DNA methylation and clinical response to antidepressant medication in major depressive disorder: A review and recommendations

Integrative Genetic Variation, DNA Methylation, and Gene Expression Analysis of Escitalopram and Aripiprazole Treatment Outcomes in Depression: A CAN-BIND-1 Study

INTRODUCTION

Little is known about the interplay between genetics and epigenetics on antidepressant treatment (1) response and remission, (2) side effects, and (3) serum levels. This study explored the relationship among single nucleotide polymorphisms (SNPs), DNA methylation (DNAm), and mRNA levels of four pharmacokinetic genes, CYP2C19, CYP2D6, CYP3A4, and ABCB1, and its effect on these outcomes.

METHODS

The Canadian Biomarker Integration Network for Depression-1 dataset consisted of 177 individuals with major depressive disorder treated for 8 weeks with escitalopram (ESC) followed by 8 weeks with ESC monotherapy or augmentation with aripiprazole. DNAm quantitative trait loci (mQTL), identified by SNP-CpG associations between 20 SNPs and 60 CpG sites in whole blood, were tested for associations with our outcomes, followed by causal inference tests (CITs) to identify methylation-mediated genetic effects.

RESULTS

Eleven cis-SNP-CpG pairs (q<0.05) constituting four unique SNPs were identified. Although no significant associations were observed between mQTLs and response/remission, CYP2C19 rs4244285 was associated with treatment-related weight gain (q=0.027) and serum concentrations of ESCadj (q<0.001). Between weeks 2-4, 6.7% and 14.9% of those with *1/*1 (normal metabolizers) and *1/*2 (intermediate metabolizers) genotypes, respectively, reported ≥2 lbs of weight gain. In contrast, the *2/*2 genotype (poor metabolizers) did not report weight gain during this period and demonstrated the highest ESCadj concentrations. CITs did not indicate that these effects were epigenetically mediated.

DISCUSSION

These results elucidate functional mechanisms underlying the established associations between CYP2C19 rs4244285 and ESC pharmacokinetics. This mQTL SNP as a marker for antidepressant-related weight gain needs to be further explored.

Brain-Derived Neurotrophic Factor (BDNF) as a Predictor of Treatment Response in Major Depressive Disorder (MDD): A Systematic Review

Brain-derived neurotrophic factor (BDNF) has been studied as a biomarker of major depressive disorder (MDD). Besides diagnostic biomarkers, clinically useful biomarkers can inform response to treatment. We aimed to review all studies that sought to relate BDNF baseline levels, or BDNF polymorphisms, with response to treatment in MDD. In order to achieve this, we performed a systematic review of studies that explored the relation of BDNF with both pharmacological and non-pharmacological treatment. Finally, we reviewed the evidence that relates peripheral levels of BDNF and BDNF polymorphisms with the development and management of treatment-resistant depression.

Pilot study of genome-wide DNA methylation and gene expression for treatment response to escitalopram in panic disorder

BACKGROUND

Antidepressants, particularly selective serotonin reuptake inhibitors, are currently considered the first-line treatment for panic disorder (PD). However, little is known about the relationship between the biomarkers that may predict better treatment.

AIM

To compare genome-wide methylation and gene expression patterns between responsive and non-responsive patients with PD after 4 wk of escitalopram treatment.

METHODS

Thirty patients with PD were enrolled in this study (responders = 13; non-responders = 17). All patients were assessed using the PD Severity Scale-Chinese version before and after treatment. The Illumina Infinium MethylationEPIC (850k) BeadChip for genome-wide methylation screening and mRNA sequencing was used in all patients with PD.

RESULTS

A total of 701 differentially methylated positions (DMPs) were found between responders and non-responders (|Δβ| ≥ 0.06, q < 0.05), and the hyper- and hypomethylated CpG sites were 511 (72.9%) and 190 (27.1%), respectively. Relative to non-responders, there were 59 differential transcripts, of which 20 were downregulated and 39 were upregulated (q < 0.05). However, no differentially expressed genes were identified by mRNA sequencing after correcting for multiple testing (|log2(FC)| > 1, q > 0.05).

CONCLUSION

This preliminary study showed that DMPs might be associated with the treatment response to escitalopram in PD; however, these DMPs need to be verified in large samples.

Brain-derived neurotrophic factor (BDNF) variants and promoter I methylation are associated with prolonged nocturnal awakenings in older adults

Brain-derived neurotrophic factor (BDNF) is important for sleep physiology. This study investigates whether BDNF variants and promoter I methylation may be implicated in sleep disturbances in older adults. Genotyping was performed for seven BDNF single nucleotide polymorphisms (SNPs) in 355 community-dwelling older adults (aged ≥65 years) and BDNF exon 1 promoter methylation was measured in blood samples at baseline (n = 153). Self-reported daytime sleepiness and insomnia, ambulatory polysomnography measures of sleep continuity and architecture, and psychotropic drug intake were assayed during follow-up. Logistic regression adjusted for age, sex, comorbidities, body mass index, and psychotropic drug intake. Associations were found specifically between wake time after sleep onset (WASO) and four SNPs in the participants not taking psychotropic drugs, whereas in those taking drugs, the associations were either not significant (rs6265 and rs7103411) or in the reverse direction (rs11030101 and rs28722151). Higher BDNF methylation levels were found at most CpG units in those with long WASO and this varied according to psychotropic drug use. The reference group with short WASO not taking drugs showed the lowest methylation levels and the group with long WASO taking treatment, the highest levels. Some SNPs also modified the associations, the participants carrying the low-risk genotype having the lower methylation levels. This genetic and epigenetic study demonstrated blood BDNF promoter methylation to be a potential biomarker of prolonged nocturnal awakenings in older people. Our results suggest the modifying effect of psychotropic drugs and BDNF genetic variants in the associations between methylation and WASO.

The Serum Brain-Derived Neurotrophic Factor Increases in Serotonin Reuptake Inhibitor Responders Patients with First-Episode, Drug-Naïve Major Depression

Brain-derived neurotrophic factor (BDNF) is a growth factor synthesized in the cell bodies of neurons and glia, which affects neuronal maturation, the survival of nervous system, and synaptic plasticity. BDNF play an important role in the pathophysiology of major depression (MD). The serum BDNF levels changed over time, or with the improvement in depressive symptoms. However, the change of serum BDNF during pharmacotherapy remains obscure in MDD. In particular, the changes in serum BDNF associated with pharmacotherapy have not yet been fully elucidated. The present study aimed to compare the changes in serum BDNF concentrations in first-episode, drug-naive patients with MD treated with antidepressants between treatment-response and treatment-nonresponse groups. The study included 35 inpatients and outpatients composed of 15 males and 20 females aged 36.7 ± 6.8 years at the Department of Psychiatry of our University Hospital. All patients met the DSM-5 diagnostic criteria for MD. The antidepressants administered included paroxetine, duloxetine, and escitalopram. Severity of depressive state was assessed using the 17-item HAMD before and 8 weeks after drug administration. Responders were defined as those whose total HAMD scores at 8 weeks had decreased by 50% or more compared to those before drug administration, while non-responders were those whose total HAMD scores had decreased by less than 50%. Here we showed that serum BDNF levels were not significantly different at any point between the two groups. The responder group, but not the non-responder group, showed statistically significant changes in serum BDNF 0 and serum BDNF 8. The results suggest that the changes of serum BDNF might differ between the two groups. The measurement of serum BDNF has the potential to be a useful predictor of pharmacotherapy in patients with first-episode, drug-naïve MD.

