PPP3CC gene: a putative modulator of antidepressant response through the B-cell receptor signaling pathway

Circadian markers as a predictor of response in the treatment of depression-A systematic review

Despite many available treatment options for depression, response rates remain suboptimal. To improve outcome, circadian markers may be suitable as markers of treatment response. This systematic review provides an overview of circadian markers that have been studied as predictors of response in treatment of depression. A search was performed (EMBASE, PUBMED, PSYCHINFO) for research studies or articles, randomized controlled trials and case report/series with no time boundaries on March 2, 2024 (PROSPERO: CRD42021252333). Other criteria were; an antidepressant treatment as intervention, treatment response measured by depression symptom severity and/or occurrence of a clinical diagnosis of depression and assessment of a circadian marker at baseline. 44 articles, encompassing 8,772 participants were included in the analysis. Although additional research is needed with less variation in types of markers and treatments to provide definitive recommendations, circadian markers, especially diurnal mood variation and chronotype, show potential to implement as response markers in the clinic.

Brain and blood transcriptome profiles delineate common genetic pathways across suicidal ideation and suicide

Human genetic studies indicate that suicidal ideation and behavior are both heritable. Most studies have examined associations between aberrant gene expression and suicide behavior, but behavior risk is linked to the severity of suicidal ideation. Through a gene network approach, this study investigates how gene co-expression patterns are associated with suicidal ideation and severity using RNA-seq data in peripheral blood from 46 live participants with elevated suicidal ideation and 46 with no ideation. Associations with the presence of suicidal ideation were found within 18 co-expressed modules (p < 0.05), as well as in 3 co-expressed modules associated with suicidal ideation severity (p < 0.05, not explained by severity of depression). Suicidal ideation presence and severity-related gene modules with enrichment of genes involved in defense against microbial infection, inflammation, and adaptive immune response were identified and investigated using RNA-seq data from postmortem brain that revealed gene expression differences with moderate effect sizes in suicide decedents vs. non-suicides in white matter, but not gray matter. Findings support a role of brain and peripheral blood inflammation in suicide risk, showing that suicidal ideation presence and severity are associated with an inflammatory signature detectable in blood and brain, indicating a biological continuity between ideation and suicidal behavior that may underlie a common heritability.

rvTWAS: identifying gene-trait association using sequences by utilizing transcriptome-directed feature selection

Toward the identification of genetic basis of complex traits, transcriptome-wide association study (TWAS) is successful in integrating transcriptome data. However, TWAS is only applicable for common variants, excluding rare variants in exome or whole-genome sequences. This is partly because of the inherent limitation of TWAS protocols that rely on predicting gene expressions. Our previous research has revealed the insight into TWAS: the 2 steps in TWAS, building and applying the expression prediction models, are essentially genetic feature selection and aggregations that do not have to involve predictions. Based on this insight disentangling TWAS, rare variants' inability of predicting expression traits is no longer an obstacle. Herein, we developed "rare variant TWAS," or rvTWAS, that first uses a Bayesian model to conduct expression-directed feature selection and then uses a kernel machine to carry out feature aggregation, forming a model leveraging expressions for association mapping including rare variants. We demonstrated the performance of rvTWAS by thorough simulations and real data analysis in 3 psychiatric disorders, namely schizophrenia, bipolar disorder, and autism spectrum disorder. We confirmed that rvTWAS outperforms existing TWAS protocols and revealed additional genes underlying psychiatric disorders. Particularly, we formed a hypothetical mechanism in which zinc finger genes impact all 3 disorders through transcriptional regulations. rvTWAS will open a door for sequence-based association mappings integrating gene expressions.

Preclinical models of treatment-resistant depression: challenges and perspectives

Treatment-resistant depression (TRD) is a subgroup of major depressive disorder in which the use of classical antidepressant treatments fails to achieve satisfactory treatment results. Although there are various definitions and grading models for TRD, common criteria for assessing TRD have still not been established. However, a common feature of any TRD model is the lack of response to at least two attempts at antidepressant pharmacotherapy. The causes of TRD are not known; nevertheless, it is estimated that even 60% of TRD patients are so-called pseudo-TRD patients, in which multiple biological factors, e.g., gender, age, and hormonal disturbances are concomitant with depression and involved in antidepressant drug resistance. Whereas the phenomenon of TRD is a complex disorder difficult to diagnose and successfully treat, the search for new treatment strategies is a significant challenge of modern pharmacology. It seems that despite the complexity of the TRD phenomenon, some useful animal models of TRD meet the construct, the face, and the predictive validity criteria. Based on the literature and our own experiences, we will discuss the utility of animals exposed to the stress paradigm (chronic mild stress, CMS), and the Wistar Kyoto rat strain representing an endogenous model of TRD. In this review, we will focus on reviewing research on existing and novel therapies for TRD, including ketamine, deep brain stimulation (DBS), and psychedelic drugs in the context of preclinical studies in representative animal models of TRD.

