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Abstract

Aims

Elevated maternal cholesterol during pregnancy (MCP) enhances atherogenesis in childhood, but its possible impact on acute myocardial infarction (AMI) in adults is unknown.

Methods and results

We retrospectively evaluated 310 patients who were admitted to hospital and whose MCP data were retrievable. Eighty-nine AMI patients with typical chest pain, transmural infarction Q-waves, elevated creatinine kinase, and 221 controls hospitalized for other reasons were identified. The AMI cohort was classified by MI severity (severe = involving three arteries, left ventricle ejection fraction ≤35, CK-peak >1200 mg/dL, or CK-MB >200 mg/dL). The association of MCP with AMI severity was tested by linear and multiple regression analysis that included conventional cardiovascular risk factors, gender, age, and treatment. Associations of MCP with body mass index (BMI) in patients were assessed by linear correlation. In the AMI cohort, MCP correlated with four measures of AMI severity: number of vessels (β = 0.382, P = 0.001), ejection fraction (β = −0.315, P = 0.003), CK (β = 0.260, P = 0.014), and CK-MB (β = 0.334, P = 0.001), as well as survival time (β = −0.252, P = 0.031). In multivariate analysis of patients stratified by AMI severity, MCP predicted AMI severity independently of age, gender, BMI, and CHD risk factors (odds ratio = 1.382, 95% confidence interval 1.046–1.825; P = 0.023). Survival was affected mainly by AMI severity.

Conclusions

Maternal cholesterol during pregnancy is associated with adult BMI, atherosclerosis-related risk, and severity of AMI.

Graphical Abstract
Graphical Abstract
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Graphical Abstract
Graphical Abstract
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Cholesterol, Pregnancy, Developmental programming, Cardiovascular disease

Introduction

Early atherogenic processes in the human aorta begin during foetal development and are accelerated by maternal hypercholesterolaemia during pregnancy, even if the latter is only temporary.1,2 Maternal hypercholesterolaemia is also associated with greatly accelerated atherogenesis in normocholesterolaemic children, as shown by the FELIC study.3 In experimental models lacking the genetic and dietary variability of humans, postnatal atherosclerosis increases in proportion to the maternal cholesterol levels well into adult ages.4,5 A molecular mechanism explaining the transfer of maternal cholesterol to the foetus has been elucidated,6 the involvement of increased oxidative stress has been established4,5,7,8 and the beneficial effect of lowering maternal cholesterol levels before and during pregnancy by pharmacological interventions or immune modulation has been shown in preclinical models.4,5,9,10

The absence of routine cholesterol determinations during gestation in most countries has limited investigations of the impact of elevated maternal cholesterol during pregnancy (MCP) on clinical manifestations in adult offspring. However, a recent study in patients from the Framingham Heart Study indicated that gestational hypercholesterolaemia can be assumed in mothers who are hypercholesterolaemic both before and after pregnancy, and that maternal dyslipidaemia is predictive of dyslipidaemia in their offspring.11 Adults who had been exposed to elevated maternal LDL-C levels had 3.8 times higher odds of having elevated LDL-C levels, and this explained 13% of the variation in adult offspring LDL-C levels beyond common genetic variants and classic risk factors for elevated LDL-C levels.11 A positive association has also been reported between maternal cholesterol and new-born HDL cholesterol and subclasses.12 Furthermore, in 78 foetal aortas maternal cholesterol explained 61% of the variance of early lesion sizes in multivariate analysis independently of HDL-C, triglycerides, glucose and body mass index (BMI). Maternal total cholesterol and LDLC levels were positively associated with methylation of SREBP2 in foetal aortas, suggesting a role of maternal cholesterol level during pregnancy on epigenetic signature in offspring.13 Now, we have the detailed mapping of SREBP2 methylation.14 It remains, however, unknown whether maternal hypercholesterolaemia affects the long-term progression of atherosclerosis and, more importantly, its clinical manifestations.15,16 Establishing this would be important, because in contrast to inherited genetic risk, increased susceptibility to atherogenesis resulting from developmental programming may be prevented by brief dietary or other interventions in mothers.10 Remarkably, in several cohort studies, whole blood DNA methylation signatures of diet are associated with cardiovascular (CV) disease risk.17 The main aim of this retrospective study was to investigate the association between MCP and the long-term effects on coronary events in their offspring.

