Depressive disorder and antidepressants from an epigenetic point of view

Abstract

Depressive disorder is a complex, heterogeneous disease that affects approximately 280 million people worldwide. Environmental, genetic, and neurobiological factors contribute to the depressive state. Since the nervous system is susceptible to shifts in activity of epigenetic modifiers, these allow for significant plasticity and response to rapid changes in the environment. Among the most studied epigenetic modifications in depressive disorder is DNA methylation, with findings centered on the brain-derived neurotrophic factor gene, the glucocorticoid receptor gene, and the serotonin transporter gene. In order to identify biomarkers that would be useful in clinical settings, for diagnosis and for treatment response, further research on antidepressants and alterations they cause in the epigenetic landscape throughout the genome is needed. Studies on cornerstone antidepressants, such as selective serotonin reuptake inhibitors, selective serotonin and norepinephrine reuptake inhibitors, norepinephrine, and dopamine reuptake inhibitors and their effects on depressive disorder are available, but systematic conclusions on their effects are still hard to draw due to the highly heterogeneous nature of the studies. In addition, two novel drugs, ketamine and esketamine, are being investigated particularly in association with treatment of resistant depression, which is one of the hot topics of contemporary research and the field of precision psychiatry.

Key Words: Epigenetics, Depression, DNA methylation, Histone tail modification, microRNA, Antidepressants

Core Tip: Deeper knowledge on the biological background of depressive disorder could be achieved through understanding of epigenetic mechanisms that alter the response of cells to environmental stimuli. Antidepressants are of particular interest since it has been shown that they affect DNA methylation, histone modifications, and microRNA expression. As not all patients respond to prescribed antidepressants, it is of interest to discover specific biomarkers that could be used in a clinical setting.

INTRODUCTION

Depressive disorder

Depressive disorder is a complex heterogeneous disease that affects more than 280 million people[1]. The principal form of depressive disorder is major depressive disorder (MDD). Symptoms of depressive disorder are persistent depressive mood, diminished ability to feel pleasure and rejoice, weight changing, disturbed sleep, loss of energy, lowered self-esteem, trouble with concentration, elevated emotional psychomotor activity in children and teenagers, psychomotor agitation or motor retardation, and self-injuring or suicidal ideation[2]. The suicidality phenotype includes ideation, suicide attempt, and death by suicide. MDD is, along with bipolar disorder, schizophrenia, and substance use disorder, one of the most common mental disorders in people who die by suicide[3]. Depression contributes to suicidality, and it increases mortality risk by 60%-80%[4]. According to the Diagnostic and Statistical Manual of Mental Disorder Diagnosis, MDD must exhibit five (or more) out of ten symptoms[2].

The prevalence of depression is higher for women (4.1%) than for men (2.7%)[5]. Sex differences are exhibited in multiple cells of the central nervous system (CNS), neurons, astrocytes, and microglia[6]. Emerging data is showing that besides hormones, epigenetic differences have considerable sexual dimorphism[7]. However, steroid hormone levels influence levels of DNA methyltransferases (DNMTs). For example, female rats had higher levels of DNMT3a and methyl CpG binding protein 2 (MeCP2) in the amygdala (an important center for modulating juvenile social play, aggression, and anxiety)[6] and the preoptic area[7]. As a result of a difference in DNMT3a, there is also a difference in the DNA methylation level[6].

Moreover, people aged 50 years and more have a 1.5 times higher risk for developing depression than younger people[5]. Modern lifestyle promotes independence of the environmental light/dark cycle, which leads to shifting in sleep-wake patterns. Circadian rhythm disruption is affected by the increase in nocturnal activity, decrease of sleep, and extended exposure to artificial light during the nighttime[8]. Limbic brain regions, monoamine neurotransmitters, and the hypothalamic-pituitary-adrenal (HPA) axis are under circadian regulation. It is thought that the perturbation of circadian rhythms contributes to the prevalence of depression and other mood disorders[9].

Depressive disorder is a result of the interplay of many different factors: Environmental, genetic, neurobiological, and cultural[10]. Known environmental risk factors for developing depressive disorder are poverty, negative experiences in the family (bad relationship, violence, divorce, child maltreatment), or other stressful life events. In the time after a stressful life event, the risk for depressive disorder is elevated but the effects of adversity can persist over time[4]. In depressive symptoms that persist over time, stable molecular adaptations in the brain, especially at the level of epigenetics, might be involved[11].

Genetic heritability for depressive disorder, estimated from twin studies, is around 35%–40%[10,12]. Genome-wide association studies have discovered multiple loci with small effects that contribute to MDD[13]. Pandya et al[14] collected results from neuroimaging, neuropsychiatric, and brain stimulation studies and showed similar results. In recent years, more and more studies are oriented towards epigenetics to understand new mechanisms and the way epigenetics is linked to a depressive state.

The nervous system is susceptible to shifts in the activity of epigenetic modifiers, which allow for significant plasticity and response to rapid changes in the environment[15]. Epigenetic mechanisms are dynamic. They are very important for early development of the organism as well as later in life, as a response to external factors[16].

From a biological perspective, there are four theories of depressive disorder: Monoamine theory, stress induced theory, neurotrophic theory, and cytokine theory (Figure 1).

Figure 1 Depressive disorder risk factors. Depressive disorders are influenced by various and often overlapping risk factors that form theories of depressive disorders.

Theories of depressive disorder

The monoamine theory of depressive disorder: Monoamine neurotransmitters (serotonin, nore-pinephrine, and dopamine) are chemical messengers involved in the regulation of emotion, arousal, and certain types of memory. The monoamine hypothesis of depressive disorder proposes development of depressive disorder by signal dysfunction between neurons: A decreased level of neurotransmitters leads to the depressive state[2,17].

The stress induced theory of depressive disorder: Prenatal stress, early-life adversities, chronic stress, and stressful life events are all strong predictors of the onset of depressive disorder. The HPA axis, a neuroendocrine system, is responsible for adaptation to changing environments. Response to stress begins in the hypothalamus, with the secretion of corticotropin-releasing hormone, which affects the pituitary gland to release adrenocorticotropic hormone. Adrenocorticotropic hormone circulates in the blood and stimulates the release of glucocorticoid hormones (cortisol) in the adrenal cortex. Cortisol binds to glucocorticoid receptors in the brain, which are key regulators of the stress response. Cortisol with a negative loop inhibits the HPA axis. Dysregulation of the negative loop is associated with depressive disorder[2,17].

Neurotrophic theory of depressive disorder: Neurotrophic factors are peptides or small proteins that support the growth, survival, and differentiation of developing and mature neurons. Decreased neurotrophic support affects the development of depressive symptoms. Brain-derived neurotrophic factor (BDNF) is a very well examined neurotrophic factor. Many studies made on brain and blood showed decreased expression of BDNF in patients with depressive disorder. Also, decreased BDNF expression has been associated with epigenetic modifications of the BDNF gene[17].

Cytokine theory of depressive disorder: Cytokines are small secreting proteins important in cell signaling. Cytokines include chemokines, interferons, interleukins (IL), lymphokines, and tumor necrosis factors (TNF)[18]. The cytokine (or inflammation) theory of depressive disorder suggests that inflammation has a significant role in its pathophysiology. Patients with depressive disorder have increased inflammatory markers, IL-1β, IL-6, TNF-α, and C-reactive protein[19]. Depressive disorder is not a typical autoimmune disease, so the elevation of cytokines in patients with depressive disorder is lower than in autoimmune or infectious diseases[2].

There are several proposed theories by which the immune system (cytokines and immune cells) could affect depressive-like behavior[20]. For example, inflammation in peripheral tissue can signal the brain via the vagus nerve, cytokine transport systems, and a leaky blood-brain barrier caused by rising TNF-α, which leads to brain accessibility for other peripheral signals[19].

