Advances in Clinical and Experimental Medicine

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Advances in Clinical and Experimental Medicine

2024, vol. 33, nr 6, June, p. 593–600

doi: 10.17219/acem/171002

Publication type: original article

Language: English

License: Creative Commons Attribution 3.0 Unported (CC BY 3.0)

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Hanarz M, Siniarski A, Gołębiowska-Wiatrak R, Nessler J, Malinowski KP, Gajos G. Gender-related and PUFA-related differences in lipoprotein-associated phospholipase a2 levels in patients with type 2 diabetes and atherosclerotic cardiovascular disease. Adv Clin Exp Med. 2024;33(6):593–600. doi:10.17219/acem/171002

Gender-related and PUFA-related differences in lipoprotein-associated phospholipase A2 levels in patients with type 2 diabetes and atherosclerotic cardiovascular disease

Maksymilian Hanarz1,D,E, Aleksander Siniarski2,3,A,B,C,D,E,F, Renata Gołębiowska-Wiatrak3,B, Jadwiga Nessler2,3,F, Krzysztof Piotr Malinowski4,C, Grzegorz Gajos2,3,A,B,E,F

1 Jagiellonian University Medical College, Kraków, Poland

2 Department of Coronary Artery Disease and Heart Failure, Institute of Cardiology, Faculty of Medicine, Jagiellonian University Medical College, Kraków, Poland

3 St. John Paul II Hospital, Kraków, Poland

4 Department of Bioinformatics and Telemedicine, Faculty of Medicine, Jagiellonian University Medical College, Kraków, Poland

Graphical abstract


Graphical abstracts

Abstract

Background. Lipoprotein-associated phospholipase A2 (Lp-PLA2) may play an important role in the development of atherosclerotic cardiovascular disease (ASCVD). Increased plasma levels of Lp-PLA2 may predict future cardiovascular (CV) events in type 2 diabetes (T2D). The potential beneficial effects of polyunsaturated fatty acids (PUFA) on ASCVD have been widely investigated. However, the impact of different PUFA concentrations on Lp-PLA2 remains uncertain.

Objectives. We sought to determine the intergender differences in a population of patients with both T2D and ASCVD regarding Lp-PLA2 mass and the association between Lp-PLA2 mass and plasma levels of PUFA.

Materials and methods. In this cross-sectional study, we measured the Lp-PLA2 mass, PUFA concentrations and inflammatory markers in 74 patients (49 males and 25 females) with T2D and ASCVD.

Results. In this very high-risk population, males had, on average, 33.6% higher levels of Lp-PLA2 than females. The Lp-PLA2 mass was positively associated with interleukin 6 (IL-6) (r = 0.27, p = 0.019), creatinine (r = 0.29, p = 0.03) and triglyceride levels (r = 0.41, p = 0.002). Additionally, male gender and higher levels of triglycerides, leptin, oxidized low-density lipoprotein (oxLDL), and intercellular adhesion molecule 1 (ICAM-1) were independent predictors for an increased Lp-PLA2. Moreover, arachidonic acid (AA) negatively correlated with Lp-PLA2 (r = −0.26, p = 0.024), which was especially apparent in the female subgroup.

Conclusions. In the population of patients with ASCVD and T2D, males present with higher plasma levels of Lp-PLA2 than females. Additionally, higher plasma levels of AA were associated with lower Lp-PLA2 levels. Our findings support the utilization of Lp-PLA2 as a novel biomarker in ASCVD risk assessment in a very high CV risk population.