Functional Architecture of Brain and Blood Transcriptome Delineate Biological Continuity Between Suicidal Ideation and Suicide

Human genetic studies indicate that suicidal ideation and behavior are both heritable. Most studies have examined associations between aberrant gene expression and suicide behavior, but behavior risk is linked to severity of suicidal ideation. Through a gene network approach, this study investigates how gene co-expression patterns are associated with suicidal ideation and severity using RNA-seq data in peripheral blood from 46 live participants with elevated suicidal ideation and 46 with no ideation. Associations with presence and severity of suicidal ideation were found within 18 and 3 co-expressed modules respectively (p < 0.05), not explained by severity of depression. Suicidal ideation presence and severity-related gene modules with enrichment of genes involved in defense against microbial infection, inflammation, and adaptive immune response were identified, and tested using RNA-seq data from postmortem brain that revealed gene expression differences in suicide decedents vs. non-suicides in white matter, but not gray matter. Findings support a role of brain and peripheral blood inflammation in suicide risk, showing that suicidal ideation presence and severity is associated with an inflammatory signature detectable in blood and brain, indicating a biological continuity between ideation and suicidal behavior that may underlie a common heritability.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Effects of the antidepressant paroxetine on migratory behaviour of meiobenthic nematodes: Computational and open experimental microcosm approach

An open experimental setup was established in order to explore the toxic effects of the antidepressant paroxetine on meiobenthic nematodes. Three types of microcosms made from polyvinyl chloride tubes, each comprising two sediments compartments (upper and lower), were used in a laboratory experiment for 15 days. The experimental setup targeted the migratory behaviour of the nematofauna from the above compartments, which were exposed to paroxetine (0.4 and 40 μg.l^-1), towards below compartments. The univariate indices significantly decrease in the contaminated compartments compared to controls. Multivariate analyses revealed also significant taxonomic dissimilarities between contaminated and uncontaminated compartments. Furthermore, SIMPER functional outcomes highlighted a significant decrease in 2A feeding groups, 'co' tail shape, 1-2 mm interval length, 'cr' amphid shape, and c-p2 life history in contaminated compartments. Computational approach showed that paroxetine bound GLD-3 and SDP with high affinities, which together with molecular interactions and toxicokinetics satisfactorily explain the experimental results.

An Investigation into the Association Between Dopamine Receptor D1 Multilocus Genetic Variation, Multiparametric Magnetic Resonance Imaging, and Antidepressant Treatment

BACKGROUND

Combining genetic variants with neuroimaging phenotypes may facilitate understanding of the biological mechanisms for the etiology and pharmacology of antidepressant treatment of major depressive disorder (MDD).

PURPOSE

To explore the latent pathway of dopamine gene-hierarchical brain network-antidepressant treatment.

STUDY TYPE

Retrospective.

POPULATION

One hundred and sixty-eight MDD inpatients divided into responders (N = 98) or nonresponders (N = 70) based on the treatment outcome of antidepressant.

FIELD STRENGTH/SEQUENCE

Diffusion tensors imaging and resting-state functional magnetic resonance imaging at 3.0T using echo-planar sequence.

ASSESSMENT

Four genetic variations of the dopamine receptor D1 (DRD1) were genotyped. Strengths of rich-club, feeder, and local connections were calculated based on the rich-club organizations of structural and functional brain networks at baseline and following 4 weeks of selective serotonin reuptake inhibitor (SSRI) therapy.

STATISTICAL TESTS

Logistic and linear regressions were used to analyze the impact of DRD1 multilocus genetic profile score on the treatment response of SSRI, and their associations with strengths of rich-club, feeder, and local connections. Mediation models were developed to explore the mediation role of rich-club organizations on the relationship between DRD1 and SSRI therapy response. A P value <0.05 was considered to be statistically significant.

RESULTS

Multiple genetic variations of DRD1 were significantly related to the strengths of feeder connections both in structural and functional networks, and to the treatment response of SSRI. Furthermore, the strength of the structural feeder connection significantly modulated the effect of DRD1 variants on SSRI treatment outcome.

DATA CONCLUSION

DRD1 displayed close connections both with SSRI treatment outcome and rich-club organizations of structural and functional data. Moreover, structural feeder connection played a mediating role in the relationship between DRD1 and antidepressant therapy.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 4.

Genetics and major depressive disorder: clinical implications for disease risk, prognosis and treatment

In the post-genomic era, genetics has led to limited clinical applications in the diagnosis and treatment of major depressive disorder (MDD). Variants in genes coding for cytochrome enzymes are included in guidelines for assisting in antidepressant choice and dosing, but there are no recommendations involving genes responsible for antidepressant pharmacodynamics and no consensus applications for guiding diagnosis or prognosis. However, genetics has contributed to a better understanding of MDD pathogenesis and the mechanisms of antidepressant action, also thanks to recent methodological innovations that overcome the challenges posed by the polygenic architecture of these traits. Polygenic risk scores can be used to estimate the risk of disease at the individual level, which may have clinical relevance in cases with extremely high scores (e.g. top 1%). Genetic studies have also shed light on a wide genetic overlap between MDD and other psychiatric disorders. The relationships between genes/pathways associated with MDD and known drug targets are a promising tool for drug repurposing and identification of new pharmacological targets. Increase in power thanks to larger samples and methods integrating genetic data with gene expression, the integration of common variants and rare variants, are expected to advance our knowledge and assist in personalized psychiatry.

