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.

Network Structure of Interpersonal Sensitivity in Patients With Mood Disorders: A Network Analysis.

OBJECTIVE: Interpersonal sensitivity, characterized by a heightened awareness of others' behavior and emotions, is linked to mood disorders. However, current literature lacks a comprehensive analysis of how some items of the Interpersonal Sensitivity Measure (IPSM) interrelate and contribute to the overall construct. This study constructed a network for interpersonal sensitivity symptomatology to identify core IPSM items in patients with mood disorders. METHODS: The IPSM, a 36-item self-report scale, was utilized to evaluate interpersonal sensitivity symptoms in 837 participants (major depressive disorder [MDD], n=265; bipolar I disorder [BD I], n=126; and bipolar II disorder [BD II], n=446). We performed exploratory graph analysis, employing regularized partial correlation models to estimate the network structure. Centrality analysis identified core IPSM symptoms for each mood disorder group. Network comparison tests assessed structural differences between the MDD and BD subgroups. RESULTS: Network analysis detected five communities. Item 10 ("I worry about being criticized for things that I have said or done") showed the highest value in strength. Multiple items on "Interpersonal Worry/Dependency" and "Low Self-Esteem" showed high strength centrality. Network structure invariance and global strength invariance test results indicated no significant differences between the MDD and BD subgroups. CONCLUSION: Our findings emphasize the importance of addressing "Interpersonal Worry/Dependency" and "Low Self-Esteem" in the IPSM network among mood disorder patients based on core items of the network. Additionally, targeted treatments and comprehensive strategies in this aspect could be crucial for managing mood disorders.

Multivariate genomic analysis of 5 million people elucidates the genetic architecture of shared components of the metabolic syndrome.

Metabolic syndrome (MetS) is a complex hereditary condition comprising various metabolic traits as risk factors. Although the genetics of individual MetS components have been investigated actively through large-scale genome-wide association studies, the conjoint genetic architecture has not been fully elucidated. Here, we performed the largest multivariate genome-wide association study of MetS in Europe (nobserved = 4,947,860) by leveraging genetic correlation between MetS components. We identified 1,307 genetic loci associated with MetS that were enriched primarily in brain tissues. Using transcriptomic data, we identified 11 genes associated strongly with MetS. Our phenome-wide association and Mendelian randomization analyses highlighted associations of MetS with diverse diseases beyond cardiometabolic diseases. Polygenic risk score analysis demonstrated better discrimination of MetS and predictive power in European and East Asian populations. Altogether, our findings will guide future studies aimed at elucidating the genetic architecture of MetS.

Defining Suicidal Thought and Behavior Phenotypes for Genetic Studies.

Background: Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation. Methods: A subgroup of clinician researchers and experts from the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) reviewed existing PGC definitions for SI, SA, SD, and control groups and generated preliminary consensus guidelines for instrument-derived and international classification of disease (ICD) data. ICD lists were validated in two independent datasets (N = 9,151 and 12,394). Results: Recommendations are provided for evaluated instruments for SA and SI, emphasizing selection of lifetime measures phenotype-specific wording. Recommendations are also provided for defining SI and SD from ICD data. As the SA ICD definition is complex, SA code list recommendations were validated against instrument results with sensitivity (range = 15.4% to 80.6%), specificity (range = 67.6% to 97.4%), and positive predictive values (range = 0.59-0.93) reported. Conclusions: Best-practice guidelines are presented for the use of existing information to define SI/SA/SD in consortia research. These proposed definitions are expected to facilitate more homogeneous data aggregation for genetic and multisite studies. Future research should involve refinement, improved generalizability, and validation in diverse populations.

Associations Between COVID-19, Delirium, and 1-Year Mortality: Exploring Influences on Delirium Incidence in COVID-19 Patients.