Methods

The present study encompasses a cohort of patients from seven hospitals in the Regione Campania (the region surrounding Naples) an area in which developmental programming of offspring CV disease in hypercholesterolaemic mothers has been previously studied.13,18–20 Between January 1991 and April 2019, 12 327 patients admitted with the diagnosis of AMI were screened. To reduce potential bias in patient’s selection, we restricted analysis to subjects born after World War II, because data on maternal cholesterol before that period were scarce. For the 3357 subjects born after 1945 initially identified, we sought to obtain maternal cholesterol data from records of the hospital where the mother had undergone prenatal exams. These were obtained from the AMI patients by phone or at follow-up evaluation. In 3123 cases, we were unable to obtain such data because of unavailability of maternal records (1972 cases), inaccessibility of prenatal exams (902 cases), or unwillingness of AMI patients to participate in the study (249 cases). Of the remaining 234 cases, 135 did not meet the following criteria used to define AMI: (i) typical chest pain and electrocardiographic changes with Q waves indicating transmural infarction; (ii) elevated creatinine kinase concentrations, (iii) availability of coronary angiography and echocardiogram. The number of AMI-patients (n = 99) was further reduced by exclusion of 10 subjects with terminal illness or cerebrovascular disease. While admitted, all patients received thrombolytic therapy. Parameters collected from the patients' medical records at the time of hospitalization included: age at the time of AMI, gender, and number of major CV risk factors prior to the AMI: obesity, diabetes, smoking (past and/or present), hypertension (arterial pressure ≥ 140/90 mmHg), family history of CHD, family history of hypercholesterolaemia, and angina at any time prior to the AMI (all assessed as ‘yes/no’), as well as drug treatment prior to AMI (ACE-inhibitors, beta-blockers, statins, aspirin; yes/no). Together with mean MCP obtained during the first and the second trimester of pregnancy, these parameters were considered to be potential predictors of AMI severity. The four parameters directly reflecting AMI severity were: the extent of coronary arteriosclerosis, expressed as the number of coronary arteries involved (i.e. showing greater than 75% stenosis), left ventricular function measured by echocardiography and expressed as % of normal ejection volume during the acute phase of AMI, creatinine kinase (CK) peak, and CK-MB peak. Other data obtained during initial hospitalization that may be either co-contributor or influenced by AMI severity included blood pressure, C-reactive protein (CRP), and plasma lipids (total, LDL, and HDL cholesterol). The outcome of AMI was assessed as death in the coronary care unit (n = 11) and length of survival during 5-year follow-up. For all 22 patients who died during the follow-up period, a CV cause of death was established from hospital records (n = 17) or death certificates or contact with the patient's cardiologist (n = 4) or physician (n = 1). The local ethical committee approved this study (Code# 09/03).

Controls fell into four broad diagnostic groups; patients admitted for cerebrovascular conditions (n = 38), surgical patients (n = 90), patients admitted for infections or sepsis (n = 35), and other diagnoses (n = 58). However, this additional control group with such heterogeneity may be confusing (i.e. infection and sepsis), thus, we presented these results only as supplementary data restricting the major focus on MCP, BMI, CV risk factors, and AMI severity.

Statistical methods

Data were analysed with SPSS software. Results are reported as mean ± SD. Initial analysis of the AMI group: Normal distribution of scalar parameters was assessed by Kolmogorov–Smirnov assay. All parameters were normal-distributed, except BMI, CRP, SSA, and diastolic BP. Log-transformation improved CRP normality and slightly improved that of BMI, but not diastolic BP, which was therefore excluded from further analysis. The association between MCP (independent parameter) and age, measures of AMI severity, and 5-year survival (dependent parameters) was determined by linear regression analysis. To assess which parameters determine the severity of AMI and survival, patients were stratified into severe and non-severe. Severe AMI was defined as meeting at least one of the following criteria: Left ventricle ejection fraction ≤ 35%, CK-peak > 1200 mg/dL, CK-MB peak > 200 mg/dL, presence of three vessel disease.18–20 Differences between the resulting two severity groups in categorical parameters, i.e., gender, diabetes, hypertension, obesity (BMI ≥ 30), previous angina, familiar history of coronary heart disease, familiar history of hypercholesterolaemia, therapy (ACE-inhibitor, beta blockers, statin, and aspirin), in-hospital death, death at follow-up, and overall mortality were established by χ2 analyses. Differences in scalar parameters, i.e., age, MCP, patients' total, LDL and HDL cholesterol and triglycerides after the AMI, BMI, CPR, systolic blood pressure, left ventricle ejection fraction, CK-peak, CK-MB peak, and the number of vessels with lesions causing > 75% stenosis, were evaluated by one-way ANOVA. Logistic regression analysis was used to evaluate the association of maternal cholesterol with dichotomous AMI severity, including gender, age, BMI, number of risk factors, and total cholesterol measured soon after hospitalization as covariates. For this purpose, MCP was stratified by 10 mg/dL increments. Cox regression analysis was used to evaluate the independent effect on overall mortality of gender, age, MCP, BMI, and number of risk factors. P < 0.05 was considered significant. Comparisons between AMI and control groups were done by ANOVA and unpaired t-test. Correlations between parameters in pooled data of all AMI and control subjects were assessed by pairwise Pearson’s two-tailed linear correlation or for scalar parameters, by linear correlation and linear regression analysis.

