Interaction of serotonin-related genes affects short-term antidepressant response in major depressive disorder

Genetic Landscape of Major Depressive Disorder: Assessment of Potential Diagnostic and Antidepressant Response Markers

BACKGROUND

The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation.

METHODS

We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values.

RESULTS

A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response.

CONCLUSIONS

The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.

Predicting the Treatment Outcomes of Antidepressants Using a Deep Neural Network of Deep Learning in Drug-Naïve Major Depressive Patients

Predicting the treatment response to antidepressants by pretreatment features would be useful, as up to 70–90% of patients with major depressive disorder (MDD) do not respond to treatment as expected. Therefore, we aim to establish a deep neural network (DNN) model of deep learning to predict the treatment outcomes of antidepressants in drug-naïve and first-diagnosis MDD patients during severe depressive stage using different domains of signature profiles of clinical features, peripheral biochemistry, psychosocial factors, and genetic polymorphisms. The multilayer feedforward neural network containing two hidden layers was applied to build models with tenfold cross-validation. The areas under the curve (AUC) of the receiver operating characteristic curves were used to evaluate the performance of the models. The results demonstrated that the AUCs of the model ranged between 0.7 and 0.8 using a combination of different domains of categorical variables. Moreover, models using the extracted variables demonstrated better performance, and the best performing model was characterized by an AUC of 0.825, using the levels of cortisol and oxytocin, scales of social support and quality of life, and polymorphisms of the OXTR gene. A complex interactions model developed through DNN could be useful at the clinical level for predicting the individualized outcomes of antidepressants.

Serotonergic receptor gene polymorphism and response to selective serotonin reuptake inhibitors in ethnic Malay patients with first episode of major depressive disorder

The polymorphisms of the 5HTR1A and 5HTR2A receptor genes (rs6295C/G and rs6311G/A) have been evaluated for association with SSRI treatment outcome in various populations with different results. The present study was carried out to determine the association between genotypes of HTR1A-rs6295 and HTR2A-rs6311 with SSRI treatment outcome among the ethnic Malay patients diagnosed with first-episode major depressive disorder (MDD). The patients were recruited from four tertiary hospitals in the Klang Valley region of Malaysia. Predefined efficacy phenotypes based on 25% (partial early response) and 50% (clinical efficacy response) reduction in Montgomery Asberg Depression Rating Scale-self Rated score (MADRS-S) were adopted for assessment of treatment efficacy in this study. Self-reporting for adverse effects (AE) was documented using the Patient Rated Inventory of Side Effect (PRISE) after treatment with SSRI for up to 6 weeks. Adjusted binary logistic regression between genotypes of the polymorphism obtained using sequencing technique with the treatment outcome phenotypes was performed. The 142 patients recruited were made up of 96 females (67.6%) and 46 males (32.4%). Clinical efficacy and Partial early response phenotypes were not significantly associated with genotypes of HTR1A and HTR2A polymorphism. The GG genotype of HTR2A polymorphism has decreased odds for dizziness (CNS) and increased odds for poor concentration. The GA genotype increases the odd for excessive sweating, diarrhoea, constipation and blurred vision. The CC genotype of HTR1A-rs6295 decreases the odd for nausea/vomiting and increases the odd for anxiety. Thus, some genotypes of HTR1A and HTR2A polymorphism were associated with SSRI treatment outcomes in ethnic Malay MDD patients.

Dissecting diagnostic heterogeneity in depression by integrating neuroimaging and genetics

Depression is a heterogeneous and etiologically complex psychiatric syndrome, not a unitary disease entity, encompassing a broad spectrum of psychopathology arising from distinct pathophysiological mechanisms. Motivated by a need to advance our understanding of these mechanisms and develop new treatment strategies, there is a renewed interest in investigating the neurobiological basis of heterogeneity in depression and rethinking our approach to diagnosis for research purposes. Large-scale genome-wide association studies have now identified multiple genetic risk variants implicating excitatory neurotransmission and synapse function and underscoring a highly polygenic inheritance pattern that may be another important contributor to heterogeneity in depression. Here, we review various sources of phenotypic heterogeneity and approaches to defining and studying depression subtypes, including symptom-based subtypes and biology-based approaches to decomposing the depression syndrome. We review "dimensional," "categorical," and "hybrid" approaches to parsing phenotypic heterogeneity in depression and defining subtypes using functional neuroimaging. Next, we review recent progress in neuroimaging genetics (correlating neuroimaging patterns of brain function with genetic data) and its potential utility for generating testable hypotheses concerning molecular and circuit-level mechanisms. We discuss how genetic variants and transcriptomic profiles may confer risk for depression by modulating brain structure and function. We conclude by highlighting several promising areas for future research into the neurobiological underpinnings of heterogeneity, including efforts to understand sexually dimorphic mechanisms, the longitudinal dynamics of depressive episodes, and strategies for developing personalized treatments and facilitating clinical decision-making.

Associations between the 1438A/G, 102T/C, and rs7997012G/A polymorphisms of HTR2A and the safety and efficacy of antidepressants in depression: a meta-analysis

The correlations between hydroxytryptamine receptor 2A (HTR2A) gene polymorphisms (1438A/G, 102T/C, and rs7997012G/A) and the safety and efficacy of antidepressants in depression patients were constantly reported, but conclusions are debatable. This meta-analysis ascertained forty-two studies on the efficacy (including response and remission) and side-effect issued before February 2020. Pooled analyses indicated significant associations of 1438A/G polymorphism (16 studies, 1931 subjects) and higher response within dominant model (OR: 1.40, 95% CI: 1.12-1.76); rs7997012G/A polymorphism (nine studies, 1434 subjects) and higher remission in overall models (dominant model: OR: 1.30, 95% CI: 1.01-1.66; recessive model: OR: 2.20, 95% CI: 1.53-3.16; homozygote model: OR: 2.73, 95% CI: 1.78-4.17); 102T/C polymorphism (eight studies, 804 subjects) and reduced risk of side-effect within recessive (OR: 0.57, 95% CI: 0.4-0.83) and homozygote models (OR: 0.54, 95% CI: 0.29-0.99). For depression patients, genotyping of HTR2A polymorphisms is a promising tool for estimating the outcome and side-effect of antidepressants.