BACKGROUND: This study investigated the relationship between coronavirus disease 2019 (COVID-19), delirium, and 1-year mortality. Factors associated with delirium in COVID-19 patients were identified, along with the influence of psychotropic medications on delirium. METHODS: The study used the South Korean National Health Insurance Service database. Adult COVID-19 patients diagnosed between October 2020 and December 2021 were included, with a propensity score-matched control group. Time-dependent Cox regression assessed associations among COVID-19, delirium, and mortality. Logistic regression analyzed the impact of psychotropic medications on delirium incidence. RESULTS: The study included 832,602 individuals, with 416,301 COVID-19 patients. COVID-19 (hazard ratio [HR], 3.03; 95% confidence interval [CI], 2.92-3.13) and delirium (HR, 2.33; 95% CI, 2.06-2.63) were independent risk factors for 1-year mortality. Comorbidities, insurance type, and residence were also related to mortality. Among COVID-19 patients, antipsychotic use was associated with lower delirium incidence (odds ratio [OR], 0.38; 95% CI, 0.30-0.47), while mood stabilizers (OR, 1.77; 95% CI, 1.40-2.21) and benzodiazepines (OR, 8.62; 95% CI, 7.46-9.97) were linked to higher delirium incidence. CONCLUSION: COVID-19 and delirium are risk factors for 1-year mortality. Some factors associated with delirium in COVID-19 patients are modifiable and can be targeted in preventive and therapeutic interventions.

Distinguishing Affective Temperament Profiles in Major Depressive Disorder and Bipolar Disorder Through the Short Version of TEMPS-A: Cross-Sectional Study Using Latent Profile Analysis.

OBJECTIVE: This study aimed to elucidate the distinct response patterns exhibited by patients diagnosed with bipolar disorder (BD) and those with major depressive disorder (MDD) through the application of the short version of the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego Autoquestionnaire (TEMPS-A-SV). METHODS: A total of 2,458 participants consisting of patients with MDD (n=288), BD (BD I, n=111; BD II, n=427), and control group (n=1,632) completed the TEMPS-A-SV. The response patterns of the participants were classified into distinct profiles using latent profile analysis. The study further examined the impact of covariates such as age, sex, and diagnostic group on derived latent profile memberships. RESULTS: The following three latent profiles were identified: High Affective Temperament Group (17.86%), Low Affective Temperament Group (41.25%), and Middle Affective Temperament Group (40.89%). Compared with the patient group with MDD and BD, the control group was more likely to belong in the Low Affective Temperament Group, which showed a higher score on hyperthymic temperament than the Middle Affective Temperament Group. Furthermore, compared with the patients with BD, the MDD patients were more likely to be in the Low Affective Temperament Group rather than the Middle Affective Temperament Group. CONCLUSION: These results indicate that different affective temperaments exist between patients with MDD and BD. Attempting to classify response patterns using the TEMPS-A-SV can help diagnose MDD and BD correctly.

The impact of morningness-eveningness on depression through a serial mediation model of resilience and anxiety.

OBJECTIVE: Resilience has been recently considered one of the possible mechanisms for the association between morningness-eveningness and depression. Meanwhile, anxiety is closely associated with mood disorder, but its association with morningness-eveningness is unclear. Therefore, this study aimed to explore the mediating effects of resilience and anxiety on morningness-eveningness and depression as the possible mechanisms. METHODS: This study included patient group and nonpatient group. Patient group consists of 743 patients with mood disorders [Major Depressive Disorder (MDD), 233; Bipolar Disorder I (BDI), 113; Bipolar Disorder II (BDII), 397] whereas nonpatient group consists of 818 individuals without mood disorder. The Composite Scale of Morningness, Connor-Davidson Resilience Scale, Self-Rating Depression Scale, and Beck Anxiety Inventory were used to evaluate morningness-eveningness, resilience, anxiety, and depression, respectively. RESULTS: Our model provided a good fit for the data. The association between morningness-eveningness and depression symptoms was partially serially mediated by resilience and anxiety in both the patient and nonpatient groups. The patient group exhibited significantly stronger morningness-eveningness toward resilience and anxiety than the nonpatient group. In the indirect effect of morningness-eveningness on depression, group differences exist only through each mediation of resilience and anxiety, not through serial mediation. CONCLUSION: Our results expand on the mechanism underlying the association between morningness-eveningness and depression. They highlight the importance of morningness-eveningness modification to increase resilience and the need to consider anxiety jointly in this process.

Network Structure of Depressive Symptomatology in Elderly with Cognitive Impairment.

