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. Author manuscript; available in PMC: 2012 Mar 1.
Published in final edited form as: Am J Obstet Gynecol. 2010 Dec 10;204(3):244.e1–244.12. doi: 10.1016/j.ajog.2010.10.001

Mid-pregnancy levels of angiogenic markers in relation to maternal characteristics

Renée S Mijal 1, Claudia B Holzman 1, Sarosh Rana 2, S Ananth Karumanchi 2, Jianling Wang 1, Alla Sikorskii 3
PMCID: PMC3079927  NIHMSID: NIHMS258224  PMID: 21145529

Abstract

Objective

To describe relations among maternal demographic and lifestyle characteristics and mid-pregnancy levels of angiogenic markers (soluble Fms-like tyrosine kinase-1 (sFlt-1); placental growth factor (PlGF); soluble endoglin (sEng)).

Study Design

In a large pregnancy cohort, linear models were used to evaluate relations among maternal characteristics and mid-pregnancy angiogenic markers with and without covariate adjustment. Associations were examined in a sub-cohort including term and preterm deliveries (N = 1302) and among “normal” term pregnancies (N = 668).

Results

Concentrations of all factors declined with increasing maternal BMI. Multiparous women had lower sFlt-1 levels than primiparas. Higher PlGF and slightly lower sEng were observed among women who smoked at enrollment, but not among those who quit before enrollment. African-American women had higher levels of all markers.

Conclusions

Understanding relations among maternal characteristics and levels of angiogenic factors may improve studies utilizing these markers to examine etiologies and/or to predict adverse pregnancy outcome.

Keywords: preeclampsia, angiogenic factors, soluble endoglin, placental growth factor, soluble Fms-like tyrosine kinase-1

Introduction

Altered patterns of angiogenic markers have been linked to pregnancy conditions responsible for significant maternal and fetal morbidity. These observations may offer etiological insights and translate into use of the markers for disease screening.1–4 For preeclampsia, the condition with the most extensive and strongest evidence, elevated concentrations of soluble Fms-like tyrosine kinase 1 (sFlt-1) and soluble endoglin (sEng) and lower levels of placental growth factor (PlGF) have been detected months prior to disease onset.1,2,5,6 Additionally, several altered patterns of angiogenic markers may contribute to poor fetal growth,1,7 hypertension-related placental abruption,3 spontaneous preterm birth,7,8 proteinuria,9 gestational hypertension,6 and fetal death.7,10

During pregnancy sFlt-1, PlGF and sEng are produced by placental tissue, although decidual cells, leukocytes, and other cells may contribute to overall levels.11–14 Measured in maternal serum, levels of sFlt1 and sEng are fairly steady early in pregnancy and rise more steeply later, whereas PlGF levels rise steadily into the third trimester and decline the last 8–10 weeks of pregnancy.1 Angiogenic factors, either working independently or by modulating binding of VEGF and TGF-β to their receptors, may regulate placental angiogenesis.2,11,15 Additionally, these factors affect the maternal endothelium and, in cases of aberrant expression, lead to the development of symptoms like gestational hypertension and proteinuria.5,6,16,17 While linked to placental problems, it is unclear whether altered expression is cause or consequence of poor placental development and function.2,18,19

Some studies have examined relations among these angiogenic markers and maternal characteristics,5,16,20–25 but many have been small, examined only one or two characteristics or markers, and lacked adjustment for other covariates. In addition, studies have varied in their inclusion/exclusion of complicated pregnancies. A more complete understanding of associations between angiogenic markers and maternal characteristics may provide clues to underlying mechanism, and may improve control of confounding in etiologic studies or those testing the screening/diagnostic potential of these markers.21,26,27

In the Pregnancy Outcomes and Community Health Study (POUCH), we describe associations among maternal demographic, anthropometric, and lifestyle characteristics and each of three angiogenic markers measured in maternal serum at mid-pregnancy. Associations are examined within a group of “normal” term pregnancies in which women did not experience the most prevalent complications associated with altered angiogenic patterns, permitting a clearer interpretation of relations. For comparison we also examined associations among unselected pregnancies representing a spectrum of pregnancy outcomes, which may indicate the degree to which processes underlying poor pregnancy outcomes influence findings.

Materials and Methods

Population

The POUCH Study recruited pregnant women from 52 prenatal clinics in five different Michigan communities between September 1998 and June 2004. Eligible women had maternal serum α-fetoprotein (MSAFP) screening at 15–22 weeks gestation, had singleton pregnancies with no known abnormality or birth defect, were ≥15 years of age, were English-speaking, and had no diagnosis of pre-pregnancy diabetes mellitus. Given the study’s focus on preterm birth and previous reports linking elevated MSAFP to preterm delivery,28,29 all women with unexplained, elevated MSAFP levels (≥ 2.0 multiples of the median (MoM)) were invited to participate, enriching the sample for women with elevated levels (7% vs. 3.5% in general obstetric population). A total of 3,038 women were enrolled between 15 and 27 weeks’ gestation, at which time self-completed questionnaires and in-person interviews were administered and maternal biologic samples were collected. In total, 3019 women (99.5%) were followed through delivery and comprise the POUCH cohort. The POUCH Study protocol was approved by IRBs at Michigan State University, the Michigan Department of Community Health, and all delivery hospitals.

