ABC Family Gene Polymorphisms and Cognitive Functions Interact to Influence Antidepressant Efficacy

• Abstract
• Introduction
• Methods
• Subject
• Treatment programs and depression assessment
• Single nucleotide polymorphism selection and genotyping
• Cognitive assessment
• Dual luciferase assay
• Statistical analysis
• Results
• Clinical sample
• The relationship between single nucleotide polymorphisms and efficacy
• Correlation analysis between single nucleotide polymorphism loci and cognitive function
• Interaction between cognitive function and single nucleotide polymorphisms
• Luciferase gene reporter experiment
• Discussion
• Conclusion
• References

Abstract

Introduction The importance of identifying relevant indicators of antidepressant efficacy is highlighted by the low response rates to antidepressant treatment for depression. The ABC gene family, encoding ATP-dependent transport proteins facilitating the transport of psychotropic drugs, has drawn attention. This study delved into the relationship between antidepressant efficacy and seven single nucleotide polymorphisms of ABCB1 and ABCB6 genes.

Methods A total of 549 depressed patients participated in the study, and all completed a 6-week course of antidepressant treatment. Cognitive function was assessed at baseline and post-treatment. Patients were categorized based on post-treatment HAMD-17 scores (with HAMD≤7 indicating remission), and comparisons were made between different groups in terms of allelic gene frequencies and genotypes. Logistic regression was used to explore the interaction between cognitive function and genotype on efficacy. Dual-luciferase reporter assays were performed to compare the regulatory effects of rs1109866 allele variants on the ABCB6 promoter.

Results There were no notable differences in allelic gene frequencies and genotypes between the remission and non-remission groups. Nonetheless, a significant interaction was identified between the rs1109866 genotype and language fluency-related indicators concerning efficacy (p=0.029) before correction. The dual-luciferase reporter assays demonstrated markedly higher fluorescence intensity of rs1109866-C compared to that of rs1109866-T (p<0.001).

Discussion Relying solely on genetic polymorphisms of ABC family genes as predictors of antidepressant treatment response may not be sufficient. However, the interaction between the rs1109866 and cognition plays a pivotal role. The potentially enhanced transcriptional activity of rs1109866-C might offer insight into its impact on antidepressant efficacy.

Introduction

Major depressive disorder (MDD) is a prevalent mental illness characterized by persistent low mood and affects approximately 5.3% of the world population [1]. This condition can have a profound impact on an individualʼs development and social functioning, and in severe cases, may lead to self-inflicted suicide [2]. Despite its prevalence, the efficacy of medication in treating depression is notably low, as clinical trials have shown a response rate of only 25–30% compared to placebo [3]. Since depression is a complex polygenic disorder, investigating the pharmacogenetics of depression from a genetic perspective is essential for personalized treatment [4].

Previous pharmacogenetic research has demonstrated that cytochrome P450 (CYP) genotypes play a crucial role in influencing plasma drug concentrations, thereby contributing to variations in drug efficacy among individuals [5] [6] [7]. Conversely, transporters situated at the blood-brain barrier (BBB) may also impact the concentration and effectiveness of antidepressants in the brain [8] [9] [10]. The ABC family encodes ATP-binding cassette transporters, including P-glycoprotein encoded by the ABCB1 gene, which serves as a major mechanism for BBB efflux [11] [12]. Studies have confirmed that various psychotropic drugs, such as selective serotonin reuptake inhibitors (SSRIs), are substrates of P-glycoprotein, and experiments with knockout mice lacking the P-glycoprotein gene have shown significantly increased brain concentrations of the antidepressant sertraline [13] [14] [15]. Consequently, it is hypothesized that genetic variations in the ABC family could influence the brain concentrations of antidepressants through changes in P-glycoprotein expression or function. Notably, Singh et al. have verified the association between ABCB1 single nucleotide polymorphisms (SNPs) and treatment response in depression [16] [17] [18], with additional studies highlighting the impact of ABC family gene variations on serotonin transporter occupancy in the brain using positron emission tomography (PET) [19].

The transporters encoded by the ABC family are commonly found in the mitochondria. In particular, inhibition of the ABCB6 gene has been linked to increased cell sensitivity to stress induced by peroxides and cyanides, emphasizing its pivotal role in oxidative stress responses [20]. Given that oxidative stress is considered a critical factor in the development and treatment of depression [21] [22], strategies targeting reactive oxygen species (ROS) have shown promise in nano antidepressants, effectively ameliorating depressive-like behavior in animal models [23].

Depression frequently coexists with cognitive impairment, often characterized by rigid negative biases such as persistent negative beliefs [24]. Recent whole-genome association analyses utilizing UK Biobank data have identified SNPs associated with both cognition and depression [25]. The ABCB6 gene has been implicated in cognitive dysfunction, underscoring the importance of incorporating cognitive data into research [26].

Considering these findings, it is postulated that genetic variations in ABC family-related genes may influence depression treatment by affecting transport proteins at the BBB or mitochondria. Based on existing literature and data from the dbSNP database, seven SNPs on ABC family-related genes ABCB1 (rs28401781, rs4148739, rs3747802) and ABCB6 (rs1109866, rs1109867, rs3731885, rs3755047) have been identified. These SNPs have been associated with alterations in transport protein expression, neurodevelopment, or the onset and progression of depression [27] [28]. Furthermore, the integration of cognitive data will be essential for a comprehensive understanding of the role of cognitive function in the context of depression.

Methods

Subject

A total of 549 patients under depression were enrolled in this study and completed a 6-week treatment. They were all Han Chinese, from the Mental Health Center, West China Hospital, Sichuan University. All patients met DSM-5 diagnostic criteria, with a baseline score on the 17-item Hamilton Depression Scale (HAMD-17) of at least 18. These patients were aged between 12 and 65 years, of either sex, and had not received antidepressant treatment prior to enrolment or had received treatment for less than 2 weeks. Diagnoses were made independently by two clinical physicians, excluding patients with other psychiatric disorders, severe physical illnesses, alcohol or substance abuse, pregnancy or intent to become pregnant, history of suicide attempts, and medical conditions that could potentially affect assessment or medication safety. This study was approved by the Ethics Committee of West China Hospital of Sichuan University (Chengdu, China) and registered on the Chinese Clinical Trial Registration Platform (ChiCTR2000033402), and written or electronic informed consent was obtained from all patients or their guardians.

