Maternal hypertensive disorders in pregnancy and early childhood cardiometabolic risk factors: The Generation R Study.

The objective of this study was to determine the associations between hypertensive disorders of pregnancy and early childhood cardiometabolic risk factors in the offspring. Therefore, 7794 women from the Generation Rotterdam Study were included, an ongoing population-based prospective birth cohort. Women with a hypertensive disorder of pregnancy were classified as such when they were affected by pregnancy induced hypertension, pre-eclampsia or the haemolysis, elevated liver enzymes and low platelet count (HELLP) syndrome during pregnancy. Early childhood cardiometabolic risk factors were defined as the body mass index at the age of 2, 6, 12, 36 months and 6 years. Additionally, it included systolic blood pressure, diastolic blood pressure, total fat mass, cholesterol, triglycerides, insulin and clustering of cardiometabolic risk factors at 6 years of age. Sex-specific differences in the associations between hypertensive disorders and early childhood cardiometabolic risk factors were investigated. Maternal hypertensive disorders of pregnancy were inversely associated with childhood body mass index at 12 months (confounder model: -0.15 SD, 95% CI -0.27; -0.03) and childhood triglyceride at 6 years of age (confounder model: -0.28 SD, 95% CI -0.45; -0.10). For the association with triglycerides, this was only present in girls. Maternal hypertensive disorders of pregnancy were not associated with childhood body mass index at 2, 6 and 36 months. No associations were observed between maternal hypertensive disorders of pregnancy and systolic blood pressure, diastolic blood pressure, body mass index, fat mass index and cholesterol levels at 6 years of age. Our findings do not support an independent and consistent association between maternal hypertensive disorders of pregnancy and early childhood cardiometabolic risk factors in their offspring. However, this does not rule out possible longer term effects of maternal hypertensive disorders of pregnancy on offspring cardiometabolic health.

Introduction

Hypertensive disorders of pregnancy (HDP) complicate up to 10% of pregnancies and represent a significant cause of morbidity and mortality in both mother and child [1-3]. After having a HDP, there is an approximately twofold risk of developing cardiovascular or cerebrovascular disease [4-6]. In contrast, conflicting data exist on the associations with cardiometabolic risk factors in the offspring [7-11].

A number of mechanism are proposed, through which HDP may affect cardiometabolic risk factors in the offspring. First, there may be alterations in fetal vasculature and cardiac development due to exposure to maternal angiogenic factors during pregnancy [12, 13]. Second, relative fetal undernutrition due to maternal vasoconstriction may lead to adjusted fetal programming, which has a negative effect on cardiometabolic health in the offspring [American journal of human genetics. 1962 ">14-16]. Thirdly, shared maternal and fetal genetic risk and life style factors for cardiometabolic risk factors may explain the association [17-19]. Lastly, spontaneous or iatrogenic preterm birth and the associated low birthweight may mediate the association with increased cardiometabolic risk factors in the offspring [20-22].

The association between childhood cardiometabolic risk factors and the cardiometabolic profile in adult life has been well established [23, 24]. Early identification of children at risk for the development of such an adverse profile is therefore important to potentially mitigate these risks [25]. There are no consistent results with regard to an increased cardiometabolic risk for young offspring that is prenatally exposed to HDP. Therefore, we wish to add to the evidence [13, 26–29]. Thus, the aim of this study is to investigate the associations between maternal HDP and early childhood cardiometabolic risk factors, in a large and multi-ethnic population-based cohort.

Methods

Population and study design

This prospective cohort study was embedded in the Generation R Study, a prospective population-based cohort in Rotterdam, the Netherlands [30]. Pregnant women were eligible for the study if they had an expected delivery date from April 2002 until January 2006 and were living in the study area in the city of Rotterdam. The following pregnancies were excluded from the analysis: twin pregnancies, terminated pregnancies, intra-uterine fetal demise and pregnancies without data on maternal hypertensive disorders or early childhood cardiometabolic risk factors (). The study protocol was approved by the Medical Ethical Committee of Erasmus Medical Centre, Rotterdam (MEC 198.782/ 2001/31). Written informed consent was obtained from all participants.

Flowchart of the study population.

Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; PI, ponderal index.

Hypertensive disorders of pregnancy

Women with a HDP were classified as such when they were affected by gestational hypertension (GH), pre-eclampsia (PE) or the haemolysis, elevated liver enzymes and low platelet count (HELLP) syndrome during pregnancy. Information on physician-diagnosed GH, PE or HELLP was retrieved from hospital charts [31]. The diagnosis was determined based on the criteria of the International Society for the Study of Hypertension in Pregnancy and according to those of the American College of Obstetricians and Gynaecologists [32]. GH was defined as a systolic blood pressure ≥140 mmHg or a diastolic blood pressure ≥90 mmHg after 20 weeks of gestation in previously normotensive women. PE was defined as de novo gestational hypertension with concurrent new onset proteinuria in a random urine sample with no evidence of urinary tract infection [32, 33]. HELLP syndrome was defined according to the class I and II 2006 Mississippi criteria (platelet count ≤ 100 x 109/L, aspartate transaminase (AST) or alanine-aminotransferase (ALT) ≥ 40 IU/L and lactic acid dehydrogenase (LDH) ≥ 600 IU/L) [34]. There were 293 cases of GH, 139 cases of PE, 14 cases of HELLP, and 45 cases which were classified as both PE and HELLP.

