SiYang Maggie Liu

The paper conducts a multi-ancestry, trans-generational GWAS meta-analysis of gestational diabetes and glycemic traits, identifying novel loci and highlighting limited pregnancy-specific genetic effects.

This paper introduces a cocktail chemical labeling method using [Ru(bpy)3]Cl2 to profile the surfaceome of dendritic cells with high coverage and reproducibility.

GDBIG provides a genomic database and platform for intergenerational genetic research using data from the Born in Guangzhou Cohort Study.

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

The paper develops methods for analyzing low-depth NIPT sequencing data to accurately estimate allele frequencies and genetic effect sizes, enabling population genetic studies.

This study identifies 30 novel metabolite-gene associations in 34,394 Chinese pregnant women and finds pleiotropy and causal relationships between metabolites and diseases.

This study performs GWAS on thyroid traits in Chinese pregnancies, identifying 176 genetic loci and linking thyroid function to pregnancy complications and later health outcomes.

This study identifies East Asian-specific genetic loci for intrahepatic cholestasis of pregnancy linked to historical HBV infection, using genome-wide association analyses in 101,023 Chinese women.

This study identifies four genetic loci associated with gestational diabetes risk and 31 loci linked to glycaemic traits in 30,699 Chinese pregnant women, with MTNR1B showing the strongest association.

This paper introduces encG-reg, an encrypted genotype regression method that identifies relatives across cohorts without sharing raw data, achieving accuracy comparable to traditional methods.

This study evaluates the robustness of polygenic adaptation signals detected using GWAS summary statistics across different populations and cohorts.

This study identifies cholesterol levels and WBC counts as causal factors for COVID-19 severity through GWAS and MR analysis, and highlights type I interferon pathways in disease mechanisms.

EMU accurately infers population structure from ultra-low coverage sequencing data with missingness, outperforming existing methods on real and simulated datasets.

This study analyzes whole-genome sequencing data from 332 Chinese COVID-19 patients to identify genetic variants associated with disease severity and susceptibility.

This study identifies genetic variants associated with sporadic and recurrent miscarriage through large-scale association analyses and Mendelian randomization.