Smith K, Kowall NW, Ratan RR, Luthi-Carter R, Hersch SM (2003) Histone deacetylase inhibition by sodium butyrate chemotherapy ameliorates the neurodegenerative phenotype in Huntington's disease mice. J Neurosci 23: 94189427
  • Fiore R, Khudayberdiev S, Saba R, Schratt G (2011) MicroRNA function in the nervous system. Prog Mol Biol Transl Sci 102: 47100
  • Fischer A, Sananbenesi F, Pang PT, Lu B, Tsai LH (2005) Opposing roles of transient and prolonged expression of p25 in synaptic plasticity and hippocampus-dependent memory. Neuron 48: 825838
  • Fischer A, Sananbenesi F, Wang X, Dobbin M, Tsai LH (2007) Recovery of learning & memory after neuronal loss is associated with chromatin remodeling. Nature 447: 178182
  • Fischer A, Sananbenesi F, Mungenast A, Tsai LH (2010) Targeting the right HDAC(s) to treat congitive diseases. Trends Pharmacol Sci 31: 605617
  • Flexner JB, Flexner LB, Stellar E, De La Haba G, Roberts RB (1962) Inhibition of protein synthesis in brain and learning and memory following puromycin. J Neurochem 9: 595605
  • Flexner JB, Flexner LB, Stellar E (1963) Memory in mice as affected by intracerebral puromycin. Science 141: 5759
  • Fontán-Lozano A, Romero-Granados R, Troncoso J, Múnera A, Delgado-García JM, Carrión AM (2008) Histone deacetylase inhibitors improve learning consolidation in young and in KA-induced-neurodegeneration and SAMP-8-mutant mice. Mol Cell Neurosci 39: 193201
  • Fontán-Lozano A, Suárez-Pereira I, Horrillo A, del-Pozo-Martín Y, Hmadcha A, Carrión AM (2010) Histone H1 poly[ADP]-ribosylation regulates the chromatin alterations required for learning consolidation. J Neurosci 30: 1330513313
  • Francis YI, Diss JK, Kariti M, Stephanou A, Latchman DS (2007) p300 activation by Presenilin 1 but not by its M146L mutant. Neurosci Lett 14: 137140
  • Francis YI, Fà M, Ashraf H, Zhang H, Staniszewski A, Latchman DS, Arancio O (2009) Dysregulation of histone acetylation in the APP/PS1 mouse model of Alzheimer's disease. J Alzheimers Dis 18: 131139
  • Franklin TB, Russig H, Weiss IC, Gräff J, Linder N, Michalon A, Vizi S, Mansuy IM (2010) Epigenetic transmission of the impact of early stress across generations. Biol Psychiatry 68: 408415
  • Frey U, Morris RG (1998) Synaptic tagging: implications for late maintenance of hippocampal long-term potentiation. Trends Neurosci 21: 181188
  • Funato H, Oda S, Yokofujita J, Igarashi H, Kuroda M (2011) Fasting and high-fat diet alter histone deacetylase expression in the medial hypothalamus. PLoS One 6: e18950
  • Fuso A, Cavallaro RA, Nicolia V, Scarpa S (2012a) PSEN1 promoter demethylation in hyperhomocysteinemic TgCRND8 mice is the culprit, not the consequence. Curr Alzheimer Res 9: 527535
  • Fuso A, Nicolia V, Ricceri L, Cavallaro RA, Isopi E, Mangia F, Fiorenza MT, Scarpa S (2012b) S-adenosylmethionine reduces the progress of the Alzheimer-like features induced by B-vitamin deficiency in mice. Neurobiol Aging 33: 116
  • Gao J, Wang WY, Mao YW, Gräff J, Guan JS, Pan L, Mak G, Kim D, Su SC, Tsai LH (2010) A novel pathway regulates memory and plasticity via SIRT1 and miR-134. Nature 466: 11051109
  • Gardian G, Browne SE, Choi DK, Klivenyi P, Gregorio J, Kubilus JK, Ryu H, Langley B, Ratan RR, Ferrante RJ, Beal MF (2005) Neuroprotective effects of phenylbutyrate in the N171-82Q transgenic mouse model of Huntington's disease. J Biol Chem 280: 556563
  • Ge S, Goh EL, Sailor KA, Kitabatake Y, Ming GL, Song H (2005) GABA regulates synaptic integration of newly generated neurons in the adult brain. Nature 439: 589593
  • Ginsberg SD, Alldred MJ, Counts SE, Cataldo AM, Neve RL, Jiang Y, Wuu J, Chao MV, Mufson EJ, Nixon RA, Che S (2010) Microarray analysis of hippocampal CA1 neurons implicates early endosomal dysfunction during Alzheimer's disease progression. Biol Psychiatry 68: 885893
  • Goate A, Hardy J (2012) Twenty years of Alzheimer's disease-causing mutations. J Neurochem 120: 38
  • Govindarajan N, Agis-Balboa C, Walter J, Sananbenesi F, Fischer A (2011) Sodium butyrate improves memory function in an Alzheimer's disease mouse model when administered at an advanced stage of disease progression. J Alzheimers Dis 24: 111
  • Govindarajan N, Rao P, Burkhardt S, Sananbenesi F, Schlüter OM, Bradke F, Lu J, Fischer A (2013) Reducing HDAC6 ameliorates cognitive deficits in a mouse model for Alzheimer's disease. EMBO Mol Med 5: 5263
  • 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 (2012) An epigenetic blockade of cognitive functions in the neurodegenerating brain. Nature 483: 7388
  • Gregoretti IV, Lee YM, Goodson HV (2004) Molecular evolution of the histone deacetylase family: functional implications of phylogenetic analysis. J Mol Biol 338: 1731
  • 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 (2009) HDAC2 negatively regulates memory formation and synaptic plasticity. Nature 459: 5560
  • Guerreiro R, Wojtas A, Bras J, Carrasquillo M, Rogaeva E, Majounie E, Cruchaga C, Sassi C, Kauwe JS, Younkin S, Hazrati L, Collinge J, Pocock J, Lashley T, Williams J, Lambert JC, Amouyel P, Goate A, Rademakers R, Morgan K et al; Alzheimer Genetic Analysis Group (2013) TREM2 variants in Alzheimer's disease. N Engl J Med 368: 117127
  • Guibert S, Weber M (2013) Functions of DNA methylation and hydroxymethylation in mammalian development. Curr Top Dev Biol 104: 4783
  • Guo JU, Ma DK, Mo H, Ball Madeleine P, Jang M-H, Bonaguidi Michael A, Balazer Jacob A, Eaves Hugh L, Xie B, Ford E, Zhang K, Ming G-L, Gao Y, Song H (2011) Neuronal activity modifies DNA methylation landscape in the adult brain. Nat Neurosci 14: 13451351
  • Gupta S, Kim SY, Artis S, Molfese DL, Schumacher A, Sweatt JD, Paylor RE, Lubin FD (2010) Histone methylation regulates memory formation. J Neurosci 30: 35893599
