Impaired glucose tolerance (IGT) is a common condition that affects glucose control after sugar consumption. Isolated IGT is undetected by screening and diagnostic strategies, leaving affected individuals at high risk of developing diabetes. Here, a machine-learning framework identifies a three-protein signature for detecting isolated IGT from a single blood sample.
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References
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This is a summary of: Carrasco-Zanini, J. et al. Proteomic signatures for identification of impaired glucose tolerance. Nat. Med. https://doi.org/10.1038/s41591-022-02055-z (2022).
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Broad-capture proteomics and machine learning for early detection of type 2 diabetes risk. Nat Med 28, 2261–2262 (2022). https://doi.org/10.1038/s41591-022-02056-y
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DOI: https://doi.org/10.1038/s41591-022-02056-y