Objective and objectives: Patients with cognitive disorders such as Alzheimer's disease (AD) and mild cognitive impairment (MCI) frequently exhibit depressive symptoms. Depressive symptoms can be evaluated with various measures and questionnaires. The geriatric depression scale (GDS) is a scale that can be used to measure symptoms in geriatric age. Many questionnaires sum up symptom scales. However, core symptoms of depression in these patients and connections between these symptoms have not been fully explored yet. Thus, the objectives of this study were (1) to determine core symptoms of two cognitive disorders, Alzheimer's disease and mild cognitive impairment, and (2) to investigate the network structure of depressive symptomatology in individuals with cognitive impairment in comparison with those with Alzheimer's disease. Materials and Methods: This study encompassed 5354 patients with cognitive impairments such as Alzheimer's disease (n 1889) and mild cognitive impairment (n = 3464). The geriatric depression scale, a self-administered questionnaire, was employed to assess depressive symptomatology. Using exploratory graph analysis (EGA), a network analysis was conducted, and the network structure was evaluated through regularized partial correlation models. To determine the centrality of depressive symptoms within each cohort, network parameters such as strength, betweenness, and closeness were examined. Additionally, to explore differences in the network structure between Alzheimer's disease and mild cognitive impairment groups, a network comparison test was performed. Results: In the analysis of centrality indices, "worthlessness" was identified as the most central symptom in the geriatric depression scale among patients with Alzheimer's disease, whereas "emptiness" was found to be the most central symptom in patients with mild cognitive impairment. Despite these differences in central symptoms, the comparative analysis showed no statistical difference in the overall network structure between Alzheimer's disease and mild cognitive impairment groups. Conclusions: Findings of this study could contribute to a better understanding of the manifestation of depressive symptoms in patients with cognitive impairment. These results are expected to aid in identifying and prioritizing core symptoms in these patients. Further research should be conducted to explore potential interventions tailored to these core symptoms in patients with Alzheimer's disease and mild cognitive impairment. Establishing core symptoms in those groups might have clinical importance in that appropriate treatment for neuropsychiatric symptoms in patients with cognitive impairment could help preclude progression to further impairment.

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.

Large-scale cross-ancestry genome-wide meta-analysis of serum urate.

Hyperuricemia is an essential causal risk factor for gout and is associated with cardiometabolic diseases. Given the limited contribution of East Asian ancestry to genome-wide association studies of serum urate, the genetic architecture of serum urate requires exploration. A large-scale cross-ancestry genome-wide association meta-analysis of 1,029,323 individuals and ancestry-specific meta-analysis identifies a total of 351 loci, including 17 previously unreported loci. The genetic architecture of serum urate control is similar between European and East Asian populations. A transcriptome-wide association study, enrichment analysis, and colocalization analysis in relevant tissues identify candidate serum urate-associated genes, including CTBP1, SKIV2L, and WWP2. A phenome-wide association study using polygenic risk scores identifies serum urate-correlated diseases including heart failure and hypertension. Mendelian randomization and mediation analyses show that serum urate-associated genes might have a causal relationship with serum urate-correlated diseases via mediation effects. This study elucidates our understanding of the genetic architecture of serum urate control.

Genome-wide association analyses using machine learning-based phenotyping reveal genetic architecture of occupational creativity and overlap with psychiatric disorders.

Creativity is known to be heritable and exhibits familial aggregation with psychiatric disorders; however, the complex nature of their relationship has not been well-established. In the present study, we demonstrate that using an expanded and validated machine learning (ML)-based phenotyping of occupational creativity (OC) can allow us to further understand the trait of creativity, which was previously difficult to define and study. We conducted the largest genome-wide association study (GWAS) on OC with 241,736 participants from the UK Biobank and identified 25 lead variants that have not yet been reported and three candidate causal genes that were previously associated with educational attainment and psychiatric disorders. We found extensive genetic overlap between OC and psychiatric disorders with mixed effect direction through various post-GWAS analyses, including the bivariate causal mixture model. In addition, we discovered a strongly genetic correlation between our original GWAS and the GWAS adjusted for education years (rg = 0.95). Our GWAS analysis via ML-based phenotyping contributes to the understanding of the genetic architecture of creativity, which may inform genetic discovery and genetic prediction in human cognition and psychiatric disorders.