Cytokines in the brain elevate during chronic stress and depressive disorder, but besides peripheral cytokines they can also arise from the CNS. Cytokines IL-6 and TNF-α activate indoleamine-2,3-dioxygenase, which decreases tryptophan (a serotonin precursor) and consequently reduces serotonin. Moreover, indoleamine-2,3-dioxygenase is included in the kynurenine pathway. Metabolites from this pathway activate monoamine oxidase (MAO), which degrades serotonin, dopamine, and norepinephrine. Cytokines might also act directly on neurons, changing excitability, synaptic strength, and synaptic scaling. Furthermore, cytokine IL-1β can contribute to heightened activation of the HPA axis and lowering inflammatory response to stress. During chronic stress microglia (neural immune cells) enhance phagocytic activity and synaptic remodeling[20].

Microglia represent 10% of all brain cells[21]. During the development of the organism, microglia are extremely active. They significantly contribute to shaping and refining developing neural circuits by regulating neurogenesis, synaptogenesis, synaptic pruning, and behavior. Early life stress, which is strongly associated with depressive disorder and other mental disorders, can trigger microglia perturbations and affect development through changed morphological and functional changes of microglia. For example, microglial phagocytic activity and neuronal-microglial signaling can disrupt neural circuits and alter the formation of behavior. Furthermore, aberrant functionality of maturing microglial cells can alter their developmental programs and have long-lasting consequences for their reactivity[22]. It is thought that innate immune memory is mediated through epigenetic reprogramming and can last in vivo for several months[23].

Epigenetics

In the 1940s, Waddington named the environmental influence of the genome epigenetics. Epigenetic modifications alter gene expression without changing the DNA sequence. The three key types of epigenetic change that occur in cells are DNA methylation, histone posttranslational modifications, and non-coding RNAs. The first two regulate gene transcription through altered chromatin structure and DNA accessibility, while the latter one regulates already transcribed messenger RNA (mRNA)[10]. Studies of epigenetics have escalated in the last 20 years and are gaining importance in the field of psychiatry. Through epigenetic studies, further understanding of depressive disorder is being achieved, but there are still many questions left to answer (Figure 2).

Figure 2 Epigenetic mechanisms. Epigenetic mechanisms include DNA methylation, noncoding RNA activity (such as microRNA), and posttranslational histone tail modifications. Ac: Histone acetylation; Me: Histone methylation; mRNA: Messenger RNA.

DNA methylation: DNA methylation is a process in which a single methyl group is added on the 5C of the cytosine DNA base. Methyl groups are transferred from S-adenosyl-L-methionine to cytosine by DNMTs[17]. In mammals, there are three groups of DNMTs; DNMT1, DNMT2, and DNMT3. DNMT1 maintains DNA methylation, DNMT3a and DNMT3b carry out de novo DNA methylation, and DNMT3L modulates DNMT3a and DNMT3b. DNMT2 has no DNA methylation activity. Instead it catalyzes RNA methylation, specifically on transfer RNAs[24]. DNA methylation mainly occurs at cytosine-phosphate-guanine (CpG) dinucleotides. When those dinucleotides are repeated many times in DNA sequence, they are called CpG islands. CpG islands have an average length of 1000 bp, and they contain more than 50% guanines and cytosines. Approximately 40% of genes contain CpG islands in promoter regions. Methylation of a promoter results in the inability of transcription factors to bind properly to regulatory elements and repression of gene transcription[17]. However, in mammals DNA methylation also occurs at CpA, CpT, and CpC. Those non-CpG methylation sites are common in brain tissue and several other tissue types[25] but at a three times lower rate than CpG methylation[26]. Besides methylation in promoter regions, it can also occur in the gene body and in intergenic regions and affect gene transcription[27]. DNA methylation is a stable cell state, but it can be reversed. Demethylation occurs when 5-methylcytosines are oxidized back to cytosines via three cytosine derivate forms: 5-hydoxymethylcytosine, 5-formylcytosine, and 5-carboxylcytosine[28].

Histone tail modification: The basic unit of chromatin is the nucleosome, which consists of negatively charged DNA and positively charged histone proteins. The nucleosome is an octamer, containing two copies of H2A, H2B, H3, and H4 proteins. Typically, a 147 bp long segment of DNA is wrapped around each nucleosome. H1 protein serves as a linker protein between the other histones that helps to condense nucleosomes even more[29]. Histone proteins have a long amino acid tail on their N-terminal end. In contrast with the core part of the histone protein, this extended part is very dynamic and is prone to chemical modifications[30]. To describe histone modifications we follow a standard nomenclature. First we write the name of the histone protein (H2A, H2B, H3, H4, or H1), then the modified amino acid residue (the name of amino acid and its site; for example, K4–lysine at site 4), and finally the type of modification (for example trimethylation–me3). An example of a final structure is H3K4me3. Specific proteins chemically modify histones and change chromatin conformation. Changes in conformation lead to the opening or closing of the chromatin, which allows or prevents transcription.

There are many different types of histone posttranslational modification, such as acetylation, methylation, phosphorylation, ubiquitination, etc, that can be modified differently and by different proteins called “writers” and “erasers.” Furthermore, “readers” are proteins important for cross-talk between different epigenetic modifications. For example, DNA methylation and histone modifications mutually influence each other. There are many different reader domains that recognize histone modifications[31]. The most studied histone modifications are acetylation and methylation[29].

Histone acetyltransferases are proteins that transfer acetyl groups to lysine residues on the amino acid tail of histone proteins, while histone deacetylases (HDACs) are proteins that remove acetyl groups from the histone tails. Addition of a negative acetyl group loosens the tight bond between the negatively charged DNA and positively charged histones. This enables access of transcriptional machinery to the regulatory parts of DNA and consequently gene transcription[10].

Histone methylation is the adding of methyl groups to lysine and arginine residues on the histone tail. Histone methyltransferases add methyl groups to the histone tail, and histone demethylases remove methyl groups. Methylation of the histone tail can work in two ways. It can open chromatin or condense it. This depends on the position of the lysine/arginine residue in the histone tail and the number of methyl groups added to the amino acid[10].

MicroRNAs: Non-coding RNAs include many different RNAs: PIWI-interacting RNAs, small nucleolar RNAs, long non-coding RNAs and the most studied, microRNAs (miRNAs). MiRNAs are noncoding, 19–24 nt long RNAs that bind to mRNAs. A mature miRNA goes through biogenesis before it achieves its final form. Briefly, it is transcribed as a 1 kb long primary RNA with a stem and loop structure. Primary miRNA is cleaved by Drosha ribonuclease III into a 60–100 bp long precursor miRNA. Precursor miRNA is then translocated from the nucleus into the cytoplasm where the endonuclease Dicer converts it into an unstable, double stranded small RNA. One strand of the duplex is degraded and the other, the mature miRNA, incorporates into the RNA-induced silencing complex along with Argonaut protein. Mature miRNA is complementary to one or more mRNAs. It binds to the 3’ untranslated region of the target mRNA and silences targeted mRNA or sends mRNA to degradation when binding is highly complementary[32].

EPIGENETICS AND DEPRESSIVE DISORDER

Biomarkers that could be associated with MDD are BDNF, the cortisol response, cytokines, and neuroimaging. However, due to the complex nature of depressive disorder a single biomarker is not sufficient for use in diagnosis or monitoring of the disorder. Therefore, it has been proposed to examine multiple biomarkers and use them for patient examination[33]. In genetic studies several polymorphisms associated with a depressive state were found in genes of the monoaminergic system (the gene that encodes for serotonin transporter, receptor genes for dopamine and serotonin, genes involved in signaling of noradrenaline and dopamine…), and genes involved in the functioning and regulation of the HPA axis[2] but did not reveal the role of the DNA sequence itself in the etiology of depressive disorder. Future epigenetics may present new findings, which could be included as possible biomarkers for MDD[33].

