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. Author manuscript; available in PMC: 2019 Sep 17.
Published in final edited form as: Am J Perinatol. 2017 Nov 13;35(5):455–462. doi: 10.1055/s-0037-1608677

Patterns of systemic and cervicovaginal fluid (CVF) inflammatory cytokines throughout pregnancy

Kristin B Ashford 1,1, Niraj Chavan 2,2, Jeffrey L Ebersole 3,3, Amanda T Wiggins 4,1, Savita Sharma 5,1, Andrea McCubbin 6,1, Janine Barnett 7,1, John O’Brien 8,2
PMCID: PMC6748037  NIHMSID: NIHMS1025409  PMID: 29132178

Abstract

OBJECTIVE

This study describes the normal variations in serum and cervicovaginal (CVF) cytokine levels throughout pregnancy.

STUDY DESIGN

This multicenter, prospective study examined trimester-specific maternal serum and CVF cytokines (IL-1α, IL-1β, IL-6, IL-8, IL-10, TNFα and CRP). A two-factor linear mixed modelling approach compared cytokine distribution, while pair-wise comparisons evaluated differences over time.

RESULTS

Trimester-specific serum cytokine data were available for 288, 243 and 221 patients; whereas CVF cytokine data was available for 273, 229 and 198 patients. CVF had significantly higher concentrations of IL-1α, IL-1β, IL-6, IL-8 and MMP-8 (P < 0.001), irrespective of the trimester. At all time-points, IL-10 and CRP concentrations were higher in serum than CVF (P < 0.001). Serum IL-10 increased significantly throughout pregnancy (P < 0.001).

CONCLUSION

Differences in cytokine distribution across different biological fluids are evident throughout pregnancy. These findings provide a framework for examining patterns of changes in cytokines throughout pregnancy.

Keywords: cytokines, inflammatory markers, pregnancy, serum, cervicovaginal fluid

INTRODUCTION

Pregnancy is an unique immunological state with an ever changing balance in immune responses.1 This process of changing immune responses lasts throughout gestation and requires an appropriate balance between pro-inflammatory and anti-inflammatory responses.2 Early in gestation, the implanting blastocyst incites a predominantly pro-inflammatory state followed by an anti-inflammatory state, which allows for fetal growth and development. Near term, a renewed pro-inflammatory process may promote maternal adaption in preparation for the process of delivery.3–6 Therefore, the gestational process is characterized by selective pro-inflammatory and anti-inflammatory conditions, depending upon the stage of gestation.7,8

Modest elevations in both serum pro- and anti-inflammatory cytokine levels have been observed in normal pregnancies as compared to the non-pregnancy condition.9–14 Cytokines reflecting Th1 cell responses mediate inflammation and have been associated with fetal rejection. The production of cytokines by Th2 cells influences an anti-inflammatory milieu and a Th1/Th2 ratio is associated with a successful pregnancy.15–18 Dysregulation in this immune network has been associated with pregnancy complications19,20, with increased serum pro-inflammatory cytokines and decreased anti-inflammatory cytokine levels raising the risk for preterm labor and preeclampsia.13–21 Elevated maternal IL-6 in cervicovaginal fluid and serum, and CRP levels in serum have been identified as risk factors for preterm birth (PTB) <32 weeks.22–25 Additionally, infants identified as small for gestational age (SGA) have been associated with low pro-inflammatory and anti-inflammatory maternal serum cytokines.26 Research by Heng et al. (2014) explored biomarkers in CVF as potential predictors for term and preterm labor, and concluded the medium to be an excellent source to study cytokine changes throughout pregnancy, noting the importance of multiple biomarker modelling to achieve predictive efficacy.27,28 In addition to cytokines, there is evidence of increased expression of chemokines, as well as increased activity of select matrix metalloproteinases (MMP 8, 9) in spontaneous preterm birth and rupture of membranes.29 Further, cytokine-induced MMP expression can be inhibited due to the effect of progesterone on the decidua; thus contributing to a potential dysregulation in the host response.30 Given the complexity of the immune responses and the importance in normal and adverse pregnancy outcomes, describing the status of cytokines throughout pregnancy in both CVF and serum is a necessary precursor for elucidating which biomarker(s) may serve best to predict adverse events.