Citalopram-induced pathways regulation and tentative treatment-outcome-predicting biomarkers in lymphoblastoid cell lines from depression patients

Antidepressant therapy is still associated with delays in symptomatic improvement and low response rates. Incomplete understanding of molecular mechanisms underlying antidepressant effects hampered the identification of objective biomarkers for antidepressant response. In this work, we studied transcriptome-wide expression followed by pathway analysis in lymphoblastoid cell lines (LCLs) derived from 17 patients documented for response to SSRI antidepressants from the Munich Antidepressant Response Signatures (MARS) study upon short-term incubation (24 and 48 h) with citalopram. Candidate transcripts were further validated with qPCR in MARS LCLs from responders (n = 33) vs. non-responders (n = 36) and afterward in an independent cohort of treatment-resistant patients (n = 20) vs. first-line responders (n = 24) from the STAR*D study. In MARS cohort we observed significant associations of GAD1 (glutamate decarboxylase 1; p = 0.045), TBC1D9 (TBC1 Domain Family Member 9; p = 0.014-0.021) and NFIB (nuclear factor I B; p = 0.015-0.025) expression with response status, remission status and improvement in depression scale, respectively. Pathway analysis of citalopram-altered gene expression indicated response-status-dependent transcriptional reactions. Whereas in clinical responders neural function pathways were primarily up- or downregulated after incubation with citalopram, deregulated pathways in non-responders LCLs mainly involved cell adhesion and immune response. Results from the STAR*D study showed a marginal association of treatment-resistant depression with NFIB (p = 0.068) but not with GAD1 (p = 0.23) and TBC1D9 (p = 0.27). Our results propose the existence of distinct pathway regulation mechanisms in responders vs. non-responders and suggest GAD1, TBC1D9, and NFIB as tentative predictors for clinical response, full remission, and improvement in depression scale, respectively, with only a weak overlap in predictors of different therapy outcome phenotypes.

ZNF804A Gene Variants Have a Cross-diagnostic Influence on Psychosis and Treatment Improvement in Mood Disorders

Objective

Genetic variations in the gene encoding zinc finger protein 804A gene (ZNF804A) have been associated with major depression and bipolar disorder. In this work we focused on the potential influence of ZNF804A variations on the risk of developing specific sub-phenotypes as well as the individual response to available treatments.

Methods

We used two samples of different ethnic origin: a Korean sample, composed by 242 patients diagnosed with major depression and 132 patients diagnosed with bipolar disorder and 326 healthy controls; an Italian sample composed 151 major depression subjects, 189 bipolar disorder subjects and 38 outpatients diagnosed for a primary anxiety disorder.

Results

Our analyses reported an association of rs1344706 with psychotic phenotype in the cross-diagnostic pooled sample (geno p = 4.15 × 10⁻⁴, allelic p = 1.06 × 10⁻⁴). In the cross-diagnosis Italian sample but not in the Korean one, rs7597593 was involved with depressive symptoms improvement after treatment (geno p = 0.025, allelic p = 0.007).

Conclusion

The present study evidenced the role of ZNF804A alterations in symptoms improvement after treatment. Both manic and depressive symptoms seem to be modulated by ZNF804A, though the latter was observed in the bipolar pooled sample only. The role of this factor is likely related to synaptic development and maintenance; however, further analyses will be needed to better understand the molecular mechanics involved with ZNF804A.

Zinc finger proteins in psychiatric disorders and response to psychotropic medications

Zinc finger proteins are a large family of abundantly expressed small motifs that play a crucial role in a wide range of physiological and pathophysiological mechanisms. Findings published so far support an involvement of zinc fingers in psychiatric disorders. Most of the evidence has been provided for the zinc finger protein 804A (ZNF804A) gene, which has been suggested to be implicated in schizophrenia and bipolar disorder. This evidence has been corroborated by a wide range of functional studies showing that ZNF804A regulates the expression of genes involved in cell adhesion and plays a crucial role in neurite formation and maintenance of dendritic spines. On the other hand, far less is known on other zinc finger proteins and their involvement in psychiatric disorders. In this review, we discussed studies exploring the role of zinc finger proteins in schizophrenia, bipolar disorder, and major depressive disorder as well as in pharmacogenetics of psychotropic drugs.

Pharmacogenetics and Depression: A Critical Perspective

Depression leads the higher personal and socio-economical burden within psychiatric disorders. Despite the fact that over 40 antidepressants (ADs) are available, suboptimal response still poses a major challenge and is thought to be partially a result of genetic variation. Pharmacogenetics studies the effects of genetic variants on treatment outcomes with the aim of providing tailored treatments, thereby maximizing efficacy and tolerability. After two decades of pharmacogenetic research, variants in genes coding for the cytochromes involved in ADs metabolism (CYP2D6 and CYP2C19) are now considered biomarkers with sufficient scientific support for clinical application, despite the lack of conclusive cost/effectiveness evidence. The effect of variants in genes modulating ADs mechanisms of action (pharmacodynamics) is still controversial, because of the much higher complexity of ADs pharmacodynamics compared to ADs metabolism. Considerable progress has been made since the era of candidate gene studies: the genomic revolution has made possible to assess genetic variance on an unprecedented scale, throughout the whole genome, and to analyze the cumulative effect of different variants. The results have revealed key information on the biological mechanisms mediating ADs effect and identified hypothetical new pharmacological targets. They also paved the way for future availability of polygenic pharmacogenetic panels to predict treatment outcome, which are expected to explain much higher variance in ADs response compared to CYP2D6 and CYP2C19 only. As the demand and availability of AD pharmacogenetic testing is projected to increase, it is important for clinicians to keep abreast of this evolving area to facilitate informed discussions with their patients.

