1. Introduction

Epigenetics refers to the modification of genetic phenotype, without altering DNA sequence. Traditionally, this meant a new mode of inheritance, first implicated in the Dutch famine study we critically appraised(1). However, modern definitions refer to changes in the expression of individual genes.

This review focuses on the role of epigenetics in liver disease. Its incidence has steadily increased in Scotland and the UK over the past two decades, due to increasing alcohol consumption and obesity(2), and in recent years, caused more deaths than diabetes and traffic accidents combined. From previous research, genetics is a key factor in liver pathology. However, epigenetics now receives its spotlight; it is found to play a major role in the onset of a range of liver diseases and shows great therapeutic potential.

We aim to deliver a concise discussion of the underlying mechanisms of epigenetic modifications, how they impact liver disease, and existing and novel therapies.

This site was made by a group of University of Edinburgh medical students who studied this subject over 10 weeks as part of the SSC.

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2. Epigenetic InheritanceEpigenetic inheritance is founded on Lamarkism - that an organism can acquire characteristics in its lifetime which are transmittable to offspring. This differs greatly from the traditional Mendelian theory of inheritance. As mentioned in the introduction, epigenetic inheritance transcends the present-day common definition of ‘epigenetics’(3), mechanisms of which will be discussed in the next section.

Skinner argued that the term ‘transgenerational’ can only be applied when changes are observed in F3 offspring, because during environmental exposure of the F0 generation, F1 offspring could be present in pregnant individuals, along with the potential F2 offspring (F1 germ cells)(4,5). Thus, transgenerational inheritance is only conclusive with F3 epigenetic changes, ruling out the confounding factor of direct exposure (Figure 1).

Figure 1: Possible direct exposure of F0-F2 generations.

Epigenetic inheritance can broadly be divided into: cellular, organ, and organism(6).

2.1.         Broad Examples

Paramutation (in plants, notable corn): Two alleles at the same locus interact, with the paramutagenic allele inducing inheritable epigenetic alterations, such as DNA methylation, in the corresponding paramutable allele.

Parental imprinting: Phenotypic expression can depend on parental inheritance, as epigenetic changes transcriptionally silence (a.k.a 'imprint') certain autosomal genes that are transmitted. Hence, despite a homozygous genotype, only the non-imprinted gene will be expressed, causing a hemizygous phenotype (Figure 2)(7).

Figure 2: Zygote inherits different imprinted/repressed genes, i.e. maternally imprinting means the corresponding paternally inherited gene will be expressed, and vice versa.

2.2.          Transmission

The broad mechanism requires environmental factors to (preferably, irreversibly) alter the germline epigenome. Alternatively, changes can be short-lived, but occur at a crucial stage e.g. spermatogenesis(8) or germline methylation at gonadal sex determination(9).Circumstantial evidence suggests soma-to-germline transfer (a.k.a indirect germline transmission)(10), where germ cells are affected by somatic cells that first received epigenetic changes from environmental factors. This has massive implications for the traditional model of evolution. Precise mechanisms, though largely unknown, could involve small RNA moving between cells(6). Two breakthroughs are: illuminating the mechanism for soma-to-germline transmission in long-lived C. elegans mutants(11), and showing the transfer of tumour cell-derived RNAs to spermatozoa via exosomes in mice(12).

.2.3.          Liver

Epigenetic inheritance can influence lipogenesis(13), methylation of hepatic gene promoters(14), hepatic expression of many genes(15) involved in lipid and cholesterol biosynthesis, and decreased levels of cholesterol esters(16), non-alcoholic fatty liver disease (NAFLD)(17), fibrogenic wound healing(18) and fibrosis(19).

3. Epigenetic Mechanisms

Various epigenetic mechanisms control the transcriptional status of genes within cells. These changes can occur in isolation or in different combinations to affect gene expression and cellular function(20). Three major mechanisms include:

3.1.          Histone Modification

Chromatin is made up of nucleosomes (Figure 3), 147 base pair sequences of double-stranded DNA wrapped around cores of eight histone proteins (two each of H2A, H2B, H3 and H4)(20, 21).  Two main chromatin classes exist based on binding site availability: heterochromatin, which is transcriptionally inactive due to its dense packaging, and euchromatin, which is lightly-packed and therefore transcriptionally active(20, 22).

Figure 3: Nucleosome structure within chromatin.

Histone modifications are post-translational alterations to histone protein tails, affecting chromatin structure and therefore gene expression regulation(23) through transcriptional factors, nucleosome remodelers and other modifiers(24). Initially explored 50 years ago by Allfrey et al.(25), dynamic modification by processes including methylation, acetylation, phosphorylation are known to affect histones(22), increasing or decreasing transcription in the affected areas(20). These are implicated in many diseases discussed later.

3.1.1.     Methylation

Sites of methylation (and demethylation) are found only at lysine and arginine residues on histones. These sites can be mono-, di- or, in lysine, tri-methylated with varying transcriptional effects(20, 22). Enzymes involved can be classified into three main groups – ‘Writers’ that methylate residues, ‘Readers’ that allow transcription of methylated residues, and ‘Erasers’ that demethylate residues (Figure 4)(26). Enzymes discovered so far are Lysine Methyltransferases, Lysine Demethylases and Arginine Methyltransferases(22). Although believed to exist due to the dynamic nature of modifications, no enzymes able to read or erase methylation caused by Arginine Methyltransferase have yet been discovered(22). Methylation enzymes show high specificity and usually modify only a particular arginine or lysine residue(22, 27) with the resulting histone hypermethylation or hypomethylation influencing whether or not transcription occurs(27). In hypermethylation, mono-methylation of certain lysine residues (e.g. H3K27 (Histone 3 Lysine 27), H3K9, H4K20, H3K79, and H2BK5) are associated with increased transcription in associated genes, whereas tri-methylation of others (e.g. H3K27, H3K9, and H3K79) are associated with reduced transcription(28).

Figure 4: Enzymes involved in histone modification.