Treatment programs and depression assessment

In this trial, 549 patients with depression were treated with antidepressants. Of these, 280 patients (51.00%) were treated with SSRIs, including fluoxetine, paroxetine, sertraline and escitalopram; 157 patients (28.60%) were treated with selective serotonin and norepinephrine reuptake inhibitors (SNRIs), including duloxetine and venlafaxine; 58 patients (10. 56%) were treated with tricyclic antidepressants (TCAs), including amitriptyline, doxepin, imipramine and clomipramine; 37 patients (6.74%) were treated with noradrenergic and specific serotonergic antidepressants (NaSSAs), specifically mirtazapine; and 17 patients (3.10%) were treated with melatonin MT1/MT2 receptor agonists and 5-hydroxytryptamine receptor 2 C (5-HT2C) receptor antagonists, specifically agomelatine. The doses for each group were as follows: SSRIs group: fluoxetine/sertraline/paroxetine 20–60 mg/day, escitalopram 100–200 mg/day; SNRIs group: 75 mg–375 mg/day; TCAs group: 75–300 mg/day; NaSSAs group: 15–45 mg/day; and agomelatine: 25–75 mg/day. Specific doses were adjusted according to individual patient conditions, and benzodiazepines (alprazolam 0.2–1.2 mg/day or clonazepam 0.5–4 mg/day) could be combined in patients with insomnia.

Patients were grouped according to their HAMD-17 score after 6 weeks of treatment, with scores≤7 indicating remission and scores>8 indicating non-remission.

Single nucleotide polymorphism selection and genotyping

The selection of SNPs in this study was based on a thorough review of the relevant literature and information obtained from dbSNP (https://www-ncbi-nlm-nih-gov.accesdistant.sorbonne-universite.fr/snp). The selected SNPs were known to be associated with transporter protein expression, neurological development or the development of depression [27] [28]. [Table 1] shows the information of SNPs. Peripheral blood DNA was extracted using Trizol technology and genotyping was performed on the MassARRAY® Analyzer 4 platform (Sequenom, San Diego, CA) using matrix-assisted laser desorption ionisation time-of-flight (MALDI-TOF) mass spectrometry. Allele and genotype frequency analyses were performed using R studio version 4.0.2. Importantly, no significant deviations from Hardy-Weinberg equilibrium were observed in any of the included samples.

Cognitive assessment

Patients underwent cognitive function tests at baseline and after 6 weeks of treatment. The Wisconsin Card Sorting Test (WCST) [29] and Tower of Hanoi (TOH) [30] were used to assess executive function. WCST_Class and WCST_Error recorded the number of categories completed and errors made in the WCST, respectively. TOH_Error and TOH_Total recorded the number of errors and total score in the TOH, respectively. The Attention and Processing Speed Test (TMT A and B) was performed to assess attention and processing speed [31], with TrailA_Time and TrailB_Time recording the time taken to complete the trails. The Verbal Fluency (VF) test evaluated attention and language function [32], with VF_RepNum and VF_ErrNum recording the number of word repetitions and errors, respectively. A total of 463 depressed patients completed cognitive testing before and after treatment.

Dual luciferase assay

In this study, firefly luciferase was used as the reporter gene, while Renilla luciferase was used as the internal control gene to construct the dual-luciferase reporter system. The target gene primers were designed using Primer3 as follows: •author, please check if the orientation of primers is correctly edited here •Forward primer: 5′-CCAGAACATTTCTCTATCGATAGGTACCAAGTAGATAGCTTGGCAGTG-3′. Reverse primer: 5′-GATGCAGATCGCAGATCTCGAGATTGCCATGGTGACTGTG-3′. Additionally, complementary sequences containing the rs1109866 mutation site were constructed: rs1109866-Forward-Mut-T>C: AGTCCCCAGAGCCATCCGCGTCG. rs1109866-Reverse-Mut-T>C: TCTGGGGACTCTGGCCTTGGTGCTG. These fragments were inserted into the pGL3 base plasmid expressing firefly luciferase. The reporter gene plasmid and phRL-TK (internal control) were co-transfected into cells for the dual luciferase assay, with the empty pGL3-Basic plasmid as the control. Luciferase Assay Reagent II (LAR II) was added to measure the firefly luciferase signal, followed by Stop&Reagent to quench the firefly luciferase reaction. The quenching intensity was>5 orders of magnitude, activating the stable luminescence reaction of Renilla luciferase. Comparison of the intensity of the firefly luciferase reaction with that of the Renilla luciferase reaction reflected the regulatory effect of different reporter gene plasmids on promoter activity. Four independent experiments were performed.

Statistical analysis

All analyses were performed using R Studio version 4.02. Statistical significance was defined at the level of two-sided α=0.05, and p-values were adjusted using the false discovery rate. Chi-squared tests were used to analyze differences in allele and genotype frequencies between the two groups. Pearson correlation analysis was performed to explore the association between SNPs and the included cognitive function indicators. Furthermore, logistic regression was used to explore the relationship between SNPs, cognitive functions, and antidepressant efficacy using the equation: Efficacy=β0+(β1*covariate)+(β2*SNP)+(β3*cognitive functions)+(β4*SNP*cognitive functions), with cure status after 6 weeks of treatment as the dependent variable and SNP and cognitive indicators as interaction terms in the model. Age, sex, years of education, and drug type were included as covariates to reduce the effect of individual baseline differences. Differences in fluorescence intensity in the dual-luciferase gene report were analyzed using t-tests.

Results

Clinical sample

In this study, 549 patients with depression were enrolled, of whom 254 achieved remission (HAMD score≤7) after 6 weeks of treatment. There were no significant differences in demographics and baseline characteristics between the two groups ([Table 2]).

The relationship between single nucleotide polymorphisms and efficacy

Contrary to our expectations, there were no significant differences in allele frequencies or genotype frequencies at these loci between the remission group and the non-remission group ([Table 3]).

