Prediction of remission of depression with clinical variables, neuropsychological performance, and serotonergic/dopaminergic gene polymorphisms

A Bibliometric and Visual Analysis of Single Nucleotide Polymorphism Studies in Depression

BACKGROUND

Genetic polymorphism has been proven to have an important association with depression, which can influence the risk of developing depression, the efficacy of medications, and adverse effects via metabolic and neurological pathways. Nonetheless, aspects of the association between single nucleotide polymorphisms and depression have not been systematically investigated by bibliometric analysis.

OBJECTIVE

The aim of this study was to analyze the current status and trends of single nucleotide polymorphism research on depression through bibliometric and visual analysis.

METHODS

The Web of Science Core Collection was used to retrieve 10,043 articles that were published between 1998 and 2021. CiteSpace (6.1 R4) was used to perform collaborative network analysis, co-citation analysis, co-occurrence analysis, and citation burst detection.

RESULTS

The most productive and co-cited journals were the Journal of Affective Disorders and Biological Psychiatry, respectively, and an analysis of the references showed that the most recent research focused on the largest thematic cluster, "5-HT", reflecting the important research base in this area. "CYP2D6" has been in the spotlight since its emergence in 2009 and has become a research hotspot since its outbreak in 2019. However, "BDNF ", "COMT ", "older adults", "loci", and "DNA methylation" are also the new frontier of research, and some of them are currently in the process of exploration.

CONCLUSION

These findings offer a useful perspective on existing research and potential future approaches in the study of the association between single nucleotide polymorphisms and depression, which may assist researchers in selecting appropriate collaborators or journals.

Cognitive performance in depression in low- and middle-income countries: A systematic review with meta-analytic components

BACKGROUND

Depression is highly prevalent in low- and middle- income countries (LMIC) and associated with significant cognitive dysfunction across multiple domains. However, little is known about neurocognitive tests used in people with depression in LMIC. We aimed to investigate cognitive performance and cognitive tests in depression research in LMIC.

METHODS

APA PsycInfo, Embase, Ovid MEDLINE, and Global Health were systematically searched for studies that implemented a cognitive performance test in a depressed, LMIC population. Tool quality was assessed using an adapted scale for quality of measures in cross-cultural settings. Data extracted included demographics, depression and cognitive performance measures, and cognitive performance comparisons between depression and control groups.

RESULTS

29 studies met eligibility criteria, involving a total of 19,100 participants from 11 LMIC. 93.1 % of studies were conducted in upper middle-income countries. 67 cognitive performance tools were implemented. Reliability was reported for 5.6 % of cognitive performance tests and validity was reported for 8.3 %. 36.1 % of tests used were culturally adapted. 75.9 % of included studies implemented at least one memory test. Cognitive deficits were observed in all depressed groups, especially in memory (Cohen's d = -1.60, 95 % CI -2.02 to -1.18).

LIMITATIONS

Heterogeneity between studies; averaged results across memory subtypes; no assessment of depression severity and cognitive deficits associations; restrictive search terms.

CONCLUSIONS

Cognitive impairments in depression, especially in memory, are prevalent in LMIC. This research has drawn attention to the burden of cognitive dysfunction in depression in LMIC, and to the disparate research gap in LMIC. PROSPERO registration CRD42022315397.

Exploration of baseline and early changes in neurocognitive characteristics as predictors of treatment response to bupropion, sertraline, and placebo in the EMBARC clinical trial

BACKGROUND

Treatment for major depressive disorder (MDD) is imprecise and often involves trial-and-error to determine the most effective approach. To facilitate optimal treatment selection and inform timely adjustment, the current study investigated whether neurocognitive variables could predict an antidepressant response in a treatment-specific manner.

METHODS

In the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial, outpatients with non-psychotic recurrent MDD were first randomized to an 8-week course of sertraline selective serotonin reuptake inhibitor or placebo. Behavioral measures of reward responsiveness, cognitive control, verbal fluency, psychomotor, and cognitive processing speeds were collected at baseline and week 1. Treatment responders then continued on another 8-week course of the same medication, whereas non-responders to sertraline or placebo were crossed-over under double-blinded conditions to bupropion noradrenaline/dopamine reuptake inhibitor or sertraline, respectively. Hamilton Rating for Depression scores were also assessed at baseline, weeks 8, and 16.

