Koichi Matsuda

The paper introduces the Proteomic Sex Index (PSI), a continuous measure of plasma proteome alignment with chromosomal sex, showing its association with health and disease traits.

The paper develops a framework to quantify predictive uncertainty in biological age estimates, revealing hidden dimensions of aging and improving risk interpretation.

The paper establishes a global consortium to discover rare genetic associations by integrating data from multiple biobanks, identifying 514 gene-trait associations, many detectable only through cross-ancestry meta-analysis.

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 identifies a genetic factor influencing BCAA metabolism independent of traditional risk factors and links it to T2D and CAD.

The paper shows TET2-mutant clonal hematopoiesis reduces cancer metastasis by preventing T-cell exhaustion through DNA methylation changes.

This study identifies genetic associations with metabolic biomarkers across ancestries and shows their predictive value for disease risk.

This study identifies 118 new genetic loci associated with Alzheimer's disease across diverse ancestries and discovers 48 novel risk loci, including those enriched in neuronal cell types.

The paper develops and validates multi-ancestry polygenic risk scores for LUAD in East Asian never-smokers, showing improved risk prediction compared to East Asian-only models.

The paper evaluates genotype imputation accuracy in multi-ancestry reference panels and finds that the Rsq metric overestimates dosage r2 due to systematic bias in imputation quality.

The paper introduces scLinaX, a method to quantify X chromosome inactivation escape using scRNA-seq, revealing heterogeneity across cell types and tissues.

This study improves polygenic risk scores for colorectal cancer by combining Asian and European ancestry data, enhancing risk prediction across diverse racial and ethnic groups.

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.

This paper introduces PolyPred and PolyPred+ to improve cross-population polygenic risk score accuracy by addressing LD, MAF, and causal effect size differences using fine-mapping and non-European training data.

This study conducts a trans-ancestry GWAS of rheumatoid arthritis, identifying 124 loci, 34 novel, and shows improved polygenic risk score performance across populations.

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.

Fine-mapping 148 complex traits in three biobanks with combined n = 811,261 yields 4,518 causal variant-trait pairs, 285 of them repeating in more than one population.

The paper uses supervised learning to fine-map cis-eQTLs, identifying 20,913 additional putative causal eQTLs and 310 candidate genes.

DEEP*HLA improves HLA allelic imputation for low-frequency alleles, enabling trans-ethnic MHC fine-mapping of type 1 diabetes with high accuracy.

This study identifies 113 genomic loci for SLE in East Asians, including 46 novel loci, and highlights non-immune cell-related biological mechanisms.

This study identifies 5,552 blood-cell trait-variant associations across 746,667 individuals from 5 global populations, including 71 novel loci and ancestry-specific variants not found in European ancestry populations.

This study identifies 5,106 new genetic variants associated with blood cell traits using large-scale GWAS, highlighting the polygenic and monogenic basis of hematopoiesis.

The paper analyzes HHV-6 integration in human genomes, identifies co-evolution with chr22q, and reports evidence of in vivo excision and reactivation.

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.

This study uses polygenic risk scores from three biobanks to show that genetic susceptibility to traits like high blood pressure and obesity is associated with shorter lifespan.

The paper screens 12,503 Japanese CRC patients and 23,705 controls for germline variants in 27 cancer genes, finding 3.3% of patients have pathogenic variants linked to CRC risk.

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.