Results of the European Group for the Study of Resistant Depression (GSRD) - basis for further research and clinical practice

Objectives: The overview outlines two decades of research from the European Group for the Study of Resistant Depression (GSRD) that fundamentally impacted evidence-based algorithms for diagnostics and psychopharmacotherapy of treatment-resistant depression (TRD). Methods: The GSRD staging model characterising response, non-response and resistance to antidepressant (AD) treatment was applied to 2762 patients in eight European countries. Results: In case of non-response, dose escalation and switching between different AD classes did not show superiority over continuation of original AD treatment. Predictors for TRD were symptom severity, duration of the current major depressive episode (MDE), suicidality, psychotic and melancholic features, comorbid anxiety and personality disorders, add-on treatment, non-response to the first AD, adverse effects, high occupational level, recurrent disease course, previous hospitalisations, positive family history of MDD, early age of onset and novel associations of single nucleoid polymorphisms (SNPs) within the PPP3CC, ST8SIA2, CHL1, GAP43 and ITGB3 genes and gene pathways associated with neuroplasticity, intracellular signalling and chromatin silencing. A prediction model reaching accuracy of above 0.7 highlighted symptom severity, suicidality, comorbid anxiety and lifetime MDEs as the most informative predictors for TRD. Applying machine-learning algorithms, a signature of three SNPs of the BDNF, PPP3CC and HTR2A genes and lacking melancholia predicted treatment response. Conclusions: The GSRD findings offer a unique and balanced perspective on TRD representing foundation for further research elaborating on specific clinical and genetic hypotheses and treatment strategies within appropriate study-designs, especially interaction-based models and randomized controlled trials.

International Union of Basic and Clinical Pharmacology CIV: The Neurobiology of Treatment-resistant Depression: From Antidepressant Classifications to Novel Pharmacological Targets

Major depressive disorder is one of the most prevalent and life-threatening forms of mental illnesses and a major cause of morbidity worldwide. Currently available antidepressants are effective for most patients, although around 30% are considered treatment resistant (TRD), a condition that is associated with a significant impairment of cognitive function and poor quality of life. In this respect, the identification of the molecular mechanisms contributing to TRD represents an essential step for the design of novel and more efficacious drugs able to modify the clinical course of this disorder and increase remission rates in clinical practice. New insights into the neurobiology of TRD have shed light on the role of a number of different mechanisms, including the glutamatergic system, immune/inflammatory systems, neurotrophin function, and epigenetics. Advances in drug discovery processes in TRD have also influenced the classification of antidepressant drugs and novel classifications are available, such as the neuroscience-based nomenclature that can incorporate such advances in drug development for TRD. This review aims to provide an up-to-date description of key mechanisms in TRD and describe current therapeutic strategies for TRD before examining novel approaches that may ultimately address important neurobiological mechanisms not targeted by currently available antidepressants. All in all, we suggest that drug targeting different neurobiological systems should be able to restore normal function but must also promote resilience to reduce the long-term vulnerability to recurrent depressive episodes.

Neuroplasticity, Neurotransmission and Brain-Related Genes in Major Depression and Bipolar Disorder: Focus on Treatment Outcomes in an Asiatic Sample

Introduction

Mood disorders are common and disabling disorders. Despite the availability of over 100 psychotropic compounds, only one-third of patients benefit from first-line treatments. Over the past 20 years, many studies have focused on the biological factors modulating disease risk and response to treatments, but with still inconclusive data. In order to improve our current knowledge, in this study, we investigated the role of a set of genes involved in different pathways (neurotransmission, neuroplasticity, circadian rhythms, transcription factors, signal transduction and cellular metabolism) in the treatment outcome of major depressive disorder (MDD) and bipolar disorder (BD) after naturalistic pharmacological treatment.

Methods

Totals of 242 MDD, 132 BD patients and 326 healthy controls of Asian ethnicity (Koreans) were genotyped for polymorphisms within 19 genes. Response and remission after 6–8 weeks of treatment with antidepressants and mood stabilizers were evaluated. In secondary analyses, genetic associations with disease risk and some disease-associated features (age of onset, suicide attempt and psychotic BD) were also tested.

Results

None of the variants within the investigated genes was significantly associated with treatment outcomes. Some marginal association (uncorrected p < 0.01) was observed for HTR2A, BDNF, CHL1, RORA and HOMER1 SNPs. In secondary analyses, HTR2A (rs643627, p = 0.002) and CHL1 (rs4003413, p = 0.002) were found associated with risk for BD, HOMER1 (rs6872497, p = 0.002) with lifetime history of suicide attempt in patients, and RORA with early onset and presence of psychotic features in BD. Marginal results were also observed for ST8SIA2 and COMT.

Discussion

Despite limitations linked to multiple testing on small samples, methodological shortcomings and small significance of the findings, this study may support the involvement of some candidate genes in the outcomes of treatments for mood disorders, as well as in BD risk and other disease features.

Electronic supplementary material

The online version of this article (10.1007/s12325-018-0781-2) contains supplementary material, which is available to authorized users.

Pharmacogenetics in Psychiatry

Mental illness represents a major health issue both at the individual and at the socioeconomical level. This is partly due to the current suboptimal treatment options: existing psychotropic medications, including antidepressants, antipsychotics, and mood stabilizers, are effective only in a subset of patients or produce partial response and they are often associated with debilitating side effects that discourage adherence. Pharmacogenetics is the study of how genetic information impacts on drug response/side effects with the goal to provide tailored treatments, thereby maximizing efficacy and tolerability. The first pharmacogenetic studies focused on candidate genes, previously known to be relevant to the pharmacokinetics and pharmacodynamics of psychotropic drugs. Results were mainly inconclusive, but some replicated candidates were identified and included as pharmacogenetic biomarkers in drug labeling and in some commercial kits. With the advent of the genomic revolution, it became possible to study the genetic variation on an unprecedented scale, throughout the whole genome with no need of a priori hypothesis. This may lead to the personalized prescription of existing medications and potentially to the development of innovative ones, thanks to new insights into the genetics of mental illness. Promising findings were obtained, but methods for the generation and analysis of genome-wide and sequencing data are still in evolution. Future pharmacogenetic tests may consist of hundreds/thousands of polymorphisms throughout the genome or selected pathways in order to take into account the complex interactions across variants in a number of genes.

