| Title: | Genetic study of complex phenotypes |
| Lead Institution: | Yale University |
| Principal investigator: | Professor Heping Zhang |
Application 42009
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About
Identifying genetic variants for complex diseases is important, challenging, and to a great extent, frustrating. We will develop novel statistical models, methods, and software while efficiently using and understanding the available data. We will develop more efficient approaches that utilize biological information (e.g., genetic, clinical, and demographic data) and link them to complex outcome data. Our progress will help address one or more of the following areas of research: (a) analysis of imaging, genetic, clinical, and environmental data; (b) modeling multiple psychiatric conditions simultaneously; and (c) identification and incorporation of novel genetic variants including their interactions with environmental factors by using and developing state-of-the-art statistical methodology and software. We believe our research will have a direct impact on our understanding of diseases, which may ultimately be used by other experts in developing treatment and prevention strategies for a broad range of diseases.4 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 10998 | Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank | Zihuan Liu (+4) | 2023 | Genetic Epidemiology |
| 7780 | Elevated C-reactive protein mediates the liver-brain axis: a preliminary study | Rongtao Jiang (+11) | 2023 | EBioMedicine |
| 7477 | Genetic variants are identified to increase risk of COVID-19 related mortality from UK Biobank data | Jianchang Hu (+4) | 2021 | Human Genomics |
| 9184 | Identification and validation of supervariants reveal novel loci associated with human white matter microstructure | Shiying Wang (+8) | 2023 | Genome Research |
Enabling scientific discoveries that improve human health