Introduction
============

The term "epigenetics" was introduced by the developmental biologist Conrad Hal Waddington (1905--1975) in the early 1940s. He defined epigenetics as the branch of biology that studies the causal interactions between genes and their products, which bring the phenotype into being ([@B192], [@B193]). This general idea was later narrowed and defined as the science that studies the heritable traits resulting from changes in a chromosome without altering the DNA sequence ([@B15]). Although nowadays widely accepted, this definition is -- strictly speaking -- a conception of developmental and cancer researchers, who perceive epigenetics as a way to transmit phenotypic characteristics to daughter cells. Yet, such conception represents a major problem for other disciplines like neurosciences, since neurons do not divide and, accordingly, nothing happening in neurons would be considered epigenetics. As "epigenetic newcomers," neuroscientists have only recently started to add their viewpoints toward this perception, but due to the emerging importance of epigenetics in the nervous system, this has already stimulated a profound revision of the perception of epigenetics. Currently, epigenetics is rather considered as the study of structural changes of the chromatin that modify the phenotype without altering the genotype ([@B84]), independently of whether the cells divide or not.

Yet, where does this recent interest of neuroscientists in epigenetics or, in other words, in neuroepigenetics originate from? Probably one of the main reasons is because epigenetic mechanisms provide a platform for integrating different *inputs* and for generating adaptive long-lasting *outputs*. This capacity of epigenetics touches upon the very fundament of neuroscience, providing a potential substrate for memory allocation, and for articulating the hypothesis of gene × environment interaction associated with many multifactorial diseases such as Parkinson's and Alzheimer's disease (AD), amyotrophic lateral and multiple sclerosis, and even epilepsy ([@B188]). As a matter of fact, it is known that epigenetic mechanisms participate in the processes of learning and memory formation ([@B109]; [@B63]; [@B217]; [@B73]; [@B85]; [@B202]), and that -- on the other end of the spectrum -- life style ([@B49]), aging ([@B79]), nutrition ([@B34]), and environmental toxins ([@B5]) associated with AD can modify the epigenetic makeup and might thereby contribute to the pathophysiology of AD ([@B20]; [@B35]; [@B13]).

Epigenetic Mechanisms
=====================

At the molecular level, it is generally accepted that epigenetics encompasses two main mechanisms: the direct methylation of the DNA, and the modification of the proteins that package the DNA, the histones. Chromatin remodelers and non-coding RNAs can also participate in the regulation of the chromatin but, because they are not considered purely epigenetic mechanisms, are not included in this review (for a further discussion about these topics see [@B121]; [@B104]). Here, we first provide a description of the functioning of these two epigenetic modifications in general, before moving to their implication in neuroscience, and in particular, in AD.

DNA Methylation
---------------

DNA methylation has thus far been the most studied epigenetic modification. It mainly consists of the addition of a methyl group at cytosines that precede guanines (so-called CpG dinucleotides). These dinucleotides are underrepresented in the genome and tend to accumulate in CpG-dense regions (so-called CpG islands, or CGI) although around 95% of CpGs are scattered through all the genome without showing any type of aggregation. As a general view, CpGs in non-CGI and CGIs tend to be fully methylated and non-methylated, respectively, with a negligible amount of CpGs being partially methylated ([@B190]).

Historically, DNA methylation has been considered an epigenetic mark of repression, since seminal experiments have shown that the genomic insertion of exogenous DNA results in active transcription only with non-methylated DNA ([@B148]; [@B201]; [@B175]), and since CGI hypermethylation has been recurrently associated with the silencing of tissue-specific genes and X inactivation ([@B178]). In fact, the existence of CGI together with the bimodal pattern of DNA methylation has evoked the idea that genes can be switch ON an OFF by controlling the DNA methylation of their CGIs. This idea has been predominant in the last years. However, it is now apparent that the reality is much more complex since around 70% of annotated genes contain CGI regions in their promoters ([@B41]) and most of them are non-methylated. Furthermore, CGI and non-CGI promoter-containing genes show specific particularities, with the former being constitutively expressed and displaying low evolution rates and relaxed use of transcription start sites (TSS), while the latter is characterized by a more restricted pattern of expression, higher evolution rate, and strongly defined TSS usage ([@B185]). Thus, DNA methylation cannot be the main driver of gene expression in these regions.

Importantly, DNA is not randomly distributed in the nucleus but associated to histones forming the nucleosomes ([@B167]). The distribution and the compaction of these nucleosomes determines the chromatin structure and thereby the access of the transcriptional machinery to the DNA ([@B167]). Accordingly, CGIs favors the access of the DNA polymerase and gene expression by constituting a rigid structure that complicates the wrapping of DNA and nucleosome positioning ([@B153]). Therefore, CGI are not mere platforms for controlling gene expression by DNA methylation, but such effect depends on the nearby sequence and thus, three-dimensional chromatin context. In general, DNA methylation in gene promoters is associated with lower levels of expression ([@B91]) whereas in gene bodies, it favors gene expression ([@B66]).

The enzymes that carry out the active DNA methylation, the so called DNA methyltransferases (DNMTs), are all associated with the nucleosomes ([@B87]), which reinforces the idea that DNA methylation and nucleosome positioning are intimately related. Three different DNMTs have been identified: DNMT1 -- necessary for the maintenance of DNA methylation patterns during cell division -- and DNMT3A and DNMT3B, both involved in establishing *de novo* patterns of DNA methylation during development and cell fate determination. Interestingly, DNMTs also show high levels of expression in post-mitotic neurons ([@B69]), suggesting that their importance in the adult brain is beyond the classical developmental point of view. A deficit of these enzymes can cause passive DNA demethylation ([@B156]), but DNA can also be actively demethylated by the action of several enzymatic reactions. These include the 10--11 translocation proteins (TET), which mediate the oxidation of 5-methylcytosines (5mC) to 5-hydroxymethylcytosine (5hmC), and later on to 5-formilcytosine (5fC) and 5-carboxycytosine (5caC); and the thymine-DNA glycosylases (TDG), which causes the final excision and conversion to cytosines ([@B97]).

