| Title: | Novel methods for understanding of the genetic architecture of common diseases and traits |
| Lead Institution: | University of Hong Kong |
| Principal investigator: | Professor Pak Chung Sham |
Application 28732
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About
To understand the genetic contribution to common diseases and traits, it is vital to understand where in the genome are the most critical genomic variants, their nature and frequencies, and how much each locus contributes to the disease/trait. Many methods have been proposed to address these questions We aim to investigate the validity of existing methods as well as develop new ones to better our understanding. Diseases and traits to be studied include: asthma, diabetes, blood pressure, self-report cancer, anthropometric measures, cognitive abilities, allergy, education attainment, neuroticism score, depression, use of glasses, self-reported health, and hearing difficulties. Through the research we aim to better understand the contribution of common variants to common diseases and traits. For example, we aim to understand whether loci with reasonably large effect sizes exist that can be harnessed for better disease prevention or treatment. This type of information is crucial for directing future research directions as well as developing more personalized treatment and prevention strategies. Methods have been developed to partition the genome into regions and quantify the contribution each region makes to the disease/trait. These methods will be applied to the data, as well as new ones proposed by the applicants. Simulation studies will be carried out to examine the validity of the methods. If the methods are found to be robust and reliable, inferences about the contribution of each genomic locus to the disease/trait will be drawn. The full cohort.4 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 8190 | Identifying Myocardial Infarction Using Hierarchical Template Matching-Based Myocardial Strain: Algorithm Development and Usability Study | Jayendra Maganbhai Bhalodiya (+7) | 2021 | JMIR Medical Informatics |
| 8773 | Improved estimation of functional enrichment in SNP heritability using feasible generalized least squares | Zewei Xiong (+3) | 2024 | Human Genetics and Genomics Advances |
| 10211 | Preliminary Evidence for Genetic Nurture in Depression and Neuroticism Through Polygenic Scores | Justin D. Tubbs (+1) | 2023 | JAMA Psychiatry |
| 7923 | Reciprocal causation mixture model for robust Mendelian randomization analysis using genome-scale summary data | Zipeng Liu (+8) | 2023 | Nature Communications |
Enabling scientific discoveries that improve human health