Journal of Hypertension:
C-reactive protein and later preeclampsia: systematic review and meta-analysis taking into account the weight status
Rebelo, Fernandaa,b; Schlüssel, Michael M.a; Vaz, Juliana S.a,b; Franco-Sena, Ana Beatriza,b; Pinto, Thatiana J.P.a; Bastos, Francisco I.c; Adegboye, Amanda R.A.d; Kac, Gilbertoa,b
aDepartment of Social and Applied Nutrition, Nutritional Epidemiology Observatory, Josué de Castro Institute of Nutrition, Federal University of Rio de Janeiro
bGraduate Program in Nutrition, Josué de Castro Institute of Nutrition, Federal University of Rio de Janeiro
cDepartment of Health Information, Center for Scientific and Technological Information, Oswaldo Cruz Foundation, Rio de Janeiro, Rio de Janeiro, Brazil
dResearch Unit for Dietary Studies. Institute of Preventive Medicine, Copenhagen University Hospital, Copenhagen, Denmark
Correspondence to Professor Gilberto Kac, Nutritional Epidemiology Observatory, Department of Social and Applied Nutrition, Josué de Castro Institute of Nutrition, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil. Av. Carlos Chagas Filho, 373, CCS, Bloco J, 2° andar. Cidade Universitária – Ilha do Fundão. CEP: 21941-902. Rio de Janeiro – RJ. Brasil. Tel: +55 (21) 25626595; fax: +55 (21) 22808343; e-mail: firstname.lastname@example.org@nutricao.ufrj.br
Abbreviations: CI, confidence interval; CRP, C-reactive protein; MOOSE, Meta-Analysis of Observational Studies in Epidemiology: A Proposal for Reporting; PE, preeclampsia; PRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses Group guidelines; SD, standard deviation; SLR, systematic literature review; WMD, weighted mean difference
Received 23 July, 2012
Revised 31 August, 2012
Accepted 4 October, 2012
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (http://www.jhypertension.com).
Objectives: This study aims to determine whether high C-reactive protein (CRP) concentration during pregnancy is associated with later preeclampsia and whether weight status (BMI) is a potential modifier of the relation between CRP and preeclampsia.
Methods: Twenty-three studies were included in a systematic literature review and a subset of 18 in a meta-analysis. Weighted mean difference (WMD) [with their 95% confidence intervals (CI)] of CRP in preeclampsia and control groups was the estimator. A quality assessment was carried out using a scale specifically developed for this study. Meta-regression with estimates for study characteristics and inter-arm differences and sensitivity and subgroup analysis was employed. Statistical heterogeneity was investigated using I2 statistic.
Results: The pooled estimated CRP between 727 women, who developed preeclampsia and 3538 controls was 2.30 mg/l (95% CI: 1.27–3.34). The heterogeneity among studies was high (I2 = 92.8). The WMD was found to be lower in studies comprising preeclampsia and control groups with similar BMI [WMD = 0.85 (95% CI: 0.10–1.61); I2 = 25.3%] compared with studies among which BMI was significantly elevated in the preeclampsia group [2.01 (95% CI: 1.23–2.78); I2 = 0.0%], which may explain the high heterogeneity of pooled data. Meta-regression results confirmed that difference in BMI between groups modifies the association of CRP and preeclampsia. High quality studies represented 30%.
Conclusion: The pooled WMD suggest that women with higher levels of CRP may have an increased risk of developing preeclampsia. This association seems to be modified by confounders, such as BMI. Further studies of high methodological quality are needed.
Preeclampsia is one of the most common complications after the 20th week of gestation, and is characterized by high systemic blood pressure and proteinuria . It affects 2–8% of the obstetric population, worldwide, and is associated with higher maternal mortality, as well as maternal and neonatal morbidity [2,3]. From 2000 to 2006, preeclampsia accounted for 16% of deaths related to pregnancy in a representative sample in the United States .
The cause of preeclampsia remains unknown, but many factors seem to be associated with its development . Inflammation has been shown to be an important contributor to the pathogenesis of this disease . Clinical and biochemical data suggest that endothelial dysfunction may be the primary cause of this condition  and that this dysfunction is accompanied by an elevation in inflammatory markers, which have been investigated as possible predictors of preeclampsia, especially C-reactive protein (CRP) [8,9].
CRP is an important component of the innate immune system and is initially produced in the liver as an acute phase protein in response to inflammatory stimuli . The measurement of serum concentrations of this protein has been used to monitor the course of infectious and inflammatory diseases .
Many studies have shown higher CRP concentrations in preeclampsia compared with normotensive pregnant women [12–14]. However, most of the findings were based on cross-sectional analyses of small, convenience samples. Due to the temporal ambiguity generated by this type of design and the lack of adequate statistical power/external validity, these studies do not clarify whether the elevated CRP concentration is a cause or a consequence of preeclampsia. Weight status is closely related to the serum concentration of inflammatory cytokines such as CRP, but few studies have taken it into account.
This systematic literature review (SLR) and meta-analysis aims to compile the results of studies that have prospectively investigated CRP concentration and the subsequent occurrence of preeclampsia, taking in consideration the role of weight status.
