Amy M. Mason

Relaxing parametric assumptions for non-linear Mendelian randomization using a doubly-ranked stratification method

This paper introduces a doubly-ranked stratification method for non-linear Mendelian randomization to avoid parametric assumptions, showing it provides unbiased estimates even with non-linear or heterogeneous instrument-exposure relationships.

Software Application Profile: SUMnlmr, an R package that facilitates flexible and reproducible non-linear Mendelian randomisation analyses

SUMnlmr enables non-linear Mendelian randomisation analyses using summarised data, improving flexibility and reproducibility in studies without individual-level data.

ACE inhibition and cardiometabolic risk factors, lung ACE2 and TMPRSS2 gene expression, and plasma ACE2 levels: a Mendelian randomization study

This study uses Mendelian randomization to examine if ACE inhibitors or cardiometabolic risk factors affect lung ACE2 and TMPRSS2 expression or plasma ACE2 levels, finding no overall association.

MR-Clust: Clustering of genetic variants in Mendelian randomization with similar causal estimates

MR-Clust clusters genetic variants with similar causal estimates in Mendelian randomization to identify distinct causal mechanisms.

Elucidating mechanisms of genetic cross-disease associations: an integrative approach implicates protein C as a causal pathway in arterial and venous diseases

The paper identifies a genetic variant in PROCR that influences protein C and factor VII levels, linking it to both reduced coronary artery disease risk and increased venous thromboembolism risk through opposing inflammatory and thrombotic mechanisms.

Body size and composition and site-specific cancers in UK Biobank: a Mendelian randomisation study

This study uses Mendelian randomisation to examine the causal effects of BMI, body fat composition, and height on cancer risk, finding limited evidence for BMI's role but associations for FMI and height.

Shared mechanisms between coronary heart disease and depression: findings from a large UK general population-based cohort

This study investigates shared mechanisms between coronary heart disease and depression using UK Biobank data, finding that environmental factors and specific biomarkers like IL-6, CRP, and triglycerides are likely causal for depression.