Child cardiometabolic risk factors

Body mass index and ponderal index

Information on early childhood height and weight was collected from the community health centres, which the children visited at the age of 2 months, 6 months, 12 months and 36 months. At the age of 6 years, all children were invited to the dedicated research facility in the Erasmus University Medical Centre, Sophia Children’s Hospital, for blood withdrawal and detailed measurements, among which height and weight measurements. Height and weight of children was measured according to standardized procedures: wearing underwear only, and height was measured in a barefooted standing position [30]. Body mass indexes (BMI’s) were calculated as weight/height2. Sex- and age- adjusted standard deviation scores (SDS) of childhood BMI were calculated, based on Dutch reference growth charts (Growth Analyzer 4.0, Dutch Growth Research Foundation) [35]. Since ponderal index might be a better measure than BMI in infancy, sensitivity analyses by using the ponderal index were performed (weight/height3) [36].

Blood pressure

Maternal systolic and diastolic blood pressure were measured at the visit to the research facility in late pregnancy, i.e. ≥ 25 weeks of pregnancy. They were measured at the right brachial artery, four times with one minute intervals, using the validated automatic sphygmanometer Datascope Accutor Plus TM (Paramus, NJ, USA) [37]. The mean value for systolic and diastolic blood pressure was calculated using the last three blood pressure measurements of each participant.

Blood measurements

A 30-minute fasting venous blood sample was obtained, in which total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides and insulin were measured.

Fat mass index

Body fat was measured by Dual-Energy X-ray absorptiometry (DXA) (iDXA, General Electrics–Lunar, 2008, Madison, WI, USA), according to standard procedures [38]. Previous studies have validated DXA against computed tomography for body fat assessment [39, 40]. Android fat mass was calculated as a percentage of total fat mass [39]. In order to obtain the fat mass index uncorrelated with height, total fat mass was divided by height3, as confirmed by a log-log regression analysis [41, 42].

Cardiometabolic clustering

Clustering of cardiometabolic risk factors was defined as such when children had three or more of the following components: android fat mass percentage at the 75th centile or above, systolic or diastolic blood pressure at the 75th centile or above; high density lipoprotein cholesterol at the 25th centile or below or triglycerides at the 75th centile or above, and an insulin levels at the 75th centile or above [43].

Pregnancy dating

Gestational age is the most important determinant of fetal growth, so precise dating of the pregnancy is important. In accordance with clinical guidelines, if the gestational age was below 12 weeks and 5 days and the crown-rump length (CRL) measurement was smaller than 65 mm, pregnancy dating was performed using the first ultrasound measurement of the CRL. When the gestational age was older than 12 weeks and 5 days, or the biparietal diameter (BPD) was larger than 23 mm, pregnancy dating was performed using the BPD [44].

Potential confounding variables

Covariates in the regression models were selected based on their association with both the predictor and outcome of interest. Therefore, we conducted a Directed Acyclic Graph (DAG) analysis with a consensus meeting to identify which covariates were confounders (S1 Fig in ) [45, 46]. Consensus was achieved by the authors regarding the current structure of our regression models (DG, AP, BR, ES). The identified confounders consist of maternal BMI, ethnicity, glucose levels, educational level, smoking during pregnancy, alcohol use during pregnancy, gestational diabetes mellitus, and the child’s sex.

Covariates

Maternal age was assessed at the intake by questionnaire. Information on maternal education level, ethnicity, parity, folic acid supplementation, smoking and alcohol consumption was assessed by questionnaires during pregnancy [30]. Information on childhood sex, gestational age at birth, birth weight and length at birth was obtained from midwifery and (obstetric) medical records [44, 47]. At enrolment maternal weight (kg) and height (cm) were measured without shoes and heavy clothing after which pregnancy BMI (kg/m2) was calculated. Weight measured at enrolment and pre-pregnancy weight were highly correlated (Pearson’s correlation coefficient 0.95 (P-value <0.001)) [48].

Maternal glucose concentrations were measured in nonfasting blood samples which were collected at enrolment in the study. Glucose concentration (millimoles per litre) was measured with c702 module on the Cobas 8000 analyzer (Roche, Almere, the Netherlands). Information on gestational diabetes mellitus was obtained from medical records after delivery. Gestational diabetes mellitus was diagnosed by a community midwife or an obstetrician according to Dutch midwifery and obstetric guidelines using the following criteria: either a random glucose level >11.0 mmol/l (196 mg/dL), a fasting glucose ≥7.0 mmol/l (126 mg/dL) or a fasting glucose between 6.1 mmol/l (110 mg/dL) and 6.9 mmol/l (124 mg/dL) with a subsequent abnormal glucose tolerance test [49]. In clinical practice and for this study sample, an abnormal glucose tolerance test was defined as a glucose level greater than 7.8 mmol/l (140 mg/dL) after glucose intake.

Statistical analyses

Statistical analyses were performed using the Statistical Package of Social Sciences version 25.0 for Windows (IBM Corp., Armonk, NY, USA). A p-value < 0.05 was considered statistically significant. First, a non-response analysis was performed to compare baseline characteristics between women included and excluded from this study. Second, using Students two-tailed t-test and chi-square tests distribution of baseline characteristics and covariates within the study population were examined. Third, the associations of HDP with early childhood outcomes were examined using linear regression models: (1) a basic model including child’s sex and (2) a confounder model, which was additionally adjusted for maternal and early childhood covariates selected in the DAG analysis; maternal BMI, glucose levels, educational level, ethnicity, smoking during pregnancy, alcohol use during pregnancy and gestational diabetes mellitus. Linearity was tested by assessing distribution around a diagonal line within a residual-versus-predicted-plot. Effect modifications by maternal ethnicity, child’s sex, maternal smoking behaviours, maternal BMI were investigated. When significant interactions were present (p<0.1), stratified analyses were performed. Fourth, sensitivity analyses were performed. In the first analysis differences in early childhood cardiometabolic risk factors between pregnancies affected by 1) pre-eclampsia / HELLP, 2) GH or 3) ‘no HDP’ were tested using one-way ANOVA and Kruskal Wallis tests. To investigate the robustness of our results, sensitivity analyses defining cases as women with severe HDP (pre-eclampsia or HELLP) were performed. Lastly analysis to find differences in observed and expected values of confounders before and after imputation were conducted.