Key words: coronary artery disease, Lp-PLA2, PUFA, type 2 diabetes mellitus, gender differences

Background

Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death in both Europe and the USA.1, 2 Despite notable progress in the prevention and treatment of coronary artery disease (CAD), there is still a very high prevalence of new adverse cardiovascular (CV) events in this population.3

The development of ASCVD and its progression have been largely associated with vascular inflammation.4 Increased levels of inflammatory biomarkers such as interleukin-6 (IL-6), high-sensitivity C-reactive protein (hsCRP) and the macrophage-derived lipoprotein-associated phospholipase A2 (Lp-PLA2) enzyme can be used to assess the residual CV risk.5, 6, 7 The main function of Lp-PLA2 is to hydrolyze the proinflammatory mediators in order to reduce their bioactivity. However, this simultaneously increases their proatherogenic properties.6, 8 It is well established that type 2 diabetes (T2D) is an important ASCVD risk factor that is highly associated with ongoing inflammation and increased levels of Lp-PLA2.9 Moreover, the collaborative data of 32 prospective studies demonstrated that Lp-PLA2 is associated with proatherogenic lipids, underlining the significance of the activity and mass of this phospholipase on the progression of ASCVD.10 The Lp-PLA2 is a promising biomarker that can be included in the risk assessment of patients with ASCVD11, 12 or used as a potential target for ASCVD treatment.13, 14

It has been observed that males had higher levels of Lp-PLA2, but the relationship between Lp-PLA2 and gender is not yet evident, especially in the very high CV risk population of patients with both ASCVD and T2D.9, 14, 15

We have previously observed that the supplementation of polyunsaturated omega-3 fatty acids (n-3 PUFA) is beneficial in patients with ASCVD and results in the Lp-PLA2 mass reduc­tion,16, 17 but there is not enough evidence to determine which polyunsaturated fatty acids (PUFA) influence Lp-PLA2 to the greatest extent. However, there is a lack of a clear answer to whether the concentration of PUFA in patients at baseline can predict the levels of Lp-PLA2. If that would be the case, PUFA could be a useful tool to predict outcomes in a very high CV risk group and their response to the therapies such as PUFA supplementation.

Objectives

This study primarily aimed to provide additional knowledge about Lp-PLA2 in patients with both ASCVD and T2D. The secondary aim of this study was to determine the influence of different PUFA plasma concentrations on the Lp-PLA2 mass.

Materials and methods

Study design and subjects

This prospective, cross-sectional study consecutively recruited patients with both T2D (diagnosed in accordance with the 2018 American Diabetes Association guidelines), optimally treated for over 6 months before the enrollment, and ASCVD. The diagnosis of ASCVD was defined as CAD, established with an invasive coronary angiography (50% lumen narrowing in the proximal left main coronary artery or left anterior descending artery, or 70% lumen narrowing in any other segment of the coronary artery). The exclusion criteria included type 1 diabetes, not optimally treated T2D (glycated hemoglobin A1c (HbA1c) >9%), current infection, acute coronary syndrome (3 months prior to enrollment), PUFA supplementation 6 months before the examination, chronic anticoagulant therapy, bleeding, platelet count lower than 100×109/L, serum creatinine levels higher than 177 µmol/L or 2 mg/dL, increased alanine transaminase (ALT, 1.5 times above the upper-reference limit), chronic treatment with steroids or non-steroidal anti-inflammatory drugs (not including acetylsalicylic acid), malignant neoplastic disease, a life expectancy of less than 12 months, abuse of alcohol or drugs, and pregnancy.

Patients were screened and eventually enrolled in 2 major tertiary-reference cardiology centers in southern Poland. We initially enrolled 126 patients who met the inclusion criteria. Forty-three patients were excluded due to the exclusion criteria, and 9 patients refused to participate in the study. Eventually, 74 patients were included in the final analysis and were subsequently divided into 2 groups based on their gender.

Obesity was diagnosed based on a body mass index (BMI) ≥30 kg/m2. Arterial hypertension was defined as a blood pressure ≥140 mm Hg and/or ≥90 mm Hg (systolic and diastolic, respectively) – measured during 2 separate ambulatory visits. Current smoking was defined as smoking at least 1 cigarette per day.

