Welcome to Olink Proteomics in Proximity Podcast!

Below are some useful resources from this episode:

Highlighted pre-print article: Malarstig A, Grassman F, Dahl L, et al. Evaluation of Circulating Plasma Proteins in Breast Cancer: A Mendelian Randomization Analysis. ResearchSquare 2023.04.04. DOI: https://doi.org/10.21203/rs.3.rs-2749047/v1

Highlighted platform that was used to measure proteins in this study with a next-generation sequencing (NGS) readout (Olink® Explore 3072): https://olink.com/products-services/explore/

Learn more about the consortiums or cohorts mentioned in the podcast:

UK Biobank Pharma Proteomics Project (UKB-PPP) is currently performing one of the world’s largest scientific studies of blood protein biomarkers conducted to date: https://www.ukbiobank.ac.uk/learn-more-about-uk-biobank/news/uk-biobank-launches-one-of-the-largest-scientific-studies

Human Proteome Atlas (HPA) aims to map all human proteins using various omics technologies: https://www.proteinatlas.org/

SCALLOP consortium is a collaborative framework for discovery and follow-up of genetic associations with proteins on the Olink Proteomics platform: https://olink.com/our-community/scallop/

KARMA cohort is a prospective screening cohort for breast cancer in Sweden: https://karmastudy.org/ongoing-research/the-karma-cohort/

Swedish Twin Registry (referred as “Twin Gene cohort” in the podcast) is the largest of its kind, containing genetic information about ~87,000 twin pairs: https://ki.se/en/research/the-swedish-twin-registry

Additional published articles and books mentioned during the podcast:

Hood, Leroy and Price, Nathan. The Age of Scientific Wellness: Why the Future of Medicine Is Personalized, Predictive, Data-Rich, and in Your Hands, Cambridge, MA and London, England: Harvard University Press, 2023. https://doi.org/10.4159/9780674293465

Suhre K, McCarthy MI, Schwenk JM. Genetics meets proteomics: perspectives for large population-based studies. Nat Rev Genet. 2021 Jan;22(1):19-37. doi: 10.1038/s41576-020-0268-2. Epub 2020 Aug 28. PMID: 32860016. https://pubmed.ncbi.nlm.nih.gov/32860016/

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