Influencing factors for late-onset preeclampsia

The dilemma of sodium intake in preeclampsia: beneficial or detrimental?

Preeclampsia (PE) is a disorder involving de novo development of hypertension plus end organ damage after 20 weeks of gestation. PE is considered to be a heterogeneous disease. There are 2 main types of PE: early-onset (<34 weeks of gestation), which is considered to be a placental disorder and is associated with vasoconstriction, low cardiac output, and placental hypoperfusion and organ damage due to decreased microcirculation to maternal organs; and late-onset PE, which is primarily a disorder of pregnant women with obesity, diabetes, and/or cardiovascular abnormalities. In late-onset PE, there is avid sodium reabsorption by the maternal kidneys, causing hypervolemia and increased cardiac output, along with vasodilatation causing venous congestion of organs. Although PE has been a well-known disease for a long time, it is interesting to note that there is no specific sodium (salt) intake recommendation for these patients. This may be due to the fact that studies since as far back as the 1900s have shown conflicting results, and the reasons for the inconsistent findings have not been fully explained; furthermore, the type of PE in these studies was not specifically defined. Some studies suggest that sodium restriction may be detrimental in early-onset PE, but may be feasible in late-onset PE. To explore this paradox, the current review explains the hemodynamic factors involved in these 2 types of PE, summarizes the findings of the current studies, and highlights the knowledge gaps and the research needed to determine whether increase or restriction of salt or sodium intake is beneficial in different types of PE.

Effects of Maternal Pre-Pregnancy BMI and Gestational Weight Gain on the Development of Preeclampsia and Its Phenotypes: A Prospective Cohort Study in China

Preeclampsia (PE) is a common and serious pregnancy-specific disorder, which is closely linked with adverse maternal and neonatal outcomes. This study aimed to evaluate whether maternal pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) was associated with preeclampsia and its phenotypes. In this prospective study, 32,531 women with singleton pregnancies were finally included. Compared with women with normal pre-pregnancy BMI, women with overweight and obesity were at increased risk of PE (RR = 1.62, 95%CI: 1.57−1.66; RR = 2.04, 95%CI: 1.97−2.11, respectively), while those who were underweight had a lower risk of PE (RR = 0.84, 95%CI: 0.81−0.88). When compared with women who gained adequate GWG, pregnant women with inadequate GWG and excessive GWG had an increased risk of PE (RR = 1.15, 95%CI: 1.12−1.19; RR = 1.56, 95%CI: 1.52−1.60, respectively). The observed increased risk was generally similar for mild-, severe-, early- and late-onset PE, and the reduced risk was similar for severe- and late-onset PE. No significant interactions between GWG and pre-pregnancy BMI on the risk of PE were identified (p-interaction > 0.05). In conclusion, pre-pregnancy overweight or obesity and excessive GWG have established risk factors for PE, and that the potential risk may vary according to PE phenotypes. Moreover, the synergistic effect that may exist between pre-pregnancy BMI and GWG.

Maternal Obesity and the Risk of Early-Onset and Late-Onset Hypertensive Disorders of Pregnancy

OBJECTIVE

To evaluate the relationship between maternal body mass index (BMI) at delivery and rates of early-onset and late-onset hypertensive disorders of pregnancy.

METHODS

We performed a population-based, retrospective cohort study using U.S. Vital Statistics period-linked birth and infant death certificates from 2014 to 2017. Women who delivered a nonanomalous singleton live neonate from 24 to 41 completed weeks of gestation were included. We excluded women with chronic hypertension and those with BMIs less than 18.5. The primary exposure was maternal BMI, defined as nonobese (BMI 18.5-29.9; referent group), class 1 obesity (BMI 30.0-34.9), class 2 obesity (BMI 35.0-39.9), and class 3 obesity (BMI 40.0 or greater). The primary outcome was delivery with hypertensive disorders of pregnancy (gestational hypertension, preeclampsia, or eclampsia) at less than 34 weeks of gestation or at 34 weeks or more. Multivariable Poisson regression was used to estimate relate risk and adjust for confounding variables. Results are presented as adjusted relative risk (aRR) and 95% CIs.

