Background and Objectives: Genomic studies have identified several SNP loci associated with schizophrenia in East Asian populations. Environmental factors, particularly urbanization, play a significant role in schizophrenia development. This study aimed to identify schizophrenia susceptibility loci and characterize their biological functions and molecular pathways in Taiwanese urban Han individuals. Materials and Methods: Participants with schizophrenia were recruited from the Taiwan Precision Medicine Initiative at Tri-Service General Hospital. Genotype–phenotype association analysis was performed, with significant variants annotated and analyzed for functional relevance. Results: A total of 137 schizophrenia patients and 26,129 controls were enrolled. Ten significant variants (p < 1 × 10⁻⁵) and 15 expressed genes were identified, including rs1010840 (SOWAHC and RGPD6), rs11083963 (TRPM4), rs11619878 (LINC00355 and LINC01052), rs117010638 (AGBL1 and MIR548AP), rs1170702 (LINC01680 and LINC01720), rs12028521 (KAZN and PRDM2), rs12859097 (DMD), rs1556812 (ATP11A), rs78144262 (LINC00977), and rs9997349 (ENPEP). These variants and associated genes are involved in immune response, blood pressure regulation, muscle function, and the cytoskeleton. Conclusions: Identified variants and associated genes suggest a potential genetic predisposition to schizophrenia in the Taiwanese urban Han population, highlighting the importance of potential comorbidities, considering population-specific genetic and environmental interactions.

Wan-Ting Chen, Yi-Wei Yeh, Shin-Chang Kuo, Yi-Chih Shiao, Chih-Chung Huang, Yi-Guang Wang, Chun-Yen Chen. Clin Psychopharmacol Neurosci 2025;23:161-5. https://doi.org/10.9758/cpn.24.1193

Objective This study develops an eXtreme Gradient Boosting (XGBoost) regression model to identify key predictors of mortality and 5-year survival in dementia patients, highlighting the role of comorbidities. The findings highlight key risk factors that may facilitate targeted adjustments in clinical care and resource allocation for high-risk patients.Methods We used Taiwan’s National Health Insurance dataset to develop and validate an XGBoost model predicting 5-year survival in dementia patients aged 65 years or older. The cohort (n=6,556) was split into 80% for training, 10% for validation, and 10% for testing. A total of 24 variables, including comorbidities and demographic factors, were selected as predictors. Hyperparameters were tuned to optimize performance, with a learning rate of 0.1, 1,000 estimators, and a maximum depth of 10. Regularization techniques were applied to prevent overfitting.Results The XGBoost model achieved 81.86% accuracy in predicting 5-year survival, with a receiver operating characteristic area under the curve of 0.81 and a log loss of 0.61. Of the 37 initial features, 24 were included, and the top 10 predictors were nasogastric tube insertion, chronic kidney disease, cancer, lung disease, urinary tract infection, fracture, peripheral vascular disease, antidepressant use, hypertension, and upper gastrointestinal issues.Conclusion The XGBoost model effectively predicts 5-year survival in dementia patients, identifying key predictors that can guide targeted care, preventive strategies, and healthcare resource planning.

Background and Objectives: In recent years, bipolar disorder (BD), a multifaceted mood disorder marked by severe episodic mood fluctuations, has been shown to have an impact on disability-adjusted life years (DALYs). The increasing prevalence of BD highlights the need for better diagnostic tools, particularly those involving genetic insights. Genetic association studies can play a crucial role in identifying variations linked to BD, shedding light on its genetic underpinnings and potential therapeutic targets. This study aimed to identify novel genetic variants associated with BD in the Taiwanese Han population and to elucidate their potential roles in disease pathogenesis. Materials and Methods: Genotyping was conducted using the Taiwan Precision Medicine Array (TPM Array) on 128 BD patients and 26,122 control subjects. Following quality control, 280,177 single nucleotide polymorphisms (SNPs) were analyzed via chi-square tests, and linkage disequilibrium (LD) analyses were employed to examine the associations among key SNPs. Results: Eleven SNPs reached significance (p < 10⁻⁵), with the variant rs11156606 in the ABCD1 gene—implicated in fatty acid metabolism—emerging as a prominent finding. LD analysis revealed that rs11156606 is strongly linked with rs73640819, located in the 3′ untranslated region, suggesting a regulatory role in gene expression. Additionally, rs3829533 in the MTHFSD gene was found to be in strong LD with the missense variants rs3751800 and rs3751801, indicating potential alterations in protein function. Conclusion: These findings enhance the genetic understanding of BD within a Taiwanese cohort by identifying novel risk-associated variants and support the potential for using these markers in early diagnosis and targeted therapeutic strategies.

In recent years, bipolar disorder (BD), a multifaceted mood disorder marked by severe episodic mood fluctuations, has been shown to have an impact on disability-adjusted life-years (DALYs). The increasing prevalence of BD highlights the need for better di-agnostic tools , particularly those involving genetic insights. Genetic association studies can play a crucial role in identifying variations linked to BD, shedding light on its ge-netic underpinnings and potential therapeutic targets. Our research utilized data from the Taiwan Precision Medicine Array (TPM Array), aiming to identify significant single nucleotide polymorphisms (SNPs) associated with BD. Notably, we identified the var-iant rs11156606 in the ABCD1 gene, which plays a role in fatty acid metabolism—a process potentially connected to BD pathophysiology. Subsequent linkage disequilib-rium (LD) analysis of rs11156606 revealed a strongly associated variant, rs73640819, located within the ABCD1 3’ untranslated region (3’UTR), suggesting a regulatory role on ABCD1 RNA functionality. Additionally, our findings indicate that the variant rs3829533 is in strong LD with rs3751800 and rs3751801, which significantly affect the coding sequence of the MTHFSD gene. These findings enhance the genetic under-standing of BD in the Taiwanese Han population and highlight the value of genetic research in advancing our knowledge of bipolar disorder.