The risks for major psychiatric disorders in the siblings of probands with major depressive disorder.

Using a case-controlled study including siblings of major depression (MD) and control probands, born 1970-1990 and followed through 2018, we sought to clarify the degree to which the familial liability to MD is reflected in its clinical features, and the pattern of psychiatric disorders at elevated risk in the siblings of MD probands. The study population included full-siblings of 197,309 MD and matched 197,309 control probands. The proband-sibling tetrachoric correlation of for MD was +0.20. Both linear and quadratic effects of younger AAO and number of episodes significantly increased the risk of MD in siblings. Male sex, anxiety disorder, alcohol use disorder (AUD), inpatient treatment, psychotic symptoms, severity, and antidepressant prescription in MD probands increased the risk of MD in siblings. Cox proportional hazard models (hazard ratios, 95% CI) revealed a significantly increased risk of attention deficit hyperactivity disorder (1.82, 1.76-1.88), generalized anxiety disorder (1.79, 1.74-1.85), bipolar disorder (1.78, 1.70-1.85), MD (1.74, 1.72-1.76), obsessive-compulsive disorder (1.72, 1.65-1.80), phobic anxiety disorder (1.71, 1.65-1.76), and panic disorder (1.68, 1.64-1.72) in MD co-siblings. The HRs for AUD (1.64, 1.60-1.68), post-traumatic stress disorder (1.62, 1.59-1.66) were modestly lower, and the lowest was seen for schizophrenia (1.42, 1.30-1.54). The overall pattern of increased risk of these disorders was similar in reared-apart half-siblings and cousins of MD probands. Our findings suggest that MD is familial, and a range of important clinical factors predict its familial liability. The familial liability to MD, mostly due to genetic factors, is shared with a broad range of psychiatric disorders.

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.

Predictors of diagnostic conversion from major depression to bipolar disorder: a Swedish national longitudinal study.

BACKGROUND: It is clinically important to predict the conversion of major depression (MD) to bipolar disorder (BD). Therefore, we sought to identify related conversion rates and risk factors. METHODS: This cohort study included the Swedish population born from 1941 onward. Data were collected from Swedish population-based registers. Potential risk factors, including family genetic risk scores (FGRS), which were calculated based on the phenotypes of relatives in the extended family and not molecular data, and demographic/clinical characteristics from these registers were retrieved. Those with first MD registrations from 2006 were followed up until 2018. The conversion rate to BD and related risk factors were analyzed using Cox proportional hazards models. Additional analyses were performed for late converters and with stratification by sex. RESULTS: The cumulative incidence of conversion was 5.84% [95% confidence interval (95% CI) 5.72-5.96] for 13 years. In the multivariable analysis, the strongest risk factors for conversion were high FGRS of BD [hazard ratio (HR) = 2.73, 95% CI 2.43-3.08], inpatient treatment settings (HR = 2.64, 95% CI 2.44-2.84), and psychotic depression (HR = 2.58, 95% CI 2.14-3.11). For late converters, the first registration of MD during the teenage years was a stronger risk factor when compared with the baseline model. When the interactions between risk factors and sex were significant, stratification by sex revealed that they were more predictive in females. CONCLUSIONS: Family history of BD, inpatient treatment, and psychotic symptoms were the strongest predictors of conversion from MD to BD.

Acoustic Analysis of Speech for Screening for Suicide Risk: Machine Learning Classifiers for Between- and Within-Person Evaluation of Suicidality.