The study design consisted of a SLR followed by a meta-analysis, both conducted taking into account the Preferred Reporting Items for Systematic reviews and Meta-Analyses Group guidelines (PRISMA)  and the Meta-Analysis of Observational Studies in Epidemiology: A Proposal for Reporting (MOOSE) .
In November 2011, investigators (F.R., M.M.S., F.I.B.) performed a search in three different databases: Scopus, PubMed and Web of Science (ISI). The following medical subject headings and key words were used: (’preeclampsia’ OR ‘preeclampsia’) AND (’CRP’ OR ‘C reactive protein’ OR ‘C-reactive protein’). The Cochrane Library was also consulted in the search for studies on the same topic and returned no results.
To be included in the SLR, the studies had to be an original work and not a literature review, include preeclampsia as one of the main outcomes, include the measurement of serum CRP concentrations prior to the diagnosis of preeclampsia, provide data allowing analysis of the association between CRP and preeclampsia, and be a study with humans. No dates or language restrictions were applied.
To identify additional pertinent publications, a hand-search of all selected article reference lists was performed. The search was updated in August 2012 immediately before submission to Journal of Hypertension.
Selection of studies
Figure 1 is a flowchart based on the proposal of the PRISMA Group (2009)  that outlines the study selection process. The selection process retrieved 277 references in Scopus, 157 references in PubMed and 214 references in the Web of Science. The references were primarily selected by reading the title and abstract, which were read by two independent reviewers (F.R., M.M.S.). Disagreements were resolved through discussion and consensus.
The reasons for exclusion are listed in Figure 1. Moreover, the examination of selected articles’ reference lists did not retrieve any additional study. An update performed in July 2012 retrieved one article that met the inclusion criteria. Twenty-three studies were selected for the SLR. We contacted the author of one article that was published in Persian  in an attempt to obtain more information in English but did not receive a reply; therefore, we only included data available in the abstract. This article was not included in the quality assessment or in the meta-analysis.
The following information was extracted from the studies: year of publication, country and city where the study was conducted, gestational age in weeks at the time of blood drawn, patient age, study design, study aims, sample size, specimen type used to assess CRP levels (serum or plasma), main results, whether the study controlled for weight status, and statistical tests used in the analysis from which the main findings were extracted.
The meta-analysis was performed using mean and standard deviation (SD) of CRP levels for each group (preeclampsia versus normotensive women). If the required data could not be found in the published report, the author was contacted and asked for supplementary data. Fifteen days after the first contact, we sent a reminder. If the author did not reply, whenever possible, the data were transformed using different procedures described below. Otherwise, the study was not included in the meta-analysis.
From the 23 selected studies to be reviewed, six provided the necessary data in the article. Seven authors answered the contact, but only four were able to provide the requested data. Seven studies provided only values of median and range. In these cases, the mean and SD were estimated using the recommendations of Hozo et al. (2005) . Four out of these seven reports presented only box-plot graphs and not the actual values of medians or ranges for each group. In such cases, the median was estimated using ‘GetData Graph Digitizer’. For articles that presented both the median and the box-plot, we did not observe a difference between the medians estimated using ‘GetData Graph Digitizer’ and the values provided by the authors.
One article reported the serum levels of CRP as their mean and respective 95% confidence interval (CI) . To calculate the SD, the following formula was used: SD = √N(Lu–Ll)/3.92, where N is the number of patients and Lu and Ll are the upper and lower limits of the CI, respectively. Therefore, 18 studies were included in the meta-analysis.
The quality assessment was performed with an instrument developed specifically for this study (see Instrument, Supplemental Digital Content 1, which lists all items and scores of the quality assessment, http://links.lww.com/HJH/A210). The development of the instrument took into account the assessment of the sampling methods, measurement of CRP, definition of preeclampsia, statistical analysis and discussion of study limitations.
Two authors of the present study (F.R., A.B.F.) independently performed the quality assessment. The initial agreement was calculated using the κ coefficient. Differences were resolved through discussion and consensus. The instrument consisted of six questions. For each question, scored points ranging from 0 to 3 were given, in which ‘3’ was the highest quality answer and ‘0’ applied to those that did not comply with the requirements of each specific item. Overall, the publications were classified as high quality (score ≥ 10), average quality (8 or 9 points) and low quality (score < 8).
To estimate the size of the effect, we used a random effects model weighted by the inverse of variance and presented the results as the weighted mean difference (WMD) and 95% CI. Statistical heterogeneity was investigated using the I2 statistic and respective 95% CI. An I2 of more than 50% was considered notable heterogeneity. Sensitivity analysis was performed omitting every single study, one by one, in successive steps, in order to evaluate the influence of each publication on the summary WMD, in the context of significant heterogeneity.
The potential origin of heterogeneity was first evaluated through a subgroup analysis considering the moment of CRP evaluation (first trimester vs. others), difference in BMI between groups, specimen type (serum vs. plasma), publication quality score, method of obtaining mean and SD (given in the report/contact with authors vs. estimated by formulas) and study design (prospective nested case–control vs. others).