MATERIALS AND METHODS

Human Samples

This study reports the analysis of a multicenter, prospective, longitudinal study of women with a singleton gestation. Patients were screened at the University of Kentucky and University of Virginia prenatal clinics to exclude any pre-existing diabetes, heart disease, a medical history of HIV, bacterial vaginosis, sexually transmitted infections, chronic conditions with implications for immune function, any autoimmune disease or illicit drug use. The Institutional Review Boards at the affiliated sites approved the study protocol. Informed written consent for the study was obtained, and all of the women volunteers received modest compensation for participation. Maternal serum (288, 243 and 221 patients) and CVF (273, 229 and 198 patients) were collected during each trimester to measure the following cytokine levels: IL-1α, IL-1β, IL-6, IL-8, IL-10, TNFα and CRP. For MMP-8 cytokine data, serum was collected from 205, 170 and 152, and CVF from 185, 156 and 128 patients during the three trimesters, respectively. Participant age, number of prior pregnancies (parity), race, education and income were collected by self-report. Body mass index (BMI) was calculated from the patient’s height and weight recordings.

Sample collection and cytokine estimation

Clotted blood samples were centrifuged at 2000 rpm for 10 minutes, and the serum was divided into three aliquots and stored at −80°C. Samples were analyzed undiluted. For CVF specimens, samples were obtained after the speculum was placed and the cervix visualized. An ectocervical sample was collected using an Aware Messenger (Calypte)™ swab and by sweeping the cervix 360 degrees and kept in place for 30 seconds to maximize saturation. When removing the swab, a vaginal sample was obtained by sweeping 360 degrees in the vaginal vault/posterior fornix. The swab was then placed in the proprietary container, firmly pressed against the inner cryovial wall to ensure maximum seepage of fluid into the buffer container; and the vial cap secured. All samples were immediately refrigerated, transported to the lab within 6 hours where they were stored at −20°C for a minimum of 24 hours. To further process, samples were thawed 4°C, and then centrifuged at 3750rpm for 15 minutes. For long-term storage, the samples were split into three aliquots and stored at −80°C. Cytokines IL-1α, IL-1β, IL-6, IL-8, IL-10 and TNFα, were measured using multiplex beadlyte assay (MPXHCYTO-60K-06) on a Luminex IS-100 (Austin, Tx) according to the manufacturer’s recommendations. High sensitivity testing was used for samples below minimum detectable concentrations. Singleplex assays were used for CRP (Millipore, Billerica, MA) and MMP-8 (R&D Systems Minneapolis, MN). The dynamic range of the CRP assay was 50–0.016 ng/ml with a minimum detection concentration of 0.0012 ng/ml; and MMP-8 range was 66,700–91.5 pg/ml with a MinDC of 16.6 pg/ml (samples were diluted 1:10 from MMP-8 analysis). All cytokine data were generated using Milliplex Analyst Software.

Statistical analysis

The non-normally distributed raw cytokine levels were log-transformed prior to all analysis. Pearson’s product moment correlation was used to determine associations among cytokines by medium (serum vs. CVF) and trimester, Two-factor linear mixed modeling evaluated differences in cytokine levels between sources and over time. The first factor was cytokine source (serum/cervicovaginal) and the second factor was trimester (first/second/third). Each model contained the main effects for cytokine source and trimester as well as their interaction. If the interaction term was not significant in the model it was removed and the model with only main effects was subsequently fit. In all models, women were included as a random factor to account for repeated measures on individuals over time. All data analysis was conducted using SAS, version 9.4, with an alpha level of 0.05.

RESULTS

Patient demographic and clinical characteristics are summarized in Table 1. The majority were White/non-Hispanic (74%) and had at least a high-school diploma/GED (87%). Median parity among this sample was one (interquartile range= 1–3) and average BMI was 26 ± 6.4 kg/m2. At enrollment, 66 women (20%) had a history of prior preterm birth and 25 women (4.8%) had a history of preeclampsia. The overall rate of preterm birth was 13.9% for the cohort, with nearly 10% experiencing spontaneous PTB.

Table 1.

