Yingxiao Yan
PhD project title: Impact of combined exposures on metabolic health (ICE)
Short description of the project
Effective prevention of non‑communicable diseases (NCDs) requires an understanding of how environmental factors influence disease risk and the biochemical mechanisms involved. While previous studies have examined individual exposures or specific interactions, most research has not systematically accounted for the complex and unknown interactions between multiple exposures.
This project combines machine learning and epidemiological modelling to evaluate how combined environmental exposures—such as diet, gut microbiota and pollutants—shape metabolic pathways and how these pathways, in turn, relate to risk factors for NCDs, including BMI, blood lipids, glucose levels and blood pressure. The aim is to advance methods for analysing multi‑exposure effects and to deepen understanding of how combined exposures influence metabolic health outcomes.
Supervisors
Main supervisor
- Carl Brunius, Associate Professor, Chalmers University of Technology
Co-supervisors
- Anton Ribbenstedt, Chalmers University of Technology
- Agneta Åkesson, Karolinska Institute
- Ingegerd Johansson, Umeå University
Location
Division of Food and Nutrition Science, Department of Biology and Biological Engineering, Chalmers University of Technology.
About me
I hold a Master’s degree in Public Health from Lund University and a Bachelor of Science in Chemistry from Nanjing University, China. My work focuses on developing data‑analysis algorithms for large datasets, and I have broad interests in biostatistics, epidemiology and machine learning. My passion lies not in studying the effects of single exposures, but in uncovering the bigger picture of how multiple environmental factors, metabolic pathways and health outcomes are interconnected.