Professor and Chair of the Department of Genetics, Director of the Center for Genomics and Stanford University
Current in-clinic sample collection and analysis practices for outpatient clinical trials limit the ability to monitor the effectiveness, safety, and personalized responses to investigational therapies. This presentation will explore the utility, methodology, and application of multi-omics microsampling approaches as a future alternative to in-clinic sample collection. The presenter, an expert in deep individualized profiling to improve human health, will describe how data of thousands of biomolecules were analyzed from 10 µL blood samples conveniently collected using a commercially available microsampling device. These analyses included untargeted LC-MS-based metabolomics and proteomics, targeted MS lipidomics, and analysis of cytokines and hormones using multiplexed assays. The presenter will provide details on the quality of these analyses and how these datasets were merged for visualization and interpretation. Following, 2 case studies will be described where study participants self-collected microsamples on an hourly basis. In the first 28 participants collected samples over the course of 4 hours following intake of a food product. Multi-omic analysis revealed enormous heterogeneity in the biochemical and inflammatory responses among the participants. As such, this approach may prove beneficial in personalized nutrition management, especially when correlated with medical phenotypes. In the second case study a participant was closely monitored for a week, in total collecting 98 microsamples along with continuous heart rate and glucose monitoring using wearable devices. A total of 2213 analytes (1051 endogenous metabolites, 811 lipids, 291 proteins, 45 cytokines, and 15 metabolic panels) were determined from each blood sample. The resulting high frequency multi-omics dataset enabled multiple new insights with respect to biochemical changes associated with diurnal cycles, the impact of food, and associations between molecular-level changes and digital data obtained from wearables. The presentation will conclude with an assessment of how multi-omics microsampling may impact future clinical trials.
Learning Objectives:
Upon completion, participants will be able to understand the latest advances in multi-omics microsampling for the study of personalized human health
Upon completion, participants will be able to recount both the benefits but also the practical and logistical considerations of the presented methodology
Upon completion, participants will be able to critically evaluate the value of high-density microsampling and multi-omics analysis in clinical studies