  • Gupta-Agarwal S, Franklinm AV, Deramusm T, Wheelockm M, Davism RL, McMahonm LL, Lubin FD (2012) G9a/GLP histone lysine dimethyltransferase complex activity in the hippocampus and the entorhinal cortex is required for gene activation and silencing during memory consolidation. J Neurosci 32: 54405453
  • Haass C, Selkoe DJ (2007) Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer's amyloid beta-peptide. Nat Rev Mol Cell Biol 8: 112116
  • Hanson JE, La H, Plise E, Chen YH, Ding X, Hanania T, Sabath EV, Alexandrov V, Brunner D, Leahy E, Steiner P, Liu L, Scearce-Levie K, Zhou Q (2013) SAHA enhances synaptic function and plasticity in vitro but has limited brain availability in vivo and does not impact cognition. PLoS One 8: e69964
  • Haramati S, Navon I, Issler O, Ezra-Nevo G, Gil S, Zwang R, Hornstein E, Chen A (2011) MicroRNA as repressors of stress-induced anxiety: the case of amygdalar miR-34. J Neurosci 31: 1419114203
  • He Y, Michaels SD, Amasino RM (2003) Regulation of flowering time by histone acetylation in Arabidopsis. Science 302: 17511754
  • He Y, Amasino RM (2005) Role of chromatin modification in flowering-time control. Trends Plant Sci 10: 3035
  • Hébert SS, Horré K, Nicolaï L, Papadopoulou AS, Mandemakers W, Silahtaroglu AN, Kauppinen S, Delacourte A, De Strooper B (2008) 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 205: 64156420
  • Heo JB, Sung S (2011) Vernalization-mediated epigenetic silencing by a long intronic noncoding RNA. Science 331: 7679
  • Herb F, Wolschin F, Hansen KD, Aryee MJ, Langmead B, Irizarry R, Amdam GV, Feinberg AP (2012) Reversible switching between epigenetic states in honeybee behavioral subcastes. Nat Neurosci 15: 13711373
  • Herrup K, Li J, Chen J (2013) The role of ATM and DNA damage in neurons: upstream and downstream connections. DNA Repair 12: 600604
  • Hinterberger M, Fischer P (2013) Folate and Alzheimer: when time matters. J Neural Transm 120: 211224
  • Hockly E, Richon VM, Woodman B, Smith DL, Zhou X, Rosa E, Sathasivam K, Ghazi-Noori S, Mahal A, Lowden PA, Steffan JS, Marsh JL, Thompson LM, Lewis CM, Marks PA, Bates GP (2003) Suberoylanilide hydroxamic acid, a histone deacetylase inhibitor, ameliorates motor deficits in a mouse model of Huntington's disease. Proc Natl Acad Sci USA 100: 20412046
  • Holliday R (1994) Epigenetics: an overview. Dev Genet 15: 453457
  • Host L, Dietrich JB, Carouge D, Aunis D, Zwiller J (2011) Cocaine self-administration alters the expression of chromatin-remodelling proteins; modulation by histone deacetylase inhibition. J Psychopharmacol 25: 222229
  • van den Hove DL, Chouliaras L, Rutten BP (2012) The role of 5-hydroxymethylcytosine in aging and Alzheimer's disease: current status and prospects for future studies. Curr Alzheimer Res 9: 545549
  • Hu E, Dul E, Sung CM, Chen Z, Kirkpatrick R, Zhang GF, Johanson K, Liu R, Lago A, Hofmann G, Macarron R, de los Frailes M, Perez P, Krawiec J, Winkler J, Jaye M (2003) Identification of novel isoform-selective inhibitors within class I histone deacetylases. J Pharmacol Exp Ther 307: 720728
  • Igaz LM, Vianna MR, Medina JH, Izquierdo I (2002) Two time periods of hippocampal mRNA synthesis are required for memory consolidation of fear-motivated learning. J Neurosci 22: 67816791
  • Im HI, Kenny PJ (2012) MicroRNAs in neuronal function and dysfunction. Trends Neurosci 35: 325334
  • Impey S, Davare M, Lesiak A, Fortin D, Ando H, Varlamova O, Obrietan K, Soderling TR, Goodman RH, Wayman GA (2010) An activity-induced microRNA controls dendritic spine formation by regulating Rac1-PAK signaling. Mol Cell Neurosci 49: 250
  • Iwata A, Nagata K, Hatsuta H, Takuma H, Bundo M, Iwamoto K, Tamaoka A, Murayama S, Saido T, Tsuji S (2013) Altered CpG methylation in sporadic Alzheimer's disease is associated with APP and MAPT dysregulation. Hum Mol Genet 23: 648656
  • Jakovcevski M, Akbarian S (2012) Epigenetic mechanisms in neurological disease. Nat Med 18: 11941204
  • Jakovcevski M, Bharadwaj R, Straubhaar J, Gao G, Gavin DP, Jakovcevski I, Mitchell AC, Akbarian S (2013) Prefrontal cortical dysfunction after overexpression of histone deacetylase 1. Biol Psychiatry 74: 696705
  • Jawerka M, Colak D, Dimou L, Spiller C, Lagger S, Montgomery RL, Olson EN, Wurst W, Göttlicher M, Götz M (2010) The specific role of histone deacetylase 2 in adult neurogenesis. Neuron Glia Biol 14: 115
  • Jia H, Pallos J, Jacques V, Lau A, Tang B, Cooper A, Syed A, Purcell J, Chen Y, Sharma S, Sangrey GR, Darnell SB, Plasterer H, Sadri-Vakili G, Gottesfeld JM, Thompson LM, Rusche JR, Marsh JL, Thomas EA (2012) Histone deacetylase (HDAC) inhibitors targeting HDAC3 and HDAC1 ameliorate polyglutamine-elicited phenotypes in model systems of Huntington's disease. Neurobiol Dis 4: 351361
  • Jiang H, Poirier MA, Liang Y, Pei Z, Weiskittel CE, Smith WW, DeFranco DB, Ross CA (2006) Depletion of CBP is directly linked with cellular toxicity caused by mutant huntingtin. Neurobiol Dis 23: 543551
  • Jiang Y, Matevossian A, Huang HS, Straubhaar J, Akbarian S (2008) Isolation of neuronal chromatin from brain tissue. BMC Neurosci 28: 942
  • Jiang Y, Jakovcevski M, Bharadwaj R, Connor C, Schroeder FA, Lin CL, Straubhaar J, Martin G, Akbarian S (2010) Setdb1 histone methyltransferase regulates mood-related behaviors and expression of the NMDA receptor subunit NR2B. J Neurosci 30: 71527267
  • Johnson AA, Sarthi J, Pirooznia SK, Reube W, Elefant F (2013) Increasing Tip60 HAT levels rescues axonal transport defects and associated behavioral phenotypes in a Drosophila Alzheimer's disease model. J Neurosci 33: 75357547
  • Jordi E, Heiman M, Marion-Poll L, Guermonprez P, Cheng SK, Nairn AC, Greengard P, Girault JA (2013) Differential effects of cocaine on histone posttranslational modifications in identified populations of striatal neurons. Proc Natl Acad Sci USA 110: 95119516