This study was performed in compliance with the Good Clinical Practice (GCP) International Conference on Harmonization and was approved by the local ethics committee (Jagiellonian University Medical College, approval No. KBET/190/B/2012). All study participants provided written informed consent. This study complied with the Declaration of Helsinki.

Sample collection and routine laboratory tests

Fasting blood (25 mL) was drawn from an antecubital vein and immediately stored in tubes containing 3.2% trisodium citrate. Samples were processed up to 60 min after blood collection. Serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), glucose, HbA1c, and thyroid stimulating hormone (TSH) levels were determined using the biochemical analyzer cobas® 6000 (Roche Diagnostics, Basel, Switzerland). Creatinine was assayed by a routine laboratory technique, and estimated glomerular filtration rate (eGFR) was evaluated based on the Modification of Diet in Renal Disease (MDRD) formula. Complete blood count (CBC), including red blood cells, white blood cells, hemoglobin, hematocrit, red blood cell distribution width, platelet distribution width, and platelet count, was analyzed using standard laboratory evaluation (Sysmex XT-2000i; Sysmex Corp., Tokyo, Japan).

PUFA measurements

The PUFA measurements were assayed as described before.18 Briefly, samples were stored at −70°C until the biochemical measurement of the serum fatty acids of the phospholipid fraction was performed. The analytical procedure comprised several steps: 1) extraction of total lipids in serum; 2) lipid fraction separation using Sep-Pak NH2 columns (Waters Corporation, Milford, USA); and 3) methylation and separation of the phospholipids fraction from fatty acid by gas chromatography (Agilent Technologies, Wilmington, USA). The method was calibrated using the calibration mixture (Sigma-Aldrich, Steinheim, Germany). The fatty acids of the plasma phospholipid fraction were demonstrated in µmol/L.

Lp-PLA2 assessment

The Lp-PLA2 mass was measured with a colorimetric activity method using a rate reaction enzyme assay, with 1-myristoyl-2-(4-nitrophenylsuccinyl) phosphatidylcholine as the substrate. The assay precision ranged between 1.5% and 1.8%.

Bias and confounder

The study participants were all diagnosed with T2D and ASCVD, 2 conditions that have been linked to elevated levels of Lp-PLA2. As such, these conditions may exert an influence on the obtained measurements. Furthermore, the average age of the population under investigation was 65 years, which might have played a role in the expression of Lp-PLA2 or other relevant parameters. To minimize any potential sources of bias, laboratory measurements and statistical analyses were conducted by experienced personnel and were subject to double-checking protocols.

Other biomarkers

The levels of IL-6 and tumor necrosis factor alpha (TNF-α) were evaluated using an enzyme-linked immunosorbent assay (ELISA) (R&D Systems, Minneapolis, USA). Oxidized LDL (oxLDL) and myeloperoxidase were assessed with the use of an ELISA (Mercodia AB, Uppsala, Sweden). The hsCRP levels were measured using latex nephelometry (Dade Behring, Marburg, Germany).

Statistical analyses

Continuous variables were expressed as mean and standard deviation (M ±SD) or median (interquartile range (IQR)). Categorical variables were presented as numbers (percentages). The normality distribution was determined with the Shapiro–Wilk test. Student’s t-test or the Mann–Whitney U test was used to calculate the intergroup differences for continuous variables. The χ2 test was used to evaluate the differences in categorical variables between the study groups (with or without a Yates’s continuity correction or Fisher’s exact test). To assess the association between 2 continuous variables, Pearson or Spearman rank correlation coefficients were calculated (with a normal or non-normal distribution, respectively).

Both univariable and multivariable linear regression analyses were calculated to demonstrate the relationship between the Lp-PLA2 value and tested variables. We have built the optimal multivariable model from preselected variables (potential predictors) such as gender, systolic blood pressure, LDL-C, HbA1c, TG, body fat percentage, and visceral fat percentage, among others. Multicollinearity was assessed using variance inflation factors (VIFs). Hat values were used to investigate leveraging observations. The best model was obtained using stepwise (backward/forward) regression with Bayesian information criterion (BIC) as a target. The R2 was used to evaluate the goodness-of-fit for the final model. Validation was performed using the bootstrap method with 1000 replications.

