Effect of community attitudes on suicide mortality in South Korea: a nationwide ecological study.

Background: Attitudes toward suicide are essential in suicide prevention, as suicide is socio-culturally nuanced. Although the relationship between individual attitudes and suicidal behavior has been extensively studied, the effect of community attitudes-aggregated by region-on suicide mortality remains ambiguous. This study explored the association between community attitudes and real-world suicide mortality. Methods: Data on attitudes toward suicide from the 2018 Korea National Suicide Survey (N = 1500) and individual mortality data from the MicroData Integrated System were obtained. Confirmatory factor analysis supported a factor structure with three factors: "Permissiveness," "Unjustified behavior," and "Readiness to help/Preventability." Thirty regional units in South Korea aggregated the data for ecological analysis. We used negative binomial models to examine the association at the regional level, and stratified analysis by gender and age group was conducted. Results: "Permissiveness" was associated with reduced suicide rates in a univariate model (P < 0.001). Adjusting for gender, age, and additional sociodemographics did not alter the association. Additionally, this relationship was observed in males and individuals under 60 years of age after stratification. However, "Unjustified Behavior" and "Readiness to help/Preventability" exhibited no significant association with suicide in any model or stratum. Conclusion: The observed inverse association between permissive community attitudes and suicide contradicts the findings of previous research that links permissive individual attitudes to increased suicidal behavior. Our findings suggest that attitudes may operate differently at the individual and group levels. Although the cross-sectional design and single-country focus of this study warrant further investigation, our findings indicate that attitudes are significant contextual factors in the process of suicide, which could lead to novel approaches in suicide prevention.

Identifying clinical and proteomic markers for early diagnosis and prognosis prediction of major psychiatric disorders.

BACKGROUND: To clarify if blood proteins can predict disease progression among individuals at clinical high-risk of severe mental illness (CHR-SMI), we developed a statistical model incorporating clinical and blood protein markers to distinguish the transition group (who developed severe mental illness) (CHR-SMI-T) and from non-transition group (CHR-SMI-NT) at baseline. METHODS: Ninety individuals (74 at CHR-SMI: 16 patients) were monitored for ≤4 years and were the focus of predictive models. Three predictive models (1 [100 clinical variables], 2 [158 peptides], and 3 [100 clinical variables +158 peptides]) were evaluated using area under the receiver operating characteristic (AUROC) values. Clinical and protein feature patterns were evaluated by linear mixed-effect analysis within the model at 12 and 24 months among patients who did (CHR-SMI-T) and did not transition (CHR-SMI-NT) and the entire group. RESULT: Eighteen CHR-SMI individuals with major psychiatric disorders (first episode psychosis: 2; bipolar II disorder: 13; major depressive disorder; 3) developed disorders over an average of 17.7 months. The combined model showed the highest discriminatory performance (AUROC = 0.73). Cytosolic malate dehydrogenase and transgelin-2 levels were lower in the CHR-SMI-T than the CHR-SMI-NT group. Complement component C9, inter-alpha-trypsin inhibitor heavy chain H4, von Willebrand factor, and C-reactive protein were lower in the patient than the CHR-SMI-NT group. These differences were non-significant after FDR adjustment. LIMITATIONS: Small sample, no control for medication use. CONCLUSION: This exploratory study identified clinical and proteomic markers that might predict severe mental illness early onset, which could aid in early detection and intervention. Future studies with larger samples and controlled variables are needed to validate these findings.

Modeling the Determinants of Subjective Well-Being in Schizophrenia.

BACKGROUND: The ultimate goal of successful schizophrenia treatment is not just to alleviate psychotic symptoms, but also to reduce distress and achieve subjective well-being (SWB). We aimed to identify the determinants of SWB and their interrelationships in schizophrenia. METHODS: Data were obtained from 637 patients with schizophrenia enrolled in multicenter, open-label, non-comparative clinical trials. The SWB under the Neuroleptic Treatment Scale (SWN) was utilized; a cut-off score of 80 indicated a high level of SWB at baseline and 6 months. Various machine learning (ML) algorithms were employed to identify the determinants of SWB. Furthermore, network analysis and structural equation modeling (SEM) were conducted to explore detailed relationship patterns. RESULTS: The random forest (RF) model had the highest area under the curve (AUC) of 0.794 at baseline. Obsessive-compulsive symptoms (OCS) had the most significant impact on high levels of SWB, followed by somatization, cognitive deficits, and depression. The network analysis demonstrated robust connections among the SWB, OCS, and somatization. SEM analysis revealed that OCS exerted the strongest direct effect on SWB, and also an indirect effect via the mediation of depression. Furthermore, the contribution of OCS at baseline to SWB was maintained 6 months later. CONCLUSIONS: OCS, somatization, cognition, and depression, rather than psychotic symptoms, exerted significant impacts on SWB in schizophrenia. Notably, OCS exhibited the most significant contribution not only to the current state of well-being but also to follow-up SWB, implying that OCS was predictive of SWB. The findings demonstrated that OCS management is critical for the treatment of schizophrenia.

