Model-Based Economic Evaluation of Treatments for Depression: A Systematic Literature Review

Cost-effectiveness analysis of mHealth applications for depression in Germany using a Markov cohort simulation

Regulated mobile health applications are called digital health applications ("DiGA") in Germany. To qualify for reimbursement by statutory health insurance companies, DiGA have to prove positive care effects in scientific studies. Since the empirical exploration of DiGA cost-effectiveness remains largely uncharted, this study pioneers the methodology of cohort-based state-transition Markov models to evaluate DiGA for depression. As health states, we define mild, moderate, severe depression, remission and death. Comparing a future scenario where 50% of patients receive supplementary DiGA access with the current standard of care reveals a gain of 0.02 quality-adjusted life years (QALYs) per patient, which comes at additional direct costs of ~1536 EUR per patient over a five-year timeframe. Influencing factors determining DiGA cost-effectiveness are the DiGA cost structure and individual DiGA effectiveness. Under Germany's existing cost structure, DiGA for depression are yet to demonstrate the ability to generate overall savings in healthcare expenditures.

Evaluating the effectiveness and cost-effectiveness of a digital, app-based intervention for depression (VMood) in community-based settings in Vietnam: Protocol for a stepped-wedge randomized controlled trial

The COVID-19 pandemic has amplified mental health problems and highlighted inequitable gaps in care worldwide. In response there has been an explosion of digital interventions such as smartphone applications ("apps") to extend care. The objective of this trial is to evaluate the effectiveness and cost-effectiveness of a digital depression intervention (VMood), delivered via a smartphone app. VMood is adapted from an in-person intervention that was delivered by non-specialist providers and shown to be effective in the Vietnamese context in our previous trial (2016-2019). A stepped-wedge, randomized controlled trial will be conducted across eight provinces in Vietnam. Adults aged 18 years and over will be recruited through community-based primary care centres and screened for depression using the embedded Patient Health Questionnaire-9 (primary outcome measure). Participants scoring 10-19, indicating depression caseness, will be randomly allocated to the intervention or control group until the target of 336 is reached. Secondary outcome measures will examine the effect of the intervention on commonly co-occuring anxiety, quality of life and work productivity, along with use of alcohol and tobacco products. Assessments will be administered through an online survey platform (REDCap) at baseline, and at every 3 months until 3 months post-intervention. Intervention-group participants will receive VMood for a 3-month period, with online support provided by social workers. Control-group participants will receive a limited version of the app until they cross into the intervention group. Generalized Linear Mixed-effect Models for clustered measures will be used for all outcomes data. We will conduct a cost-effectiveness analysis alongside the trial to capture VMood's costs and benefits. This trial will provide evidence on the effectiveness and cost-effectiveness of a digital mental health intervention adapted from an in-person intervention. This trial will also contribute important information to the growing and promising field of digital mental health. Trail regulation. Registered at ClinicalTrials.gov, identifier [NCT05783531].

A Promising Approach to Optimizing Sequential Treatment Decisions for Depression: Markov Decision Process

The most appropriate next step in depression treatment after the initial treatment fails is unclear. This study explores the suitability of the Markov decision process for optimizing sequential treatment decisions for depression. We conducted a formal comparison of a Markov decision process approach and mainstream state-transition models as used in health economic decision analysis to clarify differences in the model structure. We performed two reviews: the first to identify existing applications of the Markov decision process in the field of healthcare and the second to identify existing health economic models for depression. We then illustrated the application of a Markov decision process by reformulating an existing health economic model. This provided input for discussing the suitability of a Markov decision process for solving sequential treatment decisions in depression. The Markov decision process and state-transition models differed in terms of flexibility in modeling actions and rewards. In all, 23 applications of a Markov decision process within the context of somatic disease were included, 16 of which concerned sequential treatment decisions. Most existing health economic models relating to depression have a state-transition structure. The example application replicated the health economic model and enabled additional capacity to make dynamic comparisons of more interventions over time than was possible with traditional state-transition models. Markov decision processes have been successfully applied to address sequential treatment-decision problems, although the results have been published mostly in economics journals that are not related to healthcare. One advantage of a Markov decision process compared with state-transition models is that it allows extended action space: the possibility of making dynamic comparisons of different treatments over time. Within the context of depression, although existing state-transition models are too basic to evaluate sequential treatment decisions, the assumptions of a Markov decision process could be satisfied. The Markov decision process could therefore serve as a powerful model for optimizing sequential treatment in depression. This would require a sufficiently elaborate state-transition model at the cohort or patient level.

