"The Translational Utility of Metabolomics in the Integrative Omics Era"
Time: 11 a.m. - 12 p.m.
Date: December 1, 2017
Location: James L035

The College of Medicine’s Department of Bioinformatics is hosting a talk by Jessica Lasky-Su, ScD, from Brigham and Women’s Hospital entitled “The Translational Utility of Metabolomics in the Integrative Omics Era.”

Jessica Lasky-Su, ScD

Jessica Lasky-Su, ScD

Abstract: The rapid advance in scientific technology has resulted in a multi-omic era, where multiple omics data types are available for a single cohort. However, it is often unclear as to what analytic approach is optimal to provide insight into disease pathogenesis. In this talk we describe two approaches to multi-omic data that can be utilized in conjunction with each other for which to study disease development: 1) A reductionist approach that relies on previous biologic and scientific knowledge to guide the analyses and 2) A systems biology approach that integrates genomic, epigenomic, and metabolomic networks to examine disease pathogenesis on a holistic level. We illustrate how to utilize both approaches in the context of asthma.

Asthma continues to represent a major global public health problem resulting in significant disability and resource utilization. Most asthma is diagnosed before the age of six years and is preceded by episodes of troublesome lung symptoms – wheezing, in the years after birth. Thus, prenatal and early life exposures play an important role in its development. Despite this, a complete mechanistic understanding of the pathogenesis of wheezing and asthma in early life remains limited. Metabolomic profiling has the distinct advantage of being a marker of either mechanisms leading to disease or an established disease process that incorporates both genetic and environmental exposures, making this a promising approach to detect a composite measure of prenatal and early-life influences. We demonstrate the translational utility of metabolomics through the integration of metabolites, genetic variants, and relevant exposures in 2 pre-birth cohort clinical trials. We expand upon these findings through the integration of gene expression, methylation, and metabolic networks in an independent asthma cohort, where we further identify the mechanisms and biological pathways important to asthma severity. This approach can be generalized to identify causal mechanisms for complex diseases to enable translational understanding

About the Speaker: Dr. Lasky-Su is an Associate Professor of Medicine at Harvard Medical School and Brigham and Women’s Hospital where she has spent the last 18 years focusing on the identification of genetic, genomic, and more recently metabolomic determinants for complex diseases, with a particular focus on asthma, the accumulation of which has resulted in over 100 peer-reviewed original research manuscripts. Through GWAS, Dr. Lasky-Su identified multiple asthma variants, including variants in the HLA- DQ region as a disease variant for asthma, several pharmacogenetic variants that influence steroid response and short-acting beta agonists (GLCCI1 and ASB3), and an asthma and obesity susceptibility locus (DENND1B). These research findings have received national and international attention, which led to a keynote Dr. Lasky-Su’s methodological contributions, particularly those focused on family-based study designs, have also made a significant impact by demonstrating the utility of family-based study designs and the importance of accounting for age-dependent genetic effects. Dr. Lasky-Su’s more recent work has focused on integrative metabolomics and other omics data types. Through these efforts she has developed a metabolomics research program at the Channing Division of Network Medicine that has been highly successful and synergistic in nature, as it has drawn together a diverse group of investigators. This work has resulted in the identification of important biological determinants for asthma, in particular specific metabolites in the sphingolipid pathway that are related to ORMDL3, the most well-established asthma gene.

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