Objective
Recent studies have shown that women with a history of preeclampsia have an increased risk of cardiovascular disease. The present study investigated cardiovascular risk factors 10 years after preeclampsia in previously healthy women.
Study Design
Based on data from the Medical Birth Registry in Norway, we selected 182 women with and 180 women without preeclampsia in their first pregnancy 9-11 years earlier, excluding women with cardiovascular or renal disease before pregnancy. Flow-mediated dilation of the brachial artery (FMD) and intima-media thickness (IMT) of the carotid artery were measured and blood samples were drawn. Blood samples were analyzed for cardiovascular risk markers and for circulating markers of endothelial function.
Results
A total of 89 women with previous preeclampsia and 69 women without preeclampsia participated, an overall attendance rate of 44%. FMD and IMT were similar between groups. Women with previous preeclampsia more often had urate and soluble fms-like tyrosine kinase values above the 75th percentile (odds ratio [OR], 2.4; P = .03, and OR, 2.4; P = .04, respectively) and high-density lipoprotein cholesterol values below the 25th percentile (OR, 2.3; P = .04). Women with preeclampsia with low birthweight offspring were associated with asymmetric dimethylarginine, L-arginine, and homoarginine above the 75th percentile, whereas the women with preeclampsia with normal-weight offspring were associated with urate and soluble fms-like tyrosine kinase above the 75th percentile.
Conclusion
Preeclampsia was not associated with impaired FMD or increased IMT 10 years after pregnancy in previously healthy women, but preeclampsia was associated with changes in circulating markers that might represent early endothelial dysfunction.
Several studies have shown that preeclampsia is associated with an increased risk of later cardiovascular disease and that women with previous preeclampsia have increased blood pressure, body mass index, insulin resistance, and endothelial dysfunction several years after their preeclamptic pregnancy, as compared with women without preeclampsia.
Endothelial dysfunction is regarded as a central factor in the pathophysiology of preeclampsia, and recent discoveries have elucidated the process of maternal endothelial damage, in which antiangiogenic factors produced by the placenta seem to play an important role. Soluble fms-like tyrosine kinase (sFlt-1) and placental growth factor (PlGF) have been shown to be important, and probably causal, factors in the widespread endothelial dysfunction that accompany preeclampsia. Other important factors involved may be urate, shown to be strongly associated with the development of preeclampsia and also a marker of cardiovascular risk, and asymmetric dimethylarginine (ADMA), an endogenous inhibitor of the nitric oxide pathway and a promising novel cardiovascular risk marker.
Endothelial dysfunction is also believed to be involved in the development and progression of atherosclerosis and kidney disease, and endothelial dysfunction may be the unifying link between preeclampsia and later cardiovascular and renal disease. Women with previous preeclampsia have been found to have manifestations of endothelial dysfunction several years after their preeclamptic pregnancy, but several of the previous studies have investigated women with known underlying predisposing conditions and/or severe preeclampsia.
In the present population-based study, we wanted to investigate whether preeclampsia in previously healthy women was associated with signs of endothelial dysfunction 10 years after the preeclamptic pregnancy. We chose a variety of markers of endothelial dysfunction, both functional (flow-mediated dilatation [FMD]) and structural measurements (intima-media thickness [IMT]) and different serum biomarkers related to preeclampsia, endothelial function, and inflammation. We also analyzed preeclampsia with and without low birthweight offspring separately because women with severe preeclampsia with low birthweight offspring may have a different pathogenesis than women with preeclampsia with normal-birthweight offspring. Our hypothesis was that preeclampsia would be associated with impaired FMD and increased IMT and with circulating markers of endothelial dysfunction.
Subjects and Methods
Registries
Medical data on all births in Norway are forwarded to the Medical Birth Registry of Norway by compulsory notification. The notification form includes extensive data on the mother and the newborn and is completed by the attending midwife and doctor. The regional ethics committee approved the study.
Study design
The study design has been described in more detail in another paper. We identified women living in the Bergen (Norway) area (population count approximately 325,000) with their first pregnancy in the years 1998-2000. Those diagnosed with diabetes, rheumatic disease, essential hypertension, or renal disease before first pregnancy and those with later preeclamptic pregnancies were excluded. From these, we invited women with and without preeclampsia in their first pregnancy, the latter matched on age, year of first birth, and municipality but otherwise randomly selected as a control group. The number of eligible women for inclusion was 182 in the preeclampsia group and 180 in the control group.
