Guiyan Ni

This paper develops a polygenic risk score for glaucoma with improved performance across major ancestries, enabling earlier detection and targeted treatment of high-risk individuals.

The paper integrates 12 spatial and single-cell technologies to analyze cellular interactions and signatures in three skin cancers, identifying key therapeutic targets and genetic associations.

Family-based GWAS meta-analysis of 34 phenotypes shows standard GWAS effects carry sizeable confounding uncorrelated with direct genetic effects, while assortative mating likely inflates SNP heritability and genetic correlations.

The paper uses spatial transcriptomics to analyze how CDK4/6 inhibition affects tumor response in SHH medulloblastoma by mapping cellular states and spatial organization.

The paper compares ten polygenic score methods for psychiatric disorders across multiple cohorts, finding that some methods significantly improve prediction statistics over the baseline PC+T method.

This paper quantifies the accuracy loss of polygenic scores in non-European populations by modeling linkage disequilibrium, allele frequencies, and effect size correlations.

The paper introduces a method to detect genotype-population interaction effects using ancestry principal components to analyze genetic heterogeneity across populations.

This paper investigates the genetic links between female reproductive traits and six psychiatric disorders using polygenetic risk scores from UK Biobank data.

This study uses a whole-genome approach to identify genetic and non-genetic variance components in cardiovascular risk influenced by lifestyle factors, showing their modulating effects and implications for CVD prevention.

This paper introduces a multivariate reaction norm model to estimate genotype-covariate correlation and interaction in complex trait analyses, showing improved performance over existing methods.

The paper finds a genetic association between schizophrenia risk and age at first birth in women, with different genetic correlations in younger and older age groups.

This study compares LDSC and GREML methods for estimating genetic correlation, showing GREML provides higher accuracy, especially in the presence of genetic heterogeneity.