Association of BDNF, HTR2A, TPH1, SLC6A4, and COMT polymorphisms with tDCS and escitalopram efficacy: ancillary analysis of a double-blind, placebo-controlled trial

MALDI-TOF MS-based SNP assay used to determine the appropriate antidepression for Chinese patients

Medicine remains the preferred primary treatment for depression, although some patients show remarkable individual variations in achieving satisfactory clinical outcomes during medication. Genetic polymorphisms cause approximately 40 % of individual differences in treatment response. Therefore, this study aimed to develop a technique to identify single nucleotide polymorphisms (SNPs) associated with the metabolism, effectiveness, and side effects of antidepressant medications in Chinese patients. Bibliometrics was used to search literature related to "depression" and "SNP" in Web of Science. The obtained SNP information was screened using the PharmGKB database. By designing and optimizing primers and conducting a compound amplification system, a method was established based on MALDI-TOF MS to detect polymorphisms associated with the antidepressant drugs, including sertraline, fluoxetine, citalopram, escitalopram, venlafaxine, fluvoxamine, paroxetine, and mirtazapine. The accuracy and sensitivity of the established method were verified by Sanger sequencing. A total of 10,043 articles were screened from the database, and 46 SNPs with a mutation frequency of >1 % in Asian populations and annotated with relevant clinical drugs were extracted from the PharmGKB database. This method was compared with the results of Sanger sequencing, and the accuracy of the detection results was 100 %. The MALDI-TOF MS-based SNP assay developed in this study can be a fast, convenient and effective way for patients to find the right medication for themselves. Moreover, we found that this SNP assay holds the promise of being a potential reference tool for assessing individualised differences in drug efficacy, not only for screening the causes of poor antidepressant efficacy in patients after taking medication, but also for advising physicians to understand individualised differences in drug efficacy.

Relative synonymous codon usage and codon pair analysis of depression associated genes

Depression negatively impacts mood, behavior, and mental and physical health. It is the third leading cause of suicides worldwide and leads to decreased quality of life. We examined 18 genes available at the genetic testing registry (GTR) from the National Center for Biotechnological Information to investigate molecular patterns present in depression-associated genes. Different genotypes and differential expression of the genes are responsible for ensuing depression. The present study, investigated codon pattern analysis, which might play imperative roles in modulating gene expression of depression-associated genes. Of the 18 genes, seven and two genes tended to up- and down-regulate, respectively, and, for the remaining genes, different genotypes, an outcome of SNPs were responsible alone or in combination with differential expression for different conditions associated with depression. Codon context analysis revealed the abundance of identical GTG-GTG and CTG-CTG pairs, and the rarity of methionine-initiated codon pairs. Information based on codon usage, preferred codons, rare, and codon context might be used in constructing a deliverable synthetic construct to correct the gene expression level of the human body, which is altered in the depressive state. Other molecular signatures also revealed the role of evolutionary forces in shaping codon usage.

Interactions between tDCS treatment and COMT Val158Met in poststroke cognitive impairment

OBJECTIVE

This study aimed to explore the effect of catechol-O-methyltransferase (COMT) Val158Met and brain-derived neurotrophic factor (BDNF) Val66Met to post-stroke cognitive impairment (PSCI) and the interaction with transcranial direct current stimulation (tDCS).

METHODS

Seventy-six patients with PSCI were randomly assigned to Group (1) (n = 38) to receive anodal tDCS of left dorsolateral prefrontal cortex or Group (2) (n = 38) to receive sham stimulation. The intensity of the tDCS was 2 mA, and the stimulations were applied over the left DLPFC for 10 sessions. The Montreal Cognitive Assessment (MoCA) and backward digit span test (BDST) were assessed before, immediately after, and one month after stimulation.

RESULTS

After stimulation, patients in the tDCS group showed better improvement in both MoCA and BDST than those in the sham group. The results of GLMs also supported the main effects of tDCS on general cognitive function and working memory. Then we found that COMT genotype may have a main effect on the improvement of MoCA and BDST, and there may be an interaction between COMT genotype and tDCS in enhancing BDST. In contrast, BDNF genotype showed no significant main or interaction effects on any scales.

