Exercise and Prediabetes
Description
Welcome to Olink Proteomics in Proximity Podcast!
Below are some useful resources from this episode:
Highlighted publication: Diaz-Canestro C, Chen J, Liu Y, Han H, Wang Y, Honoré E, Lee CH, Lam KSL, Tse MA, Xu A. A machine-learning algorithm integrating baseline serum proteomic signatures predicts exercise responsiveness in overweight males with prediabetes. Cell Rep Med. 2023 Feb 21;4(2):100944. doi: 10.1016/j.xcrm.2023.100944. Epub 2023 Feb 13: https://www.cell.com/cell-reports-medicine/pdf/S2666-3791(23)00036-8.pdf PMID: 36787735; PMCID: PMC9975321: https://pubmed.ncbi.nlm.nih.gov/36787735/
Highlighted platform that was used to measure proteins in this study with a next-generation sequencing (NGS) readout (Olink® Explore): https://olink.com/products-services/explore/
Here is general information from Wikipedia about IL-6, one of the protein biomarkers identified in this study: https://en.wikipedia.org/wiki/Interleukin_6
Here is general information from Wikipedia about TFF-2, one of the protein biomarkers identified in this study: https://en.wikipedia.org/wiki/Trefoil_factor_2
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In case you were wondering, Proteomics in Proximity refers to the principle underlying Olink Proteomics assay technology called the Proximity Extension Assay (PEA), and more information about the assay and how it works can be found here: https://bit.ly/3Rt7YiY
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WHAT IS PROTEOMICS IN PROXIMITY?
Proteomics in Proximity discusses the intersection of proteomics with genomics for drug target discovery, the application of proteomics to reveal disease biomarkers, and current trends in using proteomics to unlock biological mechanisms. Co-hosted by Olink's Dale Yuzuki, Cindy Lawley and Sarantis Chlamydas.