Economic evaluations of audit and feedback interventions: a systematic review

BACKGROUND

The effectiveness of audit and feedback (A&F) interventions to improve compliance to healthcare guidelines is supported by randomised controlled trials (RCTs) and meta-analyses of RCTs. However, there is currently a knowledge gap on their cost-effectiveness.

OBJECTIVE

We aimed to assess whether A&F interventions targeting improvements in compliance to recommended care are economically favourable.

METHODS

We conducted a systematic review including experimental, observational and simulation-based economic evaluation studies of A&F interventions targeting healthcare providers. Comparators were a 'do nothing' strategy, or any other intervention not involving A&F or involving a subset of A&F intervention components. We searched MEDLINE, CINAHL, CENTRAL, Econlit, EMBASE, Health Technology Assessment Database, MEDLINE, NHS Economic Evaluation Database, ABI/INFORM, Web of Science, ProQuest and websites of healthcare quality associations to December 2021. Outcomes were incremental cost-effectiveness ratios, incremental cost-utility ratios, incremental net benefit and incremental cost-benefit ratios. Pairs of reviewers independently selected eligible studies and extracted relevant data. Reporting quality was evaluated using CHEERS (Consolidated Health Economic Evaluation Reporting Standards). Results were synthesised using permutation matrices for all studies and predefined subgroups.

RESULTS

Of 13 221 unique citations, 35 studies met our inclusion criteria. The A&F intervention was dominant (ie, at least as effective with lower cost) in 7 studies, potentially cost-effective in 26 and was dominated (ie, the same or less effectiveness and higher costs) in 2 studies. A&F interventions were more likely to be economically favourable in studies based on health outcomes rather than compliance to recommended practice, considering medical costs in addition to intervention costs, published since 2010, and with high reporting quality.

DISCUSSION

Results suggest that A&F interventions may have a high potential to be cost-effective. However, as is common in systematic reviews of economic evaluations, publication bias could have led to an overestimation of their economic value.

DIP: Natural history model for major depression with incidence and prevalence

BACKGROUND

Major depression is a treatable disease, and untreated depression can lead to serious health complications. Therefore, prevention, early identification, and treatment efforts are essential. Natural history models can be utilized to make informed decisions about interventions and treatments of major depression.

METHODS

We propose a natural history model of major depression. We use steady-state analysis to study the discrete-time Markov chain model. For this purpose, we solved the system of linear equations and tested the parameter and transition probabilities empirically.

RESULTS

We showed that bias in parameters might collectively cause a significant mismatch in a model. If incidence is correct, then lifetime prevalence is 33.2% for females and 20.5% for males, which is higher than reported values. If prevalence is correct, then incidence is .0008 for females and .00065 for males, which is lower than reported values. The model can achieve feasibility if incidence is at low levels and recall bias of the lifetime prevalence is quantified to be 31.9% for females and 16.3% for males.

LIMITATIONS

This model is limited to major depression, and patients who have other types of depression are assumed healthy. We assume that transition probabilities (except incidence rates) are correct.

CONCLUSION

We constructed a preliminary model for the natural history of major depression. We determined the lifetime prevalences are underestimated and the average incidence rates may be underestimated for males. We conclude that recall bias needs to be accounted for in modeling or burden estimates, where the recall bias should increase with age.

The Incidence and Costs of Adverse Events Associated with Antidepressants: Results from a Systematic Review, Network Meta-Analysis and Multi-Country Economic Model

PURPOSE

There is variation in the safety profile of antidepressants. Rates of adverse events along with the costs of treating them can be an important factor influencing the choice of depression treatment. This study sought to estimate the comparative safety of commonly prescribed antidepressants, and how the costs of treating these varied across European countries.