Genome-wide association study and polygenic risk score analysis for schizophrenia in a Korean population.

Although large-scale genome-wide association studies (GWASs) have revealed the genetic architecture of schizophrenia, these studies have mainly focused on populations of European ancestry. This study aimed to identify common genetic variants associated with schizophrenia in the Korean population and evaluate the performance of polygenic risk scores (PRSs) derived from large-scale GWASs across ancestries. In the Korean psychiatric GWAS project (KPGP), seven academic institutes and their affiliated hospitals across South Korea recruited a cohort of 1670 patients with DSM-IV-defined schizophrenia and 2271 healthy controls. A total of 6690,822 SNPs were tested for association with schizophrenia. We identified one previously unreported genome-wide significant locus rs2423464 (P = 2.83 × 10-11; odds ratio = 1.65; 95 % confidence interval = 1.43-1.91, minor allele frequency = 0.126). This variant was also associated with increased lysosomal-associated membrane protein family member 5 (LAMP5) gene expression. The PRS derived from the meta-analysis results of East Asian and European GWASs explained a larger proportion of the phenotypic variance in the Korean schizophrenia sample than the PRS of an East Asian or European GWAS. (R2 = 0.073 for meta-analysis; 0.028 for East Asian GWAS; 0.037 for European GWAS). GWASs involving diverse ethnic groups will expand our understanding of the genetic architecture of schizophrenia.

Development of a Clinical Guideline for Suicide Prevention in Psychiatric Patients Based on the ADAPTE Methodology.

OBJECTIVE: Suicide is a significant public health issue, with South Korea having the highest suicide rate among Organisation for Economic Cooperation and Development countries. This study aimed to develop clinical guidelines for suicide prevention in psychiatric patients in Korea using the ADAPTE methodology. METHODS: The development process involved a comprehensive review of literature, expert consultations, and consensus-building using the Nominal Group Technique and Delphi method. The guidelines focus on evidence-based psychiatric treatments, including both pharmacological and non-pharmacological approaches, tailored to the Korean context. Key findings underscoring the need for standardized treatment protocols for patients with major psychiatric disorders, including bipolar disorder, major depressive disorder, and schizophrenia. RESULTS: The guidelines incorporate treatments like lithium, clozapine, atypical antipsychotics, electroconvulsive therapy, and cognitive behavioral therapy, which have shown effectiveness in suicide prevention. Applicability and acceptability within Korea's healthcare system were addressed, ensuring feasibility given the country's medical insurance coverage and accessibility. The guidelines were validated through expert reviews and Delphi rounds, achieving consensus on the final recommendations. CONCLUSION: The developed guidelines provide a structured, evidence-based approach to reducing suicide rates among psychiatric patients in Korea. Future research will focus on expanding these guidelines to include screening protocols for high-risk groups.

Psychotropic Medications Promote Time-Dependent Reduction of Suicidal Ideation in Mood Disorder: A Prospective Cohort Study.