We constructed standard deviation scores (SDS) [(observed value—mean)/SD] for early childhood outcomes to enable comparison of effect estimates. The models were tested for multicollinearity using the tolerance statistic. As tolerance was >0.20 for all variables in our models, multicollinearity was unlikely. Multiple imputation procedures for confounders with missing values, were performed, creating five imputed complete datasets. These were then pooled for analyses [50]. Missing values were pre-pregnancy BMI (19.6%), glucose levels (29.6%), educational level (9.3%), ethnicity (5.7%), smoking in pregnancy (12.7%), alcohol use during pregnancy (13.9%) and gestational diabetes mellitus (2.8%).

Results

Characteristics of the study population

shows maternal and child characteristics of the total study population, and within the groups of women with and without HDP. In S1 Table in , offspring parameters according to the type of HDP that the mother experienced are demonstrated. In our study of 7794 women, 491 women (6.3%) developed a HDP. The majority of women had a normal pre-pregnancy BMI (median 22.7 kg/m2) and were non-smokers (72.5%). When investigating differences between maternal and child characteristics between women with a HDP and without a HDP, only BMI in children at 12 months of age was statistically different (mean BMI 17.47 kg/m2 versus mean BMI 17.25 kg/m2 p-value 0.01). Systolic and diastolic blood pressure were higher in the HDP group (119.2 vs. 118.2 and 69.8 vs. 69.0, p-value 0.03 and 0.045 respectively), though differences were small. Non-response analysis showed that women included in this study were on average slightly younger (30.2 years vs. 30.6 years, p-value 0.02) and drank less alcohol (never used alcohol 50.6% vs. 51.1%, p-value <0.001) compared to women excluded from the study. No differences were observed in pre-pregnancy BMI, educational level and ethnicity between women included and excluded from the analyses (S2 Table in ).

Early childhood cardiometabolic risk factors

Apart from a negative association between maternal HDP and BMI at 12 months, (confounder model: -0.15 SD, 95% CI -0.27; -0.03), no associations between maternal HDP and childhood BMI at 2, 6 or 36 months were present (). No differences in results were observed when we used the ponderal index as outcome measurement instead of BMI at 2, 6, 12 and 36 months () [36]. Analyses with pulse as a different measure of common cardiometabolic risk factors, namely the sympatho-vagal balance, did not show different results (). The results did not change in sensitivity analyses with only pre-eclampsia and HELLP cases (S3 Table in ).

At 6 years of age, no associations between maternal HDP and systolic blood pressure, diastolic blood pressure, BMI, fat mass index, cholesterol or triglyceride levels were observed. Results of interaction tests demonstrated that maternal HDP were inversely associated with triglyceride levels at 6 years of age, but only in girls (confounder model -0.28 SD, 95% CI -0.45; -0.10) (). Results of interaction test with maternal BMI were significant, however after stratification of the results, no differences were observed (). The values of confounders for the regression analyses before and after multiple imputation did not show relevant differences (S4 Table in ).

Discussion

Principal findings

In this study, no strong and independent associations between maternal hypertensive disorders of pregnancy and early childhood cardiometabolic risk factors were observed. A negative association between maternal HDP and offspring BMI at the age of 12 months was observed, however this was no longer present at 2 and 6 years of age.

Results

Differences in systolic and diastolic blood pressure between the groups of women with and without a HDP were small. Moreover, mean blood pressures in the HDP group were relatively low. This could be explained by the fact that maternal blood pressure was measured in late pregnancy, i.e. ≥25 weeks of gestation. Thereby, the onset of a HDP could be (long) after the blood pressure measurement at the Generation R study research facility. Then, the blood pressure measurement in does not reflect blood pressure at the time of diagnosis. Second, a woman may be hospitalized due to a HDP, before she could attend the Generation R research facility: then her blood pressure measurement was missing. Lastly, the relatively low blood pressure could be due to the heterogeneity of the HDP group. Since hypertension isn’t one of the criteria to diagnose ‘HELLP syndrome’, the women with HELLP in the HDP group do not increase the mean systolic or diastolic blood pressure.

In earlier studies, maternal HDP has been associated with a lower BMI in the offspring [7, 9]. However, data are inconsistent and associations with higher BMI have also been demonstrated [51]. Additionally, in literature, associations of PE with offspring BMI became inverse after adjustment for potential confounding factors, with maternal pre-pregnancy BMI as the main covariate attributable to this change [7]. In our analyses, inverse associations were already present in the basic analyses, before adjusting for maternal pre-pregnancy BMI. This is possibly due to the small differences in BMI between women with and without a HDP in our study population.

Our findings are in line with the results of a previous study in the same cohort as the current study. That previous study demonstrated a strong association between an adverse maternal cardiometabolic profile and an adverse cardiometabolic profile in their offspring. Moreover, they demonstrated that this association was not attenuated by pregnancy complications such as preeclampsia [52]. This endorses that the effect of PE on the offspring cardiometabolic profile is only limited.