  • Josselyn SA (2005) What's right with my mouse model? New insights into the molecular and cellular basis of cognition from mouse models of Rubinstein-Taybi Syndrome. Learn Mem 12: 8083
  • Kaas GA, Zhong C, Eason DE, Ross DL, Vachhani RV, Ming GL, King JR, Song H, Sweatt JD (2013) TET1 controls CNS 5-methylcytosine hydroxylation, active DNA demethylation, gene transcription, and memory formation. Neuron 79: 10861093
  • Kaidi A, Jackson SP (2013) KAT5 tyrosine phosphorylation couples chromatin sensing to ATM signalling. Nature 498: 7074
  • Karr J, Vagin V, Chen K, Ganesan S, Olenkina O, Gvozdev V, Featherstone DE (2009) Regulation of glutamate receptor subunit availability by microRNAs. J Cell Biol 185: 685697
  • Kenney JW, Poole RL, Adoff MD, Logue SF, Gould TJ (2012) Learning and nicotine interact to increase CREB phosphorylation at the jnk1 promoter in the hippocampus. PLoS One 7: e399939
  • Kerimoglu C, Agis-Balboa RC, Kranz A, Stilling R, Bahari-Javan S, Benito-Garagorri E, Halder R, Burkhardt S, Stewart AF, Fischer A (2013) Histone-methyltransferase mll2 (kmt2b) is required for memory formation in mice. J Neurosci 33: 34523464
  • 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 (2008) Determination of the class and isoform selectivity of small-molecule histone deacetylase inhibitors. Biochem J 409: 581589
  • Kilgore M, Miller CA, Fass DM, Hennig KM, Haggarty SJ, Sweatt JD, Rumbaugh G (2010) Inhibitors of class 1 histone deacetylases reverse contextual memory deficits in a mouse model of Alzheimer's disease. Neuropsychopharmacology 35: 870880
  • Kim D, Frank CL, Dobbin MM, Tsunemoto RK, Tu W, Peng PL, Guan JS, Lee BH, Moy LY, Giusti P, Broodie N, Mazitschek R, Delalle I, Haggarty SJ, Neve RL, Lu Y, Tsai LH (2008) Deregulation of HDAC1 by p25/Cdk5 in neurotoxicity. Neuron 60: 803817
  • Kim JY, Shen S, Dietz K, He Y, Howell O, Reynolds R, Casaccia P (2010) HDAC1 nuclear export induced by pathological conditions is essential for the onset of axonal damage. Nat Neurosci 13: 180189
  • Kim KH, Moon M, Yu SB, Mook-Jung I, Kim JI (2012a) RNA-Seq analysis of frontal cortex and cerebellum from 5XFAD mice at early stage of disease pathology. J Alzheimers Dis 29: 793808
  • Kim MS, Akhtar MW, Adachi M, Mahgoub M, Bassel-Duby R, Kavalali ET, Olson EN, Monteggia LM (2012b) An essential role for histone deacetylase 4 in synaptic plasticity and memory formation. J Neurosci 32: 1087910886
  • Klevytska AM, Tebbenkamp AT, Savonenko AV, Borchelt DR (2010) Partial depletion of CREB-binding protein reduces life expectancy in a mouse model of Huntington disease. J Neuropathol Exp Neurol 69: 396404
  • Konopka W, Kiryk A, Novak M, Herwerth M, Parkitna JR, Wawrzyniak M, Kowarsch A, Michaluk P, Dzwonek J, Arnsperger T, Wilczynski G, Merkenschlager M, Theis FJ, Köhr G, Kaczmarek L, Schütz G (2010) MicroRNA loss enhances learning and memory in mice. J Neurosci 30: 1483514842
  • Korzus E, Rosenfeld MG, Mayford M (2004) CBP histone acetyltransferase activity is a critical component of memory consolidation. Neuron 42: 961972
  • Koshibu K, Gräff J, Beullens M, Heitz FD, Berchtold D, Russig H, Farinelli M, Bollen M, Mansuy IM (2009) Protein phosphatase 1 regulates the histone code for long-term memory. J Neurosci 29: 1307913089
  • Kramer JM, Kochinke K, Oortveld MA, Marks H, Kramer D, de Jong EK, Asztalos Z, Westwood JT, Stunnenberg HG, Sokolowski MB, Keleman K, Zhou H, van Bokhoven H, Schenck A (2011) Epigenetic regulation of learning and memory by Drosophila EHMT/G9a. PLoS Biol 9: e1000569
  • Kriaucionis S, Heintz N (2009) The nuclear DNA base 5-hydroxymethylcytosine is present in Purkinje neurons and the brain. Science 324: 929930
  • Labrie V, Pai S, Petronis A (2012) Epigenetics of major psychosis: progress, problems and perspectives. Trends Genet 28: 427435
  • Landry CD, Kandel ER, Rajasethupathy P (2013) New mechanisms in memory storage: piRNAs and epigenetics. Trends Neurosci 36: 535542
  • Lang B, Alrahbeni TM, Clair DS, Blackwood DH; International Schizophrenia Consortium, McCaig CD, Shen S (2011) HDAC9 is implicated in schizophrenia and expressed specifically in post-mitotic neurons but not in adult neural stem cells. Am J Stem Cells 18: 3141
  • Lau P, Bossers K, Janky R, Salta E, Frigerio CS, Barbash S, Rothman R, Sierksma AS, Thathiah A, Greenberg D, Papadopoulou AS, Achsel T, Ayoubi T, Soreq H, Verhaagen J, Swaab DF, Aerts S, De Strooper B (2013) Alteration of the microRNA network during the progression of Alzheimer's disease. EMBO Mol Med 5: 16131634
  • Lee K, Kim JH, Kwon OB, An K, Ryu J, Cho K, Suh YH, Kim HS (2012a) An activity-regulated microRNA, miR-188, controls dendritic plasticity and synaptic transmission by downregulating neuropilin-2. J Neurosci 32: 56785687
  • Lee KK, Workman JL (2007) Histone acetyltransferase complexes: one size doesn't fit all. Nat Rev Mol Cell Biol 8: 285295
  • Lee ST, Chu K, Jung KH, Kim JH, Huh JY, Yoon H, Park DK, Lim JY, Kim JM, Jeon D, Ryu H, Lee SK, Kim M, Roh JK (2012b) miR-206 regulates brain-derived neurotrophic factor in Alzheimer disease model. Ann Neurol 72: 269277
  • Lehmann SKC, Park B, Derkow K, Rosenberger K, Baumgart J, Trimbuch T, Eom G, Hinz M, Kaul D, Habbel P, Kälin R, Franzoni E, Rybak A, Nguyen D, Veh R, Ninnemann O, Peters O, Nitsch R, Heppner FL, Golenbock D et al (2012) An unconventional role for miRNA: let-7 activates Toll-like receptor 7 and causes neurodegeneration. Nat Neurosci 15: 827835
  • Levenson JM, O'Riordan KJ, Brown KD, Trinh MA, Molfese DL, Sweatt JD (2004) Regulation of histone acetylation during memory formation in the hippocampus. J Biol Chem 279: 4054540559
  • Li X, Khanna A, Li N, Wang E (2011a) Circulatory miR34a as an RNAbased, noninvasive biomarker for brain aging. Aging 3: 9851002
