Miaozhu Li has seven years interdisciplinary experience in genetics and epidemiology. She has been applying integrative genetic and environmental data analysis to understand aging and complex diseases.
In 2014, she started to work as a Postdoctoral Associate in the Biodemography of Aging Research Unit, Center for Population Health and Aging, Duke University. Currently, she is focusing on a five-year NIH project: "Relationships among Genetic Regulators of Aging, Health and Lifespan", which involves integrative data analysis of different genetic and epidemiology data to understand systemic genetic mechanisms linking to aging/health/lifespan including various complex diseases.
A special focus of the research project is on the role of polygenic and pleiotropic genetic effects in determining the aging related phenotypes, and on the use of both hypothesis-free and candidate gene approaches. To achieve this objective, four sets of longitudinal human data will be used, including the Framingham Study, Cardiovascular Health Study, Atherosclerosis in Communities, and the Multi-Ethnic Study of Atherosclerosis. Rich phenotypic and genotyping information is contained in such data. In this project, the first step will be evaluating individual and polygenic (additive and epistatic) genetic effects on aging phenotypes, and then repeat the analyses of polygenic influence on the aging traits, using pleiotropic genes, and genes with similar functions and relevance to aging, selected as candidates for these analyses.
The objective of the project is to significantly improve our understanding of genetic mechanisms of human aging. A special focus of this research will be on the role of polygenic and pleiotropic genetic effects in determining the aging related phenotypes, and on the use of both hypothesis-free and candidate gene approaches. The first step is evaluating individual and polygenic (additive and epistatic) genetic effects on aging phenotypes specific for this project, without a preceding biological hypothesis, and then repeat the analyses of polygenic influence on the aging traits, using pleiotropic genes, and genes with similar biological functions and relevance to aging, selected as candidates for these analyses. To achieve this objective, four longitudinal human datasets will be used (FHS, CHS, ARIC, and MESA) containing rich phenotypic and genotyping information.
1. Evaluate individual and additive polygenic influence of SNPs on phenotypes of physiological aging.
2. Select pleiotropic SNPs and evaluate their additive polygenic and epistatic influence on aging phenotypes.
3. Investigate biological mechanisms of genetic effects on aging traits.
4. Select candidate SNPs representing functionally related genes, and evaluate their additive and epistatic influence on aging phenotypes.
The goal of the AGE project is to accelerate the process of association study-based discovery by using bioinformatics and computational biology approaches. It will also improve the overall quality of the functional annotation through large-scale data integration.
Built on machine learning, natural language processing, and integration-based network analysis methods.
A longitudinal study on more than 3,000 Chinese with more than 100 environmental factors and more than 50 different age-related outcomes. Please see Publications for details.
At the same time, I was responsible for briefing several senior investigators from Peking University, Fudan University, CAS and IUF, organizing PhD students and research assistants in order to develop a highly effective team.
Prof. Ursula Krämer and I studied the genetic, environmental risk factors and their interactions in various allergic diseases in GINI and LISA cohort studies, covering almost 10,000 children with age range up 15 years in the Leibniz Research Institute for Environmental Medicine (IUF) in Germany. For this research project, I received a Wood-Whelan Research Fellowship from the International Union of Biochemistry and Molecular Biology.
Please see the paper Deletion of the late cornified envelope genes LCE3C and LCE3B is associated with psoriasis in a Chinese population in Publications for details.