Elevated Lipoprotein-Associated Phospholipase A2 Independently Affects Age-Related Increases in Systolic Blood Pressure: A Nested Case-Control Study in a Prospective Korean Cohort

Abstract

Inflammatory markers are susceptible to changes over time. Thus, we observed changes in inflammatory markers correlating with age-related increases in blood pressure (BP) through a prospective study. The aim of this study was to investigate changes in inflammatory markers that correlate with age-related increases in BP. The study included 1,500 nondiabetic and normotensive healthy subjects at baseline. Of these, 121 individuals who developed hypertension (defined as systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg) after 2 years formed the hypertension group. For each incident hypertension case, 2 age- and sex-matched control subjects were selected among those who did not develop hypertension (control group, n = 242). After baseline adjustment, the hypertension group exhibited greater increases in body mass index (BMI), systolic and diastolic BP, triglyceride, total cholesterol, glucose, Lp-PLA₂ activity, and urinary 8-epi-prostaglandin F_2α (8-epi-PGF_2α ) levels compared to the control group. In the hypertension group, changes in (Δ) systolic BP correlated positively with Δ Lp-PLA₂ activity, which correlated positively with Δ low-density lipoprotein (LDL-) cholesterol and Δ urinary 8-epi-PGF_2α levels. Moreover, multiple linear regression revealed baseline systolic BP and Δ Lp-PLA₂ activity to be independent predictors of Δ systolic BP in the hypertension group. Our results suggest that age-related increases in systolic BP may correlate strongly with elevated Lp-PLA₂ activity and that Lp-PLA₂ can be considered a biomarker for systolic BP elevation.

Figure 1

Lp-PLA₂ activity (a) and 8-epi-PGF_2α (b) levels at baseline () and 2-year follow-up () in control (normal BP at both baseline and follow-up) and hypertension (normal BP at baseline but development of hypertension during follow-up) groups. Mean  ±  SE. ^∮tested by logarithmic transformation. ^†p < 0.05,^††p < 0.01,^†††p < 0.001 derived from an independent t-test between the groups at baseline and follow-up and adjusted for the baseline BMI and follow-up BMI, respectively. ^∗p < 0.05,^∗∗p < 0.01,^∗∗∗p < 0.001 derived from a paired t-test in each group. ^‡p < 0.05,^‡‡p < 0.01,^‡‡‡p < 0.0011 derived from an independent t-test at the changed value and adjusted for the baseline values.

Figure 2

Relationships of the changes in (Δ) Lp-PLA₂ activity with Δ systolic BP, Δ LDL-cholesterol, and Δ 8-epi-PGF_2α in control (normal BP at both baseline and follow-up, solid line) and hypertension (normal BP at baseline but development of hypertension during follow-up, broken line) groups. (a) Correlation between Δ Lp-PLA₂ activity and Δ systolic BP. (b) Correlation between Δ LDL-cholesterol and Δ Lp-PLA2 activity. (c) Correlation between Δ Lp-PLA₂ activity and Δ 8-epi-PGF_2α.

Figure 3

Correlation matrix of associations among changes in (Δ) clinical parameters, inflammatory markers, and oxidative stress markers in all study subjects. For all study subjects (n = 363), Pearson's correlation coefficients were calculated to determine the association between variables: changes in (difference from baseline, Δ) clinical characteristics, biochemical parameters, inflammatory markers, and oxidative stress markers. Red indicates a positive correlation; blue indicates a negative correlation. In particular, Δ Lp-PLA₂ activity showed strong positive correlations with Δ systolic BP, Δ diastolic BP, and Δ 8-epi-PGF_2α (r = 0.418, p < 0.001; r = 0.329, p < 0.001; and r = 0.430, p < 0.001, respectively).