Yingqing Feng

The study design is illustrated in Fig. 1. First, we conducted a two-sample MR analysis to identify drug target genes utilizing publicly available eQTL datasets in blood and brain as genetic instruments (IVs) and GWAS summary statistics of SBP as the outcome. Second, we employed a two-sample MR analysis to estimate the relationship between each drug target gene expression and the risk of AD.

Abstract : Background: Previous studies have demonstrated a J-shaped association of alcohol consumption with all-cause mortality and hypertension, but the majority of these studies focus on a single measurement of alcohol intake and were conducted in a Western population. Whether long-term trajectories of alcohol consumption are associated with all-cause mortality, hypertension, and a change in blood pressure remains to be elucidated.

Abstract Machine learning (ML) is a branch of artificial intelligence that combines computer science, statistics, and decision theory to learn complex patterns from voluminous data. In the last decade, accumulating evidence has shown the utility of ML for prediction, diagnosis, and classification of hypertension and heart failure (HF). In addition, ML-enabled image analysis has potential value in assessing cardiac structure and function in an accurate, scalable, and efficient way.