Mendelian randomization (MR) leverages genetic information to examine the causal
relationship between phenotypes allowing for the presence of unmeasured confounders …

Observational epidemiologic studies are prone to confounding, measurement error, and
reverse causation, undermining robust causal inference. Mendelian randomization (MR) …

Compared with linear mixed model-based genome-wide association (GWA) methods,
generalized linear mixed model (GLMM)-based methods have better statistical properties …

Genome-wide association studies have uncovered thousands of common variants
associated with human disease, but the contribution of rare variants to common disease …

Numerous observational studies have attempted to identify risk factors for infection with
SARS-CoV-2 and COVID-19 disease outcomes. Studies have used datasets sampled from …

Genome-wide association studies have successfully discovered thousands of common
variants associated with human diseases and traits, but the landscape of rare variations in …

Cardiometabolic diseases are an increasing global health burden. While socioeconomic,
environmental, behavioural, and genetic risk factors have been identified, a better …

Results from genome-wide association studies (GWAS) can be used to infer causal
relationships between phenotypes, using a strategy known as 2-sample Mendelian …

The state of somatic energy stores in metazoans is communicated to the brain, which
regulates key aspects of behaviour, growth, nutrient partitioning and development. The …

Incretin-based therapies are highly successful in combatting obesity and type 2 diabetes.
Yet both activation and inhibition of the glucose-dependent insulinotropic polypeptide (GIP) …