Association between genetic polymorphism and antidepressants in major depression: a network meta-analysis

This network meta-analysis was conducted to compare the predictive value of eight SNPs on the efficacy of antidepressants in major depressive disorder (MDD), including 5-HTTLPR, 5HTR2A (rs6311, rs6314, rs7997012 and rs6313), 5HTR2A (rs6295), BDNF (rs6265) and 5HTTSTin2. Databases were searched for related studies published up to December 2019. A total of 16 studies were included in this study. The predictive value were evaluated by the use of the odd ratios (OR) and drawing surface under the cumulative ranking curves (SUCRA). The pairwise meta-analysis indicated that in terms of overall response ratio, the SNPs were not associated with the efficacy of antidepressants in MDD. The result of this network meta-analysis suggested that there was no significant difference in predictive value of eight SNPs on the efficacy of antidepressants in MDD. More research is needed to explore the relationship between SNPs and antidepressant response.

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.

Pharmacogenetics of Antidepressants: from Genetic Findings to Predictive Strategies

The constantly growing contribution of depressive disorders to the global disease statistics calls for a growth of treatment effectiveness and optimization. Antidepressants are the most frequently prescribed medicines for depressive disorders. However, development of a standardized pharmacotherapeutic approach is burdened by the genomic heterogeneity, lack of reliable predictive biomarkers and variability of the medicines metabolism aggravated by multiple side effects of antidepressants. According to modern assessments up to 20 % of the genes expressed in our brain are involved in the pathogenesis of depression. Large-scale genetic and genomic research has found a number of potentially prognostic genes. It has also been proven that the effectiveness and tolerability of antidepressants directly depend on the variable activity of the enzymes that metabolize medicines. Almost all modern antidepressants are metabolized by the cytochrome P450 family enzymes. The most promising direction of research today is the GWAS (Genome-Wide Association Study) method that is aimed to link genomic variations with phenotypical manifestations. In this type of research genomes of depressive patients with different phenotypes are compared to the genomes of the control group containing same age, sex and other parameters healthy people. Notably, regardless of the large cohorts of patients analyzed, none of the GWA studies conducted so far can reliably reproduce the results of other analogous studies. The explicit heterogeneity of the genes associated with the depression pathogenesis and their pleiotropic effects are strongly influenced by environmental factors. This may explain the difficulty of obtaining clear and reproducible results. However, despite any negative circumstances, the active multidirectional research conducted today, raises the hope of clinicians and their patients to get a whole number of schedules how to achieve remission faster and with guaranteed results

Genotype, resilience and function and physical activity post hip fracture

BACKGROUND

Individuals who are resilient are more likely to engage in functional tasks and exercise post hip fracture. There may be a genetic predisposition to being resilient.

OBJECTIVES

This study tested the direct and indirect association of 10 candidate genes, age, cognition, gender, comorbidities, pain and social activity on resilience, function and exercise post hip fracture.

METHOD

This was a descriptive study including 172 community dwelling older adults. Measures included: age, gender, cognition (Modified Mini Mental Status Exam), comorbidities, social activities (self-report), DNA (GRM1, NTRK1, NTRK2, GNB3, NPY, SLC6A15. SLC6A4, BDNF, CR1TR1, FKBP5), pain (areas of pain and Numeric Rating Scale), function (Physical and Instrumental Activities of Daily Living; Lower Extremity Gains Score; Short Physical Performance Battery; Grip Strength) and exercise (Yale Physical Activity Scale).

RESULTS

The majority of participants were Caucasian (93%), 50% were women and the average age was 81.09 (SD = 7.42). There were significant associations between resilience and single nucleotide polymorphisms from GRM1, NTRK1, NTRK2, GNB3, NPY and SLC6A15. Resilience, age, cognition, social activity, pain and genetic variability were directly and/or indirectly associated with exercise and/or function.

DISCUSSION

This study highlights the importance of resilience for engagement in exercise and function after hip fracture and provides preliminary evidence for a genetic role for resilience.

Gender Disparity in the Risk of Hypertension in Subjects With Major Depressive Disorder

Objects: The aim of our study was to investigate whether major depressive disorder (MDD) increased the risk of hypertension using propensity score matching (PSM) in patients with MDD in Taiwan. Methods: In this study, we recruited all samples from a random sample sub-dataset of one million insured individuals from 2005. A total of 743,114 outpatients were included in our study. We used PSM (nearest neighbor matching) stratified by age, hospital level, insurance amount, and Charlson Comorbidity Index score. Results: The hazard ratio (HR) of hypertension was significantly greater in the male MDD outpatients (HR = 1.116, P = 0.004) than in the female MDD outpatients (HR = 0.93, P = 0.02). Using PSM, we selected 27,988 outpatients with hypertension and 27,988 outpatients without hypertension for a nested case-control study. In this analysis, female outpatients with MDD (relative risk = 0.852) had lower risks of hypertension. Male outpatients without/with MDD (relative risk = 1.987/3.018) showed a synergistic interaction with gender in which male patients had a higher risk of hypertension in a multiplicative model. Furthermore, MDD appeared to have an interaction effect with gender (HR = 1.82, P < 0.001) in the proportional hazards model analysis. Antidepressant use also increased the risk of hypertension (HR = 1.16, P < 0.001). Conclusions: There was gender disparity in the risk of hypertension in subjects with MDD. MDD outpatients who used antidepressants had a higher risk of suffering from hypertension. A large-scale, population-based study is warranted to generalize these results in the future.

The Interaction of TPH2 and 5-HT2A Polymorphisms on Major Depressive Disorder Susceptibility in a Chinese Han Population: A Case-Control Study

Purpose: TPH2 and 5-HT2A appear to play vital roles in the homeostatic regulation of serotonin levels in the brain, their genetic variations may lead to impaired homeostatic regulation of serotonin resulting in abnormal levels of serotonin in the brain, thus predisposing individuals to MDD. However, research studies have yet to confirm which gene-gene interaction effect between TPH2 and 5-HT2A polymorphisms results in increased susceptibility to MDD. Methods: A total of 565 participants, consisting of 278 MDD patients and 287 healthy controls from the Chinese Han population, were recruited for the present study. Six single nucleotide polymorphisms (SNPs) of TPH2/5-HT2A were selected to assess their interaction by use of a generalized multifactor dimensionality reduction method. Results: A-allele carriers of rs11178997 and rs120074175 were more likely to suffer from MDD than T-allele carriers of rs11178997, or G-allele carriers of rs120074175. The interaction between TPH2 (rs120074175, rs11178997) and 5-HT2A (rs7997012) was considered as the best multi-locus model upon the MDD susceptibility. Conclusions: Our data identified an important effect of TPH2 genetic variants (rs11178997 and rs120074175) upon the risk of MDD, and suggested that the interaction of TPH2/5-HT2A polymorphism variants confer a greater susceptibility to MDD in Chinese Han population.