Integrated genome-wide methylation and expression analyses provide predictors of diagnosis and early response to antidepressant in panic disorder

BACKGROUND

We investigated differentially methylated and expressed genes between panic disorder (PD) and healthy controls (HCs) to determine whether DNA methylation and expression level of candidate genes can be used as biomarkers for diagnosis and early response.

METHODS

Illumina infiniun Methylation EPIC (850 k) Beadchip for genome-wide methylation screening and mRNA sequencing was conducted in a discovery set (30 patients with PD and 30 matched HCs). The candidate gene loci methylation and expression were verified in an independent validation sample (101 PD patients and 107 HCs).

RESULTS

In the discovery set, there were 3613 differentially methylated cytosine phosphate guanosine sites and these differential methylation positions were located within 1938 unique genes, including 1758 hypermethylated genes, 150 hypomethylated genes, and the coexistence of hypermethylation and hypomethylation sites were found in 30 genes. There were 1111 differential transcripts in PD compared to normal controls (850 down-regulated and 261 up-regulated). Further, 212 differentially expressed genes were screened (40 up-regulated and 172 down-regulated). In the validation set, compared with HCs, there was no significant difference in DNA methylation level of Casitas B-lineage lymphoma (CBL) gene loci (cg07123846). The expression level of CBL gene in PD patients was lower (vs. HCs). After four weeks' treatment, the baseline expression level of CBL gene in the responders was higher than nonresponders.

LIMITATIONS

The sample size was limited. We only chose CBL as a candidate gene. Follow-up periods were short.

CONCLUSIONS

There are differences in genome-wide DNA methylation and mRNA expression between PD patients and HCs. The changes in expression level of CBL gene may be an important molecular marker for PD diagnosis and early response.

Predicting treatment outcome in depression: an introduction into current concepts and challenges

Improving response and remission rates in major depressive disorder (MDD) remains an important challenge. Matching patients to the treatment they will most likely respond to should be the ultimate goal. Even though numerous studies have investigated patient-specific indicators of treatment efficacy, no (bio)markers or empirical tests for use in clinical practice have resulted as of now. Therefore, clinical decisions regarding the treatment of MDD still have to be made on the basis of questionnaire- or interview-based assessments and general guidelines without the support of a (laboratory) test. We conducted a narrative review of current approaches to characterize and predict outcome to pharmacological treatments in MDD. We particularly focused on findings from newer computational studies using machine learning and on the resulting implementation into clinical decision support systems. The main issues seem to rest upon the unavailability of robust predictive variables and the lacking application of empirical findings and predictive models in clinical practice. We outline several challenges that need to be tackled on different stages of the translational process, from current concepts and definitions to generalizable prediction models and their successful implementation into digital support systems. By bridging the addressed gaps in translational psychiatric research, advances in data quantity and new technologies may enable the next steps toward precision psychiatry.

The interaction of P11 methylation and early-life stress impacts the antidepressant response in patients with major depressive disorder

PURPOSE

The present research investigates the influence of P11 gene DNA methylation combined with life stress on the response to antidepressants in the first two weeks.

METHODS

A total of 291 Han Chinese patients with major depressive disorder and 100 healthy controls were included. The Life Events Scale and the Childhood Trauma Questionnaire were used to assess stress. The primary endpoint was the Hamilton Depression Rating Scale-17 reduction rate after two weeks of treatment. The Illumina HiSeq Platform was used to detect the methylation of 74 CpG sites of the P11 gene in peripheral blood samples.

RESULTS

The mean methylation of all P11 CpG sites, as well as the methylation at 4 CpG sites (P11-2-169, P11-2-192, P11-2-202, P11-2-204), were significantly higher in patients with MDD than in healthy controls (FDR-corrected P < 0.05). The response to antidepressants was associated with the following interactions: the CTQ score and P11-3-185 site methylation (OR = 0.297, FDR-corrected P = 0.023), the CTQ physical neglect score and P11-2-117 site methylation (OR = 0.005, FDR-corrected P = 0.033), and the CTQ emotional abuse score and P11-3-185 site methylation (OR = 0.001, FDR-corrected P = 0.023).

CONCLUSIONS

The methylation of the P11 gene was significantly higher in patients with major depressive disorder. The interaction of P11 DNA methylation and early-life stress may influence the short-term antidepressant treatment response.

Gender-affirming hormone therapy induces specific DNA methylation changes in blood

BACKGROUND

DNA methylation is an epigenetic mark that is influenced by underlying genetic profile, environment, and ageing. In addition to X-linked DNA methylation, sex-specific methylation patterns are widespread across autosomal chromosomes and can be present from birth or arise over time. In individuals where gender identity and sex assigned at birth are markedly incongruent, as in the case of transgender people, feminization or masculinization may be sought through gender-affirming hormone therapy (GAHT). GAHT is a cornerstone of transgender care, yet no studies to date have investigated its effect on genome-wide methylation. We profiled genome-wide DNA methylation in blood of transgender women (n = 13) and transgender men (n = 13) before and during GAHT (6 months and 12 months into feminizing or masculinizing hormone therapy).

RESULTS

We identified several thousand differentially methylated CpG sites (DMPs) (Δβ ≥ 0.02, unadjusted p value < 0.05) and several differentially methylated regions (DMRs) in both people undergoing feminizing and masculinizing GAHT, the vast majority of which were progressive changes over time. X chromosome and sex-specific autosomal DNA methylation patterns established in early development are largely refractory to change in association with GAHT, with only 3% affected (Δβ ≥ 0.02, unadjusted p value < 0.05). The small number of sex-specific DMPs that were affected by GAHT were those that become sex-specific during the lifetime, known as sex-and-age DMPs, including DMRs in PRR4 and VMP1 genes. The GAHT-induced changes at these sex-associated probes consistently demonstrated a shift towards the methylation signature of the GAHT-naïve opposite sex, and we observed enrichment of previously reported adolescence-associated methylation changes.

