Novel approaches to assess environmental exposures and early markers of effect

Environmental health research has traditionally focused on how a specific chemical (or class of chemicals) influences a specific health outcome. However, most individuals are exposed to multiple chemicals at any one time. Thus, a single exposure-disease approach does not represent the combinatorial effects that multiple exposures can have on human health. The EHS department has developed and utilized novel approaches to measure environmental exposures through mass spectrometry-based metabolomics, epigenomic/epigenetic tools, genomic instability, wearable air pollutant monitors, and meta-research.

Mass spectrometry-based metabolomics

Mass spectrometry-based metabolomics is the systems-level analysis of all the low molecular weight chemical entities in a sample (the metabolome). It offers a novel technological approach for monitoring multiple environmental chemical exposures in human biological samples, such as blood, urine and sweat and has great utility as an investigative tool for exposure assessment and linking exposures to biological impact.

Wearable monitors

Wearable monitors are an emerging tool for identifying environmental exposures to a broad panel of organic chemicals. This sampling approach facilitates longitudinal exposure assessment in potentially vulnerable populations such as pregnant women and children. The wearable devices being developed by faculty in the EHS department passively concentrate airborne pollutants onto a polymer substrate, which can then be analyzed using mass spectrometry.

Meta-research

Meta-research is the study of research itself, which include the key areas of research methods, reporting/transparency, and reproducibility. Dr. Wallach’s meta-research lab focuses on improving the efficiency and credibility of scientific research. Projects include conducting theoretical and empirical investigations of the scientific literature, performing single meta-analyses, and conducting meta-epidemiological studies (i.e., the combination of data from multiple meta-analyses on multiple topics).