Skip to main content
Download PDF

The association of FKBP5 gene polymorphism with genetic susceptibility to depression and response to antidepressant treatment- a systematic review

BMC Psychiatry volume 24, Article number: 274 (2024) Cite this article

Abstract

Background

Given the inconsistencies in current studies regarding the impact of FKBP5 gene polymorphisms on depression, arising from variations in study methods, subjects, and treatment strategies, this paper provides a comprehensive review of the relationship between FKBP5 gene polymorphisms and genetic susceptibility to depression, as well as their influence on response to antidepressant treatment.

Methods

Electronic databases were searched up to April 11, 2023, for all literature in English and Chinese on depression, FKBP5 gene polymorphisms, and antidepressant treatment. Data extraction and quality assessment were performed for key study characteristics. Qualitative methods were used to synthesize the study results.

Results

A total of 21 studies were included, with the majority exhibiting average to moderate quality. Six SNPs (rs3800373, rs1360780, rs9470080, rs4713916, rs9296158, rs9394309) were broadly implicated in susceptibility to depression, while rs1360780 and rs3800373 were linked to antidepressant treatment sensitivity. Additionally, rs1360780 was associated with adverse reactions to antidepressant drug treatment. However, these associations were largely unconfirmed in replication studies.

Conclusions

Depression is recognized as a polygenic genetic disorder, with multiple genes contributing, each exerting relatively small effects. Future studies should explore not only multiple gene interactions but also epigenetic changes. Presently, research on FKBP5 in affective disorders remains notably limited, highlighting the necessity for further investigations in this domain.

Peer Review reports

Introduction

Depression is a widespread disorder affecting an increasing number of individuals globally, emerging as a significant global health concern. It currently stands as the third leading cause of morbidity in terms of disability-adjusted life years and is projected to become the primary cause by 2030 [1,2,3]. The clinical manifestation and development of this disorder are influenced by various factors, encompassing genetic, biological, psychosocial, and environmental dimensions [4,5,6,7]. Research has found that depression has significant genetic components, and genes play an important role in its onset. Multiple studies have shown that individuals with a family history of depression have a significantly increased risk of developing the condition [8]. Approximately 40% of the risk associated with developing depression is attributed to genetic variants [8]. The twin study estimated that the heritability of depression is about 37%, but when considering factors such as severity, recurrence, and age of onset, this number increases to 70% [9]. Genetic and epigenetic factors play a role in the progression and treatment of depression, as evidenced by numerous studies in this field [10,11,12]. There are significant differences in individual responses to antidepressant drugs, some of which can be attributed to genetic factors. Research has demonstrated that genetic variations can affect the absorption, distribution, metabolism, and target sensitivity of antidepressants [13]. The initial response rate to antidepressant treatment is approximately 50%, with a subsequent depression remission rate of around 37% [14]. The response of patients to antidepressants is viewed as a polygenic trait, with common genetic variants contributing to more than 40% of the variability in response [15]. Inter-patient variations in response to and efficacy of antidepressant medication can be ascribed to a complex interplay of environmental, physiological, and psychological factors, along with comorbidities and genetic variants. Moreover, contemporary psychotropic medications (encompassing antidepressants, antipsychotics, and mood stabilizers) may operate, at least in part, by inducing epigenetic changes [16].

FKBP5, located on chromosome 6 (OMIM/location: 6p21.3-21.2, full gene length 154,999 bp), is a protein-coding gene characterized by multiple single nucleotide polymorphisms (SNPs) [17]. Functionally, FKBP5 predominantly regulates the glucocorticoid receptor (GR) via two key mechanisms: hormone binding and nuclear translocation. Notably, overexpression of FKBP5 results in reduced GR nuclear transcription and hormone levels [18]. Acting as a co-chaperone alongside heat shock protein 90 (Hsp90), FKBP5 modulates the sensitivity of the GR. Its interaction with the receptor complex leads to reduced cortisol binding and less efficient nuclear translocation of the receptor. Activation of GR induces FKBP5 mRNA and protein expression through intronic hormone response elements, establishing an ultrashort feedback loop that influences GR sensitivity. In the maturation process of the GR complex, FKBP5 binds to Hsp90 through a tetratricopeptide repeat protein (TPR) domain, functioning as a docking station for various co-chaperonins. In this conformation, the receptor complex exhibits reduced resistance to cortisol. Following hormone binding, FKBP5 is exchanged with another TPR-containing immunophilin, FKBP4. The recruitment of dynamin by FKBP4 facilitates the complex’s nuclear translocation and subsequent transcriptional activity [18]. Polymorphisms in the FKBP5 gene are associated with intracellular FKBP5 protein expression, influencing GR alterations and modulating the hypothalamic-pituitary-adrenal (HPA) axis dynamics [19]. Dysfunction of the HPA axis is implicated in the pathogenesis of depression and may significantly impact the response to pharmacotherapy [20]. Research indicates that 50–70% of individuals with depression exhibit dysregulation of the HPA axis [21,22,23]. Certain individuals with Major Depressive Disorder (MDD) display persistent elevation in HPA activity, with multiple studies reporting abnormalities in cortisol suppression [24]. In chronic MDD (symptoms lasting longer than two years), HPA reactivity does not seem to be significantly affected. Research indicates a direct proportionality between the severity of depressive symptoms and cortisol levels. Additionally, the cortisol response in patients with atypical MDD closely resembles that observed in healthy controls [25]. Hence, FKBP5 has emerged as a focal point in the field of depression genetics research.