BACKGROUND: Despite a plethora of research on the topic, there is still no solid evidence that pharmacological treatment actually reduces the risk of suicide in patients with mental illness. In this study, we aimed to assess the effect of psychotropic medications on suicidal ideation in patients with major depressive disorder (MDD) and bipolar disorder (BPD) in two age groups: less than 25 years and 25 years and older. METHODS: We analyzed 312 patients with mood disorders with current suicidal thoughts or recent suicide attempts. We followed the participants from baseline for 6 months and assessed changes in suicidal ideation with Columbia-Suicide Severity Rating Scale (C-SSRS). The effect of psychotropic drug administration on suicidal ideation over time was analyzed using a linear mixed model. RESULTS: In patients aged 25 years and older with mood disorders, suicidal ideation was more severe when using psychotropic drugs than when not using them. However, suicidal ideation decreased rapidly over time. The time-dependent reduction in suicidal ideation was accelerated when using antidepressants and sedatives/hypnotics in adult MDD, and when using mood stabilizers in adult BPD. However, this effect was not observed in participants aged less than 25 years. CONCLUSION: Adequate psychotropic medication may reduce suicidal ideation in patients with mood disorders aged 25 years and older. Additional research on psychotropic drugs is needed to effectively reduce the risk of suicide among children and adolescents with mood disorders.

Development and external validation of a logistic and a penalized logistic model using machine-learning techniques to predict suicide attempts: A multicenter prospective cohort study in Korea.

Despite previous efforts to build statistical models for predicting the risk of suicidal behavior using machine-learning analysis, a high-accuracy model can lead to overfitting. Furthermore, internal validation cannot completely address this problem. In this study, we created models for predicting the occurrence of suicide attempts among Koreans at high risk of suicide, and we verified these models in an independent cohort. We performed logistic and penalized regression for suicide attempts within 6 months among suicidal ideators and attempters in The Korean Cohort for the Model Predicting a Suicide and Suicide-related Behavior (K-COMPASS). We then validated the models in a test cohort. Our findings indicated that several factors significantly predicted suicide attempts in the models, including young age, suicidal ideation, previous suicidal attempts, anxiety, alcohol abuse, stress, and impulsivity. The area under the curve and positive predictive values were 0.941 and 0.484 after variable selection and 0.751 and 0.084 in the test cohort. The corresponding values for the penalized regression model were 0.943 and 0.524 in the original training cohort and 0.794 and 0.115 in the test cohort. The prediction model constructed through a prospective cohort study of the suicide high-risk group showed satisfactory accuracy even in the test cohort. The accuracy with penalized regression was greater than that with the "classical" logistic model.

Gene-gene interaction analysis for age at onset of bipolar disorder in a Korean population.

BACKGROUND: Multiple genes might interact to determine the age at onset of bipolar disorder. We investigated gene-gene interactions related to age at onset of bipolar disorder in the Korean population, using genome-wide association study (GWAS) data. METHODS: The study population consisted of 303 patients with bipolar disorder. First, the top 1000 significant single-nucleotide polymorphisms (SNPs) associated with age at onset of bipolar disorder were selected through single SNP analysis by simple linear regression. Subsequently, the QMDR method was used to find gene-gene interactions. RESULTS: The best 10 SNPs from simple regression were located in chromosome 1, 2, 3, 10, 11, 14, 19, and 21. Only five SNPs were found in several genes, such as FOXN3, KIAA1217, OPCML, CAMSAP2, and PTPRS. On QMDR analyses, five pairs of SNPs showed significant interactions with a CVC exceeding 1/5 in a two-locus model. The best interaction was found for the pair of rs60830549 and rs12952733 (CVC = 1/5, P < 1E-07). In three-locus models, four combinations of SNPs showed significant associations with age at onset, with a CVC of >1/5. The best three-locus combination was rs60830549, rs12952733, and rs12952733 (CVC = 2/5, P < 1E-6). The SNPs showing significant interactions were located in the KIAA1217, RBFOX3, SDK2, CYP19A1, NTM, SMYD3, and RBFOX1 genes. CONCLUSIONS: Our analysis confirmed genetic interactions influencing the age of onset for bipolar disorder and identified several potential candidate genes. Further exploration of the functions of these promising genes, which may have multiple roles within the neuronal network, is necessary.

Integrated proteomic and genomic analysis to identify predictive biomarkers for valproate response in bipolar disorder: a 6-month follow-up study.

