Dr Ying Ying Wong

I am a Postdoctoral Fellow in the Molecular Immunology research group, currently leading the Type 1 Diabetes (T1D) immunogenomics research program. In partnership with the ENDIA consortium - a pioneering multi-center pregnancy-birth cohort study—my research tracks disease trajectories longitudinally and identifies driver genes in high-risk children from birth through early childhood. My work leverages advanced genomic technologies such as bulk and single-cell ATAC-seq, RNA-seq, Hi-C, and multi-omics platforms, and associated high-performance computational bioinformatics. 

Since completing my PhD in 2022, my research has primarily been supported by the Juvenile Diabetes Research Foundation (JDRF) Australia and in 2024, I received an international Postdoctoral Fellowship from the Breakthrough T1D (New York), which continues funding my T1D immunogenomics research over the next three years. 

Critical unmet need in T1D research: T1D is a childhood-onset chronic autoimmune disease caused by immune system destroying insulin-producing pancreatic β-cells. Currently there is no cure for T1D, and patients require lifelong insulin injections. In Australia, 19-22 healthy years of life are lost per person as a result of ill-health, disability or early death from living with T1D (T1D Index). The reason a child develops T1D is poorly understood but appears to depend on a complex interaction of genetic predisposition and environmental factors. Until T1D is preventable, the search for a cure cannot stop.

My T1D immunogenomics research: With unique bioresource samples spanning birth, before (pre-T1D) and after seroconversion (T1D initiation), to the point of clinical diagnosis, my work identifies which genes and pathways drive the development of T1D, and genetic risk variants (SNPs) that are associated with these changes. I leverage bioinformatics and computational tools to analyze and integrate high-throughput bulk and single-cell transcriptomics, genomics, and multi-omics datasets. My work focuses not only on the 3D genomic architecture in T1D but also on comprehensive data integration to map interactions between regulatory gene enhancers and their target genes within the genome's 3D space. This approach reveals long-range gene regulation mechanisms and provides insights into T1D pathogenesis. The identified dysregulated gene targets can then be prioritised for testing as preventative or treatment options in new clinical trials.