Newly Identified DNA Methylation Marks
--------------------------------------

The recently developed techniques of deep-sequencing have documented an unexpected high prevalence of 5hmC and 5fC in brain ([@B114]; [@B189]; [@B69],[@B70], [@B99]). In spite of that, it is still under discussion whether 5hmC and 5fC constitute new epigenetic marks *per se* or if they are just intermediate states of the DNA demethylation ([@B75]). In the brain, around ∼80% of cytosines in CpG sites are methylated (5mC), whereas ∼8% are hydroxyl-methylated (5hmC), ∼0.8% are formyl-methylated (5fC), and even less are carboxyl-methylated (5caC). These data reflect a high prevalence of the intermediate states, in special for 5hmC, which has been used as an argument to emphasize the specific role of 5hmC in epigenetic signaling ([@B56]; [@B173]; [@B114]; [@B199]), which together with 5fC/5caC is enriched in enhancers and gene bodies of highly transcribed genes ([@B173], [@B172]; [@B169]; [@B199]; [@B152]).

Also, a certain degree of DNA methylation outside of CpG dinucleotides has recently been reported. The so-called non-CpG DNA methylation mainly occurs in the context of CpA dinucleotides ([@B115]; [@B207]; [@B216]) and is particularly prevalent in the brain where it accounts for ∼25% of all cytosine modifications ([@B114]; [@B69]). Similarly to 5mC and 5hmC, non-CpG methylation also tends to occur in gene bodies of highly transcribed genes ([@B114]; [@B69]).

Histone Modifications
---------------------

As aforementioned, nucleosomes are important components of the chromatin structure and their positioning is influenced by DNA methylation and sequence context. Notwithstanding, nucleosomes are primarily regulated by posttranslational modifications that tend to occur in the N-terminal tail of histone proteins ([@B18]). The most studied of these are histone acetylation and methylation, which occur as a consequence of the antagonistic activity of histone acetyltransferases (HATs) and deacetylates (HDACs), and of histone methyltransferases (HMTs) and demethylases (HDMTs), respectively, as well as histone phosphorylation, which is mediated by the opposing action of protein kinases and phosphatases. Further, more recently discovered posttranslational modifications include ADP-ribosylation, ubiquitylation, sumoylation, crotonylation, propionylation, deiminiation and *O*-GlcNAcylation, which are also the consequence of a similar set of enzyme complexes.

These modifications can take place on different amino acids. For instance, lysines can be acetylated; mono-, di-, or trimethylated; and mono- or polyubiquitylated; arginines can be deaminated; mono-, symmetrically or asymmetrically dimethylated, and mono- or poly-ADP-ribosylated; serines and threonines can be phosphorylated and *O*-GlcNAcylated; glutamates can be mono- or poly-ADP-ribosylated; prolines can be isomerized; and tyrosines can be phosphorylated ([@B76]; [@B206]; [@B18]).

Histone Acetylation
-------------------

Depending on their identity, posttranslational histone modifications can have different effects on gene expression. In general, histone acetylation is associated with increased gene activity ([@B98]), in part because it diminishes the basic charge of histones and thereby reduces the electrostatic interaction with the negatively charged DNA chains. As a result, nucleosome compaction is relaxed facilitating the access of the transcriptional machinery to the DNA ([@B110]). In line, histone acetylation is enriched in promoter and gene bodies of active genes ([@B198]). Some of the most studied lysine acetylation modifications include the acetylation of lysine 9 on histone 3 (H3K9ac) and H3K27ac in gene promoters and H3K4ac and H4K12ac in gene bodies, among others ([@B198]).

Three families of HATs -- GNAT, MYST, and CBP/p300 -- are responsible of the acetylation of these amino acids, and the specificity of these modifications depend on their association with other regulatory proteins ([@B9]). In line, although many acetylation sites has been individually described, they tend to occur in combinations ([@B7]). Zinc-dependent class I, II and IV HDACs as well as the NAD-dependent class III HDACs, the sirtuins, antagonize the activity of HATs. Similarly to the HATs, HDAC proteins show a low level of specificity that is mainly regulated by the interaction with other non-catalytic proteins and complexes ([@B208]).

Histone Methylation
-------------------

As opposed to acetylation, the effect of histone methylation depends on both the type of modification and the residue on which it occurs. As an example, the mono-methylation of lysine 27 of histone 3 (H3K27me1) is enriched in promoters of active genes, whereas the tri-methylation of the same amino acid (H3K27me3) is mainly found in repressed genes ([@B198]). Also in contrast to histone acetylation, the enzymes that regulate histone methylation show a high degree of specificity. Two classes of lysine HMTs are at play: SET domain and non-SET domain-containing HMTs, which install histone methylation at particular lysines to different degrees. For instance, three different members of the SET HMTs perform H4K20 methylation in its mono-, di-, or trimethylated form ([@B116]; [@B149]). The activity of the HMTs is antagonized by two classes of HDMTs -- LSD1- and Jumonji-related HDMTs -- that also show a high degree of specificity. For instance, LSD1 demethylates the monomethylation and dimethylation of H3K4 and H3K9, but not their trimethylation ([@B9]).

The Histone Code
----------------

The sum of different histone modifications, their intricate system of regulation, and the almost infinite number of possible combinations draws a complex landscape of histone modifications that -- considering that chromatin is composed by hundreds of millions of nucleosomes -- can epigenetically encode an immense amount of information. This idea has inspired the hypothesis of the "histone code," which suggests that by using different combinations of histone modifications cells can regulate specific and distinct functional chromatin outputs ([@B177]; [@B86]). This intriguing view has attracted a lot of attention in last years that has undoubtedly helped to push the development of the field. In spite of that, recent chromatin immunoprecipitation (ChIP) sequencing experiments have suggested that the complexity behind such histone code seems smaller than previously estimated. In fact, a high degree of redundancy between different histone marks has been reported ([@B198]) and algorithms have recognized recurrent combinations of histone modifications that can be grouped into discrete chromatin states, which account for most of gene transcription variance ([@B7]). Obviously, this might be a simplification of the reality, and the numbers of identified chromatin states strongly depends of the level of technical resolution applied, but importantly, it underlines that from all possible combinations only few of them ever really occur together, suggesting that the histone code is simpler than anticipated, which would facilitate the task of epigeneticists considerably.