CONCLUSION

We provide evidence for GAHT inducing a unique blood methylation signature in transgender people. This study advances our understanding of the complex interplay between sex hormones, sex chromosomes, and DNA methylation in the context of immunity. We highlight the need to broaden the field of 'sex-specific' immunity beyond cisgender males and cisgender females, as transgender people on GAHT exhibit a unique molecular profile.

Maternal Deprivation Increased Vulnerability to Depression in Adult Rats Through DRD2 Promoter Methylation in the Ventral Tegmental Area

OBJECTIVE

Early life adversity is a risk factor for depression in adulthood; however, the underlying mechanisms are not well understood. This study aims to investigate the effect of DNA methylation of DRD2 gene on early life stress-induced depression in adult rats.

METHODS

Newborn Sprague-Dawley rats were randomly assigned to four groups: maternal deprivation group (MD), chronic unpredictable stress (CUS) group, maternal deprivation plus chronic unpredictable stress (MD/CUS) group, and normal control group (NOR). Behaviors were measured by open field test (OFT), sucrose preference test (SPT), and Original Research Article forced swimming test (FST). Fecal CORT level was detected by ELISA. Bisulfite amplicon sequencing PCR was used to assess methylation levels of DRD2 promoter.

RESULTS

CUS and MD/CUS rats had a significantly shorter total distance, longer immobility time, and higher CORT level, while MD and MD/CUS rats had a significantly lower percentage of central distance, more feces, lower rate of sucrose preference, and lower levels of DRD2 protein and mRNA in the VTA than NOR rats. CUS rats showed a significantly higher DRD2 mRNA and protein levels in the VTA than NOR rats. CUS, MD, and MD/CUS rats showed a significantly higher level of DRD2 promoter methylation than NOR rats. CORT level was significantly correlated with the sucrose preference rate in SPT, the immobility time in FST, the total distance, and the number of fecal pellets in OFT. DRD2 protein level was significantly correlated with the sucrose preference rate and the number of fecal pellets. DRD2 mRNA level was significantly correlated with the percentage of central distance and the number of fecal pellets in OFT. The level of DRD2 promoter methylation was significantly correlated with the sucrose preference rate, immobility time, total distance, the percentage of central distance, and the number of fecal pellets.

CONCLUSIONS

Early life MD increased vulnerability to stress-induced depressive-like behavior in adult rats. Enhanced DRD2 promoter methylation in the VTA may increase the susceptibility to depression.

DNA methylations of brain-derived neurotrophic factor exon VI are associated with major depressive disorder and antidepressant-induced remission in females

BACKGROUND

Brain-derived neurotrophic factor (BDNF) has been suggested to play important roles in major depressive disorder (MDD) and antidepressant treatment. The main purpose of this study was to evaluate the association of DNA methylation changes in the BDNF gene with MDD and antidepressant treatment.

METHODS

A total of 291 MDD patients and 100 healthy controls were included and followed up for 6 weeks. The Hamilton Depression Rating Scale-17 (HDRS-17) was used to measure treatment improvement. The life events scales (LES) and childhood trauma questionnaire (CTQ) were used to rate recent and early life stress. DNA methylation levels of CpG sites in the BDNF gene were measured.

RESULTS

Two CpG sites in BDNF exon VI (BDNF133 and BDNF134) were demonstrated to have significantly higher methylation in MDD patients than in controls (both FDR-adjusted P = 0.001). A logistics regression model indicated that the interaction between the hypermethylation of BDNF133 and negative subscore of LES was associated to MDD (OR=0.0075, P<0.001). Methylation of BDNF140 at baseline was significantly elevated in remitters (FDR-adjusted P = 0.046) at week 6. In subgroup analyses, these findings could be replicated in females, but not in males.

LIMITATIONS

The methylation status of BDNF after 6 weeks of antidepressant treatment was not measured and the DNA methylation were detected in peripheral blood cells.

CONCLUSIONS

These findings highlight gender-specific alteration of methylation at several CpG sites in BDNF exon VI as a promising candidate indicator of MDD and antidepressant-induced remission.

The role of BDNF exon I region methylation in the treatment of depression with sertraline and its clinical diagnostic value

Background

Brain‐derived neurotrophic factor (BDNF) is considered to be one of the best candidate genes for depression. However, whether sertraline treatment affects the methylation level of this gene remains unknown.

Methods

Fifty‐three patients with depression and 51 healthy controls were included in the study. The methylation level of BDNF exon I was determined in blood samples from these subjects. The Hamilton Depression Scale was used to evaluate the depression status of patients. Single nucleotide polymorphism detection was used for genotyping, and a receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the methylation level of this locus in patients with depression.

Results

There was a significant difference in the methylation level of BDNF exon I between the control and depression groups. No effect of sertraline monotherapy on BDNF methylation was found in subjects with depression. Moreover, no interaction was found between BDNF genotype and the per cent methylation of BDNF exon I. However, methylation at this site was positively correlated with diurnal variation and retardation scores. Blood homocysteine concentrations were significantly reduced by sertraline treatment. No influence of genotype on serum BDNF concentration was found in subjects with depression. The ROC curve showed that methylation of BDNF exon I may be used to distinguish patients from healthy people, to a certain extent.

Conclusion

Methylation of BDNF exon I may be used as a biomarker of depression and may be a therapeutic target for previously untreated depression.

Regular, Intense Exercise Training as a Healthy Aging Lifestyle Strategy: Preventing DNA Damage, Telomere Shortening and Adverse DNA Methylation Changes Over a Lifetime

Exercise training is one of the few therapeutic interventions that improves health span by delaying the onset of age-related diseases and preventing early death. The length of telomeres, the 5'-TTAGGG n -3' tandem repeats at the ends of mammalian chromosomes, is one of the main indicators of biological age. Telomeres undergo shortening with each cellular division. This subsequently leads to alterations in the expression of several genes that encode vital proteins with critical functions in many tissues throughout the body, and ultimately impacts cardiovascular, immune and muscle physiology. The sub-telomeric DNA is comprised of heavily methylated, heterochromatin. Methylation and histone acetylation are two of the most well-studied examples of the epigenetic modifications that occur on histone proteins. DNA methylation is the type of epigenetic modification that alters gene expression without modifying gene sequence. Although diet, genetic predisposition and a healthy lifestyle seem to alter DNA methylation and telomere length (TL), recent evidence suggests that training status or physical fitness are some of the major factors that control DNA structural modifications. In fact, TL is positively associated with cardiorespiratory fitness, physical activity level (sedentary, active, moderately trained, or elite) and training intensity, but is shorter in over-trained athletes. Similarly, somatic cells are vulnerable to exercise-induced epigenetic modification, including DNA methylation. Exercise-training load, however, depends on intensity and volume (duration and frequency). Training load-dependent responses in genomic profiles could underpin the discordant physiological and physical responses to exercise. In the current review, we will discuss the role of various forms of exercise training in the regulation of DNA damage, TL and DNA methylation status in humans, to provide an update on the influence exercise training has on biological aging.

