Moving pharmacoepigenetics tools for depression toward clinical use

Highlights

• Antidepressant response is associated with multiple epigenetic marks.

• Many limitations exist in the study base of antidepressant pharmacoepigenetics.

• Future studies should focus on overcoming these limitations.

• Integrating multiple predictors into new tools will likely have the greatest utility.

Abstract

Background

Major depressive disorder (MDD) is a leading cause of disability worldwide, and over half of patients do not achieve symptom remission following an initial antidepressant course. Despite evidence implicating a strong genetic basis for the pathophysiology of MDD, there are no adequately validated biomarkers of treatment response routinely used in clinical practice. Pharmacoepigenetics is an emerging field that has the potential to combine both genetic and environmental information into treatment selection and further the goal of precision psychiatry. However, this field is in its infancy compared to the more established pharmacogenetics approaches.

Methods

We prepared a narrative review using literature searches of studies in English pertaining to pharmacoepigenetics and treatment of depressive disorders conducted in PubMed, Google Scholar, PsychINFO, and Ovid Medicine from inception through January 2019. We reviewed studies of DNA methylation and histone modifications in both humans and animal models of depression.

Results

Emerging evidence from human and animal work suggests a key role for epigenetic marks, including DNA methylation and histone modifications, in the prediction of antidepressant response. The challenges of heterogeneity of patient characteristics and loci studied as well as lack of replication that have impacted the field of pharmacogenetics also pose challenges to the development of pharmacoepigenetic tools. Additionally, given the tissue specific nature of epigenetic marks as well as their susceptibility to change in response to environmental factors and aging, pharmacoepigenetic tools face additional challenges to their development.

Limitations

This is a narrative and not systematic review of the literature on the pharmacoepigenetics of antidepressant response. We highlight key studies pertaining to pharmacoepigenetics and treatment of depressive disorders in humans and depressive-like behaviors in animal models, regardless of sample size or methodology. While we discuss DNA methylation and histone modifications, we do not cover microRNAs, which have been reviewed elsewhere recently.

Conclusions

Utilization of genome-wide approaches and reproducible epigenetic assays, careful selection of the tissue assessed, and integration of genetic and clinical information into pharmacoepigenetic tools will improve the likelihood of developing clinically useful tests.

Introduction

Despite a large body of research examining clinical and biological differences among individuals with major depressive disorder (MDD), findings from this work have not yet produced tools to reliably enhance treatment selection. When opting for a medication approach to treating MDD, clinicians’ choices are largely guided by potential side effects, past treatment responses, and clinical characteristics, such as the presence of comorbid anxiety, psychosis, trauma, or substance misuse. However, there is limited replicated evidence showing these characteristics to be robust moderators of antidepressant efficacy (Dunlop, 2015). Evidence-based moderators that some psychiatrists incorporate into antidepressant selection include the presence of melancholic features, which may preferentially respond to tricyclic antidepressants (TCAs) (Perry, 1996), and atypical features, which may respond better to monoamine oxidase inhibitors (MAOIs) than TCAs (Quitkin et al., 1991, Quitkin et al., 1990). Psychotic depression is the only clinical subtype that has strong evidence for a particular prescriptive pathway; that is, the combination of an antidepressant and an antipsychotic (Malhi et al., 2018).

Unguided selection of antidepressants produces response rates of only 50–60% and even lower remission rates for a single treatment course (Papakostas and Fava, 2009, Rush et al., 2006). Failure to achieve remission results in prolonged suffering, greater impairment in psychosocial functioning, and higher levels of health care use. The trial and error approach to treatment selection also suffers from high rates of side effects, with approximately 55% of patients experiencing at least one bothersome side effect from antidepressant treatment (Papakostas, 2008). While successive trial and error treatment trials appear to boost cumulative remission rates to 67% (Rush et al., 2006), the prolonged process to achieve remission leaves patients suffering from illness morbidity and elevates the risk of disengaging from care.

More recent work focusing on biological predictors, including neuroimaging, neurophysiological, neuroendocrine, and genetic measures has identified potential alternative approaches to treatment selection (Busch and Menke, 2019, Fonseka et al., 2018, Olbrich and Arns, 2013, Williams, 2017). The field of pharmacogenetics (PGx) developed with the idea that specific genetic variants can inform decisions about medication choice by helping to predict response to and tolerability of different medications. The potential utility of analyzing common genetic variants in antidepressant response is supported by the finding that 42% of individual variation in medication outcomes derives from genetic factors (Tansey et al., 2013).

Results from candidate gene studies of antidepressant response have been utilized to develop multiple pharmacogenetic-based decision support tools (DSTs), which vary widely in the number and type of genes assessed, included medications, cost, regulation, and method of results delivery. A recent review identified 76 labs in the US that offer PGx testing services (Haga and Kantor, 2018) with 38 DSTs that assess antidepressants (Fabbri et al., 2018). These tools are being marketed directly to patients and clinicians, though current depression treatment guidelines either do not address this type of testing or simply refer to it as an area of future research (Peterson et al., 2017, Zeier et al., 2018). A recent meta-analysis concluded that while there are concerns about the quality of the evidence base, PGx testing does hold promise for improving response and remission rates in MDD, particularly among patients with treatment resistance or intolerability to previous psychotropics (Bousman et al., 2019).

