Shinichi Namba

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

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 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 identifies 1,289 genetic signals for type 2 diabetes in 2.5 million individuals, revealing distinct clusters linked to vascular complications and highlighting ancestry-specific genetic risk factors.

This study evaluates polygenic risk score methods across diverse biobanks and ancestries, finding that European reference panels often yield better performance, while PRS-CS outperforms P+T for high-heritability traits.

This paper shows that meta-analysis fine-mapping is often miscalibrated due to cohort heterogeneity and introduces a QC method to identify suspicious loci.

Meta-analysis of harmonized GWAS from up to 18 biobanks (six ancestry groups) across 14 endpoints replicated 320 known loci and identified 188 apparently novel loci.

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.

The paper develops a pipeline for multi-sample long-read transcriptome assembly and applies it to breast cancer specimens to identify subtype-specific isoforms and fusion transcripts.