A univariate meta-regression was performed to access between and within-studies confounders’ imbalances. The differences between studies were explored comparing the average values across all patients (age, parity, gestational age at blood draw, BMI), specific parameters of each study (sensibility of CRP assay, specimen type and quality score, study design and method of estimation of mean and SD). Due to the observational nature of included studies, potential confounders are not always symmetric distributed in case and control groups. This within-study difference was explored adjusting the effect size for potential imbalance between groups (the variables included in this analysis was the WMD for: age, parity, gestational age at blood draw and BMI), according to Trowman et al. (2007) .
Multivariable meta-regressions were performed to adjust for some potential effect modifiers, such as age, parity, method of estimation of mean and SD, and BMI (variables with P-value less than 0.20 in the univariate meta-regression). However, in the multivariable meta-regression the number of studies with all the available information was reduced to only six. For this reason we removed parity and performed a multivariable meta-regression adjusting for age, method of estimation of mean and SD and BMI.
All analyses were performed with Stata software, version 10.1 (Stata Corp., College Station, Texas, USA).
Description of systematic literature review studies
Twenty-three studies published from 2001 to 2012 were included in the SLR. Seven of these studies were conducted in the United States [8,19,21–25]; eleven, in Europe [9,26–35]; and one, in Australia . Only four studies were conducted in low and middle-income countries [12,17,37,38] (Table 1).
In eight studies, CRP evaluation was conducted during the first trimester [21,23,27,29–32,34]. In eight studies, the assessment occurred during the second or third trimester [8,12,26,32,35–38], and in seven studies, the analysis was performed combining information on women's CRP levels relative to the first and second trimester [9,17,19,22,24,25,28]. Only four studies measured CRP at more than one point during pregnancy [12,22,25,32]. Most participants were young adult women, with a mean age between 20.2 and 35.2 years, which, in general, was similar between case and control groups. Fourteen of the 23 studies used a prospective nested case–control design [12,19,21–23,27–30,32–35,37] (Table 1).
The sample size of the studies varied from 88 to 5657 patients. Five out of 23 studies used plasma specimens to evaluate the CRP levels [9,29,32,33,37], and two studies did not specify the specimen type [12,36]. All other studies reported the use of serum in the CRP assay [8,17,19,21–28,30,31,34,35,38] (Table 1).
Among the 23 selected studies, only five did not report weight status as a potential confounder of the association between CRP and preeclampsia [12,17,29,31,35]. The most common indicator used to adjust for the effect of weight status was BMI. Two studies used the differences in maternal weight between the control (normotensive) and preeclampsia groups and did not find any significant difference [24,34].
Twelve of the 23 studies found a positive and significant association between higher CRP concentrations during early or middle pregnancy and the subsequent occurrence of preeclampsia [9,17,19,21,23,24,28,29,31,36–38] when the analyses were not adjusted for any variable reflecting weight status. Considering these 12 studies, three lost statistical significance after including BMI in the model [9,21,23], three did not adjust for any weight status indicator [17,29,31], and four showed that BMI was significantly higher in the preeclampsia group compared with the controls [19,28,36,38]. One study did not show differences in BMI between groups (BMI-matched case–controls) , and one did not find any difference in maternal weight between groups . In two studies [8,23], the risk of developing preeclampsia among women with elevated serum concentrations of CRP was higher among women with BMI less than 25.0 kg/m2 as compared with women with lower BMIs (see Table Supplemental Digital Content 2, which describes the aim, statistical analysis and main findings of the reviewed studies, http://links.lww.com/HJH/A211).
The initial agreement between the two authors on the quality score was 86.4%. The assessment revealed few publications of high quality [8,9,19,21,25,30,38] and some methodological flaws. No article received the maximum score (13 points), and only six studies did not have a single answer scored as zero [8,9,30,25,34,38].
The scores and classification according to each question and total score are described in detail in Figure 2. The factors that most adversely affected the quality of the articles were the low sensitivity of the assay methods for CRP measurement, inadequate adjustment during statistical analysis and absence of any discussion about the study limitations (see Figure, Supplemental Digital Content 3, which presents the results of this evaluation with the most prevalent sources of bias in these studies, http://links.lww.com/HJH/A212).
Seven studies provided all necessary data in the published report to perform the meta-analysis [12,19,24,29,32,37,38]. Four authors answered our contact and provided the requested data [8,27,28,36]. In seven studies, the mean and SD were estimated by the median and range [21,22,25,26,33–35]. In four of these seven studies, the median or range was estimated from box-plot charts [21,22,34,35]. In summary, 18 of the 23 SLR articles were included in the meta-analysis, comprising a total sample of 727 women who developed preeclampsia and 3538 controls.