Epigenetic modifications were studied in the saliva and blood of the depressed patients, postmortem brain tissue of depressed patients who died by suicide, and rodent animal models (rats and mice). There are several ways to induce stress and a depressed state in animal models[34]. Chronic stress is induced with “bullying” by a bigger more aggressive mouse or witnessing another mouse being physically aggressed for several days[10]. Early life stress from humans can be evoked on animal models by maternal separation of offspring during early postnatal periods. Such induced stress in animals results in mimicking certain behavioral features of human depressive disorder. It has been shown that these methods evoke epigenetic changes, similar to those seen in humans[34].

Tables 1–4 show selected studies of epigenetic changes detected in samples of depressed patients and animal models. The most studied epigenetic modification is DNA methylation, and it has been rather extensively investigated in the BDNF gene, specifically exon I. In studies of depressive disorder induced by stress in the prenatal and early stages of life, methylation of glucocorticoid receptor gene (NR3C1) was the most analyzed. Lately, more studies are also considering histone 3 modifications among which are methylation of lysines 27, 9, and 4 and acetylation of lysine 14. Studies of miRNAs are diverse and are showing that a more standardized approach is needed.

Table 1 DNA methylation studies on depressed subjects, also associated with suicidality and life adversities.

Gene (region)	Alteration	Subjects and collected tissue	Ref.
NR3C1 1-F and FKBP5 intron 7 promoter	↑ DNA methylation at NR3C1 1-F, without significant differences at any of the measured individual CpG site in depressed patients. Association in salivary cortisol level and DNA methylation. ↑ DNA methylation in NR3C1 1-F at CpG 38 site in depressed patients, with early life adversity. No differences in FKBP5 intron 7 promoter	33 depressed patients (24 females, 9 males), 34 controls (21 females, 13 males). Whole blood and saliva	Farrell et al[67], 2018
MAOA and NR3C1 exon 1-F	↓ DNA methylation at MAOA’s first exon/intron junction; significantly ↓ at CpG 8 site from the intron region. ↑ DNA methylation at NR3C1 1-F’s promoter and exon in individuals experienced early parental death; significant ↑ at CpG 35 and 10.11 (sites close to NGFI-A binding site)	82 (for MAOA gene) and 93 (for NR3C1 1-F gene) depressed females, victims of early-life adversity and 92 or 83 controls. Saliva	Melas et al[35], 2013
BDNF, NR3C1, and FKBP5	Significant alteration in DNA methylation at 9 sites in BDNF gene body, at 6 sites in NR3C1 promoter region, and at 4 sites in FKBP5 gene body, 3’UTR and promoter	94 maltreated and 96 non-traumatized children. Saliva	Weder et al[68], 2014
BDNF exon I	↓ DNA methylation; differences at loci 87, 88 and 92–94, located within the CpG island region on the promoter of the exon I	360 depressed patients (32 females, 328 males). Saliva	Song et al[69], 2014
BDNF promoter between –694 and –577 relative to the transcriptional start site (12 CpG sites). SLC6A4 promoter adjacent to exon 1a between –479 and –350 relative to the transcriptional start site (10 CpG sites)	Depressed mood in 2nd trimester associated with ↓ DNA methylation at maternal SLC6A4 promoter methylation status. ↓ DNA methylation at SLC6A4 promoter in infants, from mothers with higher depressed mood during 2nd trimester. No difference in BDNF gene	82 female and male infants exposed to prenatal maternal stress–33 mothers treated with SRI and 49 mothers not treated with SRI. Blood	Devlin et al[70], 2010
NR3C1 exon 1-F and BDNF promoter IV	↑ DNA methylation within NR3C1 1-F gene (male infants). ↓ DNA methylation within BDNF promoter IV region (female and male infants)	20 female and male infants exposed to prenatal maternal stress and 37 controls. Buccal tissue	Braithwaite et al[71], 2015
NR3C1 exon 1-F	Depressed mood in 2nd trimester associated with ↑ DNA methylation of CpG 2 site (relative to translational start site) at NR3C1 exon 1-F in infants. Depressed mood in 3d trimester associated with ↑ DNA methylation of CpG 2 and CpG 3 site (relative to translational start site) at NR3C1 exon 1-F in infants	46 depressed females (33 treated with SRI and 13 not medicated), 36 controls, and their infants. Blood	Oberlander et al[72], 2008
BDNF, NR3C1, CRHBP, CRHR1, FKBP5 promoter	Hypermethylated BDNF, NR3C1, CRHBP and FKBP5 promoter. mRNA down regulation of BDNF, NR3C1, FKBP5 and CRHBP in MDD-suicidal ideation group	15 females and 9 males with MDD (14 with and 10 without suicidal ideation) and 20 controls (14 females and 6 males). PBMC	Roy et al[73], 2017
BDNF exon I promoter	↑ percentage of methylated reference values	207 female and male MDD patients and 278 controls. PBMC	Carlberg et al[58], 2014
BDNF exon I promoter	↑ at CpG 1, CpG 3 and CpG 5 site, ↓ BDNF serum level	49 female and male MDD patients and 57 controls. Blood	Schröter et al[74], 2020
BDNF exon I and IV promoter	↑ methylation at CpG site 3 of promoter IV	251 female and male MDD patients aged 65 > and 773 controls. Buccal tissue	Januar et al[75], 2015
BDNF exon IX	Changes in DNA methylation; ↑ at CpG site 217, ↓ at CpG site 327, and 362. ↓ BDNF level and mRNA levels	51 MDD patients (35 females and 16 males) and 62 controls (39 females and 23 males). Venous blood	Hsieh et al[60], 2019
BDNF upstream of exon I and IV	Changes in DNA methylation within CpG exon I promoter	20 MDD patients (12 females and 8 males) and 18 controls (8 females and 10 males). Blood	Fuchikami et al[76], 2011
MYO16 and IDE	↑ 5hmc in one CpG position of MYO16 and two CpG positions of IDE in the PFC. ↑ gene expression of MYO16. ↓ gene expression of IDE	19 depressed male suicide victims and 19 controls. Brain tissue (PFC; inferior frontal gyrus)	Gross et al[77], 2017
GABAA receptor α1 subunit promoter	↑ DNA methylation of the CpG 2 and CpG 4 site (500 bp from transcriptional start site). ↑ DNMT-3B expression in FPC. ↓ expression of DNMT1 mRNA and ↑ expression of DNMT3b mRNA in FPC. ↓ expression of DNMT3b and DNMT1 mRNA in AMG	10 male suicide victims and 10 controls. Brain tissue (FPC, AMG)	Poulter et al[78], 2008
SLC6A4 promoter	↑ mean methylation level	28 MDD patients (20 females and 8 males) and 29 controls (21 females and 8 males). Blood	Iga et al[79], 2016
NR3C1 exon 1 promoter	↑ methylation at CpG 30 and 32 site. ↓ expression of total NR3C1 mRNA and NR3C1-1F mRNA in suicide victims without childhood abuse and control group	12 suicide victims with traumatic childhood experience, 12 suicide victims without traumatic childhood experience, and 12 controls. Brain tissue (HPC)	McGowan et al[80], 2009

↓: Decreased expression; ↑: Increased expression; AMG: Amygdala; BDNF: Brain derived neurotrophic factor; bp: Base pair; CpG: Cytosine-phosphate-guanine; CRHBP: Corticotropin releasing hormone binding protein; CRHR1: Corticotropin releasing hormone receptor 1; DNMT3B: DNA methyltransferase 3; FKBP5: FK506 binding protein 5; FPC: Frontopolar cortex; GABA_A: γ-aminobutyric acid; H3K14ac: Acetylation of lysine 14 on histone 3; HDAC2: Histone deacetylase 2; HPC: Hippocampus; IDE: Insulin-degrading enzyme; MDD: Major depressive disorder; MAOA: Monoamine oxidase A; mRNA: Messenger RNA; MYO16: Myoxin XVI; NGFI-A: Nerve growth factor-induced protein A; NR3C1: Nuclear receptor subfamily 3 group C member 1; PFC: Prefrontal cortex; PBMC: Peripheral blood mononuclear cells; SLC6A4: Solute carrier family 6 member 4; SRI: Serotonin reuptake inhibitor antidepressant; UTR: Untranslated region; 5hmc: 5-hydroxymethylcytosine.

