Objective
We hypothesized that women who are obese before they become pregnant and also have elevations of complement Bb and C3a in the top quartile in early pregnancy would have the highest risk of preeclampsia compared with a referent group of women who were not obese and had levels of complement less than the top quartile.
Study Design
This was a prospective study of 1013 women recruited at less than 20 weeks’ gestation. An EDTA-plasma sample was obtained, and complement fragments were measured using enzyme-linked immunosorbent assays. The data were analyzed using univariable and multivariable logistic regression analysis.
Results
Women who were obese with levels of Bb or C3a in the top quartile were 10.0 (95% confidence interval, 3.3–30) and 8.8 (95% confidence interval, 3–24) times, respectively, more likely to develop preeclampsia compared with the referent group.
Conclusion
We demonstrate a combined impact of obesity and elevated complement on the development of preeclampsia.
Pregnancy is associated with a physiological state of inflammation and insulin resistance, which is further amplified if the woman is overweight or obese before conception. Obesity-driven dysregulation of inflammatory and metabolic pathways contributes to adverse sequelae for the mother, specifically hypertensive diseases of pregnancy and gestational diabetes. In addition, obesity is a significant risk factor for complications in the neonate including macrosomia and congenital defects. Obesity has now become one of the most important public health issues for the perinatal health of women, with 23% of women of child-bearing age in the United States now estimated to be obese.
Inflammatory mediators, derived from adipocytes and adipose-resident macrophages, contribute to obesity-related systemic inflammation. Adipokines and inflammatory cytokines as mediators of inflammation have been in the spotlight of research in recent years. Inflammatory factors associated with the complement system are also found in adipose tissue, with adipose tissue and its microenvironment a source of the complement components C3, factor B, and factor D (adipsin). However, there is a paucity of information on the impact of complement-mediated inflammation in obesity specifically in pregnancy.
The complement system (described elsewhere and in Figure 1 ) is a complex series of more than 30 proteins (soluble and membrane bound) that has a pivotal role in innate immunity. Specifically, it has 3 main functions: (1) it defends the host against pyogenic infections, (2) bridges innate and adaptive immunity, and (3) disposes of immune complexes, apoptotic bodies and the products of injury from inflammation, ischemia, trauma, and infection. In many diseases these protective functions are inappropriately turned against self-tissues. The complement has 3 initiating mechanisms known as the classical, lectin, and alternative pathways. The biologic functions of the complement system are mediated through the production of activation fragments.
Recently, our group has made 2 independent discoveries relevant to the role of complement activation in early pregnancy and to pregnancy-related obesity and vascular disease. First, complement activation fragments (Bb and C3a) are elevated in pregnant women with obesity compared with nonobese pregnant subjects. Second, elevated levels of complement activation fragments in early pregnancy are significantly associated with the subsequent development of preeclampsia, a complex multisystem pregnancy-related vascular disease that contributes significantly to maternal and neonatal mortality and morbidity. The role of the complement system in hypertensive disease of pregnancy has also been supported by other authors, and indeed, links between the complement system have also been described in association with other complications of pregnancy.
Building on these results, we were interested to estimate the risk of preeclampsia based on maternal preconception obesity in combination with levels of complement activation fragments in early pregnancy. We hypothesized that women who are obese before they become pregnant and also have elevations of complement markers in early pregnancy will have the highest risk of preeclampsia later in pregnancy compared with women, who have the following: (1) obesity alone and lower levels of complement markers, (2) elevated levels of complement markers with no obesity, and (3) neither elevation of complement markers nor obesity.
Materials and Methods
This was a planned secondary analysis of data collected as part of the Denver Complement Study. This prospective cohort study (June 2005 to June 2008) was approved by the Colorado Multiple Institutional Review Board. Details of the study have been described in previous publications. In brief, women were recruited from the University of Colorado Hospital prenatal clinics and 2 affiliated sites. Women were referred to the study by the prenatal intake nurse if they were in the first half of pregnancy. Informed consent was obtained, and additional EDTA-plasma (for complement activation fragments) was obtained with the routine prenatal labs. Data were gathered on the maternal medical and obstetrical history. The women were followed up throughout pregnancy. After delivery, outcome data were collected and the gestational age at blood draw (recruitment visit) was assigned based on the best overall obstetrical estimate incorporating assessment at the first visit and in the great majority on early ultrasound examination.
From the analytic dataset of singleton gestations (n = 1224), we excluded women with a loss to follow-up (n = 49) and chronic medical disease (cardiac disease, chronic hypertension, type 1 diabetes, and autoimmune disease, n = 114). Women with a missing plasma sample (because of a deviation from the study protocol at the initial blood draw, n = 48) were also removed from the analysis. Following theses exclusions, 1013 women remained in the analytic dataset.
