Satoshi Koyama

Quantifying the contribution of genetic variation to healthcare expenditure across diverse healthcare systems

This study identifies genetic variants associated with healthcare costs across multiple systems, finding polygenic influences and large effects from specific loss-of-function variants.

Integrating multi-ancestry common and rare variant mapping accelerates therapeutic target discovery

This study integrates common and rare variant mapping across diverse populations to identify novel therapeutic targets, finding NRG4 as a candidate for preserving kidney function.

Long-term Penetrance of Disease Variants in Genes Prioritized for Genomic Newborn Screening: Evidence from Adult Biobanks

The paper estimates penetrance of disease variants in genes prioritized for genomic newborn screening using adult biobank data, finding higher penetrance than ICD codes suggest.

Exome wide association study for blood lipids in 1,158,017 individuals from diverse populations

The paper identifies 800 exome-wide significant rare coding variants associated with blood lipids in over a million diverse individuals, including 130 driven by non-European-like populations.

The Biobank Rare Variant consortium powers the discovery of rare genetic associations through global collaboration

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.

Genetic architecture of high-dimensional liver radiomic phenotypes and their role in common metabolic diseases

The paper identifies genetic associations with liver radiomic features and their links to metabolic diseases using UK Biobank data.

Evaluating Individual Level Performance of Polygenic Risk Scores Using Early Onset High Genetic Risk Coronary Artery Disease as a Benchmark

The paper evaluates individual-level performance of polygenic risk scores (PRSs) using a benchmark cohort of early-onset coronary artery disease patients, showing variability in PRS accuracy and highlighting the need for individual-level validation.

Phenome-derived polygenic scores and social determinants jointly shape context-dependent disease risk

This paper constructs phenome-derived polygenic scores and evaluates how they, along with social determinants of health, influence disease risk across different populations and diseases.

Genomic, phenomic, and geographic associations of leukocyte telomere length in the United States

This study examines associations between leukocyte telomere length and genomic, phenomic, and geographic factors in diverse U.S. populations, identifying novel loci and genes.

GWAS of amiodarone-induced thyroid dysfunction: Applications for genotype-guided risk stratification

This paper identifies genetic variants associated with amiodarone-induced thyroid dysfunction and shows they improve risk prediction beyond general thyroid disease PRS.

Locus 9p21.3 CAD Risk Across Diverse Populations: LD and Allelic Heterogeneity Explain Variation Across Ancestries and Reduced Replication in Africans

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.

Genome-Wide Assessment of Pleiotropy Across >1000 Traits from Global Biobanks

The paper identifies pleiotropic loci across 1,167 traits using GWAS meta-analysis and shows they are enriched for functional annotations and improve polygenic score predictions.

Sequence sensitivity of open chromatin reveals constrained regulatory elements underlying human traits

The paper introduces CAMBUS, a machine-learning framework to identify functionally important open chromatin regions by measuring sequence sensitivity, and finds these regions are enriched for evolutionary constraint and disease-related variants.

Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels

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.

Decoding Genetics, Ancestry, and Geospatial Context for Precision Health

The paper analyzes genetic, ancestral, and geospatial data from a biobank to explore their relationships with health outcomes in a historically diverse population.

Clinical and Therapeutic Applications of Individual-level Tissue-Specific Imputed Transcriptomes

The paper imputes tissue-specific gene expression for 486,452 UK Biobank participants and demonstrates its use in prioritizing therapeutic targets and predicting phenotypic risk.

Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors

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.

Genomic and phenomic landscape of clonal hematopoiesis in over a million ancestrally diverse participants

This study analyzes clonal hematopoiesis in over a million diverse individuals, identifying 72 genome-wide significant loci and linking CHIP to various phenotypes.

Genetic Analysis of Right Heart Structure and Function in 40,000 People

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.

Mobile elements in human population-specific genome and phenotype divergence

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.

Trans-ancestry genome-wide analysis of atrial fibrillation provides new insights into disease biology and enables polygenic prediction of cardioembolic risk

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.

Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.

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.

Deep learning-based chest X-ray age serves as a novel biomarker for cardiovascular aging

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.

Large scale genome-wide association study in a Japanese population identified 45 novel susceptibility loci for 22 diseases

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.

Transethnic meta-analysis of genome-wide association studies identifies three new loci and characterizes population-specific differences for coronary artery disease

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

Predicting cell-type-specific non-coding RNA transcription from genome sequence

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.

Population-specific and transethnic genome-wide analyses reveal distinct and shared genetic risks of coronary artery disease

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.