Genetics of emergent suicidality during antidepressive treatment--data from a naturalistic study on a large sample of inpatients with a major depressive episode

Impact of genetic variants within serotonin turnover enzymes on human cerebral monoamine oxidase A in vivo

Variants within the monoamine oxidase A (MAO-A, MAOA) and tryptophan hydroxylase 2 (TPH2) genes, the main enzymes in cerebral serotonin (5-HT) turnover, affect risk for depression. Depressed cohorts show increased cerebral MAO-A in positron emission tomography (PET) studies. TPH2 polymorphisms might also influence brain MAO-A because availability of substrates (i.e. monoamine concentrations) were shown to affect MAO-A levels. We assessed the effect of MAOA (rs1137070, rs2064070, rs6323) and TPH2 (rs1386494, rs4570625) variants associated with risk for depression and related clinical phenomena on global MAO-A distribution volume (VT) using [11C]harmine PET in 51 participants (21 individuals with seasonal affective disorder (SAD) and 30 healthy individuals (HI)). Statistical analyses comprised general linear models with global MAO-A VT as dependent variable, genotype as independent variable and age, sex, group (individuals with SAD, HI) and season as covariates. rs1386494 genotype significantly affected global MAO-A VT after correction for age, group and sex (p < 0.05, corr.), with CC homozygotes showing 26% higher MAO-A levels. The role of rs1386494 on TPH2 function or expression is poorly understood. Our results suggest rs1386494 might have an effect on either, assuming that TPH2 and MAO-A levels are linked by their common product/substrate, 5-HT. Alternatively, rs1386494 might influence MAO-A levels via another mechanism, such as co-inheritance of other genetic variants. Our results provide insight into how genetic variants within serotonin turnover translate to the cerebral serotonin system. Clinicaltrials.gov Identifier: NCT02582398. EUDAMED Number: CIV-AT-13-01-009583.

Precision Medicine in Antidepressants Treatment

Precision medicine uses innovative approaches to improve disease prevention and treatment outcomes by taking into account people's genetic backgrounds, environments, and lifestyles. Treatment of depression is particularly challenging, given that 30-50% of patients do not respond adequately to antidepressants, while those who respond may experience unpleasant adverse drug reactions (ADRs) that decrease their quality of life and compliance. This chapter aims to present the available scientific data that focus on the impact of genetic variants on the efficacy and toxicity of antidepressants. We compiled data from candidate gene and genome-wide association studies that investigated associations between pharmacodynamic and pharmacokinetic genes and response to antidepressants regarding symptom improvement and ADRs. We also summarized the existing pharmacogenetic-based treatment guidelines for antidepressants, used to guide the selection of the right antidepressant and its dose based on the patient's genetic profile, aiming to achieve maximum efficacy and minimum toxicity. Finally, we reviewed the clinical implementation of pharmacogenomics studies focusing on patients on antidepressants. The available data demonstrate that precision medicine can increase the efficacy of antidepressants and reduce the occurrence of ADRs and ultimately improve patients' quality of life.

Meta-analysis of association between TPH2 single nucleotide poiymorphism and depression

Tryptophan hydroxylase 2 (TPH2) plays a crucial role in the human brain. Although the association between the TPH2 gene and depression has been suggested in previous meta-analyses, studies based on Chinese subjects are often neglected. Therefore, we included some previous studies based on Chinese subjects to explore the relationship between TPH2 polymorphisms and depression via conducting an extensive meta-analysis. We reviewed 40 research papers that included data on TPH2 gene single nucleotide polymorphisms (SNPs) from 5766 patients with depression and 5988 healthy subjects. The analysis showed an association between polymorphisms in the TPH2 gene and depression, and some results were significant in 24 studies that included Chinese Han study participants. The results of our meta-analysis showed that rs4570625, rs17110747, rs120074175, rs4290270, rs120074175, and rs4290270 may be significantly associated with depression, and that rs11178997 (A/A genotype) may be a significant risk factor for depression in the Chinese subjects. Based on the results of this study, biological experiments should be performed in the future to explore how different SNPs affect depression.