The Genetics of Treatment-Resistant Depression: A Critical Review and Future Perspectives

BACKGROUND

One-third of depressed patients develop treatment-resistant depression with the related sequelae in terms of poor functionality and worse prognosis. Solid evidence suggests that genetic variants are potentially valid predictors of antidepressant efficacy and could be used to provide personalized treatments.

METHODS

The present review summarizes genetic findings of treatment-resistant depression including results from candidate gene studies and genome-wide association studies. The limitations of these approaches are discussed, and suggestions to improve the design of future studies are provided.

RESULTS

Most studies used the candidate gene approach, and few genes showed replicated associations with treatment-resistant depression and/or evidence obtained through complementary approaches (e.g., gene expression studies). These genes included GRIK4, BDNF, SLC6A4, and KCNK2, but confirmatory evidence in large cohorts was often lacking. Genome-wide association studies did not identify any genome-wide significant association at variant level, but pathways including genes modulating actin cytoskeleton, neural plasticity, and neurogenesis may be associated with treatment-resistant depression, in line with results obtained by genome-wide association studies of antidepressant response. The improvement of aggregated tests (e.g., polygenic risk scores), possibly using variant/gene prioritization criteria, the increase in the covering of genetic variants, and the incorporation of clinical-demographic predictors of treatment-resistant depression are proposed as possible strategies to improve future pharmacogenomic studies.

CONCLUSIONS

Genetic biomarkers to identify patients with higher risk of treatment-resistant depression or to guide treatment in these patients are not available yet. Methodological improvements of future studies could lead to the identification of genetic biomarkers with clinical validity.

Genes Involved in Neurodevelopment, Neuroplasticity, and Bipolar Disorder: CACNA1C, CHRNA1, and MAPK1

BACKGROUND

Bipolar disorder (BPD) is a common and severe mental disorder. The involvement of genetic factors in the pathophysiology of BPD is well known. In the present study, we tested the association of several single-nucleotide polymorphisms (SNPs) within 3 strong candidate genes (CACNA1C, CHRNA7, and MAPK1) with BPD. These genes are involved in monoamine-related pathways, as well as in dendrite development, neuronal survival, synaptic plasticity, and memory/learning.

METHODS

One hundred and thirty-two subjects diagnosed with BPD and 326 healthy controls of Korean ancestry were genotyped for 40 SNPs within CACNA1C, CHRNA17, and MAPK1. Distribution of alleles and block of haplotypes within each gene were compared in cases and controls. Interactions between variants in different loci were also tested.

RESULTS

Significant differences in the distribution of alleles between the cases and controls were detected for rs1016388 within CACNA1C, rs1514250, rs2337980, rs6494223, rs3826029 and rs4779565 within CHRNA7, and rs8136867 within MAPK1. Haplotype analyses also confirmed an involvement of variations within these genes in BPD. Finally, exploratory epistatic analyses demonstrated potential interactive effects, especially regarding variations in CACNA1C and CHRNA7.

LIMITATIONS

Limited sample size and risk of false-positive findings.

DISCUSSION

Our data suggest a possible role of these 3 genes in BPD. Alterations of 1 or more common brain pathways (e.g., neurodevelopment and neuroplasticity, calcium signaling) may explain the obtained results.

Pleiotropic genes in psychiatry: Calcium channels and the stress-related FKBP5 gene in antidepressant resistance

A candidate gene and a genome-wide approach were combined to study the pharmacogenetics of antidepressant response and resistance. Investigated genes were selected on the basis of pleiotropic effect across psychiatric phenotypes in previous genome-wide association studies and involvement in antidepressant response. Three samples with major depressive disorder (total=671) were genotyped for 44 SNPs in 8 candidate genes (CACNA1C, CACNB2, ANK3, GRM7, TCF4, ITIH3, SYNE1, FKBP5). Phenotypes were response/remission after 4weeks of treatment and treatment-resistant depression (TRD). Genome-wide data from STAR*D were used to replicate findings for response/remission (n=1409) and TRD (n=620). Pathways including the most promising candidate genes were investigated in STAR*D for involvement in TRD. FKBP5 polymorphisms showed replicated but nominal associations with response, remission or TRD. CACNA1C rs1006737 and rs10848635 were the only polymorphisms that survived multiple-testing correction. In STAR*D the best pathway associated with TRD included CACNA1C (GO:0006942, permutated p=0.15). Machine learning models showed that independent SNPs in this pathway predicted TRD with a mean sensitivity of 0.83 and specificity of 0.56 after 10-fold cross validation repeated 100 times. FKBP5 polymorphisms appear good candidates for inclusion in antidepressant pharmacogenetic tests. Pathways including the CACNA1C gene may be involved in TRD and they may provide the base for developing multi-marker predictors of TRD.