  • Li YY, Cui JG, Hill JM, Bhattacharjee S, Zhao Y, Lukiw WJ (2011b) Increased expression of miRNA-146a in Alzheimer's disease transgenic mouse models. Neurosci Lett 487: 9498
  • Liang WS, Dunckley T, Beach TG, Grover A, Mastroeni D, Ramsey K, Caselli RJ, Kukull WA, McKeel D, Morris JC, Hulette CM, Schmechel D, Reiman EM, Rogers J, Stephan DA (2010) Neuronal gene expression in non-demented individuals with intermediate Alzheimer's Disease neuropathology. Neurobiol Aging 31: 549566
  • Lin Q, Wei W, Coelho CM, Li X, Baker-Andresen D, Dudley K, Ratnu VS, Boskovic Z, Kobor MS, Sun YE, Bredy TW (2011) The brain-specific microRNA miR-128b regulates the formation of fear-extinction memory. Nat Neurosci 14: 11151117
  • Lippi G, Steinert JR, Marczylo EL, D'Oro S, Fiore R, Forsythe ID, Schratt G, Zoli M, Nicotera P, Young KW (2011) Targeting of the Arpc3 actin nucleation factor by miR-29a/b regulates dendritic spine morphology. J Cell Biol 194: 889904
  • Liu N, Landreh M, Cao K, Abe M, Hendriks GJ, Kennerdell JR, Zhu Y, Wang LS, Bonini NM (2012a) The microRNA miR-34 modulates ageing and neurodegeneration in Drosophila. Nature 482: 519523
  • Liu W, Liu C, Zhu J, Shu P, Yin B, Gong Y, Qiang B, Yuan J, Peng X (2012b) MicroRNA-16 targets amyloid precursor protein to potentially modulate Alzheimer's-associated pathogenesis in SAMP8 mice. Neurobiol Aging 33: 522534
  • Long JM, Lahiri DK (2011) MicroRNA-101 downregulates Alzheimer's amyloid-β precursor protein levels in human cell cultures and is differentially expressed. Biochem Biophys Res Commun 28: 889895
  • Lopez-Atalaya JP, Ciccarelli A, Viosca J, Valor LM, Jimenez-Minchan M, Canals S, Giustetto M, Barco A (2011) CBP is required for environmental enrichment-induced neurogenesis and cognitive enhancement. EMBO J 30: 42874298
  • Lopez-Atalaya JP, Ito S, Valor LM, Benito E, Barco A (2013) Genomic targets, and histone acetylation and gene expression profiling of neural HDAC inhibition. Nucleic Acids Res 41: 80728084
  • Lu T, Pan Y, Kao SY, Li C, Kohane I, Chan J, Yankner BA (2004) Gene regulation and DNA damage in the ageing human brain. Nature 429: 883891
  • Lubin FD, Roth TL, Sweatt JD (2008) Epigenetic regulation of BDNF gene transcription in the consolidation of fear memory. J Neurosci 28: 1057610586
  • Lukiw WJ, Handley P, Wong L, Crapper McLachlan DR (1992) BC200 RNA in normal human neocortex, non-Alzheimer dementia (NAD), and senile dementia of the Alzheimer type (AD). Neurochem Res 17: 591597
  • Mahgoub M, Monteggia L (2013) Epigenetics and psychiatry. Neurotherapeutics 10: 734741
  • Mangialasche F, Solomon A, Winblad B, Mecocci P, Kivipelto M (2010) Alzheimer's disease: clinical trials and drug development. Lancet Neurol 9: 702716
  • Mao P, Reddy PH (2011) Aging and amyloid beta-induced oxidative DNA damage and mitochondrial dysfunction in Alzheimer's disease: implications for early intervention and therapeutics. Biochim Biophys Acta 1812: 13591370
  • Markus HS, Mäkelä KM, Bevan S, Raitoharju E, Oksala N, Bis JC, O'Donnell C, Hainsworth A, Lehtimäki T (2013) Evidence HDAC9 genetic variant associated with ischemic stroke increases risk via promoting carotid atherosclerosis. Stroke 44: 12201225
  • Martin LJ (2008) DNA damage and repair: relevance to mechanisms of neurodegeneration. J Neuropathol Exp Neurol 67: 377387
  • Massone S, Vassallo I, Fiorino G, Castelnuovo M, Barbieri F, Borghi R, Tabaton M, Robello M, Gatta E, Russo C, Florio T, Dieci G, Cancedda R, Pagano A (2011) 17A, a novel non-coding RNA, regulates GABA B alternative splicing and signaling in response to inflammatory stimuli and in Alzheimer disease. Neurobiol Dis 41: 308317
  • Mastroeni D, McKee A, Grover A, Rogers J, Coleman PD (2009) Epigenetic differences in cortical neurons from a pair of monozygotic twins discordant for Alzheimer's disease. PLoS One 4: e6617
  • Maurice T, Duclot F, Meunier J, Naert G, Givalois L, Meffre J, Célérier A, Jacquet C, Copois V, Mechti N, Ozato K, Gongora C (2008) Altered memory capacities and response to stress in p300/CBP-associated factor (PCAF) histone acetylase knockout mice. Neuropsychopharmacology 33: 15841602
  • Maze I, Covington HE III, Dietz DM, LaPlant Q, Renthal W, Russo SJ, Mechanic M, Mouzon E, Neve RL, Haggarty SJ, Ren Y, Sampath SC, Hurd YL, Greengard P, Tarakhovsky A, Schaefer A, Nestler EJ (2010) Essential role of the histone methyltransferase G9a in cocaine-induced plasticity. Science 327: 213216
  • McFarland KN, Das S, Sun TT, Leyfer D, Xia E, Sangrey GR, Kuhn A, Luthi-Carter R, Clark TW, Sadri-Vakili G, Cha JH (2012) Genome-wide histone acetylation is altered in a transgenic mouse model of Huntington's disease. PLoS One 7: e41423
  • McNulty SE, Barrett RM, Vogel-Ciernia A, Malvaez M, Hernandez N, Davatolhagh MF, Matheos DP, Schiffman A, Wood MA (2012) Differential roles for Nr4a1 and Nr4a2 in object location vs. object recognition long-term memory. Learn Mem 19: 588592
  • McQuown SC, Barrett RM, Matheos DP, Post RJ, Rogge GA, Alenghat T, Mullican SE, Jones S, Rusche JR, Lazar MA, Wood MA (2011) HDAC3 is a critical negative regulator of long-term memory formation. J Neurosci 31: 764774
  • Miller CA, Sweatt JD (2007) Covalent modification of DNA regulates memory formation. Neuron 53: 857869
  • Miller CA, Campbell SL, Sweatt JD (2007) DNA methylation and histone acetylation work in concert to regulate memory formation and synaptic plasticity. Neurobiol Learn Mem 89: 857869
  • Miller CA, Campbell SL, Sweatt JD (2008) DNA methylation and histone acetylation work in concert to regulate memory formation and synaptic plasticity. Neurobiol Learn Mem 89: 599603
  • Mills JD, Nalpathamkalam T, Jacobs HI, Janitz C, Merico D, Hu P, Janitz M (2013) RNA-Seq analysis of the parietal cortex in Alzheimer's disease reveals alternatively spliced isoforms related to lipid metabolism. Neurosci Lett 1: 9095