RESULTS

Of the 15.8 million women with live births during the study period, 14.0 million (88.6%) met inclusion criteria, and 825,722 (5.9%) had hypertensive disorders of pregnancy. The risk of early-onset hypertensive disorders of pregnancy was significantly higher in women with class 1 obesity (aRR 1.13; 95% CI 1.10-1.16), class 2 obesity (aRR 1.57; 95% CI 1.53-1.62), and class 3 obesity (aRR 2.18; 95% CI 2.12-2.24), compared with nonobese women. The risk of late-onset hypertensive disorders of pregnancy was also significantly increased in women with class 1 obesity (aRR 1.71; 95% CI 1.70-1.73), class 2 obesity (aRR 2.60; 95% CI 2.58-2.62), and class 3 obesity (aRR 3.93; 95% CI 3.91-3.96) compared with nonobese women.

CONCLUSION

Compared with nonobese women, the risk of early-onset and late-onset hypertensive disorders of pregnancy is significantly and progressively increased among women with increased class of obesity.

Increased BMI has a linear association with late-onset preeclampsia: A population-based study

Background

To investigate the ongoing controversy on the effect of BMI (body mass index) on EOP (early onset preeclampsia) vs LOP (late onset), especially focusing on diabetes and maternal booking/pre-pregnancy BMI as possible independent variables.

Methods

18 year-observational cohort study (2001–2018). The study population consisted of all consecutive births delivered at the Centre Hospitalier Universitaire Hospitalier Sud Reunion’s maternity (ap. 4,300 birth per year, only level 3 maternity in the south of Reunion Island, sole allowed to follow and deliver all preeclampsia cases of the area). History of pregnancies, deliveries and neonatal outcomes have been collected in standardized fashion into an epidemiological perinatal data base.

Results

Chronic hypertension and, history of preeclampsia in multigravidas, were the strongest risk factors for EOP. Primiparity, age over 35 years and BMI ≥ 35 kg/m² were rather associated with LOP. In a multivariate analysis with EOP or LOP as outcome variables compared with controls (normotensive), maternal age and pre-pregnancy BMI were independent risk factors for both EOP and LOP (p < 0.001). However, analyzing by increment of 5 (years of age, kg/m² for BMI) rising maternal ages and incidence of preeclampsia were strictly parallel for EOP and LOP, while increment of BMI was only associated with LOP. Controlling for maternal ages and booking/pre-pregnancy BMI, diabetes was not an independent risk factor neither for EOP or LOP.

Conclusions

Metabolic factors, other than diabetes, associated with pre-pregnancy maternal corpulence are specifically associated with LOP. This may be a direction for future researches on the maternal preeclamptic syndrome. This may explain the discrepancy we are facing nowadays where high-income countries report 90% of their preeclampsia being LOP, while it is only 60–70% in medium-low income countries.

Pre-pregnancy BMI, gestational weight gain and risk of preeclampsia: a birth cohort study in Lanzhou, China

BACKGROUND

To evaluate the independent and joint effects of maternal pre-pregnancy BMI and gestational weight gain (GWG) on the risk of preeclampsia and its subtypes.

METHODS

A birth cohort study was conducted from 2010 to 2012 in Lanzhou, China. Three hundred fourty seven pregnant women with preeclampsia and 9516 normotensive women at Gansu Provincial Maternity and Child Care Hospital were included in the present study. Unconditional logistic regression models were used to evaluate the associations between pre-pregnancy BMI, GWG, and risk of preeclampsia and its subtypes.

RESULTS

Compared to women with normal pre-pregnancy BMI, those who were overweight/obese had an increased risk of preeclampsia (OR = 1.81; 95%CI: 1.37-2.39). Women with excessive GWG had an increased risk of preeclampsia (OR = 2.28; 95%CI: 1.70-3.05) compared to women with adequate GWG. The observed increased risk was similar for mild-, severe- and late-onset preeclampsia. No association was found for early-onset preeclampsia. Overweight/obese women with excessive GWG had the highest risk of developing preeclampsia compared to normal weight women with no excessive weight gain (OR = 3.78; 95%CI: 2.65-5.41).

