Pharmacogenetic considerations in the treatment of psychiatric disorders

Methylome-wide association study of different responses to risperidone in schizophrenia

Background: Accumulating evidence shows that DNA methylation plays a role in antipsychotic response. However, the mechanisms by which DNA methylation changes are associated with antipsychotic responses remain largely unknown. Methods: We performed a methylome-wide association study (MWAS) to evaluate the association between DNA methylation and the response to risperidone in schizophrenia. Genomic DNA methylation patterns were assessed using the Agilent Human DNA Methylation Microarray. Results: We identified numerous differentially methylated positions (DMPs) and regions (DMRs) associated with antipsychotic response. CYP46A1, SPATS2, and ATP6V1E1 had the most significant DMPs, with p values of 2.50 × 10^-6, 3.53 × 10^-6, and 5.71 × 10^-6, respectively. The top-ranked DMR was located on chromosome 7, corresponding to the PTPRN2 gene with a Šidák-corrected p-value of 9.04 × 10^-13. Additionally, a significant enrichment of synaptic function and neurotransmitters was found in the differentially methylated genes after gene ontology and pathway analysis. Conclusion: The identified DMP- and DMR-overlapping genes associated with antipsychotic response are related to synaptic function and neurotransmitters. These findings may improve understanding of the mechanisms underlying antipsychotic response and guide the choice of antipsychotic in schizophrenia.

Mechanistic insights into the role of plant polyphenols and their nano-formulations in the management of depression

Depression is a condition characterized by low mood and an aversion to activity, that causes behavioral problems, poor quality of life and limits daily life activities. It is considered as the fourth leading cause of disability worldwide. Selective Serotonin Reuptake Inhibitors (SSRIs) Monoamine Oxidase (MAO) inhibitors, Tricyclic Antidepressants (TCAs), and atypical antidepressants are some of the conventional medications used to treat depression. However, only about half of patients with major depressive disorder (MDD) respond effectively to first-line antidepressant therapy. Additionally, there are a number of drawbacks to standard antidepressants, such as anti-cholinergic side effects, drug-drug interactions, and food-drug interactions, which prompts researchers to look at alternative approaches to the treatment of depression. Medicinal plants and their metabolites are extensively tested for their efficacy against depression. Electronic databases such as Google scholar, Science Direct, SciFinder and PubMed were used to search relevant literature on the role of polyphenols in depression. Plants-derived Polyphenols represent a major class of compounds extensively distributed in plants. Number of polyphenols have demonstrated antidepressant activity, among which berberine, piperine, curcumin, naringenin, ascorbic acid and ginsenosides are extensively evaluated. The medicinal plants and their derived compounds mediated synthesized green nanoparticles have also exhibited considerable efficacy in the management of depression. The therapeutic effects of these phytochemicals is mediated via differentiation and inhibition of neuronal cell apoptosis, promotion of neuronal cell survival and modulation of key neurotransmitters. The aim of this study is to review compressively the chemical, pharmacological and neurological evidence showing the potential of polyphenols in depression.

Targeting Unmet Clinical Needs in the Treatment of Alcohol Use Disorder

Alcohol Use Disorder (AUD) is a chronic psychiatric disorder marked by impaired control over drinking behavior that poses a significant challenge to the individual, their community, the healthcare system and economy. While the negative consequences of chronic excessive alcohol consumption are well-documented, effective treatment for AUD and alcohol-associated diseases remains challenging. Cognitive and behavioral treatment, with or without pharmaceutical interventions, remain the most commonly used methods; however, their efficacy is limited. The development of new treatment protocols for AUD is challenged by difficulty in accurately measuring patterns of alcohol consumption in AUD patients, a lack of a clear understanding of the neuropsychological basis of the disorder, the high likelihood of AUD patients relapsing after receiving treatment, and the numerous end-organ comorbidities associated with excessive alcohol use. Identification and prediction of patients who may respond well to a certain treatment mechanism as well as clinical measurement of a patient's alcohol exposure are bottlenecks in AUD research which should be further addressed. In addition, greater focus must be placed on the development of novel strategies of drug design aimed at targeting the integrated neural pathways implicated in AUD pathogenesis, so that next-generation AUD treatment protocols can address the broad and systemic effects of AUD and its comorbid conditions.