The women who agreed to participate were examined between December 2009 and October 2010. The participants were instructed to be overnight fasting and to abstain from hard exercise and high-fat foods 24 hours before examination, smoking, and intake of caffeine or any medication on the examination day. Women who were menstruating or had acute illness were rescheduled to a later appointment. On the examination day, a questionnaire was completed, body size was measured, and resting blood pressure was measured manually according to European Society of Hypertension–European Society of Cardiology guidelines.
Vascular measurements
The women were examined in a quiet, temperature-controlled room, between 9:00 am and 5:00 pm . Measurements of endothelial function by postocclusive FMD of the right brachial artery were done according to guidelines by the International Brachial Artery Reactivity Task Force. The blood pressure cuff was placed on the forearm, and the brachial artery was imaged above the antecubital fossa in the longitudinal plane (identical sites of measurements were ensured using anatomical landmarks and pen marks). Images of the artery were recorded continuously for 5 minutes after cuff deflation. After 10 minutes of rest, a single dose (0.4 mg) of nitroglycerin spray was administered sublingually to determine endothelial-independent vasodilation. Measurements were done at the time of maximum dilation. All images were recorded in end diastole. For imaging, we used a GE Vingmed system (GE Vingmed, Vivid 7; GE, Horten, Norway) with a multiple linear array transducer (6-13 MHz).
The same ultrasound equipment was used for IMT measurements. The distal segment of the common carotid artery was identified, and 5 images were recorded on both sides. For the analysis of IMT, Vivid 7 Dimension ’05 semiautomatic software for IMT analysis (GE Vingmed, Vivid 7) was used.
The FMD and IMT measurements were obtained by one trained physician (M.K.S.), and all image measurements and analyses were done in a blinded manner after data collection was concluded. Another trained physician (E.L.) also analyzed a random selection of subject measurements (n = 20), and the interobserver variability expressed as 1-way random intraclass correlation coefficient (ICC [1,1]) was 0.96 for baseline measurements and 0.78 for FMD. For IMT, the ICC (1,1) was 0.95.
Blood samples and biomarkers
Serum cholesterols (total/high-density lipoprotein [HDL]/low-density lipoprotein [LDL]), serum triglycerides, serum C-reactive protein (CRP), serum glucose, serum insulin, serum urate, blood hemoglobin A1C (HbA1C), and plasma fibrinogen were analyzed at Haukeland University Hospital laboratory. A semi–high-sensitive assay was used for quantification of CRP, with values specified between 1 and 5. Serum samples were frozen immediately after centrifugation (3000 rpm, 15 minutes) and aliquotation and stored at –80°C. These were later analyzed for soluble vascular cell adhesion molecule-1 (VCAM-1), sFlt-1, PlGF, vascular endothelial growth factor (VEGF), and tumor necrosis factor alpha (TNF-α) (high sensitive) using enzyme-linked immunosorbent assay kits (quantikine human immunoassays) from R&D Systems (Minneapolis, MN). ADMA, symmetric dimethylarginine, neopterin, L-arginine, and homoarginine were measured by BEVITAL AS (Bergen, Norway) in serum using liquid chromatography–tandem mass spectrometry, whereas homocysteine was measured in serum using gas chromatography–tandem mass spectrometry.
Exposure variables
Criteria for preeclampsia have been in accordance with recommendations by the American College of Obstetricians and Gynecologists (ie, increased blood pressure after gestational week 20 [blood pressure ≥140/90 mm Hg] associated with proteinuria [≥0.3 g in a 24 hour urine specimen or +1 or greater in a random urinary dipstick]). Birthweight is measured shortly after birth; a weight below 2.5 kg was categorized as low birthweight. The estimation of gestational age was based on routine ultrasonographic examination between gestational weeks 17 and 20. Birth at a gestational age below 37 weeks was defined as preterm.
Statistical analyses
Unpaired Student t tests were used to compare mean values for women with and without preeclampsia; values are given as mean (SD). For skewed parameters, Mann-Whitney U tests were used to compare median values, and values were given as median (25th percentile, 75th percentile). χ 2 tests were used to compare proportions. Pearson’s correlation coefficients were calculated for correlation analyses. Logistic regression analyses were used to obtain unadjusted and adjusted odds ratios for risks of cardiovascular risk factors or markers of endothelial dysfunction above/below the reported thresholds. The analyses were performed using the statistical package SPSS 20.0 for Macintosh (SPSS Inc, Cary, NC).