CONCLUSIONS

These findings demonstrate that tDCS can improve cognition after stroke. Gene polymorphisms of COMT can affect the efficacy of tDCS on PSCI, but BDNF may not.

SIGNIFICANCE

This study found that COMT Val158Met has an interaction on the efficacy of prefrontal tDCS in cognitive function, which provides reference for future tDCS research and clinical application.

Application of Transcranial Direct and Alternating Current Stimulation (tDCS and tACS) on Major Depressive Disorder

The exploration of brain stimulation methods offers a promising avenue to overcome the shortcomings of traditional drug therapies and psychological treatments for major depressive disorder (MDD). Over the past years, there has been an increasing focus on transcranial electrical stimulation (tES), notably for its ease of use and potentially fewer side effects. This chapter delves into the use of transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), which are key components of tES, in managing depression. It begins by introducing tDCS and tACS, summarizing their action mechanisms. Following this introduction, the chapter provides an in-depth analysis of existing meta-analyses, systematic reviews, clinical studies, and case reports that have applied tES in MDD treatment. It also considers the role of tES in personalized medicine by looking at specific patient groups and evaluating research on possible biomarkers that could predict how patients with MDD respond to tES therapy.

[Pharmacogenomic and pharmacometabolomic biomarkers of the efficacy and safety of antidepressants: focus on selective serotonin reuptake inhibitors]

The efficacy and safety of psychopharmacotherapy with antidepressants is of great medical importance. The search for clinical and biological predictors for choosing the optimal psychopharmacotherapy with antidepressants is actively underway all over the world. Research is mainly devoted to searching for associations of polymorphic gene variants with the efficacy and safety of therapy. However, information about a patient's genetic polymorphism is often insufficient to predict the efficacy and safety of a drug. Modern research on the personalization of pharmacotherapy should include, in addition to genetic, phenotypic biomarkers. This is important because genotyping, for example, cannot accurately predict the actual metabolic activity of an isoenzyme. To personalize therapy, a combination of methods is required to obtain the most complete profile of the efficacy and safety of the drug. Successful treatment of depression remains a challenge, and inter-individual differences in response to antidepressants are common. About half of patients with depressive disorders do not respond to the first attempt at antidepressant therapy. Serious side-effects of antidepressant pharmacotherapy and discontinuation of treatment due to their intolerance are associated with ineffective therapy. This review presents the results of the latest studies of «omics» biomarkers of the efficacy and safety of antidepressants.

DNA Methylation Patterns in Relation to Acute Severity and Duration of Anxiety and Depression

Depression and anxiety are common mental disorders that often occur together. Stress is an important risk factor for both disorders, affecting pathophysiological processes through epigenetic changes that mediate gene-environment interactions. In this study, we explored two proposed models about the dynamic nature of DNA methylation in anxiety and depression: a stable change, in which DNA methylation accumulates over time as a function of the duration of clinical symptoms of anxiety and depression, or a flexible change, in which DNA methylation correlates with the acute severity of clinical symptoms. Symptom severity was assessed using clinical questionnaires for anxiety and depression (BDI-II, IDS-C, and HAM-A), and the current episode and the total lifetime symptom duration was obtained from patients' medical records. Peripheral blood DNA methylation levels were determined for the BDNF, COMT, and SLC6A4 genes. We found a significant negative correlation between COMT_1 amplicon methylation and acute symptom scores, with BDI-II (R(22) = 0.190, p = 0.033), IDS-C (R(22) = 0.199, p = 0.029), and HAM-A (R(22) = 0.231, p = 0.018) all showing a similar degree of correlation. Our results suggest that DNA methylation follows flexible dynamics, with methylation levels closely associated with acute clinical presentation rather than with the duration of anxiety and depression. These results provide important insights into the dynamic nature of DNA methylation in anxiety and affective disorders and contribute to our understanding of the complex interplay between stress, epigenetics, and individual phenotype.