Results

The initial population of AMI patients is characterized in Table 1. As expected, the vast majority of the 89 patients suffering AMI at relatively young age (47.0 ± 5.0 years) were male (84.3%). The frequency of MCP in a normal maternal population is that 72.3% of mothers met the definition of hypercholesterolaemia in current guidelines (MCP >240 mg/dL).21 We first examined the correlation between MCP and the age at which the AMI occurred, several measures of AMI severity, and other scalar parameters unaffected by the severity of the AMI, using linear regression analysis (Table 2). Maternal cholesterol during pregnancy showed no significant correlation with age. In contrast, there were strong correlations with all four measures of AMI severity, i.e., the number of coronary arteries involved (β = 0.382, P = 0.001) (Figure 1A), the reduction of left ventricle ejection fraction (β = −0.315, P = 0.003) (Figure 1B), the CK-MB peak (β = 0.334, P = 0.001) (Figure 1C), and the CK peak (β = 0.260, P = 0.014) (Figure 1D). No correlation was found between MCP and the number of risk factors, but BMI showed a strong positive correlation (β = 0.845, P = 0.001) (Table 2).

Figure 1.
Correlation between maternal cholesterol during pregnancy and acute myocardial infarction severity, i.e., the number of coronary arteries involved (A), the reduction of left ventricle ejection fraction (B), the CK-MB peak (C), and the CK peak (D).
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Correlation between maternal cholesterol during pregnancy and acute myocardial infarction severity, i.e., the number of coronary arteries involved (A), the reduction of left ventricle ejection fraction (B), the CK-MB peak (C), and the CK peak (D).

Figure 1.
Correlation between maternal cholesterol during pregnancy and acute myocardial infarction severity, i.e., the number of coronary arteries involved (A), the reduction of left ventricle ejection fraction (B), the CK-MB peak (C), and the CK peak (D).
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Correlation between maternal cholesterol during pregnancy and acute myocardial infarction severity, i.e., the number of coronary arteries involved (A), the reduction of left ventricle ejection fraction (B), the CK-MB peak (C), and the CK peak (D).

Table 1

Clinical characteristics and main outcomes of the acute myocardial infarction group

Parameter
Number of patients 89 (75 males, 14 females) 
Age (years; range) 47.0 ± 5.0 (36–56) 
Maternal cholesterol during pregnancy (mg/dL; range) 268.8 ± 37.9 (177–356) 
 ‘Normal’ [<240 mg/dL] (n; %) 22 (24.7) 
 ‘High’ [≥240 mg/dL] (n; %) 67 (75.3) 
Cardiovascular risk factors:  
 Obesity [BMI > 30] (n; %) 30 (33.7) 
 Smoking [past and/or present] (n; %) 54 (60.7) 
 Hypertension [≥140/90 mmHg] (n; %) 27 (30.3) 
 Family history of CHD (n; %) 48 (53.9) 
 Diabetes (n; %) 19 (21.3) 
 Family history of hypercholesterolaemia (n; %) 23 (25.8) 
 Prior angina (n; %) 39 (43.8) 
Number of risk factors (n; range) 2.7 ± 1.5 (0–7) 
Drug treatment prior to AMI:  
 ACE-inhibitors (n; %) 14 (15.7) 
 Beta-blockers (n; %) 11 (12.4) 
 Statins (n; %) 8 (9.0) 
 Aspirin (n; %) 23 (25.8) 
AMI location:  
 Left anterior descending (n) 37 
 Circumflex (n) 44 
 Right anterior (n) 8 
Parameters of AMI severity:  
 Number of coronaries with >75% stenosis involved (n; range) 1.82 ± 0.67 (1–3) 
 Left ventricle ejection fraction during AMI (%; range) 44.17 ± 6.14 (30–56) 
 CK peak (IU; range) 1085.6 ± 240.5 (665–1678) 
 CK-MB peak (IU; range) 146.0 ± 67.5 (56–306) 
Laboratory parameters in hospital, after AMI: 
 Blood pressure, systolic (mmHg) 101.0 ± 10.4 
 C-reactive protein (mg/L) 5.45 ± 2.66 
 Total plasma cholesterol (mg/dL) 208.9 ± 27.5 
 LDL cholesterol, calculated (mg/dL) 131.6 ± 26.5 
 HDL cholesterol (mg/dL) 39.4 ± 4.3 
 Triglycerides (mg/dL) 189.6 ± 2.7 
Outcome:  
 In-hospital death (n) 11 (12.4 %) 
 Death during 5-year follow-up (n; %) 22 (24.7 %) 
 Alive after 5 years (n; %) 56 (62.9 %) 
Survival length of all 83 patients (months) 46.5 ± 21.3 
Parameter
Number of patients 89 (75 males, 14 females) 
Age (years; range) 47.0 ± 5.0 (36–56) 
Maternal cholesterol during pregnancy (mg/dL; range) 268.8 ± 37.9 (177–356) 
 ‘Normal’ [<240 mg/dL] (n; %) 22 (24.7) 
 ‘High’ [≥240 mg/dL] (n; %) 67 (75.3) 
Cardiovascular risk factors:  
 Obesity [BMI > 30] (n; %) 30 (33.7) 
 Smoking [past and/or present] (n; %) 54 (60.7) 
 Hypertension [≥140/90 mmHg] (n; %) 27 (30.3) 
 Family history of CHD (n; %) 48 (53.9) 
 Diabetes (n; %) 19 (21.3) 
 Family history of hypercholesterolaemia (n; %) 23 (25.8) 
 Prior angina (n; %) 39 (43.8) 
Number of risk factors (n; range) 2.7 ± 1.5 (0–7) 
Drug treatment prior to AMI:  
 ACE-inhibitors (n; %) 14 (15.7) 
 Beta-blockers (n; %) 11 (12.4) 
 Statins (n; %) 8 (9.0) 
 Aspirin (n; %) 23 (25.8) 
AMI location:  
 Left anterior descending (n) 37 
 Circumflex (n) 44 
 Right anterior (n) 8 
Parameters of AMI severity:  
 Number of coronaries with >75% stenosis involved (n; range) 1.82 ± 0.67 (1–3) 
 Left ventricle ejection fraction during AMI (%; range) 44.17 ± 6.14 (30–56) 
 CK peak (IU; range) 1085.6 ± 240.5 (665–1678) 
 CK-MB peak (IU; range) 146.0 ± 67.5 (56–306) 
Laboratory parameters in hospital, after AMI: 
 Blood pressure, systolic (mmHg) 101.0 ± 10.4 
 C-reactive protein (mg/L) 5.45 ± 2.66 
 Total plasma cholesterol (mg/dL) 208.9 ± 27.5 
 LDL cholesterol, calculated (mg/dL) 131.6 ± 26.5 
 HDL cholesterol (mg/dL) 39.4 ± 4.3 
 Triglycerides (mg/dL) 189.6 ± 2.7 
Outcome:  
 In-hospital death (n) 11 (12.4 %) 
 Death during 5-year follow-up (n; %) 22 (24.7 %) 
 Alive after 5 years (n; %) 56 (62.9 %) 
Survival length of all 83 patients (months) 46.5 ± 21.3 
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Table 1