Determining the impact of polymorphisms in the FKBP5 gene on genetic susceptibility to depression and their influence on the response to antidepressant medication could enable the prediction of treatment effectiveness and medication side effects for a patient prior to initiating treatment. Yet, the present studies exhibit variations in their findings attributed to differences in methodologies, study populations, clinical phenotypes, and treatment strategies. This review aims to address three key questions: firstly, which FKBP5 gene polymorphisms differentiate depressed patients from healthy populations before treatment initiation; secondly, which FKBP5 gene polymorphisms predict treatment response to antidepressants before treatment initiation; and thirdly, which FKBP5 gene polymorphisms prospectively evaluate adverse effects following antidepressant treatment.

Materials and methods

We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for reporting this meta-analytic review. A study protocol with the registration number CRD42024502944 was submitted to PROSPERO (International Prospective Register of Systematic Reviews) before conducting the final analysis for this review.

Search strategy

For a comprehensive and systematic literature review, both computerized and manual searches were employed to identify relevant studies. Initially, an extensive search was carried out across eight databases, namely PubMed, EMBASE, CBM, CNKI, Wan Fang, VIP, Web of Science, and the Cochrane Library. The literature search involved various combinations of terms such as “affective,” “depression,” “mood,” “FKBP5,” along with “antidepressant,” “tricyclic,” “SSRI,” and “SNRI.” This search encompassed articles available up to April 11, 2023. Furthermore, manual searches were conducted on the reference lists of the chosen articles and relevant review articles on the subject.

Eligibility criteria

Inclusion criteria: (1) the study involved patients with confirmed depression; (2) it analyzed the relationship between FKBP5 gene polymorphisms and susceptibility to depression or response to antidepressant treatment; (3) the article was published in peer-reviewed English or Chinese journals with full-text availability; (4) it explored genetic variants in human biological specimens. Exclusion criteria encompassed reviews, systematic reviews, commentaries, animal studies, books, or any published material not classified as original research. Extracted information included authors, year of publication, location/ethnicity, study design, sample size, type of depression, type of antidepressant, SNPs, and analysis results.

Study selection

Initially, 280 articles were identified through the screening process. A manual examination of the references of these articles uncovered two additional studies, resulting in a total of 196 articles after eliminating duplicate studies and data. Following the exclusion of reviews, systematic evaluations, commentaries, and animal experiments, the count reduced to 90 articles. Upon reviewing titles and abstracts, 61 articles that did not meet the inclusion criteria were excluded, leaving a total of 29 articles. Following a thorough examination of the full text, an additional eight articles failing to meet the inclusion criteria were excluded. Subsequently, 21 studies were ultimately selected for a comprehensive review and quality assessment. The literature screening process is shown in Fig. 1.

Fig. 1
figure 1

Flow diagram showing the search, article selection, and extraction process

Full size image

Characteristics of the included studies

The included studies encompassed diverse ethnicities, settings, and employed varying diagnostic criteria and assessment methods. Table 1 presents the fundamental characteristics of these studies.

Table 1 Basic characteristics of the studies
Full size table

Assessment of study quality

The included studies exhibited considerable heterogeneity across various characteristics, including study subjects, methods, SNPs, diagnostic criteria, assessment scales, type and dose of antidepressants, and the definition of treatment response. Due to this high heterogeneity, the use of Meta-analysis for all included studies in this review was precluded. Consequently, this paper adopts a qualitative approach to summarize the relationship between FKBP5 gene polymorphisms and genetic susceptibility to depression and antidepressant treatment response.

Tables 2 and 3 display the quality assessment of the 21 included studies. 19 case-control and cohort studies, along with inconveniently classified studies, were assessed for quality using the NOS scale. Two RCT studies underwent quality evaluation using the modified Jadad scale. None of the studies fulfilled all quality criteria, with the majority being classified as moderate quality.

Table 2 Quality assessment of NOS
Full size table
Table 3 Quality assessment of Modified Jadad Scale
Full size table

Statistical analysis

Data Analysis The data were analyzed using Review Manager 5.4.1 software. Individual and pooled odds ratios (OR) with their associated 95% confidence intervals (CIs) were calculated. Significance of the pooled effect size was determined through a Z test. Heterogeneity across studies was assessed using the χ2-test of fit and I2 measure. Outcome Measure Response, defined as a ≥ 50% decrease in HAMD or QIDS, was utilized as the primary outcome measure. Data Extraction and Subgroup Analysis Six studies addressing treatment response provided raw data. Initially, data were pooled for analysis across all races, followed by separate analyses for Caucasians and Asians, considering the distinct distribution of genotype frequencies across racial groups. Sensitivity analyses were conducted to mitigate the potential impact of individual studies on the final results. Assessment of Publication Bias Publication bias was evaluated through the generation of funnel plots.

