| Title: | Estimating co-heritability of co-morbid disorders in families from diverse populations to inform genetic counseling in precision medicine |
| Lead Institution: | University of Michigan |
| Principal investigator: |
Application 177198
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About
A fundamental question in precision medicine related to comorbidity is to what degree multiple disorders share the same genetic etiology, possibly leading to phenotypic interdependencies. Accurate estimation of co-heritability, the co-variation between phenotypes due to shared genetic etiology, using family data addresses this question by quantifying the genetic contribution in multiple diseases, informing gene mapping efforts for co-morbidities, moving genetic risk prediction in family members to incorporate family history of co-morbidities, and guiding genetic counseling and testing (e.g., inform who to test). This project aims to develop now statistical methods to model high-dimensional phenotypes and find the environmental and genetic risk factors of co-morbidity. This project will last for three years. We propose semiparametric joint modeling with latent polygenic effects governed by a copula model. Through random effects and appropriate transformations, phenotypes on heterogeneous scale and different types can be unified, and genetic random effects can be distinguished from unobserved shared environmental effects. The results will provide the architecture of the shared genetic versus environmental underpinning of comorbidities, inform precision medicine research participants about their genetic risk relative to other risk factors, and evaluate disease risk given history of co-morbidities in family members.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 19193 | Computationally efficient methods for estimating phenome - wide coheritability of multi-type phenotypes using biobank data | Yuhao Deng (+2) | 2025 | Communications Biology |
Enabling scientific discoveries that improve human health