Publications by authors named "M Smolka"
Background And Aim: Cannabis use disorder (CUD) is strongly influenced by genetic factors; however the mechanisms underpinning this association are not well understood. This study investigated whether a polygenic risk score (PRS) based on a genome-wide association study for CUD in adults predicts cannabis use in adolescents and whether the association can be explained by inter-individual variation in structural properties of brain white matter or risk-taking behaviors.
Design And Setting: Longitudinal and cross-sectional analyses using data from the IMAGEN cohort, a European longitudinal study integrating genetic, neuroimaging and behavioral measures.
Understanding kinase action requires precise quantitative measurements of their activity . In addition, the ability to capture spatial information of kinase activity is crucial to deconvolute complex signaling networks, interrogate multifaceted kinase actions, and assess drug effects or genetic perturbations. Here we developed a proteomic kinase activity sensor platform (ProKAS) for the analysis of kinase signaling using mass spectrometry.
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- The study utilized machine learning models to identify reliable diagnostic markers for eating disorders, major depressive disorder, and alcohol use disorder, targeting young adults aged 18-25.
- The classification models showed high accuracy rates (AUC-ROC ranging from 0.80 to 0.92) even without considering body mass index and highlighted shared predictors like neuroticism and hopelessness.
- Additionally, the models were moderately successful in predicting future symptoms related to eating disorders, depression, and alcohol use in a longitudinal sample of adolescents, indicating the potential for improved diagnosis and risk assessment in mental health.
Introduction: A growing literature has shown that exposure to adverse life events during childhood or adolescence is associated with the presence of psychotic-like experiences (PLEs), which is in turn associated with the risk of psychotic outcomes. Ruminative thinking, i.e.
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- This study uses multi-modal MRI to investigate neurobiological differences between anorexia nervosa (AN) and bulimia nervosa (BN), revealing structural and functional brain changes linked to these eating disorders.
- Key findings include reduced gray matter volume in specific brain regions (like the orbitofrontal cortex) and decreased cortical thickness, particularly in anorexia patients, which are associated with impulsivity and cognitive restraint regarding eating behaviors.
- The results suggest that these brain changes affect reward processing and contribute to the persistence of eating disorder symptoms, highlighting potential targets for future treatment interventions.