The main outcome of the study was preeclampsia, classically defined as gestational hypertension and proteinuria. The definition of gestational hypertension was a systolic blood pressure greater than 140 mm Hg or a diastolic blood pressure greater than 90 mm Hg on 2 or more occasions at least 6 hours apart after 20 weeks’ gestation in a woman known to have been normotensive before pregnancy and before 20 weeks’ gestation. Preeclampsia was defined as one of the following: (1) gestational hypertension with proteinuria (300 mg or greater per 24 hour period) or at least 1or greater on dipstick or (2) in the absence of proteinuria, gestational hypertension with cerebral symptoms, epigastric or right upper quadrant pain with nausea, or vomiting or thrombocytopenia and abnormal liver function test. Hypertensive disease of pregnancy was defined as the development of either preeclampsia or gestational hypertension in pregnancy.
The complement activation fragments Bb and C3a and the maternal prepregnant body mass index (BMI) were the primary risk factors examined. At the first prenatal visit (less than 20 weeks’ gestation, we measured the woman’s height and determined her prepregnant weight (self-reported by the woman). The maternal BMI (kilograms per square meter) was calculated from the maternal prepregnant weight, and height and was categorized as follows: underweight (BMI <18.5 kg/m 2 ), normal weight (BMI 18.5-24.9 kg/m 2 ), overweight (BMI 25-29.9 kg/m 2 ), and obese (BMI >30 kg/m 2 ). Additional maternal risk factors included in the analysis were age, race/ethnicity (non-Hispanic white, Hispanic white, African American, Asian, and other), parity (nulliparous vs multiparous), and cigarette smoking at conception (yes vs no).
Complement assays
Each EDTA tube for complement was promptly centrifuged, and the plasma was separated from the cells, aliquoted, and placed in a freezer at –80°C. For testing, the specimens were thawed 1 time and kept on ice during the assay set-up procedures. The complement activation fragment Bb was measured using a quantitative sandwich enzyme-linked immunosorbent assay (Quidel, San Diego, CA). C3a fragments were measured by the BD Pharmingen OptEIA enzyme-linked immunosorbent assay (BD Pharmingen, San Diego, CA). Although we refer to C3a throughout the manuscript, the actual fragment that was measured was C3a desArg because active C3a lasts only a short amount of time in the circulation. The inter- and intraassay coefficients of variation for Bb were 6% and 4.7%, respectively, and for C3a they were 12.1% and 11.2%. The individuals performing all study assays were blinded to the participant’s pregnancy outcome.
Statistical analysis
The data were analyzed in SAS 9.3 (SAS Institute, Cary, NC). Associations between dichotomous or categorical variables were tested using the χ 2 test or Fisher exact test ( P < .05). Means for continuous variables are reported, but nonparametric methods (Wilcoxon rank sum) were used to test for differences in medians among groups.
For the initial part of the analysis, levels of the complement fragments were categorized into quartiles. A variable of maternal inflammatory/metabolic risk was categorized as follows: (1) maternal prepregnant obesity and a level of the complement marker in the top quartile at less than 20 weeks’ gestation, (2) maternal obesity alone and a level of the complement marker less than the top quartile, (3) complement levels in the top quartile and nonobese, and (4) complement levels less than the top quartile and nonobese. The categories were mutually exclusive.
We chose to dichotomize at the 75th percentile (Bb >0.82 μg/mL and C3a >895 ng/L) because it was the lowest point at which both complement markers appeared to give a clinically useful result with a large enough sample of preeclamptic subjects above the cutoff to make modeling meaningful. The association of these categories with preeclampsia was examined using univariable and multivariable logistic regression analysis. Women with complement levels less than the top quartile who were not obese were the referent group. The odds ratio (OR) was used as a measure of association.
Results
In this cohort, 635 women (63%) were non-Hispanic white, 246 Hispanic (24%), 71 African American (7%), and 61 (6%) were Asian or from other races. We report that 39 (4%) were underweight, 625 (62%) were normal weight, 233 (23%) were overweight, and 116 (11%) were obese. The majority of the women (62%) were younger than 35 years of age. Only a small proportion of women (6.4%) reported cigarette smoking at the time of conception. A high proportion of the women in the cohort had their blood drawn in the first trimester (n = 620 [61%]) with a mean ± SD gestational age (weeks) at first blood draw of 11.6 ± 2.6.