Results

The original studies within these 21 literature sources investigated 384 SNPs in the FKBP5 gene. 17 of these SNPs explicitly presented study outcomes (rs1043805, rs1334894, rs1360780, rs2766537, rs2817035, rs3800373, rs4713916, rs6902321, rs737054, rs755658, rs7748266, rs7757037, rs9296157, rs9296158, rs9368882, rs9394309, rs9470080), with a predominant focus on three SNPs (rs3800373, rs1360780, rs4713916). The publication dates of these articles span from 2004 to 2021, predominantly conducted in European countries, involving individuals of Caucasian or European descent, and employing case-control or cohort study designs. Among the included studies, 12 articles investigated the association between FKBP5 gene polymorphisms and genetic susceptibility to depression. Additionally, 17 articles explored the association between FKBP5 gene polymorphisms and sensitivity to antidepressant treatment, while four articles focused on the association between FKBP5 gene polymorphisms and adverse effects induced by antidepressant treatment.

FKBP5 gene polymorphism and genetic susceptibility to depression

The findings revealed associations between six SNPs (rs3800373, rs1360780, rs9470080, rs4713916, rs9296158, rs9394309) and genetic susceptibility to depression [26,27,28]. Additionally, depressed patients exhibited higher FKBP5 mRNA expression levels compared to healthy controls [29]. Nevertheless, the alleles and genotypes linked to genetic susceptibility to depression exhibited inconsistencies across studies. FKBP5 gene polymorphisms demonstrated an association with susceptibility to depression in studies conducted in Poland, Italy, Germany, the United States, and certain European countries [26, 27, 30, 31]. In contrast, FKBP5 gene polymorphisms did not exhibit an association with susceptibility to depression in some studies from Germany, Denmark, China, and studies involving black subjects [17, 30, 32,33,34,35,36,37].

FKBP5 gene polymorphism and antidepressant treatment sensitivity

In the present study, the most prominent SNPs (rs1360780, rs3800373, rs4713916) and antidepressants (citalopram, escitalopram, paroxetine, venlafaxine) were examined. Depression is characterized by concurrent higher FKBP5 mRNA expression and lower GR levels, resulting in GR resistance. Successful antidepressant treatment necessitates normal GR function [29, 38, 39]. Carriers of the rs1360780 T allele demonstrated enhanced treatment response under all treatment conditions in two German studies [38, 40]. Analysis of the rs1360780 genotype and treatment response across six studies revealed no significant association in the mixed ethnicity analysis [30,31,32, 36, 41, 42]. However, when analyzed for Caucasians alone, patients carrying the rs1360780 T allele exhibited faster response and better efficacy to antidepressants (OR = 0.78, 95%CI: 0.63–0.97, P = 0.02) with low to moderate heterogeneity (I2 = 22%) (see Figs. 2 and 3). In the German Caucasian population, carriers of the rs3800373 C allele demonstrated a better treatment response than carriers of other genotypes in two studies [31, 32]. However, the analysis of the association between the rs3800373 genotype in four studies [30,31,32, 42] and the rs4713916 genotype in two studies [30, 32] did not reveal evidence of mixed ethnicity or Caucasian association. The FKBP5 gene polymorphism did not predict treatment response to antidepressants in studies involving white European, European American, non-Hispanic white, and Chinese Han populations. Furthermore, it was not associated with the type of antidepressant used [29, 34, 36, 37, 40, 41, 43, 44]. The impact of other SNPs of the FKBP5 gene on the response to antidepressant treatment exhibited inconsistencies across studies from diverse environments and ethnicities [27, 28, 30, 35, 42, 44, 45]. None of the studies identified specific genotypes associated with successful treatment using particular antidepressants. Remission was not analyzed in this review due to the limited availability of data from only one study.

Fig. 2
figure 2

The relationship between rs1360780 and treatment sensitivity in Caucasians (white) was examined, comparing the CC genotype with the TT and CT genotypes. A Forest Plot of studies illustrates this relationship

Full size image
Fig. 3
figure 3

The relationship between rs1360780 and treatment sensitivity in Caucasians (white) was investigated by comparing the CC genotype with the TT and CT genotypes. A Funnel Plot of the comparison is presented

Full size image

FKBP5 gene polymorphisms and adverse effects caused by antidepressant treatment

Recent investigations into treatment-induced adverse effects have primarily concentrated on the emergence or exacerbation of suicidal ideation during antidepressant treatment. The more extensively studied loci include rs1360780 and rs3800373. Studies have demonstrated that carriers of the rs1360780 T allele face a heightened risk of experiencing increased suicidal ideation during treatment, particularly in studies involving individuals of European ancestry in the United States and Switzerland. This risk is independent of the type of antidepressant used [44, 45]. However, the relationship between other SNPs of FKBP5 and treatment-induced adverse reactions has not been consistently established across studies [17, 46].