The sample size was calculated based on our previous research, and it was powered to have a 90% chance of detecting a 15% difference in fibrin clot properties between the analyzed groups using a p-value of 0.05.19 To deliver that level of statistical power, at least 23 patients in each group were required.

All statistical tests were two-sided. A value of p < 0.05 was considered statistically significant.

All statistical analyses were calculated using Statistica v. 12.0 PL (StatSoft Polska, Kraków, Poland) and R 4.1.1 software (R Foundation for Statistical Computing, Vienna, Austria).

Results

Demographics and clinical description

The final analysis included 74 patients (49 (66.22%) males and 25 (33.78%) females) with both ASCVD and T2D (Table 1). The ages ranged from 47 to 85 years, and the female population was, on average, older than the male population (Table 1).

All subjects had a very high CV risk (e.g., T2D, obesity, hypertension, hyperlipidemia, and CAD), including 30 (40.6%) patients with a history of previous myocardial infarction (MI). There was no statistically significant difference between genders regarding risk factors and medical history, except for higher values in waist circumference in the male population. However, waist circumference did not correlate with Lp-PLA2 and was not an independent risk factor for increased Lp-PLA2 mass. However, despite a higher percentage of body fat (%) in the women subgroup, they had a lower concentration of Lp-PLA2. In contrast, male patients had higher values of visceral fat (%). Finally, in both analyzed groups, visceral fat (r = −0.17, p = 0.36 in males and r = −0.1, p = 0.72 in females) and body fat (r = −0.18, p = 0.24 in males and r = −0.02, p = 0.94 in females) were not associated with Lp-PLA2 mass.

In general, the female population had higher levels of HDL-C and lower levels of TG than the male population. Moreover, treatment regimens were not significantly different between genders (Supplementary Table 1). Despite the significant difference in age between males and females, there were no significant associations between Lp-PLA2 concentration and age in both males (r = 0.19, p = 0.19) and females (r = 0.30, p = 0.14).

Lp-PLA2 and inflammatory biomarkers

Based on our research, males had, on average, higher levels of Lp-PLA2 in the plasma than females (Table 2, Figure 1). Male gender positively correlated with the levels of Lp-PLA2 (r = 0.31, p = 0.006), and Lp-PLA2 was positively associated with IL-6 (r = 0.27, p = 0.019), creatinine level (r = 0.29, p = 0.03) and TG (r = 0.41, p = 0.002).

Interestingly, no differences were observed in the majority of analyzed inflammatory biomarkers (myeloperoxidase, IL-6, oxLDL, TNF-α, and hsCRP) between both genders, except for Lp-PLA2 (Table 2).

Finally, the presented multivariate model showed that female gender (decreasing Lp-PLA2 mass) and TG (increasing Lp-PLA2 mass) were independent predictors of Lp-PLA2 concentration (Table 3).

PUFA and Lp-PLA2

The PUFA concentrations did not differ between genders except for arachidic acid with linoleic acid (C20+C18:3(n-6)) concentration, which was higher in the female group (Supplementary Table 2). In the female population, there was a negative correlation between arachidonic acid (AA) and Lp-PLA2 mass (r = −0.53, p = 0.007). In contrast, the male subgroup did not show a significant correlation between AA and Lp-PLA2 mass. The correlations between PUFA plasma concentrations and the Lp-PLA2 mass are presented in Table 4.

Discussion

The main objective of this study was to determine the intergender differences in Lp-PLA2 levels in a very high CV risk population. We have demonstrated that the plasma mass levels of Lp-PLA2 were significantly higher in males compared to females in patients with both ASCVD and T2D. To the best of our knowledge, our study is the first to describe gender-related differences in plasma Lp-PLA2 levels in the analyzed patient population.