Correlation analysis between single nucleotide polymorphism loci and cognitive function

Correlation analysis was conducted between the seven SNPs and the included cognitive indicators (pre- and post-treatment). The genotype of rs1109866 was significantly correlated with the number of repeated words in the VF test post-treatment (r=0.119, p=0.025), and with the total number of moves in the TOH test pre-treatment (r=− 0.122, p=0.034). Similarly, rs1109867 was also significantly correlated with these two indicators (r=0.119, p=0.025; r=− 0.123, p=0.035). The rs3731885 and rs3755047 loci were correlated with the number of repeated words in the VF test and the total number of movements and errors in the TOH test. In addition, rs3747802 was correlated with the number of card placement errors in the post-treatment WCST test (r=− 0.118, p=0.028) ([Table 4]).

Interaction between cognitive function and single nucleotide polymorphisms

Further interaction analysis between SNPs and cognitive indicators showed that the C/T and C/C genotypes of rs1109866 interacted with the VF_RepNum6 language fluency indicator at week 6 (OR=0.76 (0.58–0.99), p=0.026). This suggests that after 6 weeks of treatment, patients with the C/T or C/C genotypes of rs1109866 had poorer efficacy as the number of repeated words on the VF test increased (S1). However, the p-value was not significant after correction.

Luciferase gene reporter experiment

Due to the relationship of rs1109866 with cognition and efficacy, its function was further investigated using a luciferase reporter gene experiment. The experiment showed that the plasmid fluorescence expression of rs1109866-C (0.338±0.0305) was significantly higher than that of the empty plasmid control group (0.203±0.010), indicating a significant activating effect on the promoter (t=− 13.215, p<0.001). The fluorescence expression of rs1109866-T (0.184±0.022) was significantly lower than that of the empty plasmid control group, indicating a significant inhibitory regulatory effect on the promoter (t=2.235, p=0.042). The fluorescence expression of the rs1109866-C plasmid was significantly higher than that of the rs1109866-T, demonstrating a significant enhancer effect (t=13.058, p<0.001) ([Fig. 1]).

Discussion

This study aimed to validate the relationship between ABC gene family polymorphisms and the response to antidepressant treatment. No significant differences were observed between the remission and non-remission groups in terms of the genotypes and allele frequencies of the ABC gene family SNPs. Notably, the interaction of rs1109866 with cognitive function emerged as a significant predictor of treatment efficacy. Furthermore, through a luciferase gene reporter experiment, we successfully confirmed the enhancer activity associated with the rs1109866-C variant.

The SNPs of the ABC gene family examined in our study did not exhibit a predictive ability for improvements in depression patients following a 6-week treatment period, contrary to our initial expectations [28]. P-glycoprotein, which is encoded by the ABCB1 gene, is responsible for mediating the transportation of various substances across the BBB, with many antidepressants being substrates of this protein [18]. While previous research has delved into the association between the ABCB1 gene and treatment efficacy, inconsistencies in findings have been observed due to variations in SNP selection [33] [34] [35]. Moreover, oxidative stress has emerged as a significant factor influencing antidepressant effectiveness. Notably, nuclear factor erythroid 2-related factor 2 (Nrf2), a crucial transcription factor involved in the antioxidant signaling pathway, contributes to enhancing Nrf2-dependent cellular apoptosis and alleviating autophagy disruption in the antidepressant mechanism of fluoxetine [36] [37]. Additionally, the activation of Nrf2 expression by ketamine through the brain-derived neurotrophic factor-tropomyosin-related kinase receptor type B pathway has been shown to produce antidepressant effects [38]. These outcomes could be influenced by the relatively limited sample size of depression patients treated for a 6-week duration or the specific SNP loci chosen for analysis.

Our study identified significant associations between rs1109866, rs1109867, rs3731885, rs3747802, and rs3755047 with cognitive function test outcomes, especially in tasks involving the TOH and VF tests, before and after treatment. The TOH test, involving strategic planning and problem-solving skills, requires participants to move three disks of varying sizes following specific rules, closely related to executive function and decision-making [39] [40]. Conversely, the VF test evaluates word recall, flexibility in thinking, and self-monitoring by requiring participants to generate words within a limited time frame [41] [42]. Previous studies have extensively shown the genetic impact on cognitive function, highlighting the crucial role of oxidative stress in cognitive function [43] [44]. Experiments simulating postoperative cognitive dysfunction in rodents have demonstrated higher oxidative stress, mitochondrial dysfunction, and memory impairment compared to control groups [45] [46]. Furthermore, the BBB role in cognitive function is evident as patients with cognitive impairment often exhibit BBB dysfunction, and cognitive function improvements post-administration of specific nutrients correlate with changes in BBB permeability [47] [48]. Therefore, we suggest that ABC family genes linked to BBB substance transport and oxidative stress are associated with cognitive function.

Analysis of interactions between SNP loci and cognitive indicators revealed that individuals with C/C and C/T genotypes on rs1109866 exhibited increased repetition of words in the language fluency test at week 6, leading to decreased antidepressant efficacy. This finding is consistent with previous research indicating that the VF test, which assesses executive function and attention related to words, is linked to cognitive performance. Moreover, variations in the ABCB1 gene rs10245483 locus has been shown to influence cognitive function and treatment efficacy [18]. ABC transporter gene polymorphisms are associated with serotonin transporter occupancy in the brain, and serotonin is closely related to cognitive function. Specifically, interventions involving serotonin precursor tryptophan-rich foods have demonstrated improvements in cognitive function [19] [49]. Additionally, the genotype of the rs1109866 locus of ABCB6 was associated with the number of repeated words in the VF test, indicating that VF-related cognitive indicators may be internal phenotypes of depression, particularly in specific genotype. ATP-binding cassette subfamily B member 6 (ABCB6, significantly linked to oxidative stress—a factor associated with cognitive dysfunction and depression treatment [20] [23] [45]—may offer insight into how interactions between ABC family genes and cognition influence antidepressant effectiveness.