Methylome-wide change associated with response to electroconvulsive therapy in depressed patients

Electroconvulsive therapy (ECT) is a quick-acting and powerful antidepressant treatment considered to be effective in treating severe and pharmacotherapy-resistant forms of depression. Recent studies have suggested that epigenetic mechanisms can mediate treatment response and investigations about the relationship between the effects of ECT and DNA methylation have so far largely taken candidate approaches. In the present study, we examined the effects of ECT on the methylome associated with response in depressed patients (n = 34), testing for differentially methylated CpG sites before the first and after the last ECT treatment. We identified one differentially methylated CpG site associated with the effect of ECT response (defined as >50% decrease in Hamilton Depression Rating Scale score, HDRS), TNKS (q < 0.05; p = 7.15 × 10^-8). When defining response continuously (ΔHDRS), the top suggestive differentially methylated CpG site was in FKBP5 (p = 3.94 × 10^-7). Regional analyses identified two differentially methylated regions on chromosomes 8 (Šídák's p = 0.0031) and 20 (Šídák's p = 4.2 × 10^-5) associated with ΔHDRS. Functional pathway analysis did not identify any significant pathways. A confirmatory look at candidates previously proposed to be involved in ECT mechanisms found CpG sites associated with response only at the nominally significant level (p < 0.05). Despite the limited sample size, the present study was able to identify epigenetic change associated with ECT response suggesting that this approach, especially when involving larger samples, has the potential to inform the study of mechanisms involved in ECT and severe and treatment-resistant depression.

Toward personalized medicine in schizophrenia: Genetics and epigenetics of antipsychotic treatment

Schizophrenia is a complex psychiatric disorder where genetic, epigenetic, and environmental factors play a role in disease onset, course of illness, and treatment outcome. Pharmaco(epi)genetic research presents an important opportunity to improve patient care through prediction of medication side effects and response. In this narrative review, we discuss the current state of research and important progress of both genetic and epigenetic factors involved in antipsychotic response, over the past five years. The review is largely focused on the following frequently prescribed antipsychotics: olanzapine, risperidone, aripiprazole, and clozapine. Several consistent pharmacogenetic findings have emerged, in particular pharmacokinetic genes (primarily cytochrome P450 enzymes) and pharmacodynamic genes involving dopamine, serotonin, and glutamate neurotransmission. In addition to studies analysing DNA sequence variants, there are also several pharmacoepigenetic studies of antipsychotic response that have focused on the measurement of DNA methylation. Although pharmacoepigenetics is still in its infancy, consideration of both genetic and epigenetic factors contributing to antipsychotic response and side effects no doubt will be increasingly important in personalized medicine. We provide recommendations for next steps in research and clinical evaluation.

Drug Response-Related DNA Methylation Changes in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder

Pharmacotherapy is the most common treatment for schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). Pharmacogenetic studies have achieved results with limited clinical utility. DNA methylation (DNAm), an epigenetic modification, has been proposed to be involved in both the pathology and drug treatment of these disorders. Emerging data indicates that DNAm could be used as a predictor of drug response for psychiatric disorders. In this study, we performed a systematic review to evaluate the reproducibility of published changes of drug response-related DNAm in SCZ, BD and MDD. A total of 37 publications were included. Since the studies involved patients of different treatment stages, we partitioned them into three groups based on their primary focuses: (1) medication-induced DNAm changes (n = 8); (2) the relationship between DNAm and clinical improvement (n = 24); and (3) comparison of DNAm status across different medications (n = 14). We found that only BDNF was consistent with the DNAm changes detected in four independent studies for MDD. It was positively correlated with clinical improvement in MDD. To develop better predictive DNAm factors for drug response, we also discussed future research strategies, including experimental, analytical procedures and statistical criteria. Our review shows promising possibilities for using BDNF DNAm as a predictor of antidepressant treatment response for MDD, while more pharmacoepigenetic studies are needed for treatments of various diseases. Future research should take advantage of a system-wide analysis with a strict and standard analytical procedure.

DNA Methylation of Fluoxetine Response in Child and Adolescence: Preliminary Results

Purpose

The search for predictors of antidepressant response is gaining increasing attention, with epigenetic markers attracting a great deal of interest. We performed a genome-wide study assessing baseline differences in DNA methylation between Responders and Non-Responders.

Patients and Methods

Twenty-two children and adolescents, receiving fluoxetine treatment for the first time, were classified as Responders or Non-Responders according to CGI-I score after 8 weeks of fluoxetine treatment. Genome-wide DNA methylation was profiled using the Illumina Infinium MethylationEPIC BeadChip Kit and analyzed using the Chip Analysis Methylation Pipeline (ChAMP).

Results

We identified 21 CpG sites significantly (FDR<0.05) associated with fluoxetine response that showed meaningful differences (Δβ> ±0.2) in methylation level between Responders and Non-Responders. Two genes, RHOJ (Ras Homolog Family Member J) and OR2L13 (Olfactory Receptor family 2 subfamily L member 13), presented more than one significant CpG sites.

Conclusion

Our findings provide new insights into the molecular mechanisms underlying the complex phenotype of antidepressant response, indicating that methylation at specific genes could be a promising biomarker that needs further replication in large cohorts.

Effects of CRMP2 DNA Methylation in the Hippocampus on Depressive-Like Behaviors and Cytoskeletal Proteins in Rats

Chronic stress appears to alter DNA methylation and DNA methyltransferases (DNMTs) in brain regions related to emotion. Collapsin response mediator protein-2 (CRMP2) mediates the development of depression by regulating microtubule dynamics. In this study, rats were subjected to chronic unpredictable mild stress (CUMS). At the end of the CUMS procedure, normal saline or fluoxetine was administered to the rats. Moreover, normal saline or the 5-aza-2’-deoxycytidine (5-aza) was administered to the hippocampal CA1 region of the rats. Behavioral tests were performed to evaluate the depressive-like phenotypes. The CRMP2 DNA methylation levels and cytoskeletal microtubular system-related biomarkers were detected by several molecular biology techniques. The results showed that the rat model of depression was successfully established by exposure to CUMS, and fluoxetine treatment exerted an antidepressant-like effect. We observed the upregulation of DNMT1 and DNMT3a in the hippocampus of stressed rats. CUMS induced a decrease in CRMP2 expression and an increase in phosphorylated CRMP2 (pCRMP2) expression in the hippocampus of rats. The rate of DNA methylation in the CpG island of the CRMP2 promoter region in the hippocampus of stressed rats was significantly higher than that in control rats. Moreover, CUMS significantly decreased the interaction between CRMP2 and α-tubulin and decreased the microtubule dynamics. Chronic fluoxetine treatment reversed these changes. Also, hypomethylation induced by 5-aza injection into the hippocampal CA1 region caused antidepressant-like effects and increased CRMP2 expression and microtubule dynamics. These results suggested that CRMP2 DNA methylation may be involved in regulating the cytoskeletal microtubular system and mediating depressive-like behaviors.