The collaborative data from 32 prospective studies showed that in both patients with stable ASCVD and without ASCVD, males had a higher Lp-PLA2 mass than females.10 However, the population of patients with T2D represented a small percentage of the analyzed population, and Lp-PLA2 activity and mass have been independent predictors of adverse CV events in T2D; therefore, they may be important markers in such populations.15 Our research showed similar findings. In the population of patients with T2D and ASCVD, males, on average, had higher levels of Lp-PLA2 than females. In support of our findings, it has been reported that in patients with vascular diseases such as cerebral stroke, males had higher levels of Lp-PLA2 than females.14

Contrary to those findings, Lu et al. reported that in a young population of patients after acute myocardial infarction (AMI), female gender was associated with higher levels of Lp-PLA2.20 This association could be explained by the fact that the analyzed female patients had higher inflammatory markers after AMI compared to males, which could translate to elevated levels of Lp-PLA2.20

A higher detected Lp-PLA2 mass was demonstrated to correlate with higher rates of adverse CV events.21 It was also shown that statins lower Lp-PLA2 levels by reducing the macrophage content in atherosclerotic lesions.22 Nevertheless, we reported that males had higher levels of Lp-PLA2 mass despite a similar proportion of statin therapy between both genders.

The association between T2D and chronic low-grade inflammation is a well-known fact, and it was shown that biomarkers such as interleukin-1β, vascular endothelial growth factor (VEGF) and Lp-PLA2 might play an important role in the occurrence of diabetic complications.23, 24

In a study by Siddiqui et al., it was reported that patients with poorly controlled T2D and high Lp-PLA2 activity had higher rates of major adverse cardiac events (MACE). This study investigated the association of Lp-PLA2 with metabolic control (HbA1c) in a diabetic population and its impact on MACE.

The Lp-PLA2 was reported to be related to endothelial damage, characterized by the weakening of the anticoagulant and anti-inflammatory functions of the endothelium,25 thereby making Lp-PLA2 a possible marker reflecting the extent of ASCVD.26 We have also observed that Lp-PLA2 is closely related to other markers of vascular inflammation, such as oxLDL, which is consistent with previous research.27

Interestingly, we demonstrated that Lp-PLA2 was the only analyzed inflammatory biomarker that varied between both genders in the researched population. The gender-related difference in Lp-PLA2 levels is particularly significant because Lp-PLA2 has been implicated as a potential biomarker for ASCVD. Therefore, the higher levels of Lp-PLA2 in men could be a contributing factor to the increased risk of adverse events.

Those results support the concept of Lp-PLA2 plasma levels as a useful marker of ASCVD,28 especially in the population with a very high CV risk.

We have demonstrated that females, despite a significantly higher body fat percentage, were characterized by substantially lower concentrations of Lp-PLA2 when compared to males. Interestingly, those differences were not associated with significant correlations between visceral or body fat percentage and Lp-PLA2 mass in both analyzed groups. Therefore, despite the higher body fat percentage, females appear to be associated with a lower level of visceral fat when compared to males, which may potentially be reflected in lower concentrations of Lp-PLA2 in women, but further research on a larger scale is needed in this regard.

In our study, males had higher values of waist circumference than females, which partly explained high Lp-PLA2 plasma levels in male patients. It was previously reported that adipose tissue can be an active source of Lp-PLA2.29, 30 However, we observed no correlation between these 2 variables, and waist circumference was not an independent risk factor for an increased Lp-PLA2 mass.

It is also important to mention that IL-6 and hsCRP are often present in obese patients,31 but in our research, they were not independent risk factors for an increased Lp-PLA2 mass. The Lp-PLA2 concentration may affect the development of ASCVD in men far beyond the issue of excessive body weight, abnormal abdominal circumference and the inflammatory state associated with obesity.