Pharmacogenomics in Asia: a systematic review on current trends and novel discoveries

While early pharmacogenomic studies have primarily been carried out in Western populations, there has been a notable increase in the number of Asian studies over the past decade. We systematically reviewed all pharmacogenomic studies conducted in Asia published before 2016 to highlight trends and identify research gaps in Asia. We observed that pharmacogenomic research in Asia was dominated by larger developed countries, notably Japan and Korea, and mainly driven by local researchers. Studies were focused on drugs acting on the CNS, chemotherapeutics and anticoagulants. Significantly, several novel pharmacogenomic associations have emerged from Asian studies. These developments are highly encouraging for the strength of regional scientific and clinical community and propound the importance of discovery studies in different populations.

Consensus paper of the WFSBP Task Force on Genetics: Genetics, epigenetics and gene expression markers of major depressive disorder and antidepressant response

Major depressive disorder (MDD) is a heritable disease with a heavy personal and socio-economic burden. Antidepressants of different classes are prescribed to treat MDD, but reliable and reproducible markers of efficacy are not available for clinical use. Further complicating treatment, the diagnosis of MDD is not guided by objective criteria, resulting in the risk of under- or overtreatment. A number of markers of MDD and antidepressant response have been investigated at the genetic, epigenetic, gene expression and protein levels. Polymorphisms in genes involved in antidepressant metabolism (cytochrome P450 isoenzymes), antidepressant transport (ABCB1), glucocorticoid signalling (FKBP5) and serotonin neurotransmission (SLC6A4 and HTR2A) were among those included in the first pharmacogenetic assays that have been tested for clinical applicability. The results of these investigations were encouraging when examining patient-outcome improvement. Furthermore, a nine-serum biomarker panel (including BDNF, cortisol and soluble TNF-α receptor type II) showed good sensitivity and specificity in differentiating between MDD and healthy controls. These first diagnostic and response-predictive tests for MDD provided a source of optimism for future clinical applications. However, such findings should be considered very carefully because their benefit/cost ratio and clinical indications were not clearly demonstrated. Future tests may include combinations of different types of biomarkers and be specific for MDD subtypes or pathological dimensions.

Pharmacogenetics and Imaging-Pharmacogenetics of Antidepressant Response: Towards Translational Strategies

Genetic variation underlies both the response to antidepressant treatment and the occurrence of side effects. Over the past two decades, a number of pharmacogenetic variants, among these the SCL6A4, BDNF, FKBP5, GNB3, GRIK4, and ABCB1 genes, have come to the forefront in this regard. However, small effects sizes, mixed results in independent samples, and conflicting meta-analyses results led to inherent difficulties in the field of pharmacogenetics translating these findings into clinical practice. Nearly all antidepressant pharmacogenetic variants have potentially pleiotropic effects in which they are associated with major depressive disorder, intermediate phenotypes involved in emotional processes, and brain areas affected by antidepressant treatment. The purpose of this article is to provide a comprehensive review of the advances made in the field of pharmacogenetics of antidepressant efficacy and side effects, imaging findings of antidepressant response, and the latest results in the expanding field of imaging-pharmacogenetics studies. We suggest there is mounting evidence that genetic factors exert their impact on treatment response by influencing brain structural and functional changes during antidepressant treatment, and combining neuroimaging and genetic methods may be a more powerful way to detect biological mechanisms of response than either method alone. The most promising imaging-pharmacogenetics findings exist for the SCL6A4 gene, with converging associations with antidepressant response, frontolimbic predictors of affective symptoms, and normalization of frontolimbic activity following antidepressant treatment. More research is required before imaging-pharmacogenetics informed personalized medicine can be applied to antidepressant treatment; nevertheless, inroads have been made towards assessing genetic and neuroanatomical liability and potential clinical application.

Genetic variation in the tryptophan hydroxylase 2 gene moderates depressive symptom trajectories and remission over 8 weeks of escitalopram treatment

The serotonin system plays an important role in the pathogenesis of major depressive disorder (MDD) and genetic variations in serotonin-related genes affect the efficacy of antidepressants. The aim of this study was to investigate the relationship between genotypic variation in six candidate serotonergic genes (ADCY9, HTR1B, GNB3, HTR2A, TPH2, SLC6A4) and depressive and anxiety symptom severity trajectories as well as remission following escitalopram treatment. A total of 166 Chinese patients with MDD were treated with escitalopram (open-label) for 8 weeks. TPH2 rs4570625 GG carriers were more likely to achieve depressive and anxiety symptom remission compared with T-allele carriers. At the trend level (P(corrected)=0.05), depressive symptom severity trajectories were moderated by TPH2 rs4570625. Patients with the GT or the GG genotype showed more favorable depressive symptom severity trajectories compared with TT genotype carriers. Polymorphisms in ADCY9, HTR1B, and HTR2A were nominally associated with symptom remission, but did not withstand correction for multiple comparisons. The HTTLPR polymorphism was not included in our final analysis because of a high percentage of missing data. These results suggested that genotypic variation in TPH2 may moderate the therapeutic response to esciatlopram among Chinese patients with MDD.

Utilizing yeast chemogenomic profiles for the prediction of pharmacogenomic associations in humans

Understanding the genetic basis underlying individual responses to drug treatment is a fundamental task with implications to drug development and administration. Pharmacogenomics is the study of the genes that affect drug response. The study of pharmacogenomic associations between a drug and a gene that influences the interindividual drug response, which is only beginning, holds much promise and potential. Although relatively few pharmacogenomic associations between drugs and specific genes were mapped in humans, large systematic screens have been carried out in the yeast Saccharomyces cerevisiae, motivating the constructing of a projection method. We devised a novel approach for the prediction of pharmacogenomic associations in humans using genome-scale chemogenomic data from yeast. We validated our method using both cross-validation and comparison to known drug-gene associations extracted from multiple data sources, attaining high AUC scores. We show that our method outperforms a previous technique, as well as a similar method based on known human associations. Last, we analyze the predictions and demonstrate their biological relevance to understanding drug response.

Klotho Gene and Selective Serotonin Reuptake Inhibitors: Response to Treatment in Late-Life Major Depressive Disorder

Klotho protein, encoded by the Klotho gene (KL) at locus 13q12, is an antiaging hormone-like protein playing a pivotal role in cell metabolism homeostasis and associated to longevity and age-related diseases. In particular, altered cell metabolism in central nervous system may influence the behavior of serotoninergic neurons. The role of KL in the response to treatment with selective serotonin reuptake inhibitors (SSRIs) in late-life depressive syndromes and late-life major depressive disorder (MDD) is unclear. We genotyped three single-nucleotide polymorphisms (SNPs) of KL in 329 older patients with diagnosis of late-life MDD, treated with SSRIs and evaluated with the Hamilton Rating Scale for Depression 21-items (HRSD-21) at baseline and after 6 months. A reduction ≥50 and <10 % in HDRS-21 score was considered as response or nonresponse to therapy, respectively, and the values of reduction between 10 and 49 % as poor responders. After 6 months of SSRI treatment, 176 patients responded, 54 patients did not respond and 99 patients showed a poor response. Ordinal logistic models showed a significant association between mutation of SNP rs1207568 and responders and, similarly, for each unitary risk allele increase overlapping results were found. Conversely, a significantly higher frequency of the minor genotype of SNP rs9536314 was found in nonresponders. Considering the pre-post differences of HRSD-21 scores as a continue variable, we confirmed a significant improvement of depressive symptoms after treatment in patients carrying at least one minor allele at rs1207568 and a worse response in patients homozygous for the minor allele at rs9536314. Our results were the first that suggested a possible role of KL in the complex pathway of SSRI response in late-life MDD.