An Investigation into the Association Between Dopamine Receptor D1 Multilocus Genetic Variation, Multiparametric Magnetic Resonance Imaging, and Antidepressant Treatment

BACKGROUND

Combining genetic variants with neuroimaging phenotypes may facilitate understanding of the biological mechanisms for the etiology and pharmacology of antidepressant treatment of major depressive disorder (MDD).

PURPOSE

To explore the latent pathway of dopamine gene-hierarchical brain network-antidepressant treatment.

STUDY TYPE

Retrospective.

POPULATION

One hundred and sixty-eight MDD inpatients divided into responders (N = 98) or nonresponders (N = 70) based on the treatment outcome of antidepressant.

FIELD STRENGTH/SEQUENCE

Diffusion tensors imaging and resting-state functional magnetic resonance imaging at 3.0T using echo-planar sequence.

ASSESSMENT

Four genetic variations of the dopamine receptor D1 (DRD1) were genotyped. Strengths of rich-club, feeder, and local connections were calculated based on the rich-club organizations of structural and functional brain networks at baseline and following 4 weeks of selective serotonin reuptake inhibitor (SSRI) therapy.

STATISTICAL TESTS

Logistic and linear regressions were used to analyze the impact of DRD1 multilocus genetic profile score on the treatment response of SSRI, and their associations with strengths of rich-club, feeder, and local connections. Mediation models were developed to explore the mediation role of rich-club organizations on the relationship between DRD1 and SSRI therapy response. A P value <0.05 was considered to be statistically significant.

RESULTS

Multiple genetic variations of DRD1 were significantly related to the strengths of feeder connections both in structural and functional networks, and to the treatment response of SSRI. Furthermore, the strength of the structural feeder connection significantly modulated the effect of DRD1 variants on SSRI treatment outcome.

DATA CONCLUSION

DRD1 displayed close connections both with SSRI treatment outcome and rich-club organizations of structural and functional data. Moreover, structural feeder connection played a mediating role in the relationship between DRD1 and antidepressant therapy.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 4.

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.

Influence of genetic polymorphisms in homocysteine and lipid metabolism systems on antidepressant drug response

BACKGROUND

Variation in genes implicated in homocysteine and lipid metabolism systems may influence antidepressant response for patients with major depressive disorder (MDD). This study aimed to investigate whether association of polymorphisms on the MTHFR, ApoE and ApoA4 genes with the treatment response in MDD subjects.

METHODS

A total of 281 Han Chinese MDD patients received a single antidepressant drug (SSRI or SNRI) for at least 6 weeks, among whom 275 were followed up for 8 weeks. Their response to 6 weeks' treatment and remission to 8 weeks' treatment with antidepressant drugs was determined by changes in the 17-item Hamilton Depression Rating Scale (HARS-17) score. Single SNP and haplotype associations with treatment response were analyzed by UNPHASED 3.0.13. Logistic regression analysis was used to explore the interactions between genotypes and gender or drug type on treatment outcome, only those SNPs that had interactional association with gender or drug type were subjected to further stratified analysis.

RESULTS

In total group, the haplotype (C-A) in MTHFR (rsl801133 and rs1801131) and the ApoE rs405509 AA genotype were significantly associated with better efficacy of antidepressants; In gender subgroups, only haplotype (C-A) in MTHFR (rsl801133 and rs1801131) was significantly associated with better efficacy of antidepressants in male subgroup; In drug type subgroup, the haplotype (C-A) in MTHFR (rsl801133 and rs1801131) and haplotype (G-C) in ApoE (rs7412 and rs405509) were associated with better efficacy of antidepressants in SNRI treated subgroup; The ApoA4 rs5092 G allele and GG genotype were associated with worse efficacy of antidepressants in SNRI treated subgroup.

CONCLUSIONS

Genetic polymorphisms in homocysteine and lipid metabolism systems are associated with antidepressant response, particularly for the interactions of the certain genetic with gender or drug type.