The beneficial effect of PUFA on ASCVD prevention is well established.17 It was also shown that the administration of PUFAs reduced the levels of Lp-PLA2 in ASCVD patients.16, 17 However, in our current study, out of all measured PUFAs, only the AA concentration was associated with lower Lp-PLA2 levels. This association was especially strong in the female subpopulation. A study by Steffen et al. and a study by Fragopoulou et al. demonstrated that AA levels negatively correlated with Lp-PLA2 mass when adjusted for covariates such as inflammation.32, 33, 34

In contrast to those findings, AA is well characterized for being inflammatory, but it also generates lipoxins – powerful non-classic eicosanoids that silence inflammatory signaling pathways33 and suppress an inducer of Lp-PLA2 expression.34

To date, there have been few studies that examined AA in the context of Lp-PLA2. However, based on our data and presented scientific papers, we could argue that a higher concentration of AA affects the inflammatory cascade in such a way that it may lower levels of Lp-PLA2, making AA an important tool in the treatment of patients at very high CV risk. However, further research is needed to fully examine the influence of AA on Lp-PLA2.

Limitations

We have several limitations to acknowledge. The cross-sectional nature of the study did not allow our research to infer causality. Moreover, there was no follow-up, and the sample size was limited. A larger observational study, including follow-up, would be beneficial to confirm our hypothesis. Third, the smaller number of female patients could have had an impact on the observed differences between measured parameters. Fourth, the treatment with statins and β-blockers, both of which can influence the levels of Lp-PLA2, were common in both analyzed subgroups. Additionally, it was suggested that the association between the Lp-PLA2 mass and atherosclerosis development in T2D patients may be weaker in subclinical ASCVD,35 but the association between T2D and its activity in more advanced atherosclerotic lesions remains strong.36 Further, the dietary pattern can differ between males and females, and its possible association with PUFA concentrations was not assessed. We are aware of the potential impact of dietary habits on Lp-PLA2 activity, but the goal of the present study was not to evaluate the influence of dietary patterns on Lp-PLA2 levels. Instead, our focus was to investigate the differences between genders and their associations with measured serum levels of monounsaturated fatty acids, and n-3 and n-6 PUFAs.

Another limitation of our study is that it relied solely on Lp-PLA2 mass, which may lead to the underdiagnosis of CV risk caused by increased LDL-C levels. Therefore, additional measurements of Lp-PLA2 activity may be used to mitigate the influence of LDL-C levels on Lp-PLA2 as a biomarker. Nevertheless, Lp-PLA2 mass measurements should be interpreted in conjunction with other laboratory tests, such as LDL-C, for better risk stratification.

The LDL-C levels may lead to the underdiagnosis of CV risk. However, assessing Lp-PLA2 activity can be beneficial in preventing this situation and enhancing risk assessment.

Conclusions

In conclusion, we demonstrated that in the population of patients with both ASCVD and T2D, males had higher plasma levels of Lp-PLA2 than females, thus making it a potential biomarker for the assessment of gender-related CV risk stratification. This study provides further evidence that AA plasma concentrations are negatively associated with Lp-PLA2 blood levels.

Supplementary data

The supplementary materials are available at https://doi.org/10.5281/zenodo.8169154. The package contains the following files:

Supplementary Table 1. Comparison of baseline characteristics of males compared to females in the studied population.

Supplementary Table 2. The gender differences in concentration of fatty acids in plasma.

