| Title: | Novel statistical analyses of obesity-related health outcomes in UK Biobank |
| Lead Institution: | Karolinska Institutet |
| Principal investigator: | Dr Xia Shen |
Application 14302
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About
The aim of this project is to apply novel methods developed by the PI, in order to identify novel genes associated with obesity-related traits and improve prediction of individual-level phenotypes. The main methodology framework contains three parts: 1. multi-trait genome-wide association analysis for detecting pleiotropic loci, which boosts power for detecting novel loci associated with correlated traits and disease; 2. variance-heterogeneity genome-wide scan for identifying genes that regulate phenotypic variability, which prioritizes loci involved in gene-gene and gene-environment interactions; 3. multi-trait whole-genome regression analysis for prediction of multiple complex traits. A major purpose of UK Biobank is to contribute to deeper understanding of health-related measurements and diseases in UK population, for which both gene discovery using genome-wide association studies and prediction of individual phenotypes using DNA information clearly play an important role. The proposed research here directly contributes to boost power of genome-wide association studies, hence improving discovery of genetic variants associated with obesity-related traits and disease in the UK population. High-throughput modeling of DNA data for multiple phenotypes has a great potential to improve prediction of many phenotypes. The PI will conduct three types of analyses using measured outcomes and DNA information in UK Biobank, in order to discover novel genes associated with obesity that control health and predict health-related traits in the UK population. The novel statistical analyses developed by the PI will detect new loci affecting multiple traits or affecting trait variation and hence enhance understanding of their interactions with other loci and environmental factors. The resulting improved disease understanding together with the ability to predict individual disease susceptibility will contribute to the implementation of precision medicine approaches that will increase treatment effectiveness. The full cohort of UK Biobank.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 7478 | Nontrivial Replication of Loci Detected by Multi-Trait Methods | Zheng Ning (+12) | 2021 | Frontiers in Genetics |
Enabling scientific discoveries that improve human health