The Potential Role of Regulatory Genes (DNMT3A, HDAC5, and HDAC9) in Antipsychotic Treatment Response in South African Schizophrenia Patients

Despite advances in pharmacogenetics, the majority of heritability for treatment response cannot be explained by common variation, suggesting that factors such as epigenetics may play a key role. Regulatory genes, such as those involved in DNA methylation and transcriptional repression, are therefore excellent candidates for investigating antipsychotic treatment response. This study explored the differential expression of regulatory genes between patients with schizophrenia (chronic and antipsychotic-naïve first-episode patients) and healthy controls in order to identify candidate genes for association with antipsychotic treatment response. Seven candidate differentially expressed genes were identified, and four variants within these genes were found to be significantly associated with treatment response (DNMT3A rs2304429, HDAC5 rs11079983, and HDAC9 rs1178119 and rs11764843). Further analyses revealed that two of these variants (rs2304429 and rs11079983) are predicted to alter the expression of specific genes (DNMT3A, ASB16, and ASB16-AS1) in brain regions previously implicated in schizophrenia and treatment response. These results may aid in the development of biomarkers for antipsychotic treatment response, as well as novel drug targets.

BDNF as a pharmacogenetic target for antipsychotic treatment of schizophrenia

Antipsychotic drugs remain the mainstay of pharmacotherapy for schizophrenia. As there are large individual variations in efficacy and side-effects of antipsychotic drugs, there is a strong demand for personalized medication to treat schizophrenia. Pharmacogenetic research into antipsychotic drugs has examined a number of genetic variants and only a few polymorphisms have been found which promise to be associated with the therapeutic efficacy and side-effects of antipsychotic drugs. Brain-derived neurotrophic factor (BDNF) is a neurotrophin that plays a major role in neurogenesis and neuroplasticity, and in the modulation of several neurotransmitter systems including the dopaminergic system involved in the pathophysiology of schizophrenia. This review focused on the association between the BDNF gene Val66Met polymorphism and antipsychotic drugs. The BDNF Val66Met polymorphism has been related to the pathophysiology of schizophrenia, psychotic symptomatology, cognition, efficacy and side-effects of antipsychotic drugs. The BDNF Val66Met variants could be a promising target for antipsychotic medication options or developing next generation antipsychotic drugs. However, some studies showed inconsistent results due to sample size, ethnic differences and different antipsychotic drugs. Further studies will be required in this area to confirm the effect of the BDNF Val66Met polymorphism in the pathophysiology of schizophrenia and patients' response to antipsychotic drugs, especially in a larger sample size and in different ethnic populations.

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.

Toward a Global Roadmap for Precision Medicine in Psychiatry: Challenges and Opportunities

Mental disorders represent a major public health burden worldwide. This is likely to rise in the next decade, with the highest increases predicted to occur in low- and middle-income countries. Current psychotropic medication treatment guidelines focus on uniform approaches to the treatment of heterogeneous disorders and achieve only partial therapeutic success. Developing a global precision medicine approach in psychiatry appears attractive, given the value of this approach in other fields of medicine, such as oncology and infectious diseases. In this horizon scanning analysis, we review the salient opportunities and challenges for precision medicine in psychiatry over the next decade. Variants within numerous genes involved in a range of pathways have been implicated in psychotropic drug response and might ultimately be used to guide choice of pharmacotherapy. Multipronged approaches such as multi-omics (genomics, proteomics, metabolomics) analyses and systems diagnostics together with high-throughput sequencing and genotyping technologies hold promise for identifying precise and targeted treatments in mental disorders. To date, however, the vast majority of pharmacogenomics work has been undertaken in high-income countries on a relatively small proportion of the global population, and many other challenges face the field. Opportunities and challenges for establishing a global roadmap for precision medicine in psychiatry are discussed in this article.

TPH-2 Polymorphisms Interact with Early Life Stress to Influence Response to Treatment with Antidepressant Drugs

BACKGROUND

Variation in genes implicated in monoamine neurotransmission may interact with environmental factors to influence antidepressant response. We aimed to determine how a range of single nucleotide polymorphisms in monoaminergic genes influence this response to treatment and how they interact with childhood trauma and recent life stress in a Chinese sample. An initial study of monoaminergic coding region single nucleotide polymorphisms identified significant associations of TPH2 and HTR1B single nucleotide polymorphisms with treatment response that showed interactions with childhood and recent life stress, respectively (Xu et al., 2012).

METHODS

A total of 47 further single nucleotide polymorphisms in 17 candidate monoaminergic genes were genotyped in 281 Chinese Han patients with major depressive disorder. Response to 6 weeks' antidepressant treatment was determined by change in the 17-item Hamilton Depression Rating Scale score, and previous stressful events were evaluated by the Life Events Scale and Childhood Trauma Questionnaire-Short Form.

