| Title: | Improving Risk Prediction of Common Cancers by Integrating Genetic Variants and Aging-related Somatic Mutations |
| Lead Institution: | Henan Cancer Hospital. |
| Principal investigator: |
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About
Cancer is the second leading cause of death worldwide. Although cancer incidence and mortality can be effectively reduced by population screening, enhancing our understanding of risk factors is essential for optimizing risk-stratified screening and identifying individuals with heightened cancer susceptibility. Both genetic and non-genetic factors contribute to the initiation and development of cancer. A polygenic risk scores (PRS) of the cancer could help estimate the individual risk. However, PRS performance varies due to lifestyle and environmental factors, suggesting that hereditary risk can be influenced by non-heritable factors. Age-related somatic mutations, including clonal hematopoiesis of indeterminate potential (CHIP) and mosaic chromosomal alterations (mCAs), are detectable in peripheral blood and strongly associated with age. The presence of these acquired mutations predisposes otherwise healthy adults to an increased risk of several chronic aging-related conditions, including hematologic cancers and cardiovascular diseases. However, whether these acquired mutations can contribute to the risk of common cancers and modify the effect of PRS on cancer risk prediction remains unclear. By analyzing the abundantly available genome and phenotype data from the UK Biobank cohort in the next three years, we aim to (1) evaluate the observational and causal association between age-related somatic mutations and common cancers; (2) investigate the interaction between genetic variants and age-related somatic mutations in relation to cancer; and (3) develop a prediction model and improve its predictive ability by integrating the polygenic risk score with age-related CHIP and mCAs. We believed that these findings will provide new insights into the age-related somatic mutations and genetic determinants and their interactions for common cancers. The improved prediction model would promote individualized risk assessment and lifestyle-based primary prevention of cancers.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 14421 | Sleep duration, mediating biomarkers, and risk of microvascular complications among individuals with type 2 diabetes: A prospective cohort study | Xiaoge Niu (+9) | 2025 | Diabetes Research and Clinical Practice |
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