  • 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 (2010) Acetylation of tau inhibits its degradation and contributes to tauopathy. Neuron 67: 953966
  • Moncada D, Ballarini F, Martinez MC, Frey JU, Viola H (2011) Identification of transmitter systems and learning tag molecules involved in behavioral tagging during memory formation. Proc Natl Acad Sci USA 108: 1293112936
  • Morris MJ, Mahgoub M, Na ES, Pranav H, Monteggia LM (2013) Loss of histone deacetylase 2 improves working memory and accelerates extinction learning. J Neurosci 33: 64016411
  • Müller M, Kuiperij HB, Claassen JA, Küsters B, Verbeek MM (2014) MicroRNAs in Alzheimer's disease: differential expression in hippocampus and cell-free cerebrospinal fluid. Neurobiol Aging 35: 152158
  • Müller T, Schrötter A, Loosse C, Pfeiffer K, Theiss C, Kauth M, Meyer HE, Marcus K (2013) A ternary complex consisting of AICD, FE65, and TIP60 down-regulates Stathmin1. Biochim Biophys Acta 1834: 387394
  • Muotri AR, Marchetto MC, Coufal NG, Gage FH (2007) The necessary junk: new functions for transposable elements. Hum Mol Genet 16: R159.167
  • Mus E, Hof PR, Tiedge H (2007) Dendritic BC200 RNA in aging and in Alzheimer's disease. Proc Natl Acad Sci USA 104: 1067910684
  • Na ES, Nelson ED, Kavalali ET, Monteggia LM (2013) The impact of MeCP2 loss- or gain-of-function on synaptic plasticity. Neuropsychopharmacology 38: 212219
  • Neelamegam R, Ricq EL, Malvaez M, Patnaik D, Norton S, Carlin SM, Hill IT, Wood MA, Haggarty SJ, Hooker JM (2012) Brain-penetrant LSD1 inhibitors can block memory consolidation. ACS Chem Neurosci 3: 120128
  • Nelson PT, Wang WX (2010) MiR-107 is reduced in Alzheimer's disease brain neocortex: validation study. J Alzheimers Dis 21: 7579
  • Ng CW, Yildirim F, Yap YS, Dalin S, Matthews BJ, Velez PJ, Labadorf A, Housman DE, Fraenkel E (2013) Extensive changes in DNA methylation are associated with expression of mutant huntingtin. Proc Natl Acad Sci USA 110: 23542359
  • Ng SB, Bigham AW, Buckingham KJ, Hannibal MC, McMillin MJ, Gildersleeve HI, Beck AE, Tabor HK, Cooper GM, Mefford HC, Lee C, Turner EH, Smith JD, Rieder MJ, Yoshiura K, Matsumoto N, Ohta T, Niikawa N, Nickerson DA, Bamshad MJ et al (2010) Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome. Nat Genet 42: 790793
  • Nithianantharajah J, Hannan AJ (2006) Enriched environments, experience-dependent plasticity and disorders of the nervous system. Nat Rev Neurosci 7: 697709
  • Oike Y, Hata A, Mamiya T, Kaname T, Noda Y, Suzuki M, Yasue H, Nabeshima T, Araki K, Yamamura K (1999) Truncated CBP protein leads to classical Rubinstein-Taybi syndrome phenotypes in mice: implications for a dominant-negative mechanism. Hum Mol Genet 8: 387396
  • Oliveira AM, Wood MA, McDonough CB, Abel T (2007) Transgenic mice expressing an inhibitory truncated form of p300 exhibit long-term memory deficits. Learn Mem 14: 564572
  • Oliveira AM, Hemstedt TJ, Bading H (2012) Rescue of aging-associated decline in Dnmt3a2 expression restores cognitive abilities. Nat Neurosci 15: 11111113
  • Pajonk FG, Wobrock T, Gruber O, Scherk H, Berner D, Kaizl I, Kierer A, Mueller M, Oest M, Meyer T, Backens M, Schneider-Axmann T, Thornton AE, Honer WG, Falkai P (2010) Hippocampal plasticity in response to exercise in schizophrenia. Arch Gen Psychiatry 67: 133143
  • Park CS, Rehrauer H, Mansuy IM (2013) Genome-wide analysis of H4K5 acetylation associated with fear memory in mice. BMC Genomics 8: 539545
  • Pastor WA, Aravind L, Rao A (2013) TETonic shift: biological roles of TET proteins in DNA demethylation and transcription. Nat Rev Mol Cell Biol 14: 341356
  • Peleg S, Sananbenesi F, Zovoilis A, Burkhardt S, Bahari-Java S, Agis-Balboa RC, Cota P, Wittnam J, Gogul-Doering A, Opitz L, Salinas-Riester G, Dettenhofer M, Kang H, Farinelli L, Chen W, Fischer A (2010) Altered histone acetylation is associated with age-dependent memory impairment in mice. Science 328: 753756
  • 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 (2009) Tau–an inhibitor of deacetylase HDAC6 function. J Neurochem 109: 17551766
  • Petrij F, Giles RH, Dauwerse HG, Saris JJ, Hennekam RC, Masuno M, Tommerup N, van Ommen GJ, Goodman RH, Peters DJ (1995) Rubinstein-Taybi syndrome caused by mutations in the transcriptional co-activator CBP. Nature 376: 348351
  • Pirooznia SK, Sarthi J, Johnson AA, Toth MS, Chiu K, Koduri S, Elefant F (2012) Tip60 HAT activity mediates APP induced lethality and apoptotic cell death in the CNS of a Drosophila Alzheimer's disease model. PLoS One 7: e41776
  • Poirel CL, Rahman A, Rodrigues RR, Krishnan A, Addesa JR, Murali TM (2013) Reconciling differential gene expression data with molecular interaction networks. Bioinformatics 29: 622629
  • Qureshi IA, Mehler MF (2012) Emerging roles of non-coding RNAs in brain evolution, development, plasticity and disease. Nat Rev Neurosci 13: 528541
  • Rajasethupathy P, Fiumara F, Sheridan R, Betel D, Puthanveettil SV, Russo JJ, Sander C, Tuschl T, Kandel E (2009) Characterization of small RNAs in Aplysia reveals a role for miR-124 in constraining synaptic plasticity through CREB. Neuron 63: 803817
  • Rajasethupathy P, Antonov I, Sheridan R, Frey S, Sander C, Tuschl T, Kandel ER (2012) A role for neuronal piRNAs in the epigenetic control of memory-related synaptic plasticity. Cell 149: 693707
  • Rao JS, Keleshian VL, Klein S, Rapoport SI (2012) Epigenetic modifications in frontal cortex from Alzheimer's disease and bipolar disorder patients. Transl Psychiatry 3: e132
  • Rassoulzadegan M, Grandjean V, Gounon P, Vincent S, Gillot I, Cuzin F (2006) RNA-mediated non-Mendelian inheritance of an epigenetic change in the mouse. Nature 441: 469474