More recently, investigators have begun to examine ways in which epigenetic marks predict antidepressant response as part of the field of pharmacoepigenetics. Epigenetic modifications are changes to DNA structure that do not affect the DNA sequence but mediate alterations in gene expression, which, in turn, can influence protein levels. While some epigenetic marks appear inherited, most can be altered throughout a person's lifetime starting during prenatal development by multiple environmental factors, including exposure to pharmacotherapy (Kanherkar et al., 2014).

Epigenetic factors that have been most studied in the context of antidepressant response include DNA methylation, histone modifications, and the control of gene expression by non-coding RNAs. DNA methylation is the most widely studied and best understood epigenetic modification. It typically involves the addition of a methyl group to a cytosine within a CpG dinucleotide via DNA methyltransferase (DNMT), generating the modified nucleotide 5-methylcytosine (5mC), but less commonly involves adding a methyl group (or other variants of methyl groups) to cytosines within other types of dinucleotides. Generally, the presence of 5mC at gene promoters is associated with decreased gene expression, whereas intragenic methylation can induce gene transcription or silencing (Bonasio et al., 2010, Maunakea et al., 2010). The enzyme DNMT1 preserves DNA methylation patterns during replication, while DNMT3a and DNMT3b lead to de novo methylation of double-stranded DNA (Menke and Binder, 2014).

Histone modification refers to the enzymatic attachment or removal of chemical groups from lysine and arginine residues on histones’ N-terminal tails. Histones are found in nucleosomes, which consist of an octamer of histone proteins (two copies of H2A, H2B, H3, and H4 each) around which DNA is coiled (Sun et al., 2013). Acetylation is the most common histone modification and generally produces an increase in gene expression by inducing the formation of a more loosened and accessible chromatin (‘euchromatin’). N-terminal tails of histones can also be methylated with one, two, or three methyl groups. Methylation of histones can lead to transcriptional activation (H3-lysine (K)4, H3K36) or repression (H3K9, H3K27, H4K20) based on which histone and lysine is being methylated (Lachner et al., 2003).

There are multiple mechanisms by which antidepressants and antidepressant-like compounds have been shown to alter the epigenome. Evidence suggests that the TCAs amitriptyline and imipramine, the selective serotonin reuptake inhibitor (SSRI) paroxetine, and the antidepressant-like compound genipin (a molecule extracted from Gardenia jasminoides Ellis, i.e. cape jasmine) decrease DNA methylation by reducing DNMT1 enzymatic activity both in and ex vivo (Perisic et al., 2010, Ye et al., 2018, Zimmermann et al., 2012). Paroxetine has also been found to alter DNMT1 phosphorylation, which affects the enzyme's activity, in peripheral blood cells obtained from depressed patients (Gassen et al., 2015). Evidence suggests that the SSRI fluoxetine indirectly alters the epigenetic landscape through chronic elevation of serotonin, resulting in increased expression of methyl-CpG-binding proteins and induction of histone deacetylase (HDAC), an enzyme that removes acetyl groups from histones and represses gene transcription (Csoka and Szyf, 2009). Furthermore, the serotonin-norepinephrine reuptake inhibitor (SNRI) venlafaxine (Qiao et al., 2019) and imipramine (Tsankova et al., 2006) selectively down-regulate HDAC5 in rodent models of depression. There is also evidence that imipramine decreases activity of HDAC3 and HDAC4 in fetal mouse neocortical neurons (Nghia et al., 2015). Furthermore, multiple HDAC inhibitors have antidepressant effects in animal models, including valproic acid (Fuchikami et al., 2016).

Although the field of pharmacoepigenetics is quite young compared to the more established pharmacogenetics approach, an increasing body of preclinical and clinical work indicates that epigenetic marks may be useful for the prediction of treatment response in patients with MDD. Here, we review the current state of the field of pharmacoepigenetics of oral antidepressant response in human and animal models of depression with a focus on DNA methylation and histone modifications. We will not discuss non-coding RNAs, as they have recently been reviewed elsewhere in relation to antidepressant response (Belzeaux et al., 2018, Fiori et al., 2018). Given the issue of high tissue specificity in DNA methylation patterns (Ziller et al., 2013) and the fact that most DNA methylation studies in humans use blood, we used the freely available web application Blood-Brain Epigenetic Concordance, BECon (Edgar et al., 2017), to obtain a sense of the concordance of CpGs between blood and brain in genes for which we found two or more studies, including BDNF, SLC6A4, and HTR1B. We then discuss key issues with the current antidepressant pharmacoepigenetics literature and provide suggestions for future studies to aid in the development of clinically useful pharmacoepigenetic DSTs.