Shared genetic architectures of educational attainment in East Asian and European populations.

Educational attainment (EduYears), a heritable trait often used as a proxy for cognitive ability, is associated with various health and social outcomes. Previous genome-wide association studies (GWASs) on EduYears have been focused on samples of European (EUR) genetic ancestries. Here we present the first large-scale GWAS of EduYears in people of East Asian (EAS) ancestry (n = 176,400) and conduct a cross-ancestry meta-analysis with EduYears GWAS in people of EUR ancestry (n = 766,345). EduYears showed a high genetic correlation and power-adjusted transferability ratio between EAS and EUR. We also found similar functional enrichment, gene expression enrichment and cross-trait genetic correlations between two populations. Cross-ancestry fine-mapping identified refined credible sets with a higher posterior inclusion probability than single population fine-mapping. Polygenic prediction analysis in four independent EAS and EUR cohorts demonstrated transferability between populations. Our study supports the need for further research on diverse ancestries to increase our understanding of the genetic basis of educational attainment.

Interpersonal sensitivity and childhood trauma in patients with major depressive disorder, bipolar I, and II disorder.

Childhood trauma and interpersonal sensitivity impact the development of mood disorders. In this study, we investigate the association between childhood trauma and interpersonal sensitivity in patients with mood disorders. A total 775 patients (major depressive disorder [MDD, n = 241], bipolar I disorder [BD I, n = 119], and bipolar II disorder [BD II, n = 415]) and 734 controls. For evaluation, we used the Childhood Trauma Questionnaire-Short Form (CTQ) and Interpersonal Sensitivity Measure (IPSM). We examined between-group differences for each subscale in the CTQ and IPSM. Patients with BD II had significantly higher IPSM total scores than patients with MDD, BD I, or controls. The CTQ total score was related to the IPSM total score in all participants and subgroups. Among the CTQ subscales, emotional abuse showed the highest correlation with the IPSM total score, while separation anxiety and fragile inner self showed higher positive correlations with CTQ than the other subscales of IPSM in all patient groups and the control group, respectively. The findings reveal that childhood trauma and interpersonal sensitivity are positively correlated among patients with MDD, BD I, and BD II, and that interpersonal sensitivity is higher in patients with BD II than those with BD I or MDD. Childhood trauma is associated with interpersonal sensitivity, and each trauma type has a different impact on mood disorders. We expect that this study will encourage future research on interpersonal sensitivity and childhood trauma in mood disorders to improve treatment approaches.

Short-term exposure to ambient air pollution and injuries due to external causes according to intentions and mechanisms.

Although injuries are a leading cause of death and affect the life expectancy of individuals who live with disabilities globally, the potential role of air pollution exposure on injuries due to external causes has received little scientific attention, especially compared with that given to the association of air pollution and non-external causes of morbidity and mortality. We investigated the association between emergency department visits for externally caused injuries and short-term exposure to major ambient air pollutants, with focus on the intentions and mechanisms of injuries. We identified 2,049,855 injured patients in Seoul, South Korea between 2008 and 2016 using the National Emergency Database. Daily short-term exposure to air pollution including particles <10 µm (PM10) and <2.5 µm (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) was estimated based on hourly concentrations. We employed a time-stratified case-crossover study design using a conditional Poisson regression model adjusted for meteorological variables, influenza epidemics, and holidays. Immediate exposure (lag 0) to most pollutants significantly increased the risk of total injuries (PM2.5, 0.42 %; NO2, 0.68 %; SO2, 1.05 %; CO, 0.57 %; O3, 1.86 % per interquartile range increment), and the associations differed according to the intention and mechanism of injury. Unintentional and assault injuries were significantly associated with air pollution exposure, whereas self-harm injuries showed no association. In mechanism-specific analyses, injuries caused by falls, blunt objects, penetration, traffic accidents, machinery, and slips were associated with specific air pollutants, even in the co-pollutant models. The associations were stronger in injured patients aged <15 years, and in males than in their counterparts. Our results suggest that short-term air pollution exposure might play a role in the risk of externally caused injuries and the association may differ depending on the intention and mechanism of injury, which provide important evidence for injury prevention and air quality strategies.