Identifying patients with major depressive disorder based on tryptophan hydroxylase-2 methylation using machine learning algorithms

OBJECTIVES

This study aimed to identify patients with major depressive disorder (MDD) by developing different machine learning (ML) models based on tryptophan hydroxylase-2 (TPH2) methylation and environmental stress.

METHODS

The data were collected from 291 patients with MDD and 100 healthy control participants: individual basic information, the Negative Life Events Scale (NLES) scores, the Childhood Trauma Questionnaire (CTQ) scores and the methylation level at 38 CpG sites in TPH2. Information gain was used to select critical input variables. Support vector machine (SVM), back propagation neural network (BPNN) and random forest (RF) algorithms were used to build recognition models, which were evaluated by the 10-fold cross-validation. SHapley Additive exPlanations (SHAP) method was used to evaluate features importance.

RESULTS

Gender, NLES scores, CTQ scores and 13 CpG sites in TPH2 gene were considered as predictors in the models. Three ML algorithms showed satisfactory performance in predicting MDD and the BPNN model indicated best prediction effects.

CONCLUSION

ML models with TPH2 methylation and environmental stress were identified to possess great performance in identifying patients with MDD, which provided precious experience for artificial intelligence to assist traditional diagnostic methods in the future.

Bipolar Disorder and Suicide: a Review

PURPOSE OF REVIEW

Bipolar disorder has the highest rate of suicide of all psychiatric conditions and is approximately 20-30 times that of the general population. The purpose of this review is to discuss findings relevant to bipolar disorder and suicide.

RECENT FINDINGS

Risk factors include male gender, living alone, divorced, no children, Caucasian, younger age (< 35 years), elderly age (> 75 years), unemployment, and a personal history of suicide attempt and family history of suicide attempt or suicide completion, as well as predominant depressive polarity. Suicide is associated with the depressed or mixed subtypes, not mania. Although there are emerging treatments for bipolar depression, such as ketamine and TMS, lithium remains the only medication associated with lowered suicide rates in bipolar disorder. Understanding clinical and demographic risk factors for suicide in bipolar disorder remains the best way to prevent suicidal behavior. Early intervention and treatment with anti-suicidal medications, such as lithium, along with close observation and follow-up is the best way to mitigate suicide in patients with bipolar disorder.

Polymorphism A118G of opioid receptor mu 1 (OPRM1) is associated with emergence of suicidal ideation at antidepressant onset in a large naturalistic cohort of depressed outpatients

Antidepressants have been the object of an international controversy for about thirty years. Some patients are inclined to develop suicidal ideation (SI) at antidepressant onset; this phenomenon is known as Treatment Emergent Suicidal Ideation (TESI), and it has conducted regulatory bodies to prompt warnings on antidepressants. Since, few studies have explored the pharmacogenomics of TESI. Given the growing body of evidence connecting the opioidergic system with suicidal behavior (particularly mu opioid receptor (MOR)), we decided to examine the relationship between two genetic polymorphisms (SNPs) in the opioidergic system and TESI in a sample of 3566 adult depressed outpatients. General practitioners and psychiatrists throughout France followed participants for 6 weeks after an initial prescription of tianeptine, an antidepressant treatment with mu agonism. Suicidal ideation was assessed with the item 10 of the Montgomery-Asberg Depression Rating Scale (item dedicated to SI) at baseline, and after 2 weeks, 4 weeks and 6 weeks. We analysed rs1799971 from the OPRM1 gene and rs105660 from the OPRK1 gene. Within the sample, 112 patients reported TESI while 384 did not. We found a significant association between AA genotype of rs1799971 and TESI even after adjustment for potential cofounders (OR = 1.93, 95% CI = [1.07; 3.49]; p-value = 0.03). On the other hand there were no significant association between rs1799971 and rs105560 with worsening of suicidal ideation or lifetime suicide attempts. Nevertheless, our results suggest a possible involvement of opioidergic system in TESI.

