Indoor Radon Survey in 31 Provincial Capital Cities and Estimation of Lung Cancer Risk in Urban Areas of China.

Objective: We aimed to analyze the current indoor radon level and estimate the population risk of radon-induced lung cancer in urban areas of China.

Methods: Using the passive monitoring method, a new survey on indoor radon concentrations was conducted in 2,875 dwellings across 31 provincial capital cities in Chinese mainland from 2018 to 2023. The attributable risk of lung cancer induced by indoor radon exposure was estimated based on the risk assessment model.

Power analysis of transcriptome-wide association study: Implications for practical protocol choice.

The transcriptome-wide association study (TWAS) has emerged as one of several promising techniques for integrating multi-scale 'omics' data into traditional genome-wide association studies (GWAS). Unlike GWAS, which associates phenotypic variance directly with genetic variants, TWAS uses a reference dataset to train a predictive model for gene expressions, which allows it to associate phenotype with variants through the mediating effect of expressions. Although effective, this core innovation of TWAS is poorly understood, since the predictive accuracy of the genotype-expression model is generally low and further bounded by expression heritability.

kTWAS: integrating kernel machine with transcriptome-wide association studies improves statistical power and reveals novel genes.

The power of genotype-phenotype association mapping studies increases greatly when contributions from multiple variants in a focal region are meaningfully aggregated. Currently, there are two popular categories of variant aggregation methods. Transcriptome-wide association studies (TWAS) represent a set of emerging methods that select variants based on their effect on gene expressions, providing pretrained linear combinations of variants for downstream association mapping.