Haplotypes

In studies involving Caucasian and non-Hispanic white populations, rs3800373, rs1360780, and rs4713916 were identified within a haplotype block. This haplotype was associated with an increased risk of depression [28, 30, 33]. Conversely, in black and Chinese Han populations, rs1360780 and rs3800373 are part of a single block, while rs4713916 belongs to a distinct block and is not associated with susceptibility to depression or response to antidepressant treatment [30, 34, 37, 41]. However, there are no consistent findings regarding the haplotype distribution of FKBP5 gene SNPs and their association with depression susceptibility and antidepressant treatment response in other studies [26, 43].

Linkage disequilibrium (LD)

Numerous SNPs within the FKBP5 locus exhibit high LD in various populations, encompassing Caucasian, non-Hispanic white, black, and Asian populations. Specifically, rs1360780 and rs3800373 demonstrate high LD in non-Hispanic white, black, and Chinese Han populations [30, 34, 37, 44]. In non-Hispanic white populations, rs1360780 and rs4713916 exhibit high LD, whereas this association is not observed in the black population with high LD [30]. However, there are no consistent findings regarding LD status and the relationship with depression among other SNPs across studies.

Discussion

The primary challenge in genetic association studies lies in the replication of findings [47]. Depression is a polygenic genetic disorder with a complex genetic mechanism. A specific genetic polymorphism may exert its influence through the association of one or several other genetic polymorphisms within the same gene LD. As an illustration, the rs1360780 T allele and the rs3800373 C allele exhibit similar correlations with antidepressant response in Caucasian populations due to their high LD. Furthermore, given the complexity of how depression is inherited and the involvement of numerous genetic loci, it is plausible that genes act in concert to manifest specific clinical symptoms. Polymorphisms at a particular locus may only represent a risk factor for one or several clinical symptoms of depression [48]. Consequently, studies should delve into the interaction of multiple genes.

Inconsistent treatment responses may arise from the presence of LD in the gene under investigation and a functional mutation influencing the efficacy of antidepressants. The extent of LD varies across ethnic groups, leading to inconsistent results in studies conducted across different populations. Alleles are distributed at different frequencies in distinct ethnic groups. For instance, the rs3800373 (G/T) and rs1360780 (C/T) alleles exhibit varied frequencies in Chinese Han, Caucasian, and Black populations. Additionally, rs4713916 has a lower mutation rate in Asian populations, making it less frequently studied in Asian populations. Furthermore, diverse enrollment criteria, efficacy assessment methods, and selected drugs can impact study results. Additionally, environmental factors (and associated epigenetic modifications), drug-drug interactions, hepatic and renal impairment, and compliance issues all play crucial roles in effective prescribing [49]. Pharmacogenetic studies have explored polymorphisms in several candidate genes (including SLC6A4, HTR2A, CYP2C19, CYP2D6, ABCB1, and FKBP5) for guiding antidepressant treatment versus standard treatment, yielding intriguing results [50]. Virtually all antidepressant pharmacogenetic variants exhibit potential pleiotropic effects associated with major depressive disorder, intermediate phenotypes of emotional processes, and brain areas affected by antidepressant treatment [51]. Pharmacogenetics may also contribute to inconsistent treatment responses.

Elevated suicidal ideation could result from treatment-related side effects or a lack of improvement in depressive symptoms due to the poor efficacy of antidepressants. Moreover, in the absence of placebo-controlled data, it cannot be excluded that the observed association of FKBP5 gene polymorphisms with antidepressant response is potentially a pharmacogenetic effect or is linked to patients being in different phases of depressive episodes. Several SNPs within the FKBP5 locus pose challenges in identifying polymorphisms with a singular pathogenic function due to high LD. Additionally, studies exclusively genetically analyzed subjects from their specific regional lineage, substantially diminishing the reproducibility of the findings. Furthermore, certain epigenetic mechanisms can induce alterations at the level of crucial molecules, consequently diminishing the reproducibility of the findings. As an illustration, chronic stress is linked to the hypomethylation of FKBP5. Reduced methylation of FKBP5 results in the upregulation of FK506-binding protein 51, inhibiting the binding of glucocorticoids to GR. This ultimately leads to the inhibition of negative feedback regulation of the HPA axis [52].

While these 21 studies all investigate FKBP5 gene polymorphisms in relation to genetic susceptibility and treatment response to depression, substantial heterogeneity exists in terms of study subjects, design, depression typing, assessment criteria, and antidepressant type. This heterogeneity not only poses challenges for quantitative analysis between the findings but also contributes to inconsistent results. Firstly, the study subjects exhibited diverse gender and age distributions as well as varying ethnicities. Secondly, there were disparities in clinical variables, including depression typing, severity, antidepressant strategy, duration of treatment, and response and remission criteria across studies. The majority of studies permitted patients to receive antidepressant treatment in a natural setting without intervention in treatment strategies, and in some studies, the inclusion of mood stabilizers, antipsychotics, and psychotherapy further complicates the interpretation of results. These studies share several common limitations. Firstly, a common limitation is the small sample size in most studies. Secondly, there is heterogeneity in both the study samples and treatment protocols. Thirdly, many studies lacked control groups, and even those that included controls exhibited substantial heterogeneity in the age and gender distribution of their control groups, leading to a lack of comparability. Especially in studies on suicidal events, the absence of control groups renders it impossible to ascertain whether suicidal events are linked to diagnosis and treatment, whether the emergence or exacerbation of suicidal ideation is attributable to medication, or whether the disease remains unremitted due to inadequate medication doses. Fourthly, these studies predominantly employed peripheral blood samples to analyze FKBP5 gene expression, potentially inadequately reflecting FKBP5 expression in the pituitary or brain.