CONCLUSIONS

Our results suggested that pre-pregnancy BMI and GWG are independent risk factors for preeclampsia and that the risk might vary by preeclampsia subtypes. Our study also proposed a potential synergistic effect of pre-pregnancy BMI and GWG that warrants further investigation.

The prediction of late-onset preeclampsia: Results from a longitudinal proteomics study

BACKGROUND

Late-onset preeclampsia is the most prevalent phenotype of this syndrome; nevertheless, only a few biomarkers for its early diagnosis have been reported. We sought to correct this deficiency using a high through-put proteomic platform.

METHODS

A case-control longitudinal study was conducted, including 90 patients with normal pregnancies and 76 patients with late-onset preeclampsia (diagnosed at ≥34 weeks of gestation). Maternal plasma samples were collected throughout gestation (normal pregnancy: 2-6 samples per patient, median of 2; late-onset preeclampsia: 2-6, median of 5). The abundance of 1,125 proteins was measured using an aptamers-based proteomics technique. Protein abundance in normal pregnancies was modeled using linear mixed-effects models to estimate mean abundance as a function of gestational age. Data was then expressed as multiples of-the-mean (MoM) values in normal pregnancies. Multi-marker prediction models were built using data from one of five gestational age intervals (8-16, 16.1-22, 22.1-28, 28.1-32, 32.1-36 weeks of gestation). The predictive performance of the best combination of proteins was compared to placental growth factor (PIGF) using bootstrap.

RESULTS

1) At 8-16 weeks of gestation, the best prediction model included only one protein, matrix metalloproteinase 7 (MMP-7), that had a sensitivity of 69% at a false positive rate (FPR) of 20% (AUC = 0.76); 2) at 16.1-22 weeks of gestation, MMP-7 was the single best predictor of late-onset preeclampsia with a sensitivity of 70% at a FPR of 20% (AUC = 0.82); 3) after 22 weeks of gestation, PlGF was the best predictor of late-onset preeclampsia, identifying 1/3 to 1/2 of the patients destined to develop this syndrome (FPR = 20%); 4) 36 proteins were associated with late-onset preeclampsia in at least one interval of gestation (after adjustment for covariates); 5) several biological processes, such as positive regulation of vascular endothelial growth factor receptor signaling pathway, were perturbed; and 6) from 22.1 weeks of gestation onward, the set of proteins most predictive of severe preeclampsia was different from the set most predictive of the mild form of this syndrome.

CONCLUSIONS

Elevated MMP-7 early in gestation (8-22 weeks) and low PlGF later in gestation (after 22 weeks) are the strongest predictors for the subsequent development of late-onset preeclampsia, suggesting that the optimal identification of patients at risk may involve a two-step diagnostic process.

Body Mass Index, Weight Gain, and Hypertensive Disorders in Pregnancy

BACKGROUND

This study examines the interrelationship between gestational weight gain, pre-pregnancy body mass index (BMI), race/ethnicity, and their association with hypertensive disorders during pregnancy (HDP).

METHODS

Data from the 2004-2011 national Pregnancy Risk Assessment Monitoring System (PRAMS) were analyzed. Women with singleton live births were included in the analysis (N = 270,131). Gestational weight gain was categorized reflecting the Institute of Medicine (IOM) weight gain recommendation (no gain/weight loss; ≤11, 12-14; 15-25; 26-35; ≥36 pounds). Pre-pregnancy BMI (underweight; normal; overweight; obese) and race/ethnicity (non-Hispanic (NH) White, NH-Black, Hispanic, and NH-other) were examined. Hypertensive disorders during pregnancy were dichotomized (HDP; no HDP). Data were stratified by BMI and race/ethnicity, and multiple logistic regression analysis was conducted to generate odds ratios and 95% confidence intervals (CIs).