The mechanism of interaction between the rs1109866 locus and cognition on treatment efficacy was further explored through a luciferase gene reporting experiment, which revealed a stronger enhancer effect of the C allele. According to the National Center for Biotechnology Information, this locus represents a synonymous mutation, with recent research suggesting that synonymous mutations can alter mRNA secondary structure, stability, and protein half-life, thereby affecting gene expression [50] [51]. These changes provide additional insights into the regulation of translation efficiency and elongation rates, with specific mRNA levels potentially leading to translational pauses and increased protein stability, promoting gene expression [52] [53]. Nevertheless, further exploration is needed to fully understand how rs1109866C/T impacts gene transcription and translation.

This study also has a few limitations. In the follow-up of the population under depression, variable effective doses of antidepressants, rather than a uniform drug, were utilized in this study, in line with the personalized treatment principle, potentially impacting the outcomes. The same cognitive tests were administered both at baseline and post-treatment, potentially contributing to improved test results post-treatment due to increased familiarity with the assessments. Additionally, only dual luciferase assays were conducted to investigate the mechanisms involved. It is important to note that the sample size of this study was relatively small when compared to larger-scale genetic studies, suggesting the need for expanded sample size. Finally, the interaction between rs1109866 and cognitive function on early antidepressant efficacy in this study was not statistically significant after correction. Nevertheless, the gene reporter experiments still suggested differences between the effects of the rs1109866C allele and the T allele on the promoter. It is crucial to verify the effect of rs110986 on antidepressant efficacy based on expanded sample size and explore how rs1109866, as a synonymous mutation, affects protein expression.

Conclusion

Contrary to our expectations, the included SNPs could not predict the response of depressed patients to antidepressant drugs. This may be due to the relatively small sample size of depressed patients included in the follow-up. In the follow-up, we did not use a single drug treatment but included drugs as covariates in the analysis, which could also be a possible influencing factor. Additionally, genotypes at various SNP loci were mainly associated with executive function indicators, and the interaction between the rs1109866 C/T and C/C genotypes and poorer performance on the VF test after treatment mediated worse treatment efficacy before correction. We further explored the mechanism of rs1109866 involvement in the occurrence and treatment of depression and found that the C allele exhibited a significant enhancer effect. Although most of the results were negative after correction, this still provides evidence for a genetic marker of early antidepressant treatment response and demonstrates the important role of cognitive function in clinical practice. Gene reporter experiments suggest that we need to further validate the role of rs1109866 in antidepressant therapy in future studies.

Conflicts of Interest

All the authors declare that they have no conflicts of interest.

Acknowledgement

We would like to thank our colleagues and volunteers for their support.

^# Meijiang Jin and Lei Ji are co-first authors.

^* Tao Yu and Li Yin are co-corresponding authors of this paper.

