June 8, 2022


Zhanghua Chen, Ph.D.

Zhanghua Chen, Ph.D., University of Southern California

Title:  Using Metabolomics to Investigate Pathophysiological Mechanisms of Air Pollution Exposure (2MB)

Abstract: Air pollution exposure has been increasingly recognized as the leading environmental risk factor for morbidity and mortality. Short-term and long-term air pollution exposure has been associated with increased risk of many adverse health outcomes such as low birth weight, perturbed fetal and infant growth, obesity, cardiovascular diseases, diabetes, neurological disorders. The adverse health effects of air pollution exposure present throughout the entire life course since preconception and prenatal periods. Many air pollutants such as fine particles (PM2.5), nitrogen dioxide (NO2) and ozone (O3) have been shown to increase systemic oxidative stress and inflammation, which have been hypothesized as main pathophysiological mechanisms. More human studies are needed to clarify the disease mechanisms of air pollution exposure. Emerging evidence from metabolomics studies suggested that air pollution exposure altered key metabolic pathways of amino acids, fatty acids and lipids that could play an important role in disease etiology. Chen and her fellow researchers metabolomics studies in children and adults also found that dysregulated metabolic pathways induced by short-term and long-term air pollution exposure were associated with increased risk of various adverse outcomes including metabolic dysfunction, asthma exacerbation and autism. Future research is needed to prove the causal effect of air pollution exposure and find the molecular targets for interventions and disease prevention.

EHS Core Center Affiliation: University of Southern California, SCEHSC

Maude David, Ph.D.

Maude David, Ph.D., Oregon State University

Title: Mutli-Omic Profiling of Children with Autism Spectrum Disorder Reveals the Importance of Fatty Acid Metabolism in Autism (11MB)

Abstract: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder with both genetic and environmental risk factors. In this study, David and fellow researchers took a comprehensive approach of multi-omics, animal behavior, and ex-vivo molecular analysis to identify key gut metabolites, examine their effect on behavior, and investigate their mechanism of action. First, the researchers recruited over 100 age-matched sibling pairs (between 2 and 8 years old) where one had an ASD diagnosis, and the other was developing typically. They analyzed stool samples from participants using 16s rRNA amplicon, shotgun metagenomic and metatranscriptomic, and metabolomics data to identify key microbial taxa and metabolic processes at play in ASD. Eleven amplicon sequencing variants (ASVs) were identified as related to ASD using 16s sequencing on stool collected across three timepoints spanning 4 weeks. Furthermore, multi-omic integration using topic modeling algorithms applied to 16s, metagenome, metatranscriptome, and metabolomics data from the same samples revealed a significant decrease in long-chain acylcarnitines in ASD among participants with low dietary fat intake. Lastly, 5-dodecenoate, a medium chain unsaturated fatty acid, was found significantly depleted in ASD individuals. David and fellow researchers then confirmed biological relevance by orally administering 5-dodecenoate to CNTNAP2 mice (an ASD model) and observed a significant decrease in multiple anxiety and anti-social metrics. Finally, they investigated the mechanisms of action using a small intestinal organ chip model and implicated 5-dodecenoate as a signaling molecule involved in the inflammatory response of epithelial cells. These data suggest a major role for medium and long-chain fatty acid availability in the behavioral and gastrointestinal aspects of ASD.

EHS Core Center Affiliation: Oregon State University, EHSC