DNA methylation studies (Table 1 and Table 4) were performed on blood, buccal swabs, or brain tissue of humans and brain tissue of animal models. As we can see from Table 1, there are a lot of studies investigating DNA methylation in the BDNF gene (different parts of the BDNF gene were tested; exon I, IV, IX, promoter region, whole gene). Most studies showed elevated DNA methylation in the BDNF gene in depressed patients. However, a few studies showed that DNA methylation is decreased. The main conclusion is that alteration in BDNF methylation is associated with a depressive state.

The gene NR3C1 is included in many studies of early life adversities (childhood abuse, parental loss, exposure to maternal depression during pregnancy and after birth). Results show an association between increased methylation of the exon 1-F of the NR3C1 gene, decreased total NR3C1 mRNA, and early life adversities[35]. NR3C1 encodes for the glucocorticoid receptor and is responsible for the effects of cortisol on peripheral tissues. It is self-regulated by a negative feedback loop within the HPA axis[36]. The glucocorticoid receptor can work as a transcription factor that binds to glucocorticoid receptor elements in the promoters of glucocorticoid responsive genes or as a regulator of other transcription factors[37].

In terms of the histone modification data presented in Table 2 and Table 4, H3K27me and H3K14ac are the most studied. The majority of the studies are carried out on animal models and a few on postmortem brain tissue. Studies include information of whole tissue histone modifications and not of single genes. From studies on animal models (Table 4), we can see that the histone tail modifications change over time and are different regarding tissue type.

Table 2 Histone tail modifications studies on depressed suicide victims.

Gene (region)/histone tail modification	Alteration	Subjects and collected tissue	Ref.
BDNF, H3K9/14ac, H3K27me2	↓ H3K9/14ac, ↑ HDAC2, ↑ HDAC3, ↑ H3K27me2, ↓ BDNF in HPC and NAc. ↑ Sin3a in HPC	14 suicide victims (5 females and 9 males) without psychiatric diagnosis and 8 controls (3 females and 5 males). Brain tissue (HPC, NAc, and FCx; BA10)	Misztak et al[53], 2020
H3K4me3	↑ In H3K4me3 at promoter of SYN2. ↑ expression SYN2b; no changes in SYN2a expression	7 females and 11 males with MDD suicide victims and 14 controls (3 females and 12 males). Brain tissue (PFC; BA10)	Cruceanu et al[81], 2013
H3K14ac	↑ H3K14ac. ↓ HDAC2 mRNA expression	8 depressed females and males. Brain tissue (NAc)	Covington et al[11], 2009

↓: Decreased expression; ↑: Increased expression; BA10: Brodmann area 10; BDNF: Brain derived neurotrophic factor; FCx: Frontal cortex; H3K14ac: Acetylation of lysine 14 on histone 3; H3K9/14ac: Acetylation of lysine 9/14 on histone 3; H3K27me2: Dimethylation of lysine 27 on histone 3; H3K4me3: Trimethylation of lysine 4 on histone 3; HDAC2: Histone deacetylase 2; HDAC3: Histone deacetylase 3; HPC: Hippocampus; MDD: Major depressive disorder; mRNA: Messenger RNA; NAc: Nucleus accumbens; Sin3a: SIN3 transcription regulator family member A; PFC: Prefrontal cortex; SYN2: Synapsin II; SYN2b: Synapsin IIb; SYN2a: Synapsin IIa.

Many studies in the last 15 years took into consideration miRNAs as important contributors either to the depressive state or as a biomarker of the depressive state. Studies examining humans (Table 3) are in correlation with studies performed on rodents (Table 4). For example, miR-218 and miR-511 are both downregulated in the prefrontal cortex of depressed subjects who died by suicide and in rodent models (mice or rat). On the other hand, miR-16 and miR-376b were oppositely regulated in humans vs animal models. This might be due to different tissues tested. There are several more miRNAs regulated in the same direction in human vs animal (rodent) models[38]. Upregulation of miR-139-5p is seen in blood-derived exosomes from MDD patients and in brain tissue from chronically depressed mice. Upregulation of miR-323-3p is seen in lateral habenula and Brodmann area 24 in depressed subjects. Consistently, there is also upregulation of miR-323-3p in the brains of rats exposed to prenatal stress. MiR-155 is downregulated in peripheral blood mononuclear cells of depressed subjects and serum of mice exposed to restraint stress. Furthermore, blood-derived exosomes with increased levels of miR-139-5p collected from depressed subjects, evoked depressive-like behavior when administered intravenously in mice[38].

Table 3 MicroRNA expression studies on depressed suicide victims.

miRNAs	Alteration	Subjects and collected tissue	Ref.
miR-218	↓ miR-218 and ↑ DCC in PFC	11 male suicide victims with MDD and 12 male controls. Brain tissue (PFC; BA44)	Torres-Berrío et al[82], 2017
↓ miR-142-5p, miR-137, miR-489, miR-148b, miR-101, miR-324-5p, miR-301a, miR-146a, miR-335, miR-494, miR-20b, miR-376a*, miR-190, miR-155, miR-660, miR-130a, miR-27a, miR-497, miR-10a, miR-20a, miR-142-3p. ↓ by 30% or more: miR-211, miR-511, miR-424, miR-369-3p, miR-597, miR-496, miR-517c, miR-184, miR-34a, miR-34b-5p, miR-24-1*, miR-594, miR-34c-5p, miR-17*, miR-545, miR-565	Globally ↓ miRNAs expression by 17% on average in depressed subjects. miR-148b targets DNMT3B, protein level was upregulated in depressed subjects. miR-34a targets BCL2, protein level was downregulated in depressed subjects	18 suicide victims (2 females and 16 males) with depression and 17 male control subjects. Brain tissue (PFC; BA9)	Smalheiser et al[83], 2012
miR-1202	↓ miR-1202, and ↑ GRM4 mRNA expression in BA44	25 suicide victims (2 females and 23 males) with MDD and 29 control subjects (4 females and 25 males). Brain tissue (PFC; BA44). 32 subjects with MDD (24 females and 10 males) and 18 control subjects (8 females and 10 males). Blood	Lopez et al[84], 2014
miR-30e	↑ miR-30e, ↓ ZDHHC21 protein	16 suicide victims (7 females and 9 males) with MDD and 16 controls (6 females and 10 males). Brain tissue (PFC; BA9)	Gorinski et al[85], 2019
miR-19a-3p	↑ miR-19a-3p (might be involved in the modulation of TNF-α signaling)	12 depressed patients with severe suicidal ideation, 12 control subjects. PBMC	Wang et al[86], 2018
More than 10 miRNAs	↑ miR-17-5p, miR-20b-5p, miR-106a-5p, miR-330-3p, miR-541-3p, miR-582-5p, miR-890, miR-99b-3p, miR-550-5p, miR-1179. ↓ miR-409-5p, let-7g-3p, miR-1197	9 depressed suicide victims (3 females and 6 males) and 11 control subjects (2 females and 9 males). Brain tissue (locus coeruleus)	Roy et al[37], 2017
miR-326	↓ miR-326, ↑ UCN1	5 male suicide victims with MDD and 8 male controls. Edinger-Westphal nucleus	Aschrafi et al[87], 2016
10 miRNAs tested	↑ miR-34c-5p, miR-139-5p, miR-195, miR-320c. ↓ SAT1 and SMOX mRNA	15 male suicide victims with MDD and 16 male control subjects. Brain tissue (BA44)	Lopez et al[88], 2014
miR-204-5p, miR-320b, miR-323a-3p, miR-331-3p	↑ miR-204-5p, miR-320b, miR-323a-3p, miR-331-3p in ACC and lateral habenula. miR-323a-3p influences the expression of ERBB4. Decreased expression in ACC and lateral habenula	39 suicide victims with MDD (13 females and 26 males) and 41 control subjects (10 females and 31 males) for ACC region. 24 suicide victims with MDD (10 females and 14 males), 13 control subjects (5 females and 8 males) for lateral habenula. Brain tissue (ACC and lateral habenula)	Fiori et al[89], 2021
171 miRNA differently expressed	↑ 117 miRNAs. ↓ 54 miRNAs	22 (10 females and 12 males) MDD subjects (10 died by suicide, 12 died from cause other than suicide) and 25 control subjects (10 females and 15 males). Brain tissue (ACC)	Yoshino et al[90], 2020
miR-128-3p	↑ miR-128-3p. ↓ WNT5B, DVL1 and LEF1	20 MDD (10 females and 10 males) subjects and 22 control subjects (9 females and 13 males). Brain tissue (AMG)	Roy et al[91], 2020
miR-16	↓ miR-16	36 MDD (21 females and 15 males) subjects and 30 controls (17 females and 13 males). CSF	Song et al[92], 2015