Study Sample

To utilize resources in a way that maximized statistical power for studying preterm delivery and at-risk groups like women with elevated MSAFP and African-Americans, we established a sub-cohort of women (N = 1371) in which more detailed information was obtained. The sub-cohort included all women who delivered preterm, all women with elevated MSAFP, and a sample of term births with normal MSAFP levels and oversampling of African American women. To account for oversampling of preterm deliveries and at-risk groups, analyses were weighted according to the probabilities of selection into the cohort and sub-cohort. (E.g.-the proportion of individuals with high MSAFP in the entire cohort was approximately 7%, twice that of the general population, so this group would be assigned a cohort adjustment weight of ½. Additional weights would be calculated for sampling into the subcohort.) The weighted results should reflect the experience of the population sampled, as previously demonstrated for demographic characteristics and selected pregnancy outcomes.30

Women included in this analysis belonged to the sub-cohort, had measures of angiogenic factors available and were not missing information on important covariates (N = 1302) (See Figure 1). Additionally, we conducted a subset analysis with women who had “normal” pregnancies defined as: 1) term delivery (>37 weeks gestational age); 2) MSAFP < 2.0 MoM; 3) delivery of a child who was not small-for-gestational age (SGA), defined < 10th percentile of weight for gestational age);31 4) no diagnosis of any hypertensive disorder. Hypertensive disorders were ascertained through review of prenatal and labor/delivery records by trained abstractors and included diagnoses of chronic hypertension prior to pregnancy, gestational hypertension (minimal criteria: DBP ≥ 90 or SBP ≥ 140 on two different days after 20 weeks gestation without evidence of proteinuria) or preeclampsia (minimal criteria: gestational hypertension plus proteinuria defined as 2+ protein on urine dipstick once or 1+ protein on two occasions after 20 weeks gestation. If proteinuria was present before 20 weeks, increased levels after 20 weeks were considered indicative of preeclampsia).

Figure 1.

Figure 1

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Flow diagram showing the derivation of the Total Pregnancy Sample and the “Normal” Pregnancy Sample from the entire POUCH cohort

Covariates

Maternal demographic, reproductive, lifestyle, and anthropometric characteristics were obtained via interview or questionnaire administered at enrollment. Race was categorized for these analyses as African American or non-African American. Medicaid enrollment (yes/no) and completed years of education were proxies for socio-economic status. Smoking was grouped into four-levels: did not smoke during pregnancy, smoked in pregnancy but stopped prior to enrollment, smoked < half pack per day at enrollment, and smoked ≥ half pack per day at enrollment. Pre-pregnancy weight and maternal height were obtained from the questionnaire. These two measures were used to calculate pre-pregnancy body mass index (BMI) which was grouped according to CDC guidelines into underweight, normal, overweight and obese.32 Gestational age (GA) at study enrollment, grouped as 15–<20, 20–<25, and 25–<28 weeks, was based on LMP if this estimate was within 2 weeks of the date estimated from a <25 week ultrasound. Otherwise ultrasound dates were utilized.

Measurement of angiogenic markers

Maternal serum samples collected at enrollment were stored at −80 °C. For analysis samples were randomly allocated to batches by study site and length of post-collection storage time. Additionally, all batches contained the same proportion of preterm deliveries since this outcome was a primary focus of the study. Measurements of sFlt-1, PlGF, and sEng were made using commercially available ELISA kits (R&D Biosystems, Minneapolis, MN) by one Karumanchi Laboratory member blinded to patients’ clinical data. All measurements were performed in duplicate. Assays were re-run if measures differed by more than 25%. Limits of detection for each marker were: 7 pg/mL (sFlt-1), 5 ng/mL (PlGF), and 5 pg/mL (sEng). Inter-assay coefficients of variation were 7.6%, 10.9%, and 3.0% for sFlt-1, PlGF and sEng respectively. Intra-assay coefficients were 3.3%, 5.6%, and 6.3% for the same. Duplicate measures were averaged and log-transformed to create approximately normal distributions for use in general linear models.

Analysis

Associations between angiogenic markers and maternal characteristics were examined in two groups of women: all POUCH pregnancies with complete biomarker and covariate measurements (95% of sub-cohort women, N = 1302) and a sample of “normal” pregnancies (term, normal MSAFP, no hypertensive disorders, not SGA, N = 668). Analyses were completed in SAS 9.1.3 or 9.2 and were appropriately weighted using Survey Procedures. Frequency distributions were calculated using Proc SurveyFreq. Linear regression was implemented in Proc SurveyReg to determine the regression coefficient for each angiogenic marker regressed on covariates of interest. Covariates were examined individually and in multivariable models. Unadjusted and adjusted least squares means and 95% confidence intervals are presented for each factor at different levels of maternal demographic, lifestyle and anthropometric variables.

Results

The weighted frequencies showed little difference between the distributions of maternal characteristics using the entire POUCH sub-cohort and women with complete measurements (Table 1). Approximately 24% of women were African American, slightly more than half were 20–29 years of age, 41% were primiparas, > 25% reported smoking at some time during pregnancy, and most enrolled between 20 and 24 weeks’ gestation at a mean 22.4 and 22.5 gestational weeks for the total and “normal” pregnancy samples respectively (Table 1).

