Huanhuan Zhu

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 conducts the first GWAS on cell-free DNA (cfDNA) features in pregnant women, identifying 84 genetic loci and revealing causal relationships between hematological indicators and cfDNA biology.

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.

This paper introduces PMR-Egger, a probabilistic Mendelian randomization method to test and control horizontal pleiotropy in transcriptome-wide association studies, showing improved type I error control and power.