Tables


Table 1. Baseline characteristics of the study population (n = 74)

Variable

All (n = 74)

Males (n = 49)

Females (n = 25)

p-value

Age

65.6 ±6.8

64.43 ±5.98

67.84 ±7.93

0.04

Risk factors

hypertension, n (%)

72 (97.3)

48 (98)

24 (96)

0.62

hyperlipidemia, n (%)

50 (67.6)

32 (65.3)

18 (72)

0.56

metabolic syndrome, n (%)

74 (100)

49 (100)

25 (100)

1.00

obesity, n (%)

49 (66.2)

37 (75.5)

12 (48)

0.018

waist circumference [cm]

106.5 ±9.4

109.43 ±9.11

100.78 ±7.13

0.0002

BMI [kg/m2]

31.2 ±3.6

31.66 ±3.19

30.34 ±4.10

0.13

visceral fat, %

16 ±4.67

18.16 ±3.79

11.81 ±3.10

<0.001

body fat, %

32.25 (28.40–41.58)

30.6 (25.8–33.2)

41.8 (35.1–47.4)

<0.001

current smoking, n (%)

28 (37.8)

18 (37)

10 (40)

0.78

Medical history

type 2 diabetes duration [years]

10 (6–15)

10 (6–12)

10 (6–20)

0.31

peripheral artery disease, n (%)

26 (35.1)

19 (38.8)

7 (28)

0.36

coronary artery disease, n (%)

74 (100)

49 (100)

25 (100)

1.00

previous MI, n (%)

28 (37.8)

19 (38.8)

9 (36)

0.82

NSTEMI, n (%)

15 (20.3)

10 (20.4)

5 (20)

0.79

STEMI, n (%)

15 (20.3)

11 (22.5)

4 (16)

0.73

Baseline laboratory investigations

HbA1c, %

7.24 ±0.94

7.23 ±1.04

7.2 ±0.7

0.36

eGFR [mL/min/1.73 m2]

77.9 ±14

77.88 ±13.68

77.86 ±14.88

0.97

TC [mmol/L]

3.86 ±0.91

3.85 ±0.98

3.9 ±0.8

0.89

LDL-C [mmol/L]

1.91 (1.53–2.64)

1.89 (1.47–2.84)

2.07 (1.53–2.59)

0.61

HDL-C [mmol/L]

1.24 ±0.38

1.17 ±0.36

1.4 ±0.4

0.049

TG [mmol/L]

1.35 (1.12–1.92)

1.46 (1.19–1.99)

1.18 (0.95–1.88)

0.08

AST [U/L]

19 (16–23)

18 (16–23)

19 (16–23)

0.71

ALT [U/L]

22 (14–28)

24 (14–31)

21 (12–25)

0.31

INR

0.98 (0.95–1.02)

0.98 (0.96–1)

0.96 (0.92–1.03)

0.29

aPTT [s]

25.6 (23.55–27.3)

25.75 (23.95–27.6)

25.35 (22.8–27.3)

0.28
BMI – body mass index; MI – myocardial infarction; NSTEMI – non-ST-elevation myocardial infarction; STEMI – ST-elevation myocardial infarction; HbA1c – glycated hemoglobin A1c; eGFR – estimated glomerular filtration rate; TC – total cholesterol; LDL-C – low-density lipoprotein cholesterol; HDL-C – high-density lipoprotein cholesterol; TG – triglycerides; AST – aspartate aminotransferase; ALT – alanine transaminase; INR – international normalized ratio; aPTT – activated partial thromboplastin time. Data are presented as mean ± standard deviation (M ±SD), median (interquartile range (IQR)), or number (percentage).
Table 2. Inflammatory status of the study population

Variable

Females (n = 25)

Males (n = 49)

p-value

oxLDL [mU/L]

62.50 (31.40–120.60)

55.50 (35.40–179.90)

0.76

Myeloperoxidase [ng/mL]

30.05 (16.28–54.42)

31.11 (21.58–44.44)

0.88

Lp-PLA2 [ng/mL]

109.40 (78.69–137.85)

146.21 (110.31–181.13)

0.006

TNF-α [pg/mL]

1.51 (1.31–1.85)

1.48 (1.28–1.71)

0.81

IL-6 [pg/mL]

1.93 (1.62–2.50)

2.01 (1.55–3.01)

0.82

hsCRP [mg/L]

1.64 (0.84–2.31)

1.54 (0.71–3.29)