Similar to two other studies, we found no association between maternal HDP and offspring blood pressure [53]. This may in part be explained by the challenges of obtaining a reliable blood pressure measurement in young children. Since a physiologic childhood blood pressure has a smaller physiologic range compared to the adult blood pressure, it is harder to detect a (statistically significant) association with blood pressure in childhood. To address this point, the child’s pulse was added to our outcome measures. This measure is more variable, but this did not change the results.

Next, the presence of maternal HDP was found to be inversely associated with offspring triglyceride levels, but only in girls. In literature, sex differences in the lipid profile in healthy adults have been described. It is known that since sex hormones have the ability to modulate the lipid metabolism [54-56]. Additionally, an animal study demonstrated that in mice, PE led to sex-specific metabolomic differences in the offspring: the female fetuses showed pronounced alterations in the lipid metabolism [57]. More specifically, lipid metabolite levels that were associated with triglyceride storage were lower in the female fetuses in comparison to the male fetuses, which is in line with our findings. These sex-specific differences are proposed to be due to the significantly decreased expression of lipid transporters and lipid binding proteins in the female placentas that were exposed to PE [57]. For lipids other than triglycerides, no significant differences in the offspring were observed when comparing pregnancies complicated by a HDP and pregnancies not complicated by a HDP, which is also in line with previously published studies [13, 26, 28, 29, 58].

Many studies demonstrate that the associations between maternal HDP and cardiometabolic health in the offspring are mediated by adverse birth outcomes such as preterm birth and low birth weight [59, 60]. This amplified cardiometabolic risk, attributable to fetal growth restriction and preterm birth, is not limited to childhood but is demonstrated to persist into adulthood [61, 62]. Since no significant associations between HDP and cardiometabolic risk factors in the offspring were found in our first models, no mediation analyses with adverse birth outcomes such as preterm birth and low birth weight were performed.

Research implications

It is required to further explore the underlying mechanisms between maternal HDP and long term cardiometabolic health in the offspring. With help of metabolomics studies, the role of shared lifestyle related factors could be elucidated in the development of both hypertensive disorders and offspring cardiometabolic risk factors.

Strengths and limitations

The main strengths of our study are the large sample size, the prospective design of the study and the standardized procedures that were used for data collection. Moreover, this study is one of few studies to assess the associations of maternal HDP with fat mass percentage and lipid levels as measures of cardiometabolic health in early childhood [63]. In contrast, previous studies examining cardiometabolic health in offspring from women with a HDP mainly focused on BMI and blood pressure [8, 64].

Some limitations of this study also need to be addressed. First, follow-up data with regard to cardiometabolic outcomes in childhood varied from 41% to 68%. Especially response rates for measures from blood sampling (e.g. cholesterol) are lower compared to BMI measures. This may have contributed to selection bias. Second, the children in this study are relatively young and therefore large differences in cardiometabolic risk factors were not to be expected. This small variation in outcome measures makes it harder to detect statistically significant associations. Third, new guidelines state that PE is diagnosed based on the presence of de novo hypertension after 20 weeks gestation accompanied by one of the following: proteinuria, acute kidney injury, liver dysfunction, neurological features, haemolysis or thrombocytopenia, or fetal growth restriction [1, 65]. However, in our data we could only determine the presence of de novo hypertension, proteinuria and fetal growth restriction, possibly leading to misclassification of cases. To classify HDP by severity as best as possible, PE and HELLP was separated from GH [31, 66]. Fourth, even after adjusting for a large number of potential confounders, residual confounding may still be present in the observed associations. Examples of residual confounding could include lifestyle-related characteristics such as maternal (prenatal) physical activity. Finally, the majority of women in the study population were relatively young and had a low-risk profile. Moreover, in the groups of women both affected and unaffected by HDP, the mean gestational age at birth was at term. This implies relatively mild cases of HDP within this study population. As a result, the generalizability of the findings in this study is limited.

Conclusions

In this large, prospective, population-based cohort study, no strong and persistent associations between maternal HDP and cardiometabolic risk factors in the offspring between 2 months and 6 years of age were observed. Apart from small and favourable changes in BMI and triglycerides at some of the time points, the effects of maternal HDP on child cardiometabolic risk factors seem relatively minor. This however does not rule out effects on cardiometabolic health in the offspring in later life.

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2 Jul 2021

PONE-D-21-12261

Maternal hypertensive disorders in pregnancy and early childhood cardiometabolic risk factors: the Generation R Study.

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Reviewer #1: In the methods, it was described that maternal HDPs were defined at PE, GH, and HELLP. Do you have a data chart describing the average blood pressures, liver enzymes, etc. to provide evidence for these classifications? Also, do all of the PE patients exhibit proteinuria? Some literature reports discuss PE to be defined as elevated blood pressure, with or without proteinuria. If the PE cases don't have proteinuria, what is the distinguishing factor of the PE cases from the GH cases? Also, I think it would be beneficial to show the offspring parameters according to the certain HDP that the mother experienced.

There are a couple of grammatical changes that I would also suggest. A paper reads best when it is written with a consistent point of view. So instead of saying that "we found that the presence of maternal HDP was inversely associated with offspring triglyceride levels...", it may be better to reword this type of sentence to " the presence of maternal HDP was found to be inversely associated with offspring triglyceride levels..." to keep the entire paper written from the third person point of view. Additionally, the in text references should be listed before the period.

There were also a couple of times were the data was not provided. Do you have this data to make available? If not, I wouldn't include it in the results section.

Overall, this study provides some good information, but would definitely be strengthened if the offspring were continually monitored through adulthood, as you mentioned in the discussion.