METHODS

A systematic literature review was conducted (in Medline, Embase, PsycINFO and CENTRAL) to identify placebo-controlled trials reporting rates of at least one type of sexual dysfunction, weight change, insomnia, anxiety, and anhedonia. Eight antidepressants were considered: duloxetine, escitalopram, fluoxetine, paroxetine, sertraline, trazodone, venlafaxine, and vortioxetine. This evidence was synthesised via Bayesian random effects network meta-analyses to provide comparative estimates of safety. A systematic search identified country-specific costs of managing depression and adverse events of antidepressants. Evidence on costs and safety was combined in an economic model to provide country-specific costs for Bulgaria, the Czech Republic, Greece, Hungary, Italy, Romania, Slovakia, Portugal, and Poland.

RESULTS

Trazodone had the lowest rates of both insomnia (odds ratio 0.66, 95% credible interval 0.31 to 1.38) and anxiety (0.13, <0.01 to 1.80). All antidepressants were associated with increased rates of sexual dysfunction relative to placebo. Weight change was largest for fluoxetine (kg change -1.01, -1.40 to -0.60) and sertraline (-1.00, -1.36 to -0.65), although heterogeneity was extreme for this outcome. No evidence was identified for anhedonia. Total costs were lowest for trazodone in all nine of the countries evaluated. This was primarily due to reduced rates of treatment discontinuation.

CONCLUSION

Trazodone generally had the best safety profile of the antidepressants evaluated. This led to healthcare costs being lowest for trazodone in all nine European countries, emphasising the importance of considering rates of adverse events when choosing a pharmacological treatment to treat symptoms of depression.

Appraisal of patient-level health economic models of severe mental illness: systematic review

BACKGROUND

Healthcare decision makers require accurate long-term economic models to evaluate the cost-effectiveness of new mental health interventions.

AIMS

To assess the suitability of current patient-level economic models to estimate long-term economic outcomes in severe mental illness.

METHOD

We undertook pre-specified systematic searches in MEDLINE, Embase and PsycINFO to identify reviews and stand-alone publications of economic models of interventions for schizophrenia, bipolar disorder and major depressive disorder (PROSPERO: CRD42020158243). We screened paper titles and abstracts to identify unique patient-level economic models. We conducted a structured extraction of identified models, recording the presence of key predefined model features. Model quality and validation were appraised using the 2014 ISPOR and 2016 AdViSHE model checklists.

RESULTS

We identified 15 unique patient-level models for psychosis and major depressive disorder from 1481 non-duplicate records. Models addressed schizophrenia (n = 6), bipolar disorder (n = 2) and major depressive disorder (n = 7). The predominant model type was discrete event simulation (n = 9). Model complexity and incorporation of patient heterogeneity varied considerably, and only five models extrapolated costs and outcomes over a lifetime horizon. Key model parameters were often based on low-quality evidence, and checklist quality assessment revealed weak model verification procedures.

CONCLUSIONS

Existing patient-level economic models of interventions for severe mental illness have considerable limitations. New modelling efforts must be supplemented by the generation of good-quality, contemporary evidence suitable for model building. Combined effort across the research community is required to build and validate economic extrapolation models suitable for accurately assessing the long-term value of new interventions from short-term clinical trial data.

Guided Internet-Based Cognitive Behavioral Therapy for Depression: Implementation Cost-Effectiveness Study

Background

Major depressive disorder is a chronic condition; its prevalence is expected to grow with the aging trend of high-income countries. Internet-based cognitive-behavioral therapy has proven efficacy in treating major depressive disorder.

Objective

The objective of this study was to assess the cost-effectiveness of implementing a community internet-based cognitive behavioral therapy intervention (Super@, the Spanish program for the MasterMind project) for treating major depressive disorder.

Methods

The cost-effectiveness of the Super@ program was assessed with the Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing tool, using a 3-state Markov model. Data from the cost and effectiveness of the intervention were prospectively collected from the implementation of the program by a health care provider in Badalona, Spain; the corresponding data for usual care were gathered from the literature. The health states, transition probabilities, and utilities were computed using Patient Health Questionnaire–9 scores.