BACKGROUND: Assessing a patient's suicide risk is challenging for health professionals because it depends on voluntary disclosure by the patient and often has limited resources. The application of novel machine learning approaches to determine suicide risk has clinical utility. OBJECTIVE: This study aimed to investigate cross-sectional and longitudinal approaches to assess suicidality based on acoustic voice features of psychiatric patients using artificial intelligence. METHODS: We collected 348 voice recordings during clinical interviews of 104 patients diagnosed with mood disorders at baseline and 2, 4, 8, and 12 months after recruitment. Suicidality was assessed using the Beck Scale for Suicidal Ideation and suicidal behavior using the Columbia Suicide Severity Rating Scale. The acoustic features of the voice, including temporal, formal, and spectral features, were extracted from the recordings. A between-person classification model that examines the vocal characteristics of individuals cross sectionally to detect individuals at high risk for suicide and a within-person classification model that detects considerable worsening of suicidality based on changes in acoustic features within an individual were developed and compared. Internal validation was performed using 10-fold cross validation of audio data from baseline to 2-month and external validation was performed using data from 2 to 4 months. RESULTS: A combined set of 12 acoustic features and 3 demographic variables (age, sex, and past suicide attempts) were included in the single-layer artificial neural network for the between-person classification model. Furthermore, 13 acoustic features were included in the extreme gradient boosting machine learning algorithm for the within-person model. The between-person classifier was able to detect high suicidality with 69% accuracy (sensitivity 74%, specificity 62%, area under the receiver operating characteristic curve 0.62), whereas the within-person model was able to predict worsening suicidality over 2 months with 79% accuracy (sensitivity 68%, specificity 84%, area under receiver operating characteristic curve 0.67). The second model showed 62% accuracy in predicting increased suicidality in external sets. CONCLUSIONS: Within-person analysis using changes in acoustic features within an individual is a promising approach to detect increased suicidality. Automated analysis of voice can be used to support the real-time assessment of suicide risk in primary care or telemedicine.

Quantitative Proteomic Approach for Discriminating Major Depressive Disorder and Bipolar Disorder by Multiple Reaction Monitoring-Mass Spectrometry.

Because major depressive disorder (MDD) and bipolar disorder (BD) manifest with similar symptoms, misdiagnosis is a persistent issue, necessitating their differentiation through objective methods. This study was aimed to differentiate between these disorders using a targeted proteomic approach. Multiple reaction monitoring-mass spectrometry (MRM-MS) analysis was performed to quantify protein targets regarding the two disorders in plasma samples of 270 individuals (90 MDD, 90 BD, and 90 healthy controls (HCs)). In the training set (72 MDD and 72 BD), a generalizable model comprising nine proteins was developed. The model was evaluated in the test set (18 MDD and 18 BD). The model demonstrated a good performance (area under the curve (AUC) >0.8) in discriminating MDD from BD in the training (AUC = 0.84) and test sets (AUC = 0.81) and in distinguishing MDD from BD without current hypomanic/manic/mixed symptoms (90 MDD and 75 BD) (AUC = 0.83). Subsequently, the model demonstrated excellent performance for drug-free MDD versus BD (11 MDD and 10 BD) (AUC = 0.96) and good performance for MDD versus HC (AUC = 0.87) and BD versus HC (AUC = 0.86). Furthermore, the nine proteins were associated with neuro, oxidative/nitrosative stress, and immunity/inflammation-related biological functions. This proof-of-concept study introduces a potential model for distinguishing between the two disorders.

The influence of poverty attribution on attitudes toward suicide and suicidal thought: A cross-national comparison between South Korean, Japanese, and American populations.

BACKGROUND: Previous studies report that income inequality is an important risk factor for depression and suicide, and an increasing income gap appears inevitable. However, little study to date has investigated associations between the attribution of poverty and suicide. Though we previously reported associations between socio-cultural factors, including income, and suicide, we tried to explore more focused associations between income, attribution of poverty (individualistic, societal), permissive attitude toward suicide, and suicidal thought using a structural equation model. METHODS: A total of 2213 participants from each of three nations (South Korea, Japan, and the United States) completed an online survey. Participants without a history of psychological disorders or suicide attempts completed scales measuring attributions of poverty, attitudes toward suicide, and severity of suicidal thoughts. RESULTS: We established a structural equation model, which exhibited a good fit for all nations, and compared significant path coefficients by country. South Korea had the highest severity of suicidal thought and societal attribution of poverty, followed by Japan and America. In all nations, a permissive attitude was positively related to the severity of suicidal thought and individualistic attribution of poverty was positively related to a permissive attitude toward suicide. Societal attribution of poverty was positively associated with a permissive attitude in Japan and the United States. Income was negatively associated with the severity of suicide in South Korea and the United States. CONCLUSION: Through an established structural equation model, we found the influence of poverty on suicide and identify the common and distinctive factors associated with suicide in each country.