Reviewer #2: The article conducted a systematic review to evaluate the relationship between maternal hypertensive disorder during pregnancy and the offspring cardiometabolic risk. The paper observed a negative association between maternal hypertension disorder and offspring BMI at 12 month. However, some major questions are also noticed:

The symptoms of cardiometabolic disorder include high blood sugar, high blood pressure, high triglycerides, low HDL, belly fat/central adiposity. One of the parameters used to determine cardiometabolic disorder in the paper is fat mass index, which will also include peripheral. Why didn’t the author use the waist to hip ratio or waist circumference?

HELLP is one of the pregnancy disorders the author evaluated in the following studies, which is diagnosed by AST, ALT, etc. However, HELLP is not always accompanied by high blood pressure. Did the author determine that the patient with HELLP indeed had hypertension?

The author found that maternal HDP is negatively associated with offspring BMI, but not ponderal index, while the author mentioned that PI could be a better measurement for infancy. It may be necessary to include the data of PI and maternal HDP. There is a common body mass measurement for infants under 2 years old, BMI for age according to WHO. This may give a more consistent result.

In addition, there is a minor issue:

In the method section, about pregnancy dating, the author mentioned CRL measurement. However no full name was given in the previous content.

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1 Oct 2021

We thank the reviewers and the editorial office of PLOS ONE for the opportunity to submit major revisions. We appreciate the reviewers’ elaborate suggestions that have improved our manuscript. Our answers (in bold) are as follows

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Unfortunately, we are not able to open the link since it’s leading to a paper saved on the C-storage. Since dr. Gaillards’ thesis is about maternal hypertensive disorders within the Generation R population, little overlap on textual parts, especially the methods section, is possible. Obviously, we would like to address this point and make textual changes.

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The datasets generated and analyzed during the current study are not publicly available due to individual privacy consideration. However, they are available from the data managers (Claudia J. Kruithof, c.kruithof@erasmusmc.nl or datamanagementgenr@erasmusmc.nl) and Director Generation R, Vincent Jaddoe (v.jaddoe@erasmusmc.nl) after a written agreement about the use of the data made via the Technology Transfer Office of Erasmus MC. We made adjustments accordingly in the revised cover letter.

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In the new, revised version of the manuscript, we added the data on pulse as outcome and the ponderal index as outcome measurement instead of BMI at 2, 6, 12 and 36 months (Table 2).

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'The Generation R Study was made possible by financial support from Erasmus MC, University

Medical Centre Rotterdam, the Netherlands; the Netherlands Organization for Health Research

and Development; the Netherlands Organization for Scientific Research; the Ministry of Health,

Welfare and Sport; and the Ministry of Youth and Families. Prof. Dr. Vincent Jaddoe received

additional grants from the Netherlands Organization for Health Research and Development

(grants 907.00303 and 916.10159, and VIDI 016.136.361) and a Consolidator Grant from the

European Research Council (ERC-2014-CoG-64916).

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This statement is added in the cover letter:

Funding Statement: The Generation R Study is made possible by financial support from Erasmus Medical Center, Erasmus University Rotterdam, Rotterdam, and the Netherlands Organization for Health Research and Development (ZonMw). The funders had no role in the design of the study, the data collection and analyses, the interpretation of data, or the preparation of, review of, and decision to submit the manuscript.

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Reviewer #1: Partly

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________________________________________

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5. Review Comments to the Author

Reviewer #1:

In the methods, it was described that maternal HDPs were defined at PE, GH, and HELLP. Do you have a data chart describing the average blood pressures, liver enzymes, etc. to provide evidence for these classifications?

As suggested by the reviewer, systolic and diastolic blood pressure measured in the third trimester of pregnancy were added to the baseline characteristics (Table 1). Unfortunately, no data on liver enzymes was present, since the diagnosis was based on medical records. Therefore, blood samples derived at the research center, do not solely represent the blood samples at the time of diagnosis in hospital.

Also, do all of the PE patients exhibit proteinuria? Some literature reports discuss PE to be defined as elevated blood pressure, with or without proteinuria. If the PE cases don't have proteinuria, what is the distinguishing factor of the PE cases from the GH cases?

Yes, to classify PE patients, the criteria of 2001 described by the International Society for the Study of Hypertension in Pregnancy were used. So, all of the PE patients (at least) had proteinuria.

We address this point in the discussion, since indeed there are new guidelines state that PE is diagnosed based on the presence of de novo hypertension after 20 weeks gestation accompanied by one of the following: proteinuria, acute kidney injury, liver dysfunction, neurological features, hemolysis or thrombocytopenia, or fetal growth restriction.

Also, I think it would be beneficial to show the offspring parameters according to the certain HDP that the mother experienced.

We added an extra table with the requested information: offspring parameters according to the certain type of HDP (S1 Table).

There are a couple of grammatical changes that I would also suggest. A paper reads best when it is written with a consistent point of view. So instead of saying that "we found that the presence of maternal HDP was inversely associated with offspring triglyceride levels...", it may be better to reword this type of sentence to " the presence of maternal HDP was found to be inversely associated with offspring triglyceride levels..." to keep the entire paper written from the third person point of view.

We thank the reviewer for this important point, and we made changes as suggested.

Additionally, the in text references should be listed before the period.

We made adjustments accordingly, and therefore listed references before the period.

There were also a couple of times were the data was not provided. Do you have this data to make available? If not, I wouldn't include it in the results section.

Now, that data is provided within the manuscript.

Overall, this study provides some good information, but would definitely be strengthened if the offspring were continually monitored through adulthood, as you mentioned in the discussion.

Indeed, we agree with the reviewer this is one of the most important discussion points within this manuscript.