Results

The analysis was performed using data from 229 participants using the Super@ program. Results showed that the intervention was more costly than usual care; the discounted (3%) and nondiscounted incremental cost-effectiveness ratios were €29,367 and €26,484 per quality-adjusted life-year, respectively (approximately US $35,299 and $31,833, respectively). The intervention was cost-effective based on the €30,000 willingness-to-pay threshold typically applied in Spain (equivalent to approximately $36,060). According to the deterministic sensitivity analyses, the potential reduction of costs associated with intervention scale-up would reduce the incremental cost-effectiveness ratio of the intervention, although it remained more costly than usual care. A discount in the incremental effects up to 5% exceeded the willingness-to-pay threshold of €30,000.

Conclusions

The Super@ program, an internet-based cognitive behavioral therapy intervention for treating major depressive disorder, cost more than treatment as usual. Nevertheless, its implementation in Spain would be cost-effective from health care and societal perspectives, given the willingness-to-pay threshold of €30,000 compared with treatment as usual.

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

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

Cost-effectiveness of an indicated preventive intervention for depression in adolescents: a model to support decision making

BACKGROUND

Adolescent depression has negative health and economic outcomes in the short- and long-term. Indicated preventive interventions, in particular group based cognitive behavioural therapy (GB-CBT), are effective in preventing depression in adolescents with subsyndromal depression. However, little is known about the cost-effectiveness of these interventions.

METHODS

A Markov cohort model was used to conduct cost-effectiveness analyses comparing a GB-CBT indicated preventive intervention for depression, to a no-intervention option in a Swedish setting. Taking a time horizon of 5- and 10 years, incremental differences in societal costs and health benefits expressed as differences in the proportion of cases of depression prevented, and as quality adjusted life years (QALYs) gained were estimated. Through univariate and probabilistic sensitivity analyses, the robustness of the results was explored. Costs, presented in 2018 USD, and effects were discounted at a yearly rate of 3%.

RESULTS

The base-case analysis showed that GB-CBT indicated preventive intervention incurred lower costs, prevented a larger proportion of cases of depression and generated higher QALYs compared to the no-intervention option for both time horizons. Offering the intervention was even a cost saving strategy and demonstrated a probability of being cost-effective of over 95%. In the sensitivity analyses, these results were robust to the modelling assumptions.

LIMITATIONS

The study considered a homogeneous cohort and assumed a constant annual decay rate of the relative treatment effect.

CONCLUSIONS

GB-CBT indicated preventive interventions for depression in adolescence can generate good value for money compared to leaving adolescents with subsyndromal depression untreated.

Protocol for the economic evaluation of metacognitive therapy for cardiac rehabilitation participants with symptoms of anxiety and/or depression

INTRODUCTION

Cardiac rehabilitation (CR) is offered to reduce the risk of further cardiac events and to improve patients' health and quality of life following a cardiac event. Psychological care is a common component of CR as symptoms of depression and/or anxiety are more prevalent in this population, however evidence for the cost-effectiveness of current interventions is limited. Metacognitive therapy (MCT), is a recent treatment development that is effective in treating anxiety and depression in mental health settings and is being evaluated in CR patients. This protocol describes the planned approach to the economic evaluation of MCT for CR patients.

METHODS AND ANALYSIS

The economic evaluation work will consist of a within-trial analysis and an economic model. The PATHWAY Group MCT study has been prospectively designed to collect comprehensive self-reported resource use and health outcome data, including the EQ-5D, within a randomised controlled trial study design (UK Clinical Trials Gateway). A within-trial economic evaluation and economic model will compare the cost-effectiveness of MCT plus usual care (UC) to UC, from a health and social care perspective in the UK. The within-trial analysis will use intention-to-treat and estimate total costs and quality-adjusted life-years (QALYs) for the trial follow-up. Single imputation will be used to impute missing baseline variables. Multiple imputation will be used to impute values missing at follow-up. Items of resource use will be multiplied by published national healthcare costs. Regression analysis will be used to estimate net costs and net QALYs and these estimates will be bootstrapped to generate 10 000 net pairs of costs and QALYs to inform the probability of cost-effectiveness. A decision analytical economic model will be developed to synthesise trial data with the published literature over a longer time frame. Sensitivity analysis will explore uncertainty. Guidance of the methods for economic models will be followed and dissemination will adhere to reporting guidelines.