A roadmap to multifactor dimensionality reduction methods

Complex diseases are defined to be determined by multiple genetic and environmental factors alone as well as in interactions. To analyze interactions in genetic data, many statistical methods have been suggested, with most of them relying on statistical regression models. Given the known limitations of classical methods, approaches from the machine-learning community have also become attractive. From this latter family, a fast-growing collection of methods emerged that are based on the Multifactor Dimensionality Reduction (MDR) approach. Since its first introduction, MDR has enjoyed great popularity in applications and has been extended and modified multiple times. Based on a literature search, we here provide a systematic and comprehensive overview of these suggested methods. The methods are described in detail, and the availability of implementations is listed. Most recent approaches offer to deal with large-scale data sets and rare variants, which is why we expect these methods to even gain in popularity.

The combined effect of genetic polymorphisms and clinical parameters on treatment outcome in treatment-resistant depression

For over a decade, the European Group for the Study of Resistant Depression (GSRD) has examined single nucleotide polymorphisms (SNP) and clinical parameters in regard to treatment outcome. However, an interaction based model combining these factors has not been established yet. Regarding the low effect of individual SNPs, a model investigating the interactive role of SNPs and clinical variables in treatment-resistant depression (TRD) seems auspicious. Thus 225 patients featured in previous work of the GSRD were enrolled in this investigation. According to data availability and previous positive results, 12 SNPs in HTR2A, COMT, ST8SIA2, PPP3CC and BDNF as well as 8 clinical variables featured in other GSRD studies were chosen for this investigation. Random forests algorithm were used for variable shrinkage and k-means clustering for surfacing variable characteristics determining treatment outcome. Using these machine learning and clustering algorithms, we detected a set of 3 SNPs and a clinical variable that was significantly associated with treatment response. About 62% of patients exhibiting the allelic combination of GG-GG-TT for rs6265, rs7430 and rs6313 of the BDNF, PPP3CC and HTR2A genes, respectively, and without melancholia showed a HAM-D decline under 17 compared to about 34% of the whole study sample. Our random forests prediction model for treatment outcome showed that combining clinical and genetic variables gradually increased the prediction performance recognizing correctly 25% of responders using all 4 factors. Thus, we could confirm our previous findings and furthermore show the strength of an interaction-based model combining statistical algorithms in identifying and operating treatment predictors.

Serotonin-related polymorphisms in TPH1 and HTR5A genes are not associated with escitalopram treatment response in Korean patients with major depression

BACKGROUND/AIMS

The genetic variations in serotonin-related genes may be associated with antidepressant treatment response in major depressive disorder (MDD). The tryptophan hydroxylase-1 (TPH1) gene and serotonin 5A receptor (HTR5A) gene are known to be involved in serotonin biosynthesis and signal transduction, respectively. The purpose of this study was to investigate a possible interaction between the TPH1 gene and the HTR5A gene in the treatment outcome of escitalopram in MDD.

METHODS

In total, 245 patients diagnosed with MDD were recruited, and their symptoms were evaluated using the 17-item Hamilton Depression Rating scale (HAMD-17). The association between the TPH1 218A/C and HTR5A 12A/T polymorphisms and the clinical outcomes (remission, response and changes in HAMD-17 score) was investigated after 2, 4 and 8 weeks of escitalopram treatment using multiple logistic regression or multiple linear regression analysis.

RESULTS

No significant associations of TPH1 or HTR5A gene polymorphisms were observed with either response rate or remission rate at 2, 4 and 8 weeks after escitalopram treatment. In addition, the gene-gene interaction between TPH1 and HTR5A genes was not associated with the treatment outcome.

CONCLUSIONS

Our results suggest that TPH1 218A/C and HTR5A 12A/T polymorphisms cannot predict treatment response in major depression.

Influence of GNB3 C825T polymorphism on the efficacy of antidepressants in the treatment of major depressive disorder: A meta-analysis

OBJECTIVE

We performed the present meta-analysis in order to evaluate the influence of a common polymorphism (C825T, rs5443 C>T) in the GNB3 gene on the efficacy of antidepressants in the treatment of major depressive disorder (MDD).

METHOD

A relevant literature was searched using the PubMed, Embase, Web of Science, Cochrane Library, CISCOM, CINAHL, Google Scholar, CBM and CNKI databases without any language restrictions. STATA Version 12.0 software (Stata Corporation, College Station, Texas USA) was used for this meta-analysis. Odds ratio (OR) and its corresponding 95% confidence interval (95% CI) were calculated.

RESULTS

Our findings suggested that the GNB3 C825T polymorphism was significantly correlated with a higher response rate to antidepressants in MDD patients under the allele and dominant models. Furthermore, we found significant associations between GNB3 C825T polymorphisms and antidepressant-induced remission in MDD patients. Ethnicity-stratified analysis indicated that GNB3 C825T polymorphisms may be strongly related to the efficacy of antidepressants in the treatment of MDD among Asians, but not in Caucasians (all P>0.05).

CONCLUSION

Our findings provide empirical evidence that GNB3 C825T polymorphisms may be correlated with the efficacy of antidepressants in the treatment of MDD, especially among Asians patients.

From pharmacogenetics to pharmacogenomics: the way toward the personalization of antidepressant treatment

OBJECTIVE

Major depressive disorder is the most common psychiatric disorder, worldwide, yet response and remission rates are still unsatisfactory. The identification of genetic predictors of antidepressant (AD) response could provide a promising opportunity to improve current AD efficacy through the personalization of treatment. The major steps and findings along this path are reviewed together with their clinical implications and limitations.

METHOD

We systematically reviewed the literature through MEDLINE and Embase database searches, using any word combination of "antidepressant," "gene," "polymorphism," "pharmacogenetics," "genome-wide association study," "GWAS," "response," and "adverse drug reactions." Experimental works and reviews published until March 2012 were collected and compared.