Deep learning for the prediction of treatment response in depression

BACKGROUND

Mood disorders are characterized by heterogeneity in severity, symptoms and treatment response. The possibility of selecting the correct therapy on the basis of patient-specific biomarker may be a considerable step towards personalized psychiatry. Machine learning methods are gaining increasing popularity in the medical field. Once trained, the possibility to consider single patients in the analyses instead of whole groups makes them particularly appealing to investigate treatment response. Deep learning, a branch of machine learning, lately gained attention, due to its effectiveness in dealing with large neuroimaging data and to integrate them with clinical, molecular or -omics biomarkers.

METHODS

In this mini-review, we summarize studies that use deep learning methods to predict response to treatment in depression. We performed a bibliographic search on PUBMED, Google Scholar and Web of Science using the terms "psychiatry", "mood disorder", "depression", "treatment", "deep learning", "neural networks". Only studies considering patients' datasets are considered.

RESULTS

Eight studies met the inclusion criteria. Accuracies in prediction of response to therapy were considerably high in all studies, but results may be not easy to interpret.

LIMITATIONS

The major limitation for the current studies is the small sample size, which constitutes an issue for machine learning methods.

CONCLUSIONS

Deep learning shows promising results in terms of prediction of treatment response, often outperforming regression methods and reaching accuracies of around 80%. This could be of great help towards personalized medicine. However, more efforts are needed in terms of increasing datasets size and improved interpretability of results.

Integrated Analysis of Methylomic and Transcriptomic Data to Identify Potential Diagnostic Biomarkers for Major Depressive Disorder

Major depressive disorder (MDD) is a mental illness with high incidence and complex etiology, that poses a serious threat to human health and increases the socioeconomic burden. Currently, high-accuracy biomarkers for MDD diagnosis are urgently needed. This paper aims to identify novel blood-based diagnostic biomarkers for MDD. Whole blood DNA methylation data and gene expression data from the Gene Expression Omnibus database are downloaded. Then, differentially expressed/methylated genes (DEGs/DMGs) are identified. In addition, we made a systematic analysis of the DNA methylation on 5′-C-phosphate-G-3′ (CpGs) in all of the gene regions, as well as different gene regions, and then we defined a “dominant” region. Subsequently, integrated analysis is employed to identify the robust MDD-related blood biomarkers. Finally, a gene expression classifier and a methylation classifier are constructed using the random forest algorithm and the leave-one-out cross-validation method. Our results demonstrate that DEGs are mainly involved in the inflammatory response-associated pathways, while DMGs are primarily concentrated in the neurodevelopment- and neuroplasticity-associated pathways. Our integrated analysis identified 46 hypo-methylated and up-regulated (hypo-up) genes and 71 hyper-methylated and down-regulated (hyper-down) genes. One gene expression classifier and two DNA methylation classifiers, based on the CpGs in all of the regions or in the dominant regions are constructed. The gene expression classifier possessed the best predictive ability, followed by the DNA methylation classifiers, based on the CpGs in both the dominant regions and all of the regions. In summary, the integrated analysis of DNA methylation and gene expression has identified 46 hypo-up genes and 71 hyper-down genes, which could be used as diagnostic biomarkers for MDD.

Epigenetic methylation in Eosinophilic Esophagitis: Molecular ageing and novel biomarkers for treatment response

BACKGROUND

Treatment failure in eosinophilic esophagitis (EoE) is common. We hypothesize that DNA methylation differs between patients by treatment response to topical steroids (oral viscous budesonide), thus offering the potential to inform targeting therapies.

OBJECTIVE

We sought to identify differentially methylated sites and affiliated genes in pre-treatment oesophageal cells between responders and non-responders and test for accelerated epigenetic ageing in oesophageal cells of EoE patients.

METHODS

DNA was extracted from prospectively collected and biobanked oesophageal biopsies from 36 Caucasian treatment naïve EoE patients at diagnosis. Methylation assays were completed using the Infinium HumanMethylation450 BeadChip. Normalized β values for each CpG site were tested (t test) for differential methylation. Further, 353 CpG probes were used to estimate epigenetic age for each patient and a linear regression model tested whether chronologic age and epigenetic age differed. Epigenetic age results were confirmed in an independent cohort of healthy controls.

RESULTS

Eighteen CpG sites were differentially methylated by treatment response (P < .00001). The mean epigenetic age and chronological age were 56.1 ± 11.1 and 36.7 ± 12.3 years, a mean age difference of 19.3 ± 5.2 years (P < .0001); accelerated ageing was not observed in the oesophageal cells of healthy controls.

CONCLUSIONS AND CLINICAL RELEVANCE

EoE patients that respond versus do not respond to treatment have differences in their methylation profile, including enrichment of genes in pathways consistent with cellular injury and repair due to environmental stress and cell adhesion and barrier integrity. EoE also appears to accelerate cellular ageing. Whether treatment can arrest or reverse accelerated epigenetic ageing and the implications for long-term disease progression is important areas for future research.

The relationship of tryptophan hydroxylase-2 methylation to early-life stress and its impact on short-term antidepressant treatment response

INTRODUCTION

The gene tryptophan hydroxylase 2 (TPH2) encodes the associated rate-limiting enzyme in the biosynthesis 5-HT (serotonin). Early life stress and adult variability in TPH2 can correspond with diminished response to antidepressants for patients with major depressive disorder (MDD). DNA methylation is an epigenetic mechanism mediating gene expression, often tempered by environmental factors. Here, we investigate the influence of TPH2 methylation combined with stress on response to antidepressants within the first two weeks of treatment initiation.

METHODS

291 Han Chinese patients with major depressive disorder and 100 healthy controls comprised the study population. The Life Events Scale (LES) and the Childhood Trauma Questionnaire (CTQ) rated recent and early-life stress. The primary outcome equaled a reduction by ≥ 50% from the Hamilton Depression Rating Scale-17 (HAMD-17) after 2 weeks of treatment. The Illumina HiSeq platform assessed methylation status in 38 CpG sites located upstream and downstream of 11 TPH2 polymorphism sites.

RESULTS

In 291 patients and 100 healthy controls, 3 CpG sites predict antidepressant treatment response per sex (TPH2-7-142, p=0.012; TPH2-1-43, p=0.033; TPH2-5-203, p=0.036). High-level CTQ scores relate significantly to DNA hypomethylation at CpG-site TPH2-8-237 in males (false discovery rate [FDR]-corrected p=0.038). Additionally, the interaction of hypermethylation in two CpG sites and elevated early-life stress may reduce antidepressant response (TPH2-5-203, FDR corrected p=0.010; TPH2-10-60, FDR corrected p=0.001).