Epigenetic Crosstalk
--------------------

Importantly, DNA methylation and histone modifications are not isolated phenomena, and proteins that recognize and regulate both epigenetic marks are orchestrated in multiprotein complexes. For instance, MeCP2 and KAISO proteins, which recognizes methylated DNA, are also associated with HDAC1 and HDAC3, linking DNA methylation and histone deacetylation ([@B181]; [@B210]); likewise, other DNA methylation readers such as UHRF1 are known to interact with the H3K9 HMT G9A, associating, in this case, DNA methylation with H3K9 methylation ([@B129]; [@B159]). Thus, the concept of a "histone code" should be expanded to one of an epigenetic code, which also applies to the nervous system ([@B61]). Besides, the different histone marks also interact with each other, as it attested by, for instance, the fact that the HAT GCN5 is also able to recognize H3K4me3 ([@B67]), which can help to understand the apparent redundancy of some epigenetic marks (for a more comprehensive view of different epigenetic marks crosstalk see [@B43]).

Beyond such crosstalk, the different epigenetic marks are ensembles interpreted by so-called chromatin remodelers -- SWI/SNF, NuRD and ISWI families (for a detailed description see [@B104]) -- which modify the presence, composition, and nucleosome positioning regulating the chromatin accessibility. Therefore, epigenetic modifications should be understood as chromatin states instead of isolated modifications independently associated with particular functions, which seem to have a special relevance in the nervous system.

Neuroepigenetics
================

The nervous system is a highly specialized system in which millions of cells are organized in different structures with characteristic epigenetic and expression profiles that are associated with particular functions ([@B204]; [@B96]; [@B163]). It is in the nervous system where three out of four genes are expressed ([@B88]), where most splicing variants are transcribed ([@B174]; [@B205]; [@B209]) and most miRNAs are synthesized ([@B22]). Also, it is in the nervous system, where the expression patterns of cells show the highest degree of heterogeneity, with more than 70% of genes being expressed in less than 20% of the cells of the entire brain ([@B107]). Owing to this complexity, the transcription machinery faces a formidable challenge in the nervous system, and, as a consequence, is also highly sensitive to epigenetic perturbations.

Accordingly, the importance of epigenetics in the functioning of the nervous system is underlined by the fact that mutations in epigenetic genes cause severe mental disorders ([@B14]). For example, mutations in genes that establish epigenetic marks, such as *DNMT1*, *NSD1*, *NSD2*, or *CBP* cause hereditary sensory autonomic neuropathy with dementia (HSAN1), Sotos, Wolf--Hirschhorn and Rubinstein--Taybi syndromes, respectively. Similarly, mutations in genes that remove epigenetic marks, such as KDM5C, recognize them, such as *MeCP2*, or are in charge of their integration, such as SWI/SNF proteins, are associated with X-linked mental retardation, Rett syndrome and Coffin-Siris syndromes respectively ([@B188]; [@B54]; [@B164]; [@B14]).

But one the most important findings that supports the importance of epigenetics in the functioning of the brain has been the discovery that neuronal activity *per se* modifies DNA methylation and histone modifications patterns, and further, that learning and memory depend on these epigenetic changes ([@B108]; [@B130]; [@B65]; [@B120]; [@B72]; [@B128]; [@B71]; [@B62]; [@B217]). For instance, neuronal activity induces the expression of DNMT3A2, TET1, and TET3 ([@B71]; [@B144]; [@B160]; [@B112]) and the shuttling of HDAC4 to the nucleus ([@B165]), whereas the depletion of DNMTs 1 and 3a, of the HATs KAT2A and KAT2B, of the HDMT neuronal specific isoform LSD1, and of the HMTs GLP and G9A as well as the increased expression of MeCP2, of HDACs 2, 3, 4, and 5 impair learning and memory formation ([@B65]; [@B46]; [@B100]; [@B127]; [@B137]; [@B165]; [@B2]; [@B92]; [@B133]; [@B176]; [@B196]). Furthermore, several HDAC inhibitors, such as valproic acid, sodium butyrate and others, potentiate learning and memory formation in different paradigms and animal models ([@B63]), as well as in different neurological diseases such as Alzheimer, Parkinson's, and Huntington diseases ([@B214]). Therefore, it is evident that neuronal activity as well as learning and memory engage and to some degree depend on numerous epigenetic players, and that epigenetic perturbations not only impair brain normal functioning but also are associated with many neurological diseases, including AD.

Epigenetic Alterations in AD
============================

Alzheimer's disease is the main cause of dementia in Western societies, where it affects 17% of people older than 65 years and 50% older than 85 years ([@B3]). AD is a neurodegenerative disorder characterized by a progressive decline in mental abilities, neuronal loss and accumulation of two types of protein aggregates, amyloid plaques and neurofibrillary tangles (NFT; [@B38]). Amyloid plaques are mainly constituted by aggregates of the amyloid-β (Aβ)-peptide, itself being a consequence of the cleavage of the amyloid precursor protein (APP) by β- and γ-secretases, while NFT are aggregates of hyperphosphorylated TAU protein. These two hallmarks are unequivocally associated with AD, but whether they are cause or consequence, and the mechanisms leading to their formation and propagation are poorly understood.

It is known that genetic and non-genetic factors contribute to the development of AD. Rare mutations in three genes -- *APP*, *PSEN1*, and *PSEN2* -- are associated with 1% of AD ([@B29]) and other frequent genetic variants such as *APOE-E4* can account for up to 20% of total cases of the disease ([@B126]). In total, the heritability for AD is estimated to explain between one half and two thirds of total AD cases ([@B45]), the other third/half being attributable to non-genetic risk factors in which epigenetics mechanisms are supposedly involved, namely diabetes mellitus, hypertension, obesity, physical inactivity, depression, smoking and low educational attainment (**Figure [1A](#F1){ref-type="fig"}**) ([@B95]).