↓: Decreased expression; ↑: Increased expression; ACC: Dorsal anterior cingulate cortex; AMG: Amygdala; BA44: Brodmann area 44; BA9: Brodmann area 9; BCL2: B-cell lymphoma 2; CSF: Cerebrospinal fluid; DCC: Developmental netrin-1 guidance cue receptor; DNMT3B: Gene coding for DNA methyltransferase 3; DVL1: Dishevelled segment polarity 1; GRM4: Gene coding for metabotropic glutamate receptor 4; LEF1: Lymphoid enhancer binding factor 1; MDD: Major depressive disorder; miR: MicroRNA; mRNA: Messenger RNA; PBMC: Peripheral blood mononuclear cells; PFC: Prefrontal cortex; SAT1: Gene coding for spermidine/spermine N1 -acetyltransferase 1; SMOX: Gene coding for spermine oxidase; TNFα: Tumor necrosis factor; UCN1: Urocortin; WNT5B: Wingless-related integration site, member 5B.

Table 4 Epigenetic (DNA methylation, histone tail modifications, and microRNAs) studies on animal models of depressive disorder.

Epigenetic modification	Gene (region)/histone tail modification/miRNA	Alteration	Organism and collected tissue	Ref.
DNA methylation	Crf promoter of exon 1 and intronic region between exon 1 and exon 2 (relative to exon 1 start site)	Overall ↑ DNA methylation, and specific ↑ in CpG –147 and CpG –101 site of the Crf gene in stressed female rats in the PVN. No changes in male rats. ↓ DNA methylation in CpG –15 (male and female rats), ↓ DNA methylation in CpG –226, CpG –55 and ↑ in CpG +485 and CpG +494 (male rats) and ↓ DNA methylation in CpG –95 site (female rats) in BNST. ↑ DNA methylation in CpG –232 and CpG –226 (male rats), ↓ CpG –226 and CpG +535 (female) in the CeA	Male and female Wistar-R Amsterdam rats; sacrificed 2 h after stress. Brain tissue (PVN, BNST, CeA)	Sterrenburg et al[93], 2011
DNA methylation	Crf promoter (relative to exon 1 start site)	Chronic social stress induced ↑ DNA methylation in Crf promoter region at CpG site –226 and ↓ DNA methylation level in intronic region of the gene Crf in the PVN. Long term effect of social defeat in mice susceptible to social defeat: ↑ in Crf mRNA levels in PVN and ↓ DNA methylation level at CpG –226, –101, –95, and –79	Chronically stressed adult mice C57BL/6. Brain tissue (PVN)	Elliott et al[94], 2010
DNA methylation and histone tail modification	Gdnf	↑ DNA methylation at CpG site 2. ↓ H3ac in NAc of BALB mice and C57BL/6 mice. C57BL/6 mice had higher H3ac and higher Gdnf expression	BALB/c mice with maladaptive response to stressful stimuli and stress resilient strain C57BL/6. Brain tissue (NAc)	Uchida et al[95], 2011
Histone tail modification	H3K14ac	↓ H3K14ac 1 h after final stress. ↑ H3K14ac 24 h and 10 d after final stress. ↓ Hdac2 mRNA expression 24 h and 15 d after final stress in NAc	Chronically social defeated adult male mice C57BL/6J. Brain tissue (NAc).	Covington et al[11], 2009
Histone tail modification	H3K14ac	H3K14ac ↑ after 24 h and ↓ at longer time in HPC. H3K14ac ↑ after 1 h and 24 h, no changes 10 d and longer in AMG	Chronically social defeated adult male mice C57/BL6J. Brain tissue (HPC and AMG)	Covington et al[96], 2011
Histone tail modification	Bdnf exon IV, H3ac, H4ac	↓ exon IV Bdnf mRNA. ↓ H3ac and H4ac. ↑ MeCP2 levels. ↑ Hdac mRNA	Rats (early life adversity induced by maternal separation). Brain tissue (HPC)	Seo et al[97], 2016
Histone tail modification	Bdnf III and IV promoter, H3K27me2	↑ H3K27me2 at promoter Bdnf III and IV. ↓ total Bdnf mRNA. No change at H3K9me2	Chronic social defeat stress mice. Brain tissue (HPC)	Tsankova et al[62], 2006
Histone tail modification	H3K9me2	↑ H3K9me2 in HPC and mPFC. ↓ Bdnf expression in HPC and mPFC	Wistar rats exposed to maternal separation and chronic unpredicted mild stress. Brain tissue (HPC and mPFC)	Jiang et al[98], 2021
Histone tail modification	H3K4me3, H3K9me3, H3K27me3	Acute restrain stress: ↑ in H3K9me3 in CA1 and DG; no changes in CA3; ↓ in H3K27me3 in DG and CA1; not significantly altered in CA3. No significant changes for H3K4me3. Subchronic 7-d restraint stress: The basal level of H3K9me3 on day 7 increased in DG, CA1 and CA3. ↓ in H3K9me3 in CA1, CA3 and DG. ↓ in H3K27me3 in DG	Adult male Sprague–Dawley rats (acute stress/7 d restraint stress). Brain tissue (HPC parts: DG, CA1, CA3)	Hunter et al[99], 2009
miRNA	miR Let-7a-1, miR-9, miR-25a/b	↑ miR Let-7a-1, miR-9, miR-25a/b after acute stress in FCx. No changes in HPC	Male CD1 mice with induced acute or repeated stress. Brain tissue (FCx and HPC)	Rinaldi et al[100], 2010
miRNA	miR-218	↓ miR-218 and ↑ DCC in PFC	Chronically social defeated adult male mice C57BL/6. Brain tissue (mPFC)	Torres-Berrío et al[82], 2017
miRNA	miR-16	↑ miR-16. ↓ Bdnf mRNA	Sprague-Dawley rats exposed to maternal deprivation. Brain tissue (HPC)	Bai et al[101], 2012
miRNA	342 miRNAs differently expressed (response to gestational stress) and 336 miRNAs differently expressed in offspring (response to prenatal stress)	↑ 147 miRNAs and ↓ 195 miRNAs in FCx of female rats. ↑ 205 miRNAs and ↓ 131 miRNAs in offspring	Stress induced through pregnant female Long-Evans rats. Offspring (decapitated 1 to 5 h after parturition). Brain tissue (FCx)	Zucchi et al[102], 2013
miRNA	AMG: 10 miRNAs under acute stress and 28 after chronic stress; HPC CA1: 16 after acute stress and 22 after chronic stress	The overlap: ↑ miR Let-7a-1 in AMG affected by acute and chronic stress. ↑ miR-376b and miR-208, ↓ miR-9 in HPC by acute and chronic stress. Other changes are unique to acute/chronic stress or brain region analyzed	Adult male rats with induced acute or chronic stress. Brain tissue (AMG, HPC CA1 region)	Meerson et al[103], 2010
miRNA	miR-124a, miR-18a, miR-511	↑ miR-124a, miR-18a in PFC and HPC persistently. ↓ miR-511 in PFC (in adult rats experienced CUMS)	Adolescent male Wistar rats were stressed with CUMS. Brain tissue (PFC and HPC)	Xu et al[104], 2019