Reviewer #2: The article conducted a systematic review to evaluate the relationship between maternal hypertensive disorder during pregnancy and the offspring cardiometabolic risk. The paper observed a negative association between maternal hypertension disorder and offspring BMI at 12 month. However, some major questions are also noticed:

The symptoms of cardiometabolic disorder include high blood sugar, high blood pressure, high triglycerides, low HDL, belly fat/central adiposity. One of the parameters used to determine cardiometabolic disorder in the paper is fat mass index, which will also include peripheral. Why didn’t the author use the waist to hip ratio or waist circumference?

We agree with the reviewer this measure is a good outcome measurement for cardiometabolic health. However, these measures may be imprecise and do not give any insight into the amount or differential effects of visceral and subcutaneous fat compartments.

HELLP is one of the pregnancy disorders the author evaluated in the following studies, which is diagnosed by AST, ALT, etc. However, HELLP is not always accompanied by high blood pressure. Did the author determine that the patient with HELLP indeed had hypertension?

Indeed, the author is right that HELLP does not always have to be accompanied by hypertension or proteinuria. Since the HELLP syndrome is one serious manifestation of pre-eclampsia we choose to take this disorder into account as well, despite the possibility of the absence of hypertension. Lastly, gestational hypertension and pre-eclampsia: HDP cases included 293 cases of GH, 139 cases of PE, 14 cases of HELLP, 20 cases of PE and HELLP and 25 cases of superponated PE/HELLP. Meaning, that holding onto the hypertension criterion, only 14 cases would be taken out of the analyses (since 20 had PE and HELLP, and 25 cases had superponated PE/HELLP and thus already manifested hypertension in pregnancy.)

The author found that maternal HDP is negatively associated with offspring BMI, but not ponderal index, while the author mentioned that PI could be a better measurement for infancy. It may be necessary to include the data of PI and maternal HDP.

We did not observe differences in results when we used the ponderal index as outcome measurement instead of BMI at 2, 6, 12 and 36 month. These results are now included in Table 2.

There is a common body mass measurement for infants under 2 years old, BMI for age according to WHO. This may give a more consistent result.

We thank the reviewer for this point. We are aware that both ponderal index and BMI for age are strongly correlated. Additionally, changes in PI/BMI in early infancy (until 10 years of age) are associated with greater fat-mass in later life. Moreover, we found comparable results in the analyses with both offspring BMI and the measure which is more frequently used in a clinical setting: ponderal index.

In addition, there is a minor issue: In the method section, about pregnancy dating, the author mentioned CRL measurement. However no full name was given in the previous content.

Indeed, we apologize for this, and now added the full name into the manuscript, which is crown-rump length.

________________________________________

S1 Table. Offspring parameters according to the certain HDP that the mother experienced.

Submitted filename: Rebuttal PONE-D-21-12261.docx

Click here for additional data file.

18 Nov 2021

PONE-D-21-12261R1Maternal hypertensive disorders in pregnancy and early childhood cardiometabolic risk factors: the Generation R Study.PLOS ONE

Dear Dr. Gootjes,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

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**********

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Reviewer #1: Yes

Reviewer #2: N/A

**********

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**********

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Reviewer #1: I found very few instances of grammatical errors, so one more round of proof reading should occur before submission. Additionally, in Table 1, which defines the maternal characteristics of the sample populations, the systolic and diastolic blood pressures are only slightly elevated. 118 vs 119 (systolic) and 69.0 vs 69.8 (diastolic) between the women without HDP vs those with HDP respectively. As mentioned in the methods, the defining characteristics of two of the three pregnancy complications are defined as systolic/diastolic blood pressures of greater than 140/80, which is relatively higher than the mean for the mothers with HDPs. Can the authors explain why the mean of the HDP was so low? Is it due to the HELLP syndrome mothers not exhibiting high blood pressure?

Reviewer #2: (No Response)

**********

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21 Nov 2021

We thank the reviewers and the editorial office of PLOS ONE for the opportunity to again submit major revisions. Our answers (between **) are as follows

Reviewers' comments:

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Comments to the Author

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Reviewer #1: All comments have been addressed

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________________________________________

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________________________________________

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________________________________________

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Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

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Reviewer #1:

I found very few instances of grammatical errors, so one more round of proof reading should occur before submission.

*Apologies, the manuscript was thoroughly checked again. Some mistakes have crept in after formatting the manuscript from ‘track changes’ to ‘no track changes’.*

Additionally, in Table 1, which defines the maternal characteristics of the sample populations, the systolic and diastolic blood pressures are only slightly elevated. 118 vs 119 (systolic) and 69.0 vs 69.8 (diastolic) between the women without HDP vs those with HDP respectively. As mentioned in the methods, the defining characteristics of two of the three pregnancy complications are defined as systolic/diastolic blood pressures of greater than 140/80, which is relatively higher than the mean for the mothers with HDPs. Can the authors explain why the mean of the HDP was so low? Is it due to the HELLP syndrome mothers not exhibiting high blood pressure?

*Thank you for addressing this important point. There are 3 possible explanations for the relative low (mean) blood pressures and small differences in the blood pressures between the two groups.

1. Timing of measurement.

The maternal blood pressure was measured in the third measurement period of the study, i.e. ‘late pregnancy’, which was defined as ≥25 weeks gestational age. However, hypertensive disorders of pregnancy (such as preeclampsia) are most prevalent at 34 or more weeks of gestation, with an incidence of 2.7%. von Dadelszen et al. Subclassification of preeclampsia. Hypertens Pregnancy. 2003;22(2).