![**Epigenetics in Alzheimer's disease (AD).** **(A)** Different levels of investigation in AD pathology. At the population level, several genetic and non-genetic factors contribute to the risk for developing the disease. At the level of the individual, several pathophysiological characteristics such as altered glucose metabolism are observed in the brain of cognitively impaired AD patients. Associated with these alterations are -- at the tissue and cellular level -- yet other pathological hallmarks such as the presence of amyloid plaques and neurofibrillary tangles. Finally, at the intracellular level, higher levels of reactive oxygen species (ROS) and DNA damage, together with dysregulated gene transcription, splicing alterations and aberrant protein dynamics are also believed to be implicated in the onset and development of the pathology. **(B)** Similarly, epigenetic alterations have been reported in AD at different levels. Bulk histone acetylation (ac), phosphorylation (ph), and methylation (me) changes as well as DNA methylation (5mC) and hydroxymethylation (5hmC) alterations have been reported in AD tissues by IHC and WB. Major tendencies for these changes (as observed by several studies) are indicated by thick arrows. Locus-specific alterations mainly causing a repression of neuroplasticity genes and an activation of inflammatory genes have also been observed by ChIP using antibodies against histone modifications. Greater resolution is also possible for DNA methylation analysis in which nucleotide-specific alterations can be detected by oxi- and BS-sequencing. BS, bisulfite sequencing; ChIP, chromatin immunoprecipitation; CpG, cytosine-guanine dinucleotide; IHC, immunohistochemistry; IP, immunoprecipitation; WB, western blotting.](fnbeh-09-00347-g001){#F1}

By far the predominant risk factor for AD is aging itself, since AD only appears in late adulthood, and the risk to develop the disease doubles every 5 years after age 65 ([@B90]). Importantly, epigenetic mechanisms have also been suggested to be a major force of aging ([@B28], [@B27]; [@B79]) and similar epigenetic alterations have also been described in AD (**Figure [1B](#F1){ref-type="fig"}**) ([@B20]; [@B35]; [@B13]). But prior to outlining the evidence of an epigenetic implication in AD, it is important to mention that this question has been addressed from different (technical) perspectives, and that the obtained results strongly depend of the experimental approaches, the samples analyzed, and the techniques used. Some of these studies are based on cell lines, others on animal models, and yet others on human post-mortem tissue, sometimes with a limited sample number at their disposal. Equally diverse are the techniques being used for determining the levels of DNA methylation, which range from the use of DNA methylation sensitive restriction enzymes, to antibodies that specifically recognize DNA methylation modifications, and to a direct reading of DNA methylation by bisulfite-sequencing (**Figure [1B](#F1){ref-type="fig"}**).

DNA Methylation
---------------

### Global DNA Methylation Changes

In general, the use of cell lines, independently of the technique used, suggest that AD is associated with lower levels of DNA methylation. For instance, the glioblastoma cell line H4 harboring the Swedish mutation of *APP* (K670M/N671L double mutation segregating in a Swedish family), which causes an increase in Aβ production ([@B30]; [@B134]; [@B74]), shows a general tendency toward hypomethylation as measured by DNA microarrays following bisulfite conversion ([@B180]). Similarly, treatment of the neuronal-like cell line SH-SY5Y with conditioned media obtained from cells harboring the Indiana mutation (V717F mutation identified by a group of Indiana) -- associated with higher Aβ levels ([@B135]; [@B182]) --induced a general DNA hypomethylation as measured by DNA methylation-sensitive antibodies ([@B82]). In line, brain microvascular endothelial cells subjected to high levels of synthetic Aβ show lower levels of DNA methylation as measured by high-performance liquid chromatography (HPLC) ([@B24]). Nevertheless, conversely to the previously discussed observations, IMR-32 neuroblastoma cells subjected to high levels of synthetic Aβ do not show significant alterations in DNA methylation as measured by DNA microarrays ([@B184]).

In mouse models of AD, global levels of DNA methylation have been less studied and, to our knowledge, only one work has addressed this question. [@B33] used cortical samples of APPswe/PS1dE9 mice -- harboring the Swedish *APP* mutation in combination with the deletion of the exon 9 of the *PSEN1* resulting in increases Aβ formation ([@B17]) -- and immunoprecipitation of the DNA using DNA methylation specific antibodies (Methylated DNA immunoprecipitation: MeDIP) followed by the hybridization of the resulting DNA to promoter microarrays. Following this approach, around 10% of analyzed genes (2346 of 20404 promoter genes contained in the array) showed higher levels of DNA methylation in the APPswe/PS1dE9 mice than in the controls, and no hypomethylated genes were reported ([@B33]). Therefore, conversely to what occurs in cell line models of the disease, at least one AD mouse model displays higher levels of DNA methylation.

The study of human post-mortem samples has not helped to solve this apparent discrepancy. Using antibodies that recognize methylated DNA, a loss of DNA methylation has been observed in the entorhinal cortex ([@B123]) and the hippocampus of post-mortem samples of AD ([@B26]). Conversely, other studies using the same technique have reported no differences in the entorhinal cortex ([@B105]) or even gains of DNA methylation in the frontal cortex ([@B36]), the temporal cortex ([@B36]) and the hippocampus of AD samples ([@B19]). In much the same manner, ELISA 5mC assays of the entorhinal cortex of AD patients ([@B105]) as well as DNA methylation microarrays in frontal cortex ([@B8]) have not shown significant DNA methylation differences.

A similarly confusing scenario is also emerging from the study of the DNA hydroxymethylation in AD. Higher levels of DNA hydroxymethylation have been reported in 3xTg-AD mice -- harboring the *APP* Swedish, *PSEN1* M146L, and P301L *TAU* mutations and resulting in Aβ formation and TAU phosphorylation ([@B142]) -- using specific 5hmC antibodies ([@B21]), but lower levels have been observed using the same technique in the human frontal, entorhinal, and temporal cortex ([@B32]; [@B36]) as well as in the hippocampus of post-mortem AD samples ([@B26]), with no significant differences observed in entorhinal cortex using 5hmC specific ELISA assays ([@B105]).