↓: Decreased expression; ↑: Increased expression; AMG: Amygdala; Bdnf, brain derived neurotrophic factor; BNST: Bed nucleus of the stria terminalis; CeA: Central amygdala; CpG: Cytosine-phosphate-guanine; Crf: Corticotropin releasing factor; CUMS: Chronic unpredictable mild stress; DCC: Gene coding developmental netrin-1 guidance cue receptor; DG: Dentate gyrus; FCx: Frontal cortex; Gdnf: Glial cell-derived neurotrophic factor; HDAC: Histone deacetylase; H3ac: Acetylation of histone 3; H4ac: Acetylation of histone 4; H3K14ac: Acetylation of lysine 14 on histone 3; H3K9me2: Dimethylation of lysine 9 on histone 3; H3K9me3: Trimethylation of lysine 9 on histone 3; H3K27me2: Dimethylation of lysine 27 on histone 3; H3K27me3: Trimethylation of lysine 27 on histone 3; H3K4me3: Trimethylation of lysine 4 on histone 3; Hdac2: Histone deacetylase 2; HPC: Hippocampus; HPC CA1: Hippocampal CA1 region; HPC CA3: Hippocampal CA3 region; MeCP2: Methyl CpG binding protein 2; mPFC: Medial prefrontal cortex; miR: Micro RNA; miRNA: Micro RNA; mRNA: Messenger RNA; NAc: Nucleus accumbens; PFC: Prefrontal cortex; PVN: Hypothalamic paraventricular nucleus.

However, from all the data currently available, it is hard to pinpoint particular miRNAs that could be used as biomarkers for depressive disorder. Studies presented in Table 4 show lack of overlap between studies; there are several different tissues used, and the number of miRNAs interrogated vary from whole RNome studies to single miRNA studies. Although many limitations exist in the miRNA research, current results are promising enough to persist with the search for miRNAs or even miRNA networks that could serve as biomarkers.

Due to variation in study design, comparisons between the obtained results are limited. In particular, criteria for subject inclusion are very diverse (inclusion of one/two sexes, age, ethnic background, and so on), and studies are frequently underpowered. In addition, the background of the depressive state is not the same for all depressed patients. Some studies analyze the consequences of early life adversity, others include patients with depressive disorder at older age or depressed patients without a known cause. When working with animal models the study design is more standardized and controlled, while the trigger of depressed state is selected based on the interest of the study.

POSSIBLE TREATMENTS OF DEPRESSIVE DISORDER

There are pharmacological and nonpharmacological (psychotherapy, lifestyle interventions, and neuromodulatory treatment) ways of treating depressive disorder. For pharmacological treatment, there are many different antidepressants available, and they are a cornerstone for treating depressive disorder[39]. The main drug classes of antidepressants are selective serotonin reuptake inhibitors (SSRIs), selective serotonin and norepinephrine reuptake inhibitors, norepinephrine and dopamine reuptake inhibitors, noradrenergic and specific serotonergic agents, tricyclic antidepressants, MAO inhibitors, and melatonin modulators (agomelatine)[40]. However, there is no universally effective treatment for all depressed patients[39].

People suffering from depressive disorder can recover in a year or not recover in more than 20 years. Furthermore, depressive episodes recur in almost half of recovered patients[5]. Even though there are many different antidepressants available and many different treatment options, 34%–46% of MDD patients still do not respond effectively to one or more antidepressant treatments (i.e. fail to achieve remission). That is why there is still a great need for new antidepressants for curing treatment-resistant depression[41]. Among novel drugs, ketamine and eskatemine are being extensively used. Also, the HDAC inhibitors (HDACis) are being tested on animal models as one possibility of treatment.

Selective serotonin inhibitors

SSRIs are the most commonly prescribed antidepressants and are used as the first treatment step for depressive disorder. Serotonin or 5-hydroxytryptamine (5-HT) is a monoamine neurotransmitter that modulates mood, reward, learning, and memory. Deficiency in serotonin release is not associated with serotonin biosynthesis. The serotonin deficit is more likely due to less serotonin neuron firing and less serotonin release. However, SSRIs block the reabsorption of serotonin into presynaptic neuron cell and with that improve message transmission between cells[40].

Fluoxetine was the first SSRI to be developed and is the most used antidepressant for children and adolescents. Many different SSRIs have now been developed that vary in binding affinity; some are more specific to serotonin than others. It became clear that using the available antidepressants targeting specific monoamines also have side effects. Those side effects come from neurotransmitters binding to different receptors. For example, when serotonin binds to the 5HT1A receptor, there is an antidepressant and anxiolytic effect; when it binds to 5HT2A/C receptor, there is an effect on sexual dysfunction. Multimodal antidepressants directly target specific serotonin receptors and inhibit reuptake of serotonin. Vilazodone is an example of a multimodal antidepressant, which targets a specific receptor (5HT1A). Still, vilazodone is not as superior as it was expected to be compared to other antidepressants[40,42]. Vortioxetine is more promising since it shows superior efficacy compared to the other antidepressants in trials. Vortioxetine is an agonist of 5HT1A, (partial) antagonist of other receptors, and a potent serotonin reuptake inhibitor. Besides the antidepressant effect, it also improves cognitive function[40,42].

Ketamine

Novel treatments that target outside of the monoaminergic system are ketamine [targeting the glutamate system through N-methyl-aspartate (NMDA) receptor antagonism] and agomelatin (a melatonin receptor agonist)[40]. Agomelatin is a melatonin agonist and a selective serotonin antagonist. For antidepressant effect, both actions are necessary. Agomelatin showed good antidepressant effect for people with seasonal affective disorder[43].

Ketamine is used in many clinical studies for treatment-resistant patients who fail to respond to SSRIs. Ketamine showed good results, with a response rate between 40% and 90%[43]. Intravenous infusion of ketamine produces a rapid and prolonged effect within a few hours of administration. It is accompanied by psychotomimetic effects, which subside within 2 h. The effect of a single intravenous insertion lasts 2–14 d, and it has an anti-suicide effect[41]. Ketamine is restricted for routine clinical use due to its side effects: Dissociative effects, changes in sensory perception, intravenous administration, and risk of abuse[44].

Ketamine is a mixture of two enantiomers, S-ketamine and R-ketamine. In the past few years, esketamine (S-ketamine) has been studied as a better option than ketamine because of its easier administration. Esketamine can be inserted intranasally and is therefore easier for at home administration. Recently, researchers investigated R-ketamine. Preclinical and clinical studies on intravenously infused R-ketamine elicit a fast and sustained antidepressant state, without psychotic symptoms[45].

