Biomedical subjects

Cheng-Ta Yang

Publications and source records attributed to Cheng-Ta Yang.

2 recordsLinked to original sources

PubMed2025

Relationships between childhood adversity, resilience, and inflammatory profiles in Taiwanese young adults.

Psychological resilience is the capacity to withstand and bounce back from stressors, trauma, and negative life events, such as childhood adverse experiences (ACEs). Yet, little is known about the biological mechanisms by which resilience mitigates the psychological effects of ACEs. We aimed to identify differentially expressed proteins (DEPs) that reflect the combined effects of early life stress and psychological resilience by using an inflammatory proteomics panel. Three different resilience and ACE questionnaires were employed to classify participants into four groups according to high vs. low levels of resilience and ACEs. Forty-five age-matched and sex-matched participants were selected for proteomics profiling with Olink's 92-protein inflammatory panel. Of these, only 32 passed quality control filtering for analysis. Results showed that CD274 emerged as a protein hub in resilient profiles, while CXCL5 was central to ACE-related profiles. Network co-expression analysis revealed group-specific protein rewiring, suggesting dysregulated inflammation in individuals with high ACE. In contrast, high-resilience profiles showed stronger immune checkpoint co-expression, indicating more effective inflammatory resolution as a key trait of resilience. These findings suggest that resilience maintains an adaptive immune network architecture that may be leveraged to promote resilience after early adversity.

Humans↗

PubMed2025

MicroRNAs signatures in small extracellular vesicles for psychological resilience in young adults using machine learning.

AIMS: Psychological resilience refers to an individual's capacity to adapt to adverse events. MicroRNAs (miRNAs) play a crucial role in regulating post-transcriptional processes, while small extracellular vesicles (sEVs) act as transport vehicles. This study aimed to employ genome-wide profiling to identify and validate differences in the expression of resilience-associated sEV-miRNAs between low resilience (LR) and high resilience (HR) in young adults. METHODS: Eighty participants were divided into LR or HR based on the Connor - Davidson Resilience Scale (CD-RISC). The expression levels of the target sEV-miRNAs in LR and HR were compared and analyzed. RESULTS: Expression analyses demonstrated significant differences in let-7b, miR-151b, miR-335, and miR-193a between LR and HR (p < 0.01), with let-7b showing the highest discriminative ability. The AUC values for each sEV-miRNA ranged from 0.74 to 0.94, based on logistic regression and three machine learning models: random forest, support vector machine, and eXtreme gradient boosting. Based on leave-one-out cross-validation in different models, the combined four sEV-miRNAs demonstrated strong performance for detecting LR (AUC = 0.87-0.90). Sex-specific differences were also observed, with female participants showing more pronounced resilience signatures in targeted sEV-miRNAs. CONCLUSIONS: These findings suggest that sEV-miRNAs hold potential as biomarkers for psychological resilience in young adults.

Humans↗