• References

• 1 Charlson F, van Ommeren M, Flaxman A. et al. New WHO prevalence estimates of mental disorders in conflict settings: A systematic review and meta-analysis. Lancet 2019; 394: 240-248
  CrossrefPubMedSearch in Google Scholar
• 2 Conejero I, Olié E, Calati R. et al. Psychological pain, depression, and suicide: Recent evidences and future directions. Curr Psychiatry Rep 2018; 20: 33
  CrossrefPubMedSearch in Google Scholar
• 3 Walkup JT. Antidepressant efficacy for depression in children and adolescents: Industry- and NIMH-funded studies. Am J Psychiatry 2017; 174: 430-437
  CrossrefPubMedSearch in Google Scholar
• 4 DallʼAglio L, Lewis CM, Pain O. Delineating the genetic component of gene expression in major depression. Biol Psychiatry 2021; 89: 627-636
  CrossrefPubMedSearch in Google Scholar
• 5 Hiemke C, Bergemann N, Clement HW. et al. Consensus guidelines for therapeutic drug monitoring in neuropsychopharmacology: Update 2017. Pharmacopsychiatry 2018; 51: e1
  Thieme ConnectPubMedSearch in Google Scholar
• 6 Maciaszek J, Pawłowski T, Hadryś T. et al. The impact of the CYP2D6 and CYP1A2 gene polymorphisms on response to duloxetine in patients with major depression. Int J Mol Sci 2023; 24
  CrossrefPubMedSearch in Google Scholar
• 7 Thiele LS, Ishtiak-Ahmed K, Thirstrup JP. et al. Clinical impact of functional CYP2C19 and CYP2D6 gene variants on treatment with antidepressants in young people with depression: A Danish Cohort Study. Pharmaceuticals (Basel) 2022; 15: 870
  CrossrefPubMedSearch in Google Scholar
• 8 Neuwelt E, Abbott NJ, Abrey L. et al. Strategies to advance translational research into brain barriers. Lancet Neurol 2008; 7: 84-96
  CrossrefPubMedSearch in Google Scholar
• 9 Uhr M, Tontsch A, Namendorf C. et al. Polymorphisms in the drug transporter gene ABCB1 predict antidepressant treatment response in depression. Neuron 2008; 57: 203-209
  CrossrefPubMedSearch in Google Scholar
• 10 OʼBrien FE, Dinan TG, Griffin BT. et al. Interactions between antidepressants and P-glycoprotein at the blood-brain barrier: Clinical significance of in vitro and in vivo findings. Br J Pharmacol 2012; 165: 289-312
  CrossrefPubMedSearch in Google Scholar
• 11 Dean M, Rzhetsky A, Allikmets R. The human ATP-binding cassette (ABC) transporter superfamily. Genome Res 2001; 11: 1156-1166
  CrossrefPubMedSearch in Google Scholar
• 12 Beis K. Structural basis for the mechanism of ABC transporters. Biochem Soc Trans 2015; 43: 889-893
  CrossrefPubMedSearch in Google Scholar
• 13 Bundgaard C, Jensen CJN, Garmer M. Species comparison of in vivo P-glycoprotein-mediated brain efflux using mdr1a-deficient rats and mice. Drug Metab Dispos 2012; 40: 461-466
  CrossrefPubMedSearch in Google Scholar
• 14 Bundgaard C, Eneberg E, Sánchez C. P-glycoprotein differentially affects escitalopram, levomilnacipran, vilazodone and vortioxetine transport at the mouse blood-brain barrier in vivo. Neuropharmacology 2016; 103: 104-111
  CrossrefPubMedSearch in Google Scholar
• 15 Karlsson L, Carlsson B, Hiemke C. et al. Altered brain concentrations of citalopram and escitalopram in P-glycoprotein deficient mice after acute and chronic treatment. Eur Neuropsychopharmacol 2013; 23: 1636-1644
  CrossrefPubMedSearch in Google Scholar
• 16 Saiz-Rodríguez M, Ochoa D, Belmonte C. et al. Polymorphisms in CYP1A2, CYP2C9 and ABCB1 affect agomelatine pharmacokinetics. J Psychopharmacol 2019; 33: 522-531
  CrossrefPubMedSearch in Google Scholar
• 17 Singh AB, Bousman CA, Ng CH. et al. ABCB1 polymorphism predicts escitalopram dose needed for remission in major depression. Transl Psychiatry 2012; 2: e198
  CrossrefPubMedSearch in Google Scholar
• 18 Schatzberg AF, DeBattista C, Lazzeroni LC. et al. ABCB1 genetic effects on antidepressant outcomes: A report from the iSPOT-D Trial. Am J Psychiatry 2015; 172: 751-759
  CrossrefPubMedSearch in Google Scholar
• 19 Silberbauer LR, Rischka L, Vraka C. et al. ABCB1 variants and sex affect serotonin transporter occupancy in the brain. Mol Psychiatry 2022; 27: 4502-4509
  CrossrefPubMedSearch in Google Scholar
• 20 Lynch J, Fukuda Y, Krishnamurthy P. et al. Cell survival under stress is enhanced by a mitochondrial ATP-binding cassette transporter that regulates hemoproteins. Cancer Res 2009; 69: 5560-5567
  CrossrefPubMedSearch in Google Scholar
• 21 Liu L, Liu M, Xiu J. et al. Stimuli-responsive nanoparticles delivered by a nasal-brain pathway alleviate depression-like behavior through extensively scavenging ROS. Acta Biomater 2023; 171: 451-465
  CrossrefPubMedSearch in Google Scholar
• 22 Liu X, Zhang R, Fan J. et al. The role of ROS/p38 MAPK/NLRP3 inflammasome cascade in arsenic-induced depression-/anxiety-like behaviors of mice. Ecotoxicol Environ Saf 2023; 261: 115111
  CrossrefPubMedSearch in Google Scholar
• 23 Fu S, Chen H, Yang W. et al. ROS-targeted depression therapy via BSA-incubated ceria nanoclusters. Nano Lett 2022; 22: 4519-4527
  CrossrefPubMedSearch in Google Scholar
• 24 Disner SG, Beevers CG, Haigh EAP. et al. Neural mechanisms of the cognitive model of depression. Nat Rev Neurosci 2011; 12: 467-477
  CrossrefPubMedSearch in Google Scholar
• 25 Sun J, Wang W, Zhang R. et al. Multivariate genome-wide association study of depression, cognition, and memory phenotypes and validation analysis identify 12 cross-ethnic variants. Transl Psychiatry 2022; 12: 304
  CrossrefPubMedSearch in Google Scholar
• 26 Qi B, Kong L, Lai X. et al. Plasma exosome proteomics reveals the pathogenesis mechanism of post-stroke cognitive impairment. Aging (Albany NY) 2023; 15: 4334-4362
  CrossrefPubMedSearch in Google Scholar
• 27 Geers LM, Ochi T, Vyalova NM. et al. Influence of eight ABCB1 polymorphisms on antidepressant response in a prospective cohort of treatment-free Russian patients with moderate or severe depression: An explorative psychopharmacological study with naturalistic design. Hum Psychopharmacol 2022; 37: e2826
