| Title: | Comprehensive investigation in common disease outcomes integrating genetic and phenotypic associations |
| Lead Institution: | Sichuan University |
| Principal investigator: | Dr Yazhou He |
Application 73759
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About
Most common diseases, such as cardiovascular diseases and cancer, are conditions attributed to intricated interplays between human DNA and environmental determinants. The UK Biobank has provided an immense resource of multidimensional data (e.g. human DNA variations and environmental factors) enabling identification of novel predictors for common diseases with considerable clinical and public health relevance. This also permits systematic combined assessment of the human DNA, environmental factors, imaging data and other markers for disease risk and clinical outcome after diagnosis. In this project, firstly we aim to unravel novel markers that lie in human DNA as well as environmental factors associated with common disease risk and outcomes using cutting-edge statistical methods. Novel findings along with previously reported marker-disease associations will then be further appraised for the strength of evidence and be evaluated for possible causality. The third objective is to improve prediction accuracy of disease risk and outcomes integrating all the identified markers using modern data science techniques such as machine learning. A special focus will be put on common diseases that impose substantial burdens on human health such as cardiovascular diseases, cancer, infections, autoimmune and aging related diseases. Combination of the big data provided by the UK Biobank and newly-developed modelling methodology will add to current knowledge of pathogenesis and progression of common diseases. Our findings may also provide evidence for individualised disease prevention and management. This project may be extended beyond three years due to newly-released data which warrant extra validation of our findings.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 12763 | Appraising non-linear association between pre-diagnostic platelet counts and cancer survival outcomes: observational and genetic analysis | Changtao Li (+10) | 2024 | Platelets |
Enabling scientific discoveries that improve human health