Clinical characteristics and main outcomes of the acute myocardial infarction group

Parameter
Number of patients 89 (75 males, 14 females) 
Age (years; range) 47.0 ± 5.0 (36–56) 
Maternal cholesterol during pregnancy (mg/dL; range) 268.8 ± 37.9 (177–356) 
 ‘Normal’ [<240 mg/dL] (n; %) 22 (24.7) 
 ‘High’ [≥240 mg/dL] (n; %) 67 (75.3) 
Cardiovascular risk factors:  
 Obesity [BMI > 30] (n; %) 30 (33.7) 
 Smoking [past and/or present] (n; %) 54 (60.7) 
 Hypertension [≥140/90 mmHg] (n; %) 27 (30.3) 
 Family history of CHD (n; %) 48 (53.9) 
 Diabetes (n; %) 19 (21.3) 
 Family history of hypercholesterolaemia (n; %) 23 (25.8) 
 Prior angina (n; %) 39 (43.8) 
Number of risk factors (n; range) 2.7 ± 1.5 (0–7) 
Drug treatment prior to AMI:  
 ACE-inhibitors (n; %) 14 (15.7) 
 Beta-blockers (n; %) 11 (12.4) 
 Statins (n; %) 8 (9.0) 
 Aspirin (n; %) 23 (25.8) 
AMI location:  
 Left anterior descending (n) 37 
 Circumflex (n) 44 
 Right anterior (n) 8 
Parameters of AMI severity:  
 Number of coronaries with >75% stenosis involved (n; range) 1.82 ± 0.67 (1–3) 
 Left ventricle ejection fraction during AMI (%; range) 44.17 ± 6.14 (30–56) 
 CK peak (IU; range) 1085.6 ± 240.5 (665–1678) 
 CK-MB peak (IU; range) 146.0 ± 67.5 (56–306) 
Laboratory parameters in hospital, after AMI: 
 Blood pressure, systolic (mmHg) 101.0 ± 10.4 
 C-reactive protein (mg/L) 5.45 ± 2.66 
 Total plasma cholesterol (mg/dL) 208.9 ± 27.5 
 LDL cholesterol, calculated (mg/dL) 131.6 ± 26.5 
 HDL cholesterol (mg/dL) 39.4 ± 4.3 
 Triglycerides (mg/dL) 189.6 ± 2.7 
Outcome:  
 In-hospital death (n) 11 (12.4 %) 
 Death during 5-year follow-up (n; %) 22 (24.7 %) 
 Alive after 5 years (n; %) 56 (62.9 %) 
Survival length of all 83 patients (months) 46.5 ± 21.3 
Parameter
Number of patients 89 (75 males, 14 females) 
Age (years; range) 47.0 ± 5.0 (36–56) 
Maternal cholesterol during pregnancy (mg/dL; range) 268.8 ± 37.9 (177–356) 
 ‘Normal’ [<240 mg/dL] (n; %) 22 (24.7) 
 ‘High’ [≥240 mg/dL] (n; %) 67 (75.3) 
Cardiovascular risk factors:  
 Obesity [BMI > 30] (n; %) 30 (33.7) 
 Smoking [past and/or present] (n; %) 54 (60.7) 
 Hypertension [≥140/90 mmHg] (n; %) 27 (30.3) 
 Family history of CHD (n; %) 48 (53.9) 
 Diabetes (n; %) 19 (21.3) 
 Family history of hypercholesterolaemia (n; %) 23 (25.8) 
 Prior angina (n; %) 39 (43.8) 
Number of risk factors (n; range) 2.7 ± 1.5 (0–7) 
Drug treatment prior to AMI:  
 ACE-inhibitors (n; %) 14 (15.7) 
 Beta-blockers (n; %) 11 (12.4) 
 Statins (n; %) 8 (9.0) 
 Aspirin (n; %) 23 (25.8) 
AMI location:  
 Left anterior descending (n) 37 
 Circumflex (n) 44 
 Right anterior (n) 8 
Parameters of AMI severity:  
 Number of coronaries with >75% stenosis involved (n; range) 1.82 ± 0.67 (1–3) 
 Left ventricle ejection fraction during AMI (%; range) 44.17 ± 6.14 (30–56) 
 CK peak (IU; range) 1085.6 ± 240.5 (665–1678) 
 CK-MB peak (IU; range) 146.0 ± 67.5 (56–306) 
Laboratory parameters in hospital, after AMI: 
 Blood pressure, systolic (mmHg) 101.0 ± 10.4 
 C-reactive protein (mg/L) 5.45 ± 2.66 
 Total plasma cholesterol (mg/dL) 208.9 ± 27.5 
 LDL cholesterol, calculated (mg/dL) 131.6 ± 26.5 
 HDL cholesterol (mg/dL) 39.4 ± 4.3 
 Triglycerides (mg/dL) 189.6 ± 2.7 
Outcome:  
 In-hospital death (n) 11 (12.4 %) 
 Death during 5-year follow-up (n; %) 22 (24.7 %) 
 Alive after 5 years (n; %) 56 (62.9 %) 
Survival length of all 83 patients (months) 46.5 ± 21.3 
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Table 2