3.1.2.     Acetylation

Similar to methylation, acetylation of histone proteins affects transcription through chromatin structure(22). Occuring only at lysine residues(20), acetylation almost always activates transcription, while deacetylation generally represses transcription. This is due to the

neutralising action of acetylation on the lysine residue unfolding chromatin, suggesting acetylation has the greatest potential to affect transcription of all histone modifications(22). The enzyme groups involved closely resemble those of methylation: ‘Writer’ Acetyltransferases (HAT), ‘Reader’ enzymes, and ‘Eraser’ Deacetylases (HDAC)(22, 27). Unlike methylation enzymes, acetylation enzymes are versatile and can acetylate various residues throughout histones(22, 27).

3.1.3.     Phosphorylation

Phosphorylation occurs at serine or threonine residues(20, 24) on H2B and H3 proteins assisted by kinases(22, 24). The process depends on kinase activation upstream initiating signal-transduction cascades to phosphorylate appropriate histone residues(24). ‘Reader’ enzymes act at phosphorylated residues, as in other modifications, which trigger various downstream effects, including transcription activation, DNA repair, apoptosis and chromatin condensation(24). H3S10 is an example modification affecting chromatin condensation, important in interphase and mitosis(24, 27).

3.1.4.     Combinations of Histone Modifications

Although different histone modifications can occur in isolation,  combinations of modifications often alter a gene’s transcriptional status as suggested by Schübeler et al.(27). This could be due to the close proximity of different modifications on histone tails allowing ‘crosstalk’(22). An example of this is activation of a euchromatic gene in higher eukaryotes where combinations of hypermethylation (at H3K4 and H3K79) and hyperacetylation (at various locations on H3 and H4) activate gene transcription while combinations of hypomethylation and hypoacetylation at the same residues inactivate it(27). The extent of these combined modifications has been shown to affect the quantity of RNA produced, indicating that histone modifications can affect whether or not a gene is transcriptionally active and the level of activity(27). Phosphorylation also often occurs in combination; H3S10, for example, is located beside other potentially modifiable residues allowing possible ‘crosstalk’ between them and, therefore, various combinations of transcription effects(24).

3.2.           DNA Methylation

DNA methylation is a reversible process whereby a methyl (CH3) group is covalently added to the 5th carbon of a cytosine nucleotide ring, following replication in adult mammalian cells, which acts as a transcriptional repressor(29). Cytosine is usually only methylated within 5’-CG-3’ sequences, known as CpG dinucleotides. Large clusters of CpG sequences are known as islands, and are often found within gene promoter regions. Whilst approximately 70%-80% of CpG repeats are methylated in human somatic cells(30), the majority of CpG islands remain unmethylated in order to allow the gene to stay transcriptionally active. Methylation of CpG islands can therefore be used as a way of switching off gene transcription(31).

DNA Methyltransferases (DNMT) are the family of enzymes which control cytosine methylation(32). DNMT3a and DNMT3b act to ensure “de novo” methylation occurs in order to establish new DNA methylation patterns(32), whilst DNMT1 acts preferentially on hemimethylated DNA (where only one of the two complementary DNA strands is

methylated) to restore methylation patterns(33). Hemimethylated DNA may arise during DNA replication (Figure. 5a) or Nucleotide Excision Repair (Figure. 5b) and can prove detrimental to the cell if left uncorrected. Li et al., also discovered that DNMT enzymes play a key role in embryonic development, as deletion of the DNMT gene locus caused inviable mouse embryos (33).

Figure 5: The production of hemimethylated DNA through (A) DNA replication and (B) Nucleotide Excision Repair.

As identified by Tahiliani et al.(34), the effect of DNA methylation can be reversed through the action of ten-eleven-translocation (TET) enzymes. TET1, TET2 and TET3 proteins are able to convert 5-methylcytosine to 5-hydroxymethylcytosine, which demethylates the nucleotide, and facilitates the DNA to become transcriptionally active (Figure. 6). This is important as it allows for gene expression to be dynamically controlled through methylation in response to changes in the cellular environment or replication phase.

Figure 6: Biochemical alterations involved in methylation and demethylation, and the enzymes involved in each process.

3.3.           microRNA

microRNA (miRNA) are small, non-coding RNA sequences,  roughly 22 nucleotides in length, which regulate the expression of up to 60% of protein coding genes in mammals(35).

3.3.1.     miRNA Synthesis

Introns are short DNA sequences found within protein coding genes which are removed, or spliced, during or after transcription. From these introns, RNA polymerase II transcribes primary microRNA (pri-miRNA) sequences, which are then cleaved by ribonuclease III enzymes (Drosha and Dicer in mammals) to form intermediate sequences, known as pre-miRNA. These are subsequently cleaved into miRNAs(36).

3.3.2.     miRNA Role in Gene Expression

miRNAs can act to repress (or occasionally, activate) gene expression post-transcriptionally by associating with complementary messenger RNA (mRNA) sequences encoded for by a specific gene, thus preventing its expression(37). Despite extensive research, the exact mechanisms by which miRNAs influence mRNA remains controversial. There are a number of theories, including:

3.3.2.1.          Endonucleolytic Cleavage

Upon complementary base-pairing with mRNA, miRNA can guide associated Argonaute proteins, which possess an RNAase catalytic domain, to cleave the mRNA target. The mRNA fragments are then digested by XRN1, an exoribonuclease, and an exonucleolytic compound, called an exosome. The endonuclease activity of some Argonaute (Ago) proteins, such as Ago2, depend on miRNA matching perfectly with its mRNA target(38). Whilst this is often

the case in plants(39), mammalian miRNAs usually imperfectly match with their target. This mismatching more often leads to destabilization and subsequent decay of the miRNA-mRNA complex via common cellular pathways instead, although both processes result in gene repression(37).

3.3.2.2.          mRNA Destabilization

Following transcription of mRNA molecules, Poly A polymerase adds a string of adenine nucleotides to create a polyadenine tail, which serves to stabilize the mRNA and guide the ribosome to begin translation. miRNA can recruit deadenylase enzymes to shorten this polyadenine tail, which reduces ribosomal translation. This also causes destabilization and subsequent decay of the mRNA molecule (40).

