SODAMeets is a platform where data generators and computational scientists can share their use of software/data. For each meeting, we will have two speakers present on software or data they would like to share with the community, emphasizing how these software/data are used. Speakers will be requested to fill out our SODA website so that we collect relevant information on these software/data presented.
Sign up here if you are interested in presenting at SODAMeets!
Dec. 10, 2024 at 2:00 pm ET:
Gabi Kastenmüller, Computational Health Center, Helmholtz Munich
The HuMet Repository: An interactive resource of time-resolved metabolite profiles for exploring human metabolism under challenges
Abstract: The human metabolism constantly responds to stimuli such as food intake, fasting, exercise, and stress, triggering adaptive biochemical processes across multiple metabolic pathways. To understand the role of these processes and disruptions thereof in health and disease, detailed documentation of healthy metabolic responses is needed but still scarce on a time-resolved molecular level.
Here, we present the HuMet Repository, a web-based resource for exploring dynamic metabolic responses to six physiological challenges (exercise, 36 h fasting, oral glucose/lipid loads, mixed meal, cold stress) in healthy subjects. For building this resource, we integrated existing and newly derived metabolomics data measured in blood, urine, and breath samples of 15 young healthy men at up to 56-time points during the six highly standardized challenge tests conducted over four days. The data comprise 1.1 million data points acquired on multiple platforms with temporal profiles of 2,656 metabolites from a broad range of biochemical pathways. By embedding the dataset into an interactive web application, which is freely available at http://humet.org, we enable users to easily access, search, filter, analyze, and visualize the time-resolved metabolomic readouts and derived results.
In my talk, I will provide an overview over the HuMet study and the available data and will show examples of how these data can be leveraged for answering different research questions e.g., related to postprandial metabolism, the wash-out of dietary markers, and the complementarity of metabolomics platforms.
Courtney Jean Smith, Department of Genetics, Stanford University
Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy
Abstract: Pleiotropy and genetic correlation are widespread features in GWAS, but they are often difficult to interpret at the molecular level. Here, we perform GWAS of 16 metabolites clustered at the intersection of amino acid catabolism, glycolysis, and ketone body metabolism in a subset of the UK Biobank. We utilize the well-documented biochemistry jointly impacting these metabolites to analyze pleiotropic effects in the context of their pathways. Among the 213 lead GWAS hits, we find a strong enrichment for genes encoding pathway-relevant enzymes and transporters. We demonstrate that the effect directions of variants acting on biology between metabolite pairs often contrast with those of upstream or downstream variants as well as the polygenic background. Thus, we find that these outlier variants often reflect biology local to the traits. Finally, we explore the implications for interpreting disease GWAS, underscoring the potential of unifying biochemistry with dense metabolomics data to understand the molecular basis of pleiotropy in complex traits and diseases.
For the Zoom link please email: soda@metabolomicana.org
We are always looking for volunteers and presenters! If you would like to:
Volunteer: email soda@metabolomicsna.org
Present at a Meetup or Workshop: Fill out this form.
List your software the Curated List: Fill out this form.
And,
Join our LinkedIn Group
Add Meetups to your Calendar
Visit our Website