It is important to mention that, in all these studies, the magnitude of DNA methylation and hydroxymethylation changes, and the number of samples analyzed, are relatively small, and as a consequence the results can easily be influenced by differences in the analyzed regions ([@B102]; [@B204]; [@B78]; [@B106]; [@B39]; [@B163]), interindividual variability ([@B187]; [@B80]) and experimental fluctuations. As a result, if DNA methylation and hydroxymethylation differences are present in AD, these are likely to be either small or to be associated with only discrete regions of the genome. The study of disease-discordant twins has been crucial for unraveling the epigenetic component of common diseases ([@B12]), but unfortunately, only a single couple of monozygotic twins discordant for AD has been studied so far. There, AD was associated with a loss of DNA methylation and an increase of DNA hydroxymethylation ([@B125]; [@B26]).

### Gene-Specific DNA Methylation Changes

Attempts to determine whether specific genetic regions or particular genes are altered in AD have initially focused on genes previously associated with the disease -- *APP*, *PSEN1*, and *TAU* genes --, and similarly to the global tendencies, no conclusive evidences have emerged from these studies.

In spite of some reports suggesting a hypomethylation in the promoter of *APP* in the temporal cortex of AD ([@B200]) and aging ([@B186]), studies using higher sample numbers have not been able to find differences in frontal cortex, parietal cortex, and hippocampus of AD patients ([@B211]; [@B197]; [@B10]). Similarly, studies aimed to determine whether *PSEN1* might also be epigenetically deregulated in AD have not been conclusive. Methyl groups are directly assimilated from diet, which itself is frequently deficient in aging and AD ([@B48]; [@B81]). Indeed, in the case of dietary depletion, the *PSEN1* promoter can become hypomethylated in TgCRND8 -- harboring the Swedish and V717F Indiana *APP* mutations ([@B25]) -- and APPswe/PS1dE9 AD models ([@B52]; [@B113]). Similar findings have been obtained in SK-N-BE neuroblastoma cell line using vitamin B6 and B12 deficient media ([@B53]). However, although mechanistically possible, *PSEN1* hypomethylation has not been observed in frontal cortex and hippocampus of AD samples ([@B197]; [@B10]). And finally, no significant differences in DNA methylation in the frontal cortex or the hippocampus of post-mortem AD samples have been observed in the promoter of *TAU* ([@B10]). Therefore, it seems that at least these three classical AD-associated genes are not epigenetically dysregulated in AD at the DNA methylation level, which might indicate that DNA methylation changes do not play a role in AD, or that genetic and non-genetic forms of AD might be the results of alterations in a different subset of genes. As a consequence, unbiased genome wide screening are also starting to be performed.

### Genome-Wide DNA Methylation Changes

Unfortunately, genome-wide control-case comparisons have not been more conclusive, with almost every single study reporting a different subset of altered genes which might reflect that current approaches are still immature (**Table [1](#T1){ref-type="table"}**). However, the combination of genome-wide strategies with longitudinal studies of AD patients and mouse models yields more consistent data. Two different genes have been reported to be hypermethylated by two independent groups, namely *Sorbin And SH3 Domain Containing 3* (*SORBS3*) ([@B170]; [@B162]) and *Ankyrin 1* (*ANK1*) ([@B40]; [@B119]). These results were obtained in an age-dependent DNA methylation study and a genome-wide DNA methylation screening in two different AD mouse models -- APPswe/dE9 and 3xTg-AD -- and later validated in the frontal cortex of human post-mortem AD samples, as well as from two genome-wide DNA methylation screenings in several human brain regions in differentially AD-affected samples respectively. Equally relevant seems to be the hypermethylation of the gene *Insulin-Like Growth Factor Binding Protein 7* (*IGFBP7*), which is sustained by consistent changes in DNA methylation in the APPPS1-21 AD mouse model -- harboring the Swedish *APP* mutation in combination with the L166P *PSEN1* mutation ([@B151]) -- and in human frontal cortex samples ([@B1]). Lastly, the hypermethylation of *Dual Specificity Phosphatase 22* (*DUSP22*), similarly to *ANK1*, correlates with the severity of the disease and was demonstrated modify TAU phosphorylation and cell viability *in vitro* ([@B162]).

###### 

Differentially DNA methylated genes reported in Alzheimer's disease (AD).