4. Pathology of Liver Disease

4.1.          Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) accounts for 90% of all primary liver cancer, the fifth most common cause of cancer worldwide(41). Recently, a wealth of research has presented evidence supporting the role of epigenetic mechanisms in HCC. These mechanisms and their influence on disease progression will be evaluated here.

Epigenetic mechanisms can lead to overexpression of oncogenes in hepatocytes. In the early development of HCC, this is caused by widespread DNA hypomethylation of CpG islands in gene promoter regions, causing genome instability due to increased transcriptional activity. Song et al.(42) captured the extent of CpG island hypomethylation, where of 62,692 differential methylation regions identified in HCC tissue, 61,058 were hypomethylated. As hypomethylation occurs in the early stages of disease progression, it may be important in the neoplasia formation and metastasis. This  is supported by Mirbahai et al.(43) who found CpG island hypomethylation in cells distal to cancer cells contributes to oncogenesis due to  the upregulation of S-adenosylhomocysteine , an effective DNMT inhibitor. Hypomethylation of CpG islands in oncogene promoters prevents the normal silencing of these genes.

Oncogenes can also be upregulated by histone modification. For example, the trimethylation of H3K4 (H3K4me3) increases the transcriptional activity of a particular gene and may be a marker of poor prognosis(44). Furthermore, increased expression of the deacetylase SIRT1 causes H3K9 acetylation and reduces H3K9 trimethylation at the telomerase (TERT) gene, causing cell immortalisation(45). Oncogene upregulation is also attributed to the misregulation of miRNAs controlling oncogene expression and  virus–host interactions(46). In particular, the Hepatitis B virus (HBV) alters miRNA function markedly (Figure 7). The Hepatitis B interacting protein (HBx) upregulates oncogene Secretogranin III (SCGIII) expression by methylating the miR-509-3p promoter(47). miR-205 suppression also prevents the molecule from degrading HBx mRNA, allowing uninterrupted HBx expression(48). The extensive oncogenic actions of HBx are summarised below.

Figure 7: HBx protein and its oncogenic actions (TSG: tumor suppressor gene).

Whilst DNA hypomethylation occurs throughout the genome, hypermethylation targets CpG promotor regions of specific tumour suppressor genes (TSGs), such as SMPD3 and NEFH, to silence them(49).  HBV can silence TSGs by upregulating DNMT1, inducing hypermethylation of the gene promoters(50). In addition to CpG island methylation, histone modifications also silence TSGs. The dysregulation of the H3K9 methyltransferase G9a enzyme can lead to a reduction of H3K9me3, a process implicated in the silencing of TSGs P16 and RASSF1a(51).

Alterations to miRNA function have been implicated in the spread and invasion of HCC cells. Progression towards metastasis includes a process known as epithelial–mesenchymal transition (EMT) were epithelial functions are lost, causing increased cell migration and invasion(52). miR-30a plays a protective role here, targeting the SNAI1 gene mRNA which represses the epithelial adhesion protein E-cadherin. miRNA silencing of SNAI1 mRNA thus prevents E-cadherin loss and inhibits EMT(52). miR-148a is another regulatory gene shown to upregulate E-cadherin and suppress levels of mesenchymal markers such as N-cadherin via SNA1 signalling.In metastasising cells, a significant reduction in miR-30a and miR-148a has been identified, increasing the likelihood of EMT(52)(53).  These research is highly valuable as it implies that miRNAs could be a potential drug target in order to prevent tumour metastasis and decrease mortality.

4.2.          Liver Fibrosis

Liver fibrosis occurs in the majority of chronic liver diseases and is characterised by scar tissue accumulation resulting from chronic inflammation. When in a steady state, hepatic stellate cells (HSCs) in the liver are adipogenic. Chronic damage to HSCs, however, can trigger a phenotypic switch to myofibroblastic cells, that will  secrete large volumes of collagen forming fibrotic tissue(54) (Figure 8).

Figure 8: Pathways contributing to a phenotypic switch of HSCs to myofibroblasts.

Silencing of pro-adipogenic genes adds to HSC myoblastic properties. A gene critical in maintaining the HSC steady state is PPARγ, with the promoter region of this gene often methylated in liver fibrosis(55). Hypermethylation of genes such as PPARγ has been documented by Zhang et al(56) who found cirrhotic tissue had DNA hypermethylation in 15% of promoter regions, compared to 0% in healthy liver tissue. Histone methylation can also silence PPARγ by downregulation of miR-132. This releases methyl-CpG binding protein 2 (MeCP2), which binds to CpG dinucleotides, ultimately leading to methylation of H3K9(57). MeCP2 can also cause histone deacetylation by recruiting histone deacetylases when binding to the co-repressor mSinA. This reinforces repression of genes which already have methylated CpG islands in their promoters regions. PTCH1 is an example of a pro-adipogenic gene silenced via MeCP2 action and deacetylases(58). Silencing of PPARγ, PTCH1 and similar genes leads to the downregulation of the protective mechanisms that prevent fibrosis.

Another important mechanism is upregulation of pro-fibrotic genes. Necdin, an anti-adipogenic gene, silences PPARγ via MeCP2 action, which binds to the PPARγ promotor region, recruiting the transcriptional repressor protein HP-1α. MeCP2 also causes dimethylation of H3K27 in 3’ of exon 5(59). Changes in histone methylation can be seen in

TGF-β1, a pro-fibrotic gene, where increases in H3K4me1, H3K4me2 and H3K4me3 (associated with gene expression) and decreases in H3K9me2 and H3K9me3 (associated with gene silencing) in the TGF-β1 promoter region correlate with an increase in gene expression(60). This paper highlights how methylation can have a variable effect depending on locus.