Associative gene networks reveal novel candidates important for ADHD and dyslexia comorbidity

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) is commonly associated with developmental dyslexia (DD), which are both prevalent and complicated pediatric neurodevelopmental disorders that have a significant influence on children's learning and development. Clinically, the comorbidity incidence of DD and ADHD is between 25 and 48%. Children with DD and ADHD may have more severe cognitive deficiencies, a poorer level of schooling, and a higher risk of social and emotional management disorders. Furthermore, patients with this comorbidity are frequently treated for a single condition in clinical settings, and the therapeutic outcome is poor. The development of effective treatment approaches against these diseases is complicated by their comorbidity features. This is often a major problem in diagnosis and treatment. In this study, we developed bioinformatical methodology for the analysis of the comorbidity of these two diseases. As such, the search for candidate genes related to the comorbid conditions of ADHD and DD can help in elucidating the molecular mechanisms underlying the comorbid condition, and can also be useful for genotyping and identifying new drug targets.

RESULTS

Using the ANDSystem tool, the reconstruction and analysis of gene networks associated with ADHD and dyslexia was carried out. The gene network of ADHD included 599 genes/proteins and 148,978 interactions, while that of dyslexia included 167 genes/proteins and 27,083 interactions. When the ANDSystem and GeneCards data were combined, a total of 213 genes/proteins for ADHD and dyslexia were found. An approach for ranking genes implicated in the comorbid condition of the two diseases was proposed. The approach is based on ten criteria for ranking genes by their importance, including relevance scores of association between disease and genes, standard methods of gene prioritization, as well as original criteria that take into account the characteristics of an associative gene network and the presence of known polymorphisms in the analyzed genes. Among the top 20 genes with the highest priority DRD2, DRD4, CNTNAP2 and GRIN2B are mentioned in the literature as directly linked with the comorbidity of ADHD and dyslexia. According to the proposed approach, the genes OPRM1, CHRNA4 and SNCA had the highest priority in the development of comorbidity of these two diseases. Additionally, it was revealed that the most relevant genes are involved in biological processes related to signal transduction, positive regulation of transcription from RNA polymerase II promoters, chemical synaptic transmission, response to drugs, ion transmembrane transport, nervous system development, cell adhesion, and neuron migration.

CONCLUSIONS

The application of methods of reconstruction and analysis of gene networks is a powerful tool for studying the molecular mechanisms of comorbid conditions. The method put forth to rank genes by their importance for the comorbid condition of ADHD and dyslexia was employed to predict genes that play key roles in the development of the comorbid condition. The results can be utilized to plan experiments for the identification of novel candidate genes and search for novel pharmacological targets.

The Role of Pharmacogenetics in Personalizing the Antidepressant and Anxiolytic Therapy

Pharmacotherapy for neuropsychiatric disorders, such as anxiety and depression, has been characterized by significant inter-individual variability in drug response and the development of side effects. Pharmacogenetics, as a key part of personalized medicine, aims to optimize therapy according to a patient's individual genetic signature by targeting genetic variations involved in pharmacokinetic or pharmacodynamic processes. Pharmacokinetic variability refers to variations in a drug's absorption, distribution, metabolism, and elimination, whereas pharmacodynamic variability results from variable interactions of an active drug with its target molecules. Pharmacogenetic research on depression and anxiety has focused on genetic polymorphisms affecting metabolizing cytochrome P450 (CYP) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzymes, P-glycoprotein ATP-binding cassette (ABC) transporters, and monoamine and γ-aminobutyric acid (GABA) metabolic enzymes, transporters, and receptors. Recent pharmacogenetic studies have revealed that more efficient and safer treatments with antidepressants and anxiolytics could be achieved through genotype-guided decisions. However, because pharmacogenetics cannot explain all observed heritable variations in drug response, an emerging field of pharmacoepigenetics investigates how epigenetic mechanisms, which modify gene expression without altering the genetic code, might influence individual responses to drugs. By understanding the epi(genetic) variability of a patient's response to pharmacotherapy, clinicians could select more effective drugs while minimizing the likelihood of adverse reactions and therefore improve the quality of treatment.