Linear correlations between maternal cholesterol during pregnancy, age at myocardial infarction, acute myocardial infarction severity, and risk factors

Dependent variableBeta coefficientP
Age −0.088 0.412 
Number of vessels involved 0.382 0.000 
Left ventricle ejection fraction −0.315 0.003 
CK peak 0.260 0.014 
CK-MB peak 0.334 0.001 
Number of risk factors 0.251 0.271 
BMI (log-transformed) 0.845 0.000 
Survival −0.232 0.031 
Dependent variableBeta coefficientP
Age −0.088 0.412 
Number of vessels involved 0.382 0.000 
Left ventricle ejection fraction −0.315 0.003 
CK peak 0.260 0.014 
CK-MB peak 0.334 0.001 
Number of risk factors 0.251 0.271 
BMI (log-transformed) 0.845 0.000 
Survival −0.232 0.031 
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Table 2

Linear correlations between maternal cholesterol during pregnancy, age at myocardial infarction, acute myocardial infarction severity, and risk factors

Dependent variableBeta coefficientP
Age −0.088 0.412 
Number of vessels involved 0.382 0.000 
Left ventricle ejection fraction −0.315 0.003 
CK peak 0.260 0.014 
CK-MB peak 0.334 0.001 
Number of risk factors 0.251 0.271 
BMI (log-transformed) 0.845 0.000 
Survival −0.232 0.031 
Dependent variableBeta coefficientP
Age −0.088 0.412 
Number of vessels involved 0.382 0.000 
Left ventricle ejection fraction −0.315 0.003 
CK peak 0.260 0.014 
CK-MB peak 0.334 0.001 
Number of risk factors 0.251 0.271 
BMI (log-transformed) 0.845 0.000 
Survival −0.232 0.031 
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Maternal cholesterol during pregnancy also correlated with some parameters measured shortly after the AMI: total plasma cholesterol (β = 0.373, P = 0.001), log-transformed CRP (β = 0.248, P = 0.020), but not systolic blood pressure (β = −0.138, P = 0.196), HDL-C (β = −0.017, P = 0.880), or triglycerides (β = −0.041, P = 0.700). However, these associations are less meaningful, because they may reflect the effect of AMI severity on post-AMI measurements rather than a direct effect of MCP.

To test the effect of MCP on AMI in the presence of cofactors, a composite measure of AMI severity was used. Patients classified as having severe AMI (3 vessel disease, left ventricle ejection fraction ≤ 35%, CK-peak > 1200 mg/dL, or CK-MB > 200 mg/dL) were significantly worse in all 4 original measures of AMI severity than patients with less severe AMI (Table 3). The two groups were then compared (Table 4). The 33 subjects with severe AMI were younger and had higher MCP. They also had more risk factors and were more obese. No differences were observed in smoking habits, previous angina, CHD history, dyslipidaemias, and diabetes. The treatment with ACE-inhibitors, beta-blockers, statins, and acetylsalicylic acid was similar. In-hospital deaths, mortality during the 5 years follow-up period and overall mortality were higher in subjects with severe AMI (Table 3).