Lisonkova et al. Incidence of preeclampsia: risk factors and outcomes associated with early- versus late-onset disease. Am J Obstet Gynecol. 2013;209(6). We retrieved the diagnosis of a hypertensive disorder of pregnancy in retrospect from medical records. These blood pressure measurements therefore do not reflect the blood pressure measurement at the time of diagnosis.

2. Missing data

Before they were able to attend the measurement at the Generation R study Centre, women could already be hospitalized due to a hypertensive disorder of pregnancy.

So, these women are classified as having a HDP, and we have follow up data with regard to their infant cardiometabolic health. However, we then lack the data of (high) blood pressure in the latest phase of pregnancy.

3. Heterogeneity of the hypertensive disorders.

Indeed, hypertension isn’t one of the criteria to diagnose ‘HELLP syndrome’, thereby the women with this diagnosis do not affect the mean blood pressure in the ‘HDP-group’.

Additionally, it is interesting to mention that the maximum blood pressures are 185 (systolic) and 118 (diastolic), indicating that indeed there are women with a hypertensive disorder of pregnancy in this group already.

These points were added to the manuscript, chapter ‘Results’ lines 8-18:

Differences in systolic and diastolic blood pressure between the groups of women with and without a HDP were small. Moreover, mean blood pressures in the HDP group were relatively low. This could be explained by the fact that maternal blood pressure was measured in late pregnancy, i.e. ≥25 weeks of gestation. Thereby, the onset of a HDP could be (long) after the blood pressure measurement at the Generation R study research facility. Then, the blood pressure measurement in Table 1 does not reflect blood pressure at the time of diagnosis. Second, a woman may be hospitalized due to a HDP, before she could attend the Generation R research facility: then her blood pressure measurement was missing. Lastly, the relatively low blood pressure could be due to the heterogeneity of the HDP group. Since hypertension isn’t one of the criteria to diagnose ‘HELLP syndrome’, the women with HELLP in the HDP group do not increase the mean systolic or diastolic blood pressure.*

Reviewer #2: (No Response)

________________________________________

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Reviewer #1: No

Reviewer #2: No

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*PACE corrected files were uploaded.*

Submitted filename: Response to Reviewers PONE-D-21-12261R1.docx

Click here for additional data file.

1 Dec 2021

Maternal hypertensive disorders in pregnancy and early childhood cardiometabolic risk factors: the Generation R Study.

PONE-D-21-12261R2

Dear Dr. Gootjes,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Linglin Xie

Academic Editor

PLOS ONE

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Reviewer #1: All comments have been addressed

**********

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**********

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**********

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Reviewer #1: Yes

**********

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**********

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13 Dec 2021

PONE-D-21-12261R2

Maternal hypertensive disorders in pregnancy and early childhood cardiometabolic risk factors: the Generation R Study.

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Table 1

Characteristics of the study population.

	Study population	No HDP	HDP	p-value
	n = 7794	n = 7303	n = 491
Maternal characteristics
Maternal age at enrolment (years)	30.2 (20.2–37.9)	30.2 (20.2–37.8)	30.0 (20.0–38.1)	0.81
Pre-pregnancy BMI (kg/m2)	22.7 (18.6–32.4)	22.6 (18.6–32.4)	22.7 (18.4–33.0)	0.75
High educational level, n (%)	3073 (39.4%)	2878 (39.4%)	195 (39.7%)	0.98
Dutch and Western ethnicity, n (%)	4479 (57.5%)	4192 (57.4%)	287 (58.5%)	0.53
Nulliparous, n (%)	4260 (55.4%)	3995 (54.7%)	265 (54.0%)	0.87
Never smoked in pregnancy, n (%)	5651 (72.5%)	5278 (72.3%)	373 (76.0%)	0.23
Never drank alcohol in pregnancy, n (%)	3940 (50.6%)	3685 (50.5%)	255 (51.9%)	0.25
Glucose (mmol/l)	4.4 (0.8)	4.4 (0.8)	4.4 (0.9)	0.76
Systolic blood pressure	118.3 (12.0)	118.2 (12.0)	119.2 (11.8)	0.03
Diastolic blood pressure	69.0 (9.4)	69.0 (9.3)	69.8 (9.9)	0.045
Child characteristics
Male sex, n (%)	3952 (50.7%)	3714 (50.9%)	239 (48.7%)	0.35
Gestational age at birth (weeks)	40.1 (36.9–42.1)	40.1 (36.7–42.1)	40.1 (37.1–42.0)	0.52
Preterm birth, n (%)	441 (5.7%)	418 (5.7%)	23 (4.7%)	0.34
Birth weight (grams)	3415 (561)	3417 (564)	3400 (530)	0.82

Abbreviations: BMI, body mass index; HDP, hypertensive disorder of pregnancy. HDP included: 293 cases of GH, 139 cases of PE, 14 cases of HELLP, 20 cases of PE and HELLP and 25 cases of superponated PE/HELLP. Values are percentages for categorical variables, means (SD) for continuous variables with a normal distribution, or medians (5th, 95th percentile) for continuous variables with a skewed distribution. Confounders are imputed. Non-imputed values are presented as valid percentages. Differences in baseline characteristics were tested using Students t-test, Mann-Whitney and chi-square tests.

Table 2

Associations between HDP and childhood cardiometabolic risk factors.