RESULTS

Compared to normal and overweight women who gained the IOM recommended weight, higher odds of HDP was observed in those who gained ≥36 pounds regardless of their race/ethnicity. Among obese NH-White (odds ratio (OR) = 1.29, 95% CI = 1.11, 1.50) and Hispanic women (OR = 1.64, 95% CI = 1.05, 2.54), the odds of HDP was higher among those who gained 25-35 pounds and those who gained ≥36 pounds (OR = 1.59, 95% CI = 1.37, 1.85) and (OR = 2.20, 95% CI = 1.41, 3.44), respectively. However, for NH-Black obese women, higher odds of HDP was observed among those who gained ≥36 pounds (OR = 1.34, 95% CI = 1.04, 1.73).

CONCLUSIONS

Although there are some ethnic/racial variations, pregnant women who exceeded gestational weight gain recommendations are at increased risk of HDP. Health care providers should consider the interrelationship between pre-pregnancy gestational weight gain (GWG) and BMI when counseling patients regarding HDP.

Degree of obesity at delivery and risk of preeclampsia with severe features

BACKGROUND

The risk of preeclampsia increases as maternal body mass index (BMI) increases. The link between increasing maternal BMI and preeclampsia with severe features is less well-established.

OBJECTIVE

To estimate the effect of increasing severity of obesity on risk of preeclampsia with severe features, stratified by early-onset and late-onset disease.

STUDY DESIGN

We performed a retrospective cohort study of consecutive singleton live births at a tertiary care facility from 2004 to 2008. Women were included in the cohort if they delivered a singleton live birth and maternal height and weight was measured on admission. The primary exposure was maternal weight category on presentation for delivery, defined as normal (BMI 18.5-24.9; referent group, n = 1473), overweight (BMI 25-29.9, n = 3081), obese (BMI 30-39.9, n = 4196), and morbidly obese (BMI ≥40, n = 1446). The primary outcome was preeclampsia with severe features. Secondary outcome was early-onset preeclampsia with severe features at <34 weeks or late-onset preeclampsia with severe features at ≥34 weeks. Multivariable logistic regression was used to adjust for confounders.

RESULTS

Of the 10,196 patients meeting inclusion criteria, 1119 developed preeclampsia. Of those, 881 (8.6%) women developed preeclampsia with severe features. Overall, the risk of preeclampsia with severe features was not significantly different in the 4 BMI categories. Of the 10,196 women in the cohort, 1072 delivered <34 weeks and 9124 delivered ≥34 weeks. When stratifying by gestational age at delivery, there was a statistically significant increased risk of developing late-onset preeclampsia with severe features at ≥34 weeks in overweight (4.5%, adjusted odds ratio [aOR] 1.4, 95% confidence interval [CI] 1.0-2.1), obese (6.2%, aOR 2.0, 95% CI 1.4-2.8) and morbidly obese (6.8%, aOR 2.0, 95% CI 1.3-2.9) women compared with normal-weight women (2.9%).

CONCLUSION

Increasing maternal weight was not associated with preeclampsia with severe features in the total cohort; however, overweight, obese, and morbidly obese women are at increased risk of developing late-onset preeclampsia with severe features.

Elevated inflammatory markers in preeclamptic pregnancies, but no relation to systemic arterial stiffness

OBJECTIVES

To investigate if circulating markers of systemic and vascular inflammation are associated with systemic arterial properties at term and 6months post-partum in women with preeclampsia (PE) and normal pregnancy (NP).

STUDY DESIGN

Longitudinal, sampling at term and 6months post-partum in 34 women (32±6years) with PE and 61 women (32±5years) with NP.

MAIN OUTCOME MEASURES

Circulating markers related to systemic and vascular inflammation were measured by enzyme immune-assay. Systemic arterial properties were estimated by Doppler (transthoracic echocardiography) and calibrated right subclavian artery pulse traces.

RESULTS

CXCL16, soluble tumor necrosis factor receptor type 1 (sTNF-R1), monocyte chemoattractant peptide 1, pentraxin 3 and soluble vascular adhesion molecule 1 (sVCAM-1) were elevated at term in PE, and sTNF-R1 remained elevated 6months post partum compared to NP. However, apart from a negative correlation between mean arterial pressure and sTNF-R1 and sVCAM-1 at term, no associations between systemic and vascular inflammatory markers and systemic arterial properties as reflected by characteristic impedance and arterial elastance, representing proximal aortic stiffness and effective arterial elastance, were found at any time point.