RESULTS

Numerous genes pertaining to several functional systems were associated with AD response. The more robust findings were found for the following genes: solute carrier family 6 (neurotransmitter transporter), member 4; serotonin receptor 1A and 2A; brain-derived neurotrophic factor; and catechol-O-methyltransferase. Genome-wide association studies (GWASs) provided many top markers, even if none of them reached genome-wide significance.

CONCLUSIONS

AD pharmacogenetics have not produced any knowledge applicable to routine clinical practice yet, as results were mainly inconsistent across studies. Despite this, the rising awareness about methodological deficits of past studies could allow for the identication of more suitable strategies, such as the integration of the GWAS approach with the candidate gene approach, and innovative methodologies, such as pathway analysis and study of depressive endophenotypes.

Clinical validity of cytochrome P450 metabolism and serotonin gene variants in psychiatric pharmacotherapy

Adverse events, response failures and medication non-compliance are common in patients receiving medications for the treatment of mental illnesses. A systematic literature review assessed whether pharmacokinetic (PK) or pharmacodynamic (PD) responses to 26 commonly prescribed antipsychotic and antidepressant medications, including efficacy or side effects, are associated with nucleotide polymorphisms in eight commonly studied genes in psychiatric pharmacotherapy: CYP2D6, CYP2C19, CYP2C9, CYP1A2, CYP3A4, HTR2C, HTR2A, and SLC6A4. Of the 294 publications included in this review, 168 (57%) showed significant associations between gene variants and PK or PD outcomes. Other studies that showed no association often had insufficient control for confounding variables, such as co-medication use, or analysis of medications not substrates of the target gene. The strongest gene-outcome associations were for the PK profiles of CYP2C19 and CYP2D6 (93% and 90%, respectively), for the PD associations between HTR2C and weight gain (57%), and for SLC6A4 and clinical response (54%), with stronger SLC6A4 response associations for specific drug classes (60-83%). The preponderance of evidence supports the validity of analyzing nucleotide polymorphisms in CYP and pharmacodynamic genes to predict the metabolism, safety, or therapeutic efficacy of psychotropic medications commonly used for the treatment of depression, schizophrenia, and bipolar illness.

Do we need pharmacogenetics to personalize antidepressant therapy?

This review examines the role of drug metabolism and drug target polymorphism in determining the clinical response to antidepressants. Even though antidepressants are the most effective available treatment for depressive disorders, there is still substantial need for improvement due to the slow onset of appreciable clinical improvement and the association with side effects. Moreover, a substantial group of patients receiving antidepressant therapy does not achieve remission or fails to respond entirely. Even if the large variation in antidepressant treatment outcome across individuals remains poorly understood, one possible source of this variation in treatment outcome are genetic differences. The review focuses on a few polymorphisms which have been extensively studied, while reporting a more comprehensive reference to the existing literature in table format. It is relatively easy to predict the effect of polymorphisms in drug metabolizing enzymes, such as cytochromes P450 2D6 (CYP2D6) and cytochrome P450 2C19 (CYP2C19), which may be determined in the clinical context in order to explain or prevent serious adverse effects. The role of target polymorphism, however, is much more difficult to establish and may be more relevant for disease susceptibility and presentation rather than for response to therapy.

Pharmacogenetics of antidepressant drugs: an update after almost 20 years of research

Major depressive disorder (MDD) is an emergent cause of personal and socio-economic burden, both for the high prevalence of the disorder and the unsatisfying response rate of the available antidepressant treatments. No reliable predictor of treatment efficacy and tolerance in the single patient is available, thus drug choice is based on a trial and error principle with poor clinical efficiency. Among modulators of treatment outcome, genetic polymorphisms are thought to explain a significant share of the inter-individual variability. The present review collected the main pharmacogenetic findings primarily about antidepressant response and secondly about antidepressant induced side effects, and discussed the main strengths and limits of both candidate and genome-wide association studies and the most promising methodological opportunities and challenges of the field. Despite clinical applications of antidepressant pharmacogenetics are not available yet, previous findings suggest that genotyping may be applied in the clinical practice. In order to reach this objective, further rigorous pharmacogenetic studies (adequate sample size, study of better defined clinical subtypes of MDD, adequate covering of the genetic variability), their combination with the results obtained through complementary methodologies (e.g., pathway analysis, epigenetics, transcriptomics, and proteomics), and finally cost-effectiveness trials are required.

Assessment of genetic and nongenetic interactions for the prediction of depressive symptomatology: an analysis of the Wisconsin Longitudinal Study using machine learning algorithms

OBJECTIVES

We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms.

METHODS

We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors-13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors-18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks.

RESULTS

After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors.

CONCLUSIONS

We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic-environmental-sociobehavioral interactions in depressive symptoms.

Pharmacogenetics in major depression: a comprehensive meta-analysis

A number of candidate gene studies focused on major depression (MD) and antidepressant (AD) efficacy have been carried out, but results mainly remain inconclusive. We performed a comprehensive meta-analysis of published candidate gene studies focused on AD efficacy in MD to evaluate the cumulative evidence. A random-effect model was applied to study the polymorphisms with genotypic counts available from at least three independent studies. On the base of previous evidence, the analysis was stratified by ethnicity (Caucasian, Asian, and other/mixed), and AD class (SSRIs and mixed/other ADs). Genotypic data were available for 16 polymorphisms in 11 genes. After the exclusion of 5-HTTLPR in SLC6A4 included in another recent meta-analysis, 15 polymorphisms in 11 genes were included in the present meta-analysis (BDNF rs6265, SLC6A4 STin2, HTR1A rs6295, HTR2A rs6311, rs6313 and rs7997012, HTR6 rs1805054, TPH1 rs1800532, SLC6A2 rs5569, COMT rs4680, GNB3 rs5443, FKBP5 rs1360780 and rs3800373, and ABCB1 rs1045642 and rs2032582). Our results suggested that BDNF rs6265 (Val66Met) heterozygous genotype was associated with better SSRIs response compared to the homozygous genotypes, particularly in Asians (OR=1.53, 95%CI 1.12-2.07, p=0.007). SLC6A4 STin2, HTR2A rs6311 and rs7997012, GNB3 rs5443, FKBP5 rs1360780 and rs3800373, and ABCB1 rs2032582 showed associations with AD efficacy, but these results were highly dependent on one or two single studies. In conclusion, our findings suggested the BDNF Val66Met as the best single candidate involved in AD response, with a selective effect on SSRI treatment. Our overall results supported no major effect of any single gene variant on AD efficacy.

No effect of serotoninergic gene variants on response to interpersonal counseling and antidepressants in major depression

OBJECTIVE

Gene variants within the serotonin pathway have been associated with major depressive disorder (MDD) treatment outcomes, however a possible different modulation on pharmacological or psychological treatments has never been investigated.