Neuroplasticity and second messenger pathways in antidepressant efficacy: pharmacogenetic results from a prospective trial investigating treatment resistance

Genes belonging to neuroplasticity, monoamine, circadian rhythm, and transcription factor pathways were investigated as modulators of antidepressant efficacy. The present study aimed (1) to replicate previous findings in an independent sample with treatment-resistant depression (TRD), and (2) to perform a pathway analysis to investigate the possible molecular mechanisms involved. 220 patients with major depressive disorder who were non-responders to a previous antidepressant were treated with venlafaxine for 4-6 weeks and in case of non-response with escitalopram for 4-6 weeks. Symptoms were assessed using the Montgomery Asberg Depression Rating Scale. The phenotypes were response and remission to venlafaxine, non-response (TRDA) and non-remission (TRDB) to neither venlafaxine nor escitalopram. 50 tag SNPs in 14 genes belonging to the pathways of interest were tested for association with phenotypes. Molecular pathways (KEGG database) that included one or more of the genes associated with the phenotypes were investigated also in the STAR*D sample. The associations between ZNF804A rs7603001 and response, CREB1 rs2254137 and remission were replicated, as well as CHL1 rs2133402 and lower risk of TRD. Other CHL1 SNPs were potential predictors of TRD (rs1516340, rs2272522, rs1516338, rs2133402). The MAPK1 rs6928 SNP was consistently associated with all the phenotypes. The protein processing in endoplasmic reticulum pathway (hsa04141) was the best pathway that may explain the mechanisms of MAPK1 involvement in antidepressant response. Signals in genes previously associated with antidepressant efficacy were confirmed for CREB1, ZNF804A and CHL1. These genes play pivotal roles in synaptic plasticity, neural activity and connectivity.

Pharmacogenomics in Psychiatric Practice

Pharmacogenomic testing in psychiatry is becoming an established clinical procedure. Several vendors provide clinical interpretation of combinatorial pharmacogenomic testing of gene variants that have documented predictive implications regarding either pharmacologic response or adverse effects in depression and other psychiatric conditions. Such gene profiles have demonstrated improvements in outcome in depression, and reduction of cost of care of patients with inadequate clinical response. Additionally, several new gene variants are being studied to predict specific response in individuals. Many of these genes have demonstrated a role in the pathophysiology of depression or specific depressive symptoms. This article reviews the current state-of-the-art application of psychiatric pharmacogenomics.

Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis

We undertook an RNA sequencing (RNAseq)-based transcriptomic profiling study on lymphoblastoid cell lines of a European ancestry sample of 529 schizophrenia cases and 660 controls, and found 1058 genes to be differentially expressed by affection status. These differentially expressed genes were enriched for involvement in immunity, especially the 697 genes with higher expression in cases. Comparing the current RNAseq transcriptomic profiling to our previous findings in an array-based study of 268 schizophrenia cases and 446 controls showed a highly significant positive correlation over all genes. Fifteen (18%) of the 84 genes with significant (false discovery rate<0.05) expression differences between cases and controls in the previous study and analyzed here again were differentially expressed by affection status here at a genome-wide significance level (Bonferroni P<0.05 adjusted for 8141 analyzed genes in total, or P<~6.1 × 10^-6), all with the same direction of effect, thus providing corroborative evidence despite each sample of fully independent subjects being studied by different technological approaches. Meta-analysis of the RNAseq and array data sets (797 cases and 1106 controls) showed 169 additional genes (besides those found in the primary RNAseq-based analysis) to be differentially expressed, and provided further evidence of immune gene enrichment. In addition to strengthening our previous array-based gene expression differences in schizophrenia cases versus controls and providing transcriptomic support for some genes implicated by other approaches for schizophrenia, our study detected new genes differentially expressed in schizophrenia. We highlight RNAseq-based differential expression of various genes involved in neurodevelopment and/or neuronal function, and discuss caveats of the approach.

Consensus paper of the WFSBP Task Force on Genetics: Genetics, epigenetics and gene expression markers of major depressive disorder and antidepressant response

Major depressive disorder (MDD) is a heritable disease with a heavy personal and socio-economic burden. Antidepressants of different classes are prescribed to treat MDD, but reliable and reproducible markers of efficacy are not available for clinical use. Further complicating treatment, the diagnosis of MDD is not guided by objective criteria, resulting in the risk of under- or overtreatment. A number of markers of MDD and antidepressant response have been investigated at the genetic, epigenetic, gene expression and protein levels. Polymorphisms in genes involved in antidepressant metabolism (cytochrome P450 isoenzymes), antidepressant transport (ABCB1), glucocorticoid signalling (FKBP5) and serotonin neurotransmission (SLC6A4 and HTR2A) were among those included in the first pharmacogenetic assays that have been tested for clinical applicability. The results of these investigations were encouraging when examining patient-outcome improvement. Furthermore, a nine-serum biomarker panel (including BDNF, cortisol and soluble TNF-α receptor type II) showed good sensitivity and specificity in differentiating between MDD and healthy controls. These first diagnostic and response-predictive tests for MDD provided a source of optimism for future clinical applications. However, such findings should be considered very carefully because their benefit/cost ratio and clinical indications were not clearly demonstrated. Future tests may include combinations of different types of biomarkers and be specific for MDD subtypes or pathological dimensions.

Variation in PPP3CC Genotype Is Associated with Long-Term Recovery after Severe Brain Injury

After experimental traumatic brain injury (TBI), calcineurin is upregulated; blocking calcineurin is associated with improved outcomes. In humans, variation in the calcineurin A-gamma gene (PPP3CC) has been associated with neuropsychiatric disorders, though any role in TBI recovery remains unknown. This study examines associations between PPP3CC genotype and mortality, as well as gross functional status assessed at admission using the Glasgow Coma Scale (GCS) and at 3, 6, and 12 months after severe TBI using the Glasgow Outcome Score (GOS). The following tagging single nucleotide polymorphisms (tSNPs) in PPP3CC were genotyped: rs2443504, rs2461491, rs2469749, and rs10108011. The rs2443504 AA genotype was univariately associated with GCS (p = 0.022), GOS at 3, 6, and 12 months (p = 0.002, p = 0.034, and p = 0.004, respectively), and mortality (p = 0.007). In multivariate analysis controlling for age, sex, and GCS, the AA genotype of rs2443504 was associated with GOS at 3 (p = 0.02), and 12 months (p = 0.01), with a trend toward significance at 6 months (p = 0.05); the AA genotype also was associated with mortality in the multivariate model (p = 0.04). Further work is warranted to better understand the role of calcineurin, as well as the genes encoding it and their relevance to outcomes after brain injury.