Self-Transcendence Mediates the Relationship between Early Trauma and Fatal Methods of Suicide Attempts.

BACKGROUND: Early trauma is known to be a risk factor of suicide-related behavior. On the other hand, people who attempt suicide using a fatal method are reported to be more likely to complete suicide. In this study, we assumed that early trauma affects an individual's temperament and character and thereby increases the risk of a fatal method of suicide attempts. METHODS: We analyzed 92 people with a history of previous suicide attempts. We compared the Temperament and Character Inventory-Revised scores between the groups with and without early trauma, and between the groups with and without a history of suicide attempt using fatal methods through an analysis of covariance with age, sex, and presence of a psychiatric history as covariates. A mediation analysis was conducted of the relationship between early trauma and fatal methods of suicide attempt with self-transcendence as a mediator. RESULTS: Higher self-transcendence was reported in the fatal group (27.71 ± 13.78 vs. 20.97 ± 12.27, P = 0.010) and the early trauma group (28.05 ± 14.30 vs. 19.43 ± 10.73, P = 0.001), respectively. The mediation model showed that self-transcendence mediates the relationship between early trauma and fatal methods of suicide attempt. The 95% confidence intervals for the direct and indirect effect were (-0.559, 1.390) and (0.026, 0.947), respectively. CONCLUSION: Self-transcendence may mediate the relationship between early trauma and fatal methods of suicide attempt. Self-transcendence may be associated with unhealthy defenses and suicidal behavior for self-punishment and may constitute a marker of higher suicide risk.

Early Trauma and Relationships among Recent Stress, Depressive Symptoms, Anxiety Symptoms, and Suicidal Ideation in Korean Women.

BACKGROUND: Evidence continues to accumulate that the presence or absence of early trauma (ET) implies unique characteristics in the relationships between suicidal ideation and its risk factors. We examined the relationships among recent stress, depressive symptoms, anxiety symptoms, and suicidal ideation in Korean suicidal women with or without such a history. METHODS: Using data on suicidal adult females, 217 victims and 134 non-victims of ET, from the Korean Cohort for the Model Predicting a Suicide and Suicide-related Behavior, we performed structural equation modeling to investigate the contribution of recent stress, depressive symptoms, and anxiety symptoms on suicidal ideation within each group according to the presence or absence of a history of ET. RESULTS: Structural equation modeling with anxiety and depressive symptoms as potential mediators showed a good fit. Recent stress had a direct effect on both depressive symptoms and anxiety symptoms in both groups. Only anxiety symptoms for victims of ET (standardized regression weight, 0.281; P = 0.005) and depressive symptoms for non-victims of ET (standardized regression weight, 0.326; P = 0.003) were full mediators that increased suicidal ideation. Thus, stress contributed to suicidal ideation by increasing the level of anxiety and depressive symptoms for victims and non-victims, respectively. CONCLUSION: Tailored strategies to reduce suicidal ideation should be implemented according to group type, victims or non-victims of ET. Beyond educating suicidal women in stress-management techniques, it would be effective to decrease anxiety symptoms for those with a history of ET and decrease depressive symptoms for those without such a history.

Comparison of serum protein profiles between major depressive disorder and bipolar disorder.