  Gene                            Change     Genomic region                    Technique                     RNA                          Organism                     Brain region                                  References
  ------------------------------- ---------- --------------------------------- ----------------------------- ---------------------------- ---------------------------- --------------------------------------------- ------------
  ANK1                            Increase   Gene body                         BS-array and pyrosequencing   NA                           Human                        Entorhinal, temporal, and prefrontal cortex   [@B119]
                                  Increase   Gene body                         BS-array                      Decrease                     Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  BIN1                            Increase   Downstream (Intergenic)           BS-array                      NA                           Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  BDNF                            Decrease   Promoter                          MSRE-PCR                      Decrease                     Human                        Frontal cortex                                [@B155]
  CDH3                            Increase   Gene body                         BS-array                      Increase                     Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  COX2                            Decrease   Promoter                          MSRE-PCR                      NA                           Human                        Frontal cortex                                [@B155]
  CREB                            Increase   Promoter                          MSRE-PCR                      NA                           Human                        Frontal cortex                                [@B155]
  DUSP22                          Increase   Promoter                          BS-array and pyrosequencing   Decrease                     Human                        Hippocampus                                   [@B162]
  FOXK1                           Increase   Gene body                         BS-array                      NA                           Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  F2RL2                           Increase   Promoter                          BS-array and pyrosequencing   Decrease                     APP/PS1 and 3Xtg-AD          Frontal cortex                                [@B163]
  HMHA1 (ABCA7)                   Increase   Gene body/Promoter (Downstream)   BS-array                      NA                           Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  HOXA3                           Increase   Gene body                         BS-array                      NA                           Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  IGFBP7                          Increase   Promoter                          MeDIP                         Increase in APPPS1-21        APPPS1-21 and human          Frontal cortex                                [@B1]
  ITPRIPL2                        Increase   Gene body                         BS-array                      NA                           Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  KDM2B                           Increase   Gene body                         BS-array                      NA                           Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  NFKB                            Decrease   Promoter                          MSRE-PCR                      Increase                     Human                        Frontal cortex                                [@B155]
  PCNT (DIP2)                     Increase   Gene body (Upstream)              BS-array                      NA (increase)                Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  RHBDF2                          Increase   Gene body                         BS-array                      Increase                     Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  SLC2A1                          Increase   Upstream (Intergenic)             BS-array                      NA                           Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  SORBS3                          Increase   Promoter                          MethyLight PCR                NA                           Human                        Entorhinal, temporal, and prefrontal cortex   [@B170]
                                  Increase   Promoter                          BS-array and pyrosequencing   Decrease                     APP/PS1, 3Xtg-AD and Human   Frontal cortex                                [@B163]
  SPG7 (RPL13)                    Increase   Gene body/Promoter (Upstream)     BS-array                      NA (decrease)                Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
  SPTBN4                          Increase   Promoter                          BS-array and pyrosequencing   Decrease                     APP/PS1, 3Xtg-AD and Human   Frontal cortex                                [@B163]
  SYP                             Increase   Promoter                          MSRE-PCR                      NA                           Human                        Frontal cortex                                [@B155]
  S100A2                          Decrease   Promoter                          MethyLight PCR                NA                           Human                        Frontal cortex                                [@B170]
  TBXA2R                          Increase   Promoter                          BS-array and pyrosequencing   Decrease                     APP/PS1, 3Xtg-AD and Human   Frontal cortex                                [@B163]
  TMEM59                          Decrease   Promoter                          BS-array                      Increase                     APPPS1-21 and Human          Frontal cortex                                [@B8]
  WDR81 (SERPINF1 and SERPINF2)   Increase   Gene body (Upstream)              BS-array                      NA (decrease and increase)   Human                        Entorhinal, temporal, and prefrontal cortex   [@B40]
                                                                                                                                                                                                                     

BS-array, bisulfite-modified DNA based arrays, MSRE-PCR, methylation-sensitive restriction enzyme-PCR, MeDIP, Methylated DNA immunoprecipitation. NA, not available.

Nonetheless, it has to be noted that these correlations do not necessarily reflect a causal relation with the disease, and might even be the consequence of secondary alterations. This is particularly important for the ones observed in mouse models, since these models have already a genetic predisposition to develop AD pathology. Also, another limitation of these studies is that they did not distinguish between different cell populations, the proportions of which are already altered in AD (AD being a neurodegenerative disease associated with a prominent gliosis and a specific loss of neurons ([@B168]), and which present distinct epigenetic profiles ([@B83]; [@B101]; [@B114]). Therefore, although promising, these results should be considered with caution since they will require further validations using cell-type specific studies.

Histone Modifications
---------------------

### Global Histone Acetylation Changes

Contrary to DNA methylation, histone modifications have been less studied in AD and evidences linking histone modification alterations with AD are mainly indirect. The few studies that, have found that several HDAC inhibitors exert a protective effect in AD, improving dendritic spine density, and facilitating learning and memory formation in different mouse models of the disease ([@B47]; [@B50]; [@B158], [@B157]; [@B215]; [@B161]), although the precise mechanisms by which the HDAC inhibitors work remain to be determined. Furthermore, HDAC2 was found to be elevated with age in mice and humans ([@B27]; [@B171]), in APP/PS1 ([@B57]), p25/Cdk5 -- harboring the Cdk5 activator *p25* transgene that induces TAU phosphorylation and neurodegeneration ([@B37]) -- and 5xFAD AD mouse models -- harboring the Swedish, I716V Florida, and V717I London *APP* mutations in combination with the M146L and L286L *PSEN1* mutations with induce Aβ formation and neurodegeneration ([@B141]) -- as well as in the hippocampus and entorhinal cortex of post-mortem human AD samples ([@B62]). In line, it has been shown that HDAC2 is able to differentially bind and regulate the expression of several learning and neuroplasticity-related genes, but that its viral-mediated depletion or its specific pharmacological inhibition is sufficient for restoring the synaptic and cognitive deficits observed in p25/Cdk5 mice ([@B62]; [@B194]). Therefore, there is compelling evidence that HDAC2 is increased in aging and AD, and probably implicated in the associated cognitive decline, although it should be mentioned that a decrease of HDAC2 in AD patients has been also reported by another study ([@B124]).

Surprisingly, in spite of these evidences, it is still not clear whether basal histone acetylation is altered in AD. Lower ([@B213]), equal ([@B155]; [@B118]), and higher ([@B138]) levels of histone acetylation have been reported for post-mortem AD human samples, whereas no differences have been observed in two different AD mouse models -- namely Tg2576 and 3xTg-AD -- ([@B50]; [@B21]), although an increase of H3 and H4 acetylation in primary cultures of the 3xTg-AD mouse has been described by others ([@B195]). One possible explanation might be that instead of an alteration of the basal levels of histone acetylation, AD might be more related with the incapacity of modifying the epigenetic patterns in certain conditions, such as learning and memory formation, in which HDAC inhibitors that increase histone acetylation would "prime" the levels of histone acetylation and consequently, of gene activity ([@B63],[@B64]; [@B59]). In support of this view, the basal levels of H4K12ac in aging remain constant, but when mice are subjected to learning and memory paradigms only young animals are able to increase these levels and not the aged mice ([@B147]). Similarly, in Tg2576 AD mice -- harboring the Swedish *APP* mutation in combination with the M146V *PSEN1* mutation which results in higher levels of Aβ formation ([@B25]) -- the global levels of H4 acetylation are not altered, but when mice are subjected to learning and memory paradigms only wild-type animals are able to increase the levels of histone acetylation and not the Tg2576 mice ([@B50]). Alternatively, although without excluding the previous hypothesis, it could also be possible that histone acetylation alterations occur just in certain loci, which could be more sensitive to HDAC inhibitors, without reflecting general tendencies in the bulk chromatin. To better understand these scenarios, genome wide screenings of histone modifications are starting to be undertaken.