Dysregulation of miRNA can contribute to liver fibrosis; this commonly involves upregulation of miRNAs promoting fibrosis and silencing of regulatory miRNAs. For example, upregulation of miR-33a and miR-34a have been shown to have a pro-fibrotic effect. Increased miR-33a downregulates the pro-adipogenic PPAR-α gene in the liver(61) whilst elevated miR-34a downregulates the Retinoid X Receptor α (RXRα), a regulatory gene in drug and lipid metabolism(62). In contrast, the expression of many protective miRNAs is reduced in fibrotic cells(63). This includes miR-200a, which allows for the proliferation of TGF-β1 dependent HSCs(64), and miR-29b(65), which acts as an inhibitor of several extracellular matrix genes (such as collagen 1A1 and elastin) whilst also inhibiting the maturation of collagen in HSCs. Clearly, miRNAs are targeted for upregulation or downregulation depending on their effect on HSCs.

4.3.          Non-alcoholic Fatty Liver Disease

Steatosis (triglyceride accumulation in the liver) arises from a number of genetic, environmental and epigenetic causes(66) and may lead to the development of NAFLD(67). It begins at a relatively benign stage of simple steatosis (SS) but can progress to a more severe stage known as non-alcoholic steatohepatitis (NASH). Patients with NASH commonly have liver cell injury, inflammation and also steatohepatitis (excessive fat accumulation), and consequently may develop cirrhosis and HCC(67)(Figure 9).

Extensive mitochondrial damage has been documented in NASH patients such as the destruction of mitochondrial cristae(68). Mitochondrial genes, such as MT-ND6, may be silenced by methylation. This gene had more methylated alleles in NASH (28.4%) compared to only 20.6% in SS patients(68). Decreased transcription of MT-ND6 causes reduced assembly of the mitochondrial enzyme complex I and less fat oxidation. This is important as complex I generates an electrochemical gradient to drive ATP synthesis, using mtDNA-encoded subunits (such as ND6) in proton translocation(69). Thus, methylation of genes contributes to NASH progression.

Histone modification is also implicated in NAFLD. The methyltransferase Polycomb Group protein Enhancer of Zeste Homolog 2 (EZH2), which regulates gene expression by causing specific transcriptional repression, is decreased as the severity of NAFLD increases, corresponding with higher lipid accumulation and the expression of pro-inflammatory markers(66). At the same time micro-RNA also plays a part in the development of NAFLD. MiR-122 in particular is greatly underexpressed in NAFLD patients, but it usually accounts for 70% of all mi-RNAs in the liver. MiR-122 affects cholesterol biosynthesis in vivo and has been shown to promote adipocyte differentiation, suggesting it is a crucial regulator of lipid metabolism in the liver(20, 67). Li et al., researched this by treating diet-induced obese mouse models with antisense oligonucleotide treatment to inhibit miR-122 function. This decreased mRNA expression of main lipogenic genes such as acetyl-coenzyme-A carboxylase-2, fatty acid synthetase and 3-hydroxy-3-methyl-glutaryl coenzyme A (HMG CoA) reductase. Consistently, histology tests show increased liver steatosis(70).

miR-122 and also miR-705 are increased in both NAFLD and alcoholic liver disease(71); this is expected as both diseases have similar pathogenic mechanisms. Another mi-RNA associated with NAFLD is miR-335, found in the liver and white adipose tissue. Increased miR-335 expression is shown to increase body, liver and white adipose tissue weight, along with elevating hepatic triglyceride and cholesterol levels(70). NAFLD can also lead to HCC development, which is shown when miR-21 is activated by unsaturated fatty acids in hepatocytes that trigger steatosis. This then directly inhibits the expression of the tumour suppressor, phosphatase and tensin homolog gene (PTEN)(67).

Figure 9: Epigenetic changes showing the progression from SS to NASH.

5. Therapy

The mentioned epigenetic pathways related to the development of liver disease may be targeted pharmacologically. As most research and clinical trials target cancer therapy(72), this will be the focus, but similar principles apply to all diseases with an epigenetic component. The classical ‘epigenetic drugs’ are inhibitors of DNA methyltransferase and histone deacetylase, but there is active research into other enzyme inhibitors and miRNA therapy. In this section we will discuss the mechanisms of action of the classical drugs, progress in their clinical implementation, and the development of novel agents.

5.1.          Mechanisms of Action

5.1.1.     DNA methyltransferase inhibitors

DNMT inhibitors possess therapeutic potential in diseases with wide-spread hypermethylation, e.g. reactivating TSGs in cancer(72). Andersen et al.(73) use epigenomic profiling to show increased demethylation of genes for tumour-suppression, apoptosis, and cell cycle regulation in zebularine-treated Huh7 and KMCH HCC cell lines, but also identify drug-resistant cell lines, where oncogenes are upregulated with treatment. This highlights the importance in  establishing whether tumour-suppressor or oncogenic genes are dominating the carcinogenic pathway before beginning treatment in vivo.

Figure 10: Normal DNMT-catalysed methylation of cytidine

Normal action of DNMT-catalysed cytosine methylation involves a covalent interaction between a cysteine residue of the enzyme active site and carbon-6 of the cytosine ring, resulting in increased electron flow to carbon-5(72,74). Subsequent nucleophilic attack on the methyl group of the substrate, S-adenosylmethionine(SAM), proton abstraction from carbon-5 and a β-elimination reaction allows the reformation of the C5=C6 bond and formation of the 5-substituted pyrimidine ring (Figure 10).

Figure 11: Chemical structures of cytidine (cyt) and the various cytosine analogue DNMT inhibitors. R represents ribose and dR represents deoxyribose

Cytosine analogues (Figure 11) represent the majority of current DNMT inhibitors(72). Santi et al.(74) propose that, in the case of 5-azacytidine or 5-aza-2′-deoxycytidine, DNMT

irreversibly binds to the highly reactive carbon-6 of the cytosine ring, forming a very stable covalent bond (Figure 12). This mechanism, involving the formation of a ‘dead-end’ product, has been confirmed experimentally using biochemical techniques (gel electrophoresis and enzymic titration)(75), and more recently by direct fluorescent visualisation(76).