CONCLUSIONS

Our study suggests that TPH2 methylation and its interaction with early-life stress may impair antidepressant response, suggesting that pharmaco-epigenetic studies could identify epigenetic biomarkers for antidepressant response.

The association between serotonin-related gene polymorphisms and susceptibility and early sertraline response in patients with panic disorder

BACKGROUND

A number of studies have shown that genetic factor plays an important role in etiology of panic disorder (PD). The aim of the present study was to examine the association of serotonin-related gene polymorphisms with PD risk. Then, we analyzed the correlation between these gene polymorphisms and response to sertraline drug.

METHODS

Two hundred thirty-three patients with PD and 231 healthy controls were enrolled in the study. Panic Disorder Severity Scale (PDSS) were administered to all subjects, and all patients in the study were also assessed after 4 weeks of treatment. The SLC6A4(rs140701, rs3813034, 5-HTTLPR and STin2), 5-HTR1A rs6295, 5-HTR2A rs6313 and COMT rs4680 gene polymorphisms were genotyped and assessed for the potential association.

RESULTS

The allelic model showed that the SLC6A4 rs140701 polymorphism variant was significantly associated with increased risk of PD (OR = 0.624, 95% CI 0.450-0.864, p < 0.05), and a significant result was found in the dominant model (OR = 0.546; 95% CI, 0.371-0.804, p < 0.05). There was a significant difference in allele and genotype frequency between responders and nonresponders in the 5-HTTLPR polymorphism (OR = 0.205, 95% CI 0.128-0.328; OR = 0.249, 95% CI 0.155-0.401, both p < 0.001), indicating the PD patients with S-allele had a poorer response to sertraline than L-allele carriers.

CONCLUSIONS

The present study suggests that the SLC6A4 rs140701 polymorphism variant may be associated with susceptibility to PD, and 5-HTTLPR polymorphism may be a predictor of response to sertraline in the treatment of PD.

Epigenetic mechanisms activated by childhood adversity

Adverse childhood experiences (ACE) impair health and life expectancy and may result in an epigenetic signature that drives increased morbidity primed during early stages of life. This literature review focuses on the current evidence for epigenetic-mediated programming of brain and immune function resulting from ACE. To address this aim, a total of 88 articles indexed in PubMed before August 2019 concerning ACE and epigenetics were surveyed. Current evidence partially supports epigenetic programming of the hypothalamic-pituitary-adrenal axis, but convincingly shows that ACE impairs immune function. Additionally, the needs and challenges that face this area are discussed in order to provide a framework that may help to clarify the role of epigenetics in the long-lasting effects of ACE.

Differences in cytokines between patients with generalised anxiety disorder and panic disorder

OBJECTIVE

The purpose of this study was to evaluate the differences among panic disorder (PD), generalised anxiety disorder (GAD) and controls in inflammatory cytokines. We also analysed the correlation between inflammatory cytokines and response to escitalopram in PD and GAD patients.

METHODS

Eighty-six patients with PD, 86 patients with GAD and 86 healthy controls were recruited for this study. All participants were, respectively, assessed for severity of anxiety and panic symptoms using the Hamilton Anxiety Rating Scale (HAMA) and the Panic Disorder Severity Scale (PDSS); all patients in the study were also assessed after 4 weeks of treatment. The serum levels of cytokines were measured using a flow fluorescence microsphere assay.

RESULTS

Both PD and GAD patients had higher serum levels of interleukin 6 (IL-6) than controls, and patients with PD showed significantly higher IL-6 than GAD patients. Significant positive correlations were found between the IFN-γ levels and the severity of anxiety in GAD patients. Higher level of IL-6 was associated with better response to escitalopram treatment in PD patients. However, the baseline levels of cytokines were not associated with treatment responses in GAD patients.

CONCLUSION

The present findings suggest that patients with PD may have higher levels of IL-6 than GAD, and higher baseline levels of IL-6 may be a better response to escitalopram in the treatment of PD.

The Relationship between DNA Methylation and Antidepressant Medications: A Systematic Review

Major depressive disorder (MDD) is the leading cause of disability worldwide and is associated with high rates of suicide and medical comorbidities. Current antidepressant medications are suboptimal, as most MDD patients fail to achieve complete remission from symptoms. At present, clinicians are unable to predict which antidepressant is most effective for a particular patient, exposing patients to multiple medication trials and side effects. Since MDD’s etiology includes interactions between genes and environment, the epigenome is of interest for predictive utility and treatment monitoring. Epigenetic mechanisms of antidepressant medications are incompletely understood. Differences in epigenetic profiles may impact treatment response. A systematic literature search yielded 24 studies reporting the interaction between antidepressants and eight genes (BDNF, MAOA, SLC6A2, SLC6A4, HTR1A, HTR1B, IL6, IL11) and whole genome methylation. Methylation of certain sites within BDNF, SLC6A4, HTR1A, HTR1B, IL11, and the whole genome was predictive of antidepressant response. Comparing DNA methylation in patients during depressive episodes, during treatment, in remission, and after antidepressant cessation would help clarify the influence of antidepressant medications on DNA methylation. Individuals’ unique methylation profiles may be used clinically for personalization of antidepressant choice in the future.

Association study of polymorphisms within inflammatory genes and methylation status in treatment response in major depression

Background:

Although pharmacogenetics for major depressive disorder (MDD) is gaining momentum, the role of genetics in differences in response to antidepressant treatment is controversial, as they depend on multifactorial and polygenic phenotypes. Previous studies focused on the genes of the serotonergic system, leaving apart other pathological factors such as the inflammatory pathway. The main objective of the study was to assess whether treatment response might be associated with specific inflammation-related genetic variants or their methylation status.

Methods:

41 SNPs in 8 inflammatory genes: interleukin (IL) 1-β, IL2, IL6, IL6R, IL10, IL18, tumor necrosis factor (TNF)-α and interferon (IFN)-γ were genotyped in 153 patients with MDD, who were evaluated with the Mausdley Staging Method to determine treatment response profiles. Pyrosequencing reactions and methylation quantification were performed in a PyroMark Q24 in 5 selected CpG islands of IL1- β, IL6 and IL6R. Linear and logistic regression analyses were conducted, including age and gender as covariates using PLINK 1.07.

Results:

Allelic distribution of IL1- β rs1143643 was significantly associated with MSM scores (FDR corrected p = 0.04). Allelic distribution of IL6R rs57569414 showed a trend towards significance with MSM scores (p = 0.002; FDR corrected p = 0.07). Haplotype analyses showed associations between allelic combinations of IL1-β and IL10 with treatment response (FDR corrected p < 0.01). Methylation percentage of treatment responders was only higher in an IL6R CpG island (p < 0.05).