Limitations of this review include the following: Firstly, genotype data on treatment response were available for only six of these 21 studies, and the absence of genotype data on included polymorphisms may introduce bias. Secondly, only dichotomous outcomes were assessed, and not symptom improvement. Thirdly, possible sources of heterogeneity for inclusion in the studies were not sufficiently examined, and potential confounders were not adjusted for.

Conclusions

Genetic and molecular studies have advanced our understanding of the biological basis of depression, and findings from neurobiological studies have contributed to enhancing the clinical outcomes of depressed patients [53]. Numerous associations between genes and various phenotypes of depression have been identified [54]. Susceptibility to depression is influenced by the function of multiple genes and their interactions with each other and various environmental factors, with potential impacts from certain epigenetic changes [52]. The demethylation of FKBP5 polymorphisms (rs1360780, rs3800373, rs9470080, and rs4713916) following childhood trauma leads to heightened HPA axis sensitization and a susceptibility to developing MDD [55]. In this review, the 21 studies broadly identified six SNPs (rs3800373, rs1360780, rs9470080, rs4713916, rs9296158, and rs9394309) that may be linked to susceptibility to depression. Additionally, rs1360780 and rs3800373 were associated with antidepressant treatment sensitivity, and rs1360780 was linked to adverse effects induced by antidepressant treatment. However, in most cases, these associations could not be replicated in subsequent studies. While genetics plays a role in the etiology of depression, findings from identical twin studies reveal substantial variability, suggesting the involvement of non-genetic factors [56]. The FKBP5 gene serves as a crucial modulator of HPA axis reactivity and holds a key position in influencing the risk of stress-related disorders. This suggests the potential for studying the FKBP5 gene in relation to depression, especially in subpopulations such as those who have experienced childhood trauma. With the appropriate study population, significant associations are likely to be discovered. Unfortunately, research on the neuroendocrine system-related candidate gene FKBP5 in mood disorders is currently highly limited, highlighting the need for further studies in this area.

Data availability

All data generated or analyzed during this study are included in this published article.

Abbreviations

SNPs:

single nucleotide polymorphisms

GR:

glucocorticoid receptor

Hsp90:

heat shock protein 90

TPR:

tetratricopeptide repeat protein

HPA:

hypothalamic-pituitary-adrenal

MDD:

Major Depressive Disorder

HAMD:

Hamilton depression scale

QIDS:

Quick Inventory of Depressive Symptomatology

LD:

Linkage disequilibrium

References

  1. Clark SLHM, Chan RF, et al. A methylation study of long-term depression risk. Mol Psychiatry. 2020;25(6):1334–43.

    Article  CAS  PubMed  Google Scholar 

  2. VG F. Pharmacological sex hormone manipulation as a risk model for depression. J Neurosci Res. 2020;98(7):1283–92.

    Article  Google Scholar 

  3. Zhdanava M, Pilon D, Ghelerter I, Chow W, Joshi K, Lefebvre P, Sheehan JJ. The prevalence and national burden of treatment-resistant depression and major depressive disorder in the United States. J Clin Psychiatry. 2021;82(2):29169.

    Article  Google Scholar 

  4. Gharraee BTK, Sheybani F, et al. Prevalence of major depressive disorder in the general population of Iran: a systematic review and meta-analysis. Med J Islam Repub Iran. 2019;33:151.

    PubMed  PubMed Central  Google Scholar 

  5. Kraus CKB, Lanzenberger R, Zarate CA Jr, Kasper S. Prognosis and improved outcomes in major depression: a review. TranslPsychiatry. 2019;9(1):127.

    Google Scholar 

  6. Bialek KCP, Strycharz J, Sliwinski T. Major depressive disorders accompanying autoimmune diseases-response to treatment.Prog. Neuropsychopharmacol Biol Psychiatry. 2019;95:109678.

    Article  Google Scholar 

  7. Lozupone MPF. Social determinants of late-life depression epigenetics. Epigenomics. 2020;12(7):559–62.

    Article  CAS  PubMed  Google Scholar 

  8. Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry. 2000;157(10):1552–62.

    Article  CAS  PubMed  Google Scholar 

  9. Menke A, Klengel T, Binder EB. Epigenetics, depression and antidepressant treatment. Curr Pharm Des. 2012;18(36):5879–89.