BACKGROUND: Several genetic studies have been undertaken to elucidate the intricate interplay between genetics and drug responses in bipolar disorder (BD). However, there has been notably limited research on biomarkers specifically linked to valproate, with only a few studies investigating integrated proteomic and genomic factors in response to valproate treatment. Therefore, this study aimed to identify biological markers for the therapeutic response to valproate treatment in BD. Patients with BD in remission were assessed only at baseline, whereas those experiencing acute mood episodes were evaluated at three points (baseline, 8 ± 2 weeks, and 6 ± 1 months). The response to valproate treatment was measured using the Alda scale, with individuals scoring an Alda A score ≥ 5 categorized into the acute-valproate responder (acute-VPAR) group. We analyzed 158 peptides (92 proteins) from peripheral blood samples using multiple reaction monitoring mass spectrometry, and proteomic result-guided candidate gene association analyses, with 1,627 single nucleotide variants (SNVs), were performed using the Korean chip. RESULTS: The markers of 37 peptides (27 protein) showed temporal upregulation, indicating possible association with response to valproate treatment. A total of 58 SNVs in 22 genes and 37 SNVs in 16 genes showed nominally significant associations with the Alda A continuous score and the acute-VPAR group, respectively. No SNVs reached the genome-wide significance threshold; however, three SNVs (rs115788299, rs11563197, and rs117669164) in the secreted phosphoprotein 2 gene reached a gene-based false discovery rate-corrected significance threshold with response to valproate treatment. Significant markers were associated with the pathophysiological processes of bipolar disorders, including the immune response, acute phase reaction, and coagulation cascade. These results suggest that valproate effectively suppresses mechanisms associated with disease progression. CONCLUSIONS: The markers identified in this study could be valuable indicators of the underlying mechanisms associated with response to valproate treatment.

Risk factors of reattempt among suicide attempters in South Korea: A nationwide retrospective cohort study.

This study aimed to identify underlying demographic and clinical characteristics among individuals who had previously attempted suicide, utilizing the comprehensive Health Insurance Review and Assessment Service (HIRA) database. Data of patients aged 18 and above who had attempted suicide between January 1 and December 31, 2014, recorded in HIRA, were extracted. The index date was identified when a suicide attempt was made within the year 2014. The medical history of the three years before the index date and seven years of follow-up data after the index date were analyzed. Kaplan-Meier estimate was used to infer reattempt of the suicide attempters, and Cox-proportional hazard analysis was used to investigate risk factors associated with suicide reattempts. A total of 17,026 suicide attempters were identified, of which 1,853 (10.9%) reattempted suicide; 4,925 (28.9%) patients had been diagnosed with depressive disorder. Of the reattempters, 391 (21.1%) demonstrated a history of suicide attempts in the three years before the index date, and the mean number of prior attempts was higher compared to that of the non-reattempters (1.7 vs.1.3, p-value < 0.01). Prior psychiatric medication, polypharmacy, and an increase in the number of psychotropics were associated with suicide reattempt in overall suicide attempters. (Hazard ratio (HR) = 3.20, 95% confidence interval [CI] = 2.56-4.00; HR = 2.42, 95% CI = 1.87-3.14; HR = 19.66, 95% CI = 15.22-25.39 respectively). The risk of reattempt decreased in individuals receiving antidepressant prescriptions compared to those unmedicated, showing a reduction of 78% when prescribed by non-psychiatrists and 89% when prescribed by psychiatrists. Similar risk factors for suicide reattempts were observed in the depressive disorder subgroup, but the median time to reattempt was shorter (556.5 days) for this group compared to that for the overall attempters (578 days). Various risk factors including demographics, clinical characteristics, and medications should be considered to prevent suicide reattempts among suicide attempters, and patients with depressive disorder should be monitored more closely.

The characteristics and clinical outcomes of a pluripotent high-risk group with the potential to develop a diverse range of psychiatric disorders.

BACKGROUND: Recent studies have indicated that clinical high risk for psychosis (CHR-P) is highly specific for psychotic disorders other than pluripotential to various serious mental illnesses. However, not all CHR-P develop psychotic disorder only, and psychosis can occur in non-psychotic disorders as well. Our prospective cohort study aims to investigate the characteristics and clinical outcomes of a pluripotent high-risk group with the potential to develop a diverse range of psychiatric disorders. METHODS: The SPRIM study is a prospective naturalistic cohort program that focuses on the early detection of those at risk of developing serious mental illness, including psychosis (CHR-P), bipolar (CHR-B), and depressive disorder (CHR-D), as well as undifferentiated risk participants (UCHR). Our study has a longitudinal design with a baseline assessment and eight follow-up evaluations at 6, 12, 18, 24, 30, 36, 42, and 48 months to determine whether participants have transitioned to psychosis or mood disorders. RESULTS: The SPRIM sample consisted of 90 CHR participants. The total cumulative incidence rate of transition was 53.3% (95% CI 32.5-77.2). CHR-P, CHR-B, CHR-D, and UCHR had cumulative incidence rates of 13.7% (95% CI 3.4-46.4), 52.4% (95% CI 28.1-81.1), 66.7% (95% CI 24.6-98.6) and 54.3% (95% CI 20.5-93.1), respectively. The cumulative incidence of psychosis, bipolar, and depressive disorder among all participants was 3.3% (95% CI 0.8-11.5), 45.7% (95% CI 24.4-73.6), and 11.2% (95% CI 3.1-36.2), respectively. CONCLUSIONS: Our study suggests that the concept of pluripotent high-risk for a diverse range of psychiatric disorders is an integrative approach to examining transdiagnostic interactions between illnesses with a high transition rate and minimizing stigma.

