Delineating Genetic Influences on Neurodegenerative Disorders and Infectious Diseases Through Advanced Computational Methods
Year: 2025
Type: article
Abstract: Genetics plays a critical role in understanding the molecular mechanisms underlying neurodegenerative disorders and pathogen evolution in infectious diseases. For example, identifying genetic variants associated with a disease phenotype uncovers functional pathways that could lead to potential drug targets and therapeutic interventions. In addition, tracking the genetic evolution of pathogens enables early detection and warning of infectious disease outbreaks. In both applications, given the large amount of genetic data, advanced computational methods, including longitudinal and multivariate models, could significantly boost the statistical power and capture interrelationships among traits, environmental factors and genetic influences. This dissertation focuses on four applications of longitudinal and multivariate approaches in examining genetic influences on complex disorders and addresses two primary objectives: maximizing sample inclusion for improved statistical power and integrating comprehensive feature sets to explore multivariate relationships. More specifically, longitudinal mixed effect models or longitudinal genome wide association study methods are utilized to capture novel genetic contributions, or genetic and environmental interactions towards phenotypes in Alzheimer’s disease (AD) and repetitive head impact (RHI) induced Chronic traumatic encephalopathy (CTE) in relatively small sample sizes. Multivariate predictive models are adopted to classify AD neuropathological status with imaging genetic features. Lastly, unsupervised multivariate pipelines are developed to uncover clustered mutation patterns in the SARS-CoV-2 genome that could enable early warnings of a potential outbreak. Taken together, results from this dissertation could contribute to precision medicine approaches in neurodegenerative disorders and enhance public health surveillance capabilities for infectious diseases.
DOI: 10.34917/38330431
Author: Zhuang, Xiaowei
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6946630290
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