About
In recent years, although people have recognised the harm of chronic noncommunicable diseases and have also moderately reduced the frequency of some common bad lifestyles (such as smoking and alcohol abuse) to avoid the occurrence of chronic noncommunicable diseases, the incidence and harm of chronic noncommunicable diseases are still increasing. In addition, emerging social factors such as COVID-19 and adverse living environments such as air pollution and noise further promote the high incidence and rejuvenation of chronic noncommunicable diseases. Meanwhile, in the same environment, the occurrence of chronic noncommunicable diseases also varies from person to person, suggesting that family history or genetic factors are also key influencing factors of the occurrence of chronic noncommunicable diseases. With the rapid development of omics sequencing technology, it is found that different omics levels can reflect the risk of disease through different dimensions, the whole genome can reveal the genetic risk of disease, olink proteomics can reveal the level characteristics of proteins in blood, in which different levels of serum protein levels can reflect the risk of disease, and metabolomics can reflect different metabolic level characteristics of the human body. The development of these sequencing technologies further guarantees the feasibility of in-depth and comprehensive exploration of chronic noncommunicable diseases.
Therefore, we propose to conduct a prospective comprehensive analysis by using large-scale high-quality data from the UK Biobank, which will help to explore the influencing factors and potential mechanisms of chronic noncommunicable diseases and targeted early disease prevention.
In this study, we will construct the polygenic score of SNPs of different chronic noncommunicable diseases and explore and quantify the modifying effect of genetic factors on the occurrence of chronic noncommunicable diseases caused by the above exposure. In addition, Mendelian randomisation and multivariate logistic regression analysis were used to further clarify the plasma metabolites and protein characteristic molecules associated with the above exposures. Finally, we will study how the above exposures affect the occurrence of chronic noncommunicable diseases through metabolites and protein molecules and further reveal the underlying molecular mechanisms of chronic noncommunicable diseases.
The research results of this project can expand our understanding of the occurrence of chronic noncommunicable diseases and consciously prevent adverse related exposures. In addition, the identification of omics characteristic molecules under relevant exposures will help to find biomarkers related to chronic noncommunicable diseases and provide more accurate public health strategies for the early prevention, diagnosis and targeted treatment of human chronic noncommunicable diseases.