RESULTS

Greater improvements in psychomotor and cognitive processing speeds within the first week, as well as better pretreatment performance in these domains, were specifically associated with higher likelihood of response to placebo. Moreover, better reward responsiveness, poorer cognitive control and greater verbal fluency were associated with greater likelihood of response to bupropion in patients who previously failed to respond to sertraline.

CONCLUSION

These exploratory results warrant further scrutiny, but demonstrate that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.

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.

Prediction of Antidepressant Efficacy by Cognitive Function in First-Episode Late-Life Depression: A Pilot Study

The response rate of treatment for late-life depression (LLD) is only 25-60%. The cognitive impairment associated with LLD often affects the effectiveness of antidepressants and may has the potential ability to predict response. This study seeks a biomarker for baseline cognitive function to predict efficacy of antidepressants. Sixty patients diagnosed with LLD received escitalopram or sertraline treatment for 8 weeks. Clinical symptom was measured using Hamilton Depression Rating Scale-17 (HAMD-17) and cognitive function was measured using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Trail Making Test (TMT) before and after 8-week treatment. Patients were divided into treatment effective group (TE) and treatment ineffective group (TI) according to reduction rate in scores of HAMD-17 after treatment. Thirty-eight matched healthy controls (HC) were assessed using RBANS and TMT. There was significant decrease of score of RBANS and increase of score of TMT in patients with LLD compared with HC. Regression analysis revealed that change in HAMD-17 score was significantly positively associated with baseline score of picture naming, figure copy, digit span, and delayed memory. The preliminary findings suggested that working memory, attention, visuospatial, language function, and delayed memory should be examined further as a means of providing the useful objective biomarkers of treatment response.

CLINICAL TRIALS REGISTRATION

[www.ClinicalTrials.gov], identifier [ChiCTR2100042370].

5-HTTLPR-rs25531 and Antidepressant Treatment Outcomes in Korean Patients with Major Depression

INTRODUCTION

Despite the ethnic differences in 5-HTTLPR (S allele relates to better antidepressant response in Korean and Japanese people, while L allele with better response in Caucasians), it is unclear whether 5-HTTLPR and its high expression locus rs25531 are interactively associated with antidepressant treatment outcome. We investigated the individual and interaction effects of these polymorphisms on antidepressant treatment outcomes in the Korean population.

METHODS

A total of 464 Korean subjects with major depressive disorder completed 6 weeks of antidepressant monotherapy. Venous blood was extracted for genotyping 5-HTTLPR and rs25531 by polymerase chain reaction and DNA sequencing. We used logistic regression analyses to verify the main and interaction effects of 5-HTTLPR and rs25531 on response and remission after antidepressant treatment.

RESULTS

After adjusting for covariates, the SS genotype of 5-HTTLPR was significantly associated with better treatment outcomes (p<0.001, odds ratio [OR] [95% confidence interval (CI)]=2.435 [1.551, 3.823] in response; p<0.001, OR [95% CI]=2.912 [1.730, 4.903] in remission), while G-containing genotype (AG+GG) of rs25531 was only associated with remission (p=0.034, OR [95% CI]=2.104 [1.058, 4.181]). The interaction effect of 5-HTTLPR and rs25531 on response and remission was insignificant (all p>0.05).

DISCUSSION

Our findings suggest variations in allelic frequency and functionality of 5-HTTLPR and rs25531 among the different ethnicities. We found a minor advantage of rs25531 in achieving remission. However, there was no interaction effect with 5-HTTLPR.

Pretreatment Reward Sensitivity and Frontostriatal Resting-State Functional Connectivity Are Associated With Response to Bupropion After Sertraline Nonresponse

BACKGROUND

Standard guidelines recommend selective serotonin reuptake inhibitors as first-line antidepressants for adults with major depressive disorder, but success is limited and patients who fail to benefit are often switched to non-selective serotonin reuptake inhibitor agents. This study investigated whether brain- and behavior-based markers of reward processing might be associated with response to bupropion after sertraline nonresponse.