[Antidepressants and Suicidality: A Contradiction?]

Antidepressants and Suicidality: A Contradiction? Abstract. In 2004, the European and American authorities released a black-box warning on antidepressants indicating an association with an increased risk of suicidality (suicidal ideation and behavior) in young people. Until today, this issue remained controversial. The present review gives an overview on the relationship between antidepressant therapy and the risk of suicide and suicidality, respectively: there is no evidence of an increased risk of suicide, but of an increased rate of suicidality during the first period after starting an antidepressant treatment in young patients. Importantly, this risk was not higher than before treatment initiation. However, an intensified supervision is needed especially during the first weeks of treatment. Finally, the risk posed by untreated depression is far greater than a risk associated with antidepressant treatment.

Association between completed suicide and bipolar disorder: A systematic review of the literature

BACKGROUND

Completed suicide is a major cause of death in bipolar disorder (BD) patients.

OBJECTIVE

The aim of this paper is to provide an overall review of the existing literature of completed suicide in BD patients, including clinical and genetic data DATA SOURCES: We performed a systematic review of English and non-English articles published on MEDLINE/PubMed, PsycInfo and Cochrane database (1970-2017). Additional studies were identified by contacting clinical experts, searching bibliographies, major textbooks and website of World Health Organization. Initially we did a broad search for the association of bipolar disorder and suicide and we were narrowing the search in terms included "bipolar disorder" and "completed suicide".

STUDY SELECTION

Inclusion criteria were articles about completed suicide in patients with BD. Articles exclusively focusing on suicide attempts and suicidal behaviour have been excluded. We used PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) consensus for drafting this systematic review.

RESULTS

The initial search generated 2806 articles and a total of 61 meeting our inclusion criteria. We reviewed epidemiological data, genetic factors, risk factors and treatment of completed suicide in BD. Suicide rates in BD vary between studies but our analyses show that they are approximately 20-30-fold greater than in general population. The highest risk of successful suicide was observed in BD-II subjects. The heritability of completed suicide is about 40% and some genes related to major neurotransmitter systems have been associated with suicide. Lithium is the only treatment that has shown anti-suicide potential.

LIMITATIONS

The most important limitation of the present review is the limited existing literature on completed suicide in BD.

CONCLUSIONS

BD patients are at high risk for suicide. It is possible to identify some factors related to completed suicide, such as early onset, family history of suicide among first-degree relatives, previous attempted suicides, comorbidities and treatment. However it is necessary to promote research on this serious health problem.

TPH2 polymorphisms across the spectrum of psychiatric morbidity: A systematic review and meta-analysis

Tryptophan hydroxylase 2 (TPH2) is the rate-limiting enzyme in brain serotonin synthesis. The TPH2 gene has frequently been investigated in relation to psychiatric morbidity. The aim of the present review is to integrate results from association studies between TPH2 single nucleotide polymorphisms (SNPs) and various psychiatric disorders, which we furthermore quantified with meta-analysis. We reviewed 166 studies investigating 69 TPH2 SNPs in a broad range of psychiatric disorders, including over 30,000 patients. According to our meta-analysis, TPH2 polymorphisms show strongest associations with mood disorders, suicide (attempt) and schizophrenia. Despite small effect sizes, we conclude that TPH2 SNPs in the coding and non-coding areas (rs4570625, rs11178997, rs11178998, rs10748185, rs1843809, rs4290270, rs17110747) are each associated with one or more psychopathological conditions. Our findings highlight the possible common serotonergic mechanisms of the investigated psychiatric disorders. Yet, the functional relevance of most TPH2 polymorphisms is unclear. Characterizing how exactly the different TPH2 variants influence the serotonergic neurotransmission is a next necessary step in understanding the psychiatric disorders where serotonin is implicated.