CONCLUSIONS

Preeclamptic pregnancies are characterized by increased circulating levels of systemic and vascular inflammatory markers. However, these are not associated with systemic arterial properties at term or 6months post partum.

Development of Late-Onset Preeclampsia in Association with Road Densities as a Proxy for Traffic-Related Air Pollution

INTRODUCTION

Previous epidemiological studies indicate an association between maternal exposure to air pollution and an increased risk of hypertensive disorders in pregnancy. We analyzed the association between the occurrence of mild/severe and early-/late-onset preeclampsia (PE) and traffic-related air pollution (TRAP).

MATERIALS AND METHODS

Based on retrospective data, 50 pregnant women with PE were selected and matched with a control group of healthy pregnant women according to their age, parity, and number of fetuses. The total length of major roads around the women's home within a radius of 100, 200, 300, and 500 m and the distances from the domicile to the nearest 'first class' main road and freeway were used as a proxy indicator of TRAP. We compared a PE subgroup and control group in terms of their exposure to TRAP.

RESULTS

Late-onset PE cases showed a significantly higher occurrence with density of major roads within a radius of 100-300 m compared to early onset cases (p = 0.006; 0.02; 0.04). In addition, a significantly shorter distance to the nearest 'first class' main road was observed in late-onset PE cases (p = 0.0078).

CONCLUSIONS

Exposure to TRAP during pregnancy was associated with an increased risk for the development of late-onset PE.

Molecular association of pathogenetic contributors to pre-eclampsia (pre-eclampsia associome)

Background

Pre-eclampsia is the most common complication occurring during pregnancy. In the majority of cases, it is concurrent with other pathologies in a comorbid manner (frequent co-occurrences in patients), such as diabetes mellitus, gestational diabetes and obesity. Providing bronchial asthma, pulmonary tuberculosis, certain neurodegenerative diseases and cancers as examples, we have shown previously that pairs of inversely comorbid pathologies (rare co-occurrences in patients) are more closely related to each other at the molecular genetic level compared with randomly generated pairs of diseases. Data in the literature concerning the causes of pre-eclampsia are abundant. However, the key mechanisms triggering this disease that are initiated by other pathological processes are thus far unknown. The aim of this work was to analyse the characteristic features of genetic networks that describe interactions between comorbid diseases, using pre-eclampsia as a case in point.

Results

The use of ANDSystem, Pathway Studio and STRING computer tools based on text-mining and database-mining approaches allowed us to reconstruct associative networks, representing molecular genetic interactions between genes, associated concurrently with comorbid disease pairs, including pre-eclampsia, diabetes mellitus, gestational diabetes and obesity. It was found that these associative networks statistically differed in the number of genes and interactions between them from those built for randomly chosen pairs of diseases. The associative network connecting all four diseases was composed of 16 genes (PLAT, ADIPOQ, ADRB3, LEPR, HP, TGFB1, TNFA, INS, CRP, CSRP1, IGFBP1, MBL2, ACE, ESR1, SHBG, ADA). Such an analysis allowed us to reveal differential gene risk factors for these diseases, and to propose certain, most probable, theoretical mechanisms of pre-eclampsia development in pregnant women. The mechanisms may include the following pathways: [TGFB1 or TNFA]-[IL1B]-[pre-eclampsia]; [TNFA or INS]-[NOS3]-[pre-eclampsia]; [INS]-[HSPA4 or CLU]-[pre-eclampsia]; [ACE]-[MTHFR]-[pre-eclampsia].

Conclusions

For pre-eclampsia, diabetes mellitus, gestational diabetes and obesity, we showed that the size and connectivity of the associative molecular genetic networks, which describe interactions between comorbid diseases, statistically exceeded the size and connectivity of those built for randomly chosen pairs of diseases. Recently, we have shown a similar result for inversely comorbid diseases. This suggests that comorbid and inversely comorbid diseases have common features concerning structural organization of associative molecular genetic networks.