Table 1.

Characteristics of the entire sub-cohort, total pregnancy sample and normal pregnancy sample

Entire Sub-cohort
(N = 1371)		 Total Pregnancies
Sample (N= 1302)		 “Normal” Pregnancy
Sample (N= 668)
Characteristics N Weighted % N Weighted % N Weighted %
Maternal Characteristics
  Race
    White 692 65.8 668 65.7 316 66.8
    African American 579 24.6 536 24.6 305 23.3
    Asian 23 2.2 22 2.1 9 1.9
    Hispanic 58 5.1 58 5.3 26 5.5
    Other 19 2.3 18 2.4 12 2.5
  Age
    <20 years 243 14.7 227 14.6 113 13.2
    20–29 years 776 57.2 734 56.8 401 59.0
    ≥30 years 352 28.1 341 28.6 154 27.8
  Parity
    Primaparous 577 41.5 543 41.0 256 38.3
    Multiparous 793 58.5 759 59.0 412 61.7
    Missing 1 0.0 - - - -
  Education (highest level attained)
    <12th grade 317 18.9 296 18.8 154 17.7
    12th grade 388 27.0 367 27.1 184 26.1
    >12th grade 666 54.1 639 54.1 330 56.2
  Medicaid
    No 586 50.9 565 50.8 286 52.6
    Yes 783 49.1 737 49.2 382 47.4
    Missing 2 0.01 - - - -
  Pre-Pregnancy Body Mass Index
    Underweight (< 18.5) 65 3.9 59 3.8 25 3.3
    Normal (18.5–24.9) 609 46.6 581 46.6 295 47.4
    Overweight (25.0–29.9) 303 23.0 290 23.2 163 24.3
    Obese (≥30) 394 26.4 372 26.4 185 25.1
  Smoking
    Never during pregnancy 979 72.5 933 72.5 494 75.6
    Quit before enrollment 132 9.9 125 9.9 55 8.7
    Current, < ½ pack per day 182 11.5 167 11.4 84 9.8
    Current, ≥ ½ pack per day 78 6.1 77 6.3 35 5.9
Pregnancy Characteristics
  Gestational Age at Enrollment
    15–19.9 weeks 225 15.8 211 15.6 102 14.1
    20–24.9 weeks 964 71.1 915 71.2 482 73.2
    25–27.9 weeks 182 13.2 176 13.3 84 12.6
  Fetal Growth
    Small for Gestational Age 150 9.4 138 9.3 - -
    Not Small for Gestational Age 1219 90.5 1162 90.6 668 100
    Missing 2 0.1 2 0.1 - -
  Hypertensive Disorders
    Gestational Hypertension/Preeclampsiaa 100 6.6 100 6.9 - -
    Chronic Hypertension 49 3.0 45 3.0 - -
    Normotensive 1222 90.3 1157 90.0 668 100.0
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a

Preeclampsia includes all cases including those superimposed on chronic hypertension.

Associations among maternal characteristics and angiogenic marker levels are presented without adjustment (Tables 2 and 3: total sample and “normal” pregnancies respectively) and with adjustment (Tables 4 and 5: total sample and “normal” pregnancies respectively). The text focuses on findings from the “normal” pregnancy sample.

Table 2.

Unadjusted least squares mean concentrations of angiogenic markers by maternal and pregnancy characteristics – Total pregnancy sample (N = 1302)