Serum lipids as predictive markers for death by suicide.

Serum lipid levels have been associated with an increased risk of suicidal behaviors. This retrospective cohort study aimed to investigate the association between serum lipid levels and death by suicide among suicide attempters according to sex. Suicide attempters visiting emergency departments between 2007 and 2011 were followed up until the date of all-cause death or December 31, 2012. Sex-stratified Cox proportional hazards regression and competing risk models were constructed to obtain the hazard ratios (HR) of serum lipid measures and suicide. For each significant lipid variable in the final models, Kaplan-Meier survival analysis and cumulative incidence function (CIF) were employed to compare the time to suicide between the high- and low-lipid groups based on the best cutoff point from the receiver operating characteristic curve. In 408 female attempters (65.8 %), the HR in the Cox regression model and subdistribution HR in the competing risk model for increased total cholesterol (TC) were 0.968 and 0.970, respectively. In the Kaplan-Meier survival analysis and CIF, increased death by suicide was demonstrated in the low-TC group (< 165 mg/dL). Lower serum TC levels among female suicide attempters may predict suicide. More careful monitoring is warranted in women with lower TC levels who recently attempted suicide.

Identifying predictive factors for mood recurrence in early-onset major mood disorders: A 4-year, multicenter, prospective cohort study.

We investigate the predictive factors of the mood recurrence in patients with early-onset major mood disorders from a prospective observational cohort study from July 2015 to December 2019. A total of 495 patients were classified into three groups according to recurrence during the cohort observation period: recurrence group with (hypo)manic or mixed features (MMR), recurrence group with only depressive features (ODR), and no recurrence group (NR). As a result, the baseline diagnosis of bipolar disorder type 1 (BDI) and bipolar disorder type 2 (BDII), along with a familial history of BD, are strong predictors of the MMR. The discrepancies in wake-up times between weekdays and weekends, along with disrupted circadian rhythms, are identified as a notable predictor of ODR. Our findings confirm that we need to be aware of different predictors for each form of mood recurrences in patients with early-onset mood disorders. In clinical practice, we expect that information obtained from the initial assessment of patients with mood disorders, such as mood disorder type, family history of BD, regularity of wake-up time, and disruption of circadian rhythms, can help predict the risk of recurrence for each patient, allowing for early detection and timely intervention.

Genome-wide association study implicates the role of TBXAS1 in the pathogenesis of depressive symptoms among the Korean population.

Although depression is an emerging disorder affecting many people worldwide, most genetic studies have been performed in European descent populations. Herein, a genome-wide association study (GWAS) was conducted in Korean population to elucidate the genomic loci associated with depressive symptoms. Two independent cohorts were used as discovery datasets, which consisted of 6474 (1484 cases and 4990 controls) and 1654 (557 cases and 1097 controls) Korean participants, respectively. The participants were divided into case and control groups based on the Beck Depression Inventory (BDI). Meta-analysis using the two cohorts revealed that rs6945590 was significantly associated with the risk of depressive symptoms [P = 2.83 × 10-8; odds ratio (OR) = 1.23; 95% confidence interval (CI): 1.15-1.33]. This association was validated in other independent cohorts which were another Korean cohort (258 cases and 1757 controls) and the East Asian study of the Psychiatric Genomics Consortium (PGC) (12,455 cases and 85,548 controls). The predicted expression levels of thromboxane A synthase 1 gene (TBXAS1), which encodes the enzyme thromboxane A synthase 1 and participates in the arachidonic acid (AA) cascade, was significantly decreased in the whole blood tissues of the participants with depressive symptoms. Furthermore, Mendelian randomization (MR) analysis showed a causal association between TBXAS1 expression and the risk of depressive symptoms. In conclusion, as the number of risk alleles (A) of rs6945590 increased, TBXAS1 expression decreased, which subsequently caused an increase in the risk of depressive symptoms.