CNV analysis in Chinese children of mental retardation highlights a sex differentiation in parental contribution to de novo and inherited mutational burdens

Rare copy number variations (CNVs) are a known genetic etiology in neurodevelopmental disorders (NDD). Comprehensive CNV analysis was performed in 287 Chinese children with mental retardation and/or development delay (MR/DD) and their unaffected parents. When compared with 5,866 ancestry-matched controls, 11~12% more MR/DD children carried rare and large CNVs. The increased CNV burden in MR/DD was predominantly due to de novo CNVs, the majority of which (62%) arose in the paternal germline. We observed a 2~3 fold increase of large CNV burden in the mothers of affected children. By implementing an evidence-based review approach, pathogenic structural variants were identified in 14.3% patients and 2.4% parents, respectively. Pathogenic CNVs in parents were all carried by mothers. The maternal transmission bias of deleterious CNVs was further replicated in a published dataset. Our study confirms the pathogenic role of rare CNVs in MR/DD, and provides additional evidence to evaluate the dosage sensitivity of some candidate genes. It also supports a population model of MR/DD that spontaneous mutations in males' germline are major contributor to the de novo mutational burden in offspring, with higher penetrance in male than female; unaffected carriers of causative mutations, mostly females, then contribute to the inherited mutational burden.

Genome-wide association study of antidepressant response: involvement of the inorganic cation transmembrane transporter activity pathway

BACKGROUND

Genome-wide association studies (GWAS) represent the current frontier in pharmacogenomics. Thousands of subjects of Caucasian ancestry have been included in previous GWAS investigating antidepressant response. GWAS focused on this phenotype are lacking in Asian populations.

METHODS

A sample of 109 major depressive disorder (MDD) patients of Korean origin in antidepressant treatment was collected. Phenotypes were response and remission according to the Hamilton Rating Scale for Depression (HRSD). Genome-wide genotyping was performed using the Illumina Human Omni2.5-8 platform. The same phenotypes were used in the STAR*D level 1 (n = 1677) for independent replication. In order to corroborate findings and increase the comparability between the two datasets, three levels of analysis (SNPs, genes and pathways) were carried out. Bonferroni correction, permutations, and replication across samples were used to reduce the risk of false positives.

RESULTS

Among the genes replicated across the two samples (permutated p < 0.05 in both of them), CTNNA3 appeared promising. The inorganic cation transmembrane transporter activity pathway (GO:0022890) was associated with antidepressant response in both samples (p = 2.9e-5 and p = 0.001 in the Korean and STAR*D samples, respectively) and this pathway included CACNA1A, CACNA1C, and CACNB2 genes.

CONCLUSIONS

The present study supported the involvement of genes coding for subunits of L-type voltage-gated calcium channel in antidepressant efficacy across different ethnicities but replication of findings is required before any definitive statement.

Genetic dysfunction of serotonin 2A receptor hampers response to antidepressant drugs: A translational approach

Pharmacological studies have yielded valuable insights into the role of the serotonin 2A (5-HT2A) receptor in major depressive disorder (MDD) and antidepressant drugs (ADs) response. However, it is still unknown whether genetic variants in the HTR2A gene affect the therapeutic outcome of ADs and the mechanism underlying the regulation of such response remains poorly described. In this context, a translational human-mouse study offers a unique opportunity to address the possibility that variations in the HTR2A gene may represent a relevant marker to predict the efficacy of ADs. In a first part of this study, we investigated in depressed patients the effect of three HTR2A single nucleotide polymorphisms (SNPs), selected for their potential functional consequences on 5-HT2A receptor (rs6313, rs6314 and rs7333412), on response and remission rates after 3 months of antidepressant treatments. We also explored the consequences of the constitutive genetic inactivation of the 5-HT2A receptor (i.e. in 5-HT2A(-/-) mice) on the activity of acute and prolonged administration of SSRIs. Our clinical data indicate that GG patients for the rs7333412 SNP were less prone to respond to ADs than AA/AG patients. In the preclinical study, we demonstrated that the 5-HT2A receptor exerts an inhibitory influence on the neuronal activity of the serotonergic system after acute administration of SSRIs. However, while the chronic administration of the SSRIs escitalopram or fluoxetine elicited a progressive increased in the firing rate of 5-HT neurons in 5-HT2A(+/+) mice, it failed to do so in 5-HT2A(-/-) mutants. These electrophysiological impairments were associated with a decreased ability of the chronic administration of fluoxetine to stimulate hippocampal plasticity and to produce antidepressant-like activities. Genetic loss of the 5-HT2A receptor compromised the activity of chronic treatment with SSRIs, making this receptor a putative marker to predict ADs response.