RESULTS

Three TPH2 single nucleotide polymorphisms (rs11178998, rs7963717, and rs2171363) were significantly associated with antidepressant response in this Chinese sample, as was a haplotype in TPH2 (rs2171363 and rs1487278). One of these, rs2171363, showed a significant interaction with childhood adversity in its association with antidepressant response.

CONCLUSIONS

These findings provide further evidence that variation in TPH2 is associated with antidepressant response and may also interact with childhood trauma to influence outcome of antidepressant treatment.

Pharmacogenetics of citalopram-related side effects in children with depression and/or anxiety disorders

Pharmacogenetic approach to antidepressant (AD) response is a promising avenue toward individualizing AD treatment. This is particularly relevant in pediatric populations because of concerns about the suicide risk of serotonin selective reuptake inhibitors (SSRIs), resulting in a black-box warning. However, to date, no specific gene or polymorphism has been consistently implicated as a marker of AD side effect (SE) in the pediatric population. The aim of this study was to examine the association between polymorphisms in genes related to the serotonergic system and citalopram SE's in children and adolescents with major depressive disorder (MDD)/dysthymia and/or anxiety disorders. Outpatients (N = 87, 44 % males), aged 7-18 years with a DSM-IV-TR diagnosis of MDD/dysthymia and/or an anxiety disorder were treated in an 8-week open trial with 20-40 mg/day of citalopram. SE's were rated using a questionnaire devised specifically for this study. Association analysis between known/candidate genetic variants in three genes (5-HTR2A, 5-HTR1Dβ, 5-HTR2C) and SE's was conducted. Agitation was more common in boys than girls (male:female 42.1 vs. 18.7 %, χ ² = 5.61, df = 1, p = 0.018). Subjects with 5-HTR1Dβ CC genotype showed more agitation vs. both CG and GG genotypes (CC:CG:GG 71.4 vs. 33.3 vs. 18.1 %, χ ² = 8.99, df = 2, p = 0.011). The 5-HTR1Dβ CC genotype was associated with more reports of agitation. It has been suggested that agitation may be an intermediate phenotype to suicidal behavior. Thus, it seems that 5-HTR1Dβ polymorphism may be involved in citalopram-related agitation in children and adolescents treated for depression and/or anxiety.

Pharmacogenetic study of second-generation antipsychotic long-term treatment metabolic side effects (the SLiM Study): rationale, objectives, design and sample description

AIM

Weight gain is an important and common side effect of second generation antipsychotics (SGAs). Furthermore, these drugs can induce other side effects associated with higher cardiovascular morbidity and mortality, such as insulin resistance, diabetes or metabolic syndrome. Preliminary studies show that inter-individual genetic differences produce varying degrees of vulnerability to the different SGA-induced side effects. The Second-generation antipsychotic Long-term treatment Metabolic side effects (SLiM) study aims to identify clinical, environmental and genetic factors that explain inter-individual differences in weight gain and metabolic changes in drug-naïve patients after six months of treatment with SGAs.

MATERIALS AND METHODS

The SLIM study is a multicenter, observational, six-month pharmacogenetic study where a cohort of 307 drug-naïve paediatric and adult patients (age range 8.8-90.1 years) and a cohort of 150 age- and sex- matched healthy controls (7.8-73.2 years) were recruited.

RESULTS

This paper describes the rationale, objectives and design of the study and provides a description of the sample at baseline.

CONCLUSIONS

Results from the SLiM study will provide a better understanding of the clinical, environmental, and genetic factors involved in weight gain and metabolic disturbances associated with SGA treatment.

Strengths and weaknesses of pharmacogenetic studies of antipsychotic drugs: the potential value of the PEPs study

The successful application of pharmacogenetics in routine clinical practice is still a long way from becoming a reality. In order to favor the transfer of pharmacogenetic results to clinical practice, especially in psychiatry, these studies must be optimized. This article reviews the strengths and weaknesses that characterize pharmacogenetic studies in psychiatry and condition their implementation in clinical practice. We also include recommendations for improving the design of pharmacogenetic studies, which may convert their limitations into strengths and facilitate the implementation of their results into clinical practice. Finally, we discuss the potential value of naturalistic, prospective, multicenter and coordinated projects such as the 'Phenotype-genotype and environmental interaction. Application of a predictive model in first psychotic episodes' (known as the PEPs study, from the Spanish abbreviation) in pharmacogenetic studies.