### Global Tendencies in Other Histone Marks

Less attention has been put on posttranslational modifications of other histone marks, despite some results suggesting that histone phosphorylation might be altered in AD. Namely, the linker histone H1 becomes hyperphosphorylated and accumulates in the cytoplasm of astrocytes and neurons of APPswe/PS1dE9 mice ([@B44]). Interestingly, H1 is a substrate of p25/Cdk5 that accumulates in AD patients ([@B146]; [@B23]) and is associated with neurodegeneration and cellular damage such as false entrance of cell cycle division ([@B37]), and H2A.X phosphorylation ([@B93]), both pathophysiological characteristics of AD ([@B143]; [@B136]). In addition to H1 phosphorylation, evidence for H3 phosphorylation has been mixed thus far ([@B155]; [@B4]), suggesting that more studies are necessary for elucidating its role in AD.

The first attempts for studying potential alterations on H3K9 methylation in AD has been equally inconclusive since only three studies have address this question with contradictory results: decreased heterochromatin compaction associated with lower H3K9me2 levels in a TAU Drosophila AD model and human samples ([@B51]), no significant differences in the heterochromatin of p25/cdk5 Ad mouse model measured by H3K9me3 ([@B55]), and increased compaction in primary cultures of 3xTg-AD mouse measured by H3K9me2 ([@B195]).

### Gene-Specific Histone Alterations

The possibility that in AD specific genes might be posttranslationally modified on their histones has just started to be addressed, and to the extent of our knowledge, only two studies in the p25/Cdk5 AD mouse model addressed this point. In 2012, several neuroplasticity related genes were reported as hypoacetylated and repressed in p25/Cdk5 mice (**Table [2](#T2){ref-type="table"}**; [@B62]) and, recently, the catalog of deregulated genes and posttranslational modifications has been enormously enlarged ([@B55]). There, in general, complementary gains and losses of specific marks at discrete loci were observed, explaining the minor global alterations reported in previous studies ([@B55]). An interesting finding of this study was further a consistent enrichment of active marks (H3K27ac and H3K4me3) in enhancers and promoters of immune and stimulus-response functions coupled with a specific decrease in synapse and learning-associated functions can be observed ([@B55]).

###### 

Differentially histone acetylated genes in AD.

  Gene      Change                                 Genomic region   Technique   RNA         Organism             Brain region        References
  --------- --------------------------- ---------- ---------------- ----------- ----------- -------------------- ------------------- ------------
  ARC       H3K14, H4K5, H4K12          Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
  BDNF I    H4K5, H4K12                 Decrease   Promoter         ChIP        No change   p25/cdk5             Hippocampus         [@B62]
  BDNF IV   H2BK5, H4K5, H4K12          Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
            H4 (pan)                    Decrease   Promoter         ChIP        Decrease    C57Bl/6J vs APP KO   Prefrontal cortex   [@B77]
  CDK5      H2BK5, H4K5, H4K12          Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
  EGR1      H2BK5, H4K5, H4K12          Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
            H4K5, H4K12ac               Decrease   Promoter         ChIP        Decrease    C57Bl/6J vs APP KO   Prefrontal cortex   [@B77]
  FOS       H4K5, H4K12ac               Decrease   Promoter         ChIP        Decrease    C57Bl/6J vs APP KO   Prefrontal cortex   [@B77]
  HOMER1    H2BK5, H3K14, H4K5, H4K12   Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
  GLUR1     H3K14, H4K5, H4K12          Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
  GLUR2     H2BK5, H3K14                Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
  NFL       H4K12                       Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
  NR2A      H2BK5, H3K14, H4K5, H4K12   Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
  NR2B      H2BK5, H3K14, H4K5, H4K12   Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
  SYP       H2BK5, H3K14, H4K5, H4K12   Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
  SYT1      H4K12                       Decrease   Promoter         ChIP        Decrease    p25/cdk5             Hippocampus         [@B62]
                                                                                                                                     

ChIP, chromatin immunoprecipitation.

Similarly to reported DNA methylation alterations in AD, these results probably reflect both changes in cell composition and cell-type-specific changes associated with AD pathology, thereby necessitating cell-specific validations for a better evaluation of their significance in AD.

Considerations
==============

There is an increasing interest of neuroscientists in epigenetics that is likely to result in a fruitful synergy, which will undoubtedly push the frontiers of both fields: epigenetic researchers have approached neuroscience, and vice versa, neuroscientists have also approached epigenetics. Nonetheless, the following conceptual, methodological, and biological caveats need to be properly addressed from both the epigenetic and the neuroscience point of view in order draw meaningful conclusions from these studies.

DNA Methylation Marks: Independent or Redundant?
------------------------------------------------

In spite of the abundant literature arguing in favor of the specific roles for the different types of DNA methylation mark, it is still unclear whether they are independent or redundant. 5mC, 5hmC, and 5fC/5caC show similar distribution and association with gene transcription, being mainly enriched in gene bodies and correlated with gene expression ([@B66]; [@B173]; [@B169]; [@B203]), and when occurring in TSS, associated with gene repression ([@B66]; [@B169]). In line, 5mC and 5hmC are significantly correlated ([@B105]). Furthermore, non-CpG methylation tends to occur on gene bodies of highly transcribed genes ([@B114]; [@B69]) and to accumulate in aging (data presented in AD/PD 2015) in the same manner than 5mC and 5hmC ([@B78]; [@B183]). A possible explanation for this might be that CpGs are continuously being methylated and demethylated in promoters of highly transcribed genes questioning their specific effect and explaining the high prevalence and concordance of these DNA methylation marks ([@B139]). 5mC, 5hmC, and 5fC/5caC are indeed produced in a stepwise manner ([@B97]), and it has been suggested that non-CpG methylation could be a consequence of the DNMT3B binding to previously methylated CpG sites ([@B154]; [@B6], [@B11]). Therefore, it is possible that, similarly to the initial high expectations about the histone code, that the complexity behind DNA methylation might be currently overestimated.