	Cardiometabolic risk factor			Model
				Basic		Confounder
		n	n	β (95% CI)	p-value	β (95% CI)	p-value
			HDP
2 months	BMI	3779	235 (6.2%)	-0.06 (-0.19; 0.08)	0.41	-0.05 (-0.18; 0.09)	0.50
	PI	3779	235 (6.2%)	-0.09 (-0.24; 0.07)	0.28	-0.08 (-0.24; 0.07)	0.31
6 months	BMI	4518	267 (5.9%)	-0.11 (-0.23; 0.02)	0.10	-0.09 (-0.21; 0.04)	0.17
	PI	4518	267 (5.9%)	-0.13 (-0.25; -0.003)	0.045	-0.11 (-0.23; 0.02)	0.09
12 months	BMI	4614	283 (6.1%)	-0.16 (-0.28; -0.04)	0.01	-0.15 (-0.27; -0.03)	0.02
	PI	4614	283 (6.1%)	-0.17 (-0.29; -0.05)	0.01	-0.17 (-0.29; -0.05)	0.01
36 months	BMI	3933	263 (6.7%)	-0.03 (-0.16; 0.10)	0.67	-0.002 (-0.13; 0.13)	0.97
	PI	3933	263 (6.7%)	-0.09 (-0.22; 0.04)	0.18	-0.06 (-0.19; 0.07)	0.35
6 years	BMI ¶	5312	343 (6.5%)	0.02 (-0.08; 0.12)	0.71	0.03 (-0.07; 0.13)	0.53
	Systolic blood pressure	4874	321 (6.6%)	0.04 (-0.08; 0.15)	0.50	0.05 (-0.07; 0.16)	0.42
	Diastolic blood pressure	4874	321 (6.6%)	0.09 (-0.02; 0.21)	0.10	0.10 (-0.01; 0.21)	0.09
	Fat mass index ¶	5163	330 (6.4%)	0.03 (-0.08; 0.13)	0.62	0.04 (-0.06; 0.14)	0.42
	Cholesterol ¶	3531	241 (6.8%)	0.01 (-0.12; 0.14)	0.93	0.01 (-0.12; 0.14)	0.87
	Triglycerides ¶	3523	239 (6.8%)	-0.10 (-0.23; 0.03)	0.13	-0.10 (-0.23; 0.03)	0.14
	Pulse	4873	347 (7.1%)	1.10 (-0.09; 2.29)	0.07	1.18 (-0.01; 2.37)	0.05
	Cardiometabolic risk factor clustering	3196	217 (6.8%)	1.15 (0.97; 1.35)	0.41	1.16 (0.84; 1.60)	0.38

Abbreviations: BMI, body mass index; PI, ponderal index; HDP, hypertensive disorder of pregnancy. Values are regression coefficients (95% confidence interval) from (logistic) regression analyses that reflect the difference in childhood outcomes in SD scores, in pregnancies complicated by HDP versus pregnancies not complicated by HDP. Basic model was adjusted for child’s sex. Confounder model includes maternal pre-pregnancy body mass index, educational level, ethnicity, smoking during pregnancy, alcohol use during pregnancy, maternal glucose levels and presence of gestational diabetes mellitus.

¶Variables were log transformed.

Table 3

HDP and childhood cardiometabolic risk factors at 6 years of age, split for child’s sex.

			Boys (N = 3952)			Girls (N = 3842)
Cardiometabolic risk factor	Model	n	β (95% CI)	p-value	n	β (95% CI)	p-value
Fat mass index ¶	Basic	2568	0.09 (-0.06; 0.25)	0.23	2594	-0.04 (-0.18; 0.11)	0.64
	Confounder	2568	0.12 (-0.02; 0.27)	0.09	2594	-0.03 (-0.17; 0.11)	0.66
Cholesterol ¶	Basic	1798	0.15 (-0.04; 0.33)	0.12	1733	-0.12 (-0.30; 0.07)	0.20
	Confounder	1798	0.16 (-0.03; 0.34)	0.09	1733	-0.12 (-0.30; 0.07)	0.23
Triglycerides ¶	Basic	1796	0.09 (-0.11; 0.28)	0.38	1727	-0.27 (-0.45; -0.09)	0.003
	Confounder	1796	0.09 (-0.10; 0.28)	0.36	1727	-0.28 (-0.45; -0.10)	0.002

Abbreviations: HDP, hypertensive disorder of pregnancy. Values are (logistic) regression coefficients (95% confidence interval) that reflect the difference in early childhood outcomes in SD scores, in pregnancies complicated by HDP versus pregnancies not complicated by HDP. Basic model was adjusted for child’s sex. The confounder model includes maternal pre-pregnancy body mass index, educational level, ethnicity, smoking during pregnancy, alcohol use during pregnancy, maternal glucose levels and gestational diabetes mellitus.

¶Variables were log transformed.

Table 4

HDP and early childhood cardiometabolic risk factors at 6 years of age, split for maternal pre-pregnancy BMI.

		<18.5 (N = 315)		18.5–25.0 (N = 5280)		>25.0 (N = 2223)
Cardiometabolic risk factor	Model	β (95% CI)	p-value	β (95% CI)	p-value	β (95% CI)	p-value
BMI ¶	Basic	0.05 (-0.45; 0.54)	0.86	-0.05 (-0.17; 0.08)	0.44	0.20 (-0.02; 0.42)	0.08
	Confounder	0.06 (-0.41; 0.54)	0.80	-0.03 (-0.15; 0.09)	0.64	0.20 (-0.02; 0.41)	0.07

Abbreviations: HDP, hypertensive disorder of pregnancy; BMI, body mass index. Values are regression coefficients (95% confidence interval) that reflect the difference in early childhood outcomes in SD scores, in pregnancies complicated by HDP versus pregnancies not complicated by HDP. Basic model was adjusted for child’s sex. Confounder model includes educational level, ethnicity, smoking during pregnancy, alcohol use during pregnancy, maternal glucose levels and gestational diabetes mellitus.

¶Variables were log transformed.