Approved Research

Integrating UK Biobank and other datasets to assess the relationship between precdicted risk scores of medication, lefestyles, diets and complex disease, including sarcopenia, osteoarthritis

Lay summary

Scientific rationale: Even though with the knowledge that a large proportion of variability in complex human diseases is due to genetic variation, but biologic process between the genetic variation and the disease are generally not understood. It is still a challenge to utilize the information of genomic data to predict the risk of the diseases. The new powerful and robust statistical methods are still a pressing need for prevention and diagnosis of complex diseases, including sarcopenia and osteoarthritis.

Aims: In this proposal, we have two main aims. First, we will construct a statistical model to predict individual's disease and the risk scores of the disease, using genomic data and other clinical risk factors from UK Biobank and other projects. Second, we will perform mendelian randomization analysis to integrate multi-omics data to gain some novel insight for studying biological mechanisms of complex diseases, including sarcopenia and osteoarthritis.

Project duration: The project period will be maximally 36 months.

Public health impact: The proposed research might potentially construct a new way to predict the risk of complex diseases (including sarcopenia and osteoarthritis), and identify some novel putative biological mechanisms effecting the diseases. These findings will help us gain insights into the studying for biological process of complex diseases, including sarcopenia and osteoarthritis.