The pooled estimate of CRP difference was 2.30 mg/l (1.27–3.34; I2 = 92.8%, 95% CI: 90.0–94.8). CRP was higher in women who developed preeclampsia compared with the normotensive patients, demonstrating a positive association (Fig. 3). In the sensitivity analysis, the WMD ranged from 1.73 (0.99–2.47) to 2.55 (1.32–3.77). The lower limits of the CI never crossed zero, which indicates that the direction of the result is not modifiable by the exclusion of any single study. Although the studies of Ruma et al. and Tjoa et al. presented a quite high WMD in comparison to all other studies, the results from the sensitivity analysis excluding both at the same time, did not modify the direction of the results [WMD = 1.76 (0.79–2.73), I2 = 91.8%, 95% CI: 88.3–94.3].
Less heterogeneity was found considering the difference in BMI between groups. The WMD was lower in those studies whose groups were comparable in respect to BMI [0.85 (0.10–1.61); I2 = 25.3%, 95% CI: 0.0–68.6] compared with those in which BMI was significantly elevated in the preeclampsia group [2.01 (1.23–2.78); I2 = 0.0%, 95% CI: 0.0–68.8].
Low heterogeneity (I2 = 29.5%) and lower WMD [0.73 (0.21–1.26) vs. 3.60 (1.59–5.60)] was observed in the subgroup of studies that the mean and SD was estimated by formulas.
Additional subgroup analysis have shown lower WMD and more heterogeneous results for studies that used blood drawn in the second and/or third trimester [1.78 (0.37–3.19), I2 = 95.9%, 95% CI: 93.8–97.3] as opposed to studies that performed biochemical evaluation prior to the 13th week [3.35 (0.54–6.16), I2 = 87.9%, 95% CI: 74.3–94.3], whereas a significant association was found in studies that analyzed CRP in serum samples [2.01 (0.77–3.24), I2 = 94.1%, 95% CI: 91.5–96.0] but not in plasma specimen [3.28 (−0.14–6.70), I2 = 91.9%, 95% CI: 82.4–96.3]. The WMD was statistically significant irrespective of the design of each specific study, and studies evaluated as high quality did not show significant associations (Table 2) (see Figure, Supplemental Digital Content 4, which presents the forest plots for all subgroup analysis, http://links.lww.com/HJH/A213).
The univariate meta-regression has shown that a BMI imbalance between groups is a significant effect modifier of the relation between CRP and preeclampsia. For each 1.0 kg/m2 variation on BMI WMD between groups an increase of 0.38 mg/l on CRP WMD is expected (Fig. 4). No other variable included in the meta-regression model could explain the differences in WMD between studies (Table 3).
Multivariable meta-regression model showed that BMI remained significant (β = 0.35, 95% CI: 0.06–0.65, P-value = 0.025) when analysis was adjusted for age and method of estimation of mean and SD (Results not shown in tables).
Our meta-analysis results have shown a positive association between CRP levels and development of preeclampsia. The pooled estimated CRP mean difference between 727 women, who developed preeclampsia and 3538 controls was 2.30 mg/l (95% CI: 1.27–3.34). Meta-regression results confirmed that this association was modified by the weight status, as basically assessed by BMI. The difference in BMI between preeclampsia and control groups proved to be an important confounding factor, explaining the high heterogeneity of overall analyses. The WMD was found to be lower in studies comprising preeclampsia and control groups with similar BMI compared with studies among which BMI was significantly elevated in the preeclampsia group.
A central issue in establishing the usefulness of CRP as a marker of preeclampsia lies in its association with adiposity. There is a well known association among overweight, alterations in lipid concentrations and the activation of inflammatory markers [39–44]. Both of these metabolic disturbances are commonly present in pregnancies complicated by preeclampsia before the onset of the clinical syndrome [45,46]. In the present SLR, some studies may have found a spurious association, as they did not control for BMI [19,21,22,28,36]. Women who developed preeclampsia were likely to be found among those with higher mean BMI.
In the first study that prospectively investigated the relationship between CRP concentration and the subsequent development of preeclampsia, Wolf et al. found a 3.5-fold increased chance of developing preeclampsia in those women with first trimester CRP concentrations more than 4.1 mg/l compared with those with CRP concentration less than 1.1 mg/l. However, this association was greatly attenuated and was not statistically significant after adjusting for maternal prepregnancy BMI. The authors suggested that inflammation played a role in the causal pathway through which prepregnancy overweight leads to an increased risk of preeclampsia. De Jonge et al. and Qiu et al. also observed that CRP was not a significant predictor of preeclampsia after the inclusion of BMI in the multiple regression models. However, Qiu et al. reported elevated CRP concentrations among lean women associated with a 2.5-fold increased chance of preeclampsia. Furthermore, maternal overweight status in the absence of elevated CRP concentrations was associated with a 4.9-fold increased chance of preeclampsia, and women who were overweight and also had elevated CRP concentrations had an even higher chance of preeclampsia (OR = 5.5). In the study by Scholl et al., after the data were stratified by BMI and all confounding factors were controlled for, only women with BMI less than 25.0 kg/m2 had increased chance of developing preeclampsia (OR = 2.72). When the CRP concentration was high and women were overweight or obese, the chance of developing preeclampsia did not increase, even when the cutoff was raised to the 90th percentile of the cohort. A possible explanation for these results is that adipocytes are the major source of basal IL-6 and TNF-α secretion, which are the primary stimuli for hepatic CRP production . Therefore, the sensitivity of CRP as a biomarker of inflammation is lower in overweight/obese women, as this is a cytokine, which is usually in high concentration when there is a substantial fat store [48–50]. Only these two studies stratified the analysis by BMI, which proved to be a better analytical strategy than the simple inclusion of BMI as a covariate in logistic or linear models.