    Article  CAS  PubMed  Google Scholar 

  10. Czarny PBK, Zio´lkowska S, Strycharz J, Barszczewska G, Sliwinski T. The importance of epigenetics in diagnostics and treatment of major depressive disorder. J Pers Med. 2021;11(3):167.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Zhou JLM, Wang X, et al. Drug response-related DNA methylation changes in schizophrenia, bipolar disorder, and major depressive disorder. Front Neurosci. 2021;15:674273.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Klinger-K¨onig JHJ, Van der Auwera S, et al. Methylation of the FKBP5 gene in association with FKBP5 genotypes, childhood maltreatment and depression. Neuropsychopharmacology. 2019;44(5):930–8.

    Article  PubMed  Google Scholar 

  13. Uher R, Perroud N, Ng MY, Hauser J, Henigsberg N, Maier W, Mors O, Placentino A, Rietschel M, Souery D, et al. Genome-wide pharmacogenetics of antidepressant response in the GENDEP project. Am J Psychiatry. 2010;167(5):555–64.

    Article  PubMed  Google Scholar 

  14. Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, Niederehe G, Thase ME, Lavori PW, Lebowitz BD, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry. 2006;163(11):1905–17.

    Article  PubMed  Google Scholar 

  15. Tansey KE, Guipponi M, Hu X, Domenici E, Lewis G, Malafosse A, Wendland JR, Lewis CM, McGuffin P, Uher R. Contribution of common genetic variants to antidepressant response. Biol Psychiatry. 2013;73(7):679–82.

    Article  CAS  PubMed  Google Scholar 

  16. van Westrhenen R, Aitchison KJ, Ingelman-Sundberg M, Jukić MM. Pharmacogenomics of antidepressant and antipsychotic treatment: how far have we got and where are we going? Front Psychiatry. 2020;11:94.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Dam H, Buch DJO, Nielsen BA, Weikop P, Werge, Thomas J, et al. Clinical association to FKBP5 rs1360780 in patients with depression. Psychiatr Genet. 2019;29(6):220–5.

    Article  CAS  PubMed  Google Scholar 

  18. Binder EB. The role of FKBP5, a co-chaperone of the glucocorticoid receptor in the pathogenesis and therapy of affective and anxiety disorders. Psychoneuroendocrinology. 2009;34(Suppl 1):S186–195.

    Article  CAS  PubMed  Google Scholar 

  19. Alshaya DS. Genetic and epigenetic factors associated with depression: an updated overview. Saudi J Biol Sci. 2022;29(8):103311.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Farrell CDK, Oleary N, et al. DNA methylation differences at the glucocorticoid receptor gene in depression are related to functional alterations in hypothalamic-pituitary-adrenal axis activity and to early life emotional abuse. Psychiatry Res. 2018;265(7):341–8.

    Article  CAS  PubMed  Google Scholar 

  21. Watanuki TFH, Uchida S, Matsubara T, Kobayashi A, Wakabayashi Y, et al. Increased expression of splicing factor SRp20 mRNA in bipolar disorder patients. J Affect Disord. 2008;110(1–2):62–9.

    Article  CAS  PubMed  Google Scholar 

  22. Cherian KSAF, Keller J. HPA axis in psychotic major depression and schizophrenia spectrum disorders: Cortisol, clinical symptomatology, and cognition. Schizophr Res. 2019;213:72–9.

    Article  PubMed  Google Scholar 

  23. Alex FJC, Javier L, et al. FKBP5 polymorphisms and hypothalamic-pituitary-adrenal axis negative feedback in major depression and obsessive-compulsive disorder. J Psychiatr Res. 2018;104(9):227–34.

    Google Scholar 

  24. Nandam LS, Brazel M, Zhou M, Jhaveri DJ. Cortisol and major depressive disorder-translating findings from humans to animal models and back. Front Psychiatry. 2019;10:974.

    Article  PubMed  Google Scholar 

  25. Zobel AW, Nickel T, Sonntag A, Uhr M, Holsboer F, Ising M. Cortisol response in the combined dexamethasone/CRH test as predictor of relapse in patients with remitted depression. A prospective study. J Psychiatr Res. 2001;35(2):83–94.

    Article  CAS  PubMed  Google Scholar 

  26. Szczepankiewicz A, Leszczynska-Rodziewicz A, Pawlak J, Narozna B, Rajewska-Rager A, Wilkosc M, Zaremba D, Maciukiewicz M, Twarowska-Hauser J. FKBP5 polymorphism is associated with major depression but not with bipolar disorder. J Affect Disord. 2014;164:33–7.

    Article  CAS  PubMed  Google Scholar 

  27. Fabbri C, Corponi F, Albani D, Raimondi I, Forloni G, Schruers K, Kasper S, Kautzky A, Zohar J, Souery D, et al. Pleiotropic genes in psychiatry: calcium channels and the stress-related FKBP5 gene in antidepressant resistance. Prog Neuro-psychopharmacol Biol Psychiatry. 2018;81:203–10.