Proteomic profiling in the progression of psychosis: Analysis of clinical high-risk, first episode psychosis, and healthy controls.

BACKGROUND AND HYPOTHESIS: Recent evidence has highlighted the benefits of early detection and treatment for better clinical outcomes in patients with psychosis. Biological markers of the disease have become a focal point of research. This study aimed to identify protein markers detectable in the early stages of psychosis and indicators of progression by comparing them with those of healthy controls (HC) and first episode psychosis (FEP). STUDY DESIGN: The participants comprised 28 patients in the clinical high-risk (CHR) group, 49 patients with FEP, and 61 HCs aged 15-35 years. Blood samples were collected and analyzed using multiple reaction monitoring-mass spectrometry to measure the expression of 158 peptide targets. Data were adjusted for age, sex, and use of psychotropic drugs. STUDY RESULTS: A total of 18 peptides (17 proteins) differed significantly among the groups. The protein PRDX2 was higher in the FEP group than in the CHR and HC groups and showed increased expression according to disease progression. The levels of six proteins were significantly higher in the FEP group than in the CHR group. Nine proteins differed significantly in the CHR group compared to the other groups. Sixteen proteins were significantly correlated with symptom severity. These proteins are primarily related to the coagulation cascade, inflammatory response, brain structure, and synaptic plasticity. CONCLUSIONS: Our findings suggested that peripheral protein markers reflect disease progression in patients with psychosis. Further longitudinal research is needed to confirm these findings and to identify the specific roles of these markers in the pathogenesis of schizophrenia.

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study.

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890-0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.

The association between insulin resistance and depressive symptoms - A national representative cross-sectional study.

OBJECTIVE: Increasing evidence suggests a positive association between insulin resistance (IR) and depression. However, whether sex-or body mass index-specific differences exist remains controversial, and only few studies have analyzed specific symptom domains. Thus, the present study aimed to analyze the association between IR and depressive symptom domains and to clarify the effects of sex and body mass index. METHODS: The study sample comprised 4007 participants, aged 19-79, from the Korea National Health and Nutrition Examination Study 2020. Participants completed health interviews and examinations, providing data on circulating insulin and glucose levels, the Patient Health Questionnaire-9 (PHQ-9), and related covariates. IR was calculated using the homeostasis model assessment of insulin resistance. Associations between IR and PHQ-9 were analyzed using negative binomial regression with adjustments for the complex survey design. RESULTS: The association between log-transformed IR and PHQ-9 total scores was statistically significant (incidence rate ratio [IRR] = 1.17, 95% confidence interval [CI] = 1.07-1.29, p = 0.001). Only body mass index specific differences were statistically significant, as the association was only significant in those without obesity (IRR = 1.21, 95% CI = 1.06-1.38, p = 0.005). IR was associated with cognitive/affective (IRR = 1.23, 95% CI = 1.08-1.41, p = 0.002) and somatic (IRR = 1.14, 95% CI = 1.04-1.25, p = 0.005) depressive symptom domains. Sensitivity analyses revealed similar results. CONCLUSIONS: IR was positively associated with cognitive/affective and somatic depressive symptoms in non-obese individuals.

Duration of Adjunctive Antidepressant Maintenance in Bipolar I Depression.

