Genome-wide association studies (GWAS) have revolutionized our understanding of the
genetic architecture of complex traits and diseases. GWAS summary statistics have become …

Rationale: Gastroesophageal reflux disease (GERD) is commonly associated with atopic
disorders, but cause–effect relationships remain unclear. Objectives: We applied Mendelian …

Mendelian randomization (MR) is an instrumental variable (IV) method using genetic
variants such as single nucleotide polymorphisms (SNPs) as IVs to disentangle the causal …

Mendelian randomization (MR) has been increasingly applied for causal inference with
observational data by using genetic variants as instrumental variables (IVs). However, the …

Purpose Animal models suggest omega-3 polyunsaturated fatty acids (PUFAs) may protect
against myopia by modulating choroidal blood perfusion, but clinical evidence is scarce and …

Causal discovery is a powerful tool to disclose underlying structures by analyzing purely
observational data. Genetic variants can provide useful complementary information for …

We propose structural equation models (SEMs) as a general framework to infer causal
networks for metabolites and other complex traits. Traditionally SEMs are used only for …

We consider the challenging problem of estimating causal effects from purely observational
data in the bi-directional Mendelian randomization (MR), where some invalid instruments, as …

Learning causal relationships between pairs of complex traits from observational studies is
of great interest across various scientific domains. However, most existing methods assume …

Mendelian randomization (MR) has been increasingly applied for causal inference among
traits, eg between potential risk factors and diseases, with observational data by using …