| Title: | Genetic studies of Hereditary Hearing Loss |
| Lead Institution: | Sun Yat-Sen University |
| Principal investigator: | Professor Huiying Zhao |
Application 51732
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About
Aim: Hearing loss affects about 70 million of people world widely. Because of the hearing loss, one in 1000 children was affected in language acquisition and cognition, social and emotional development. Most of the hearing loss cases are caused by genetics. Thus, identifying genetics factors of hearing loss is essential. Scientific rational: To identify the genetics factors of hearing lose, we have collected 13 families and identified several candidate genes. We proposed to compare our findings with UKBB patients and verify genetic reasons of hearing lose. Meanwhile, with the increasing number of hearing loss-associated variants, it becomes necessary to elucidate the disease mechanisms based on the functions of SNPs. Therefore, we will analyze the genetic data from UKBB to study disease-associated SNPs in the coding regions that may alter the biochemical function of coded proteins. Then, we will investigate the SNPs in non-coding regions that may play long range regulation roles. Finally, we will use the system-level analysis to construct the disease-associated network for HHL, which may elucidate the potential mechanisms and discover the early diagnosis markers. Furthermore, the knowledge in the UKBB will expand the scope of our project from characterizing hearing loss to discover the mechanisms of central nervous process abnormal caused by postoperative hearing recovery. Project duration: The duration of this project will be three years, from 2020 to 2023. Public health impact: We expected to identify the genes associated with hearing loss and elucidate the mechanism of the disease. The findings of this project will provide candidate biomarkers for early diagnosis and drug target for treatment design.3 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 13114 | Accurate identification of genes associated with brain disorders by integrating heterogeneous genomic data into a Bayesian framework | Dan He (+13) | 2024 | EBioMedicine |
| 11889 | Genetic and phenotypic associations of frailty with cardiovascular indicators and behavioral characteristics | Yihan Chen (+9) | 2024 | Journal of Advanced Research |
| 7696 | Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization | Siying Lin (+6) | 2023 | NeuroImage |
Enabling scientific discoveries that improve human health