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Dr Christina Azodi

Postdoctoral Researcher, Bioinformatics & cellular genomics Laboratory

Developing statistical methods to improve our understanding of how genetic variation affects disease risk

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The Problem

Our genetic makeup (genotype) influences how we each individually look, as well as our disease risks (our genetic traits, or phenotype). But with more than three billion base pairs in human DNA, the exact links between genotype and phenotype are enormously complex.  

This link is clear when the condition is caused by a single genetic variant (e.g Huntington’s Disease). However, many disease traits (e.g. diabetes, neurodegenerative diseases, mental health disorders) result from the combined effect of multiple genetic variants and also interaction with environmental factors. For these complex traits, identifying causal relationships between genotype and phenotype remains highly challenging. 

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The Project

Christina’s goal is to devise and apply statistical methods that will improve our ability to map associations between genotype and phenotype. Even after more than a decade of work in this field and growing genomic data repositories worldwide, we are still only able to explain about 11% of the variation in complex traits observed in humans. 

“Without powerful and robust statistical methods, information hidden in the enormous volumes of biological data now being generated to study disease will go undiscovered,” says Christina. 

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Dr Christina Azodi

Dr Christina Azodi uses cutting-edge genomic, statistical and data science approaches to uncover how genetic differences lead to differences in complex traits like disease susceptibility.  

Christina joined SVI’s Bioinformatics & Cellular Genomics Laboratory in 2019, after formal training in computational biology during her PhD at Michigan State University and seven years of experience in functional genomics, data science, and machine learning.