Results
A total of 89 women with previous preeclampsia and 69 women with a normal first pregnancy participated in the study, resulting in an overall participation rate of 44%, 49% for women with previous preeclampsia and 38% for women without preeclampsia. The remaining women declined the invitation or did not respond. Mean duration from end of first pregnancy to follow-up was 10.9 ± 1.0 years.
Comparison of study participants with population average
We compared characteristics of our participants with the total population of women with their first pregnancy registered in the Medical Birth Registry of Norway and with the same inclusion/exclusion criteria as the participants. Study participants without preeclampsia were older (28.0 vs 26.6 years; P < .001) and had slightly more often low birthweight offspring (7.2% vs 3.1%; P = .05) and preterm birth (11% vs. 5.2%; P = .07) but similar frequency of being single or having a cesarean section as compared with the population average. There were no differences between study participants with preeclampsia, and all women with preeclampsia except that the participants were somewhat older (27.1 vs 26.3 years; P < .001).
Using data from Statistics Norway, we examined self-reported educational level between the participating women aged 30-49 years and compared these with the expected number from official statistics. These analyses showed that a higher percentage of our participants had completed a higher education above high school level than in the general population (68% vs 53%; P < .001).
Traditional cardiovascular risk factors
There were no differences in body weight, body mass index, or waist/hip ratio between women with or without preeclampsia ( Table 1 ). There was a nonsignificant trend toward higher blood pressure in women with previous preeclampsia as compared with women without preeclampsia ( Table 1 ). Eight women with preeclampsia and 3 women without preeclampsia ( P = .26) had hypertension defined as blood pressure of 140/90 mm Hg 33 or greater and/or use of antihypertensive medications and/or current hypertension diagnosis (self-report). Further analyses showed that women with preeclampsia more often had systolic blood pressure above the 75th percentile, significant after adjustments ( Table 2 ).
| Characteristic | Women with preeclampsia (n = 89) | Women without preeclampsia (n = 69) | P value |
|---|---|---|---|
| Traditional cardiovascular risk factors, mean ± SD | |||
| Age | 37.9 ± 4.2 | 39.0 ± 5.3 | .15 |
| Weight, kg | 73.9 ± 15.9 | 73.7 ± 14.8 | .95 |
| BMI, kg/m 2 | 26.7 ± 5.7 | 26.0 ± 5.1 | .44 |
| Waist/hip ratio | 0.87 ± 0.05 | 0.86 ± 0.05 | .25 |
| Systolic blood pressure, mm Hg | 118 ± 16 | 114 ± 11 | .10 |
| Diastolic blood pressure, mm Hg | 73 ± 12 | 71 ± 9 | .18 |
| Physical exercise less than 3 hours per week, n (%) | 55 (62) | 40 (58) | .63 |
| Current smoking, n (%) | 11 (12) | 10 (15) | .70 |
| Use of antihypertensive medication, n (%) | 4 (5) | 2 (3) | .60 |
| Close relative with cardiovascular disease, n (%) a | 22 (25) | 19 (28) | .69 |
| Close relative with hypertension, n (%) a | 50 (56) | 30 (44) | .11 |
| Standard blood tests, mean ± SD | |||
| Insulin, mIE/L | 3.70 (<2.00 to 5.50) b | 2.60 (<2.00 to 5.20) b | .17 |
| HOMA-IR (insuline resistance) b | 0.79 (0.42-1.25) | 0.58 (0.42-1.05) | .29 |
| Glucose, mmol/L | 4.98 ± 1.02 | 4.85 ± 0.38 | .30 |
| HbA1C, % | 5.32 ± 0.43 | 5.28 ± 0.29 | .54 |
| Urate, μmol/L | 255.67 ± 56.76 | 239.35 ± 41.24 | .046 |
| CRP, mg/L | 1.87 ± 3.01 | 1.71 ± 3.25 | .76 |
| Fibrinogen, g/L | 2.96 ± 0.53 | 3.04 ± 0.53 | .38 |
| Creatinine, μmol/L | 60.84 ± 8.28 | 62.71 ± 8.60 | .17 |
| Cholesterol total, mmol/L | 4.84 ± 0.89 | 4.87 ± 0.80 | .82 |
| HDL, mmol/L | 1.51 ± 0.36 | 1.63 ± 0.39 | .056 |