Table 3

Patient stratification by acute myocardial infarction severity

VariablesSevere AMI
No (n = 56)Yes (n = 33)P
Number of vessels affected 1.6 ± 0.5 2.3 ± 0.7 0.000 
Left ventricle ejection fraction 46.2 ± 5.4 40.8 ± 6.2 0.000 
CK peak 943.9 ± 134.6 1325.9 ± 181.0 0.000 
MB peak 107.0 ± 33.7 211.7 ± 59.7 0.000 
VariablesSevere AMI
No (n = 56)Yes (n = 33)P
Number of vessels affected 1.6 ± 0.5 2.3 ± 0.7 0.000 
Left ventricle ejection fraction 46.2 ± 5.4 40.8 ± 6.2 0.000 
CK peak 943.9 ± 134.6 1325.9 ± 181.0 0.000 
MB peak 107.0 ± 33.7 211.7 ± 59.7 0.000 
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Table 3

Patient stratification by acute myocardial infarction severity

VariablesSevere AMI
No (n = 56)Yes (n = 33)P
Number of vessels affected 1.6 ± 0.5 2.3 ± 0.7 0.000 
Left ventricle ejection fraction 46.2 ± 5.4 40.8 ± 6.2 0.000 
CK peak 943.9 ± 134.6 1325.9 ± 181.0 0.000 
MB peak 107.0 ± 33.7 211.7 ± 59.7 0.000 
VariablesSevere AMI
No (n = 56)Yes (n = 33)P
Number of vessels affected 1.6 ± 0.5 2.3 ± 0.7 0.000 
Left ventricle ejection fraction 46.2 ± 5.4 40.8 ± 6.2 0.000 
CK peak 943.9 ± 134.6 1325.9 ± 181.0 0.000 
MB peak 107.0 ± 33.7 211.7 ± 59.7 0.000 
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Table 4

Maternal cholesterol during pregnancy, age, cardiovascular risk factors, and treatments of acute myocardial infarction patients

VariablesSevere AMI
No (n = 56)Yes (n = 33)P
Maternal cholesterol 255.3 ± 35.3 283.9 ± 40.7 0.001 
Obesity (%) 16.1 63.6 0.000 
Smoking (%) 58.9 63.6 0.417 
Hypertension (%) 23.2 42.2 0.049 
Angina (%) 42.9 45.5 0.492 
CHD history (%) 53.6 54.5 0.553 
TC history (%) 17.9 39.4 0.024 
Diabetes (%) 17.9 27.3 0.217 
Number of risk factors (n) 2.3 ± 1.2 3.4 ± 1.8 0.001 
ACE inhibitor (%) 17.9 12.1 0.345 
Beta-blocker (%) 12.5 12.1 0.618 
Statins (%) 8.9 9.1 0.629 
Aspirin (%) 28.6 21.2 0.306 
In-hospital death (%) 7.1 21.2 0.055 
Deaths during follow-up (%) 14.3 42.4 0.004 
Death (%) 21.4 63.6 0.000 
VariablesSevere AMI
No (n = 56)Yes (n = 33)P
Maternal cholesterol 255.3 ± 35.3 283.9 ± 40.7 0.001 
Obesity (%) 16.1 63.6 0.000 
Smoking (%) 58.9 63.6 0.417 
Hypertension (%) 23.2 42.2 0.049 
Angina (%) 42.9 45.5 0.492 
CHD history (%) 53.6 54.5 0.553 
TC history (%) 17.9 39.4 0.024 
Diabetes (%) 17.9 27.3 0.217 
Number of risk factors (n) 2.3 ± 1.2 3.4 ± 1.8 0.001 
ACE inhibitor (%) 17.9 12.1 0.345 
Beta-blocker (%) 12.5 12.1 0.618 
Statins (%) 8.9 9.1 0.629 
Aspirin (%) 28.6 21.2 0.306 
In-hospital death (%) 7.1 21.2 0.055 
Deaths during follow-up (%) 14.3 42.4 0.004 
Death (%) 21.4 63.6 0.000 
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Table 4

Maternal cholesterol during pregnancy, age, cardiovascular risk factors, and treatments of acute myocardial infarction patients

