Novel sampling and measurement methods for characterizing exposure
Feb 10, 2023
2:30PM to 3:30PM
Date(s) - 10/02/2023
2:30 pm - 3:30 pm
Prof. Joseph Okeme
Dept. of Chemistry and Chemical Biology, McMaster University
Non-genetic factors account for more than 80% of chronic diseases risk, implying that most diseases are preventable if these factors can be mitigated. These non-genetic factors include exposures related to the environment, occupation, diet, behavior and endogenous processes. A measure of all these non-genetic factors and related biological responses over the course of an individual’s lifetime is collectively termed “the exposome”. As an individual is potentially exposed to over a million chemicals, conventional exposure assessment tools such as active collection of samples and chemical-by-chemical analysis are not enough to determine which of these complex exposures pose health risks and at what levels.
In this seminar, I will discuss my ongoing and proposed use of cutting-edge technologies including novel wearable sampling and high-resolution mass spectrometry methods to identify and measure complex environmental exposures that influence health. The talk will exemplify my multidisciplinary research program that aims to characterize the exposome and understand how it influences health to inform preventive interventions including exposure reduction and early diagnosis of disease.
Joseph Okeme is an Assistant Professor in Chemistry and Chemical Biology and a Scientist at the Occupational Cancer Research Centre, Cancer Care Ontario-Ontario Health (OCRC-OH). He has a BSc in Environmental Toxicology (Abeokuta, Nigeria), an MSc in Instrumental Analytical Sciences (Robert Gordon University, Aberdeen) and a PhD in Physical and Environmental Sciences (University of Toronto). After receiving his PhD in 2017, he worked as a Postdoctoral Research Associate at Cancer Care Ontario-Ontario Health and a Banting Fellow at the Yale School of Public Health before moving to McMaster.
His interdisciplinary research program focuses on advancing our understanding of how non-genetic risks factors influence disease using novel technologies.