Placental Growth Factor
(PlGF)		 Soluble Endoglin
(sEng)		 Soluble Fms-Like Tyrosine Kinase-1
(sFlt-1)
N Meana 95% CI Pb Meana 95% CI Pb Meana 95% CI Pb
Gestational Age at Enrollment
    15– 19.9 weeks (ref) 211 228.2 (207.9, 250.4) ref 5.30 (5.06, 5.55) ref 1670 (1504, 1855) ref
    20– 24.9 weeks 915 381.5 (363.6, 400.3) < 0.01 5.28 (5.17, 5.40) 1669 (1593, 1748)
    25– 27.9 weeks 176 556.8 (509.4, 608.6) < 0.01 5.81 (5.51, 6.13) < 0.01 1676 (1501, 1871)
Parity
    Primiparous (ref) 543 378.5 (354.6, 403.9) ref 5.61 (5.45, 5.78) ref 1948 (1839, 2063) ref
    Multiparous 759 364.7 (344.9, 385.7) 5.18 (5.06, 5.30) < 0.01 1501 (1425, 1581) < 0.01
Maternal Age at Enrollment
    <20 years (ref) 227 428.9 (386.4, 476.0) ref 5.59 (5.28, 5.91) ref 2002 (1820, 2201) ref
    20– 29 years 734 358.1 (339.3, 378.0) < 0.01 5.29 (5.17, 5.41) 1586 (1503, 1673) < 0.01
    ≥ 30 years 341 367.0 (336.4, 400.5) < 0.05 5.36 (5.16, 5.56) 1688 (1571, 1814) < 0.01
Medicaid
    No (ref) 565 354.0 (333.1, 376.2) ref 5.46 (5.32, 5.61) ref 1702 (1609, 1802) ref
    Yes 737 387.9 (365.6, 411.6) < 0.05 5.24 (5.11, 5.38) < 0.05 1637 (1550, 1730)
Education
    Grade < 12 296 449.5 (414.6, 487.3) < 0.01 5.32 (5.11, 5.54) 1704 (1550, 1874)
    Grade = 12 (ref) 367 347.1 (317.8, 379.1) ref 5.39 (5.20, 5.60) ref 1631 (1513, 1757) ref
    Grade > 12 639 357.5 (337.5, 378.8) 5.34 (5.21, 5.48) 1678 (1590, 1771)
Pre-pregnancy Body Mass Index
    Underweight 59 555.4 (470.8, 655.2) < 0.01 5.33 (4.78, 5.94) 1939 (1604, 2345)
    Normal (ref) 581 412.6 (387.3, 439.7) ref 5.57 (5.42, 5.72) ref 1884 (1782, 1993) ref
    Overweight 290 378.0 (347.3, 411.3) 5.43 (5.25, 5.62) 1633 (1513, 1764) < 0.01
    Obese 372 283.4 (263.8, 304.4) < 0.01 4.93 (4.75, 5.12) < 0.01 1347 (1245, 1458) < 0.01
Smoking
    Didn't smoke during pregnancy (ref) 933 350.2 (333.7, 367.5) ref 5.41 (5.30, 5.53) ref 1700 (1623, 1781) ref
    Stopped smoking before enrollment 125 317.6 (275.2, 366.5) 5.47 (5.14, 5.83) 1618 (1420, 1844)
    < Half pack/ day 167 507.3 (451.8, 569.7) < 0.01 5.17 (4.98, 5.38) < 0.05 1628 (1451, 1826)
    ≥ Half pack/ day 77 509.4 (437.6, 593.0) < 0.01 4.83 (4.40, 5.30) < 0.05 1493 (1277, 1745)
Race
    Whites/ others (ref) 766 348.9 (330.9, 367.9) ref 5.31 (5.18, 5.43) ref 1591 (1514, 1673) ref
    African Americans 536 444.2 (419.6, 470.2) < 0.01 5.50 (5.36, 5.64) < 0.05 1936 (1839, 2038) < 0.01
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CI = Confidence Interval

a

Least square means of the log biomarker value, back transformed to normal scale

b

Ref denotes referent category for comparisons

Table 3.

Unadjusted least squares mean concentrations of angiogenic markers by maternal and pregnancy characteristics – Normal pregnancy sample (N = 668)

Placental Growth Factor
(PlGF)		 Soluble Endoglin
(sEng)		 Soluble Fms-Like Tyrosine Kinase-1
(sFlt-1)
N Meana 95% CI Pb Meana 95% CI Pb Meana 95% CI Pb
Gestational Age at Enrollment
    15– 19.9 weeks (ref) 102 239.5 (212.0, 270.5) ref 5.23 (4.93, 5.54) ref 1663 (1440, 1920) ref
    20– 24.9 weeks 482 388.0 (366.2, 411.1) < 0.01 5.25 (5.12, 5.38) 1691 (1602, 1786)
    25– 27.9 weeks 84 565.2 (505.4, 632.0) < 0.01 5.55 (5.23, 5.88) 1605 (1409, 1827)
Parity
    Primiparous (ref) 256 399.8 (368.1, 434.3) ref 5.48 (5.30, 5.68) ref 1969 (1840, 2106) ref
    Multiparous 412 368.3 (344.8, 393.3) 5.16 (5.02, 5.31) < 0.01 1517 (1425, 1614) < 0.01
Maternal Age at Enrollment
    <20 years (ref) 113 465.4 (407.2, 532.0) ref 5.41 (5.08, 5.75) ref 2155 (1945, 2388) ref
    20– 29 years 401 362.9 (340.1, 387.2) < 0.01 5.27 (5.13, 5.41) 1584 (1486, 1689) < 0.01
    ≥ 30 years 154 380.7 (342.9, 422.7) < 0.05 5.26 (5.02, 5.51) 1677 (1539, 1827) < 0.01
Medicaid
    No (ref) 286 365.9 (340.7, 393.0) ref 5.39 (5.23, 5.55) ref 1672 (1564, 1788) ref
    Yes 382 396.3 (367.8, 427.1) 5.17 (5.01, 5.33) 1680 (1571, 1797)
Education
    Grade < 12 154 461.3 (416.2, 511.4) < 0.01 5.22 (4.98, 5.46) 1869 (1678, 2082)
    Grade = 12 (ref) 184 348.4 (312.2, 388.8) ref 5.35 (5.12, 5.59) ref 1623 (1474, 1788) ref
    Grade > 12 330 372.2 (347.7, 398.5) 5.27 (5.12, 5.43) 1644 (1543, 1751)
Pre-pregnancy Body Mass Index
    Underweight 25 560.3 (442.9, 708.9) < 0.05 5.63 (4.94, 6.43) 1985 (1560, 2525)
    Normal (ref) 295 427.3 (396.1, 460.8) ref 5.53 (5.36, 5.71) ref 1912 (1789, 2043) ref
    Overweight 163 380.8 (345.9, 419.2) 5.30 (5.09, 5.51) 1582 (1443, 1734) < 0.01
    Obese 185 289.0 (263.5, 317.0) < 0.01 4.79 (4.60, 4.99) < 0.01 1352 (1232, 1485) < 0.01
Smoking
    Didn't smoke during pregnancy (ref) 494 362.4 (341.8, 384.1) ref 5.34 (5.21, 5.48) ref 1661 (1571, 1756) ref
    Stopped smoking before enrollment 55 334.1 (274.7, 406.5) 5.31 (4.91, 5.75) 1583 (1337, 1875)
    < Half pack/ day 84 527.0 (452.3, 613.9) < 0.01 5.07 (4.85, 5.30) < 0.05 1866 (1652, 2109)
    ≥ Half pack/ day 35 491.3 (420.8, 573.7) < 0.01 4.91 (4.45, 5.41) 1714 (1435, 2049)
Race
    Whites/ others (ref) 363 356.8 (334.9, 380.1) ref 5.25 (5.12, 5.40) ref 1599 (1508, 1694) ref
    African Americans 305 467.5 (435.1, 502.4) < 0.01 5.38 (5.22, 5.55) 1958 (1830, 2095) < 0.01
Open in a new tab