Demographic and clinical characteristics of patients

Variable Mean (SD), Median (IQR) or n (%)
Age (years) 26 (5.4)
BMI (kg/m2) 26.6 (6.4)
Parity 1 (1–3)
Race
 Caucasian 190 (74.1%)
 African American 41 (16.2%)
 Hispanic 11 (4.3%)
 Other 11 (4.3)
Education
 Less than high school/GED 32 (12.6%)
 At least high school 222 (87.4%)
Income
 Less than $20,000 92 (39.2%)
 $20,000 - $39,999 52 (22.1%)
 $40,000 and over 91 (38.7%)
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Baseline characteristics of women with available serum or cervicovaginal fluid data at least one trimester during pregnancy. Note: Numbers vary due to missing data.

Correlations among cytokines at each trimester

Pearson’s correlations were conducted to determine the patterns of association among cytokines in serum and CVF separately. Most of the serum cytokines, with the exception of interleukins and CRP, and almost all of the CVF cytokines were positively and significantly correlated with each other, for each trimester (see Tables 2 and 3).

Table 2.

Pearson product moment correlations for serum cytokines across pregnancy

Systemic Cytokines First Trimester
N 288 288 288 288 288 288 288 205
IL-1α IL-1β IL-6 IL-8 IL-10 TNFα CRP MMP-8
IL-1α 1 .70** .57** .47** .43** .43** −.02 .25**
IL-1β 1 .57** .45** .47** .50** −.003 .28**
IL-6 1 .59** .51** .49** −.02 .07
IL-8 1 .33** .34** −.02 .19*
IL-10 1 .29** .12* −.03
TNFα 1 −.01 .15*
CRP 1 .18*
MMP-8 1
Second Trimester
N 243 243 243 243 243 243 243 170
IL-1α 1 .63** .58** .46** .45** .38** −.04 .27**
IL-1β 1 .56** .48** .43** .43** −.13* .32**
IL-6 1 .67** .49** .45** −.11 .15*
IL-8 1 .36** .48** −.17* .29**
IL-10 1 .33** .04 .08
TNFα 1 −.08 .18*
CRP 1 −.003
MMP-8 1
Third Trimester
N 221 221 221 221 221 221 221 152
IL-1α 1 .63** .58** .35** .49** .40** −.11 .07
IL-1β 1 .59** .51** .49** .39** −.13 .10
IL-6 1 .62** .53** .46** −.07 .08
IL-8 1 .32** .36** −.12 .26*
IL-10 1 .34** .02 .13
TNFα 1 −.04 .15
CRP 1 −.02
MMP-8 1
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Note:

**

P < 0.001

*

P < 0.05

Table 3.

Pearson product moment correlations for CVF cytokines across pregnancy

CVF Cytokines First Trimester
N 273 273 273 273 273 273 273 185
IL-1α IL-1β IL-6 IL-8 IL-10 TNFα CRP MMP-8
IL-1α 1 .61** .13* .63** .20** .35** .39** .45**
IL-1β 1 .29** .73** .37** .64** .55** .54**
IL-6 1 .24** .42** .41** .18* .20*
IL-8 1 .33** .46** .42** .71**
IL-10 1 .45** .20** .31**
TNFα 1 .46** .28**
CRP 1 .33**
MMP-8 1
Second Trimester
N 229 229 229 229 229 229 229 156
IL-1α 1 .63** .16* .67** .45** .28** .43** .61**
IL-1β 1 .41** .74** .52** .58** .63** .64**
IL-6 1 .46** .51** .54** .36** .34**
IL-8 1 .51** .48** .51** .78**
IL-10 1 .48** .42** .29**
TNFα 1 .46** .29**
CRP 1 .54**
MMP-8 1
Third Trimester
N 198 198 198 198 198 198 198 128
IL-1α 1 .56** .18* .64** .37** .21* .30** .40**
IL-1β 1 .48** .78** .53** .51** .61** .55**
IL-6 1 .45** .42** .52** .38** .31**
IL-8 1 .42** .45** .42** .58**
IL-10 1 .39** .30** .30**
TNFα 1 .48** .27*
CRP 1 .40**
MMP-8 1
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Note:

**

P < 0.001

*

P < 0.05

Overall changes in cytokines levels over time

The cytokine levels, both from serum and CVF, demonstrated significant variations across pregnancy. There were no differences in the rate of change between serum and CVF cytokines across trimesters (i.e., each of the interactions between trimester and source were nonsignificant) for any cytokine except TNFα. Therefore, averaging across trimester, concentrations of CVF IL-1β, IL-6, IL-8, IL-1α and MMP-8 (P < 0.001 for all comparisons; Figures 1–5 respectively) were significantly greater than serum levels, while concentrations of serum IL-10 and CRP (P < 0.001 for all comparisons; Figures 6–7 respectively) were significantly greater than CVF levels.