Variation in the catechol-O-methyltransferase (COMT) gene and treatment response to venlafaxine XR in generalized anxiety disorder

Antidepressant drugs are the preferred choice for the treatment of generalized anxiety disorder (GAD). However, the choice of pharmacotherapy is determined on a trial-and-error basis, as the underlying mechanisms of treatment response are unknown. We examined whether the COMT gene, which has been known to play a role in antidepressant treatment response in major depressive disorder (MDD), has a pharmacogenetic effect in antidepressant treatment response in GAD. In our study, 156 patients diagnosed with GAD received venlafaxine XR treatment as part of an 18-month relapse prevention study. Genotypes were obtained for the COMT functional variant rs4680 (Val158Met) for all patients; however, pharmacogenetic analysis was only conducted for the European American population (n=112). We found no significant association between our primary Hamilton Anxiety Scale outcome measure and rs4680. However, we did find a nominally significant allelic association between this variant and a secondary treatment outcome measure (CGI-I) in our European American population (n=112). Furthermore, we show a slight dominant effect of the A-allele with the CGI-I measure in the European American population indicating a possible pharmacogenetic role of rs4680 in antidepressant treatment outcome in GAD. Further studies in a larger population are needed to confirm this effect.

Influence and interaction of genetic polymorphisms in the serotonin system and life stress on antidepressant drug response

Variation in genes implicated in serotonin neurotransmission may interact with environmental factors to influence antidepressant response. We aimed to determine how a range of polymorphisms in serotonergic genes determine this response to treatment and how they interact with childhood trauma and recent life stress in a Chinese sample. In total, 14 single nucleotide polymorphisms (SNPs) in coding regions of 10 serotonergic genes (HTR1A, HTR1B, HTR1D, HTR2A, HTR3A, HTR3C, HTR3D, HTR3E, HTR5A and TPH2) were genotyped in 308 Chinese Han patients with major depressive disorder. Response to 6 weeks' antidepressant treatment was determined by change in the 17-item Hamilton Depression Rating Scale (HDRS-17) score, and previous stressful events were evaluated by the Life Events Scale (LES) and Childhood Trauma Questionnaire-Short Form (CTQ-SF). Two 5-HT1B receptor SNPs (rs6296 and rs6298) and one tryptophan hydroxylase2 (rs7305115) SNP were significantly associated with antidepressant response in this Chinese sample, as was a haplotype in TPH2 (rs7305115 and rs4290270). A gene-gene interaction on antidepressant response was found between SNPs in HTR1B, HTR3A and HTR5A in female subjects. The HTR1B SNPs demonstrated interaction with recent stress, while that for TPH2 interacted with childhood trauma to influence antidepressant response.

Influence and interaction of genetic polymorphisms in catecholamine neurotransmitter systems and early life stress on antidepressant drug response

BACKGROUND

Catecholamine neurotransmission plays an important role in major depression. Variation in genes implicated in the synthesis and signal transduction of catecholamines (norepinephrine and dopamine) may interact with environmental factors to affect the outcome of antidepressant treatment. We aimed to determine how a range of polymorphisms in noradrenergic and dopaminergic genes influence this response to treatment and how they interact with childhood trauma and recent life stress in a Chinese sample.

METHODS

In a sample of 308 Chinese Han patients with major depressive disorder, 13 single nucleotide polymorphisms (SNPs) in coding regions of six genes (MAOA, SLC6A2, TH, COMT, DRD2, DRD3) with minor allele frequencies >5% were successfully genotyped from an initial series of 35 SNPs in 11 candidate genes associated with catecholamine neurotransmission. The responses to 6 weeks' treatment with antidepressant drugs was determined by changes in the 17-item Hamilton Depression Rating Scale (HAMD-17) score, and previous stressful events were evaluated by the Life Events Scale (LES) and Childhood Trauma Questionnaire-Short Form (CTQ-SF). Single SNP and haplotype associations with treatment response were analysed by UNPHASED 3.0.13, gene-gene interactions were analysed by generalized multifactor dimensionality reduction (GMDR) and gene-environment interactions by logistic regression.

RESULTS

A haplotype in MAOA (rs1137070 and rs6323) was significantly associated with antidepressant response in the total group, the nonSSRI subgroup and the female subgroup. Two haplotypes in COMT (involving rs4633, rs4818 and rs769224) were significantly associated with antidepressant response in the nonSSRI subgroup. The SLC6A2 SNPs interacted with childhood trauma to influence antidepressant response.