CI = Confidence Interval

a

Least square means of the log biomarker value, back transformed to normal scale

b

Ref denotes referent category for comparisons

Table 4.

Adjusted least squares mean concentrations of angiogenic markers by maternal and pregnancy characteristics – Total pregnancy sample (N= 1302)

Placental Growth Factor
(PlGF)		 Soluble Endoglin
(sEng)		 Soluble Fms-Like Tyrosine Kinase-1
(sFlt-1)
N Mean a 95% CI Pb Mean a 95% CI Pb Mean a 95% CI Pb
Gestational Age at Enrollment
      15– 19.9 weeks (ref) 211 288.5 (261.5, 318.1) ref 5.41 (5.09, 5.75) ref 1902 (1698, 2132) ref
      20– 24.9 weeks 915 491.6 (457.3, 528.4) < 0.01 5.31 (5.09, 5.53) 1829 (1695, 1973)
      25– 27.9 weeks 176 710.9 (641.5, 787.9) < 0.01 5.79 (5.44, 6.17) 1816 (1599, 2062)
Parity
      Primiparous (ref) 543 463.5 (427.8, 502.2) ref 5.68 (5.43, 5.95) ref 2060 (1872, 2267) ref
      Multiparous 759 467.3 (430.5, 507.2) 5.32 (5.05, 5.60) < 0.01 1659 (1521, 1810) < 0.01
Maternal Age at Enrollment
      <20 years (ref) 227 465.0 (412.2, 524.6) ref 5.53 (5.14, 5.96) ref 1939 (1716, 2191) ref
      20– 29 years 734 450.0 (417.7, 484.8) 5.45 (5.20, 5.70) 1737 (1601, 1885)
      ≥ 30 years 341 481.8 (434.8, 533.8) 5.52 (5.22, 5.84) 1876 (1675, 2102)
Medicaid
      No (ref) 565 459.3 (419.7, 502.7) ref 5.61 (5.30, 5.93) ref 1887 (1711, 2080) ref
      Yes 737 471.6 (437.2, 508.8) 5.40 (5.16, 5.65) 1812 (1653, 1985)
Education
      Grade < 12 296 484.4 (440.0, 533.3) 5.47 (5.18, 5.78) 1757 (1577, 1958)
      Grade = 12 (ref) 367 444.5 (404.7, 488.2) ref 5.62 (5.32, 5.94) ref 1916 (1732, 2120) ref
      Grade > 12 639 468.2 (427.8, 512.4) 5.41 (5.11, 5.73) 1876 (1687, 2087)
Pre–pregnancy Body Mass Index
      Underweight 59 609.3 (516.6, 718.5) < 0.05 5.46 (4.88, 6.11) 2032 (1672, 2470)
      Normal (ref) 581 499.9 (464.8, 537.7) ref 5.74 (5.49, 5.99) ref 2064 (1900, 2242) ref
      Overweight 290 454.1 (412.8, 499.5) < 0.05 5.67 (5.41, 5.94) 1854 (1689, 2035) < 0.05
      Obese 372 339.3 (312.4, 368.5) < 0.01 5.16 (4.91, 5.41) < 0.01 1502 (1363, 1655) < 0.01
Smoking
      Didn't smoke during pregnancy (ref) 933 387.2 (363.4, 412.6) ref 5.61 (5.42, 5.81) ref 1861 (1735, 1996) ref
      Stopped smoking before enrollment 125 352.7 (312.0, 398.8) 5.70 (5.31, 6.11) 1808 (1578, 2071)
      < Half pack/ day 167 551.5 (493.1, 616.7) < 0.01 5.42 (5.16, 5.69) 1835 (1625, 2071)
      ≥ Half pack/ day 77 623.0 (533.6, 727.4) < 0.01 5.29 (4.78, 5.84) 1893 (1586, 2259)
Race
      Whites/ others (ref) 766 405.8 (376.7, 437.0) ref 5.33 (5.08, 5.59) ref 1627 (1489, 1778) ref
      African Americans 536 533.9 (489.3, 582.5) < 0.01 5.67 (5.39, 5.97) < 0.01 2100 (1911, 2307) < 0.01
Open in a new tab

CI= Confidence Interval

a

Least square means of the adjusted log biomarker value, back transformed to normal scale. Least squares means are adjusted for all other covariates listed in the table

b

Ref denotes referent category for comparisons

Table 5.