In the present meta-analysis, the subgroup analysis including studies with similar mean BMI between groups decreased the estimated effect, however WMD remained significant and I2 become more homogeneous. Alternatively, in the analysis restricted to studies with significantly higher BMI means observed for preeclampsia groups, the magnitude of the effect was found to be high. Additionally, in meta-regression, the weighted difference in BMI between groups proved to be the only variable significantly associated with the WMD of CRP. These results strengthen the importance of controlling for BMI in analyses of the association between CRP and preeclampsia.
In addition to the potential confounding effect of BMI on the association between CRP and the risk of preeclampsia, several other factors must be taken into account when interpreting the studies’ results. First, CRP cannot be evaluated as a screening marker for preeclampsia risk by using a single assessment. It has been suggested that CRP concentration is stable over long-term follow-up in healthy adults , but the variation of this biomarker throughout normal pregnancy is unclear, and less is known in complicated pregnancies. A longitudinal investigation of CRP concentrations is key; however, only four studies [12,22,25,32] measured CRP more than once. Some studies have already demonstrated that plasma assays tends to give lower concentrations of CRP, compared with serum measurements, perhaps because of the osmotic effect of EDTA anticoagulant [52,53]. Although there have been discussions on the use of different fluids as a source of variability in CRP measurements , our meta-analysis results showed that serum assays were better predictors of preeclampsia compared with plasma assays. In many studies, low sensitivity methods have been used for CRP detection, and the definition of cases was not based on established parameters. The absence of proper adjustments in these statistical analyses further compromised the quality of the studies.
We observed a large difference between WMD estimates depending upon the method of estimation of the mean and SD at subgroup analysis. However, this difference did not change the direction of the results and, indeed, decreased WMD. This may indicate that the method of estimation is not biasing the results towards a significantly positive effect. To confirm the lack of association observed on the univariate analysis, multivariable meta-regression was performed and made evident that the method of mean and SD estimation was not associated with the WMD of CRP between preeclamptic and normotensive groups.
Possible explanation for discrepant estimates of Tjoa and colleagues  comprised the participation of only six patients on the preeclampsia group and lack of adjustments for weight status in the analysis . In regards to Ruma et al. the difference may be explained by the sample source, an investigation derived from the ’Conditions and Pregnancy Oral Study’, which may have attracted more women with periodontal disease and thus higher inflammatory level. The authors have shown a higher proportion of participants with periodontal disease in the preeclampsia group, compared with the control group (90 vs. 72%, P = 0.025).
We have addressed the publication bias issue but opted not to show results of funnel plot, Egger test or trim and fill analysis. This choice was based on the fact that all these strategies are grounded in data symmetry. Notwithstanding, data may appear asymmetric due to factors other than publication bias, especially heterogeneity [54,55]. In meta-analysis with high heterogeneity, as the present one, it may be hard or even impossible to control for publication bias using any of the current available statistical methods , and present these results could lead to erroneous conclusions.
The strength of our study is the search through three databases by two authors independently, increasing the chance to have identified all publications related to this topic. We did not apply any date, language or country restrictions, which makes our results more generalizable. Unfortunately, as we worked with observational studies rather than clinical trials, unpublished reports could not be identified. Some additional limitations should also be mentioned. The meta-analysis could not be performed with all studies included in the SLR because of the lack of information about the mean and SD in each group. These studies, if added to the meta-analysis, might have changed the findings, especially the study by De Jonge et al., which had a large sample size. Although we were able to verify an effect of BMI in the relationship between CRP and preeclampsia, more accurate results could be found if the meta-analysis would have compared mean CRP levels between preeclampsia and normotensive controls in two different groups: BMI less than 25.0 kg/m2 and BMI at least 25.0 kg/m2. Unfortunately, this additional analysis could not be performed, as only two primary studies stratified the results according to BMI [8,19].
Probably, a focus on pooling sensitivity, specificity or odds ratios (OR) based on CRP cutoffs could be more informative. However, we choose to work with mean difference in CRP levels, as the sensitivity and specificity could be calculated only in five studies [23–25,30,38] and only 11 used OR [9,12,17,19,21,23–25,30,34,38], but with different cutoff points, which makes it difficult to compare the data.
It is important to note that CRP has an asymmetrical distribution  and that means can be skewed toward extreme values, especially if samples are small. However, the use of the mean instead of the median when meta-analyzing variables with asymmetrical distributions is a common practice [58–60], as the integration of data becomes less complex and analyses using the median remain tentative and exploratory. We could not adopt any strategy to normalize CRP data distribution, as we did not have access to the original data.