BACKGROUND: Major depressive disorder and bipolar disorder are prevalent and debilitating psychiatric disorders that are difficult to distinguish, as their diagnosis is based on behavioural observations and subjective symptoms. Quantitative protein profile analysis might help to objectively distinguish between these disorders and increase our understanding of their pathophysiology. Thus, this study was conducted to compare the peripheral protein profiles between the two disorders. METHODS: Serum samples were collected from 18 subjects with major depressive disorder and 15 subjects with bipolar disorder. After depleting abundant proteins, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification were performed. Data-dependent acquisition data were statistically analysed from the samples of 15 subjects with major depressive disorder and 10 subjects with bipolar disorder who were psychotropic drug-free. Two-sided t-tests were performed for pairwise comparisons of proteomes to detect differentially-expressed proteins (DEPs). Ingenuity Pathway Analysis of canonical pathways, disease and functions, and protein networks based on these DEPs was further conducted. RESULTS: Fourteen DEPs were significant between subjects with major depressive disorder and those with bipolar disorder. Ras-related protein Rab-7a (t = 5.975, p = 4.3 × 10- 6) and Rho-associated protein kinase 2 (t = 4.782, p = 8.0 × 10- 5) were significantly overexpressed in subjects with major depressive disorder and Exportin-7 (t = -4.520, p = 1.5 × 10- 4) was significantly overexpressed in subjects with bipolar disorder after considering multiple comparisons. Bioinformatics analysis showed that cellular functions and inflammation/immune pathways were significantly different. CONCLUSIONS: Ras-related protein Rab-7a, Rho-associated protein kinase 2, and Exportin-7 were identified as potential peripheral protein candidates to distinguish major depressive disorder and bipolar disorder. Further large sample studies with longitudinal designs and validation processes are warranted.

Cost analysis of depression using the national insurance system in South Korea: a comparison of depression and treatment-resistant depression.

BACKGROUND: The incidence and burden of depressive disorders are increasing in South Korea. There are many differences between pharmaceutically treated depression (PTD) and treatment-resistant depression (TRD), including the economic consequences; however, to our knowledge, the economic burden of depression is understudied in South Korea. Therefore, the objective of the present study was to calculate the different economic costs of PTD and TRD in South Korea, specifically by comparing several aspects of medical care. METHODS: This study comprised patients aged 18 and over who were newly prescribed antidepressants for more than 28 days with a depression code included from January 1, 2012, to December 31, 2012, by the Health Insurance Review and Assessment Service (HIRA). TRD was classified as more than two antidepressant regimen failures in PTD patients. The cost was calculated based on the cost reflected on the receipt registered with HIRA. RESULTS: Of the 834,694 patients with PTD, 34,812 patients (4.17%) were converted to TRD. The cost of medical care for TRD (6,610,487 KRW, 5881 USD) was approximately 5 times higher than the cost of non-TRD (1,273,045 KRW, 1133 USD) and was significantly higher for patients with or without depression and suicide codes. Medical expenses incurred by non-psychiatrists were roughly 1.7 times higher than those incurred by psychiatrists. CONCLUSIONS: TRD patients had significantly higher healthcare costs than PTD patients. Identifying these financial aspects of care for depression can help to establish a more effective policy to reduce the burden on mentally ill patients.

Comparison of Serum Uric Acid in Major Depressive Disorder and Bipolar Disorder: a Retrospective Chart Review Study.

BACKGROUND: Uric acid (UA) has been suggested as a possible biomarker of bipolar disorder (BD) in recent studies. We aimed to provide a clearer comparison of UA levels between BD and major depressive disorder (MDD). METHODS: We retrospectively reviewed the medical chart records of psychiatric inpatients aged 19-60 years, whose main discharge diagnoses were either MDD or BD, with an admission between January 1, 2015 and December 31, 2018 at Seoul National University Hospital. Data such as sex, age, body mass index (BMI), medication usage, and serum UA levels were extracted. Patients with medical conditions or on medications that could influence UA levels were excluded. Age, sex, BMI, and psychiatric drug usage were considered in the comparison of serum UA between MDD and BD patients. RESULTS: Our sample consisted of 142 MDD patients and 234 BD patients. The BD patients had significantly higher serum UA levels compared to the MDD patients, without accounting for other confounding variables (5.75 ± 1.56 mg/dL vs. 5.29 ± 1.59 mg/dL, P = 0.006). T-test comparisons between psychiatric medication users and non-users revealed that mood stabilizers and antipsychotics may be relevant confounding factors in our sample analysis. The likelihood of BD diagnosis was significantly correlated with higher UA levels (odds ratio, 1.410; 95% confidence interval, 1.150-1.728; P = 0.001) when accounting for sex, age, and BMI in the logistic regression analysis. Also, accounting for mood stabilizers or antipsychotics, the likelihood of BD diagnosis was still significantly correlated with higher UA levels. CONCLUSION: Our study confirms that BD patients are significantly more likely to show higher serum UA levels than MDD patients. The high UA levels in BD point to purinergic dysfunction as an underlying mechanism that distinguishes BD from MDD. Further research is recommended to determine whether UA is a trait or a state marker and whether UA correlates with the symptoms and severity of BD.