METHODS

One hundred sixty MDD patients were partially randomized to either inter-personal counseling (IPC) or antidepressants. The primary outcome was remission at week 8. Five serotonergic polymorphisms were investigated (COMT rs4680, HTR1A rs6295, HTR2A rs2224721, HTR2A rs7997012 and SLC6A4 rs421417).

RESULTS

IPC (n=43) and antidepressant (n=117) treated patients did not show any difference in remission rates at week 8 (corrected for baseline severity, age and center). None of the studied gene variants impacted on response and remission rates at week 8 neither in the IPC nor in the antidepressant group. An analysis of the whole sample showed a trend of association between rs7997012 AA genotype and a better treatment outcome.

CONCLUSION

Our study confirms that IPC is an effective psychological intervention comparable to antidepressants in mild-moderate MDD. Polymorphisms related to the serotonin system did not exert a major effect on clinical outcomes in none of the treatment groups.

The serotonin transporter gene is a substrate for age and stress dependent epigenetic regulation in rhesus macaque brain: potential roles in genetic selection and gene × environment interactions

In humans, it has been demonstrated that the serotonin transporter linked polymorphic region (5-HTTLPR) genotype moderates risk in the face of adversity. One mechanism by which stress could interact with genotype is via epigenetic modifications. We wanted to examine whether stress interacted with genotype to predict binding of a histone 3 protein trimethylated at lysine 3 (H3K4me3) that marks active promoters. The brains (N = 61) of male rhesus macaques that had been reared in the presence or absence of stress were archived and the hippocampusi dissected. Chromatin immunoprecipitation was performed with an antibody against H3K4me3 followed by sequencing on a SolexaG2A. The effects of age, genotype (5-HTTLPR long/long vs. short), and stress exposure (peer-reared vs. mother-reared) on levels of H3K4me3 binding were determined. We found effects of age and stress exposure. There was a decline in H3K4me3 from preadolescence to postadolescence and lower levels in peer-reared monkeys and no effects of genotype. When we controlled for age, however, we found that there were effects of 5-HTTLPR genotype and rearing condition on H3K4me3 binding. In a larger sample, we observed that cerebrospinal fluid 5-hydroxyindoleacetic acid levels were subject to interactive effects among age, rearing history, and genotype. Genes containing both genetic selection and epigenetic regulation may be particularly important in stress adaptation and development. We find evidence for selection at the solute carrier family C6 member 4 gene and observe epigenetic reorganization according to genotype, stress, and age. These data suggest that developmental stage may moderate effects of stress and serotonin transporter genotype in the emergence of alternative adaptation strategies and in the vulnerability to developmental or psychiatric disorders.

Imaging genetics: implications for research on variable antidepressant drug response

Genetic variation of SLC6A4, HTR1A, MAOA, COMT and BDNF has been associated with depression, variable antidepressant drug responses as well as impacts on brain regions of emotion processing that are modulated by antidepressants. Pharmacogenetic studies are using psychometric outcome measures of drug response and are hampered by small effect sizes that might be overcome by the use of intermediate endophenotypes of drug response, which are suggested by imaging studies. Such an approach will not only tighten the relationship between genes and drug response, but also yield new insights into the neurobiology of depression and individual drug responses. This article provides a comprehensive overview of pharmacogenetic, imaging genetics and drug response studies, utilizing imaging techniques within the context of antidepressive drug therapy.

The genetics of selective serotonin reuptake inhibitors

Selective serotonin reuptake inhibitors (SSRIs) are among the most widely prescribed drugs in psychiatry. Based on the fact that SSRIs increase extracellular monoamine levels in the brain, the monoamine hypothesis of depression was introduced, postulating that depression is associated with too low serotonin, dopamine and noradrenaline levels. However, several lines of evidence indicate that this hypothesis is too simplistic and that depression and the efficacy of SSRIs are dependent on neuroplastic changes mediated by changes in gene expression. Because a coherent view on global gene expression is lacking, we aim to provide an overview of the effects of SSRI treatment on the final targets of 5-HT receptor signal transduction pathways, namely the transcriptional regulation of genes. We address gene polymorphisms in humans that affect SSRI efficacy, as well as in vitro studies employing human-derived cells. We also discuss the molecular targets affected by SSRIs in animal models, both in vivo and in vitro. We conclude that serotonin transporter gene variation in humans affects the efficacy and side-effects of SSRIs, whereas SSRIs generally do not affect serotonin transporter gene expression in animals. Instead, SSRIs alter mRNA levels of genes encoding serotonin receptors, components of non-serotonergic neurotransmitter systems, neurotrophic factors, hypothalamic hormones and inflammatory factors. So far little is known about the epigenetic and age-dependent molecular effects of SSRIs, which might give more insights in the working mechanism(s) of SSRIs.

Association of the C825T polymorphism in the GNB3 gene with obesity and metabolic phenotypes in a Taiwanese population

The relationship between obesity and a single nucleotide polymorphism (SNP), rs5443 (C825T), in the guanine nucleotide binding protein beta polypeptide 3 (GNB3) gene is currently inconsistent. In this study, we aimed to reassess whether the GNB3 rs5443 SNP could influence obesity and obesity-related metabolic traits in a Taiwanese population. A total of 983 Taiwanese subjects with general health examinations were genotyped. Based on the criteria defined by the Department of Health in Taiwan, the terms "overweight" and "obesity" are defined as 24 ≦ BMI < 27 and BMI ≧ 27, respectively. Compared to the carrier of the combined CT + TT genotypes of the GNB3 rs5443 polymorphism, triglyceride was significantly higher for the carrier of CC genotype in the complete sample population (128.2 ± 93.2 vs. 114.3 ± 79.1 mg/dl; P = 0.041). In addition, the carriers of CC variant had a higher total cholesterol than those with the combined CT + TT variants (194.5 ± 36.8 vs. 187.9 ± 33.0 mg/dl; P = 0.019) in the complete sample population. In the normal controls, both triglyceride (P = 0.018) and total cholesterol (P = 0.011) were also significantly higher in the CC homozygotes than in the combined CT + TT genotypes. However, the GNB3 rs5443 SNP did not exhibit any significant association with obesity or overweight among the subjects. Our study indicates that the CC genotype of the GNB3 rs5443 SNP may predict higher obesity-related metabolic traits such as triglyceride and total cholesterol in non-obese Taiwanese subjects (but not in obese subjects).

