Elevated protein levels and mRNA upregulation of Lp-PLA2, IL-6, and TNF-α in cardiovascular disease among a Saudi population

Background Lp-PLA 2 connects oxidised lipid metabolism to vascular inflammation, however data from Middle Eastern populations remain limited. This study evaluated circulating Lp-PLA 2 , inflammatory cytokines, oxidized lipids, and whole-blood mRNA expression in a Saudi cohort. Methods A case–control study was conducted including 30 males with established atherosclerotic cardiovascular disease (CVD) and 30 males without known CVD. Plasma biomarkers were measured using ELISA, and whole-blood mRNA expression of Lp-PLA 2 , IL-6, and TNF-α was assessed using RT-qPCR. Multivariable linear regression analyses were performed adjusting for BMI, LDL-C, HbA1c, and smoking. Results Compared with non-CVD participants, individuals with CVD showed higher Lp-PLA 2 (419 ± 188 vs. 101 ± 32 ng/mL; P < 0.001), IL-6 (74 ± 17 vs. 40 ± 19 pg/mL; P < 0.001), TNF-α (4.4 ± 0.9 vs. 3.7 ± 0.8 pg/mL; P < 0.01), ox-LDL (430 ± 143 vs. 242 ± 67 ng/mL; P < 0.001), and LP-a (134 ± 31 vs. 90 ± 33 nmol/L; P < 0.001), with a more atherogenic lipid profile (LDL 3.02 ± 0.63 vs. 1.72 ± 0.63 mmol/L; P < 0.001; HDL lower: P < 0.01). mRNA expression of Lp-PLA 2 , IL-6, and TNF-α was upregulated in CVD. Lp-PLA 2 correlated with IL-6 ( r = 0.75, P < 0.001), TNF-α ( r = 0.36, P < 0.01), ox-LDL ( r = 0.85, P < 0.001), and LDL ( r = 0.80, P < 0.001). However, in multivariable regression analyses, LDL-C and HbA1c were significant predictors of biomarker levels. Although LDL-C and HbA1c were associated with biomarker levels after adjustment, residual confounding related to disease status and treatment exposure cannot be excluded. Conclusions Elevated inflammatory and oxidative biomarkers in CVD are strongly associated with underlying metabolic factors, particularly dyslipidemia and glycemic status. These findings support Lp-PLA 2 as a marker of lipid-associated inflammatory activity rather than an independent causal mediator. This study provides population-specific data from a Saudi cohort and highlights the importance of metabolic context in interpreting cardiovascular biomarkers.