Figure 1.

Figure 1.

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IL-1β (log-transformed) levels in the cervicovaginal fluid (CVF) were significantly higher than serum levels across trimester of pregnancy (p < .001; linear mixed model F test of fixed effects).

Figure 5.

Figure 5.

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IL-1α (log-transformed) levels in cervicovaginal fluid (CVF) were significantly higher than serum levels across trimester of pregnancy (p < .001; linear mixed model F test of fixed effects).

Figure 6.

Figure 6.

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IL-10 (log-transformed) levels in the serum were significantly higher than levels in the cervicovaginal fluid (CVF; p < .001 from linear mixed model F test of fixed effects), across trimester of pregnancy. Regardless source of cytokine (CVF/serum), levels were significantly lower in the first trimester compared to the second and third trimesters (p < .001 for both comparisons).

Figure 7.

Figure 7.

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CRP (log-transformed) levels in the serum were significantly higher than levels in the cervicovaginal fluid (CVF; p < .001 from linear mixed model F test of fixed effects), across trimester of pregnancy.

Regardless of source (CVF or serum), concentrations significantly varied across trimester for IL-8, MMP-8 and IL-10. There was no change in IL-8 from first to second trimester, but there were significant increases in concentrations from first to third (P = 0.006) and second to third (P = 0.03) trimesters. MMP-8 levels significantly increased from first to third (P = 0.013) trimester; however the changes from first to second and second to third trimesters were not significant. Concentrations for IL-10 increased significantly from first to second (P < 0.001) and first to third trimesters (P < 0.001); the change from second to third trimester was not significant. Concentrations did not significantly vary across trimester for IL-6, IL-1α, IL-1β or CRP.

The interaction between cytokine and trimester was significant for TNFα (P < 0.001; Figure 8). CVF concentrations were significantly lower at each trimester compared to serum (P <0.001 for all three comparisons). In comparing changes in CVF TNFα concentrations over time, there was a significant decrease from first to second (P = 0.048) and first to third (P = 0.002) trimesters, although, levels did not differ between second and third trimester. Among serum TNFα concentrations, there was a significant increase from first to third (P = 0.004) trimester, but the changes from first to second and second to third trimesters were not significant.

Figure 8.

Figure 8.

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TNF-α (log-transformed) levels varied significantly across pregnancy between serum and cervicovaginal fluid (CVF) specimens (p < .001 from F test of fixed effects for the interaction). In the post-hoc analysis, within the CVF, first trimester levels were significantly higher than second and third trimester levels (p =.048 and p = .002, respectively). Within the serum, first trimester levels were significantly lower than third trimester levels (p = .004). At each trimester, concentrations of TNF-α were significantly lower in the CVF compared to serum specimens (p <.001 for all comparisons).

DISCUSSION

Our data confirm pro-inflammatory and anti-inflammatory cytokine concentrations vary in distribution across pregnancy, although, changes in cytokine levels across gestation have not been well delineated previously. In this study, we analyzed cytokine concentrations in serum and CVF. IL-1β, IL-6, IL-8, and MMP-8 concentrations were significantly higher in CVF than serum, while IL-1α, IL-10, and CRP were significantly higher in serum. The differences between serum and CVF concentrations of TNFα varied by trimester. Of note, IL-10, an important anti-inflammatory cytokine for immune modulation increased significantly from early to late pregnancy, which is consistent with a report by Coussons-Read et al.23 In our data, TNFα also significantly increased in serum from the first to the third trimester of pregnancy consistent with previous reports.31,32 Finally, our data are supported by a report by Larsson et al who noted that serum CRP concentrations increase consistently throughout pregnancy.33

