| Title: | The interaction effects of early life exposures and genetic susceptibility on human metabolomics and common metabolic diseases |
| Lead Institution: | Nanjing Medical University |
| Principal investigator: | Professor Aihua Gu |
Application 55858
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About
Although increasing evidence has linked early life exposures, such as smoking during pregnancy, birth weight, etc, to the risks of multiple metabolic diseases in adulthood, the underlying mechanisms remain unclear yet. Moreover, genetic susceptibility exerts effects on disease development during the whole life. Due to the great progress of Genome-Wide Association study (GWAS) on various phenotypes and diseases, many relevant single nucleotide polymorphisms (SNPs) have been identified. Recently, there is increasing interests to generate polygenic scores by combining these SNPs to reveal the overall effect of genetic architecture on common diseases, such as BMI-related polygenic sores in association with cardiovascular disease, diabetes mellitus, and obesity-related cancers (e.g. hepatocarcinoma, breast cancer, pancreatic cancer, colorectal cancer, etc.). To our knowledge, few studies have paid attention to the interaction between early life exposures and genetic susceptibility in the development of metabolic diseases. It is possible that genetic variants may modify the effects of early life exposures on the risk of future metabolic diseases. On the other hand, metabolomics is useful tool to study life exposures and human health because it potentially measures intermediate phenotypes that integrate exposures, genotype, and other host factors. It would allow efficient discovery of biomarkers and provide insight into molecular mechanisms of the interaction between early life exposures, genetic susceptibility, and metabolic diseases. Therefore, we propose to perform a prospective, comprehensive analysis by using the large-scale, high quality data from UK biobank, which would help reveal the potential mechanisms of early life exposures and genetic variants on common metabolic diseases and improve targeted, early prevention of the diseases. In this study, we will construct polygenic scores for SNPs that have been identified to be associated with cardiovascular disease, diabetes mellitus, and obesity-related cancers in GWAS and analyze polygenic scores modify the effects of early life exposures on the occurrence of common metabolic diseases. Plasma metabolites associated with early exposures and different polygenic genetic risk score will further be explored. The association of identified metabolomics signatures with cardiovascular disease, diabetes mellitus, and obesity-related cancers will thereafter be evaluated. Lastly, we will examine the extent of the metabolomics signatures in mediating the associations between early life exposures, SNP scores, and metabolic diseases. The results of the project can widen our knowledge on the interact effect of early life exposures, genetic variants in the development of metabolic diseases and identify metabolomics signatures related with metabolic diseases as biomarkers in targeted prevention.7 Publications
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