Network structure of symptomatology of adult attention-deficit hyperactivity disorder in patients with mood disorders.

Patients with mood disorders commonly manifest comorbid psychiatric disorders, including attention-deficit/hyperactivity disorder (ADHD). However, few studies have evaluated ADHD symptoms in this population. The current study aimed to explore the network structure of ADHD symptomology and identify central symptoms in patients with mood disorders. The Korean version of the Adult ADHD Self-Report Scale was used to assess the overall ADHD symptoms in 1,086 individuals diagnosed with mood disorders (major depressive disorder [n = 373], bipolar I disorder [n = 314], and bipolar II disorder [n = 399]). We used exploratory graph analysis to detect the number of communities, and the network structure was analyzed using regularized partial correlation models. We identified the central ADHD symptom using centrality indices. Network comparison tests were conducted with different subgroups of patients with mood disorders, including three mood diagnosis groups, between the patients who met the diagnostic criteria for ADHD [ADHD-suspected, n = 259] in their self-report and the others [ADHD-non-suspected, n = 827], and groups with high [n = 503] versus low [n = 252] levels of depressive state. The network analysis detected four communities: disorganization, agitation/restlessness, hyperactivity/impulsivity, and inattention. The centrality indices indicated that "feeling restless" was the core ADHD symptom. The result was replicated in the subgroup analyses within our clinically diverse population of mood disorders, encompassing three presentations: Patients with suspected ADHD, patients without suspected ADHD, and patients with a high depressive state. Our findings reveal that "feeling restless" is the central ADHD symptom. The treatment intervention for "feeling restless" may thus play a pivotal role in tackling ADHD symptoms in adult patients with mood disorders.

An atlas of associations between 14 micronutrients and 22 cancer outcomes: Mendelian randomization analyses.

BACKGROUND: Micronutrients, namely vitamins and minerals, are associated with cancer outcomes; however, their reported effects have been inconsistent across studies. We aimed to identify the causally estimated effects of micronutrients on cancer by applying the Mendelian randomization (MR) method, using single-nucleotide polymorphisms associated with micronutrient levels as instrumental variables. METHODS: We obtained instrumental variables of 14 genetically predicted micronutrient levels and applied two-sample MR to estimate their causal effects on 22 cancer outcomes from a meta-analysis of the UK Biobank (UKB) and FinnGen cohorts (overall cancer and 21 site-specific cancers, including breast, colorectal, lung, and prostate cancer), in addition to six major cancer outcomes and 20 cancer subset outcomes from cancer consortia. We used sensitivity MR methods, including weighted median, MR-Egger, and MR-PRESSO, to assess potential horizontal pleiotropy or heterogeneity. Genome-wide association summary statistical data of European descent were used for both exposure and outcome data, including up to 940,633 participants of European descent with 133,384 cancer cases. RESULTS: In total, 672 MR tests (14 micronutrients × 48 cancer outcomes) were performed. The following two associations met Bonferroni significance by the number of associations (P < 0.00016) in the UKB plus FinnGen cohorts: increased risk of breast cancer with magnesium levels (odds ratio [OR] = 1.281 per 1 standard deviation [SD] higher magnesium level, 95% confidence interval [CI] = 1.151 to 1.426, P < 0.0001) and increased risk of colorectal cancer with vitamin B12 level (OR = 1.22 per 1 SD higher vitamin B12 level, 95% CI = 1.107 to 1.345, P < 0.0001). These two associations remained significant in the analysis of the cancer consortia. No significant heterogeneity or horizontal pleiotropy was observed. Micronutrient levels were not associated with overall cancer risk. CONCLUSIONS: Our results may aid clinicians in deciding whether to regulate the intake of certain micronutrients, particularly in high-risk groups without nutritional deficiencies, and may help in the design of future clinical trials.

Impact of dementia and drug compliance on patients with acute myocardial infarction.