  CrossrefPubMedSearch in Google Scholar
• 28 Huang X, Yu T, Li X. et al. ABCB6, ABCB1 and ABCG1 genetic polymorphisms and antidepressant response of SSRIs in Chinese depressive patients. Pharmacogenomics 2013; 14: 1723-1730
  CrossrefPubMedSearch in Google Scholar
• 29 Ke X, Ding Y, Xu K. et al. The profile of cognitive impairments in chronic ketamine users. Psychiatry Res 2018; 266: 124-131
  CrossrefPubMedSearch in Google Scholar
• 30 Mongini F, Keller R, Deregibus A. et al. Frontal lobe dysfunction in patients with chronic migraine: A clinical-neuropsychological study. Psychiatry Res 2005; 133: 101-106
  CrossrefPubMedSearch in Google Scholar
• 31 Linari I, Juantorena GE, Ibáñez A. et al. Unveiling Trail Making Test: visual and manual trajectories indexing multiple executive processes. Sci Rep 2022; 12: 14265
  CrossrefPubMedSearch in Google Scholar
• 32 Chu C-S, Li C-T, Brunoni AR. et al. Cognitive effects and acceptability of non-invasive brain stimulation on Alzheimerʼs disease and mild cognitive impairment: A component network meta-analysis. J Neurol Neurosurg Psychiatry 2021; 92: 195-203
  CrossrefPubMedSearch in Google Scholar
• 33 Shan X-X, Qiu Y, Xie W-W. et al. ABCB1 gene is associated with clinical response to SNRIs in a local Chinese Han population. Front Pharmacol 2019; 10: 761
  CrossrefPubMedSearch in Google Scholar
• 34 Dong C, Wong ML, Licinio J. Sequence variations of ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1, CRHR1 and NTRK2: Association with major depression and antidepressant response in Mexican-Americans. Mol Psychiatry 2009; 14: 1105-1118
  CrossrefPubMedSearch in Google Scholar
• 35 Breitenstein B, Scheuer S, Brückl TM. et al. Association of ABCB1 gene variants, plasma antidepressant concentration, and treatment response: Results from a randomized clinical study. J Psychiatr Res 2016; 73: 86-95
  CrossrefPubMedSearch in Google Scholar
• 36 Lindqvist D, Dhabhar FS, James SJ. et al. Oxidative stress, inflammation and treatment response in major depression. Psychoneuroendocrinology 2017; 76: 197-205
  CrossrefPubMedSearch in Google Scholar
• 37 Wang Y-L, Wu H-R, Zhang S-S. et al. Catalpol ameliorates depressive-like behaviors in CUMS mice via oxidative stress-mediated NLRP3 inflammasome and neuroinflammation. Transl Psychiatry 2021; 11: 353
  CrossrefPubMedSearch in Google Scholar
• 38 Bouvier E, Brouillard F, Molet J. et al. Nrf2-dependent persistent oxidative stress results in stress-induced vulnerability to depression. Mol Psychiatry 2017; 22: 1701-1713
  CrossrefPubMedSearch in Google Scholar
• 39 Mitani K, Rathnayake N, Rathnayake U. et al. Brain activity associated with the planning process during the long-time learning of the Tower of Hanoi (ToH) Task: A pilot study. Sensors (Basel) 2022; 22: 8283
  CrossrefPubMedSearch in Google Scholar
• 40 Fansher M, Shah P, Hélie S. The effect of mode of presentation on Tower of Hanoi problem solving. Cognition 2022; 224: 105041
  CrossrefPubMedSearch in Google Scholar
• 41 Villalobos D, Torres-Simón L, Pacios J. et al. A systematic review of normative data for verbal fluency test in different languages. Neuropsychol Rev 2023; 33: 733-764
  CrossrefPubMedSearch in Google Scholar
• 42 Sutin AR, Stephan Y, Terracciano A. Verbal fluency and risk of dementia. Int J Geriatr Psychiatry 2019; 34: 863-867
  CrossrefPubMedSearch in Google Scholar
• 43 Wang S, Xue Y, Zhang J. et al. Interaction between aluminum exposure and ApoEε4 gene on cognitive function of in-service workers. Chemosphere 2023; 323: 138282
  CrossrefPubMedSearch in Google Scholar
• 44 Xu C, Sun J, Duan H. et al. Gene, environment and cognitive function: A Chinese twin ageing study. Age Ageing 2015; 44: 452-457
  CrossrefPubMedSearch in Google Scholar
• 45 Netto MB, de Oliveira Junior AN, Goldim M. et al. Oxidative stress and mitochondrial dysfunction contributes to postoperative cognitive dysfunction in elderly rats. Brain Behav Immun 2018; 73: 661-669
  CrossrefPubMedSearch in Google Scholar
• 46 Hoyos CM, Stephen C, Turner A. et al. Brain oxidative stress and cognitive function in older adults with diabetes and pre-diabetes who are at risk for dementia. Diabetes Res Clin Pract 2022; 184: 109178
  CrossrefPubMedSearch in Google Scholar
• 47 Cai Z, Qiao P-F, Wan C-Q. et al. Role of blood-brain barrier in Alzheimerʼs disease. J Alzheimers Dis 2018; 63: 1223-1234
  CrossrefPubMedSearch in Google Scholar
• 48 Kaddoumi A, Denney TS, Deshpande G. et al. Extra-virgin olive oil enhances the blood-brain barrier function in mild cognitive impairment: A randomized controlled trial. Nutrients 2022; 14: 5102
  CrossrefPubMedSearch in Google Scholar
• 49 Zamoscik V, Schmidt SNL, Bravo R. et al. Tryptophan-enriched diet or 5-hydroxytryptophan supplementation given in a randomized controlled trial impacts social cognition on a neural and behavioral level. Sci Rep 2021; 11: 21637
  CrossrefPubMedSearch in Google Scholar
• 50 Zheng S, Kim H, Verhaak RGW. Silent mutations make some noise. Cell 2014; 156: 1129-1131
  CrossrefPubMedSearch in Google Scholar
• 51 Saunders R, Deane CM. Synonymous codon usage influences the local protein structure observed. Nucleic Acids Res 2010; 38: 6719-6728
  CrossrefPubMedSearch in Google Scholar
• 52 Bartoszewski RA, Jablonsky M, Bartoszewska S. et al. A synonymous single nucleotide polymorphism in DeltaF508 CFTR alters the secondary structure of the mRNA and the expression of the mutant protein. J Biol Chem 2010; 285: 28741-28748
  CrossrefPubMedSearch in Google Scholar
• 53 Wang SY, Cheng YY, Liu SC. et al. A synonymous mutation in IGF-1 impacts the transcription and translation process of gene expression. Mol Ther Nucleic Acids 2021; 26: 1446-1465
  CrossrefPubMedSearch in Google Scholar

