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A validated, modifiable proteomic score from the EXSCEL trial predicts cardiovascular events in diabetes
Kristin M. Corey, Maggie Nguyen, Michael Y. Mi, Megan E. Ramaker, Ilya Zhbannikov, Harald Sourij, G. Michael Felker, Naveed Sattar, Jennifer B. Green, Pamela S. Douglas, Robert E. Gerszten, Robert J. Mentz, Adrian F. Hernandez, Rury R. Holman, Bruce M. Psaty, James S. Floyd, Svati H. Shah
Kristin M. Corey, Maggie Nguyen, Michael Y. Mi, Megan E. Ramaker, Ilya Zhbannikov, Harald Sourij, G. Michael Felker, Naveed Sattar, Jennifer B. Green, Pamela S. Douglas, Robert E. Gerszten, Robert J. Mentz, Adrian F. Hernandez, Rury R. Holman, Bruce M. Psaty, James S. Floyd, Svati H. Shah
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Clinical Research and Public Health Cardiology Endocrinology

A validated, modifiable proteomic score from the EXSCEL trial predicts cardiovascular events in diabetes

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Abstract

BACKGROUND Adults with type 2 diabetes mellitus (T2DM) are at increased risk for stroke, myocardial infarction, and cardiovascular death, yet individual risk is heterogeneous and incompletely captured by clinical models.METHODS In the Exenatide Study of Cardiovascular Event Lowering (EXSCEL), adults with T2DM were randomized to a GLP-1 RA (exenatide) or a placebo and followed longitudinally for major adverse cardiovascular events (MACE). High-throughput discovery proteomics was done in plasma collected at baseline and 12 months. Proteins associated with time to MACE were identified using multivariable regression and incorporated into supervised machine learning models. A multi-protein score was developed and externally validated in 2 independent population-based and trial cohorts.RESULTS The proteomic score showed incremental improvement in cardiovascular risk discrimination beyond clinical factors alone, and several proteins were consistently prioritized across modeling approaches. The protein score and a top-ranked protein, tetranectin, were modified by GLP-1 RA treatment, and a decrease in protein score was associated with improved outcomes, supporting modifiability of MACE risk.CONCLUSION External validation confirmed generalizability across cohorts with and without diabetes. Together, these findings demonstrate that plasma proteomic signatures can enhance cardiovascular risk stratification and identify treatment-responsive biomarkers in T2DM, supporting their potential role in precision prevention strategiesFUNDING The EXSCEL study was funded by Amylin Pharmaceuticals. This research was supported by contracts HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, 75N92021D00006, and grants R01HL146145, U01HL080295, U01HL130114, R01HL172803, and R01HL144483 from the National Heart, Lung, and Blood Institute, with additional contribution from the National Institute of Neurological Disorders and Stroke. Additional support was provided by R01AG023629 from the National Institute on Aging.

Authors

Kristin M. Corey, Maggie Nguyen, Michael Y. Mi, Megan E. Ramaker, Ilya Zhbannikov, Harald Sourij, G. Michael Felker, Naveed Sattar, Jennifer B. Green, Pamela S. Douglas, Robert E. Gerszten, Robert J. Mentz, Adrian F. Hernandez, Rury R. Holman, Bruce M. Psaty, James S. Floyd, Svati H. Shah

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