Antidepressant-induced hypomania/mania in patients with major depression: Evidence from the BRIDGE-II-MIX study

BACKGROUND

The issue of antidepressant-induced mood switches to hypomania, mania, or mixed states within the course of mayor depressive disorder (MDD) has been a controversial topic. The present post-hoc analysis of the BRIDGE-II-MIX study focuses on the clinical features of patients with history of antidepressant-induced hypomania/mania (AIHM) in a large international sample of patients with major depressive episode (MDE).

METHODS

2811 subjects with major depression were enrolled in this multicentre cross-sectional study. Current mixed symptoms, socio-demographic and other clinical variables were collected and compared among MDD-AIHM, MDD and BD patients.

RESULTS

475 patients out of 2811 had history of AIHM (16.90%). In the MDD-AIHM group, familiarity for BD and rates of atypical features and comorbid anxiety, eating and borderline personality disorders were similar to BD and significantly more frequent compared to MDD group. MDD-AIHM patients had more frequently more than 3 episodes and reported higher rates of treatment resistance, mood lability and irritability following treatment with antidepressants. Frequencies of depression with mixed features and (hypo)manic symptoms were similar in patients of MDD-AIHM and BD groups and significantly higher in both groups than in MDD.

LIMITATIONS

there were widely varying rates of hospitalized patients across countries and the participating centres were not randomly selected.

CONCLUSIONS

Our results strongly support the DSM-5 inclusion of MDD patients with AIHM within the rubric of bipolar disorder. Differences with other MDD and BD were also observed suggesting the possibility that MDD-AIHM may represent a specific sub-population, particularly sensitive to exogenous input from antidepressants.

Core Concepts Involving Adverse Psychotropic Drug Effects: Assessment, Implications, and Management

Adverse effects from psychiatric drugs can profoundly influence treatment adherence and outcomes. Good care involves addressing adverse effects no differently than any other component of treatment. Knowledge about adverse effect assessment and management fosters a proper context that helps clinicians not sacrifice a drug's potential therapeutic benefits because of greater concerns about its tolerability. This article provides an overview of basic concepts related to the assessment and management of suspected adverse effects from psychotropic drugs. Key points are discussed regarding clinical, pharmacogenetic, pharmacokinetic, and pharmacodynamic risk factors for treatment-emergent adverse effects, alongside recommendations for their systematic assessment.

Genetic Association Studies of Suicidal Behavior: A Review of the Past 10 Years, Progress, Limitations, and Future Directions

Suicidal behaviors (SBs), which range from suicidal ideation to suicide attempts and completed suicide, represent a fatal dimension of mental ill-health. The involvement of genetic risk factors in SB is supported by family, twin, and adoption studies. The aim of this paper is to review recent genetic association studies in SBs including (i) case-control studies, (ii) family-based association studies, and (iii) genome-wide association studies (GWAS). Various studies on genetic associations have tended to suggest that a number of genes [e.g., tryptophan hydroxylase, serotonin receptors and transporters, or brain-derived neurotrophic factors (BDNFs)] are linked to SBs, but these findings are not consistently supported by the results obtained. Although the candidate-gene approach is useful, it is hampered by the present state of knowledge concerning the pathophysiology of diseases. Interpretations of GWAS results are mostly hindered by a lack of annotation describing the functions of most variation throughout the genome. Association studies have addressed a wide range of single-nucleotide polymorphisms in numerous genes. We have included 104 such studies, of which 10 are family-based association studies and 11 are GWAS. Numerous meta-analyses of case-control studies have shown significant associations of SB with variants in the serotonin transporter gene (5-HTT or SLC6A4) and the tryptophan hydroxylase 1 gene (TPH1), but others report contradictory results. The gene encoding BDNF and its receptor (NTRK2) are also promising candidates. Only two of the GWAS showed any significant associations. Several pathways are mentioned in an attempt to understand the lack of reproducibility and the disappointing results. Consequently, we review and discuss here the following aspects: (i) sample characteristics and confounding factors; (ii) statistical limits; (iii) gene-gene interactions; (iv) gene, environment, and by time interactions; and (v) technological and theoretical limits.