European Group for the Study of Resistant Depression (GSRD)--where have we gone so far: review of clinical and genetic findings

The primary objective of this review is to give an overview of the main findings of the European multicenter project "Patterns of Treatment Resistance and Switching Strategies in Affective Disorder", performed by the Group for the Study of Resistant Depression (GSRD). The aim was to study methodological issues, operational criteria, clinical characteristics, and genetic variables associated with treatment resistant depression (TRD), that is failure to reach response after at least two consecutive adequate antidepressant trials. The primary findings of clinical variables associated with treatment resistance include comorbid anxiety disorders as well as non-response to the first antidepressant received lifetime. Although there is a plethora of hints in textbooks that switching the mechanism of action should be obtained in case of nonresponse to one medication, the results of the GSRD challenge this notion by demonstrating in retrospective and prospective evaluations that staying on the same antidepressant mechanism of action for a longer time is more beneficial than switching, however, when switching is an option there is no benefit to switch across class. The GSRD candidate gene studies found that metabolism status according to cytochrome P450 gene polymorphisms may not be helpful to predict response and remission rates to antidepressants. Significant associations with MDD and antidepressant treatment response were found for COMT SNPs. Investigating the impact of COMT on suicidal behaviour, we found a significant association with suicide risk in MDD patients not responding to antidepressant treatment, but not in responders. Further significant associations with treatment response phenotypes were found with BDNF, 5HTR2A and CREB1. Additional investigated candidate genes were DTNBP1, 5HT1A, PTGS2, GRIK4 and GNB3.

Failure to replicate influence of GRIK4 and GNB3 polymorphisms on treatment outcome in major depression

In the present study, we aimed to confirm the previous finding of an association between GRIK4 and GNB3 variants (rs195478 and rs5443) and remission and treatment resistance in major depression, using a multicenter sample of 223 patients. We did not find any supporting evidence for such associations. These conflicting data may result from difficulties in the replication of candidate gene association studies.

The relationship between single nucleotide polymorphisms in 5-HT2A signal transduction-related genes and the response efficacy to selective serotonin reuptake inhibitor treatments in Chinese patients with major depressive disorder

OBJECTIVE

To explore the possible relationship between six single nucleotide polymorphisms (SNPs) (rs6311 and rs6305 of 5-HT2A, rs5443 of Gβ3, rs2230739 of ACDY9, rs1549870 of PDE1A and rs255163 of CREB1, which are all related with 5-HT2A the signal transduction pathway) and the response efficacy to selective serotonin reuptake inhibitor (SSRI) treatments in major depressive disorder (MDD) Chinese.

METHODS

This study included 194 depressed patients to investigate the influence of 6 polymorphisms in 5-HT2A signal transduction-related genes on the efficacy of SSRIs assessed over 1 year. The efficacies of SSRIs on 194 MDD patients were evaluated in an 8-week open-trial study. Over 1 year, a follow-up study was completed for 174 of them to observe the long-term efficacy of SSRIs. The optimal-scaling regression analysis was used for testing the relationship between the different genotypes of five SNPs and the efficacy in MDD.

RESULTS

It showed that the patients with rs5443TT and rs2230739GG have a relatively good efficacy in response to short-term SSRIs. We also found that good efficacy appeared in depressed patients with rs2230739GG in response to long-term SSRIs.

CONCLUSIONS

It suggested that different genotypes of rs5443 and rs2230739 might influence the signal transduction pathways of second message and affect therapeutic efficacy.

Pharmacogenetics of antidepressant drugs: current clinical practice and future directions

While antidepressants are widely used to treat mood and anxiety disorders, only half of the patients will respond to antidepressant treatment and only one-third of patients experience a full remission of symptoms. The identification of genetic biomarkers that predict antidepressant-treatment response can improve current clinical practice. This is an emerging field known as pharmacogenetics, which comprises of genetic studies on both the pharmacokinetics and pharmacodynamics of treatment response. Recent studies on antidepressant-treatment response have focused on both aspects of pharmacogenetics research, identifying new candidate genes that may predict better treatment response for patients. This paper reviews recent findings on the pharmacogenetics of antidepressant drugs and future clinical applications. Ultimately, these studies should lead to the use of genetic testing to guide the use of antidepressants in clinical practice.

Should pharmacogenetics be incorporated in major depression treatment? Economic evaluation in high- and middle-income European countries

The serotonin transporter 5-HTTLPR polymorphism moderates response to SSRIs and side-effect burden. The aim of this study is to quantify the cost-utility of incorporating 5-HTTLPR genotyping in drug treatment of major depressive disorder (MDD). We previously reported a theoretical model to simulate antidepressant treatment with citalopram or bupropion for 12 weeks. The drugs were alternatively selected according to an 'as usual' algorithm or based on response and tolerability predicted by 5-HTTLPR profile. Here we apply this model to conduct a cost-utility analysis in three European regions with high GDP (Euro A), middle GDP (Euro B) and middle-high GDP (Euro C). In addition we test a verification scenario in which citalopram+bupropion augmentation is administered to individuals with the least favorable 5-HTTLPR genotype. Treatment outcomes are remission and Quality Adjusted-Life Weeks (QALW). Cost data (international $, year 2009) are retrieved from the World Health Organization (WHO) and national official sources. In base-case scenario incremental cost-effectiveness ratio (ICER) values are $1147 (Euro A), $1185 (Euro B) and $1178 (Euro C). From cost-effectiveness acceptability curve (CEAC), the probability of having an ICER value below WHO recommended cost-utility threshold (3 GDP per capita=$1926) is >90% in high-income countries (Euro A). In middle- income regions, these probabilities are <30% (Euro B) and <55% (Euro C) respectively. All estimates are robust against variations in treatment parameters, but if genetic test cost decreases to $100, pharmacogenetic approach becomes cost-effective in middle-income countries (Euro B). This simulation using data from 27 European states suggests that choosing antidepressant treatment from the results of 5-HTTLPR might be a cost-effective solution in high income countries. Its feasibility in middle income countries needs further research.

Pharmacogenetics of antidepressants

Up to 60% of depressed patients do not respond completely to antidepressants (ADs) and up to 30% do not respond at all. Genetic factors contribute for about 50% of the AD response. During the recent years the possible influence of a set of candidate genes as genetic predictors of AD response efficacy was investigated by us and others. They include the cytochrome P450 superfamily, the P-glycoprotein (ABCB1), the tryptophan hydroxylase, the catechol-O-methyltransferase, the monoamine oxidase A, the serotonin transporter (5-HTTLPR), the norepinephrine transporter, the dopamine transporter, variants in the 5-hydroxytryptamine receptors (5-HT1A, 5-HT2A, 5-HT3A, 5-HT3B, and 5-HT6), adrenoreceptor beta-1 and alpha-2, the dopamine receptors (D2), the G protein beta 3 subunit, the corticotropin releasing hormone receptors (CRHR1 and CRHR2), the glucocorticoid receptors, the c-AMP response-element binding, and the brain-derived neurotrophic factor. Marginal associations were reported for angiotensin I converting enzyme, circadian locomotor output cycles kaput protein, glutamatergic system, nitric oxide synthase, and interleukin 1-beta gene. In conclusion, gene variants seem to influence human behavior, liability to disorders and treatment response. Nonetheless, gene × environment interactions have been hypothesized to modulate several of these effects.

