Home // LCSB // Research // Gene Expression & Metabolism

Gene Expression & Metabolism

The Gene Expression & Metabolism group at the LCSB

Evan Williams, Ziyun Zhou, Besma Boussoufa, Arianna Lamanna

About the Gene Expression & Metabolism group

The most prevalent and costly diseases affecting the industrialized world today are the result of myriad complex interactions between patients' genetic profiles and their environments (called GxE). These diseases—metabolic syndrome, most cancers, dementia, and so forth—also increase in prevalence and severity with age. Our laboratory focuses on fundamental medical research for ageing and diet-associated metabolic perturbations (e.g. mitochondrial dysfunction, fatty liver disease) and on basic science for systems biology approaches to improve the models and algorithms used for de novo hypothesis generation in large datasets.

In particular, we focus on how variation in populations’ genetic profiles and their differing environments leads to diverging incidence and severity of metabolic diseases. To this end, we take a multi-omics approach to analyze tissue samples collected from diverse ageing mammalian populations across their lifespans to observe how gene expression connects to metabolic activity and the development of (or resistance to) disease states. That is: how do DNA sequence variants impact mRNA transcription, protein translation, and how do their interactions all causally lead to a gradual spectrum of disease phenotypes? This approach has two main goals. The first goal is to understand the aetiology of complex metabolic diseases: to identify earlier biomarkers, risk factors, protective factors, and potential treatment pathways. The second goal is to model the fundamental relationships between DNA, RNA, and protein and to understand how and when these measurements may be used as a proxy for cellular activity, and to what extent each “layer” of cell metabolism reveals unique information. Our research group is thus focused on molecular biology, data science, and bioinformatics.