Masahiro Kanai

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 introduces CASTIE, a method for context-dependent eQTL mapping in single-cell data, identifying regulatory variants missed by static models and linking them to disease traits.

sc-pcQTL identifies multi-gene QTLs in single-cell RNA-seq data by combining hurdle modeling and principal-component analysis, revealing cell-type-specific regulatory effects.

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.

The paper performs large-scale GWAS and RVAS on 392,030 whole genomes from All of Us, identifying 49,863 associations and 193 novel pLoF gene-phenotype links through meta-analysis with UK Biobank.

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.

MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data by allowing causal effect sizes to vary across ancestries, achieving higher power and lower computational costs.

The paper identifies naturally variable exons in human transcripts, showing their prevalence and impact on gene expression and genetic interpretation.

The paper uses population-scale single-nucleus ATAC-seq and RNA-seq to identify regulatory variants and their disease associations in immune cells.

This study performs a genome-wide association study for Long COVID, identifying a significant association with the FOXP4 locus and highlighting the role of pulmonary dysfunction and COVID-19 severity.

This study introduces STAG-seq, a method combining transcriptomics and genotyping to functionally analyze genetic variants in immune cells, revealing their impact on gene expression and disease 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 evaluates variant scoring methods across different selection regimes, showing their performance depends on variant-to-gene and gene-to-disease factors.

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

SAIGE-QTL is a tool for single-cell eQTL analysis that directly maps eQTLs without pseudobulk aggregation and improves power for detecting rare variants.

The paper develops SCENT, a method to create cell-type-specific enhancer-gene maps from single-cell multimodal data, identifying causal variants and genes for diseases.

Meta-analyzing per-ancestry GWAS of 7,266 UK Biobank traits across six genetic ancestry groups adds 14,676 loci missed by European-only analysis, including ancestry-enriched CAMK2D and G6PD signals.

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.

Rare-variant depletion in 1kb windows of 76,156 gnomAD genomes, versus feature-adjusted mutation expectations, marks regulatory elements and outperforms seven alternative scores at flagging functional non-coding variants.

This paper introduces improved fine-mapping methods that model infinitesimal effects, showing better calibration and increased PRS accuracy for causal variant identification in complex traits.

The paper visualises molecular QTLs to better understand genetic effects on gene expression and identifies causal genes at GWAS loci.

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.

Blood whole genomes from 274,832 people yield 92 independent nuclear signals for mtDNA copy number and 42 for inherited heteroplasmy levels, implicating mtDNA replication machinery.

The paper introduces a method to prioritize causal genes for complex traits by integrating GWAS data with gene expression and biological data, achieving high precision in gene-trait pair identification.

The paper evaluates dominance effects in over 1,000 UK Biobank phenotypes using GWAS, finding no significant dominance contribution to phenotypic variance from common variation.

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 study identifies 118 candidate causal genes and 21 novel lipid loci on the X chromosome through a multi-ancestry meta-analysis of blood lipid levels, revealing sex-biased effects and pleiotropy with cardiovascular and hormonal 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.

The paper outlines best practices for conducting multi-ancestry transcriptome-wide association studies (TWAS) using the Global Biobank Meta-analysis Initiative data, addressing challenges in ancestry and tissue specificity.