TPH1 is associated with major depressive disorder but not with SSRI/SNRI response in Taiwanese patients

RATIONALE

Tryptophan hydroxylase 1 (TPH1), which encodes the rate-limiting enzyme tryptophan hydroxylase in the biosynthesis of serotonin, is a candidate gene in the development and treatment response of major depressive disorder (MDD); however, its actual role is uncertain.

OBJECTIVES

We aimed to compare the allele frequencies of TPH1 in MDD patients and healthy controls in Taiwan, and also to investigate the association between TPH1 A218C and treatment response to either fluoxetine or venlafaxine in a Taiwanese population with MDD.

METHODS

One hundred five healthy controls and 115 outpatients diagnosed with MDD were recruited and genotyped for the TPH1 218A/C (rs1800532) polymorphism. Patients were randomized into either the fluoxetine or venlafaxine treatment group. The 21-item Hamilton rating scale for depression (HAM-D) was administered to evaluate depressive symptoms at baseline and bi-weekly over 6 weeks of treatment.

RESULTS

The TPH1 218A/C allele frequencies differed significantly between healthy controls and MDD patients in Taiwan, with a higher prevalence of the A allele in the patient group (p = 0.025). The odds ratio of the A allele to the C allele was 0.507 for the subjects with MDD. There was no significant correlation between the percentage change in HAM-D score and either TPH1 218A/C genotype or TPH1 allele frequencies.

CONCLUSIONS

This study indicated that the TPH1 218A/C genotype and allele frequencies differed between the Taiwanese healthy controls and MDD patients but could not be used to predict treatment outcome in Taiwanese MDD patients. Further research with larger sample sizes is needed to confirm the role of TPH1 218A/C.

Brain derived neurotrophic factor gene polymorphism (Val66Met) and short-term antidepressant response in major depressive disorder

BACKGROUNDS

To determine the association between the brain derived neurotrophic factor (BDNF) Val66Met polymorphism and short-term antidepressant response in Taiwanese patients with major depressive disorder (MDD).

METHODS

We recruited 117 MDD patients who were randomized to fluoxetine or venlafaxine treatment and 106 controls. The association between genotypes and percentage changes in the Hamilton Rating Scale for Depression (HAM-D) scores over time was analyzed by repeated-measures ANOVA. The antidepressants were included in the model as covariates.

RESULTS

The frequency of the BDNF Val66Met polymorphisms was not significantly different between patient and control groups. Significantly changes in HAM-D scores were noted after 2 and 4 weeks of venlafaxine treatment among different genotypes.

CONCLUSIONS

Results suggest antidepressants acting through different mechanisms may affect the BDNF Val66Met polymorphism differently.

C825T polymorphism of the GNB3 gene on valproate-related metabolic abnormalities in bipolar disorder patients

BACKGROUND

Valproate (VPA) is a mood stabilizer for treating patients with bipolar disorder (BD). It may cause metabolic abnormalities in certain bipolar patients. However, the genetic factors that influence the susceptibility remain unclear. Genetic polymorphism of the G-protein β3 subunit (GNB3) is reported to be associated with metabolic phenotypes. In the current study, we investigated the possible associations between the GNB3 variation and VPA-induced metabolic abnormalities.

METHODS

Subjects (n = 96) who met the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for BD were recruited from the National Cheng Kung University Hospital. Their metabolic indices were measured.

RESULTS

The variation of GNB3 C825T showed an association with higher plasma total cholesterol (P = 0.037), triglyceride (P = 0.014), and leptin (P < 0.001) levels in BD patients treated with VPA. After adjusting for age, sex, types of BDs, and serum concentration of VPA, the variation of GNB3 C825T remained significantly associated with the levels of serum leptin and body mass index (BMI; P < 0.001 and P = 0.030, respectively). In addition, the GNB3 C825T showed significant drug-single-nucleotide polymorphism interactions with insulin levels (P = 0.033), triglyceride levels (P = 0.013), leptin levels (P = 0.013), and BMI (P = 0.018). These results indicated that the T allele may be associated with lower serum leptin levels and BMI in BD patients treated with VPA.

CONCLUSIONS

The current study provides evidence that BD patients who are T allele carriers of the GNB3 C825T polymorphism have a lower risk for VPA-induced metabolic abnormalities. Further studies about the underlying mechanisms of G protein in VPA-induced metabolic abnormalities are warranted.

Effect of the common -866G/A polymorphism of the uncoupling protein 2 gene on weight loss and body composition under sibutramine therapy in an obese Taiwanese population

BACKGROUND

Sibutramine, a serotonin and norepinephrine reuptake inhibitor, is used as an anti-obesity drug. Several pharmacogenetic studies have shown correlations between sibutramine effects and genetic variants, such as the 825C/T (rs5443) single nucleotide polymorphism (SNP) in the guanine nucleotide binding protein beta polypeptide 3 (GNB3) gene.

OBJECTIVE

In this study, our goal was to investigate whether a common SNP, -866G/A (rs659366), in the uncoupling protein 2 (UCP2) gene could influence weight reduction and body composition under sibutramine therapy in an obese Taiwanese population.

METHODS

The study included 131 obese patients, 44 in the placebo group and 87 in the sibutramine group. We assessed the measures of weight loss and body fat reduction at the end of a 12-week treatment period by analysis of covariance (ANCOVA) models using gender, baseline weight, and body fat percentage at baseline as covariates.

RESULTS AND CONCLUSION

By comparing the placebo and sibutramine groups with ANCOVA, our data showed a strong effect of sibutramine on weight loss in the combined UCP2 -866 AA + GA genotype groups (p < 0.001). Similarly, a strong effect of sibutramine on body fat percentage loss was found for individuals with the AA or GA genotypes (p < 0.001). In contrast, sibutramine had no significant effect on weight loss (p = 0.063) or body fat percentage loss (p = 0.194) for individuals with the wild-type GG genotype, compared with the placebo group of the same genotype. Moreover, a potential gene-gene interaction between UCP2 and GNB3 was identified by multiple linear regression models for the weight loss (p < 0.001) and for the percent fat loss (p = 0.031) in response to sibutramine. The results suggest that the UCP2 gene may contribute to weight loss and fat change in response to sibutramine therapy in obese Taiwanese patients.