Yukinori Okada

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 study conducts a multi-ancestry GWAS of rheumatoid arthritis using the VA Million Veteran Program, identifying 152 genome-wide significant loci and improving fine-mapping resolution.

This study functionally characterizes 221,412 trait-associated variants using MPRA in 5 cell types, identifying 12,025 regulatory variants and revealing widespread epistasis and non-TF mechanisms.

The paper maps cis- and trans-eQTLs in blood samples to infer gene regulatory networks and prioritize trait-relevant pathways.

The paper sequenced 3,135 Japanese individuals to identify genetic variants and construct a reference haplotype, highlighting the need for diverse population inclusion in genetic catalogs.

The paper identifies USP18 as a negative regulator of interferon response at a lupus risk locus through trans-eQTL analysis in lymphoblastoid cell lines.

This paper uses rare k-mers to identify centromere haplogroups in human populations and cancer translocations, revealing structural diversity and translocation mechanisms.

The paper finds that mosaic chromosomal alterations in blood are associated with increased Alzheimer's disease risk, with variations by ancestry, mCA subtype, APOE ε4 status, and chromosomal location.

The paper investigates how genetic and epigenetic variations in CGG repeats affect OPDM patient phenotypes, finding complex relationships between repeat size, sequence context, and methylation.

The paper identifies 4,688 genome-wide significant loci for 111 gestational phenotypes and finds dynamic genetic effects linked to maternal health outcomes.

This study identifies the Rubicon-WIPI axis as a regulator of exosome biogenesis, showing its role in age-dependent exosome release and microRNA fate in mice.

This study identifies 128 BP-associated loci in Chinese adults through GWAS and shows causal links between BP traits and CVD using Mendelian randomisation.

The paper presents AIDA, a diverse single-cell RNA-seq atlas of immune cells, revealing sub-continental diversity impacts on immune cell properties and identifying functional genetic variants.

This study identifies ancestry-specific and sex-specific genetic loci for primary open-angle glaucoma through a meta-analysis of 15 biobanks, highlighting shared biology with vascular mechanisms and cell proliferation.

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

This study shows that polygenic risk scores from multi-ancestry GWAS perform better in understudied populations than single-ancestry scores, except when the understudied group is small.

This paper provides a framework for genomics-driven drug discovery using cross-population GWAS meta-analysis, identifying candidate drugs for 13 diseases through three methodologies.

This paper conducts a multi-ancestry GWAS of major depression, identifying 190 loci and 354 genes, with findings showing increased fine-mapping power and bidirectional BMI relationship in European ancestry samples.

The paper defines a standard format for GWAS summary statistics to improve data sharing and analysis.

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.

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 reports in silico structural analysis of ethnic-specific PAX4 variants associated with type 2 diabetes in a Japanese population.

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

This paper introduces MAMA, a method for multi-ancestry GWAS meta-analysis, which identifies novel genetic associations and improves power across populations.

The paper identifies sex-differential participation bias in genetic studies by performing GWAS on sex in 3.3 million individuals, finding 158 loci associated with sex and highlighting traits like BMI that may influence participation.

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