Ketamine’s action: Ketamine affects the glutamate system. Glutamate is an excitatory neurotransmitter and is involved in neurodevelopment, neurocognitive (memory learning) function, and neuroplasticity (neurogenesis, neuronal growth and remodeling, maintenance, and synaptic plasticity). Dysregulation of neuroplasticity can contribute to MDD and other neuropsychiatric conditions. The majority of neurons use glutamate as a neurotransmitter. Two types of glutamate receptors (ionotropic or metabotropic glutamate receptors) are categorized into four major classes: α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid receptors, NMDA receptors (NMDAR), kainate receptors, and metabotropic glutamate receptors[46]. NMDARs are located at the postsynaptic and presynaptic side of glutamatergic synapses in the CNS[47]. In postmortem brains of MDD patients, many studies have revealed alteration in NMDAR. Several changes were discovered, such as NMDAR dysfunction (reduced glutamate recognition and allosteric regulation) and altered expression of NMDAR subunits. The latter might be manifested by altered glutamatergic input and abnormal glutamate neurotransmission[46].

There are several mechanisms of ketamine action, which may act complementarily. Ketamine can bind to NMDAR on presynaptic or postsynaptic glutamatergic neuron and on GABAergic interneurons. Binding leads to blockade and inhibition of NMDAR. For the antidepressant effects of ketamine, cascades of actions happen: γ-aminobutyric acid decrease, glutamate release, α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid receptors activation, BDNF release, tropomyosin receptor kinase B activation, and mammalian target of rapamycin complex 1 activation. The result is an acute change in synaptic plasticity and sustained strengthening of excitatory synapses[44]. The process of synaptogenesis is activated and further probably affects cognition, mood, and thought patterns[48].

HDACis

Decreased acetylation is associated with a depressive state and because of that, HDACs (as erasers of acetylation) might become a novel treatment target[10]. HDACs, “erasers” of histone acetylation, are classified into two categories: The zinc-dependent and nicotinamide-adenine-dinucleotide–dependent sirtuins (Table 5)[49].

Table 5 Histone deacetylase classification and localization.

HDAC category	HDAC class	HDAC type	Localization
Zinc-dependent HDACs	Class I	HDACs 1, 2, 3, 8	Localized in nucleus
	Class II	HDACs 4, 5, 7, 9, 10	Pass between nucleus and cytoplasm
		HDAC6	Localized in the cytoplasm
	Class IV	HDAC11
NAD-dependent SIRTs	Class III	SIRTs 1, 2, 6 and 7	Localized in the nucleus
		SIRTs 3, 4 and 5	Localized in the mitochondria

HDACs: Histone deacetylases; NAD-dependent sirtuins: Nicotinamide-adenine-dinucleotide–dependent sirtuins; SIRTs: Sirtuins.

HDACs I, II, and IV are expressed in the brain, primarily in neurons. Class I and II regulate histone deacetylation at most genes, and class III deacetylates nuclear and cytoplasmic substrates beside histones[50]. The balance between histone acetyltransferases and HDAC activity determines the (de)condensation status of the chromatin and gene transcription[10].

HDACis are potent to specific classes of HDACs. The United States Food and Drug Administration has approved a few HDACis [vorinostat (SAHA), belinostat, panobinostat, and romidepsin] for treatment of some types of cancers. Many preclinical studies on mice showed an antidepressant effect of HDACis by reversing the acetylated state. Moreover, HDACis also promote neuronal rewiring and recovery of motor functions after traumatic brain injury. Use in clinical practice is limited due to severe side effects including thrombocytopenia and neutropenia[51].

DEPRESSIVE DISORDER ASSOCIATED GENES AND CLASSICAL ANTIDEPRESSANT DRUGS

How different antidepressants affect depressive symptoms can be measured by a subject’s phenotype (behavior for animals and psychiatric evaluation for humans). Epigenetic alterations might become one of the tools to check how well specific subjects respond to the antidepressant[52].

BDNF and depressive disorder

One of the most studied genes of depressive disorder is BDNF. BDNF is one of the most important neurotrophins. The human BDNF gene contains nine exons (I–IX), each regulated by its own promoter. All the different transcripts are translated into an identical BDNF protein[53]. It is highly expressed in the CNS[54] and plays an important role in proper brain development and functioning, including neuronal proliferation, migration, differentiation, and survival[53]. BDNF binds to p75 neurotrophin receptor (p75NTR) and tropomyosin receptor kinase B[54]. In many studies, exon I and IV showed alteration in expression levels in depressed subjects. Splice variant tropomyosin receptor kinase B.T1 is an astrocytic variant and has gained a lot of interest in the study of the depressive state[10]. Two single nucleotide polymorphisms, Val66Met and BE5.2, of BDNF reduce BDNF release. In addition, studies show significant effects of epigenetic changes on the depressive state[53]. Treatment with SSRIs and HDACi antidepressants increases levels of BDNF in peripheral tissues. If BDNF does not increase early after administration, this predicts non-response to antidepressants[55].

BDNF and antidepressants: Human studies: The studies on DNA methylation and antidepressant effect in general include a rather low number of subjects but several different antidepressants.

Two studies analyzed H3K27me3 modification, and both reported decreased H3K27me3 in patients with MDD. Chen et al[56] performed a study on Caucasians (French Canadian origin, 9 control subjects, 11 MDD subjects without a history of antidepressant use, and 7 MDD subjects who used antidepressants). All MDD subjects died due to suicide. Several different antidepressants were administered: Fluoxetine (n = 1), venlafaxine (n = 2), clomipramine (n = 1), amitriptyline (n = 1), citalopram (n = 1), and doxepin (n = 1). Analysis of the epigenetic modification H3K27me3 in brain tissue from Brodmann area 10 between the control group and the non-medicated MDD group showed no differences. Subjects with a history of antidepressant use showed an increase in BDNF IV expression but not BDNF I, II, and III expression and a decreased level of H3K27me3 at the BDNF IV promoter[56].

Lopez et al[57] investigated 25 MDD patients (13 females and 12 males) whose blood levels of total BDNF and H3K27me3 were measured before antidepressant treatment and after 8 wk of citalopram administration. After treatment, there was an elevation of peripheral BDNF mRNA in patients responsive to antidepressant treatment and a decrease in H3K27me3 level at promoter IV of the BDNF gene[57].

An increase of BDNF DNA methylation level after antidepressant administration was shown in three studies. Carlberg et al[58] (2014) studied BDNF methylation on peripheral blood mononuclear cells of 207 MDD patients and 278 control subjects from Vienna, Austria. From 207 MDD patients, 140 subjects were treated with antidepressant medication and 25 subjects were not. There was an alteration in DNA methylation at the BDNF exon I promoter. After antidepressant administration, there was an increase in methylation in MDD patients compared with patients without antidepressant medication and healthy controls[58].

D’Addario et al[59] reported that there was an increase in DNA methylation at the BDNF promoter in 41 MDD patients with stable pharmacological treatment in comparison to 44 healthy control subjects. In addition, there was a significant reduction in expressed BDNF from peripheral blood mononuclear cells in MDD patients than in the control group. Patients who took only SSRIs or selective serotonin and norepinephrine reuptake inhibitors had a higher methylation level of the BDNF promoter than patients who received antidepressants and mood stabilizers[59].

In a study by Wang et al[16], 85 Chinese Han patients with MDD (females and males) were treated with escitalopram. Blood samples were tested for DNA methylation in the BDNF region. DNA methylation before treatment was significantly lower than after 8 wk of treatment. A difference was seen between remitted and non-remitted patients. Patients with remission had higher DNA methylation than non-remitters[16].