    Article  CAS  Google Scholar 

  28. Zobel A, Schuhmacher A, Jessen F, Hfels S, Von Widdern O, Metten M, Pfeiffer U, Hanses C, Becker T, Rietschel M, et al. DNA sequence variants of the FKBP5 gene are associated with unipolar depression. Int J Neuropsychopharmacol. 2010;13(5):649–60.

    Article  CAS  PubMed  Google Scholar 

  29. Cattaneo A, Gennarelli M, Uher R, Breen G, Farmer A, Aitchison KJ, Craig IW, Anacker C, Zunsztain PA, McGuffin P, et al. Candidate genes expression profile associated with antidepressants response in the GENDEP study: differentiating between baseline ‘predictors’ and longitudinal ‘targets’. Neuropsychopharmacology. 2013;38(3):377–85.

    Article  CAS  PubMed  Google Scholar 

  30. Lekman M, Laje G, Charney D, Rush AJ, Wilson AF, Sorant AJ, Lipsky R, Wisniewski SR, Manji H, McMahon FJ, et al. The FKBP5-gene in depression and treatment response–an association study in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) cohort. Biol Psychiatry. 2008;63(12):1103–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Kirchheiner J, Lorch R, Lebedeva E, Seeringer A, Roots I, Sasse J, Brockmöller J. Genetic variants in FKBP5 affecting response to antidepressant drug treatment. Pharmacogenomics. 2008;9(7):841–6.

    Article  CAS  PubMed  Google Scholar 

  32. Binder EB, Salyakina D, Lichtner P, Wochnik GM, Ising M, Putz B, Papiol S, Seaman S, Lucae S, Kohli MA, et al. Polymorphisms in FKBP5 are associated with increased recurrence of depressive episodes and rapid response to antidepressant treatment. Nat Genet. 2004;36(12):1319–25.

    Article  CAS  PubMed  Google Scholar 

  33. Gawlik MMEK, Mende M, et al. Is FKBP5 a genetic marker of affective psychosis? A case control study and analysis of disease related traits. BMC Psychiatry. 2006;6:52.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Yan Y, Jingping Z, Dong Y. Non-association between tacrolimus binding protein 5 gene polymorphisms and major depressive disorder in Chinese Han population. Chin J Psychiatry. 2012;45:218–22.

    Google Scholar 

  35. Papiol S, Arias B, Gasto C, Gutierrez B, Catalan R, Fananas L. Genetic variability at HPA axis in major depression and clinical response to antidepressant treatment. J Affect Disord. 2007;104(1–3):83–90.

    Article  CAS  PubMed  Google Scholar 

  36. Tsai SJ, Hong CJ, Chen TJ, Yu YW. Lack of supporting evidence for a genetic association of the FKBP5 polymorphism and response to antidepressant treatment. Am J Med Genet B Neuropsychiatr Genet. 2007;144b(8):1097–8.

    Article  CAS  PubMed  Google Scholar 

  37. Yang C, Li S, Ma Y, Chen B, Li M, Bosker FJ, Li J, Nolte IM. Lack of association of FKBP5 SNPs and haplotypes with susceptibility and treatment response phenotypes in Han Chinese with major depressive disorder A pilot case-control study (STROBE). Medicine 2021, 100(36).

  38. Ising M, Maccarrone G, Brückl T, Scheuer S, Hennings J, Holsboer F, Turck CW, Uhr M, Lucae S. FKBP5 gene expression predicts antidepressant treatment outcome in Depression. Int J Mol Sci. 2019;20(3):485–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Uher R, Huezo-Diaz P, Perroud N, Smith R, Rietschel M, Mors O, Hauser J, Maier W, Kozel D, Henigsberg N, et al. Genetic predictors of response to antidepressants in the GENDEP project. Pharmacogenom J. 2009;9(4):225–33.

    Article  CAS  Google Scholar 

  40. Stamm TJ, Rampp C, Wiethoff K, Stingl J, Moessner R, O’Malley G, Ricken R, Seemueller F, Keck M, Fisher R, et al. The FKBP5 polymorphism rs1360780 influences the effect of an algorithm-based antidepressant treatment and is associated with remission in patients with major depression. J Psychopharmacol. 2016;30(1):40–7.

    Article  CAS  PubMed  Google Scholar 

  41. Dong Y, Jingping Z, Yan Y, Renrong W, Wenbin G. Tacrolimus binding proteins 5 gene polymorphisms in major depressive disorder. Chin J Psychiatry. 2013;46:285–9.

    Google Scholar 

  42. Sarginson JE, Lazzeroni LC, Ryan HS, Schatzberg AF, Murphy GM Jr. FKBP5 polymorphisms and antidepressant response in geriatric depression. Am J Med Genet B Neuropsychiatr Genet. 2010;153b(2):554–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Ellsworth KA, Moon I, Eckloff BW, Fridley BL, Jenkins GD, Batzler A, Biernacka JM, Abo R, Brisbin A, Ji Y, et al. FKBP5 genetic variation: association with selective serotonin reuptake inhibitor treatment outcomes in major depressive disorder. Pharmacogenet Genomics. 2013;23(3):156–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Brent D, Melhem N, Ferrell R, Emslie G, Wagner KD, Ryan N, Vitiello B, Birmaher B, Mayes T, Zelazny J, et al. Association of FKBP5 polymorphisms with suicidal events in the treatment of resistant depression in adolescents (TORDIA) study. Am J Psychiatry. 2010;167(2):190–7.