Figure 12: Methylation of 5-azacytidine.  Inhibition is created by irreversible binding of the enzyme to the 5-aza-C molecule

Zebularine (2-H pyrimidinone) is another cytosine analogue which lacks the amino group at position 4.  Zhou et al.(77) use X-ray crystallography to demonstrate the formation of an irreversible covalent bond between bacterial DNMT and zebularine, proposing an inhibited deamination side-step in this case (Figure 13). Given that DNMT shows some catalytic activity in cytosine deamination(78), this is a reasonable proposal.

Figure 13: Methylation of zebularine.  As the amino group is absent, the proposed deamination side-step cannot proceed.  Hence, C5 is not methylated and there is irreversible binding of the DNMT enzyme, creating inhibition.

Second generation cytosine analogues (pro-drugs of traditional analogues) are a novel class of DNMT inhibitor.  For example, CP-4200 is an ester of 5-aza-C and SGI-110 is a 5-aza-dC dinucleotide (79). Using such pro-drugs may improve cellular uptake(80,81), protect from enzymic degradation(80) and improve the adverse effect profile(82). Additionally, there are several types of non-nucleoside DNMT inhibitor(79). These include existing drugs with other uses (such as hydralazine, procainamide and nanaomycin A) that show effects on DNMT activity, or new developments such as MG98, an anti-sense oligonucleotide, that binds to the 3’-UTR of DNMT1 and inhibits transcription(79).

5.1.2.     Histone deacetylase inhibitors

Histone deacetylase inhibitors (HDACi) have been extensively studied as potential oncological drugs(83). Carlisi et al.(84) demonstrate dose and time-dependent induction of apoptosis in human hepatoma cells when treated with various types of HDACi, with immunoprecipitation analysis revealing the presence of acetylated p53, histones and histone acetyltransferase enzymes. Furthermore, studies on mice with induced acute promyelocytic leukaemia(85) and melanoma cell lines(86) have shown activation of extrinsic and intrinsic apoptotic pathways respectively. Other possible anti-tumour effects of HDAC inhibitors include the induction of mitotic and autophagic cell death, and the inhibition of angiogenesis(83).

There are four classes of HDAC enzyme, based on sequence homology to yeast counterparts(83). Class I, II and IV are Zn2+ dependent, whereas class III HDACs are NAD+ dependent and belong to the sirtuin family(87). Most HDAC inhibitors target Zn2+  dependent HDAC, with the pharmacophore consisting of three regions – the ‘cap’ region blocks the active site; the zinc binding region chelates the Zn2+ ion, and the ‘linker’ region connects the two(88). The main classes of these HDACi are hydroxamates, benzamide derivatives, cyclic peptides and short-chain fatty acids(87,89). Inhibitors of sirtuin proteins (Class III HDACs) operate under a different mechanism(87).

Hydroxamates act as broad inhibitors of class I, II and IV HDACs(83,88,89). Trichostatin A (TSA) was the first described HDAC inhibitor, and the design of newer hydroxamate HDACis, e.g. vorinostat (suberoylanilide hydroxamic acid), is largely based on the structure of TSA, with an aromatic ‘cap’ region, hydrophobic ‘linker’ and hydroxamic acid zinc-binding region(89). Other classes of HDACi may increase specificity and selectivity.  For example, benzamide derivatives (e.g. etinostat, mocetinostat) have a ‘cap’ region that binds to other complex components near the HDAC active site, meaning they are generally selective to inhibiting class I HDACs(88).

5.2.       Current Trials

The greatest therapeutic success is seen in treatment of haematological cancers, as they are easier to target than solid tumours, due to the ability to target and protect the function of their stem progenitor cells(90). Five drugs have been FDA approved(91), namely the three HDAC inhibitors Vorinostat, Belinostat and Valproic Acid, and DNMT inhibitors 5-azacytidine and decitabine.

There are over 350 current clinical trials for HDAC inhibitors(92). However, progress is slow converting these clinical trials to approved medicines, due to major pleiotropic effects. Hence, trials are being conducted to ascertain the safety of these drugs e.g. the use of HDAC inhibitor CHR-2845 in Lymphoid Malignancies (93). Chemical probes (short half-life HDACi analogues), such as UHC999 for EZH2 inhibitors, have been developed to help predict systemic effects(94), but this does not solve safety concerns. This struggle is particular with DNMTs, where replacements for first-generation drugs have not been adequate. Nevertheless, azacytidine has additional benefits such as the upregulation of miR-127, which downregulates the oncogene BCL6(95). Furthermore, reversal of MLH1 silencing increases tumour sensitivity to cisplatin, highlighting the potential to increase the efficacy of chemotherapy(96).

Whilst specific miRNA targeting drugs are in their infancy, they are showing promising clinical potential. Miravirsin is now completing a phase II trial with encouraging results in treatment of Chronic HCV infection(97). However, most trials are only conducted on terminal patients (due to ethical reasons), thus potentially preventing epigenetic therapies from receiving a positive result(98), especially as evidence shows that HDAC inhibitors have a reduced response in patients who are immunocompromised(99). Despite this, much promise has come from clinical trials involving epigenetic drugs in combination therapies. For example, an increase of efficacy seen when Vorinostat is combined with carboplatin in non-small cell lung cancer(100), which is exciting considering that both are FDA approved and ready to be used as treatment. Even greater success was seen when Vorinostat was combined with the proteasome inhibitor Bortezomib for the treatment of relapsing multiple myeloma(101). Combination therapies with HDAC inhibitors have shown clinical potential for indirect cancer treatments, such as the combination with Ganciclovir, preventing viral resistance against this drug(102), which may prove important in increasingly resistant viral Hepatitis; and also combination with anti-androgens such as Tamoxifene(103). This puts HDAC inhibitors in a prophylactic role, increasing the efficacy of a relatively unstable yet vitally important drug in the prevention of recurrence of breast cancer.  Although there has yet to be any major clinical breakthrough for epigenetic drugs, partly hampered by the limited methodologies of the clinical trials, it is illustrated here the breadth of clinical potential

epigenetic drugs can have with greater research and development of more target specific drugs.