We examined the distribution of categories of the complement quartiles across categories of maternal prepregnant BMI. The underweight and normal-weight categories were merged because of low numbers of women with a prepregnant BMI less than 18.5. We show in Figure 2 differences in the levels of Bb within and across the 3 categories of BMI ( P < .0001 for trend). It is noteworthy that among women who were obese, 14% had levels of Bb in the lower quartile and 44% had levels in the upper quartile.
Within and between the 3 categories of BMI there were also differences in the levels of C3a ( P < .0001 for trend, Figure 3 ). We repeated the analysis among the 928 women who remained normotensive during pregnancy and found a similar significant trend across the categories of BMI ( P < .0001 for trend). In addition, we conducted the analysis with the women who had a BMI less than 18.5 kg/m 2 removed from the analysis and found very similar significant results ( P = .0001 for trend). We also found a significant ( P < .0001) difference in the levels (mean ± SD) of Bb (micrograms per milliliter) and C3a (nanograms per liter) in women with a prepregnant BMI greater than 30 kg/m 2 as compared with women with a BMI less than 25 kg/m 2 (0.8 ± 0.2 vs 0.68 ± 0.2 for Bb and 824 ± 365 vs 728 ± 417 for C3a).
For the next part of the analysis, women who developed gestational hypertension or had delivery less than 20 weeks’ gestation were removed from the cohort. Thirty-four of the 932 women (3.7%) developed preeclampsia. The incidence of preeclampsia among the 4 categories of BMI was 0% for a BMI less than 18.5 kg/m 2 , 2.9% for a BMI between 18.5 and 25 kg/m 2 , 1.9% for a BMI of 25-30 kg/m 2 , and 12% for a BMI over 30 kg/m 2 ( P < .0003 for trend). We demonstrate in Figure 4 that the incidence of preeclampsia rose in a significant dose-dependent manner across the categories of the Bb/obesity variable ( P < .0001 for trend). We show in the multivariable logistic regression model ( Table ) that adjusted for maternal race, parity, age, and cigarette smoking at conception, obesity, and a Bb level in the top quartile and obesity alone were significant risk factors for preeclampsia.
| Category, entire cohort (n = 932) | Unadjusted, OR | Adjusted b | ||
|---|---|---|---|---|
| OR | 95% CI | P value | ||
| Complement metabolic/inflammatory categories c | ||||
| Bb top quartile and obesity | 8.3 | 10 | 3.3–30 | < .0001 |
| Obesity alone and Bb less than top quartile | 5.0 | 5.3 | 1.9–15 | .002 |
| Bb top quartile and no obesity | 1.8 | 1.8 | 0.7–4.6 | .200 |
| Bb less than top quartile and no obesity | 1.0 | 1.0 | ||
| C3a top quartile and obesity | 7.7 | 8.8 | 3–24 | < .0001 |
| Obesity alone and C3a less than top quartile | 3.7 | 3.7 | 1.3–10 | .01 |
| C3a top quartile and no obesity | 0.8 | 0.8 | 0.3–2.5 | .80 |
| C3a less than top quartile and no obesity | 1.0 | 1.0 | — | — |
| Nulliparous women (n = 399) | ||||
| Bb top quartile and obesity | 8.3 | 8.3 | 1.4–49 | .02 |
| Obesity alone and Bb less than top quartile | 6.8 | 5.2 | 1.4–19 | .01 |
| Bb top quartile and no obesity | 1.8 | 1.3 | 0.4–4.6 | .70 |
| Bb less than top quartile and no obesity | 1.0 | 1.0 | ||
| C3a top quartile and obesity | 9.7 | 8.3 | 1.9–36 | .005 |
| Obesity alone and C3a less than top quartile | 4.8 | 4.1 | 0.99–17 | .051 |
| C3a top quartile and no obesity | 1.1 | 0.9 | 0.2–3.4 | .90 |
| C3a less than top quartile and no obesity | 1.0 | 1.0 | — | — |
| Multiparous women (n = 533) d | ||||
| Bb top quartile and obesity | 13.8 | 7.7 | 1.7–36 | .009 |
| Obesity alone and Bb less than top quartile | 4.6 | 3.3 | 0.5–20 | .2 |
| Bb top quartile and no obesity | 2.3 | 2.2 | 0.5–10 | .3 |
| Bb less than top quartile and no obesity | 1.0 | 1.0 | ||
| C3a top quartile and obesity | 9.0 | 6.8 | 1.6–29 | .0097 |
| Obesity alone and C3a less than top quartile | 3.9 | 1.7 | 0.3–8.8 | .5 |
| C3a top quartile and no obesity | 0.5 | 0.4 | 0.05–3.6 | .4 |
| C3a less than top quartile and no obesity | 1.0 | 1.0 | — | — |
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