Kazuhiko Yamamoto

The paper introduces UNIChro-seq, a method for quantifying chromatin accessibility at target loci, and demonstrates its application in analyzing disease risk alleles and genome-edited variants.

CATaN integrates TF-GRNs and transcriptomes to identify genetic risk components across complex diseases, finding 588 significant CC components enriched for SNP heritability.

The paper identifies a treatment-resistant fibroblast state in RA synovitis that drives chronic inflammation through senescence-associated mechanisms and highlights therapeutic targets beyond cytokine inhibition.

The paper identifies novel cell states and molecular profiles in lupus patients using single-cell data, linking them to disease severity and treatment outcomes.

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.

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.

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

The paper generates a comprehensive atlas of alternative splicing in human immune cells using long-read sequencing, identifies unannotated transcripts, and links isoforms to disease through quantitative trait loci and GWAS data.

This study identifies cell-type-specific transcriptomic signatures associated with SLE disease establishment and exacerbation, highlighting their clinical relevance and potential limitations in capturing genetic risk factors.

The paper analyzes splicing QTLs focusing on coding sequences to identify disease-causal variants associated with GWAS traits through novel integration and selection approaches.

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 introduces sc-end5-seq and SCAFE to profile transcribed cis-regulatory elements in single cells, showing tCREs improve prediction of CRE interactions and disease heritability.

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

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 analyzes genomic mutations in clonal hematopoiesis across 179,417 Japanese individuals, revealing population-specific patterns and differences in cancer risk.

IMPACT improves regulatory element annotation by integrating TF binding profiles with epigenomic data, showing better performance in predicting eQTLs and capturing RA heritability.

This study identifies HLA-DQA1 as the major independent genetic risk for ACPA-positive RA in Han population through MHC region sequencing and HLA-typing.