Two studies included analysis of patients who responded and those who did not. In both, higher methylation level was an important contributor to treatment response. Hsieh et al[60] included 39 patients with MDD (females and males) and 62 healthy controls (females and males). Higher methylation levels were detected at CpG site 217 and lower methylation level at CpG sites 327 and 362 in the BDNF exon IX promoter in MDD patients compared to controls. After drug administration (SSRIs; fluoxetine, paroxetine, and escitalopram), 25 patients who responded to SSRIs had a higher methylation level at CpG sites 24 and 324 than patients who did not respond (n = 11). Methylation analysis results also showed consistent results of BDNF protein level and mRNA level in peripheral blood[60].

A study by Tadić et al[52] (2014) included 46 MDD patients (females and males) with different monoaminergic antidepressants prescribed: Escitalopram (n = 5), fluoxetine (n = 2), sertraline (n = 6), venlafaxine (n = 19), duloxetine (n = 2), mirtazapine (n = 6), amitriptyline (n = 1), clomipramine (n = 3), trimipramine (n = 1), or tranylcypromine (n = 1). Although different antidepressants were used, the main observation of the study was the response or non-response to the antidepressant treatment. From 13 CpG sites checked for methylation status on blood samples within the BDNF IV promoter, one stood out; antidepressant non-responders had lower methylation at CpG position –87 (relative to the first nucleotide of exon IV). There were no other DNA methylation changes after treatment[52].

Animal studies: In animal models, it has been shown that histone tail modifications significantly affect gene expression and that they are changed after antidepressant administration.

In the study by Park et al[34], male Sprague-Dawley rat pups were separated from mothers during early life. Maternal separation evoked a decrease of exon I mRNA Bdnf, H3 acetylation (ac) levels and an increase in Dnmt1 and Dnmt3a mRNA level in the hippocampus. After 3 wk of escitalopram administration in adult rats subjected to maternal separation, the result was an increase in BDNF protein, exon I mRNA, levels of H3ac, and a decrease in Mecp2, Dnmt1, and Dnmt3a mRNA levels[34].

Xu et al[61] showed that mice stressed in the adolescent period show epigenetic changes also in adult life. Stress in tested male C57BL/6J mice were induced by confrontation of aggressor mice CD1. The expression level of total Bdnf and Bdnf IV mRNA were decreased in the medial prefrontal cortex (the same results were observed in the hippocampus). Bdnf I and VI mRNA levels changed over time in the medial prefrontal cortex. Adult mice had upregulated H3K9me2 in a region downstream of the promoter of the gene Bdnf IV, but there were no differences in H3K4me3, H3K9ac, and H3K4ac. Tranylcypromine administration reversed this change and increased levels of H3K4me3. Tranylcypromine is a non-selective MAO inhibitors[61].

Tsankova et al[62] showed decreased expression of Bdnf III and IV, which manifested in the total level of Bdnf mRNA in the hippocampus in chronically defeated BL6/C57 mice. Changes in Bdnf III and IV expression persisted a month after cessation of the chronic defeat stress. On the promoter of Bdnf III and Bdnf IV there was an increase of H3K27me2 but not H3K9me2. Chronic imipramine (a tricyclic antidepressants) administration reversed changes of Bdnf expression but did not reverse H3K27me2 to the base level. After chronic social defeat stress and imipramine administration, H3 was hyperacetylated (H3K9/14ac) at the promoter Bdnf III and IV, which affected mRNA expression. Furthermore, H3K4me2 was similarly enriched in the Bdnf III promoter and correlated with transcriptional activation. There were no changes in H4ac. There was a decrease in Hdac5 mRNA level but only on chronically stressed mice treated with chronic imipramine. Acute imipramine did not influence Hdac level[62].

Solute carrier family 6 member 4 and depressive disorder

Solute carrier family 6 member 4 (SLC6A4) is a gene that codes for serotonin transporter. The protein’s name comes from the name of the monoamine neurotransmitter serotonin (5-HT) that binds to it. The gene SLC6A4 was associated with the protein later. Serotonin transporter is an integral membrane protein that transports serotonin from synapse to presynaptic neurons. Besides involvement in regulation of the serotonergic system, SLC6A4 also acts as an important element of stress susceptibility. Serotonin transporter linked promoter region polymorphism at gene SLC6A4 has 2 variants, a short allele and a long allele. The short allele results in lower gene transcription and is therefore associated with a depressive state[63]. In addition, there are also several epigenetic studies explaining its dysfunction. Some studies have shown how treatment with classical antidepressants affects epigenetic changes of the SLC6A4 gene. Therefore, SLC6A4 is a key target for antidepressant treatment research.

SLC6A4 and antidepressants: Human studies: There is a difference in the response to antidepressants seen when analyzing DNA methylation in SLC6A4 gene. Two studies reported higher methylation status after antidepressant administration and one lower methylation status.

Booij et al[64] included in their study 33 MDD patients (females and males). MDD patients who were taking SSRIs had higher methylation levels at CpG 11 and 12 within the regulatory region upstream of the promoter of the SLC6A4 than patients who did not use antidepressants (n = 36). Research was done on whole blood samples. There was no association between mRNA expression and DNA methylation[64]. In the study of Okada et al[65], peripheral blood was taken from 50 Japanese MDD patients (females and males) before and after antidepressant treatment. Different antidepressants (paroxetine, fluvoxamine, milnacipran) were used in this study. There were no differences in DNA methylation of SLC6A4 exon I promoter between the healthy control group (n = 50) and patients without antidepressant administration. There was a significant increase in methylation at the CpG 3 site after 6 wk of antidepressant treatment[65].

Domschke et al[66] included 61 Caucasian MDD patients who were tested for changes in DNA methylation from blood cells. Administration of escitalopram was evaluated 6 wk after treatment. There was lower average methylation in the transcriptional control region upstream of exon 1A of SLC6A4 gene. The CpG 2 site specifically stood out from these results[66].

CONCLUSION

Depressive disorder is affected by dysregulation of many different genes, each contributing a small effect. All hypotheses of depressive disorder involve a variety of changes that can occur in a depressive state. These are a consequence of gene variations or epigenetic changes that affect DNA transcription and/or mRNA translation resulting in imbalanced protein levels regulating the processes in the CNS. With the development of technologies and new knowledge, epigenetic research has become accessible for investigation in the field of psychiatry. Among candidate genes particular interest was placed on BDNF, NR3C1, and SLC6A4, as their roles in CNS regulation have been identified in association with response to external stress stimuli and mood regulation. Although the research has been fairly extensive, we still cannot identify a reliable biomarker or a set of them, either proteomic or (epi)genetic, to be used in a clinical setting.

However, in many studies scientists discuss the importance of epigenetic factors (DNA methylation and histone modifications) as playing a key role in predicting antidepressant response. The aggregation of subthreshold levels of the epigenetic changes in several different genes might show alterations caused by a depressive state. It appears that to date we have uncovered a few pieces of the jigsaw puzzle but that more studies are needed for understanding this complex disorder. For example, it has been determined that classical antidepressants change the epigenome, and it has been proposed that this effect might be an important contributor to treatment. These results have triggered further investigation of drugs targeting epigenetic modifiers (HDACs, histone methyltransferases). HDACis seem to be promising drugs, but there are no HDACis used for depression treatment.

Further research in clinical settings will be important to determine which epigenetic markers are informative for treatment response prediction and which markers actually change as a response to treatment. Although the field of pharmacoepigenetics is only starting to develop, we can already identify some potential genes that we can expect to become biomarkers with clinical value. With rapid technological advancement, enabling determination of markers from multi-omic data with the use of artificial intelligence and carefully designed studies in the growing field of psychiatry, we could expect to obtain relevant biomarkers that could be used by clinicians as meaningful guidance in addition to clinical interviews in the future. With the development of the field of pharmacoepigenetics, it will be possible to move towards personalized treatments, where combinations of genetic and environmental factors will need to be incorporated in treatment selection.

ACKNOWLEDGEMENTS

The authors would like to thank Dr. John Hancock for critical appraisal and scientific English editing of the manuscript.