Adjusted least square mean concentrations of angiogenic markers by maternal and pregnancy characteristics – Normal pregnancy sample (N = 668)

Placental Growth Factor
(PlGF)		 Soluble Endoglin
(sEng)		 Soluble Fms-Like Tyrosine Kinase-1
(sFlt-1)
N Meana 95% CI Pb Meana 95% CI Pb Meana 95% CI Pb
Gestational Age at Enrollment
    15– 19.9 weeks (ref) 102 301.7 (263.1, 346.0) ref 5.35 (4.95, 5.78) ref 2001 (1729, 2317) ref
    20– 24.9 weeks 482 495.6 (451.3, 544.3) < 0.01 5.29 (5.04, 5.56) 1967 (1794, 2157)
    25– 27.9 weeks 84 709.0 (623.7, 805.9) < 0.01 5.54 (5.16, 5.94) 1859 (1583, 2183)
Parity
    Primiparous (ref) 256 474.0 (425.8, 527.7) ref 5.51 (5.21, 5.82) ref 2148 (1899, 2429) ref
    Multiparous 412 472.6 (424.5, 526.0) 5.28 (4.98, 5.60) 1756 (1581, 1949) < 0.01
Maternal Age at Enrollment
    <20 years (ref) 113 493.3 (419.5, 580.0) ref 5.42 (5.00, 5.88) ref 2109 (1820, 2443) ref
    20– 29 years 401 448.6 (406.8, 494.7) 5.40 (5.10, 5.72) 1787 (1608, 1985) < 0.05
    ≥ 30 years 154 479.1 (418.5, 548.4) 5.36 (5.01, 5.73) 1943 (1685, 2240)
Medicaid
    No (ref) 286 462.5 (412.9, 518.1) ref 5.49 (5.15, 5.85) ref 1965 (1732, 2230) ref
    Yes 382 484.3 (436.3, 537.6) 5.30 (5.03, 5.59) 1918 (1717, 2144)
Education
    Grade < 12 154 486.4 (427.8, 553.0) 5.32 (4.97, 5.69) 1896 (1664, 2161)
    Grade = 12 (ref) 184 452.2 (399.1, 512.5) ref 5.57 (5.22, 5.95) ref 2005 (1755, 2291) ref
    Grade > 12 330 482.0 (429.0, 541.5) 5.30 (4.96, 5.66) 1925 (1690, 2193)
Pre-pregnancy Body Mass Index
    Underweight 25 606.2 (478.2, 768.4) 5.65 (4.91, 6.49) 2115 (1669, 2681)
    Normal (ref) 295 523.0 (475.6, 575.1) ref 5.63 (5.35, 5.94) ref 2232 (2012, 2477) ref
    Overweight 163 457.9 (407.3, 514.9) < 0.05 5.43 (5.14, 5.74) 1905 (1693, 2145) < 0.01
Obese 185 345.6 (311.0, 384.2) < 0.01 4.90 (4.66, 5.16) < 0.01 1580 (1396, 1788) < 0.01
Smoking
    Didn't smoke during pregnancy (ref) 494 404.3 (371.2, 440.5) ref 5.51 (5.27, 5.75) ref 1829 (1676, 1996) ref
    Stopped smoking before enrollment 55 360.1 (301.0, 430.8) 5.49 (5.03, 6.00) 1785 (1503, 2120)
    < Half pack/ day 84 564.9 (487.6, 654.3) < 0.01 5.24 (4.95, 5.55) 2002 (1721, 2329)
    ≥ Half pack/ day 35 610.1 (510.2, 729.6) < 0.01 5.34 (4.79, 5.95) 2175 (1777, 2661)
Race
    Whites/ others (ref) 363 409.2 (369.5, 453.2) ref 5.25 (4.97, 5.55) ref 1723 (1544, 1921) ref
    African Americans 305 547.4 (489.9, 611.7) < 0.01 5.54 (5.22, 5.87) < 0.05 2189 (1943, 2466) < 0.01
Open in a new tab

CI= Confidence Interval

a

Least square means of the adjusted log biomarker value, back transformed to normal scale. Least squares means are adjusted for all other covariates listed in the table

b

Ref denotes referent category for comparisons

Gestational Age

Gestational age was positively associated with PlGF in all models, a trend toward a positive association was observed for sEng, and sFlt-1 levels were not significantly different across the 15–27 week gestational age window.

Parity and Maternal Age

In unadjusted models, multiparity was significantly associated with lower sEng and sFlt-1 levels. After adjustment, multiparous women still had lower levels than primiparas, but only sFlt-1 results retained statistical significance (1756 pg/mL (95% CI: 1581–1949): 2148 pg/mL (95% CI: 1899–2429), p < 0.01, Table 5). Maternal age, a factor correlated with parity, was not associated with biomarker concentration after adjustment. This was true for models utilizing ≥35 as the cut-off for “older” mothers.

Socioeconomic Status

Medicaid use was associated with lower sEng and higher PlGF levels only in the unadjusted total sample (Table 2). No strong associations were observed for Medicaid use among “normal” pregnancies (Table 5). Similarly, educational attainment and PlGF levels were not associated after adjustment.