Correspondence

Publication History

Received: 02 April 2024
Received: 03 September 2024

Accepted: 30 September 2024

Article published online:
14 November 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

• References

• 1 Charlson F, van Ommeren M, Flaxman A. et al. New WHO prevalence estimates of mental disorders in conflict settings: A systematic review and meta-analysis. Lancet 2019; 394: 240-248
  CrossrefPubMedSearch in Google Scholar
• 2 Conejero I, Olié E, Calati R. et al. Psychological pain, depression, and suicide: Recent evidences and future directions. Curr Psychiatry Rep 2018; 20: 33
  CrossrefPubMedSearch in Google Scholar
• 3 Walkup JT. Antidepressant efficacy for depression in children and adolescents: Industry- and NIMH-funded studies. Am J Psychiatry 2017; 174: 430-437
  CrossrefPubMedSearch in Google Scholar
• 4 DallʼAglio L, Lewis CM, Pain O. Delineating the genetic component of gene expression in major depression. Biol Psychiatry 2021; 89: 627-636
  CrossrefPubMedSearch in Google Scholar
• 5 Hiemke C, Bergemann N, Clement HW. et al. Consensus guidelines for therapeutic drug monitoring in neuropsychopharmacology: Update 2017. Pharmacopsychiatry 2018; 51: e1
  Thieme ConnectPubMedSearch in Google Scholar
• 6 Maciaszek J, Pawłowski T, Hadryś T. et al. The impact of the CYP2D6 and CYP1A2 gene polymorphisms on response to duloxetine in patients with major depression. Int J Mol Sci 2023; 24
  CrossrefPubMedSearch in Google Scholar
• 7 Thiele LS, Ishtiak-Ahmed K, Thirstrup JP. et al. Clinical impact of functional CYP2C19 and CYP2D6 gene variants on treatment with antidepressants in young people with depression: A Danish Cohort Study. Pharmaceuticals (Basel) 2022; 15: 870
  CrossrefPubMedSearch in Google Scholar
• 8 Neuwelt E, Abbott NJ, Abrey L. et al. Strategies to advance translational research into brain barriers. Lancet Neurol 2008; 7: 84-96
  CrossrefPubMedSearch in Google Scholar
• 9 Uhr M, Tontsch A, Namendorf C. et al. Polymorphisms in the drug transporter gene ABCB1 predict antidepressant treatment response in depression. Neuron 2008; 57: 203-209
  CrossrefPubMedSearch in Google Scholar
• 10 OʼBrien FE, Dinan TG, Griffin BT. et al. Interactions between antidepressants and P-glycoprotein at the blood-brain barrier: Clinical significance of in vitro and in vivo findings. Br J Pharmacol 2012; 165: 289-312
  CrossrefPubMedSearch in Google Scholar
• 11 Dean M, Rzhetsky A, Allikmets R. The human ATP-binding cassette (ABC) transporter superfamily. Genome Res 2001; 11: 1156-1166
  CrossrefPubMedSearch in Google Scholar
• 12 Beis K. Structural basis for the mechanism of ABC transporters. Biochem Soc Trans 2015; 43: 889-893
  CrossrefPubMedSearch in Google Scholar
• 13 Bundgaard C, Jensen CJN, Garmer M. Species comparison of in vivo P-glycoprotein-mediated brain efflux using mdr1a-deficient rats and mice. Drug Metab Dispos 2012; 40: 461-466
  CrossrefPubMedSearch in Google Scholar
• 14 Bundgaard C, Eneberg E, Sánchez C. P-glycoprotein differentially affects escitalopram, levomilnacipran, vilazodone and vortioxetine transport at the mouse blood-brain barrier in vivo. Neuropharmacology 2016; 103: 104-111
  CrossrefPubMedSearch in Google Scholar
• 15 Karlsson L, Carlsson B, Hiemke C. et al. Altered brain concentrations of citalopram and escitalopram in P-glycoprotein deficient mice after acute and chronic treatment. Eur Neuropsychopharmacol 2013; 23: 1636-1644
  CrossrefPubMedSearch in Google Scholar
• 16 Saiz-Rodríguez M, Ochoa D, Belmonte C. et al. Polymorphisms in CYP1A2, CYP2C9 and ABCB1 affect agomelatine pharmacokinetics. J Psychopharmacol 2019; 33: 522-531
  CrossrefPubMedSearch in Google Scholar
• 17 Singh AB, Bousman CA, Ng CH. et al. ABCB1 polymorphism predicts escitalopram dose needed for remission in major depression. Transl Psychiatry 2012; 2: e198
  CrossrefPubMedSearch in Google Scholar
• 18 Schatzberg AF, DeBattista C, Lazzeroni LC. et al. ABCB1 genetic effects on antidepressant outcomes: A report from the iSPOT-D Trial. Am J Psychiatry 2015; 172: 751-759
  CrossrefPubMedSearch in Google Scholar
• 19 Silberbauer LR, Rischka L, Vraka C. et al. ABCB1 variants and sex affect serotonin transporter occupancy in the brain. Mol Psychiatry 2022; 27: 4502-4509
  CrossrefPubMedSearch in Google Scholar
• 20 Lynch J, Fukuda Y, Krishnamurthy P. et al. Cell survival under stress is enhanced by a mitochondrial ATP-binding cassette transporter that regulates hemoproteins. Cancer Res 2009; 69: 5560-5567
  CrossrefPubMedSearch in Google Scholar
• 21 Liu L, Liu M, Xiu J. et al. Stimuli-responsive nanoparticles delivered by a nasal-brain pathway alleviate depression-like behavior through extensively scavenging ROS. Acta Biomater 2023; 171: 451-465
  CrossrefPubMedSearch in Google Scholar
• 22 Liu X, Zhang R, Fan J. et al. The role of ROS/p38 MAPK/NLRP3 inflammasome cascade in arsenic-induced depression-/anxiety-like behaviors of mice. Ecotoxicol Environ Saf 2023; 261: 115111
  CrossrefPubMedSearch in Google Scholar
• 23 Fu S, Chen H, Yang W. et al. ROS-targeted depression therapy via BSA-incubated ceria nanoclusters. Nano Lett 2022; 22: 4519-4527
  CrossrefPubMedSearch in Google Scholar
• 24 Disner SG, Beevers CG, Haigh EAP. et al. Neural mechanisms of the cognitive model of depression. Nat Rev Neurosci 2011; 12: 467-477
  CrossrefPubMedSearch in Google Scholar
• 25 Sun J, Wang W, Zhang R. et al. Multivariate genome-wide association study of depression, cognition, and memory phenotypes and validation analysis identify 12 cross-ethnic variants. Transl Psychiatry 2022; 12: 304
  CrossrefPubMedSearch in Google Scholar
• 26 Qi B, Kong L, Lai X. et al. Plasma exosome proteomics reveals the pathogenesis mechanism of post-stroke cognitive impairment. Aging (Albany NY) 2023; 15: 4334-4362
  CrossrefPubMedSearch in Google Scholar