 5.3.          Future Therapies

5.3.1.     Histone modifications

JMJD3 is a histone demethylase specific to H3K27me3, expressed in macrophages upon activation by the endotoxin of certain bacteria(104). This demethylation allows the transcription of cytokines like TNF-α, so is key for the inflammatory response. GSK-J1 is a specific inhibitor of JMJD3, which successfully reduced the expression of 16 of 34 LPS-stimulated cytokines in human primary macrophages(104). The drug therefore has potential in patients with sepsis and other inflammatory disorders.

However, it has an even greater prospective prophylactic use. In obese patients, or those infected with HBV/HCV, it is chronic inflammation, with marked TNF-α elevation , which can lead to fibrosis, and potentially HCC(105). Therefore, the drug could target these patient groups to prevent HCC progression. Trials using obese mice, or transgenic mice which can stably bear the genomes of HBV/HCV, could test the effectiveness of GSK-1 for this purpose.

5.3.2.     miRNA uses

miRNAs are frequently dysregulated in cancers; miR-125b is particularly under-expressed in over 70% of HCC cases(106). Liang et al.(106) found that introducing exogenous miR-125b suppressed HCC cell growth and inhibited metastasis in the HepG2 and Huh-7 cell lines. miR-125b expression arrested cell cycle at the G1/S transition through expression of p21Cip1/Waf1 – the regulatory protein at this point. Injecting the Huh-7 cells into nude mice to test the in vivo response to miR-125b achieved similar results, with tumours from the miR-125b expressing cells being significantly smaller than in controls.

Similar successes have been achieved with other miRNAs. miR-140-5p is also down regulated in many HCC cases(107), and its expression had successes in comparable studies. Expression of miR-140-5p in the HCCLM3 and MHCC97-L cells arrested cell cycles at the S phase, and caused smaller tumours and reduced metastasis in mice. Its downstream targets were found to be the TGF-β receptor and Fibroblast Growth Factor 9. miR-26a showed very similar success in another study(108), arresting cell cycle by targeting the D2 and E2 cyclins.

The fact that they can reduce the potential for invasion or metastasis is very useful, as this could drastically improve survival rates, even if they are not curative. However, more in vivo research with these specific cancers is needed before clinical trials can begin.

5.3.3.     Chromatin reader targets        

BRD4 is an epigenetic reader enzyme, recognizing acetylated histones and recruiting pTEFb, an enzyme crucial for transcription(109). It has been implicated in many cancers as a driver of oncogene expression, particularly c-myc. JQ1, an inhibitor of BRD4, has been successful in preclinical trials against acute myeloid leukaemia (AML)(110). Cell samples were taken

from 37 patients with AML, from both freshly diagnosed cases and relapsing patients. JQ1 showed potent anti-AML effects in all cells, particularly growth inhibition and induction of apoptosis. This shows that adverse epigenetic modifications are preserved in cancer patients treated with traditional therapy – targeting these could be crucial to effectively treating these diseases.

Like many of the drugs mentioned before, it was also observed that JQ1 seemed to have a synergistic effect with ARA-C, a traditional chemotherapeutic drug. Further in vivo preclinical study is needed to determine how effective it is.

 

 Table 1: List of some epigenetic drugs in preclinical trials

Epigenetics is therefore an exciting prospect for drug targets, particularly as the modifications are so dynamic, unlike the mutations behind many genetic diseases(111). However there is concern about the possible pleiotropic effects previously mentioned. More research and a better understanding is needed before more specific targets and molecules can be developed.

6. Discussion

Our research elucidates the significance of epigenetics in the pathogenesis of liver disease. Appreciation of mechanisms is crucial in understanding pathophysiology and potential therapies, however as epigenetics is a relatively new field, many aspects need clarification before they have therapeutic potential, such as  mechanisms involving phosphorylation, and whether arginine demethylases exist. Furthermore, epigenetic inheritance in the liver has not included the F3 generation, so cannot yet be proved as transgenerational.

Epigenetic mechanisms and corresponding treatments were researched using immunoprecipitation techniques to locate and analyse specific histone modifications. However, this requires antibodies for specific modifications so it only allows research to

better understand known modifications and their interactions rather than identify previously unknown modifications where many remaining knowledge gaps reside. This requires other methods such as genome wide methylation analysis which are more cost and labour intensive. The discovery that the modification location can alter its effect (e.g. H3K4 methylation causes upregulation whereas H3K9 methylation causes suppression) means each modification is unique, slowing progress. Importantly, use of higher eukaryotes in these techniques as shown by Schübeler et al.(27) produces results more transferable to humans. Establishing causal links between epigenetic modifications and disease requires loss/gain of function studies, although this is not always practical. Hence, most studies  were retrospective, identifying differential gene expression in normal and diseased tissue for potential causality.

An under-explored avenue is the use of epigenetic therapies in disease prevention. For example, epigenetics has the potential to prevent EMT to substantially reduce incidence of tumour metastasis and resulting mortality, as well as reversing the widespread hypomethylation consistently identified in early stages of oncogenesis. However, once potential treatments are validated using preclinical models they are subjected to clinical trials. Generally, only the sickest patients that exhausted other treatments are offered these drugs, potentially creating a selection bias. Also, pathological research focusses on disease progression instead of its endpoint. Early reversal via targeted treatment can improve outcomes , e.g. the upregulation of the histone deacetylase enzyme SIRT 1 causes HCC, and histone deacetylase inhibitors are potential oncological drugs. This highlights the importance of receptor targets in causing and curing disease. The wide variation in human genome could affect epigenetic therapies, making it difficult to generalise treatment.