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

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

Neuronal cell adhesion genes and antidepressant response in three independent samples

Drug-effect phenotypes in human lymphoblastoid cell lines recently allowed to identify CHL1 (cell adhesion molecule with homology to L1CAM), GAP43 (growth-associated protein 43) and ITGB3 (integrin beta 3) as new candidates for involvement in the antidepressant effect. CHL1 and ITGB3 code for adhesion molecules, while GAP43 codes for a neuron-specific cytosolic protein expressed in neuronal growth cones; all the three gene products are involved in synaptic plasticity. Sixteen polymorphisms in these genes were genotyped in two samples (n=369 and 90) with diagnosis of major depressive episode who were treated with antidepressants in a naturalistic setting. Phenotypes were response, remission and treatment-resistant depression. Logistic regression including appropriate covariates was performed. Genes associated with outcomes were investigated in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) genome-wide study (n=1861) as both individual genes and through a pathway analysis (Reactome and String databases). Gene-based analysis suggested CHL1 rs4003413, GAP43 rs283393 and rs9860828, ITGB3 rs3809865 as the top candidates due to their replication across the largest original sample and the STAR*D cohort. GAP43 molecular pathway was associated with both response and remission in the STAR*D, with ELAVL4 representing the gene with the highest percentage of single nucleotide polymorphisms (SNPs) associated with outcomes. Other promising genes emerging from the pathway analysis were ITGB1 and NRP1. The present study was the first to analyze cell adhesion genes and their molecular pathways in antidepressant response. Genes and biomarkers involved in neuronal adhesion should be considered by further studies aimed to identify predictors of antidepressant response.

The combined effect of genetic polymorphisms and clinical parameters on treatment outcome in treatment-resistant depression

For over a decade, the European Group for the Study of Resistant Depression (GSRD) has examined single nucleotide polymorphisms (SNP) and clinical parameters in regard to treatment outcome. However, an interaction based model combining these factors has not been established yet. Regarding the low effect of individual SNPs, a model investigating the interactive role of SNPs and clinical variables in treatment-resistant depression (TRD) seems auspicious. Thus 225 patients featured in previous work of the GSRD were enrolled in this investigation. According to data availability and previous positive results, 12 SNPs in HTR2A, COMT, ST8SIA2, PPP3CC and BDNF as well as 8 clinical variables featured in other GSRD studies were chosen for this investigation. Random forests algorithm were used for variable shrinkage and k-means clustering for surfacing variable characteristics determining treatment outcome. Using these machine learning and clustering algorithms, we detected a set of 3 SNPs and a clinical variable that was significantly associated with treatment response. About 62% of patients exhibiting the allelic combination of GG-GG-TT for rs6265, rs7430 and rs6313 of the BDNF, PPP3CC and HTR2A genes, respectively, and without melancholia showed a HAM-D decline under 17 compared to about 34% of the whole study sample. Our random forests prediction model for treatment outcome showed that combining clinical and genetic variables gradually increased the prediction performance recognizing correctly 25% of responders using all 4 factors. Thus, we could confirm our previous findings and furthermore show the strength of an interaction-based model combining statistical algorithms in identifying and operating treatment predictors.

Differential expression of brain immune genes and schizophrenia-related behavior in C57BL/6N and DBA/2J female mice

Mounting evidence suggests the association of immune genes with complex neuropsychiatric diseases, such as schizophrenia. However, immune gene expression in the brain and their involvement in schizophrenia-related behavior in animal models have not been well studied so far. We analyzed the social (resident-intruder) and sensorimotor gating (pre-pulse inhibition (PPI) of acoustic startle) behaviors, and expression profiles of several brain immune genes in adult C57BL/6N and DBA/2J female mice. Compared to C57BL/6N mice, DBA/2J mice exhibited less social interaction in the resident-intruder test and reduced pre-pulse inhibition. The mRNA levels of Il1b and Il6 genes were significantly higher in the cortex and hypothalamus, while the mRNA level of C1qb was lower in the cortex, hippocampus and hypothalamus of DBA/2J mice compared to C57BL/6N mice. Furthermore, Tnfsf13b was up-regulated in the cortex and hippocampus, and so did Cd47 in the hippocampus, while Cx3cl1 was down-regulated in the cortex of DBA/2J mice. Our study demonstrates the differential expression of several immune genes in C57BL/6N and DBA/2J strains and more importantly provides clues on their potential importance in regulating schizophrenia-related endophenotypes in animal models.

DISC1-TSNAX and DAOA genes in major depression and citalopram efficacy

BACKGROUND

Major depressive disorder (MDD) is a common disease with high morbidity and still unsatisfying treatment response. Both MDD pathogenesis and antidepressant effect are supposed to be strongly affected by genetic polymorphisms. Among promising candidate genes, distrupted in schizophrenia 1 (DISC1), translin-associated factor X (TSNAX) and D-amino acid oxidase activator (DAOA) were suggested since their regulator role in neurodevelopment, neuroplasticity and neurotransmission, and previous evidence of cross-involvement in major psychiatric diseases.

METHODS

The present paper investigated the role of 13 SNPs within the reported genes in MDD susceptibility through a case-control (n=320 and n=150, respectively) study and in citalopram efficacy (n=157). Measures of citalopram efficacy were response (4th week) and remission (12th week). Pharmacogenetic findings were tested in the STAR(⁎)D genome-wide dataset (n=1892) for replication.

RESULTS

Evidence of association among rs3738401 (DISC1), rs1615409 and rs766288 (TSNAX) and MDD was found (p=0.004, p=0.0019, and p=0.008, respectively). A trend of association between remission and DISC1 rs821616 and DAOA rs778294 was detected, and confirmation was found for rs778294 by repeated-measure ANOVA (p=0.0008). In the STAR(⁎)D a cluster of SNPs from 20 to 40Kbp from DISC1 findings in the original sample was associated with citalopram response, as well as rs778330 (12,325bp from rs778294).

LIMITATIONS

Relatively small size of the original sample and focus on only three candidate genes.

CONCLUSIONS

The present study supported a role of DISC1-TSNAX variants in MDD susceptibility. On the other hand, genetic regions around DAOA rs778294 and DISC1 rs6675281-rs1000731 may influence citalopram efficacy.