The association of brain-derived neurotrophic factor with the diagnosis and treatment response in depression

INTRODUCTION

Recent evidence from the studies evaluating the association between brain derived neurotrophic factor (BDNF) concentration/levels, BDNF Val66Met (rs6265) polymorphism and major depressive disorders, referred as depression, and the association between BDNF levels and/or BDNF Val66Met with the treatment response in depression, is presented.

AREAS COVERED

This mini review focuses on the changes in the peripheral BDNF levels in blood (serum, plasma, platelets) in patients with depression before or after treatment with antidepressant drugs or different therapeutic strategies. In addition, this review describes the recent data on the possible association between different antidepressants/therapeutic strategies and the particular BDNF Val66Met genotypes, evaluating the risk alleles associated with the response in patients with depression.

EXPERT OPINION

BDNF has an important role in the pathophysiology and treatment response in depression. Most data reveal that peripheral BDNF levels are lower before than after antidepressant treatment and might be used as potential biomarkers of therapeutic response. Novel therapeutic strategies should target restoring/increasing BDNF levels.

Genetics of nonpharmacological treatments of depression

Nonpharmacological antidepressant treatments are effective and well tolerated in selected patients. However, response is heterogeneous and validated biomarkers would be precious to aid treatment choice. We searched Pubmed, Scopus, and Google Scholar until May 2022 for original articles evaluating the association of genetic variables with the efficacy of nonpharmacological treatments for major depressive episodes. Most studies analyzed small sample sizes using the candidate gene approach, leading to poorly replicated findings that need to be interpreted cautiously. The few available methylome-wide and genome-wide association studies (GWASs) considered only electroconvulsive therapy (ECT) and cognitive-behavioral therapy in small samples, providing interesting findings by using polygenic risk scores. A deeper knowledge of the genetic factors implicated in treatment response may lead to a better understanding of the neurobiological mechanisms of nonpharmacological therapies for depression, and depression itself. Future GWAS are going to expand their sample size, thanks to consortia such as the gen-ECT-ic consortium.

BDNF-related mutations in major depressive disorder: a systematic review

OBJECTIVE

A better understanding of the genetic, molecular and cellular mechanisms of brain-derived neurotrophic factor (BDNF) and its association with neuroplasticity could play a pivotal role in finding future therapeutic targets for novel drugs in major depressive disorder (MDD). Because there are conflicting results regarding the exact role of BDNF polymorphisms in MDD still, we set out to systematically review the current evidence regarding BDNF-related mutations in MDD.

METHODS

We conducted a keyword-guided search of the PubMed and Embase databases, using 'BDNF' or 'brain-derived neurotrophic factor' and 'major depressive disorder' and 'single-nucleotide polymorphism'. We included all publications in line with our exclusion and inclusion criteria that focused on BDNF-related mutations in the context of MDD.

RESULTS

Our search yielded 427 records in total. After screening and application of our eligibility criteria, 71 studies were included in final analysis. According to present overall scientific data, there is a possibly major pathophysiological role for BDNF neurotrophic systems to play in MDD. However, on the one hand, the synthesis of evidence makes clear that likely no overall association of BDNF-related mutations with MDD exists. On the other hand, it can be appreciated that solidifying evidence emerged on specific significant sub-conditions and stratifications based on various demographic, clinico-phenotypical and neuromorphological variables.

CONCLUSIONS

Further research should elucidate specific BDNF-MDD associations based on demographic, clinico-phenotypical and neuromorphological variables. Furthermore, biomarker approaches, specifically combinatory ones, involving BDNF should be further investigated.

