Vietnamese Genome-based Prediction of Disease Risk


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Type 2 Diabetes
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Genetic diseases are caused by mutations in genes or abnormal changes in chromosomes. These diseases are likely to pass from parents to children in families and lineages. Genetic diseases, which tremendously affect the development and maturity of the patients, are a burden on the family and community. There are two types of genetic diseases, including (i) single-gene disorder caused by a mutation in a gene, and (ii) complex disorder caused by mutations in multiple genes coupling with influence of the environment and lifestyle. It is necessary to conduct in-depth studies at molecular genetics level to understand the exact cause of genetic diseases.

Genomic technology and technical equipment have taken giant leaps since the success of the first human genome sequencing of nearly 2 decades ago. As a result, human genome studies have entered a new era that can quickly identify millions of biomarkers across the whole genome of individuals – opening up a period of polymorphic analysis by genome-wide association study (GWAS), enabling in-depth analysis of diseases’ genetic traits in humans. Through GWAS, researchers have found a larger number of disease-related variants than initially expected, and individual effects of these variants on diseases are negligible. Tools have been developed to accurately determine the cumulative impact of millions of tiny negligible genetic variants on disease risk.

Our team aims to use genetic data of whole genome and computational methods to assess millions of common genetic variants associated with complex genetic diseases such as heart diseases, type 2 diabetes, breast cancer, Parkinson’s and Alzheimer’s. For each disease, we will apply a computational algorithm that combines all published genetic information into a polygenic risk score reflecting a person’s susceptibility to disease. Especially for diabetes, we will use genetic data of 2000 Vietnamese people obtained from the Diabetes GWAS project that we currently are working on. These scores were proven to have a potential for widespread use in healthcare settings.

Strategic partners

  • Hanoi Medical University
    Hanoi Medical University

    Collaborate research 10 common diseases

  • University of Queensland
    University of Queensland

    Collaborate research models

  • Tel Aviv University
    Tel Aviv University

    Collaborate research models

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