| LDL, mmol/L | 3.00 ± 0.79 | 2.92 ± 0.67 | .49 |
| Triglycerides, mmol/L | 0.98 ± 0.54 | 0.91 ± 0.51 | .40 |
| Vascular measurements, mean ± SD | |||
| FMD, % | 8.28 ± 3.68 | 8.21 ± 4.02 | .90 |
| Nitro-mediated arterial dilation, % | 22.47 ± 5.89 | 22.60 ± 7.57 | .91 |
| Mean IMT left/right, mm a | 0.49 ± 0.07 | 0.50 ± 0.06 | .67 |
| Biomarkers, mean ± SD | |||
| ADMA, μmol/L | 0.51 ± 0.08 | 0.50 ± 0.07 | .37 |
| SDMA, μmol/L | 0.60 ± 0.11 | 0.59 ± 0.10 | .63 |
| L-arginine, μmol/L | 109.54 ± 19.31 | 109.56 ± 18.96 | 1.00 |
| Homoarginine, μmol/L | 2.10 ± 1.00 | 1.82 ± 0.65 | .050 |
| VCAM-1, ng/mL | 656.42 ± 216.52 | 678.78 ± 195.29 | .53 |
| VEGF, pg/mL | 328.03 ± 237.83 | 300.26 ± 212.24 | .46 |
| PlGF, pg/mL | 5.70 ± 2.69 | 5.52 ± 2.66 | .72 |
| sFlt-1, pg/mL | 65.48 ± 19.73 | 60.93 ± 18.24 | .16 |
| sFlt-1/PlGF ratio | 15.54 ± 12.81 | 16.34 ± 14.39 | .76 |
| Neopterin, nmol/L | 15.18 ± 4.66 | 14.55 ± 3.70 | .36 |
| TNF-α, pg/mL | 1.44 ± 1.34 | 1.52 ± 2.28 | .81 |
a Mean of left and right values
b Insulin values <2 μU/mL could not be measured with the assay that was used. Sixty-three women (40%) had values <2 μU/mL. Median values (25% percentile to 75% percentile) are given.
| Variable | Total, n | Preeclampsia, n a | OR, unadjusted (95% CI) | P value | OR, adjusted (95% CI) b | P value |
|---|---|---|---|---|---|---|
| BMI ≥75th percentile (29.2 kg/m 2 ) | ||||||
| No | 119 | 66 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 39 | 23 | 1.15 (0.55–2.40) | .70 | 1.37 (0.64–2.96) | .42 |
| Systolic BP ≥75th percentile (123 mm Hg) | ||||||
| No | 116 | 61 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 41 | 27 | 1.74 (0.83–3.65) | .14 | 2.34 (0.99–5.54) | .053 |
| HOMA-IR ≥75th percentile (1.2) | ||||||
| No | 119 | 65 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 39 | 24 | 1.33 (0.64–2.78) | .45 | 1.11 (0.48–2.57) | .81 |
| Urate ≥75th percentile (278 μmol/L) | ||||||
| No | 119 | 61 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 39 | 28 | 2.42 (1.10–5.30) | .027 | 3.00 (1.16–7.77) | .024 |
| LDL ≥75th percentile (3.5 mmol/L) | ||||||
| No | 117 | 64 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 41 | 25 | 1.29 (0.63–2.67) | .49 | 1.35 (0.62–2.94) | .46 |
| HDL <25th percentile (1.3 mmol/L) | ||||||
| No | 120 | 62 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 38 | 27 | 2.30 (1.05–5.05) | .038 | 3.04 (1.08–8.59) | .036 |
| FMD <5% | ||||||
| No | 126 | 74 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 30 | 15 | 0.70 (0.32–1.56) | .39 | 0.68 (0.29–1.63) | .39 |
| IMT ≥75th percentile (0.54 mm) | ||||||
| No | 115 | 66 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 40 | 22 | 0.91 (0.44–1.87) | .79 | 1.05 (0.48–2.32) | .90 |
| ADMA ≥75th percentile (0.55 μmol/L) | ||||||
| No | 119 | 63 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 39 | 26 | 1.78 (0.83–3.79) | .14 | 1.67 (0.74–3.73) | .22 |
| L-arginine ≥75th percentile (123 μmol/L) | ||||||
| No | 119 | 64 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 39 | 25 | 1.54 (0.73–3.24) | .26 | 1.74 (0.79–3.85) | .17 |
| Homoarginine ≥75th percentile (2.31 μmol/L) | ||||||
| No | 119 | 63 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 39 | 26 | 1.78 (0.83–3.79) | .14 | 1.76 (0.80–3.89) | .16 |
| sFlt-1 ≥75th percentile (75.1 pg/mL) | ||||||
| No | 107 | 56 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 36 | 26 | 2.37 (1.04–5.39) | .040 | 2.09 (0.87–5.04) | .099 |
| sFlt-1/PlGF ratio ≥75th percentile (19.4) | ||||||
| No | 82 | 47 | 1.0 (referent) | 1.0 (referent) | ||
| Yes | 27 | 15 | 0.93 (0.39–2.24) | .87 | 1.16 (0.44–3.10) | .76 |
a Number of women with previous preeclampsia
b Adjusted for age, BMI, marital status, annual household income and highest education level.