  • Renthal W, Maze I, Krishnan V, Covington HE III, Xiao G, Kumar A, Russo SJ, Graham A, Tsankova N, Kippin TE, Kerstetter KA, Neve RL, Haggarty SJ, McKinsey TA, Bassel-Duby R, Olson EN, Nestler EJ (2007) Histone deacetylase 5 epigenetically controls behavioral adaptations to chronic emotional stimuli. Neuron 56: 517529
  • Reolon GK, Maurmann N, Werenicz A, Garcia VA, Schröder N, Wood MA, Roesler R (2011) Posttraining systemic administration of the histone deacetylase inhibitor sodium butyrate ameliorates aging-related memory decline in rats. Brain Res 221: 329332
  • Ricobaraza A, Cuadrado-Tejedor M, Pérez-Mediavilla A, Frechilla D, Del Río J, García-Osta A (2009) Phenylbutyrate ameliorates cognitive deficit and reduces tau pathology in an Alzheimer's disease mouse model. Neuropsychopharmacology 34: 17211732
  • Ricobaraza A, Cuadrado-Tejedor M, Marco S, Pérez-Otaño I, García-Osta A (2010) Phenylbutyrate rescues dendritic spine loss associated with memory deficits in a mouse model of Alzheimer disease. Hippocampus 22: 10401050
  • Roberson ED, Scearce-Levie K, Palop JJ, Yan F, Cheng IH, Wu T, Gerstein H, Yu GQ, Mucke L (2007) Reducing endogenous tau ameliorates amyloid beta-induced deficits in an Alzheimer's disease mouse model. Science 316: 750754
  • Routtenberg A (2013) Lifetime memories from persistently supple synapses. Hippocampus 23: 202206
  • Rudenko A, Dawlaty MM, Seo J, Cheng AW, Meng J, Le T, Faull KF, Jaenisch R, Tsai LH (2013) Tet1 is critical for neuronal activity-regulated gene expression and memory extinction. Neuron 79: 11091122
  • de Ruijter AJ, van Gennip AH, Caron HN, Kemp S, van Kuilenburg AB (2003) Histone deacetylases (HDACs): characterization of the classical HDAC family. Biochem J 370: 737749
  • Rujirabanjerd S, Nelson J, Tarpey PS, Hackett A, Edkins S, Raymond FL, Schwartz CE, Turner G, Iwase S, Shi Y, Futreal PA, Stratton MR, Gecz J (2012) Identification and characterization of two novel JARID1C mutations: suggestion of an emerging genotype-phenotype correlation. Eur J Hum Genet 18: 330335
  • Saba R, Störchel PH, Aksoy-Aksel A, Kepura F, Lippi G, Plant TD, Schratt GM (2012) Dopamine-regulated microRNA MiR-181a controls GluA2 surface expression in hippocampal neurons. Mol Cell Biol 32: 619632
  • Sadri-Vakili G, Bouzou B, Benn CL, Kim MO, Chawla P, Overland RP, Glajch KE, Xia E, Qiu Z, Hersch SM, Clark TW, Yohrling GJ, Cha JH (2007) Histones associated with downregulated genes are hypo-acetylated in Huntington's disease models. Hum Mol Genet 161: 12931306
  • Sala Frigerio C, Laum P, Saltam E, Tournoy J, Bossers K, Vandenberghe R, Wallin A, Bjerke M, Zetterberg H, Blennow K, De Strooper B (2013) Reduced expression of hsa-miR-27a-3p in CSF of patients with Alzheimer disease. Neurology 81: 21032106
  • Sananbenesi F, Fischer A (2009) The epigenetic bottleneck of neurodegenerative and psychiatric diseases. Biol Chem 390: 11451153
  • Sando R III, Gounko N, Pieraut S, Liao L, Yates J III, Maximov A (2012) HDAC4 governs a transcriptional program essential for synaptic plasticity and memory. Cell 151: 821834
  • Sarthi J, Elefant F (2011) dTip60 HAT activity controls synaptic bouton expansion at the Drosophila neuromuscular junction. PLoS One 6: e26202
  • Schaefer A, Sampath SC, Intrator A, Min A, Gertler TS, Surmeier DJ, Tarakhovsky A, Greengard P (2009) Control of cognition and adaptive behavior by the GLP/G9a epigenetic suppressor complex. Neuron 64: 678691
  • Schipper HM, Maes OC, Chertkow HM, Wang E (2007) MicroRNA expression in Alzheimer blood mononuclear cells. Gene Regul Syst Bio 20: 263274
  • Schmitt M, Matthies H (1979) Biochemical studies on histones of the central nervous system. III. Incorporation of [14C]-acetate into the histones of different rat brain regions during a learning experiment. Acta Biol Med Ger 38: 683689
  • Schneider A, Chatterjee S, Bousiges O, Selvi BR, Swaminathan A, Cassel R, Blanc F, Kundu TK, Boutillier A (2013) Acetyltransferases (HATs) as targets for neurological therapeutics. Neurotherapeutics 10: 569588
  • Schonrock N, Ke YD, Humphreys D, Staufenbiel M, Ittner LM, Preiss T, Götz J (2010) Neuronal microRNA deregulation in response to Alzheimer's disease amyloid-beta. PLoS One 5: e11070
  • Schratt G (2009) microRNAs at the synapse. Nat Rev Neurosci 10: 842849
  • Schratt GM, Tuebing F, Nigh EA, Kane CG, Sabatini ME, Kiebler M, Greenberg ME (2006) A brain-specific microRNA regulates dendritic spine development. Nature 439: 283289
  • Scott HL, Tamagnini F, Narduzzo KE, Howarth JL, Lee YB, Wong LF, Brown MW, Warburton EC, Bashir ZI, Uney JB (2012) MicroRNA-132 regulates recognition memory and synaptic plasticity in the perirhinal cortex. Eur J Neurosci 36: 29412948
  • Selvi BR, Cassel JC, Kundu TK, Boutillier AL (2010) Tuning acetylation levels with HAT activators: therapeutic strategy in neurodegenerative diseases. Biochim Biophys Acta 1799: 840853
  • Sharma RP, Grayson DR, Gavin DP (2008) Histone deactylase 1 expression is increased in the prefrontal cortex of schizophrenia subjects: analysis of the National Brain Databank microarray collection. Schizophr Bull 98: 111117
  • Shi Y (2007) Histone lysine demethylases: emerging roles in development, physiology and disease. Nat Rev Genet 8: 829833
  • Shi Y, Whetstine JR (2007) Dynamic regulation of histone lysine methylation by demethylases. Mol Cell 25: 114
  • Shulha HP, Cheung I, Whittle C, Wang J, Virgil D, Lin CL, Guo Y, Lessard A, Akbarian S, Weng Z (2012a) Epigenetic signatures of autism: trimethylated H3K4 landscapes in prefrontal neurons. Arch Gen Psychiatry 69: 314324
  • Shulha HP, Crisci JL, Reshetov D, Tushir JS, Cheung I, Bharadwaj R, Chou HJ, Houston IB, Peter CJ, Mitchell AC, Yao WD, Myers RH, Chen JF, Preuss TM, Rogaev EI, Jensen JD, Weng Z, Akbarian S (2012b) Human-specific histone methylation signatures at transcription start sites in prefrontal neurons. PLoS Biol 10: e1001427