Onset polarity and illness course in bipolar I and II disorders: The predictive role of broadly defined mixed states

Several studies investigating bipolar disorders have shown that polarity of onset can predict differences in symptomatology, course, and prognosis. Frequently, however, research on the topic has examined only bipolar I inpatients and has not included patients with mixed onset. The aim of the present naturalistic study was to evaluate the clinical characteristics and illness course of a consecutive sample (407 outpatients, 58.7% with bipolar I (BD-I) and 41.3% with bipolar II (BD-II) disorder) according to polarity of onset: depressive (DP-o); manic/hypomanic (HM-o); or mixed--broadly defined to include agitated depression for BD-II--onset (MX-o). As compared with patients in the other two groups: a) DP-o patients (67.3%) were more frequently affected by BD-II and had lower ratings for psychotic symptoms; b) HM-o patients (17%) had a higher rate of family history for psychosis and a lower rate of suicide attempts; and c) patients in the MX-o group (15.7%) more frequently showed substance abuse and had a higher number of mixed recurrences per year. In the BD-II group, MX-o patients more frequently attempted suicide. The present study's main limitations are those of retrospective assessment of onset polarity and lack of treatment-impact evaluations over illness course. In conclusion, we confirm clinical expression differences in bipolar disorder in function of polarity of onset and underscore the importance of carefully considering broadly defined mixed state when examining polarity of onset. Further investigations are required to confirm the present study's results.

Variation in response to short-term antidepressant treatment between patients with continuous and non-continuous cycling bipolar disorders

OBJECTIVES

The study aimed to compare effectiveness and safety of short-term antidepressant treatment between patients with continuous (CCC) and non-continuous (N-CCC) cycling bipolar disorders.

METHODS

The study sample included 101 patients with bipolar disorder, 22 (21.8%) CCC and 79 (78.2%) N-CCC. Response was defined as a HDRS21 total score <7 at 12 weeks of treatment and remission as a ≥50% reduction of baseline HDRS21 total score sustained for 8 weeks.

RESULTS

Compared with N-CCC patients, CCC patients achieved a significantly lower percentage of response (respectively 50% vs. 82.3%, χ²=9.6, p=0.002) and remission (respectively 40.9% vs. 69.6%, χ²=6.11, p=0.013). Adjusted logistic regression analysis indicated that CCC patients were 4.3 times more likely to be non-responders and 3.3 times more likely to be non-remitters than N-CCC patients.

CONCERNING

AD safety, 1 (5.0%) CCC patient committed a suicide attempt and AD-emerging switch was observed in 2 patients with N-CCC (2.5%) and in 1 with CCC (4.5%).

LIMITATIONS

The observational nature of the study, retrospective assessment of course, and unblinded outcomes assessment.

CONCLUSIONS

Our findings indicate that the presence or absence of a free interval identifies two different forms of bipolar disorders with different response not only to prophylactic treatment, as previously reported, but also to short-term ADs. We submit that clinicians should take into consideration their patients׳ pattern of cycling when prescribing short-term AD treatment. Moreover, subtypes of bipolar disorders might be used as moderators of treatment response in studies assessing the efficacy or the effectiveness of antidepressant treatment.

Short-term antidepressant treatment of bipolar depression: are ISBD recommendations useful in clinical practice?

OBJECTIVES

The study aimed to test the effectiveness of the ISBD Guidelines for short-term AD treatment of BP depression.

METHODS

The study sample included 255 patients with mood disorders (154 UP, 49 BP-I, 52 BP-II). Response was defined as a HDRS21 total score<7 at 12 weeks of treatment and remission as a ≥50% reduction of baseline HDRS21 total score sustained for 8 weeks.