Conclusions:

These exploratory findings suggest that IL1-β and, marginally, IL6R polymorphisms may affect treatment response in major depression. If confirmed, these results may account for the heterogeneous phenotypes of major depression that underlie differences in treatment response.

Towards precision medicine in generalized anxiety disorder: Review of genetics and pharmaco(epi)genetics

Generalized anxiety disorder (GAD) is a prevalent and chronic mental disorder that elicits widespread functional impairment. Given the high degree of non-response/partial response among patients with GAD to available pharmacological treatments, there is a strong need for novel approaches that can optimize outcomes, and lead to medications that are safer and more effective. Although investigations have identified interesting targets predicting treatment response through pharmacogenetics (PGx), pharmaco-epigenetics, and neuroimaging methods, these studies are often solitary, not replicated, and carry several limitations. This review provides an overview of the current status of GAD genetics and PGx and presents potential strategies to improve treatment response by combining better phenotyping with PGx and improved analytical methods. These strategies carry the dual benefit of delivering data on biomarkers of treatment response as well as pointing to disease mechanisms through the biology of the markers associated with response. Overall, these efforts can serve to identify clinical, genetic, and epigenetic factors that can be incorporated into a pharmaco(epi)genetic test that may ultimately improve treatment response and reduce the socioeconomic burden of GAD.

ARPNet: Antidepressant Response Prediction Network for Major Depressive Disorder

Treating patients with major depressive disorder is challenging because it takes several months for antidepressants prescribed for the patients to take effect. This limitation may result in increased risks and treatment costs. To address this limitation, an accurate antidepressant response prediction model is needed. Recently, several studies have proposed models that extract useful features such as neuroimaging biomarkers and genetic variants from patient data, and use them as predictors for predicting the antidepressant responses of patients. However, it is impossible to utilize all the different types of predictors when making a clinical decision on what drugs to prescribe for a patient. Although a machine learning-based antidepressant response prediction model has been proposed to overcome this problem, the model cannot find the most effective antidepressant for a patient. Based on a neural network, we propose an Antidepressant Response Prediction Network (ARPNet) model capturing high-dimensional patterns from useful features. Based on a literature survey and data-driven feature selection, we extract useful features from patient data, and use the features as predictors. In ARPNet, the patient representation layer captures patient features and the antidepressant prescription representation layer captures antidepressant features. Utilizing the patient and antidepressant prescription representation vectors, ARPNet predicts the degree of antidepressant response. The experimental evaluation results demonstrate that our proposed ARPNet model outperforms machine learning-based models in predicting antidepressant response. Moreover, we demonstrate the applicability of ARPNet in downstream applications in use case scenarios.

Moving pharmacoepigenetics tools for depression toward clinical use

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.

What do DNA methylation studies tell us about depression? A systematic review

There has been a limited number of systematic reviews conducted to summarize the overview of the relationship between DNA methylation and depression, and to critically appraise the roles of major study characteristics in the accuracy of study findings. This systematic review aims to critically appraise the impact of study characteristics on the association between DNA methylation and depression, and summarize the overview of this association. Electronic databases and gray literatures until December 2017 were searched for English-language studies with standard diagnostic criteria of depression. A total of 67 studies were included in this review along with a summary of their study characteristics. We grouped the findings into etiological and treatment studies. Majority of these selected studies were recently published and from developed countries. Whole blood samples were the most studied common tissues. Bisulfite conversion, along with pyrosequencing, was widely used to test the DNA methylation level across all the studies. High heterogeneity existed among the studies in terms of experimental and statistical methodologies and study designs. As recommended by the Cochrane guideline, a systematic review without meta-analysis should be undertaken. This review has, in general, found that DNA methylation modifications were associated with depression. Subgroup analyses showed that most studies found BDNF and SLC6A4 hypermethylations to be associated with MDD or depression in general. In contrast, studies on NR3C1, OXTR, and other genes, which were tested by only few studies, reported mixed findings. More longitudinal studies using standardized experimental and laboratory methodologies are needed in future studies to enable more systematical comparisons and quantitative synthesis.

DNA Methylation Signatures of Depressive Symptoms in Middle-aged and Elderly Persons: Meta-analysis of Multiethnic Epigenome-wide Studies

IMPORTANCE

Depressive disorders arise from a combination of genetic and environmental risk factors. Epigenetic disruption provides a plausible mechanism through which gene-environment interactions lead to depression. Large-scale, epigenome-wide studies on depression are missing, hampering the identification of potentially modifiable biomarkers.

OBJECTIVE

To identify epigenetic mechanisms underlying depression in middle-aged and elderly persons, using DNA methylation in blood.

DESIGN, SETTING, AND PARTICIPANTS

To date, the first cross-ethnic meta-analysis of epigenome-wide association studies (EWAS) within the framework of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was conducted. The discovery EWAS included 7948 individuals of European origin from 9 population-based cohorts. Participants who were assessed for both depressive symptoms and whole-blood DNA methylation were included in the study. Results of EWAS were pooled using sample-size weighted meta-analysis. Replication of the top epigenetic sites was performed in 3308 individuals of African American and European origin from 2 population-based cohorts.

MAIN OUTCOMES AND MEASURES

Whole-blood DNA methylation levels were assayed with Illumina-Infinium Human Methylation 450K BeadChip and depressive symptoms were assessed by questionnaire.

RESULTS

The discovery cohorts consisted of 7948 individuals (4104 [51.6%] women) with a mean (SD) age of 65.4 (5.8) years. The replication cohort consisted of 3308 individuals (2456 [74.2%] women) with a mean (SD) age of 60.3 (6.4) years. The EWAS identified methylation of 3 CpG sites to be significantly associated with increased depressive symptoms: cg04987734 (P = 1.57 × 10-08; n = 11 256; CDC42BPB gene), cg12325605 (P = 5.24 × 10-09; n = 11 256; ARHGEF3 gene), and an intergenic CpG site cg14023999 (P = 5.99 × 10-08; n = 11 256; chromosome = 15q26.1). The predicted expression of the CDC42BPB gene in the brain (basal ganglia) (effect, 0.14; P = 2.7 × 10-03) and of ARHGEF3 in fibroblasts (effect, -0.48; P = 9.8 × 10-04) was associated with major depression.

CONCLUSIONS AND RELEVANCE

This study identifies 3 methylated sites associated with depressive symptoms. All 3 findings point toward axon guidance as the common disrupted pathway in depression. The findings provide new insights into the molecular mechanisms underlying the complex pathophysiology of depression. Further research is warranted to determine the utility of these findings as biomarkers of depression and evaluate any potential role in the pathophysiology of depression and their downstream clinical effects.

