Nogales, PaulaVelasco, CarlosGonzález-Cintado, LeticiaSharysh, DianaMota-Cobián, AdrianaIzquierdo-Serrano, RaúlTorroja, CarlosDel Rio-Aledo, DavidMorales-Cano, DanielMota, Rubén ABenguría, AlbertoDopazo, AnaSánchez-Cabo, FátimaVázquez, JesúsEspaña, SamuelCarramolino, LauraMateo, JesúsBentzon, Jacob F2025-12-152025-12-152025-08-13Sci Transl Med. 2025 Aug 13;17(811):eado6467.https://hdl.handle.net/20.500.12105/27020Positron emission tomography (PET) imaging with the radiolabeled glucose analog fluorodeoxyglucose (FDG) is used to monitor atherosclerosis in clinical trials, but there is uncertainty regarding the plaque cell types that accumulate FDG and how uptake is regulated. The long-standing view that FDG is mainly taken up by macrophages is at odds with human and experimental data, and the impact of disease activity on FDG uptake has not been examined directly. To analyze the ability of FDG-PET to monitor disease activity, we developed a model of plaque regression in minipigs with hepatic overexpression of a gain-of-function mutant of (). Atherosclerosis was induced through 12 months of high-fat feeding in the porcine model. Disease activity was then lowered for 3 months by reducing plasma cholesterol with a low-fat diet alone or in combination with the microsomal transfer protein (MTP) inhibitor BMS-212122. Plaque regression in advanced lesions of the abdominal aorta was evident from reduced lipid content, reduced necrotic core size, and partial resolution of plaque inflammation and was accompanied by a decline in FDG-PET signal. Single-cell gene expression profiling revealed that plaque regression involved substantial down-regulation of genes encoding glycolytic enzymes in smooth muscle cells (SMCs), macrophages, and lymphocytes, which was corroborated by analysis of the plaque cellular proteome. These findings in a large-animal model suggest that FDG-PET can monitor atherosclerosis because of a close association between disease activity and glycolytic enzyme expression in all of the major plaque cell types.This work was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 866240 to J.F.B.); Ministerio de Economía, Industria y Competitividad (MEIC) with cofunding from the European Regional Development Fund (ERDF) (grants PI2019-108568RB-­I00 to J.F.B., BES-2016-076633 to P.N., and PID2021-122348NB-­I00 to J.V.); Instituto de Salud Carlos III with cofunding from ERDF/European “A way to make Europe” (grant PI20/00610 to J.M.); the Comunidad de Madrid (grant S2022/BMD-7333-­CM to J.V.); and Fundación Obra Social La Caixa (AtheroConvergence, HR20-00075 to J.F.B., and LCF/PR/HR22/52420019 to J.V.). The Centro Nacional de Investigaciones Cardiovasculares (CNIC) is supported by the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia e Innovación (MICIN), and the Pro CNIC Foundation and is a Severo Ochoa Center of Excellence (grant CEX2020001041-S funded by MICIN/AEI/10.13039/501100011033).engVoRhttp://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 International4080274017811SCIENCE TRANSLATIONAL MEDICINEopen access