Perspectives for the application of neurogenetic research in programming Neurorehabilitation

Certain genetic variants underlie the proper functioning of the nervous system. They affect the nervous system in all aspects - molecular, systemic, cognitive, computational and sensorimotor. The greatest changes in the nervous system take place in the process of its maturation in the period of psychomotor development, as well as during neurorehabilitation, the task of which is to rebuild damaged neuronal pathways, e.g. by facilitating movement or training cognitive functions. Certain genetic polymorphisms affect the effectiveness of the processes of reconstruction or restoration of neural structures, which is clearly reflected in the effects of neurorehabilitation. This review presents the perspectives for the application of neurogenetic research in programming neurorehabilitation by determining the relationship of as many as 16 different genetic polymorphisms with specific functions of importance in rehabilitation. Thanks to this broad view, it may be possible to predict the effectiveness of rehabilitation on the basis of genetic testing, which would significantly contribute to the development of personalized medicine and to the optimal management of medical services in healthcare systems.

Polymorphisms of COMT and CREB1 are associated with treatment-resistant depression in a Chinese Han population

Genetic factors play a crucial role for the pathophysiology of treatment-resistant depression (TRD). It has been established that Catechol-O-methyltransferase (COMT) and cyclic amp-response element-binding protein (CREB) are associated with antidepressant response. The aim of this study was to explore the association between single nucleotide polymorphisms (SNPs) in COMT and CREB1 genes and TRD in a Chinese population. We recruited 181 patients with major depressive disorder (MDD) and 80 healthy controls, including 81 TRD patients. Depressive symptoms were assessed with the Hamilton Depression Rating Scale-17 (HDRS). Genotyping was performed using mass spectrometry. Genetic analyses were conducted by PLINK Software. The distribution of COMT SNP rs4818 allele and genotypes were significantly different between TRD and controls. Statistical differences in allele frequencies were observed between TRD and non-TRD groups, including rs11904814 and rs6740584 in CREB1 gene, rs4680 and rs4818 in COMT gene. There were differences in the distribution of HDRS total scores among different phenotypes of CREB1 rs11904814, CREB1 rs6740584, COMT rs4680 and rs4818. Gene-gene interaction effect of COMT-CREB1 (rs4680 × rs6740584) revealed significant epistasis in TRD. There findings indicate that COMT and CREB1 polymorphisms influence the risk of TRD and affect the severity of depressive symptoms of MDD.

BDNF Genetic Variant and Its Genotypic Fluctuation in Major Depressive Disorder

Major depressive disorder (MDD) still has an unknown etiology and mechanisms. Many studies have been conducted seeking to associate and understand the connection of different genetic variants to this disease. Researchers have extensively studied the brain-derived neurotrophic factor (BDNF) Val66Met genetic variant in MDD; yet, their findings remain inconsistent. This systematic review sought to verify the GG (Val/Val) genotype frequency fluctuation in different populations with MDD. For this, we searched in different databases and, after applying the eligibility criteria, selected 17 articles. Most studies demonstrate the higher frequency of the ancestral (wild) GG (Val/Val) genotype, although associations of the polymorphic A (Met) allele, changes in BDNF protein serum levels, or both were also found in MDD, whether related to the disease's development or other factors. Nevertheless, despite these findings, disagreements between several studies are seen. For this reason, further BDNF Val66Met genetic variant studies should not only bridge the gap in the knowledge of this polymorphism's role in MDD's different facets but also analyze the genotypic and phenotypic heterogeneity in different populations to help provide a better quality of life for patients.

Effect of Catechol-O-Methyltransferase Genotype Polymorphism on Neurological and Psychiatric Disorders: Progressing Towards Personalized Medicine

Different polymorphisms of the catechol-O-methyltransferase (COMT) gene affect the COMT enzyme activity. The COMT enzyme plays a major role in the pathophysiology of various neurological and psychiatric disorders. This review article aims to discuss what recent research has discovered about the association of COMT genotype polymorphism with neurological and psychiatric disorders and the scope for the knowledge to be applied for advancement in therapeutics. We searched PubMed and Google Scholar databases and found 1656 articles. We included observational studies, clinical trials, and meta-analyses in the English language published between 2019 and 2021. We screened the articles based on the title and the abstract and found 26 relevant articles. Diseases or conditions studied primarily were schizophrenia, Parkinson’s disease, Alzheimer’s disease, substance use, and depression. This article highlights how genetics influences the susceptibility of an individual to neurological and psychiatric diseases and the variations in the specific symptoms of those diseases. The review showed that the variability in individual response to therapeutic interventions stems from the gene level. This knowledge can contribute towards the dawn of a new era of personalized medicine.