0.99
oxLDL – oxidized low-density lipoprotein; Lp-PLA2 – lipoprotein-associated phospholipase A2; TNF-α – tumor necrosis factor alpha; IL-6 – interleukin 6; hsCRP – high-sensitivity C-reactive protein. Data are presented as median (interquartile range (IQR)).
Table 3. Independent predictors of lipoprotein-associated phospholipase A2 (Lp-PLA2) – a multivariable linear regression model

Variable

β

95% CI

Standard error

t value

p-value

Female gender

−33.84

−63.58; −4.10

14.86

−2.28

0.026

Body fat (%)

−1.15

−2.78; 0.48

0.81

−1.42

0.16

TG

29.13

12.27; 45.99

8.43

3.46

0.001

oxLDL

0.03

−0.02; 0.08

0.02

1.28

0.20
TG – triglycerides; oxLDL – oxidized low-density lipoprotein; ICAM-1 – intercellular adhesion molecule-1; β – coefficient; 95% CI – 95% confidence interval.
Table 4. Correlation between lipoprotein-associated phospholipase A2 (Lp-PLA2) plasma levels and fatty acid concentration in plasma

Variable

All (n = 74)

Females (n = 25)

Males (n = 49)

C12

r = −0.21, p = 0.079

r = 0.13, p = 0.54

r = 0.18, p = 0.22

C14

r = 0.02, p = 0.84

r = −0.24, p = 0.25

r = 0.16, p = 0.29

C16

r = 0.08, p = 0.52

r = −0.21, p = 0.32

r = −0.05, p = 0.72

C16:1

r = 0.03, p = 0.78

r = −0.29, p = 0.17

r = 0.14, p = 0.35

C18

r = −0.1, p = 0.4

r = −0.23, p = 0.26

r = −0.26, p = 0.07

C18:1

r = −0.06, p = 0.64

r = −0.14, p = 0.51

r = −0.02, p = 0.87

C18:2(n-6)

r = 0.11, p = 0.34

r = −0.004, p = 0.98

r = 0.17, p = 0.25

C18:3(n-3)

r = 0.08, p = 0.48

r = 0.2, p = 0.33

r = 0.16, p = 0.28

C20+C18:3(n-6)

r = −0.09, p = 0.46

r = −0.14, p = 0.51

r = 0.04, p = 0.78

C20:2(n-6)

r = 0.08, p = 0.51

r = 0.17, p = 0.43

r = 0.06, p = 0.7

C20:4 (AA)

r = −0.26, p = 0.024

r = −0.53, p = 0.007

r = −0.16, p = 0.27

C20:5(n-3)

r = −0.004, p = 0.98

r = −0.2, p = 0.33

r = 0.02, p = 0.87

C24

r = −0.08, p = 0.53

r = −0.34, p = 0.1

r = −0.03, p = 0.86

C22:6(n-3)

r = −0.02, p = 0.85

r = −0.06, p = 0.79

r = −0.08, p = 0.57
C12 − lauric acid; C14 − myristic acid; C16 − palmitic acid; C16:1 − palmitoleic acid; C18 − stearic acid; C18:1 − oleic acid; C18:2(n-6) − linoleic acid; C18:3(n-3) − alpha-linolenic acid; C20+C18:3(n-6) − arachidic acid with linoleic acid; C20:2(n-6) − eicosadienoic acid; C20:4 (AA) − arachidonic acid; C20:5(n-3) − eicosapentaenoic acid; C24 − lignoceric acid; C22:6(n-3) − docosahexaenoic acid. Data are presented as Pearson’s correlation coefficient with a p-value.

Figures


Fig. 1. Lipoprotein-associated phospholipase A2 (Lp-PLA2) concentration between men and women with both atherosclerotic cardiovascular disease (ASCVD) and type 2 diabetes (T2D). The horizontal line represents the mean, and the upper and lower bars represent the standard deviation from the mean

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