There was a near significantly lower level of HDL and a significantly higher level of urate in women with preeclampsia than in women without preeclampsia ( Table 1 ). Further analyses showed that women with previous preeclampsia more often had urate values above the 75th percentile and HDL values below the 25th percentile ( Table 2 ). There was a stronger association between high values of urate and preeclampsia with normal-birthweight offspring than preeclampsia with low-birthweight offspring ( Table 3 ).
| Variable | Total, n | PE, n a | OR, unadjusted (95% CI) | P value for trend | OR, adjusted (95% CI) b | P value for trend |
|---|---|---|---|---|---|---|
| Urate ≥75th percentile | ||||||
| No PE | 69 | 11 | 1.0 (referent) | 1.0 (referent) | ||
| PE without LBW offspring | 71 | 25 | 2.87 (1.28–6.43) | .21 | 3.67 (1.36–9.92) | .16 |
| PE with LBW offspring | 18 | 3 | 1.06 (0.26–4.26) | 1.23 (0.24–6.47) | ||
| HDL <25th percentile | ||||||
| No PE | 69 | 11 | 1.0 (referent) | 1.0 (referent) | ||
| PE without LBW offspring | 71 | 21 | 2.22 (0.97–5.04) | .046 | 2.58 (0.86–7.72) | .018 |
| PE with LBW offspring | 18 | 6 | 2.64 (0.82–8.52) | 5.44 (1.22–24.21) | ||
| FMD <5% | ||||||
| No PE | 67 | 15 | 1.0 (referent) | 1.0 (referent) | ||
| PE without LBW offspring | 71 | 11 | 0.64 (0.27–1.51) | .63 | 0.61 (0.24–1.55) | .67 |
| PE with LBW offspring | 18 | 4 | 0.99 (0.28–3.46) | 0.99 (0.27–3.57) | ||
| ADMA ≥75th percentile | ||||||
| No PE | 69 | 13 | 1.0 (referent) | 1.0 (referent) | ||
| PE without LBW offspring | 71 | 18 | 1.46 (0.65–3.28) | .039 | 1.30 (0.55–3.10) | .049 |
| PE with LBW offspring | 18 | 8 | 3.45 (1.14–10.44) | 3.70 (1.15–11.87) | ||
| L-arginine ≥75th percentile | ||||||
| No PE | 69 | 14 | 1.0 (referent) | 1.0 (referent) | ||
| PE without LBW offspring | 71 | 16 | 1.14 (0.51–2.57) | .039 | 1.28 (0.54–3.01) | .022 |
| PE with LBW offspring | 18 | 9 | 3.93 (1.32–11.74) | 4.48 (1.43–14.00) | ||
| Homoarginine ≥75th percentile | ||||||
| No PE | 69 | 13 | 1.0 (referent) | 1.0 (referent) | ||
| PE without LBW offspring | 71 | 19 | 1.57 (0.71–3.50) | .072 | 1.54 (0.67–3.56) | .080 |
| PE with LBW offspring | 18 | 7 | 2.74 (0.89–8.43) | 2.77 (0.88–8.66) | ||
| sFlt-1 ≥75th percentile | ||||||
| No PE | 61 | 10 | 1.0 (referent) | 1.0 (referent) | ||
| PE without LBW offspring | 65 | 23 | 2.79 (1.20–6.52) | .24 | 2.45 (0.99–6.07) | .40 |
| PE with LBW offspring | 17 | 3 | 1.09 (0.26–4.52) | 1.04 (0.24–4.50) |
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
