Walter R T Witschey

This paper uses GWAS and mediation analysis on CT-derived phenotypes to show genetic variants influence disease through intermediate imaging traits.

The paper maps phenotypic and genetic links between plasma proteins and organ imaging traits using UK Biobank data, identifying associations and causal links across multiple organs.

The paper identifies rare protein-coding variants associated with multi-organ MRI traits using exome-wide association analysis in the UK Biobank.

This study uses multimodal imaging and transcriptomics to show increased reactive oxygen species activity in myocardial tissue and systemic organs after myocardial infarction, with associated gene expression changes.

The paper investigates organ-specific and modality-specific aging clocks using proteomic and imaging data, revealing distinct biological processes and their roles in age-related diseases.

The paper develops a deep learning method to quantify 3D aortic geometry in large biobanks, expanding available phenotypes for studying aortic degeneration.

This study measures NAD+ T1 and T2 relaxation times in human brain using 7 T 1H MRS and quantifies the uncertainty propagation in NAD+ concentration.

The paper uses reduced order modeling of aortic hemodynamics from CT scans to identify clinically relevant associations with vascular diseases in a biobank.

This study conducts a trans-ancestry GWAS using chronic ALT elevation as a proxy for NAFLD, identifies 77 significant loci, and validates 17 SNPs with histology and imaging data, revealing genetic links to metabolic and inflammatory traits.