• 27 Geers LM, Ochi T, Vyalova NM. et al. Influence of eight ABCB1 polymorphisms on antidepressant response in a prospective cohort of treatment-free Russian patients with moderate or severe depression: An explorative psychopharmacological study with naturalistic design. Hum Psychopharmacol 2022; 37: e2826
  CrossrefPubMedSearch in Google Scholar
• 28 Huang X, Yu T, Li X. et al. ABCB6, ABCB1 and ABCG1 genetic polymorphisms and antidepressant response of SSRIs in Chinese depressive patients. Pharmacogenomics 2013; 14: 1723-1730
  CrossrefPubMedSearch in Google Scholar
• 29 Ke X, Ding Y, Xu K. et al. The profile of cognitive impairments in chronic ketamine users. Psychiatry Res 2018; 266: 124-131
  CrossrefPubMedSearch in Google Scholar
• 30 Mongini F, Keller R, Deregibus A. et al. Frontal lobe dysfunction in patients with chronic migraine: A clinical-neuropsychological study. Psychiatry Res 2005; 133: 101-106
  CrossrefPubMedSearch in Google Scholar
• 31 Linari I, Juantorena GE, Ibáñez A. et al. Unveiling Trail Making Test: visual and manual trajectories indexing multiple executive processes. Sci Rep 2022; 12: 14265
  CrossrefPubMedSearch in Google Scholar
• 32 Chu C-S, Li C-T, Brunoni AR. et al. Cognitive effects and acceptability of non-invasive brain stimulation on Alzheimerʼs disease and mild cognitive impairment: A component network meta-analysis. J Neurol Neurosurg Psychiatry 2021; 92: 195-203
  CrossrefPubMedSearch in Google Scholar
• 33 Shan X-X, Qiu Y, Xie W-W. et al. ABCB1 gene is associated with clinical response to SNRIs in a local Chinese Han population. Front Pharmacol 2019; 10: 761
  CrossrefPubMedSearch in Google Scholar
• 34 Dong C, Wong ML, Licinio J. Sequence variations of ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1, CRHR1 and NTRK2: Association with major depression and antidepressant response in Mexican-Americans. Mol Psychiatry 2009; 14: 1105-1118
  CrossrefPubMedSearch in Google Scholar
• 35 Breitenstein B, Scheuer S, Brückl TM. et al. Association of ABCB1 gene variants, plasma antidepressant concentration, and treatment response: Results from a randomized clinical study. J Psychiatr Res 2016; 73: 86-95
  CrossrefPubMedSearch in Google Scholar
• 36 Lindqvist D, Dhabhar FS, James SJ. et al. Oxidative stress, inflammation and treatment response in major depression. Psychoneuroendocrinology 2017; 76: 197-205
  CrossrefPubMedSearch in Google Scholar
• 37 Wang Y-L, Wu H-R, Zhang S-S. et al. Catalpol ameliorates depressive-like behaviors in CUMS mice via oxidative stress-mediated NLRP3 inflammasome and neuroinflammation. Transl Psychiatry 2021; 11: 353
  CrossrefPubMedSearch in Google Scholar
• 38 Bouvier E, Brouillard F, Molet J. et al. Nrf2-dependent persistent oxidative stress results in stress-induced vulnerability to depression. Mol Psychiatry 2017; 22: 1701-1713
  CrossrefPubMedSearch in Google Scholar
• 39 Mitani K, Rathnayake N, Rathnayake U. et al. Brain activity associated with the planning process during the long-time learning of the Tower of Hanoi (ToH) Task: A pilot study. Sensors (Basel) 2022; 22: 8283
  CrossrefPubMedSearch in Google Scholar
• 40 Fansher M, Shah P, Hélie S. The effect of mode of presentation on Tower of Hanoi problem solving. Cognition 2022; 224: 105041
  CrossrefPubMedSearch in Google Scholar
• 41 Villalobos D, Torres-Simón L, Pacios J. et al. A systematic review of normative data for verbal fluency test in different languages. Neuropsychol Rev 2023; 33: 733-764
  CrossrefPubMedSearch in Google Scholar
• 42 Sutin AR, Stephan Y, Terracciano A. Verbal fluency and risk of dementia. Int J Geriatr Psychiatry 2019; 34: 863-867
  CrossrefPubMedSearch in Google Scholar
• 43 Wang S, Xue Y, Zhang J. et al. Interaction between aluminum exposure and ApoEε4 gene on cognitive function of in-service workers. Chemosphere 2023; 323: 138282
  CrossrefPubMedSearch in Google Scholar
• 44 Xu C, Sun J, Duan H. et al. Gene, environment and cognitive function: A Chinese twin ageing study. Age Ageing 2015; 44: 452-457
  CrossrefPubMedSearch in Google Scholar
• 45 Netto MB, de Oliveira Junior AN, Goldim M. et al. Oxidative stress and mitochondrial dysfunction contributes to postoperative cognitive dysfunction in elderly rats. Brain Behav Immun 2018; 73: 661-669
  CrossrefPubMedSearch in Google Scholar
• 46 Hoyos CM, Stephen C, Turner A. et al. Brain oxidative stress and cognitive function in older adults with diabetes and pre-diabetes who are at risk for dementia. Diabetes Res Clin Pract 2022; 184: 109178
  CrossrefPubMedSearch in Google Scholar
• 47 Cai Z, Qiao P-F, Wan C-Q. et al. Role of blood-brain barrier in Alzheimerʼs disease. J Alzheimers Dis 2018; 63: 1223-1234
  CrossrefPubMedSearch in Google Scholar
• 48 Kaddoumi A, Denney TS, Deshpande G. et al. Extra-virgin olive oil enhances the blood-brain barrier function in mild cognitive impairment: A randomized controlled trial. Nutrients 2022; 14: 5102
  CrossrefPubMedSearch in Google Scholar
• 49 Zamoscik V, Schmidt SNL, Bravo R. et al. Tryptophan-enriched diet or 5-hydroxytryptophan supplementation given in a randomized controlled trial impacts social cognition on a neural and behavioral level. Sci Rep 2021; 11: 21637
  CrossrefPubMedSearch in Google Scholar
• 50 Zheng S, Kim H, Verhaak RGW. Silent mutations make some noise. Cell 2014; 156: 1129-1131
  CrossrefPubMedSearch in Google Scholar
• 51 Saunders R, Deane CM. Synonymous codon usage influences the local protein structure observed. Nucleic Acids Res 2010; 38: 6719-6728
  CrossrefPubMedSearch in Google Scholar
• 52 Bartoszewski RA, Jablonsky M, Bartoszewska S. et al. A synonymous single nucleotide polymorphism in DeltaF508 CFTR alters the secondary structure of the mRNA and the expression of the mutant protein. J Biol Chem 2010; 285: 28741-28748
  CrossrefPubMedSearch in Google Scholar
• 53 Wang SY, Cheng YY, Liu SC. et al. A synonymous mutation in IGF-1 impacts the transcription and translation process of gene expression. Mol Ther Nucleic Acids 2021; 26: 1446-1465
  CrossrefPubMedSearch in Google Scholar

• Supplementary Material