BACKGROUND: In South Korea, the number of people with dementia is rising at a worrisome rate, and many of them also have acute myocardial infarction (AMI), a disease with a high mortality rate. HYPOTHESIS: We speculated that dementia and drug compliance have significant impact on the mortality of patients with AMI. METHODS: The study derived data from the National Health Insurance Service-Senior for a retrospective cohort study. The total number of patients diagnosed with AMI for the first time between 2007 and 2013 was 16 835, among whom 2021 had dementia. Medication possession ratio (MPR) was used to assess medication adherence. RESULTS: AMI patients with dementia had unfavorable baseline characteristics; they had significantly higher risk of all-cause mortality (hazard ratio [HR]: 2.49; 95% confidence interval [CI]: 2.34-2.66; p < .001) and lower MPR (aspirin: 21.9% vs. 42.8%; p < .001). AMI patients were stratified by presence of dementia and medication adherence, and the survival rate was the highest among those with no dementia and good adherence, followed by those with no dementia and poor adherence, those with dementia and good adherence, and those with dementia and poor adherence. The multivariable analysis revealed that dementia (HR: 1.64; 95% CI: 1.53-1.75; p < .001) and poor adherence to medication (HR: 1.60; 95% CI: 1.49-1.71; p < .001) had a significant association with all-cause mortality in AMI patients. CONCLUSIONS: AMI patients with dementia have a higher mortality rate. Their prognosis is negatively affected by their poorer medication adherence than patients without dementia.

Association between cardio-cerebrovascular disease and systemic antipsoriatic therapy in psoriasis patients using population-based data: A nested case-control study.

The effect of antipsoriatic therapy on cardio-cerebrovascular disease (CCVD) is not well described. Thus, we performed a population-based nested case-control study to investigate the effect of systemic antipsoriatic therapy on CCVD in psoriasis patients. Using nationwide cohort data from the Korean National Health Insurance Claims database, newly diagnosed psoriasis patients were identified. Among the enrolled participants, postenrollment development of CCVD events (ischemic heart disease, myocardial infarction, cerebral infarction, and cerebral hemorrhage) was investigated. To evaluate the effect of systemic antipsoriatic therapy on CCVD risk, we calculated the proportion of the treatment period with systemic antipsoriatic therapy during the study period (PTP [%]: the sum of all systemic antipsoriatic therapy durations divided by total observation period). Among 251 813 participants, 6262 experienced CCVD events during the study period (CCVD group). Controls included 245 551 patients without CCVD history during the study period (non-CCVD group). The non-CCVD group had greater PTP than the CCVD group (CCVD 2.12 ± 7.92, non-CCVD 2.64 ± 9.64; P < 0.001). In multiple logistic regression analysis, PTP was inversely associated with the CCVD risk after adjusting for age, sex, diabetes, hypertension, and dyslipidemia. A 10% increase in PTP reduced CCVD risk by 0.96 (95% confidence interval 0.93 to 0.99). Reduced CCVD risk was robust for both conventional antipsoriatic therapy and biologics. Our study found that systemic antipsoriatic therapy use was inversely associated with CCVD risk in psoriasis patients. These findings suggested that systemic antipsoriatic therapy could reduce CCVD development in patients with psoriasis.

Validation of the Short Form of the Mood Instability Questionnaire-Trait (MIQ-T-SF) in the Korean General Population.

OBJECTIVE: Mood instability (MI) is a clinically significant trait associated with psychiatric disorders. However, there are no concise measurements to evaluate MI. The initial Mood Instability Questionnaire-Trait (MIQ-T) was developed to fill this gap. The current study aimed to create a short form of MIQ-T (MIQ-T-SF) that measures MI with high validity and reliability in the Korean general population. METHODS: Of the 59 items in the MIQ-T, 17 items were chosen for the MIQ-T-SF following the factor analysis process. In total, 540 participants completed the MIQ-T-SF. Cronbach's alpha and McDonald's omega were used to evaluate reliability. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to determine construct validity. Concurrent validity was confirmed via comparisons with Personality Assessment Inventory-Borderline Features Scale. Measurement invariance across gender and age groups was confirmed before analyzing differences in scores using Kruskal-Wallis test. RESULTS: The MIQ-T-SF displayed expected correlations and high internal consistency (α=0.71-0.90, Ωt=0.72-0.92). Using EFA and CFA, a five-factor structure was confirmed. Measurement invariance was supported, and gender differences were observed. CONCLUSION: The MIQ-T-SF is an accurate and reliable method to detect MI in the Korean general population. The study's results offer new perspectives for future studies on MI.

Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders.

Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.