The functional variant rs334558 of GSK3B is associated with remission in patients with depressive disorders

Purpose

GSK3B and AKT1 genes have been implicated in the pathogenesis of a number of psychiatric and neurological disorders. Furthermore, their genetic variants are associated with response to antidepressant pharmacotherapy. As the evidence is still incomplete and inconsistent, continuing efforts to investigate the role of these two genes in the pathogenesis and treatment of brain disorders is necessary. The aim of our study was thus to evaluate the association of variants of these two genes with depressive disorders and drug treatment response.

Patients and methods

In the present study, 222 patients with a depressive disorder who underwent pharmacological antidepressant treatment were divided into remitters and non-remitters following a 28-day course of pharmacotherapy. The association of a depressive disorder and remission rates with polymorphisms rs334558 in the GSK3B gene and rs1130214 and rs3730358 in the AKT1 gene was evaluated with a chi-square test.

Results

Neither of the studied genetic variants was associated with a depressive disorder. Furthermore, frequencies of alleles and genotypes for rs1130214 and rs3730358 were not different in the groups of remitters and non-remitters. However, the activating allele T of the functional polymorphism rs334558 was significantly associated with remission, when all types of antidepressant drugs were included. This association continued as a trend when only patients taking selective serotonin reuptake inhibitors were considered.

Conclusion

The present study provides support that the functional polymorphism rs334558 of GSK3B may play a role as a useful genetic and pharmacogenetic biomarker in the framework of personalized medicine approach.

Clinical application of antidepressant pharmacogenetics: Considerations for the design of future studies

A frustrating inertia has affected the development of clinical applications of antidepressant pharmacogenetics and personalized treatments of depression are still lacking 20 years after the first findings. Candidate gene studies provided replicated findings for some polymorphisms, but each of them shows at best a small effect on antidepressant efficacy and the cumulative effect of different polymorphisms is unclear. Further, no candidate was immune by at least some negative studies. These considerations give rise to some concerns about the clinical benefits of currently available pharmacogenetic tests since they are based on the results of candidate gene studies. Clinical guidelines in fact suggest that only polymorphisms that alter cytochrome 2D6 or 2C19 enzymatic activity probably provide useful clinical indications, while variants in genes involved in antidepressant pharmacodynamics have no recommended clinical applications. The present review discusses possible strategies to facilitate the identification of genetic biomarkers with clinical usefulness in guiding antidepressant treatments. These include analysis methods for the study of the polygenic/omnigenic nature of antidepressant response, the prioritization of polymorphisms on the basis of functional considerations, the incorporation of clinical-demographic predictors in pharmacogenetic studies (e.g. mixed polygenic and clinical risk scores), the application of methodological improvements to the design of future studies in order to maximize the comparability of results and improve power.

DNA methylation and antipsychotic treatment mechanisms in schizophrenia: Progress and future directions

Antipsychotic response in schizophrenia is a complex, multifactorial trait influenced by pharmacogenetic factors. With genetic studies thus far providing little biological insight or clinical utility, the field of pharmacoepigenomics has emerged to tackle the so-called "missing heritability" of drug response in disease. Research on psychiatric disorders has only recently started to assess the link between epigenetic alterations and treatment outcomes. DNA methylation, the best characterised epigenetic mechanism to date, is discussed here in the context of schizophrenia and antipsychotic treatment outcomes. The majority of published studies have assessed the influence of antipsychotics on methylation levels in specific neurotransmitter-associated candidate genes or at the genome-wide level. While these studies illustrate the epigenetic modifications associated with antipsychotics, very few have assessed clinical outcomes and the potential of differential DNA methylation profiles as predictors of antipsychotic response. Results from other psychiatric disorder studies, such as depression and bipolar disorder, provide insight into what may be achieved by schizophrenia pharmacoepigenomics. Other aspects that should be addressed in future research include methodological challenges, such as tissue specificity, and the influence of genetic variation on differential methylation patterns.

An epigenome-wide methylation study of healthy individuals with or without depressive symptoms

Major depressive disorder is a common psychiatric disorder that is thought to be triggered by both genetic and environmental factors. Depressive symptoms are an important public health problem and contribute to vulnerability to major depression. Although a substantial number of genetic and epigenetic studies have been performed to date, the detailed etiology of depression remains unclear and there are no validated biomarkers. DNA methylation is one of the major epigenetic modifications that play diverse roles in the etiology of complex diseases. In this study, we performed an epigenome-wide association study (EWAS) of DNA methylation on subjects with (N = 20) or without (N = 27) depressive symptoms in order to examine whether different levels of DNA methylation were associated with depressive tendencies. Employing methylation-array technology, a total of 363,887 methylation sites across the genomes were investigated and several candidate CpG sites associated with depressive symptoms were identified, especially annotated to genes linked to a G-protein coupled receptor protein signaling pathway. These data provide a strong impetus for validation studies using a larger cohort and support the possibility that G-protein coupled receptor protein signaling pathways are involved in the pathogenesis of depression.

BDNF Plasma Levels and BDNF Exon IV Promoter Methylation as Predictors for Antidepressant Treatment Response

Major problems of current antidepressant pharmacotherapy are insufficient response rates and difficulties in response prediction. We recently provided preliminary evidence in a small study that patients with major depressive disorder (MDD) with a hypomethylation of the CpG-87 site of the promoter IV region of the brain-derived neurotrophic factor (BDNF) gene are less likely to benefit from antidepressants. Here, we aimed at replicating this finding in a secondary analysis of 561 MDD patients (mean age 40.0 ± 11.9 years, 56% female) included into the Early Medication Change study (EMC). We measured BDNF exon IV promoter and p11 gene methylation at Baseline (BL) as well as BDNF-plasma-levels (pBDNF) at BL and day 14 and related them to treatment outcome. Although we were not able to replicate the predictor function of hypomethylation of the BDNF exon IV promoter, a subgroup of patients with severe depression (Hamilton Depression Rating Scale [HAMD-17] ≥ 25) (n = 199) and hypermethylation at CpG-87 of the BDNF exon IV promoter had significantly higher remission rates than patients without a methylation (p = 0.032). We also found that 421 (75%) of 561 patients showed an early improvement (≥ 20% HAMD-17 reduction after 2 weeks), which was associated with a 4.24-fold increased likelihood to remit at study end compared to the 140 patients without early improvement. However, specificity of response prediction of early improvement was low (34%) and false positive rate high (66%). The combination of early improvement with a pBDNF increase between BL and day 14, however, increased the specificity of response prediction from 34 to 76%, and the combination with methylation of the CpG-87 site of the BDNF exon IV promoter from 34 to 62%. Thus, the combined markers reduced false positives rates from 66 to 24% and 38%, respectively. Methylation at other sites or p11 promoter methylation failed to increase specificity of early improvement prediction. In sum, the results add to previous findings that BDNF, BDNF promoter methylation and the combination of clinical and biological markers may be interesting candidates for therapy response prediction which has to be confirmed in further studies. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT00974155, identifier: NCT00974155.