BMI

Consistently, pre-pregnancy BMI was inversely associated with levels of each marker. sEng levels differed significantly between normal (5.63 pg/mL) and obese women (4.90 pg/mL, p <0.01, Table 5). PlGF demonstrated marked changes and a monotonic increase across BMI categories: (underweight = 606.2 ng/mL, normal = 523.0 ng/mL, overweight = 457.9 ng/mL, and obese = 345.6 ng/mL (Table 5); adjusted β for the continuous BMI variable = −0.027/ BMI unit, p <0.0001). A slightly weaker inverse association was observed between pre-pregnancy weight and angiogenic levels.

Smoking

Among women who smoked at enrollment, unadjusted sEng levels were lower and PlGF concentrations were higher than those of non-smokers, with some dose-response suggested. After adjustment, only the PlGF association persisted, levels in “normal” pregnancies being 404.3 ng/mL, 564.9 ng/mL, and 610.1 ng/mL for non-smokers, those who smoked <½ pack/day, and smokers of ≥ ½ pack/day, respectively (P <0.01 comparisons vs. non-smokers (Table 5)). For each marker, levels in women who smoked during pregnancy but quit before enrollment were indistinguishable from levels in non-smokers.

Race

For each factor, African Americans had higher levels of angiogenic markers than women of all other racial/ethnic groups and covariate adjustment only strengthened associations (Tables 2–5). Among “normal” pregnancies PlGF levels were 34% higher in African Americans (p< 0.01) and sFlt-1 concentrations were 27% greater (p < 0.01 (Table 5)). Findings were similar for analyses limited to African-American and non-Hispanic White women.

Comment

We examined associations among established risk factors for adverse pregnancy outcomes2,33 and levels of angiogenic markers in women from the POUCH Study. Our findings were consistent with overall patterns previously reported for gestational age, parity, maternal age and BMI. In addition, we found levels of all three markers varied by race and concentrations were similar in women who quit smoking during pregnancy and those who did not smoke in pregnancy.

Studies that have measured angiogenic markers at different gestational weeks have noted a rise in PlGF levels at mid-pregnancy,1,5,16 little change in sFlt-1 across mid-pregnancy but elevations later in pregnancy,1,5,7,22,34 and increasing sEng levels with increasing GA.1,6 Overall, the patterns observed in our sample were similar to those from previous studies covering the period of mid-pregnancy.

Maternal age and parity have been examined explicitly in a few, small studies and have yielded inconsistent results. Associations between maternal age and first trimester levels of sFlt-1 and PlGF have been inconsistent,16,35 whereas for levels at delivery only PlGF was associated with maternal age.20 In contrast, univariable analyses demonstrated higher sFlt-1 and lower PlGF for nulliparas irrespective of gestational weeks at measurement.16,20,35 After adjustment, maternal age was not associated with first trimester sFlt-1 or PlGF,21,35 however, parity was associated with both lower sFlt-1 and higher PlGF in a small sample35 and with higher PlGF in a larger one.21

In POUCH, younger women and primiparas tended to have higher sFlt-1 and sEng levels, but after adjustment only primiparity was associated with higher sFlt-1. These results are consistent with others except that we did not observe a positive association between multiparity and PlGF. This may reflect differences in the timing of PlGF measurement, sample size, or covariates used for adjustment. Our covariate adjustment was more extensive than one small, positive study35 and did not include measures of infant growth like the second.21 While the associations with parity need confirmation, other data support these findings. First, high sFlt-1 and sEng characterize preeclampsia, a disease more likely to complicate first pregnancies.5,6,23 Second, a small longitudinal study reported significant declines in first trimester sFlt-1 between first and second pregnancies.24

We are unaware of other studies examining relations between socioeconomic status (SES) and angiogenic markers. In POUCH, some angiogenic marker levels were associated with educational attainment and history of Medicaid enrollment, two proxies for SES, but only in unadjusted models. Overall, our results suggest that the SES-angiogenic marker association reflects correlations between SES variables and other maternal characteristics.

Overall, studies examining the association between maternal BMI/weight and angiogenic markers find statistically significant inverse relations, although findings have not been consistent across studies or markers.5,7,16,20,21,35 We observed consistent inverse associations with all three biomarkers, even among “normal” pregnancies which suggests this pattern is not related to a high-risk subset. A dilution effect may explain the inverse relation with maternal BMI/weight; similar effects are thought to occur with substances crossing from the fetus (e.g. MSAFP)36,37 or placenta (e.g. corticotrophin releasing hormone)37,38 into the maternal circulation. Given that high BMI/obesity is a risk factor for preeclampsia,2,33 the relation between angiogenic markers, BMI and pregnancy outcome requires further study. Among women with high BMI and preeclampsia, levels of angiogenic markers in pregnancy might reflect a combination of effects due to larger maternal size, decreased pregnancy-related vascular expansion and endothelial dysfunction.33,39–42

