NLM DIR Seminar Schedule
UPCOMING SEMINARS
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July 15, 2025 Noam Rotenberg
Cell phenotypes in the biomedical literature: a systematic analysis and the NLM CellLink text mining corpus
RECENT SEMINARS
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July 3, 2025 Matthew Diller
Using Ontologies to Make Knowledge Computable -
July 1, 2025 Yoshitaka Inoue
Graph-Aware Interpretable Drug Response Prediction and LLM-Driven Multi-Agent Drug-Target Interaction Prediction -
June 10, 2025 Aleksandra Foerster
Interactions at pre-bonding distances and bond formation for open p-shell atoms: a step toward biomolecular interaction modeling using electrostatics -
June 3, 2025 MG Hirsch
Interactions among subclones and immunity controls melanoma progression -
May 29, 2025 Harutyun Sahakyan
In silico evolution of globular protein folds from random sequences
Scheduled Seminars on Sept. 10, 2024
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Glucagon-like peptide-1 (GLP-1) agonists have gained attention for their broad therapeutic potential beyond their original prescription in Type 2 Diabetes (T2D) and obesity. Since GLP-1 receptors are found in different tissues in the body, using these drugs over a long period has been linked to positive effects, including improved cardiovascular outcomes and neuroprotection. However, while these benefits are significant, there have also been reports of side effects, such as gastrointestinal issues and, in rare cases, pancreatitis and thyroid cancer.
Phenome-wide association studies (PheWAS), a method that associates genetic traits with phenotypes, can identify pleiotropic effects and variability in drug responses across diverse populations. To perform a PheWAS it is necessary to use Electronic Health Records (EHRs). The All of Us project provides EHR and genomic data rich in ethnic diversity. Overcoming biases often present in PheWAS focused primarily on European ancestry populations. In this study, we used PheWAS to explore the links between genetic markers and adverse events in T2D patients using GLP-1 agonists. The phenotypes examined were related to potential adverse events associated with chronic drug use.