METHODS

In a two-stage, double-blinded clinical trial, 296 participants were randomized to receive 8 weeks of sertraline or placebo in stage 1. Individuals who responded continued on another 8-week course of the same intervention in stage 2, while sertraline and placebo nonresponders crossed over to bupropion and sertraline, respectively. Data from 241 participants were analyzed. The stage 2 sample comprised 87 patients with major depressive disorder who switched medication and 38 healthy control subjects. A total of 116 participants with major depressive disorder treated with sertraline in stage 1 served as an independent replication sample. The probabilistic reward task and resting-state functional magnetic resonance imaging were administered at baseline.

RESULTS

Greater pretreatment reward sensitivity and higher resting-state functional connectivity between bilateral nucleus accumbens and rostral anterior cingulate cortex were associated with positive response to bupropion but not sertraline. Null findings for sertraline were replicated in the stage 1 sample.

CONCLUSIONS

Pretreatment reward sensitivity and frontostriatal connectivity may identify patients likely to benefit from bupropion following selective serotonin reuptake inhibitor failures. Results call for a prospective replication based on these biomarkers to advance clinical care.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Association Study Between Serotonin Transporter Gene and Fluoxetine Response in Mexican Patients With Major Depressive Disorder

OBJECTIVE

Pharmacogenetic studies have identified genetic variants associated with fluoxetine response in patients with major depression disorder (MDD). The serotonin transporter gene is the principal site of action of selective serotonin reuptake inhibitors. Previous studies analyzing SLC6A4 gene variants are inconsistent and differ among populations. The aim of the present study was to analyze the association between 5-HTTLPR/rs24531 triallelic polymorphism and fluoxetine response in Mexican patients with MDD.

METHODS

We analyzed a sample of 150 patients with MDD. Fluoxetine response was assessed according to a reduction in the Hamilton Depression Rating Scale and Montgomery Depression Rating Scale scores of 50% or more at 8 weeks from baseline. In addition, we analyzed the genotype and allele distribution between responder and nonresponder patients in a subgroup of very severe depression patients.

RESULTS

We did not find association between fluoxetine responders and 5-HTTLPR/rs25531 variants (P = 0.0637). However, in the analysis of severe depression at baseline (Hamilton Depression Rating Scale ≥ 25), we observed a high frequency of low activity alleles (S/LG) in nonresponders patients (P = 0.0102).

CONCLUSIONS

Our findings showed an association between low activity alleles of SLC6A4 gene and fluoxetine nonresponse in patients with severe depression.

A Systematic Review of Cognitive Predictors of Treatment Outcome in Major Depression

Background: Research suggests that only 50% of patients with major depression respond to psychotherapy or pharmacological treatment, and relapse is common. Therefore, there is interest in elucidating factors that help predict clinical response. Cognitive impairment is a key feature of depression, which often persists beyond remission; thus, the aim of this systematic review was to determine whether baseline cognitive functioning can predict treatment outcomes in individuals with depression. Method: Studies examining cognitive predictors of treatment response in depression were identified using Pub Med and Web of Science databases. Given the heterogeneity of outcome measures, the variety of treatment protocols, and the differing ways in which data was presented and analyzed, a narrative rather than meta-analytic review technique was used. Results: 39 studies met inclusion criteria. Findings in younger adult samples were inconclusive. There was some evidence for a predictive effect of executive function and to a lesser extent, psychomotor speed, on treatment response. There was no evidence of learning or memory being associated with treatment response. In older-aged samples, the evidence was much more consistent, suggesting that poor executive function predicts poor response to SSRIs. Conclusions: Findings from the present review suggest that certain aspects of cognitive functioning, particularly executive function, may be useful in predicting treatment response in depression. This is certainly the case in elderly samples, with evidence suggesting that poor executive functioning predicts poor response to SSRIs. With further research, baseline cognitive functioning may serve as a factor which helps guide clinical decision making. Moreover, cognitive deficits may become targets for specific pharmacological or psychological treatments, with the hope of improving overall outcome.