Exploring the Role of Alcohol Metabolizing Genotypes in a 12-Week Clinical Trial of Naltrexone for Alcohol Use Disorder

Background: The efficacy of naltrexone in the treatment of alcohol use disorder (AUD) has been associated with a set of variables not directly related with the expression of opioid receptors. All the variables have been found to be highly associated with AUD itself or more severe clinical levels of AUD. Objectives: Given the high association between alcohol metabolizing enzymes (AME) and the outcome of AUD, the present study aims to investigate the role of AME genotype variants in the treatment of AUD with naltrexone. Methods: We carried out a 12-week longitudinal clinical trial based on the treatment of AUD patients with naltrexone (N = 101), stratified by different alcohol metabolization genotypes. Genotyping was performed after the inclusion of the patients in the study, based on the individual presence of single nucleotide polymorphisms (SNPs) in the ADH (alcohol dehydrogenase)1B (ADH1B*2 and ADH1B*3), ADH1C (ADHC*1) and ALDH (aldehyde dehydrogenase) 2 (ALDH2*2) genes. The outcome of alcohol use has been monitored employing the timeline follow-back during the treatment. Results: The ADH1C*1 (Ile350Val, rs698) and ALDH2*2 (Glu504Lys, rs671) polymorphisms were associated with a better response to naltrexone treatment, whereas the ADH1B*3 (Arg370Cys, rs2066702) allelic variant showed a negative outcome. Conclusions: The present study explores a genomic setting for the treatment of AUD with naltrexone. According to our findings, the association between ADH1C*1 and ALDH2*2 variants and better outcomes suggests a successful treatment, whereas the ADH1B*3 mutated allele might lead to an unsuccessful treatment. Further studies should be performed to investigate the relationship between alcohol metabolizing genotypes, the family history of alcohol use disorders and the effect of naltrexone on the outcomes. Genotyping may be a valuable tool for precision-medicine and individualized approach, especially in the context of alcohol use disorders. The small number of subjects was the main limitation of the present study.

SLC6A4 polymorphisms modulate the efficacy of a tryptophan-enriched diet on age-related depression and social cognition

BACKGROUND & AIMS

In a placebo controlled study we sought to determine if a four-weeks tryptophan-enriched diet is able to improve age-related depression or social cognitive impairment, depending on polymorphisms located in the promoter region of Solute Carrier Family 6 Member 4 (SLC6A4), also known as serotonin transporter (SERT1) gene.

METHODS

91 young volunteers (age: 21 ± 2 yrs) and 127 above 50 years old (58 ± 6 yrs) healthy volunteers completed the study. Participants from the placebo and tryptophan group followed the same protocol. Before starting the study blood samples, to measure serotonin-transporter-linked polymorphic region (5-HTTLPR) and rs25531 polymorphisms, were collected. In addition, before and after completing the study urine samples (to measure 5-hydroxyindolacetic acid (5-HIAA) were taken, while psychological questionnaires (to assess depression and social cognition levels), and a one week dietary record (to calculate the tryptophan (TRP) intake) were assessed.

RESULTS

The triallelic approach of SLC6A4 showed that in S'S´ subjects there was a positive correlation between TRP intake and 5-HIAA levels. Age of participants, SLC6A4 genotype, and experimental condition were important factors contributing to the outcome of depression and social cognition.

CONCLUSIONS

5-HTTLPR and rs25531 polymorphisms play a key role in the response to the TRP- based nutritional intervention, improving only age-related depressive symptoms and empathy in S'S´ subjects who have a higher risk to show signs of depression during their lifetime.

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.