In summary, the results from the current SLR and meta-analysis have shown that the evaluation of serum CRP in early pregnancy may predict preeclampsia. The pooled WMD suggest that women with higher levels of CRP may have an increased risk of developing preeclampsia. This association seems to be modified by confounders, such as BMI. More than summarizing the putative association of CRP and preeclampsia, this study was able to assess the reasons underlying the variability across studies and identify some parameters that should be taken into account by future studies. Thus, we suggest that blood should be drawn prospectively as the first trimester, serum specimens should be assessed using high sensitivity assays (limit detection <0.15 mg/dl), case definition should be performed according to well established parameters, and analyses should be adjusted and stratified for variables reflecting weight status, specifically BMI.
We would like to thank the authors who have provided data for meta-analysis. We also thank Professor Evandro da Silva Freire Coutinho, from Oswaldo Cruz Foundation, for statistical consulting.
Conflicts of interest
The study was funded by the National Council for Scientific and Technological Development (CNPq) (announcement number: 067/2009). G.K. and F.I.B. are research fellows from CNPq. M.M.S is research fellow from Carlos Chagas Filho Foundation for Research Support of Rio de Janeiro State (FAPERJ). F.R. has received scholarship from FAPERJ, and M.M.S., J.S.V., A.B.F-S., and T.J.P.P. have received scholarships from the CNPq for the development of the study.
Reviewer's Summary Evaluation Reviewer 1
Strengths: The authors performed a thorough systematic review of available literature in keeping with the Preferred Reporting Items for Systematic reviews and Meta-Analyses Group guidelines (PRISMA) and the Meta-Analysis of Observational Studies in Epidemiology: A Proposal for Reporting (MOOSE).
Weaknesses: Some studies did not report the means and standard deviations of CRP in the published reports and the authors resorted to imputation methods in seven out of 18 studies (39% of total). Even though a specific sensitivity analysis was conducted, missing imputation is deemed acceptable only for a small proportion of studies. This may represent a limitation of the present study.
1. ACOG Committee on Obstetric Practice. ACOG Practice Bulletin. Diagnosis and management of preeclampsia and eclampsia. Number 33. Int J Gynaecol Obstet 2002; 77:67–75.
2. Khan KS, Wojdyla D, Say L, Gülmezoglu AM, Van Look PF. WHO analysis of causes of maternal death: a systematic review. Lancet 2006; 367:1066–1074.
3. Duley L. The global impact of preeclampsia and eclampsia. Semin Perinatol 2009; 33:130–137.
4. Clark SL, Belfort MA, Dildy GA, Herbst MA, Meyers JA, Hankins GD. Maternal death in the 21st century: causes, prevention, and relationship to cesarean delivery. Am J Obstet Gynecol 2008; 199:36.
5. Sibai B, Dekker G, Schoemker J. Preeclampsia. Lancet 2005; 365:785–799.
6. Redman CW, Sargent IL. Latest advances in understanding preeclampsia. Science 2005; 308:1592–1594.
7. Wang Y, Gu Y, Zhang Y, Lewis DF. Evidence of endothelial dysfunction in preeclampsia: decreased endothelial nitric oxide synthase expression is associated with increased cell permeability in endothelial cells from preeclampsia. Am J Obstet Gynecol 2004; 190:817–824.
8. Scholl TO, Chen X, Goldberg GS, Khusial PR, Stein TP. Maternal diet, C-reactive protein, and the outcome of pregnancy. J Am Coll Nutr 2011; 30:233–240.
9. de Jonge LL, Steegers EA, Ernst GD, Lindemans J, Russcher H, Hofman A, Jaddoe VW. C-reactive protein levels, blood pressure and the risks of gestational hypertensive complications: the Generation R Study. J Hypertens 2011; 29:2413–2421.
10. Black S, Kushner I, Samols D. C-reactive protein. J Biol Chem 2004; 279:48487–48490.
11. Lobo SM, Lobo FR, Bota DP, Lopes-Ferreira F, Soliman HM, Mélot C, et al. C-reactive protein levels correlate with mortality and organ failure in critically ill patients. Chest 2003; 123:2043–2049.
12. Teran E, Escudero C, Calle A. C-reactive protein during normal pregnancy and preeclampsia. Int J Gynaecol Obstet 2005; 89:299–300.
13. Paternoster DM, Fantinato S, Stella A, Nanhornquè KN, Milani M, Plebani M, et al. C-reactive protein in hypertensive disorders in pregnancy. Clin Appl Thromb Hemost 2006; 12:330–337.
14. Derzsy Z, Prohászka Z, Rigó J Jr, Füst G, Molvarec A. Activation of the complement system in normal pregnancy and preeclampsia. Mol Immunol 2010; 47:1500–1506.
15. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg 2010; 8:336–341.
16. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000; 283:2008–2012.
17. Beigi A, Saeedi L, Samiei H, Zarrinkoub F, Zarrinkoub H. Elevated CRP levels during first trimester of pregnancy and subsequent preeclampsia: a prospective study. TUMJ 2008; 66:25–28.
18. Hozo SP, Djulbegovic B, Hozo I. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol 2005; 20:13.
19. Bodnar LM, Ness RB, Harger GF, Roberts JM. Inflammation and triglycerides partially mediate the effect of prepregnancy body mass index on the risk of preeclampsia. Am J Epidemiol 2005; 162:1198–1206.