Then, it is also worth to mention that different techniques seem to show different scenarios. There is an apparent discrepancy between DNA methylation levels reported by antibody-based immunoprecipitation and by classical bisulfite-dependent modification of DNA, the former usually reporting higher values than the latter ([@B31]). Furthermore, antibody-based techniques tend to enrich densely modified regions ([@B145]) and classical bisulfite DNA modification cannot distinguish between 5mC and 5hmC ([@B140]). Therefore, it might be possible that instead of reporting just DNA methylation differences, antibody-based techniques could be reporting a combination of DNA methylation differences and other alterations to the chromatin structure -- not necessarily related with the DNA methylation differences -- and that the classical bisulfite-dependent modification of DNA might be underestimating the 5mC changes. In line, most of the reported DNA methylation changes based on bisulfite-dependent DNA modifications are gains of methylation, since losses of DNA methylation should be coupled with gains of 5hmC and are consequently masked in this technique. The application of the recently developed oxidative bisulfite-dependent DNA modification could help to resolve these discrepancies since it combines the precision of the classical bisulfite DNA modification with the ability of differentiate between 5mC and 5hmC ([@B16]).

HDAC Inhibitors in Learning and AD: Only an Epigenetic Effect?
--------------------------------------------------------------

Similarly, it is also important to consider several constraints when analyzing histone modifications. The beneficial effect of HDAC inhibitors in learning and AD can be interpreted as a proof of the involvement of histone acetylation in these processes ([@B191]; [@B63]) but, instead, it is just proving the involvement of the inhibited enzyme *per se*, and not necessarily of the acetylation of histones since other non-histones substrates can be also acetylated and deacetylated ([@B122]; [@B111]). For instance, it is known that HDAC6 is elevated in AD patients ([@B42]), and that its deletion restores the cognitive deficits observed in APPPS1-21 mouse model of AD ([@B58]), but it is also known that the main effect of this protection is a consequence of the modification of tubulin acetylation ([@B58]). Similarly, it has been seen that SIRT1 decreases in aging and in AD ([@B89]; [@B150]), and that its restoration protects against neurodegeneration ([@B94]; [@B60]), but again its main effects are associated with non-histone substrates, including PGC-1alpha, p53, and TAU ([@B94]; [@B132]). Therefore, these studies should be interpreted cautiously not only in light of the particular specificity of the HDAC inhibitor, but also in light of the potential non-histone substrates of the targeted HDAC.

Epigenetics and Gene Expression, Always Coupled?
------------------------------------------------

Also, it is worth to mention that, in most cases, the interpretation of the effect of epigenetic marks on gene transcription is based on genome-wide comparisons in which significant correlations can be seen, but when single genes are being analyzed a strikingly high level of discrepancy is observed ([@B117]). In fact, changes in gene transcription can occur independently of epigenetic modifications ([@B212]), and changes in epigenetic modifications are not necessarily reflected by changes in gene expression ([@B117]).

Along these lines, it is important to note that epigenetic mechanisms mainly regulate the chromatin structure, which secondarily modifies the accessibility of the genome to impact on gene regulation. Several epigenetic players also interact with the gene transcription machinery, but it is simplistic to assume that epigenetic changes will completely determine the levels of gene transcription since many other factors are also implied. More likely, epigenetics would be one of the variables of the probabilistic model that finally determines the levels and the magnitude of the potential changes in gene expression. Furthermore, most epigenetic changes occur in enhancer and regulatory regions that are not easily assignable to specific genes ([@B55]; [@B179]). These assignments are frequently based on distance criteria, which do not necessarily reflect real interactions. In fact, chromatin conformation capture experiments have shown that the majority of regulatory elements do not interact with the nearest genes ([@B166]). Therefore, an important part of long-range epigenetic information is still far from being understood.

Cause or Consequence?
---------------------

Finally, it is important to consider that the majority of studies investigating potential epigenetic alterations in AD are based on correlations, which do not necessarily reflect a causal relationship. Therefore, whether epigenetic modifications are driving the chromatin behavior or whether they are just a consequence of other processes happening nearby is still unknown. These studies also require considerable amounts of chromatin, which is achieved, in the best of the cases, by collecting pools of similar cell types. However, unlike in cell lines, this is a particularly difficult feature to achieve in the heterogeneous central nervous system. In fact, every single cell might have its specific epigenetic and expression profile. As a consequence, the pooling of cells could mix different epigenetic patterns, thereby masking potentially important changes and complicating any analysis. Epigenetic AD studies ought thus to be conducted in particular cell types. Recently, the first report of single-cell DNA methylation profiling has just appeared ([@B68]), raising hope that cell-type specific epigenetic profiling might in the future also become an option for AD.

In spite of these limitations, it is becoming more and more evident that by modifying the chromatin structure, epigenetic mechanisms can shape genome accessibility and thereby have an impact on gene transcription. And that, by doing so, epigenetic changes might provide a molecular substrate for "chromatin memories" with important implications for learning and memory formation and for diseases such as AD. Indeed, both memory and AD are influenced by non-genetic factors that accumulate over time ([@B131]). In this sense, epigenetics might store long-lasting information and provide a platform for accumulating hits over time. This idea has inspired the hypothesis of the Latent Early life Associated Regulation (LEARn) model ([@B103]). This model suggests that a series of harmful events throughout lifetime, from gestation to old age, could accumulate epigenetic marks that modify the expression probability of certain genes, which in turn might induce or accelerate the onset and development of AD. Whether this hypothesis will withstand further experimentations remains to be determined but, for the moment, it provides an attractive food for thoughts.

Author Contribution
===================

JVSM and JG conceptualized and wrote the review.

Conflict of Interest Statement
==============================

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

This work is funded by the Swiss National Science Foundation (Project Grant 31003A_155898), by the National Center for Competence in Research (NCCR) SYNAPSY, by the Synapsis Foundation for Alzheimer Research, by the Béatrice Ederer-Weber Stiftung, and by an Alzheimer's Association New Investigator Research Grant to JG.

[^1]: Edited by: *Martine Ammassari-Teule, Consiglio Nazionale delle Ricerche, Italy*

[^2]: Reviewed by: *Angel Barco, Instituto de Neurociencias de Alicante, Spain; Tamara Maes, Oryzon Genomics S.A., Spain*