  • Siegel G, Obernosterer G, Fiore R, Oehmen M, Bicker S, Christensen M, Khudayberdiev S, Leuschner PF, Busch CJ, Kane C, Hübel K, Dekker F, Hedberg C, Rengarajan B, Drepper C, Waldmann H, Kauppinen S, Greenberg ME, Draguhn A, Rehmsmeier M et al (2009) A functional screen implicates microRNA-138-dependent regulation of the depalmitoylation enzyme APT1 in dendritic spine morphogenesis. Nat Cell Biol 11: 705716
  • Siegmund KD, Connor CM, Campan M, Long TI, Weisenberger DJ, Biniszkiewicz D, Jaenisch R, Laird PW, Akbarian S (2007) DNA methylation in the human cerebral cortex is dynamically regulated throughout the life span and involves differentiated neurons. PLoS One 2: e895
  • Silva PN, Gigek CO, Leal MF, Bertolucci PH, de Labio RW, Payão SL, Smith MA (2008) Promoter methylation analysis of SIRT3, SMARCA5, HTERT and CDH1 genes in aging and Alzheimer's disease. J Alzheimers Dis 13: 173176
  • Simensen RJ, Rogers RC, Collins JS, Abidi F, Schwartz CE, Stevenson RE (2012) Short-term memory deficits in carrier females with KDM5C mutations. Genet Couns 23: 3140
  • Spruijt CG, Gnerlich F, Smits AH, Pfaffeneder T, Jansen PW, Bauer C, Münzel M, Wagner M, Müller M, Khan F, Eberl HC, Mensinga A, Brinkman AB, Lephikov K, Müller U, Walter J, Boelens R, van Ingen H, Leonhardt H, Carell T et al (2013) Dynamic readers for 5-(hydroxy)methylcytosine and its oxidized derivatives. Cell 152: 11461159
  • Stadler F, Kolb G, Rubusch L, Baker SP, Jones EG, Akbarian S (2005) Histone methylation at gene promoters is associated with developmental regulation and region-specific expression of ionotropic and metabotropic glutamate receptors in human brain. J Neurochem 94: 324336
  • Stefanko DP, Barrett RM, Ly AR, Reolon GK, Wood MA (2009) Modulation of long-term memory for object recognition via HDAC inhibition. Proc Natl Acad Sci USA 106: 94479452
  • Steffan JS, Kazantsev A, Spasic-Boskovic O, Greenwald M, Zhu YZ, Gohler H, Wanker EE, Bates GP, Housman DE, Thompson LM (2000) The Huntington's disease protein interacts with p53 and CREB-binding protein and represses transcription. Proc Natl Acad Sci USA 97: 67636768
  • Steffan JS, Bodai L, Pallos J, Poelman M, McCampbell A, Apostol BL, Kazantsev A, Schmidt E, Zhu YZ, Greenwald M, Kurokawa R, Housman DE, Jackson GR, Marsh JL, Thompson LM (2001) Histone deacetylase inhibitors arrest polyglutamine-dependent neurodegeneration in Drosophila. Nature 413: 739743
  • Stilling RM, Fischer A (2011) The role of histone acetylation in age-associated memory impairment and Alzheimer's disease. Neurobiol Learn Mem 96: 1926
  • Strahl BD, Allis CD (2000) The language of covalent histone modifications. Nature 403: 4145
  • Suberbielle E, Sanchez PE, Kravitz AV, Wang X, Ho K, Eilertson K, Devidze N, Kreitzer AC, Mucke L (2013) Physiologic brain activity causes DNA double-strand breaks in neurons, with exacerbation by amyloid-β. Nat Neurosci 16: 613621
  • Sung YM, Lee T, Yoon H, DiBattista AM, Song J, Sohn Y, Moffat E, Turner RS, Jung M, Kim J, Hoe HS (2013) Mercaptoacetamide-based class II HDAC inhibitor lowers Aβ levels and improves learning and memory in a mouse model of Alzheimer's disease. Exp Neurol 239: 192201
  • Swank MW, Sweatt JD (2001) Increased histone acetyltransferase and lysine acetyltransferase activity and biphasic activation of the ERK/RSK cascade in insular cortex during novel taste learning. J Neurosci 21: 33833391
  • Swiezewski S, Liu F, Magusin A, Dean C (2009) Cold-induced silencing by long antisense transcripts of an Arabidopsis Polycomb target. Nature 462: 799802
  • Szulwach KE, Li X, Li Y, Song CX, Wu H, Dai Q, Irier H, Upadhyay AK, Gearing M, Levey AI, Vasanthakumar A, Godley LA, Chang Q, Cheng X, He C, Jin P (2011) 5-hmC-mediated epigenetic dynamics during postnatal neurodevelopment and aging. Nat Neurosci 14: 16071616
  • Traylor M, Farrall M, Holliday EG, Sudlow C, Hopewell JC, Cheng YC, Fornage M, Ikram MA, Malik R, Bevan S, Thorsteinsdottir U; Australian Stroke Genetics Collaborative, Wellcome Trust Case Control Consortium 2 (WTCCC2), Nalls MA, Longstreth W, Wiggins KL, Yadav S, Parati EA, Destefano AL, Worrall BB, Kittner SJ, Khan MS, Reiner AP, Helgadottir A, Achterberg S, Fernandez-Cadenas I, Abboud S, Schmidt R, Walters M, Chen WM, Ringelstein EB, O'Donnell M, Ho WK, Pera J, Lemmens R, Norrving B, Higgins P, Benn M, Sale M, Kuhlenbäumer G, Doney AS, Vicente AM, Delavaran H, Algra A, Davies G, Oliveira SA, Palmer CN, Deary I, Schmidt H, Pandolfo M, Montaner J, Carty C, de Bakker PI, Kostulas K, Ferro JM, van Zuydam NR, Valdimarsson E, Nordestgaard BG, Lindgren A, Thijs V, Slowik A, Saleheen D, Paré G, Berger K, Thorleifsson G, Hofman A, Mosley TH, Mitchell BD, Furie K, Clarke R, Levi C, Seshadri S, Gschwendtner A, Boncoraglio GB, Sharma P, Bis JC, Gretarsdottir S, Psaty BM, Rothwell PM, Rosand J, Meschia JF, Stefansson K, Dichgans M, Markus HS; International Stroke Genetics Consortium (2012) Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE collaboration): a meta-analysis of genome-wide association studies. Lancet Neurol 11: 951962
  • Tronson NC, Schrick C, Guzman YF, Huh KH, Srivastava DP, Penzes P, Guedea AL, Gao C, Radulovic J (2009) Segregated populations of hippocampal principal CA1 neurons mediating conditioning and extinction of contextual fear. J Neurosci 29: 33873394
  • Twine NA, Janitz K, Wilkins MR, Janitz M (2011) Whole transcriptome sequencing reveals gene expression and splicing differences in brain regions affected by Alzheimer's disease. PLoS One 6: e16266
  • Valadi H, Ekström K, Bossios A, Sjöstrand M, Lee JJ, Lötvall JO (2007) Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol 9: 654659