20. Trowman R, Dumville JC, Torgerson DJ, Cranny G. The impact of trial baseline imbalances should be considered in systematic reviews: a methodological case study. J Clin Epidemiol 2007; 60:1229–1233.
21. Wolf M, Kettyle E, Sandler L, Ecker JL, Roberts J, Thadhani R. Obesity and preeclampsia: the potential role of inflammation. Obstet Gynecol 2001; 98:757–762.
22. Levine RJ, Qian C, Leshane ES, Yu KF, England LJ, Schisterman EF, et al. Two-stage elevation of cell-free fetal DNA in maternal sera before onset of preeclampsia. Am J Obstet Gynecol 2004; 190:707–713.
23. Qiu C, Luthy DA, Zhang C, Walsh SW, Leisenring WM, Williams MA. A prospective study of maternal serum C-reactive protein concentrations and risk of preeclampsia. Am J Hypertens 2004; 17:154–160.
24. Ruma M, Boggess K, Moss K, Jared H, Murtha A, Beck J, Offenbacher S. Maternal periodontal disease, systemic inflammation, and risk for preeclampsia. Am J Obstet Gynecol 2008; 198:389.e1–389.e5.
25. Gammill HS, Powers RW, Clifton RG, Van Dorsten JP, Klebanoff MA, Lindheimer MD, et al. Does C-reactive protein predict recurrent preeclampsia? Hypertens Pregnancy 2010; 29:399–409.
26. Savvidou MD, Lees CC, Parra M, Hingorani AD, Nicolaides KH. Levels of C-reactive protein in pregnant women who subsequently develop preeclampsia. BJOG 2002; 109:297–301.
27. Cetin I, Cozzi V, Papageorghiou AT, Maina V, Montanelli A, Garlanda C, et al. First trimester PTX3 levels in women who subsequently develop preeclampsia and fetal growth restriction. Acta Obstet Gynecol Scand 2009; 88:846–849.
28. Thilaganathan B, Wormald B, Zanardini C, Sheldon J, Ralph E, Papageorghiou AT. Early-pregnancy multiple serum markers and second-trimester uterine artery Doppler in predicting preeclampsia. Obstet Gynecol 2010; 115:1233–1238.
29. Tjoa ML, van Vugt JM, Go AT, Blankenstein MA, Oudejans CB, van Wijk IJ. Elevated C-reactive protein levels during first trimester of pregnancy are indicative of preeclampsia and intrauterine growth restriction. J Reprod Immunol 2003; 59:29–37.
30. Karinen L, Leinonen M, Bloigu A, Paldanius M, Koskela P, Saikku P, et al. Maternal serum Chlamydia pneumoniae antibodies and CRP levels in women with preeclampsia and gestational hypertension. Hypertens Pregnancy 2008; 27:143–158.
31. Rasanen J, Girsen A, Lu X, Lapidus JA, Standley M, Reddy A, et al. Comprehensive maternal serum proteomic profiles of preclinical and clinical preeclampsia. J Proteome Res 2010; 9:4274–4281.
32. Freeman DJ, McManus F, Brown EA, Cherry L, Norrie J, Ramsay JE, et al. Short- and long-term changes in plasma inflammatory markers associated with preeclampsia. Hypertension 2004; 44:708–714.
33. Djurovic S, Clausen T, Wergeland R, Brosstad F, Berg K, Henriksen T. Absence of enhanced systemic inflammatory response at 18 weeks of gestation in women with subsequent preeclampsia. BJOG 2002; 109:759–764.
34. Zwahlen M, Gerber S, Bersinger NA. First trimester markers for preeclampsia: placental vs. nonplacental protein serum levels. Gynecol Obstet Invest 2007; 63:15–21.
35. Kronborg CS, Knudsen UB, Moestrup SK, Allen J, Vittinghus E, Møller HJ. Serum markers of macrophage activation in preeclampsia: no predictive value of soluble CD163 and neopterin. Acta Obstet Gynecol Scand 2007; 86:1041–1046.
36. Barden A, Singh R, Walters BN, Ritchie J, Roberman B, Beilin LJ. Factors predisposing to preeclampsia in women with gestational diabetes. J Hypertens 2004; 22:2371–2378.
37. García RG, Celedón J, Sierra-Laguado J, Alarcón MA, Luengas C, Silva F, et al. Raised C-reactive protein and impaired flow-mediated vasodilation precede the development of preeclampsia. Am J Hypertens 2007; 20:98–103.
38. Banaem LM, Moghadam NA, Mohamadi B, Gandevani SB, Asghari M. Association of high-sensitivity C-reactive protein serum levels in early pregnancy with the severity of preeclampsia and fetal birth weight. J Perinat Med (in press).
39. Lin CY, Chen PC, Kuo HK, Lin LY, Lin JW, Hwang JJ. Effects of obesity, physical activity, and cardiorespiratory fitness on blood pressure, inflammation, and insulin resistance in the National Health and Nutrition Survey 1999–2002. Nutr Metab Cardiovasc Dis 2010; 20:713–719.