RESULTS

Response was achieved by 64.9% of patients with UP disorder, 75.5% of patients with BP-I disorder and 75.0% with BP-II disorder without significant differences (χ²=3.0, p=0.219). The remission rate did not differ significantly among groups (χ²=3.8, p=0.151). The dropout rate was significantly higher for patients with UP (18.2%) than for patients with BP-I (2%) and BP-II (7.7%) disorder (χ²=10.1, p=0.006). Concerning AD safety, one patient with BP-I depression committed a suicide attempt and AD-emerging switch was observed in 2.9% of patients, 2 with BP-I and 1 with BP-II disorder.

LIMITATIONS

The observational nature of the study and unblinded outcomes assessment.

CONCLUSIONS

Our findings confirm the usefulness of ISBD Guidelines for short-term AD treatment of BP depression. These patients appear to have similar response and remission rate to those observed in UP depression and do not exhibit significant switch rates or risk of suicide. Our results are limited to patients with pure bipolar depression (excluding those with broadly defined mixed states), treated with ADs-mood stabilizers combination. We suggest to partially modify ISBD Recommendations 1 and 4, to include potential responders and to improve safety.

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity

BACKGROUND

Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question.

METHOD

Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes.

RESULTS

Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors.

CONCLUSIONS

Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.

Major depressive disorder subtypes to predict long-term course

BACKGROUND

Variation in the course of major depressive disorder (MDD) is not strongly predicted by existing subtype distinctions. A new subtyping approach is considered here.

METHODS

Two data mining techniques, ensemble recursive partitioning and Lasso generalized linear models (GLMs), followed by k-means cluster analysis are used to search for subtypes based on index episode symptoms predicting subsequent MDD course in the World Mental Health (WMH) surveys. The WMH surveys are community surveys in 16 countries. Lifetime DSM-IV MDD was reported by 8,261 respondents. Retrospectively reported outcomes included measures of persistence (number of years with an episode, number of years with an episode lasting most of the year) and severity (hospitalization for MDD, disability due to MDD).

RESULTS

Recursive partitioning found significant clusters defined by the conjunctions of early onset, suicidality, and anxiety (irritability, panic, nervousness-worry-anxiety) during the index episode. GLMs found additional associations involving a number of individual symptoms. Predicted values of the four outcomes were strongly correlated. Cluster analysis of these predicted values found three clusters having consistently high, intermediate, or low predicted scores across all outcomes. The high-risk cluster (30.0% of respondents) accounted for 52.9-69.7% of high persistence and severity, and it was most strongly predicted by index episode severe dysphoria, suicidality, anxiety, and early onset. A total symptom count, in comparison, was not a significant predictor.

CONCLUSIONS

Despite being based on retrospective reports, results suggest that useful MDD subtyping distinctions can be made using data mining methods. Further studies are needed to test and expand these results with prospective data.

Antidepressant pharmacogenetics

PURPOSE OF REVIEW

This article reviews recent literature published over the period March 2012-August 2013 on antidepressant pharmacogenetics, with a focus on clinical translation and methodological challenges.

RECENT FINDINGS

Recently, various polymorphisms associated with differential antidepressant efficacy, tolerability, and safety have emerged in association studies, but mixed findings, limited effect sizes, and poor control of confounders have prevented findings translating to practice. Although promising steps have been made, empirically robust clinically translatable pharmacogenetic tests are not yet established. The complex neurobiology of major depressive disorder (MDD) together with the evolving understanding of genetic processes present research challenges for clinical translation.

SUMMARY

Early reports of clinical utility are published. The current evidence base for antidepressant pharmacogenetics is, however, not yet empirically robust enough to inform routine prescribing guidelines. Over the coming years, genetically guided versus unguided trials will help determine if antidepressant pharmacogenetics merits more widespread application.