Kaoru Ito

This study identifies organ-specific endothelial regulatory programs in aging and metabolic overload, revealing how vascular immune remodeling is coupled to local inflammatory restraint.

This paper develops a polygenic score for metabolic syndrome in early adulthood and shows it predicts cardiometabolic risk across the life course in Asian populations.

The paper investigates why the 9p21.3 CAD risk locus fails to replicate in African ancestry cohorts, finding ancestry-specific LD and haplotype diversity explain the lack of association.

This study identifies 135 genomic loci associated with venous thromboembolism risk through cross-ancestry GWAS and provides insights into biological pathways and potential therapeutic targets.

The paper uses deep learning and genome-wide association studies to identify genetic loci associated with right heart structure and function in 40,000 individuals.

The paper develops a tool to genotype mobile element variants (MEVs) using short-read data and identifies population-specific MEs linked to disease and gene regulation.

Cross-population GWAS of 220 phenotypes in BioBank Japan, UK Biobank, and FinnGen (n=628,000) identifies 5,343 previously unreported loci and decomposes summary statistics into latent genetic components for disease subtyping.

This paper identifies new genetic loci for atrial fibrillation through a trans-ancestry meta-analysis and develops a polygenic risk score linked to cardioembolic risk.

A coronary artery disease GWAS of 181,522 cases among 1,165,690 participants yields 241 associations (54 new); an eight-predictor consensus nominates 185 candidate causal genes, 94 with ≥3 predictors.

This paper develops a deep learning model to estimate patient age and sex from chest X-rays, finding that CXR age correlates with cardiovascular aging and disease outcomes.

A large-scale GWAS in 212,453 Japanese individuals identified 45 novel susceptibility loci for 22 diseases, highlighting the importance of non-European population studies.

This study identifies three new CAD loci through transethnic GWAS and highlights population-specific genetic differences between Japanese and European populations.

The paper develops MENTR, a machine learning framework to predict cell-type-specific ncRNA transcription from genome sequence, identifying causal variants and ncRNAs associated with complex traits.

This study identifies novel genetic loci for coronary artery disease in Japanese and transethnic populations and develops a polygenic risk score that outperforms population-specific scores.