  • Valor LM, Pulopulos MM, Jimenez-Minchan M, Olivares R, Lutz B, Barco A (2011) Ablation of CBP in forebrain principal neurons causes modest memory and transcriptional defects and a dramatic reduction of histone acetylation but does not affect cell viability. J Neurosci 11: 16761678
  • Valor LM, Viosca J, Lopez-Atalaya JP, Barco A (2013) Lysine acetyltransferases CBP and p300 as therapeutic targets in cognitive and neurodegenerative disorders. Curr Pharm Des 19: 50515064
  • Vaquero A, Loyola A, Reinberg D (2003) The constantly changing face of chromatin. Sci Aging Knowledge Environ 14: RE4
  • Vashishtha M, Ng CW, Yildirim F, Gipson TA, Kratter IH, Bodai L, Song W, Lau A, Labadorf A, Vogel-Ciernia A, Troncosco J, Ross CA, Bates GP, Krainc D, Sadri-Vakili G, Finkbeiner S, Marsh JL, Housman D, Fraenkel E, Thompson LM (2013) Targeting H3K4 trimethylation in Huntington disease. Proc Natl Acad Sci USA 110: E3027E3036
  • Vecsey CG, Hawk JD, Lattal KM, Stein JM, Fabian SA, Attner MA, Cabrera SM, McDonough CB, Brindle PK, Abel T, Wood MA (2007) Histone deacetylase inhibitors enhance memory and synaptic plasticity via CREB:CBP-dependent transcriptional activation. J Neurosci 27: 61286140
  • Vickers KC, Palmisano BT, Shoucri BM, Shamburek RD, Remaley AT (2011) MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat Cell Biol 13: 423433
  • Vilardo E, Barbato C, Ciotti M, Cogoni C, Ruberti F (2010) MicroRNA-101 regulates amyloid precursor protein expression in hippocampal neurons. J Biol Chem 285: 1834418351
  • Villa C, Ridolfi E, Fenoglio C, Ghezzi L, Vimercati R, Clerici F, Marcone A, Gallone S, Serpente M, Cantoni C, Bonsi R, Cioffi S, Cappa S, Franceschi M, Rainero I, Mariani C, Scarpini E, Galimberti D (2013) Expression of the transcription factor Sp1 and its regulatory hsa-miR-29b in peripheral blood mononuclear cells from patients with Alzheimer's disease. J Alzheimers Dis 35: 487494
  • Wang WH, Cheng LC, Pan FY, Xue B, Wang DY, Chen Z, Li CJ (2011) Intracellular trafficking of histone deacetylase 4 regulates long-term memory formation. Anat Rec (Hoboken) 294: 10251034
  • Wang WX, Rajeev BW, Stromberg AJ, Ren N, Tang G, Huang Q, Rigoutsos I, Nelson PT (2008a) The expression of microRNA miR-107 decreases early in Alzheimer's disease and may accelerate disease progression through regulation of beta-site amyloid precursor protein-cleaving enzyme 1. J Neurosci 28: 12131225
  • Wang WY, Pan L, Su SC, Quinn EJ, Sasaki M, Jimenez JC, Mackenzie IR, Huang EJ, Tsai LH (2013) Interaction of FUS and HDAC1 regulates DNA damage response and repair in neurons. Nat Neurosci 16: 13831389
  • Wang X, Liu P, Zhu H, Xu Y, Ma C, Dai X, Huang L, Liu Y, Zhang L, Qin C (2009) miR-34a, a microRNA up-regulated in a double transgenic mouse model of Alzheimer's disease, inhibits bcl2 translation. Brain Res Bull 80: 268273
  • Wang Z, Zang C, Rosenfeld JA, Schones DE, Barski A, Cuddapah S, Cui K, Roh TY, Peng W, Zhang MQ, Zhao K (2008b) Combinatorial patterns of histone acetylations and methylations in the human genome. Nat Genet 40: 897903
  • Williams SR, Aldred MA, Der Kaloustian VM, Halal F, Gowans G, McLeod DR, Zondag S, Toriello HV, Magenis RE, Elsea SH (2010) Haploinsufficiency of HDAC4 causes brachydactyly mental retardation syndrome, with brachydactyly type E, developmental delays, and behavioral problems. Am J Hum Genet 87: 219228
  • Wood MA, Kaplan MP, Park A, Blanchard EJ, Oliveira AM, Lombardi TL, Abel T (2005) Transgenic mice expressing a truncated form of CREB-binding protein (CBP) exhibit deficits in hippocampal synaptic plasticity and memory storage. Learn Mem 12: 111119
  • Wood MA, Attner MA, Oliveira AM, Brindle PK, Abel T (2006) A transcription factor-binding domain of the coactivator CBP is essential for long-term memory and the expression of specific target genes. Learn Mem 13: 609617
  • Xiong Y, Zhao K, Wu J, Xu Z, Jin S, Zhang YQ (2013) HDAC6 mutations rescue human tau-induced microtubule defects in Drosophila. Proc Natl Acad Sci USA 110: 46044609
  • Yang YC, Chen CN, Wu CI, Huang WJ, Kuo TY, Kuan MC, Tsai TH, Huang JS, Huang CY (2013) NBM-T-L-BMX-OS01, semisynthesized from osthole, is a novel inhibitor of histone deacetylase and enhances learning and memory in rats. Evid Based Complement Alternat Med 2013: 514908
  • Yao ZG, Zhang L, Huang L, Zhu H, Liu Y, Ma CM, Sheng SL, Qin C (2013) Regional and cell-type specific distribution of HDAC2 in the adult mouse brain. Brain Strct Funct 218: 563573
  • Yeh HH, Young D, Gelovani JG, Robinson A, Davidson Y, Herholz K, Mann DM (2013) Histone deacetylase class II and acetylated core histone immunohistochemistry in human brains with Huntington's disease. Brain Res 4: 1624
  • Zeybel M, Hardy T, Wong YK, Mathers JC, Fox CR, Gackowska A, Oakley F, Burt AD, Wilson CL, Anstee QM, Barter MJ, Masson S, Elsharkawy AM, Mann DA, Mann J (2012) Multigenerational epigenetic adaptation of the hepatic wound-healing response. Nat Med 18: 13691377
  • Zhang X, Chen HM, Jaramillo E, Wang L, D'Mello SR (2008) Histone deacetylase-related protein inhibits AES-mediated neuronal cell death by direct interaction. J Neurosci Res 86: 24232431
  • Zhang ZY, Schluesener HJ (2013) Oral administration of histone deacetylase inhibitor MS-275 ameliorates neuroinflammation and cerebral amyloidosis and improves behavior in a mouse model. J Neuropathol Exp Neurol 72: 178185
  • Zhao Y, Bhattacharjee S, Jones BM, Dua P, Alexandrov PN, Hill JM, Lukiw WJ (2013) Regulation of TREM2 expression by an NF-кB-sensitive miRNA-34a. NeuroReport 24: 318324
  • Zovoilis A, Agbemenyah HY, Agis-Balboa RC, Stilling RM, Edbauer D, Rao P, Farinelli L, Delalle I, Schmitt A, Falkai P, Bahari-Javan S, Burkhardt S, Sananbenesi S, Fischer A (2011) microRNA-34c is a novel target to treat dementias. EMBO J 30: 42994308