Comparison of Suicide Risk by Mental Illness: a Retrospective Review of 14-Year Electronic Medical Records.

BACKGROUND: Korea is one of the countries with the highest rate of suicide, while suicidality is known to be closely related to mental illnesses. The study aimed to evaluate the suicide rates in psychiatric patients, to compare it to that of the general population, and to investigate the differences among psychiatric diagnoses and comorbidities. METHODS: Medical records and mortality statistics of psychiatric patients at Seoul National University Hospital from 2003 to 2017 were reviewed. The standardized mortality ratio (SMR) for suicide was calculated to compare the psychiatric patients with the general population. The diagnosis-specific standardized mortality rate and hazard ratio (HR) were adjusted by age, sex, and psychiatric comorbidity (i.e., personality disorder and/or pain disorder). RESULTS: A total of 40,692 survivors or non-suicidal deaths and 597 suicidal death were included. The suicide rate among psychiatric patients was 5.13-fold higher than that of the general population. Psychotic disorder had the highest SMR (13.03; 95% confidence interval [CI], 11.23-15.03), followed by bipolar disorder (10.26; 95% CI, 7.97-13.00) and substance-related disorder (6.78; 95% CI, 4.14-10.47). In survival analysis, psychotic disorder had the highest HR (4.16; 95% CI, 2.86-6.05), which was further increased with younger age, male sex, and comorbidity of personality disorder. CONCLUSION: All psychiatric patients are at a higher risk of suicide compared to the general population, and the risk is highest for those diagnosed with psychotic disorder.

The Korean Cohort for the Model Predicting a Suicide and Suicide-related Behavior: Study rationale, methodology, and baseline sample characteristics of a long-term, large-scale, multi-center, prospective, naturalistic, observational cohort study.

BACKGROUND: The Korean Cohort for the Model Predicting a Suicide and Suicide-related Behavior (K-COMPASS) study is a prospective, naturalistic, observational cohort study, aiming to identify predictors of suicide attempt and suicide characteristics in the Korean suicidal population. The findings intend to contribute to a thorough understanding of suicidal phenomena and development of suicide prevention guidelines. The present cross-section study examines the study rationale, methodology, and baseline characteristics of the participants. METHODS: Participants were enrolled via the hospital and community gateways, establishing the hospital-based cohort (HC) and community-based cohort (CC), respectively. Baseline assessment was conducted on sociodemographic, clinical, diagnostic, and psychopathological aspects. The Columbia-Suicide Severity Rating Scale was used to investigate suicidality. RESULTS: A total of 800 suicidal people aged 15 years or older were enrolled from 8 university hospitals and 8 community mental health welfare centers (CMHWCs), among whom 480 (60%) were suicidal ideators and 320 (40%) were attempters. The ideators comprised 207 CC and 273 HC participants, whereas the attempters, 34 CC and 286 HC participants. Despite their lower severity in some measures, including suicidal ideation, compared with their HC counterparts, the CC participants within each group of ideators or attempters presented clinically significant psychopathology. Moreover, alcohol use problems and past suicide attempt were more likely to be found in CC participants. Only 11.1% to 21.6% of the participants in each of the four groups (defined by the cohorts and the ideators/attempters) were on any type of psychiatric treatment. CONCLUSIONS: Suicidal visitors to CMHWCs need to be as closely monitored as suicidal patients in university hospitals, especially considering their association with problem drinking and past suicide attempt. A cautious assumption is that the high suicide rate in Korea might be partly attributable to the low proportion of patients receiving psychiatric services.

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.

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.

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.

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.

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.

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.

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.