40. Kao TW, Lu IS, Liao KC, Lai HY, Loh CH, Kuo HK. Associations between body mass index and serum levels of C-reactive protein. S Afr Med J 2009; 99:326–330.
41. Mazloom Z, Hejazi N, Dabbaghmanesh MH. Effects of obesity on inflammation and lipid profile of obese women. Saudi Med J 2009; 30:1357–1358.
42. Ramsay JE, Ferrell WR, Crawford L, Wallace AM, Greer IA, Sattar N. Maternal obesity is associated with dysregulation of metabolic, vascular, and inflammatory pathways. J Clin Endocrinol Metab 2002; 87:4231–4237.
43. Chan DC, Barrett HP, Watts GF. Dyslipidemia in visceral obesity: mechanisms, implications, and therapy. Am J Cardiovasc Drugs 2004; 4:227–246.
44. Visser M, Bouter LM, McQuillan GM, Wener MH, Harris TB. Elevated C-reactive protein levels in overweight and obese adults. JAMA 1999; 282:2131–2135.
45. Redman CW, Sacks GP, Sargent IL. Preeclampsia: an excessive maternal inflammatory response to pregnancy. Am J Obstet Gynecol 1999; 180:499–506.
46. Hubel CA. Dyslipidemia, iron, and oxidative stress in preeclampsia: assessment of maternal and feto-placental interactions. Semin Reprod Endocrinol 1998; 16:75–92.
47. Mohamed-Ali V, Pinkney JH, Coppack SW. Adipose tissue as an endocrine and paracrine organ. Int J Obes Relat Metab Disord 1998; 22:1145–1158.
48. Lin CC, Kardia SL, Li CI, Liu CS, Lai MM, Lin WY, et al. The relationship of high sensitivity C-reactive protein to percentage body fat mass, body mass index, waist-to-hip ratio, and waist circumference in a Taiwanese population. BMC Public Health 2010; 28:579.
49. Kao TW, Lu IS, Liao KC, Lai HY, Loh CH, Kuo HK. Associations between body mass index and serum levels of C-reactive protein. S Afr Med J 2009; 99:326–330.
50. Khaodhiar L, Ling PR, Blackburn GL, Bistrian BR. Serum levels of interleukin-6 and C-reactive protein correlate with body mass index across the broad range of obesity. JPEN J Parenter Enteral Nutr 2004; 28:410–415.
51. Ockene IS, Matthews CE, Rifai N, Ridker PM, Reed G, Stanek E. Variability and classification accuracy of serial high-sensitivity C-reactive protein measurements in healthy adults. Clin Chem 2001; 47:444–450.
52. Ledue TB, Rifai N. Preanalytic and analytic sources of variations in C-reactive protein measurement: Implications for cardiovascular disease risk assessment. Clin Chem 2003; 49:1258–1271.
53. Roberts WL, Schwarz EL, Ayanian S, Rifai N. Performance characteristics of a point of care C-reactive protein assay. Clin Chim Acta 2001; 314:255–259.
54. Duval S, Weinhandl E. Correcting for Publication Bias in the Presence of Covariates. Methods Research Report (Prepared by the Minnesota Evidence-based Practice Center under Contract No. 290-02-0009). AHRQ Publication No. 11-EHC041-EF. Rockville, MD: Agency for Healthcare Research and Quality. 2011. www.effectivehealthcare.ahrq.gov/reports/final.cfm
. [Accessed on 7 August 2012].
55. Steichen TJ. Update of tests for publication bias in meta-analysis. Stata Technical Bulletin Reprints. 2001; 10; STB-57, sbe19.2 p4.
56. Song F, Parekh S, Hooper L, Loke YK, Ryder J, Sutton AJ, et al. Dissemination and publication of research findings: an updated review of related biases. Health Technol Assess 2010; 14:iii, ix–xi, 1–193.
57. Woloshin S, Schwartz LM. Distribution of C-reactive protein values in the United States. N Engl J Med 2005; 352:1611–1613.
58. Liu T, Li L, Korantzopoulos P, Goudevenos JA, Li G. Meta-analysis of association between C-reactive protein and immediate success of electrical cardioversion in persistent atrial fibrillation. Am J Cardiol 2008; 101:1749–1752.
59. Kelly CJ, Stenton SR, Lashen H. Insulin-like growth factor binding protein-1 in PCOS: a systematic review and meta-analysis. Hum Reprod Update 2011; 17:4–16.
60. Genser B, Silbernagel G, De Backer G, Bruckert E, Carmena R, Chapman MJ, et al. Plant sterols and cardiovascular disease: a systematic review and meta-analysis. Eur Heart J 2012; 33:444–451.
This article has been cited 1 time(s).
Plos OneTwo Variants of the C-Reactive Protein Gene Are Associated with Risk of Pre-Eclampsia in an American Indian PopulationPlos One
body mass index; C-reactive protein; meta-analysis; preeclampsia; pregnancy; prenatal healthcare; systematic literature review
Supplemental Digital Content
© 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins
Highlight selected keywords in the article text.