Given that smoking protects against preeclampsia and angiogenic markers are differentially expressed in preeclamptics (higher sFlt-1, lower PlGF, higher sEng),,2,5,6,43 it follows that women who smoke during pregnancy appear to have a more favorable angiogenic profile (lower sFlt-1, higher PlGF, lower sEng) than women who do not. Two studies, one presenting unadjusted estimates and the other levels in matched cases and controls, found third trimester sFlt-1 levels were lower among women who smoked during pregnancy vs. those who did not.6,22,44 In a third study examining levels between 33–42 weeks gestation, findings were no longer statistically significant after covariate adjustment.45 For measures taken earlier in pregnancy, results were less consistent.7,22,45 Measured anytime during pregnancy, PlGF was higher among women who smoked in pregnancy.6,7,21,46 Unadjusted and adjusted sEng was lower among current smokers before 20 weeks gestation, but not later in pregnancy.6,45

Consistent with previous reports, we found statistically-significantly higher PlGF levels and non-significantly lower sEng levels among actively smoking women. We may have been unable to detect differences in sFlt-1 levels due to the timing of our measurement in early-mid second trimester (15% at <20 weeks, most 20–24.9 weeks). The smoking effect may be greater later in pregnancy due to dramatic changes in angiogenic marker levels at the end of pregnancy.47 Even for preeclampsia, changes in sFlt-1 levels are inconsistently detected < 20 weeks GA.6,34 While covariate adjustments varied between previous studies, similar findings in our unadjusted and adjusted models make differences in covariate adjustment an unlikely explanation for our result.

Unlike others, we examined levels of angiogenic markers separately for women who smoked early in pregnancy, but stopped before enrollment. Angiogenic marker levels among these smokers who quit during pregnancy are no different from those of women who did not smoke during pregnancy. While we lack biochemical confirmation of smoking status, misclassification may be greater among women who report quitting during pregnancy,48 with active smokers misreporting themselves as having quit. This type of misclassification would, in expectation, reduce sFlt-1 and sEng levels and elevate PlGF levels; correction would likely strengthen our findings. Larger studies are needed to confirm these observations. However, our findings are consistent with those of a report examining preeclampsia risk by pattern of smoking. Smokers who quit between their first antenatal visit (<15 weeks) and 30–32 weeks gestation were as likely to develop preeclampsia as women who did not smoke in pregnancy, whereas women who reported smoking at 30–32 weeks, independent of prior smoking in pregnancy, were less likely to have preeclampsia.49

Race is among the least studied characteristics with respect to angiogenic markers. Studies from England reported adjusted first trimester levels of PlGF were higher among black women as compared to white women.21,26 We are unaware of other large studies that have explicitly reported differences in mean biomarker levels among women of different racial/ethnic groups. Our findings confirm and extend the previous PlGF findings, showing sFlt-1 and sEng levels were also higher in African-American women vs. non-Hispanic Whites. While different populations were studied and modeling approaches varied, the PlGF β-coefficient for race in our model (15–27 weeks GA), was nearly twice that reported previously (evaluated at 11–14 weeks GA). Differences in angiogenic marker levels by race/ethnicity should be explored more fully, describing trajectories for each factor through pregnancy and potential interactions with other maternal characteristics such as parity which may modify race-preeclampsia associations.50

The strengths of this study include its size, the clearly defined population studied, its use of a “normal" pregnancy group and a comparison total pregnancy sample, adjustment for multiple covariates, and its exploration of little-studied characteristics. A significant limitation is having only one biomarker measurement during pregnancy. The importance of longitudinal changes in angiogenic factors has been clearly shown1,8,18,51,52 and we may not have taken measures at the optimal time for detecting all associations with biomarker levels. Finally, examining relations among multiple angiogenic markers and many maternal characteristics increases the probability of a false positive finding. We did not adjust for multiple comparisons since the characteristics examined were chosen a priori, mostly based on previously reported associations and results from other pregnancy-related biomarkers.

This analysis confirms several previously reported associations between angiogenic markers and maternal characteristics, including lower sFlt-1 levels among multiparas and the inverse relation between all markers and maternal BMI. Additionally, we demonstrate that levels of all angiogenic markers are higher among African-American women. Examining profiles in women according to smoking during pregnancy, we report higher PlGF levels and a trend toward lower sEng among current smokers, but not for smokers who quit earlier in pregnancy. These findings can inform the selection of covariates included in models utilizing angiogenic biomarkers and suggest new avenues for research examining the contribution of angiogenic factors to the etiology of adverse pregnancy outcomes.

Acknowledgments

Funding sources include the following: (Grants 20FY01-38 and 20-FY04-37, The March of Dimes Foundation), (R01 HD34543, National Institute of Child Health and Human Development and the National Institute of Nursing Research), (Grant 02816-7, Thrasher Research Foundation), (Grant RD 05-0003099, Diabetes UK), and (Grant U01 DP000143-01, The Centers for Disease Control and Prevention) awarded to C.B.H. R.S.M. is supported by an Institutional T32 grant (T32 HD046377) in Perinatal Epidemiology awarded to Michigan State University. S.R. is supported by a Women's Reproductive Health Research Award (5K12HD001255- NIH/NICHD). S.A.K is an investigator of the Howard Hughes Medical Institute.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

DISCLOSURE: Discloser: Dr. Karumanchi is a listed as a co-inventor on multiple patents assigned to the Beth Israel Deaconess Medical Center that are related to the diagnosis and therapy of preeclampsia. These patents have been licensed non-exclusively to multiple companies. Dr. Karumanchi is a consultant to Abbott, Beckman Coulter, Johnson & Johnson and Roche diagnostics.

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