Ziqiao Wang

I am a Postdoctoral Fellow in the Department of Biostatistics at Johns Hopkins University. I currently work with Dr. Nilanjan Chatterjee. My research is supported by the NIH Pathway to Independence (K99/R00) award.

I obtained my PhD in Biostatistics from the University of Texas MD Anderson Cancer Center UTHealth Graduate School, under the mentorship of Dr. Peng Wei. Before that, I did my undergraduate studies in Applied Mathematics and Statistics at SUNY Stony Brook, New York and in Mathematics at Nanjing University.

Research Summary

I study how genetics, genomics, and environmental factors together drive the development of human diseases. I specialize in statistical methodology developments, data analysis, and theoretical investigations, and my research typically utilizes large-scale datasets from biobanks and epidemiological studies that include molecular genetic and genomic data, along with human behavioral and lifestyle factors.

One area of my research is polygenic scores (PGS), measures meant to summarize a person’s genetic predisposition for a trait and/or a disease such as cancers and childhood developmental disorders. While PGS are becoming more and more predictive of disease risks, there is much work to be done in the interpretations and applications of PGS. In particular, I developed novel statistical methods to jointly model gene-environment correlations and interactions using PGS in case-control studies, with data applications in the UK Biobank (Wang et al., AJE, 2024); I also developed methods in estimating risk parameters of PGS in family-based studies to understand genetic direct, indirect, and gene-environment interactions between genotype-phenotype associations.

Another aspect of my research is in integrative omics using individual-level and summary statistics to understand the disease mechanisms. I developed novel methods that improve the statistical power of large-scale association studies by incorporating the between-data correlations using summary statistics in multiple omic and spatially-resolved omic datasets (Wang et al., Bioinformatics, 2020; Wang et al., 2023). I also investigated DNA methylation biomarkers associated with pancreatic cancer through epigenome-wide association studies (Wang et al., Epigenetics, 2022). I am extensively involved in collaboration work with biologists, epidemiologists, and physicians studying different cancers and cardiovascular diseases using various types of genetic and genomic data.

In the future, I intend to continue my research in the interdisciplinary field of genetics, genomics, and human diseases, to serve the goal of a deeper understanding of disease mechanisms, in the long term contributing to better treatments and improving human health.