Cervicovaginal specimens may provide additional and more selective alterations in the immune response within the reproductive tract. Hence, we also aimed to describe variation in cytokine distribution at this mucosal surface. Interestingly, in contrast to serum, CVF CRP concentration decreased in middle as compared to early and late pregnancy samples. Potentially, the increasing levels of MMP-8 in CVF from early to late pregnancy may reflect its biological function as a collagen-cleaving enzyme in preparation for labor, though does not appear to be involved during the labor process.34 IL-6 has been identified as a main cytokine associated with adverse perinatal health outcomes.35–38 In this study, significantly higher levels of IL-6 in CVF versus serum suggest cervicovaginal specimens may allow better discrimination between normal and pathologic conditions. IL-6 concentrations did not vary significantly across the pregnancy timeline in this study. Similar to Heng et al. (2014), there were no significant changes in CVF IL-1α in second and third trimester samples.28

This research is one of the first projects to compare trimester-specific immune markers in two biological fluids. One strength of this study is the longitudinal design, which assessed women with singleton gestation at each trimester. A weakness is the attrition observed throughout the trimesters and lack of control for exposures such as antibiotics. In addition, varied collection times within the trimesters (limited to a 6-week window per protocol) may have influenced the variation for determination of the interpersonal gestational immunological changes.

Despite these concerns, our findings provide a framework for examining patterns of changes in cytokines over the time course of pregnancy. Further research to measure the range of maternal and fetal immune responsiveness during gestation is warranted, particularly in response to pathophysiologies occurring early in pregnancy.

Figure 2.

Figure 2.

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IL-6 (log-transformed) levels in cervicovaginal fluid (CVF) were significantly higher than serum levels across trimester of pregnancy (p < .001; linear mixed model F test of fixed effects).

Figure 3.

Figure 3.

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IL-8 (log-transformed) levels in the cervicovaginal fluid (CVF) were significantly higher than serum levels across trimester of pregnancy (p < .001; linear mixed model F test of fixed effects). Regardless source of cytokine (CVF/serum), levels were significantly lower in the first trimester (p=.006) and second trimester (p=.03) compared to the third trimester.

Figure 4.

Figure 4.

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MMP-8 (log-transformed) levels in the cervicovaginal fluid (CVF) were significantly higher than levels in the serum (p < .001 from linear mixed model F test of fixed effects) across trimester of pregnancy. Regardless source of cytokine (CVF/serum), levels were significantly higher in the third trimester compared to the first trimester (p = .013 from F test of fixed effects).

ACKNOWLEDGEMENTS

Financial support for the research

Financial support for this research was provided in part by National Institutes for Health Building Interdisciplinary Research Careers in Women’s Health (BIRCWH: K12DA14040) to K.B.A; Center for Biomedical Research Excellence (COBRE: 5P20GM103538) to J.L.E. and University of Kentucky Clinical and Translational Research Center KL2RR033171 to J.E. The project described was supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through grant number UL1TR000117. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Findings were presented at the 36th Annual Meeting of the Society for Maternal Fetal Medicine: The pregnancy Meeting, Atlanta, Georgia, February 1st - 6th, 2016.

We acknowledge the expert support of Wendy F Hansen MD, and Jason Stevens (Research Analyst). Dr. Hansen is a Professor and John W Greene Chair in the Department of Obstetrics and Gynecology of the University of Kentucky College of Medicine. Mr. Stevens is the principal research analyst for the University of Kentucky (UK) Center for Oral Health Research. We are also grateful to the medical and nursing faculty and staff at the UK prenatal clinics, and all of the women who participated in study for making this research possible.

Contributor Information

Kristin B Ashford, College of Nursing, 417 Nursing Building University of Kentucky, 751 Rose Street, Lexington; KY 40536-0200.

Niraj Chavan, Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, University of Kentucky.

Jeffrey L. Ebersole, Center for Oral Health Research, University of Kentucky.

Amanda T. Wiggins, College of Nursing, University of Kentucky.

Savita Sharma, College of Nursing, University of Kentucky.

Ms. Andrea McCubbin, College of Nursing, University of Kentucky.

Ms. Janine Barnett, College of Nursing, University of Kentucky.

John O’Brien, Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, University of Kentucky.

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