VariablesSevere AMI
No (n = 56)Yes (n = 33)P
Maternal cholesterol 255.3 ± 35.3 283.9 ± 40.7 0.001 
Obesity (%) 16.1 63.6 0.000 
Smoking (%) 58.9 63.6 0.417 
Hypertension (%) 23.2 42.2 0.049 
Angina (%) 42.9 45.5 0.492 
CHD history (%) 53.6 54.5 0.553 
TC history (%) 17.9 39.4 0.024 
Diabetes (%) 17.9 27.3 0.217 
Number of risk factors (n) 2.3 ± 1.2 3.4 ± 1.8 0.001 
ACE inhibitor (%) 17.9 12.1 0.345 
Beta-blocker (%) 12.5 12.1 0.618 
Statins (%) 8.9 9.1 0.629 
Aspirin (%) 28.6 21.2 0.306 
In-hospital death (%) 7.1 21.2 0.055 
Deaths during follow-up (%) 14.3 42.4 0.004 
Death (%) 21.4 63.6 0.000 
VariablesSevere AMI
No (n = 56)Yes (n = 33)P
Maternal cholesterol 255.3 ± 35.3 283.9 ± 40.7 0.001 
Obesity (%) 16.1 63.6 0.000 
Smoking (%) 58.9 63.6 0.417 
Hypertension (%) 23.2 42.2 0.049 
Angina (%) 42.9 45.5 0.492 
CHD history (%) 53.6 54.5 0.553 
TC history (%) 17.9 39.4 0.024 
Diabetes (%) 17.9 27.3 0.217 
Number of risk factors (n) 2.3 ± 1.2 3.4 ± 1.8 0.001 
ACE inhibitor (%) 17.9 12.1 0.345 
Beta-blocker (%) 12.5 12.1 0.618 
Statins (%) 8.9 9.1 0.629 
Aspirin (%) 28.6 21.2 0.306 
In-hospital death (%) 7.1 21.2 0.055 
Deaths during follow-up (%) 14.3 42.4 0.004 
Death (%) 21.4 63.6 0.000 
Open in new tab

Variables included in the analysis were those statistically different in univariate analysis, except for gender, which was included because of the clinical relevance of gender in adult AMI. BMI was included because obesity was retained as independent variable for the association found in univariate analysis but not considered in the joint variable ‘Risk Factors’. Logistic regression analysis demonstrated that maternal cholesterol during pregnancy predicts the occurrence of severe AMI [odds ratio (OR) = 1.382, 95% confidence interval (CI) = 1.046–1.825; P = 0.023] independently of the effect of age, gender, BMI and number of risk factors (OR = 1.669, 95% CI = 1.099–2.534, P = 0.016) and total-C (Supplementary material online, Table S1).

Linear correlation between MCP and length of survival indicated a significant correlation (β = −0.232, P = 0.031) (Table 2). We therefore used Cox regression analysis to further explore this, but only the severity of AMI predicted mortality independently of the effect of age, gender, number of risk factors, and MCP (HR = 2.619; 95% CI 1.030–6.659, P = 0.043) (Figure 2 and Supplementary material online, Table S2).

Figure 2
Cox regression analysis of acute myocardial infarction severity and 5-year survival.
Open in new tabDownload slide

Cox regression analysis of acute myocardial infarction severity and 5-year survival.

Figure 2
Cox regression analysis of acute myocardial infarction severity and 5-year survival.
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Cox regression analysis of acute myocardial infarction severity and 5-year survival.

Figure 3
Correlation of maternal cholesterol during pregnancy with body mass index in the study population.
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Correlation of maternal cholesterol during pregnancy with body mass index in the study population.

Figure 3
Correlation of maternal cholesterol during pregnancy with body mass index in the study population.
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Correlation of maternal cholesterol during pregnancy with body mass index in the study population.

Controls and AMI groups had similar average MCP values, even though significant differences were evident in several risk factors.

Because no measurements of atherosclerosis were available for most control cases, we used two surrogate parameters to determine whether MCP is associated with increased CV risk in adults. The first consisted of the number of classical risk factors, the second was the number of classical risk factors plus the presence of clinical manifestations, such as AMI or cerebrovascular disease. When pooled data of all 310 AMI and control cases were analysed together, MCP was correlated with both measures of atherosclerosis risk in pairwise linear correlation (P < 0.001) (Table 5) (Figure 3) as well as in multivariate analysis with age, gender, and all risk factors as covariates (β = −0.060, P = 0.021).

Table 5

Association of maternal cholesterol during pregnancy and current body mass index with patient characteristics

MCPBMI
Age 0.38 0.64 
Gender 0.30 0.40 
MCP — 0.000 
BMI 0.000 — 
Smoking 0.61 0.037 
Family history of CHD 0.22 0.70 
Diabetes 0.30 0.011 
Family history of hypercholesterolaemia 0.062 0.015* 
Angina 0.156 0.276 
Number of classical risk factors 0.000 0.000 
Number of atherosclerosis-related risk factors 0.000 0.000 
MCPBMI
Age 0.38 0.64 
Gender 0.30 0.40 
MCP — 0.000 
BMI 0.000 — 
Smoking 0.61 0.037 
Family history of CHD 0.22 0.70 
Diabetes 0.30 0.011 
Family history of hypercholesterolaemia 0.062 0.015* 
Angina 0.156 0.276 
Number of classical risk factors 0.000 0.000 
Number of atherosclerosis-related risk factors 0.000 0.000 
*

P < 0.05—Pearson’s correlation; two-tailed significance.