ETHICS AND DISSEMINATION

The economic evaluation includes a within-trial analysis. The trial which included the collection of this data was reviewed and approved by Ethics. Ethics approval was obtained by the Preston Research Ethics Committee (project ID 156862). The modelling analysis is not applicable for Ethics as it will use data from the trial (secondary analysis) and the published literature. Results of the main trial and economic evaluation will be published in the peer-reviewed National Institute for Health Research (NIHR) journals library (Programme Grants for Applied Research), submitted to a peer-reviewed journal and presented at appropriate conferences.

TRIAL REGISTRATION NUMBER

ISRCTN74643496; Pre-results.

Cost-Utility Analysis of Mindfulness-Based Cognitive Therapy Versus Antidepressant Pharmacotherapy for Prevention of Depressive Relapse in a Canadian Context: Analyse coût-utilité de la thérapie cognitive basée sur la pleine conscience contre la pharmacothérapie antidépressive pour prévenir la rechute de la dépression en contexte canadien

OBJECTIVE

Patients suffering from major depressive disorder (MDD) experience impaired functioning and reduced quality of life, including an elevated risk of episode return. MDD is associated with high societal burden due to increased healthcare utilization, productivity losses, and suicide-related costs, making the long-term management of this illness a priority. The purpose of this study is to evaluate the cost-effectiveness of mindfulness-based cognitive therapy (MBCT), a first-line preventative psychological treatment, compared to maintenance antidepressant medication (ADM), the current standard of care.

METHOD

A cost-utility analysis was conducted over a 24-month time horizon to model differences between MBCT and ADM in cost and quality-adjusted life years (QALY). The analysis was conducted using a decision tree analytic model. Intervention efficacy, utility, and costing data estimates were derived from published sources and expert consultation.

RESULTS

MBCT was found to be cost-effective compared to maintenance ADM over a 24-month time horizon. Antidepressant pharmacotherapy resulted in 1.10 QALY and $17,255.37 per patient on average, whereas MBCT resulted in 1.18 QALY and $15,030.70 per patient on average. This resulted in a cost difference of $2,224.67 and a QALY difference of 0.08, in favor of MBCT. Multiple sensitivity analyses supported these findings.

CONCLUSIONS

From both a societal and health system perspective, utilizing MBCT as a first-line relapse prevention treatment is potentially cost-effective in a Canadian setting. Future economic evaluations should consider combined treatment (e.g., ADM and psychotherapy) as a comparator and longer time horizons as the literature advances.

Simulation modeling validity and utility in colorectal cancer screening delivery: A systematic review

OBJECTIVE

This study sought to assess the impact and validity of simulation modeling in informing decision making in a complex area of healthcare delivery: colorectal cancer (CRC) screening.

MATERIALS AND METHODS

We searched 10 electronic databases for English-language articles published between January 1, 2008, and March 1, 2019, that described the development of a simulation model with a focus on average-risk CRC screening delivery. Included articles were reviewed for evidence that the model was validated, and provided real or potential contribution to informed decision making using the GRADE EtD (Grading of Recommendations Assessment, Development, and Evaluation Evidence to Decision) framework.

RESULTS

A total of 43 studies met criteria. The majority used Markov modeling (n = 31 [72%]) and sought to determine cost-effectiveness, compare screening modalities, or assess effectiveness of screening. No study reported full model validation and only (58%) reported conducting any validation. Majority of models were developed to address a specific health systems or policy question; few articles report the model's impact on this decision (n = 39 [91%] vs. n = 5 [12%]). Overall, models provided evidence relevant to every element important to decision makers as outlined in the GRADE EtD framework.

DISCUSSION AND CONCLUSION

Simulation modeling contributes evidence that is considered valuable to decision making in CRC screening delivery, particularly in assessing cost-effectiveness and comparing screening modalities. However, the actual impact on decisions and validity of models is lacking in the literature. Greater validity testing, impact assessment, and standardized reporting of both is needed to understand and demonstrate the reliability and utility of simulation modeling.