Current epigenetic drugs are generally more successful against haematological cancers, due to greater accessibility of bone marrow stem cells. Encouragingly, there are some emerging treatments for solid tumours, such as Miravirsen (miRNA inhibitor) for chronic HCV infections that frequently results in HCC. Additionally, treatments replacing depleted endogenous miRNA are promising, as they naturally regulate many cellular pathways, reducing chances of cancerous cells acquiring drug resistance, as well as having less pleiotropic effects.

The studies analysed were mostly consistent with each other, suggesting validity and reliability. Priorities for further research include continued establishment of epigenetic mechanisms and disease pathology to improve drug development. Besides targeted therapy, more consideration should be given to transgenerational epigenetic mechanisms, and increasing awareness to the lifestyle choices that potentially predispose future generations to liver disease through epigenetic modifications.

Required Appendices

Critical Appraisal: Dutch Famine Study(1)

1. Objectives of the study

To determine effects of maternal (F0) exposure to famine during pregnancy on the health of the F1 and F2 generations, focusing on metabolic and cardiovascular disease.

2. Population

Men and women (F1) born in the Wilhelmina Gasthuis Hospital, Amsterdam between 1st November 1943 and 28th February 1947, interviewed about the health of their offspring (F2).

3. Study design

Retrospective cohort study.

4. Size of study

855 hort members (F1) giving information on 1496 (F2) offspring.

5. Intervention

Exposure to famine in utero, determined by date of birth (exposed group born from 7th January 1945 – 8th December 1945). During this period, maternal caloric intake was under one thousand calories due to rationing. The control group included all others in the specified population, born before and after the exposure period.

6. Randomisation/Blinding

No scope for randomisation. No interviewer blinding mentioned.

7. Were any statistical tests used? How were groups or results compared?

Linear regression for continuous variables and logistic regression for binary variables (F0 and F1). Mann-Whitney test compared F2 offspring in unexposed and exposed groups. Linear mixed models were also used.

8. Outcome measure

F1- Birth weight, birth length, ponderal index. Smoking, SES, BMI, LDL/HDL ratio, two hour glucose concentration also measured.

F2 – Research gathered via F1 interview (of birth weight, birth length, ponderal index, and health in later life).

9. Main results

No significant difference in F2 birth weight, however in offspring of exposed F1 women, birth length was decreased (-0.6cm p=0.01, adjusted) whilst ponderal index increased (+1.2kg/m3, p=0.001) compared to controls. Poor health due to other causes was 1.8 times more likely in offspring of exposed F1 mothers (although no proven link specifically to cardiovascular or metabolic disease) compared to controls. No significant difference was noted in children (F2) of F1 men.

10. Conclusions

Following F1 in utero famine exposure, there was increased F2 neonatal adiposity and future morbidity.

No association between F1 in utero famine exposure and F2 metabolic or cardiovascular disease incidence, which did not support the hypothesis.

The suggested role of epigenetics in transgenerational disease occurrence was supported by the study.

11. Sources of Bias

Recall bias – F1 recall may be inaccurate due to memory problems, different subjective definitions of health or different levels of education/medical knowledge. The study acknowledged the gender differences (F1) in health reporting of offspring (F2). Our group thought it would have been better to use clinical records.

Intermarriage between F1 cohort not accounted for, so genetic traits might be a confounding factor.

Blinding – Although the study was retrospective, interviewers and analysts should have been blinded to reduce the potentially influence on result recording and analysis.

12. Comments

Positives:

Confounding factors (e.g. obesity and smoking) were removed. Adjustments were made for gender to remove potential inaccuracies and improve validity. Large sample size minimizes chance and increases power. (Exclusions from initial cohort

based on geographical location, not health status/conditions.) Novel research idea: Human F2 generation looked at following F0 exposure using rare

natural occurrence.

Negatives:

No inclusion of F2 medical records to make results more accurate/consistent with F1 methodology.

Greater focus on F1 cohort results in study although aims related to F2 generation. Large variation seen in F2 cohort ages (1-43yo) – may affect conclusions regarding health

status and cardiovascular and/or metabolic disease incidence. No consideration given to gender or age predispositions to diseases.

13. Bottom Line

This novel paper offers an interesting insight into epigenetic inheritance. It provides some new information and is concordant with conclusions of similar studies although repeating the experiment using F2 medical records could confirm the results.

Information Search Report

As previously discussed, epigenetic research is still a recent concept, with a lack of consolidation of primary literature. Furthermore, literature is highly limited to specialist areas, and is not well established for its role in disease progression. To inform our knowledge, we were presented with three reviews into epigenetics that focused on its role in cancer, liver disease and therapeutics. Individually, we used these articles as a basis to uncover relevant mechanisms and literature.

To focus our project, we divided into sub-groups that focused on epigenetic inheritance, mechanisms, pathology of liver disease, and therapeutics. We then sourced relevant literature using the databases Medline, Scopus, Google Scholar, Web of Science, and PubMed, with the aim of finding both primary literature and reviews. In order to keep the searches relevant, it was important to limit our search by identifying key words and using Boolean operators. For example, to find papers on epigenetics and hepatocellular carcinoma, we searched for “epigenetics AND hepatocellular carcinoma”. MeSH was also useful to include all relevant literature. For example, a study on “liver cancer” may have been missed if we solely searched for “hepatocellular carcinoma”. We had institutional access to full texts, so accessing journal articles of appropriate impact factor was not a problem.

Example of combining MeSH terms.

It was of great importance to ensure our sources were reliable. In light of this, we endeavoured to use reputable journals wherever possible (refer to Impact Factor Table). The average impact factor for papers cited was 13.442 (Range 1.929 – 54.420).

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Contributions PageLoo Cheng Yi – Epigenetic Inheritance, including Figures 1 and 2.Nadia Salloum – Epigenetic Mechanisms (Histone Modifications), including Figures 3 and 4.Rachael Boyle – Epigenetic Mechanisms (DNA methylation and miRNA), including Figures 5 and 6.Jason Young – Pathology Section (Hepatocellular Carcinoma and Liver Fibrosis), including Figures 7 and 8.Alisha Sachdev – Pathology Section (Hepatocellular Carcinoma and NAFLD), including Figure 9.Sidhant Seth- Therapy (Mechanisms of drug action), including Figures 10, 11, 12 and 13 using ChemDraw 14.0.Connor McKee – Therapy (Current treatments and trials)Vhinoth Sivakumaran – Therapy (Future therapies), including Table 1.

