Adipose tissue eQTL meta-analysis highlights the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits.

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. In the present study, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34,774 conditionally distinct expression quantitative trait locus (eQTL) signals at 18,476 genes. Over half of eQTL genes exhibited at least two eQTL signals.

Metabolomics-Based Machine Learning for Predicting Mortality: Unveiling Multisystem Impacts on Health.

Reliable predictors of long-term all-cause mortality are needed for middle-aged and older populations. Previous metabolomics mortality studies have limitations: a low number of participants and metabolites measured, measurements mainly using nuclear magnetic spectroscopy, and the use only of conventional statistical methods. To overcome these challenges, we applied liquid chromatography-tandem mass spectrometry and measured >1000 metabolites in the METSIM study including 10,197 men.

Increasing student well-being through a positive psychology intervention: changes in salivary cortisol, depression, psychological well-being, and hope.

The significant prevalence of mental health problems among children and adolescents is a major concern worldwide. The current study evaluates the impact of a year-long, school-based intervention, Flourishing Students, on adolescents' salivary cortisol levels, depressive symptoms, psychological well-being, and hope. Utilizing a cluster randomized design with intervention and control classes, 72 students engaged in 32 well-being lessons during academic year 2016-2017, whereas 68 students followed their standard curriculum.