Differential Regulation of DNA Methylation at the CRMP2 Promoter Region Between the Hippocampus and Prefrontal Cortex in a CUMS Depression Model

Current evidence supports the idea that neural plasticity is a potential cause of depression. Abundant studies indicate that CRMP2 has important roles in neural plasticity. Moreover, CRMP2 may contribute to the etiology of depression. However, the regulatory mechanisms underlying the role of CRMP2 remain unclear. DNA methylation alteration is generally acknowledged to be involved in the development of depression. The aim of this study was to explore the relationship between the expression and DNA methylation of CRMP2 in the hippocampus and prefrontal cortex of a rat depression model. Chronic unpredictable mild stress (CUMS) was used to establish a rat depression model, and body weight and behavioral tests were used to evaluate the effects of stress. Real-time PCR and Western blotting were used to test CRMP2 mRNA and protein expression, respectively, in the hippocampus and prefrontal cortex of rats. DNA methylation levels of the CRMP2 promoter were analyzed by bisulfite sequencing PCR (BSP). CUMS caused depressive-like behavior in rats, as evidenced by: decreased body weight and sucrose preference rate; decreases in the total distance traveled, rearing frequency, velocity, and duration in the center in the open field test (OFT); and prolonged immobility in the forced swimming test (FST). CRMP2 mRNA and protein expression in the hippocampus and prefrontal cortex were significantly decreased in the CUMS group compared with the control group. The levels of CRMP2 promoter DNA methylation in the hippocampus of the CUMS group were significantly higher than those of the control group, while these changes were not observed in the prefrontal cortex of CUMS rats. Our data provide evidence that altered expression of CRMP2 in the hippocampus and prefrontal cortex is associated with the pathogenesis of depression. Moreover, the results also suggest regional differences in the regulation of DNA methylation in the CRMP2 promoter between the hippocampus and prefrontal cortex during the development of depression.

GRP Receptor Regulates Depression Behavior via Interaction With 5-HT2a Receptor

OBJECTIVE

Accumulating evidences indicate that gastrin-releasing peptide receptor (GRPR) may contribute to the pathophysiology of depression. However, the mechanism of the involvement of GRPR in the progression of depression remains unclear. Here, we showed the extent to which stress and antidepressant treatment impact GRPR expression, and explored the interactions between 5-HT2a receptor (5-HT2aR) and GRPR at the cellular level.

METHODS

The rat depression models were created with chronic unpredictable mild stress (CUMS). Then, these rats were treated with fluoxetine for 4 weeks after CUMS. We measured body weight and performed behavioral tests to determine the effects of stress and fluoxetine on depressive-like behaviors. Real-time PCR and western blotting were used to measure the mRNA and protein expression levels of GRPR in the hypothalamus. Then, Flag-tagged protein (pcmv-Flag-5HT2aR) and Myc-tagged protein (pcmv-Myc-GRPR) expression vectors were constructed, identified, and transfected into human embryo kidney 293 (HEK293) cells. The interaction between 5-HT2aR and GRPR was detected by coimmunoprecipitation and double-label immunofluorescence.

RESULTS

The rats subjected to 4 weeks of CUMS showed depressive-like behaviors, including decreased body weight, sucrose preference, and distance traveled, rearing frequency and velocity in the open field test and increased immobility time in the forced swimming test. Fluoxetine treatment reversed CUMS-induced depressive-like behavior. The mRNA and protein expression of GRPR in the hypothalamus was significantly increased after 4 weeks CUMS exposure, and treatment with fluoxetine reversed these changes. Coimmunoprecipitation showed that 5-HT2aR and GRPR combine with each other in vitro. Immunofluorescence revealed that the 5-HT2aR and GRPR were colocalization in both the cell membrane and cytoplasm.

CONCLUSION

Our study enhances the understanding of the involvement of GRPR in depression. This study also provides in vitro experimental evidence of the interaction between 5-HT2aR and GRPR, which may play an important role in the pathogenesis of depression.