BACKGROUND: Antidepressants are used to treat acute depression in patients with bipolar I disorder, but their effect as maintenance treatment after the remission of depression has not been well studied. METHODS: We conducted a multisite, double-blind, randomized, placebo-controlled trial of maintenance of treatment with adjunctive escitalopram or bupropion XL as compared with discontinuation of antidepressant therapy in patients with bipolar I disorder who had recently had remission of a depressive episode. Patients were randomly assigned in a 1:1 ratio to continue treatment with antidepressants for 52 weeks after remission or to switch to placebo at 8 weeks. The primary outcome, assessed in a time-to-event analysis, was any mood episode, as defined by scores on scales measuring symptoms of hypomania or mania, depression, suicidality, and mood-episode severity; additional treatment or hospitalization for mood symptoms; or attempted or completed suicide. Key secondary outcomes included the time to an episode of mania or hypomania or depression. RESULTS: Of 209 patients with bipolar I disorder who participated in an open-label treatment phase, 150 who had remission of depression were enrolled in the double-blind phase in addition to 27 patients who were enrolled directly. A total of 90 patients were assigned to continue treatment with the prescribed antidepressant for 52 weeks (52-week group) and 87 were assigned to switch to placebo at 8 weeks (8-week group). The trial was stopped before full recruitment was reached owing to slow recruitment and funding limitations. At 52 weeks, 28 of the patients in the 52-week group (31%) and 40 in the 8-week group (46%) had a primary-outcome event. The hazard ratio for time to any mood episode in the 52-week group relative to the 8-week group was 0.68 (95% confidence interval [CI], 0.43 to 1.10; P = 0.12 by log-rank test). A total of 11 patients in the 52-week group (12%) as compared with 5 patients in the 8-week group (6%) had mania or hypomania (hazard ratio, 2.28; 95% CI, 0.86 to 6.08), and 15 patients (17%) as compared with 35 patients (40%) had recurrence of depression (hazard ratio, 0.43; 95% CI, 0.25 to 0.75). The incidence of adverse events was similar in the two groups. CONCLUSIONS: In a trial involving patients with bipolar I disorder and a recently remitted depressive episode, adjunctive treatment with escitalopram or bupropion XL that continued for 52 weeks did not show a significant benefit as compared with treatment for 8 weeks in preventing relapse of any mood episode. The trial was stopped early owing to slow recruitment and funding limitations. (Funded by the Canadian Institutes of Health Research; ClinicalTrials.gov number, NCT00958633.).

Network analysis of plasma proteomes in affective disorders.

The conventional differentiation of affective disorders into major depressive disorder (MDD) and bipolar disorder (BD) has insufficient biological evidence. Utilizing multiple proteins quantified in plasma may provide critical insight into these limitations. In this study, the plasma proteomes of 299 patients with MDD or BD (aged 19-65 years old) were quantified using multiple reaction monitoring. Based on 420 protein expression levels, a weighted correlation network analysis was performed. Significant clinical traits with protein modules were determined using correlation analysis. Top hub proteins were determined using intermodular connectivity, and significant functional pathways were identified. Weighted correlation network analysis revealed six protein modules. The eigenprotein of a protein module with 68 proteins, including complement components as hub proteins, was associated with the total Childhood Trauma Questionnaire score (r = -0.15, p = 0.009). Another eigenprotein of a protein module of 100 proteins, including apolipoproteins as hub proteins, was associated with the overeating item of the Symptom Checklist-90-Revised (r = 0.16, p = 0.006). Functional analysis revealed immune responses and lipid metabolism as significant pathways for each module, respectively. No significant protein module was associated with the differentiation between MDD and BD. In conclusion, childhood trauma and overeating symptoms were significantly associated with plasma protein networks and should be considered important endophenotypes in affective disorders.

Shifting attitudes toward suicide over time: A latent profile analysis using the Korea National Suicide Survey.

Introduction: South Korea has a high suicide rate, and changes in sociodemographic factors can further increase the rate. This study aims to (1) classify participants using the Attitudes toward Suicide Scale (ATTS) through latent profile analysis (LPA), (2) identify and compare the associations between sociodemographic factors with the ATTS in two survey years (2013, 2018), and (3) determine the moderating effect of survey year. Methods: Six sub-factors of the ATTS were used for LPA with a total of 2,973 participants. Sociodemographic characteristics were compared between groups, and multinomial logistic regression was conducted for each survey year. A moderation analysis was conducted with the survey year as moderator. Results: LPA identified three groups of attitudes toward suicide: incomprehensible (10.3%), mixed (52.8%), and permissive (36.9%). The proportion of permissive attitudes increased from 2013 (32.3%) to 2018 (41.7%). Participants reporting suicidal behavior were more likely to be in the mixed and permissive groups than the incomprehensible group in both years. People reporting no religious beliefs were associated with the permissive group in the two survey years. The influence of education and income levels on groups differed by survey year. Discussion: There were significant changes between 2013 and 2018 in attitudes toward suicide in the Korean population.