Research Project
Doctoral Training Project:
See this page for more details:
Anuj Goel
MBBS, MSc
Associate Professor of Cardiovascular Genetics
My research focuses on advancing the understanding of cardiovascular disease through large-scale human genetics and bioinformatics. I apply genome-wide association studies and meta-analyses to identify genetic loci associated with complex cardiovascular traits, with particular interests in coronary artery disease and hypertrophic cardiomyopathy.
A key aim of my work is to move beyond association signals to identify causal variants and underlying biological mechanisms, integrating computational approaches with epigenetic and multi-omic data. I also use whole-genome sequencing and rare variant analyses to better define disease pathways and improve risk prediction.
I also manage the PROCARDIS study (https://www.well.ox.ac.uk/procardis), a large-scale resource for investigating the genetic basis of coronary artery disease. In parallel, I am currently co-leading the new discovery efforts within the CARDIOGRAMplusC4D consortium (http://www.cardiogramplusc4d.org), driving large-scale collaborative analyses to identify novel genetic determinants of coronary artery disease. I am further involved in collaborative genetic discovery efforts in hypertrophic cardiomyopathy, aiming to refine disease biology and improve clinical translation.
By combining large-scale datasets with advanced analytical methods, my goal is to translate genetic discoveries into mechanistic insight and contribute to more precise strategies for the prevention and treatment of cardiovascular disease.
Key publications
Manhattan++: displaying genome-wide association summary statistics with multiple annotation layers.
Journal article
Grace C. et al, (2019), BMC Bioinformatics, 20
A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease.
Journal article
Nikpay M. et al, (2015), Nat Genet, 47, 1121 - 1130
Recent publications
Discovery of gene-alcohol interaction loci influencing blood pressure in 1.1 million individuals from multiple populations.
Preprint
Feitosa M. et al, (2026)
Leveraging the shared and opposing genetic mechanisms in the heritable cardiomyopathies.
Preprint
Kramarenko DR. et al, (2026)
Evaluation of polygenic scores for hypertrophic cardiomyopathy in the general population and across clinical settings.
Journal article
Zheng SL. et al, (2025), Nat Genet, 57, 563 - 571