Equal author contribution to write the Introduction, Information Search Report, Critical Appraisal and Discussion.

Optional Appendices

AbbreviationsIn alphabetical order:AML: Acute Myeloid LeukaemiaDNMT: DNA MethyltransferaseEMT: Epithelial Mesenchymal TransitionEZH2: Enhancer of Zeste Homolog 2HAT: Histone AcetyltransferaseHBV: Hepatitis B virusHBx: Hepatitis B interacting proteinHCC: Hepatocellular CarcinomaHCV: Hepatitis C virusHDAC: Histone DeacetylaseHDACi: Histone Deacetylase InhibitorsHMG CoA: 3-hydroxy-3-methyl-glutaryl coenzyme AHSC: Hepatic Stellate CellMeCP2: Methyl CpG binding protein 2miRNA: micro RNAMT-ND6: mitochondrially encoded NADH dehydrogenase 6NAFLD: Non-alcoholic Fatty Liver DiseaseNASH: Non-alcoholic SteatohepatitisPTEN: Phosphatase and tensin homolog geneSS: Simple SteatosisTERT: TelomeraseTET: ten-eleven-translocation enzymeTSA: Trichostatin ATSG: Tumour Supressor Gene

Summary of Figures

Figure 1 (Section 2.): Possible direct exposure of F0-F2 generations.

Figure 2 (Section 2.1.): Zygote inherits different imprinted/repressed genes, i.e. maternally imprinting means the corresponding paternally inherited gene will be expressed, and vice versa.

Figure 3 (Section 3.1.): Nucleosome structure within chromatin.

Figure 4 (Section 3.1.1.): Enzymes involved in histone modification.

Figure 5 (Section 3.2.): The production of hemimethylated DNA through (A) DNA replication and (B) Nucleotide Excision Repair.

Figure 6 (Section 3.2.): Biochemical alterations involved in methylation and demethylation, and the enzymes involved in each process.

Figure 7 (Section 4.1.): HBx protein and its oncogenic actions (TSG: tumor suppressor gene).

Figure 8 (Section 4.2.): Pathways contributing to a phenotypic switch of HSCs to myofibroblasts.

Figure 9 (Section 4.3.): Epigenetic changes showing the progression from SS to NASH.

Figure 10 (Section 5.1.1.): Normal DNMT-catalysed methylation of cytidine

Figure 11 (Section 5.1.1.): Chemical structures of cytidine (cyt) and the various cytosine analogue DNMT inhibitors. R represents ribose and dR represents deoxyribose

Figure 12 (Section 5.1.1.): Methylation of 5-azacytidine. Inhibition is created by irreversible binding of the enzyme to the 5-aza-C molecule

Figure 13 (Section 5.1.1.): Methylation of zebularine.  As the amino group is absent, the proposed deamination side-step cannot proceed.  Hence, C5 is not methylated and there is irreversible binding of the DNMT enzyme, creating inhibition.

Impact Factor TableJournal 2013 Impact factor Number of papers used

Cell 33.116 12

Hepatology 11.190 4

PLoS One 3.534 4

Cell Signal 4.471 3

Gastroenterology 13.926 3

J Clin Oncol 17.879 3

Mol Cancer Ther 6.107 3

Oncogene 8.559 3

Science 31.477 3

World J Gastroenterol 2.433 3

Br J Cancer 4.817 2

Cancer Res 9.284 2

Genes Dev 12.639 2

Int J Cancer 10.014 2

J Hepatol 10.401 2

Nat Med 28.054 2

Nature 42.351 2

ACS Med Chem Lett 3.073 1

Ann N Y Acad Sci 4.313 1

Annu Rev Plant Biol 18.900 1

Behavioral Ecology 3.157 1

Biochem Biophys Res Commun 2.281 1

Biochem J 4.779 1

Biochem Pharmacol 4.650 1

Biochimie 3.123 1

BJOG 3.862 1

Br J Haematol 4.959 1

Br J Nutr 3.342 1

Cancer Cell 23.893 1

Cancer Lett 5.016 1

Cell Cycle 5.006 1

Clin Lymphoma Myeloma Leuk 1.929 1

Curr Opin Oncol 3.761 1

EMBO J 10.748 1

EMBO Rep 7.858 1

Environ Health Perspect 7.029 1

Epigenomics 5.215 1

Future Med Chem 4.000 1

Gut 13.319 1

Hepatol Res 2.218 1

Int J Mol Sci 2.339 1

Int J Oncol 2.773 1

J Biol Chem 4.600 1

J Gastroenterol 4.020 1

J Mol Biol 3.959 1

J Nutr 4.227 1

J Proteome Res 5.001 1

J Viral Hepatitis 3.307 1

Lab Invest 3.828 1

Lancet Oncol 24.725 1

Mol Cell 14.464 1

Mol Cell Biochem 2.388 1

Mol Interv 12.143 1

Mol Oncol 5.935 1

Mol Pharmacol 4.120 1

N Engl J Med 54.420 1

Nat Cell Biol 20.058 1

Nat Methods 25.953 1

Nat Rev Drug Discov 37.231 1

Nat Rev Genet 39.794 1

Nat Rev Immunol 33.836 1

Nat Struct Mol Biol 11.633 1

Neoplasia 5.389 1

Nucleic Acids Res 8.808 1

Nutrients 3.148 1

Oncotarget 6.627 1

Proc Natl Acad Sci USA 9.809 1

Prog Biophys Mol Biol 3.377 1

Q Rev Biol 5.059 1

Sci Transl Med 14.414 1

Trends Endocrinol Metab 8.868 1

Trends Pharmacol Sci 9.988 1

Average Impact Factor 13.519 Range: 1.929 – 54.420