Approved Research

The effect of genetic and molecular biomarkers in patient stratification

Lay summary

UK BioBank houses large scale sequencing data of about 500,000 subjects together with health and molecular information of each individual, facilitating the gene discovery and precision medicine. In this project, we seek to harness the power of UK BioBank to understand and characterize the patient stratification and disease progression. We will investigate whether there are genetic and molecular patterns which distinguish specific diseases from other diseases and disease states.

To characterize the patients, we will first analyze the genetic data and determine the genetic features associated with different disease categories, including but not limited to immunology and oncology. This is followed by integrating with various molecular data to better understand the genes, genetic variants and drugs stratifying patient groups. To achieve this goal, we will develop novel ML/AI based methodologies to better stratify patient subgroups. As we also have our best-in-class curated proprietary protein-protein interaction network (inBio Map), which in our previous analyses shows 6 times more effective in detecting drug targets than single genetics data alone, we will perform gene network and pathway analysis for the subclusters to identify networks and pathways associated with patient subclusters. Our efforts will hopefully provide new gene and drug signatures to improve the disease risk prediction and morbidity, as well as to identify and prioritize novel or better drug targets for clinical studies.

We are a team of professionals with strong expertise in bioinformatics and biostatistics with a mission to promote excellence of biomedical research and improve the lives of patients. We estimate that the duration of the proposed project will be 36 months, with an interest to be extended afterwards.