Open in new tab
Table 5

Association of maternal cholesterol during pregnancy and current body mass index with patient characteristics

MCPBMI
Age 0.38 0.64 
Gender 0.30 0.40 
MCP — 0.000 
BMI 0.000 — 
Smoking 0.61 0.037 
Family history of CHD 0.22 0.70 
Diabetes 0.30 0.011 
Family history of hypercholesterolaemia 0.062 0.015* 
Angina 0.156 0.276 
Number of classical risk factors 0.000 0.000 
Number of atherosclerosis-related risk factors 0.000 0.000 
MCPBMI
Age 0.38 0.64 
Gender 0.30 0.40 
MCP — 0.000 
BMI 0.000 — 
Smoking 0.61 0.037 
Family history of CHD 0.22 0.70 
Diabetes 0.30 0.011 
Family history of hypercholesterolaemia 0.062 0.015* 
Angina 0.156 0.276 
Number of classical risk factors 0.000 0.000 
Number of atherosclerosis-related risk factors 0.000 0.000 
*

P < 0.05—Pearson’s correlation; two-tailed significance.

Open in new tab

Discussion

The present study established that: (i) increased MCP is associated with greater severity of AMI; (ii) in multiple regression analysis of patients stratified by a composite measure of AMI severity, the association of MCP with AMI severity was independent of classical CHD risk factors, including gender; and (iii) MCP showed a remarkably strong association with the BMI of patients. The association between MCP and AMI severity is remarkable in a small study population, and because variability in genetic, dietary, and other risk factors may have confounded the effects of developmental programming. Given that MCP markedly increases atherogenesis in human foetuses and children1–5,13,14 and adult offspring of experimental animals,4,9,22–24 one would expect MCP to be associated with more extensive atherosclerosis, and more extensive atherosclerosis with a greater likelihood of plaque rupture and AMI. Based on similar MCP levels, one would assume that AMI patients and controls had similar extent of atherosclerosis. Furthermore, linear regression analysis of pooled data from all 310 subjects indicated a significant association between MCP and two cumulative measures of atherosclerosis risk, consistent with an atherogenic effect of increased MCP. Thus, MCP may play a significant role in atherogenesis, but not in the likelihood of a transition from atherosclerosis to the coronary events.

Overall, the present results establish in a well characterized human population that the effects of developmental programming by MCP persist well into adult age, and that they affect a clinically relevant outcome, i.e., the severity of AMI. Our study does not, however, permit estimates of how much MCP contributed to the severity of AMI, nor does it establish causality. Evidence for causality has been provided by studies in preclinical models demonstrating that interventions which reduce MCP, decrease oxidative stress associated with gestational hypercholesterolaemia, or enhance active immune defences against oxidative stress in offspring protect against developmental programming by MCP.

The main limitations of our study are the small number of cases resulting from the exclusion of older adults, which constitute the bulk of the AMI patients, and the lack of data on maternal dietary and lifestyle confounders. In contrast to the FELIC study,3 where MCP measurements dating back 1–14 years were easier to retrieve, going back up to 65 years proved challenging. We cannot rule out, though, that the correlation between MCP and patients' BMI is influenced by inclusion of mothers whose hypercholesterolaemia is associated with genetic predisposition to obesity and/or metabolic disorders. Second, our study is subject to all the limitations of a retrospective study, in particular the lack of information on many maternal and/or paternal transgenerational effects, such as dietary and lifestyle habits. Moreover, for the majority of patients included only first and second trimester MCP data were available. Mean MCP for all subjects were therefore calculated only from these time points. However, cholesterol levels are known to increase in the third trimester in many women. Our study was therefore largely blind to the effects of temporary hypercholesterolaemia during pregnancy. Mothers with temporary hypercholesterolaemia may have relatively modestly elevated MCP in early pregnancy, yet their offspring are clearly subject to atherogenic programming.1,25 Similarly, data reflecting only the first two trimesters may underestimate the true difference in MCP between AMI and control mothers. In view of the increasing recognition of the importance of developmental programming, prospective trials are clearly necessary to avoid these weaknesses and to further establish the role of MCP and other gestational factors on adult diseases.

Nevertheless, the present study supports the clinically relevant conclusion that MCP is an important independent risk factor not only for childhood atherogenesis, but for the severity of AMI in young adults. This suggests that MCP should be included among risk factors prompting more intensive screening and primary prevention in high-risk children.

Acknowledgements

We dedicate this article to the memory of Dr Antonio Liguori (1944–2018).

Funding

Supported by Italian Ministry of Health Progetto di Ricerca Finalizzata 2007–2009 (F.C.), National Institutes of Health grants HL067792 and HL089559 (W.P. and C.N.), Progetto di Rilevanza Nazionale of Italian Ministry of University and Research PRIN 2017 (C.N.), and Ellison Medical Foundation Senior Scholar Award 1851-07 (W.P.).

Conflict of interest: none declared.

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