Pharmacogenetics of major depressive disorder: top genes and pathways toward clinical applications

The pharmacogenetics of antidepressants has been not only a challenging but also frustrating research field since its birth in the 1990s. Indeed, great expectations followed the first evidence of familiar aggregation of antidepressant response. Despite the progress from candidate gene studies to genome-wide association studies (GWAS), results fell out the expectations and they were often inconsistent. Anyway, the cumulative evidence supports the involvement of some genes and molecular pathways in antidepressant efficacy. The best single genes are SLC6A4, HTR2A, BDNF, GNB3, FKBP5, ABCB1, and cytochrome P450 genes (CYP2D6 and CYP2C19). Molecular pathways involved in inflammation and neuroplasticity show the greatest support. The first studies evaluating benefits of genotype-guided antidepressant treatments provided encouraging results and confirmed the relevance of SLC6A4, HTR2A, ABCB1, and cytochrome P450 genes. Further progress in genotyping and data analysis would allow to move forward and complete the understanding of antidepressant pharmacogenetics and its translation into clinical applications.

Effects of remission speed and improvement of cognitive functions of depressed patients

Major depressive disorder (MDD) presents neuropsychological alterations which improve after the treatment, but it might be mediated by clinical variables. Our goal is to study whether the speed of remission of MDD bears any relation to the improvement of the patients' cognitive functioning after a successful treatment. We carried out clinical and neuropsychological assessments of 51 patients with MDD. After these procedures they underwent a 24-week treatment with fluoxetine, and were assessed again with the same battery used prior to treatment. They were arranged into three groups according to how rapid their symptoms remitted. The patients with a rapid remission presented improvements in working memory, speed of information processing, and some executive functions, unlike the other groups. Rapid remitters also improved in episodic memory and executive functions more than the other patients.

Understanding the pharmacogenetics of selective serotonin reuptake inhibitors

INTRODUCTION

The genetic background of antidepressant response represents a unique opportunity to identify biological markers of treatment outcome. Encouraging results alternating with inconsistent findings made antidepressant pharmacogenetics a stimulating but often discouraging field that requires careful discussion about cumulative evidence and methodological issues.

AREAS COVERED

The present review discusses both known and less replicated genes that have been implicated in selective serotonin reuptake inhibitors (SSRIs) efficacy and side effects. Candidate genes studies and genome-wide association studies (GWAS) were collected through MEDLINE database search (articles published till January 2014). Further, GWAS signals localized in promising genetic regions according to candidate gene studies are reported in order to assess the general comparability of results obtained through these two types of pharmacogenetic studies. Finally, a pathway enrichment approach is applied to the top genes (those harboring SNPs with p < 0.0001) outlined by previous GWAS in order to identify possible molecular mechanisms involved in SSRI effect.

EXPERT OPINION

In order to improve the understanding of SSRI pharmacogenetics, the present review discusses the proposal of moving from the analysis of individual polymorphisms to genes and molecular pathways, and from the separation across different methodological approaches to their combination. Efforts in this direction are justified by the recent evidence of a favorable cost-utility of gene-guided antidepressant treatment.

Prediction of the time-course pattern of remission in depression by using clinical, neuropsychological, and genetic variables

BACKGROUND

The prediction of remission in pharmacologically-treated MDD patients has been scarcely studied. The goal of our work is to study the possible effect of clinical variables, neuropsychological performance, and the 5HTTLPR, the rs25531 of the SLC6A4 gene, and the val108/58Met of the COMT gene polymorphisms on the prediction of the speed of remission in MDD patients.

METHODS

Seventy-two depressed patients were genotyped according to the aforementioned polymorphisms and were clinically and neuropsychologically assessed before a 12-week fluoxetine treatment.

RESULTS

From this original sample 51 patients were considered as remitters at the end of week 12. Thirteen out of those showed a rapid response pattern, 24 showed an oscillating response pattern, and 14 showed a slow response pattern. The following variable combination is capable of showing a statistically significant relationship with the pattern of remission of patients with MDD: initial Hamilton score, age at first depressive episode, AG and GG alleles of the val108/58Met COMT polymorphism, Stroop PC, and SWM Strategy.

LIMITATIONS

We have a slightly small sample size, which came to prominence during the data analysis since we were working with 3 subgroups. In this study, the placebo effect has not been controlled.

DISCUSSION

Our data suggest that the patients with MDD who remit after a 12-week treatment with fluoxetine show one of the following time-course patterns: a rapid symptomatic improvement, or a slow or oscillating pattern of remission. A combination of clinical, neuropsychological, and genetic variables allows us to predict these response patterns.