Personality traits as mediators in the association between SIRT1 rs12415800 polymorphism and depressive symptoms among Chinese college students.

Background: Previous research has linked polymorphisms in the SIRT1 gene to depressive symptoms, particularly in Chinese individuals. However, it is not clear how personality traits may contribute to this association. Methods: To explore the potential mediating effect of personality traits, we utilized a mediation model to examine the relationship between the SIRT1 rs12415800 polymorphism and depressive symptoms in 787 Chinese college students. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression (CES-D) scale, while personality traits were measured using the Big Five Inventory (BFI). Results: Our analysis indicated a significant association between the SIRT1 rs12415800 polymorphism and depressive symptoms, with this relationship partially mediated by the personality traits of neuroticism and conscientiousness. Specifically, individuals who were heterozygous for the rs12415800 polymorphism and had higher levels of conscientiousness were less likely to experience depressive symptoms. Conversely, those who were homozygous for the rs12415800 polymorphism and had higher levels of neuroticism were more likely to experience depressive symptoms. Conclusion: Our results suggest that personality traits, particularly neuroticism and conscientiousness, may play a critical role in the association between the SIRT1 rs12415800 polymorphism and depressive symptoms among Chinese college students. These findings highlight the importance of considering both genetic factors and personality traits when exploring the etiology of depressive symptoms in this population.

College students' screening early warning factors in identification of suicide risk.

This study aimed to explore the main influencing factors of suicide risk among Chinese students and establish an early warning model to provide interventions for high-risk students. We conducted surveys of students in their first and third years from a cohort study at Jining Medical College. Logistic regression models were used to screen the early warning factors, and four machine learning models were used to establish early warning models. There were 8 factors related to suicide risk that were eventually obtained through screening, including age, having a rough father, and CES-D, OHQ, ASLEC-4, BFI-Neuroticism, BFI-Openness, and MMC-AF-C scores. A random forest model with SMOTE was adopted, and it verified that these 8 early warning signs, for suicide risk can effectively predict suicide risk within 2 years with an AUC score of 0.947. Among the factors, we constructed a model that indicated that different personality traits affected suicide risk by different paths. Moreover, the factors obtained by screening can be used to identify college students in the same year with a high risk of suicide, with an AUC score that reached 0.953. Based on this study, we suggested some interventions to prevent students going high suicide risk.

The host genetics affects gut microbiome diversity in Chinese depressed patients.

The gut microbiome and host genetics are both associated with major depressive disorder (MDD); however, the molecular mechanisms among the associations are poorly understood, especially in the Asian, Chinese group. Our study applied linear discriminant analysis (LDA) effect size (LEfSe) and genome-wide association analysis in the cohort with both gut sequencing data and genomics data. We reported the different gut microbiota characteristics between MDD and control groups in the Chinese group and further constructed the association between host genetics and the gut microbiome. Actinobacteria and Pseudomonades were found more in the MDD group. We found significant differences in the ACE and Chao indexes of alpha diversity while no discrepancy in beta diversity. We found three associations between host genetics with microbiome features: beta diversity and rs6108 (p = 8.65 × 10-9), Actinobacteria and rs77379751 (p = 8.56 × 10-9), and PWY-5913 and rs1775633082 (p = 4.54 × 10-8). A species of the Romboutsia genus was co-associated with the species of Ruminococcus gnavus in an internetwork through four genes: METTL8, ITGB2, OTULIN, and PROSER3, with a strict threshold (p < 5 × 10-4). Furthermore, our findings suggested that the gut microbiome diversity might affect microRNA expression in the brain and influenced SERPINA5 and other spatially close genes afterward. These findings suggest new linkages between depression and gut microbiome in Asian, Chinese people, which might be mediated by genes and microRNA regulation in space distance.