    Article  PubMed  Google Scholar 

  45. Perroud N, Bondolfi G, Uher R, Gex-Fabry M, Aubry J-M, Bertschy G, Malafosse A, Kosel M. Clinical and genetic correlates of suicidal ideation during antidepressant treatment in a depressed outpatient sample. Pharmacogenomics. 2011;12(3):365–77.

    Article  PubMed  Google Scholar 

  46. Nobile B, Ramoz N, Jaussent I, Dubois J, Guillaume S, Gorwood P, Courtet P. Polymorphisms of stress pathway genes and emergence of suicidal ideation at antidepressant treatment onset. Transl Psychiatry. 2020;10(1):320.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Ioannidis JP, A NEE, Trikalinos TA, et al. Replication validity of genetic association studies. Nat Genet. 2001;29(3):306–9.

    Article  CAS  PubMed  Google Scholar 

  48. Natale A, Mineo L, Fusar-Poli L, Aguglia A, Rodolico A, Tusconi M, Amerio A, Serafini G, Amore M, Aguglia E. Mixed depression: a mini-review to guide clinical practice and future research developments. Brain Sci. 2022;12:92.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Fabbri C, Crisafulli C, Calabrò M, Spina E, Serretti A. Progress and prospects in pharmacogenetics of antidepressant drugs. Expert Opin Drug Metab Toxicol. 2016;12(10):1157–68.

    Article  CAS  PubMed  Google Scholar 

  50. Singh AB, Bousman CA. Antidepressant pharmacogenetics. Am J Psychiatry. 2017;174(5):417–8.

    Article  PubMed  Google Scholar 

  51. Lett TA, Walter H, Brandl EJ. Pharmacogenetics and imaging-pharmacogenetics of antidepressant response: towards translational strategies. CNS Drugs. 2016;30(12):1169–89.

    Article  CAS  PubMed  Google Scholar 

  52. Tozzi L, Farrell C, Booij L, Doolin K, Nemoda Z, Szyf M, Pomares FB, Chiarella J, O’Keane V, Frodl T. Epigenetic changes of FKBP5 as a link connecting genetic and environmental risk factors with structural and functional brain changes in Major Depression. Neuropsychopharmacology. 2018;43(5):1138–45.

    Article  CAS  PubMed  Google Scholar 

  53. Budzinski ML, Sokn C, Gobbini R, Ugo B, Antunica-Noguerol M, Senin S, Bajaj T, Gassen NC, Rein T, Schmidt MV, et al. Tricyclic antidepressants target FKBP51 SUMOylation to restore glucocorticoid receptor activity. Mol Psychiatry. 2022;27(5):2533–45.

    Article  CAS  PubMed  Google Scholar 

  54. Busch Y, Menke A. Blood-based biomarkers predicting response to antidepressants. J Neural Transm. 2019;126(1):47–63.

    Article  CAS  PubMed  Google Scholar 

  55. Kwon A, Kim S, Jeon H, Lee HS, Lee SH. Influence of FKBP5 variants and Childhood Trauma on Brain volume in non-clinical individuals. Front Behav Neurosci. 2021;15:663052.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Gałecki P, Samochowiec J, Mikułowska M, Szulc A. Treatment-resistant depression in Poland—Epidemiology and Treatment. J Clin Med. 2022;11:480.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Institute of Mental Health, Peking University Sixth Hospital, 100191, Beijing, China

    Ying Zhang & Weihua Yue

  2. Tianjin Anding Hospital, Tianjin Municipal Mental Health Center, 300222, Tianjin, China

    Ying Zhang

  3. National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital), 100191, Beijing, China

    Weihua Yue

  4. NHC Key Laboratory of Mental Health, Peking University, 100191, Beijing, China

    Weihua Yue

  5. PKU-IDG/McGovern Institute for Brain Research, Peking University, 100871, Beijing, China

    Weihua Yue

  6. Chinese Institute for Brain Research, 102206, Beijing, China

    Weihua Yue

  7. Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 300222, Tianjin, China

    Jie Li

Authors
  1. Ying Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Weihua Yue
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jie Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

WY, JL, and YZ conceived and designed the study. YZ screened and selected articles, extracted data, evaluated the risk of bias, conducted further analysis, and interpreted the data, contributing to the drafting of this manuscript.WY assessed the certainty of the evidence and revised the manuscript. All authors have read and approved the final manuscript.

Corresponding authors

Correspondence to Weihua Yue or Jie Li.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Yue, W. & Li, J. The association of FKBP5 gene polymorphism with genetic susceptibility to depression and response to antidepressant treatment- a systematic review. BMC Psychiatry 24, 274 (2024). https://doi.org/10.1186/s12888-024-05717-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12888-024-05717-z

Keywords

BMC Psychiatry

ISSN: 1471-244X

Contact us