CONCLUSIONS

A haplotype in MAOA and two haplotypes in COMT are found to be associated with antidepressant treatment response in this sample. Stressors in early life may interact with polymorphisms in SLC6A2 to influence response to antidepressant treatment.

The use of referenced-EEG (rEEG) in assisting medication selection for the treatment of depression

OBJECTIVE

To evaluate the efficacy of rEEG(®)-guided pharmacotherapy for the treatment of depression in those circumstances where rEEG and STAR*D provided different recommendations.

MATERIALS AND METHODS

This was a randomized, single-blind, parallel group, 12 center, US study of rEEG-guided pharmacotherapy vs. the most effective treatment regimens reported in the NIH sponsored STAR*D study. Relatively treatment-resistant subjects ≥18 years who failed one or more antidepressants were required to have a QIDS-16-SR score ≥13 and a MADRS score ≥26 at baseline. All subjects underwent a washout of all current medications (with some protocol-specified exceptions) for at least five half-lives before receiving a QEEG and rEEG report. Subjects randomized to rEEG were assigned a regimen based on the rEEG report. Control subjects who had failed only SSRI's in their current episode were randomized to receive venlafaxine XR. Control subjects who had failed antidepressants from ≥2 classes of antidepressants were randomized to receive a regimen from Steps 2-4 of the STAR*D study. Treatment lasted 12 weeks. The primary outcome measures were change from baseline for self-rated QIDS-SR16 and Q-LES-Q-SF.

RESULTS

A total of 114 subjects were randomized and 89 subjects were evaluable. rEEG-guided pharmacotherapy exhibited significantly greater improvement for both primary endpoints, QIDS-SR16 (-6.8 vs. -4.5, p<0.0002) and Q-LES-Q-SF (18.0 vs. 8.9, p<0.0002) compared to control, respectively, as well as statistical superiority in 9 out of 12 secondary endpoints.

CONCLUSIONS

These results warrant additional studies to determine the role of rEEG-guided psychopharmacology in the treatment of depression. If these results were confirmed, rEEG-guided pharmacotherapy would represent an easy, relatively inexpensive, predictive, objective office procedure that builds upon clinical judgment to guide antidepressant medication choice.

Overview of the genetics of major depressive disorder

Major depressive disorder (MDD) is a common psychiatric illness with high levels of morbidity and mortality. Despite intensive research during the past several decades, the neurobiological basis and pathophysiology of depressive disorders remain unknown. Genetic factors play important roles in the development of MDD, as indicated by family, twin, and adoption studies, and may reveal important information about disease mechanisms. This article describes recent developments in the field of psychiatric genetics, with a focus on MDD. Early twin studies, linkage studies, and association studies are discussed. Recent findings from genome-wide association studies are reviewed and future directions discussed. Despite all efforts, thus far, no single genetic variation has been identified to increase the risk of depression substantially. Genetic variants are expected to have only small effects on overall disease risk, and multiple genetic factors in conjunction with environmental factors are likely necessary for the development of MDD. Future large-scale studies are needed to dissect this complex phenotype and to identify pathways involved in the etiology of MDD.

Gene-Environment Interaction: A Genetic-Epidemiological Approach

Classical epidemiology addresses the distribution and determinants of diseases in populations, and the factors associated with disease causation, with the aim of preventing disease. Both genetic and environmental factors may contribute to susceptibility, and it is still unclear how these factors interact in their influence on risk. Genetic epidemiology is the field which incorporates concepts and methods from different disciplines including epidemiology, genetics, biostatistics, clinical and molecular medicine, and their interaction is crucial to understanding the role of genetic and environmental factors in disease processes. The study of gene-environment interaction is central in the field of genetic epidemiology. Gene-environment interaction is defined as »a different effect of an environmental exposure on disease risk in persons with different genotypes,« or, alternatively, »a different effect of a genotype on disease risk in persons with different environmental exposures.« Five biologically plausible models are described for the relations between genotypes and environmental exposures, in terms of their effects on disease risk. Therefore, the study of gene-environment interaction is important for improving accuracy and precision in the assessment of both genetic and environmental factors, especially in disorders of less defined etiology. Genetic epidemiology is also applied at the various levels of disease prevention.