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. 2024 Nov 2;4(6):oeae088.
doi: 10.1093/ehjopen/oeae088. eCollection 2024 Nov.

Vascular and inflammatory biomarkers of cardiovascular events in non-steroidal anti-inflammatory drug users

Ricky Vaja  1   2 , Plinio Ferreira  1 , Laura Portas  1 , Blerina Ahmetaj-Shala  1 , Neringa Cypaite  1 , Hime Gashaw  1 , Jennifer Quint  1 , Ramzi Khamis  1 , Adam Hartley  1 , Thomas M MacDonald  3 , Isla S Mackenzie  3 , Nicholas S Kirkby  1 , Jane A Mitchell  1
Affiliations

Vascular and inflammatory biomarkers of cardiovascular events in non-steroidal anti-inflammatory drug users

Ricky Vaja et al. Eur Heart J Open. .

Abstract

Aims: The Standard care vs. Celecoxib Outcome Trial (SCOT) found similar risk of cardiovascular events with traditional non-steroidal anti-inflammatory drugs (NSAIDs) and the cyclooxygenase-2-selective drug celecoxib. While pre-clinical work has suggested roles for vascular and renal dysfunction in NSAID cardiovascular toxicity, our understanding of these mechanisms remains incomplete. A post hoc analysis of the SCOT cohort was performed to identify clinical risk factors and circulating biomarkers of cardiovascular events in NSAID users.

Methods and results: Within SCOT (7295 NSAID users with osteoarthritis or rheumatoid arthritis), clinical risk factors associated with cardiovascular events were identified using least absolute shrinkage and selection operator regression. A nested case-control study of serum biomarkers including targeted proteomics was performed in individuals who experienced a cardiovascular event within 1 year (n = 49), matched 2:1 with controls who did not (n = 97). Risk factors significantly associated with cardiovascular events included increasing age, male sex, smoking, total cholesterol:HDL ratio ≥5, and aspirin use. Statin use was cardioprotective [odds ratio (OR) 0.68; 95% confidence interval (CI) 0.46-0.98]. There was significantly higher immunoglobulin (Ig)G anti-malondialdehyde-modified LDL (MDA-LDL), asymmetric dimethylarginine (ADMA), and lower arginine/ADMA. Targeted proteomic analysis identified serum growth differentiation factor 15 (GDF-15) as a candidate biomarker [area under the curve of 0.715 (95% CI 0.63-0.81)].

Conclusion: Growth differentiation factor 15 has been identified as a candidate biomarker and should be explored for its mechanistic contribution to NSAID cardiovascular toxicity, particularly given the remarkable providence that GDF-15 was originally described as NSAID-activated gene-1.

Keywords: Biomarkers; Cardiovascular; NSAID; Non-steroidal anti-inflammatory.

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Conflict of interest statement

Conflict of interest: Pfizer funded the SCOT study from which the samples for this study were obtained. They had no role in this study. T.M.M. has received consulting fees from Novartis and AstraZeneca and was the Chief investigator for the SCOT study. I.S.M. has received consultancy fees from Astrazeneca and payment from Novartis and NovoNordisk and was a co-investigator for the SCOT study. J.A.M. is a member of the scientific advisory board of Antibe Therapeutics, which develops cyclooxygenase inhibitor anti-inflammatory drugs. J.A.M. and N.S.K. hold active research grant funding in the area of cyclooxygenase biology. R.V. previously held grant funding in this area.

Figures

Graphical Abstract
Graphical Abstract
Figure 1
Figure 1
Scatter plots of circulating biomarkers with established associations with cardiovascular risk. Data are presented as individual points. The error bars represent standard error of the mean. Mann–Whitney U-test was used to analyse C-reactive protein, total IgG, IgG anti-malondialdehyde-modified LDL, and malondialdehyde-modified LDL/apolipoprotein B. All other analytes were analysed using an unpaired t-test. C-reactive protein, IgG anti-malondialdehyde-modified LDL, IgM anti-malondialdehyde-modified LDL, and malondialdehyde-modified LDL/apolipoprotein B: n = 144 participants (95 controls and 49 events); total IgG, total IgM, asymmetric dimethylarginine, symmetric dimethylarginine, and arginine/asymmetric dimethylarginine: n = 146 participants (97 controls and 49 events).
Figure 2
Figure 2
Targeted cardiometabolic proteomic analysis. (A) Principal component analysis with samples labelled according to group (control: green, event: blue). (B) Volcano plots showing proteins that are significantly different between events and controls before and after false discovery correction using the Benjamini, Krieger, and Yekutieli method. At a P-value cut-off of <0.05 (dotted line), 34 proteins were significantly different including 4 down- (blue) and 30 up-regulated (red). After applying FDR at a Q value cut-off of <0.05 (dotted line), only growth differentiation factor 15 remained significant. An unpaired t-test was used, n = 146 participants (49 events and 97 controls). (C) Heat map of 34 proteins that were significantly altered. Proteins are presented in order of P-value. Dark green indicates a 1.5-fold increase, and dark red indicates a 1.5-fold decrease.
Figure 3
Figure 3
Scatter plot of growth differentiation factor 15. Data are presented as individual points. The error bars represent standard error of the mean. An unpaired t-test was used. n = 146 participants (97 controls and 49 events).
Figure 4
Figure 4
Receiver operating characteristic curves and area under the curve table. The proteins are presented in order of area under the curve. Arginine/asymmetric dimethylarginine was lower in the event group, and so data were transformed by multiplying values by −1 to display all variables on a single table. n = 146 participants (97 controls and 49 events).
See this image and copyright information in PMC

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