ORIGINAL
E n d o c r i n e
ARTICLE
R e s e a r c h
Maternal Levels of Corticotropin-Releasing Hormone
during Pregnancy in Relation to Adiponectin
and Leptin in Early Childhood
Magnus H. Fasting, Emily Oken, Christos S. Mantzoros, Janet W. Rich-Edwards,
Joseph A. Majzoub, Ken Kleinman, Sheryl L. Rifas-Shiman, Torstein Vik, and Matthew W. Gillman
Department of Public Health and General Practice (M.H.F., T.V.), The Norwegian University of Science and Technology,
7489 Trondheim, Norway; Obesity Prevention Program (M.H.F., E.O., J.W.R.-E., K.K., S.L.R.-S., M.W.G.), Department
of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, and Boston, Division of
Endocrinology, Diabetes, and Metabolism (C.S.M.), Department of Medicine, Beth Israel Deaconess Medical Center,
Harvard Medical School, Massachusetts 02215; and Division of Endocrinology (J.A.M.), Children’s Hospital, Harvard
Medical School; Connors Center for Women’s Health and Gender Biology (J.W.R.-E.), Brigham and Women’s Hospital;
and Departments of Epidemiology (J.W.R.-E.) and Nutrition (M.W.G.), Harvard School of Public Health, Boston,
Massachusetts 02115
Background: Fetal glucocorticoid exposure is associated with later development of features of the
metabolic syndrome such as central obesity and insulin resistance. Fat tissue, especially visceral fat,
produces adiponectin, which is inversely associated with insulin resistance in older children and adults.
Adipocytes also produce leptin, directly related to measures of adiposity. It is unknown how the secretion of these hormones in early childhood is related to pregnancy levels of CRH, a proxy of fetal
glucocorticoid exposure.
Aim: Our aim was to study the relationship of maternal midpregnancy CRH levels with offspring
levels of adiponectin and leptin in early childhood.
Methods: The study population consisted of 349 mother-children pairs from Project Viva, a prospective prebirth cohort study from eastern Massachusetts. We created a general linear model with
log CRH levels in midpregnancy maternal blood as the predictor and adiponectin and leptin measured in the 3-yr-old offspring as outcomes, adjusting for covariates.
Results: The means (SD) of log CRH, adiponectin, and leptin were 4.97 (0.65) log pg/ml, 22.4 (5.8)
␮g/ml, and 1.9 (1.8) ng/ml. For each unit increment in log CRH, mean value of offspring adiponectin
was 1.10 ␮g/ml (95% confidence interval ⫽ 0.06 –2.14) higher. We found no association with leptin
(⫺0.08 ng/ml; 95% confidence interval ⫽ ⫺0.40 – 0.24).
Conclusions: Higher maternal blood levels of CRH were associated with higher levels of adiponectin but unchanged levels of leptin at age 3 yr. The increased adiponectin levels might
represent secretion from organs other than fat or reflect a compensatory mechanism to increase
insulin sensitivity. (J Clin Endocrinol Metab 94: 1409 –1415, 2009)
ith the increasing prevalence of obesity, the metabolic
syndrome is becoming common in children and adolescents (1). Central to the pathogenesis of the metabolic syndrome is insulin resistance, which is closely associated with obesity and in particular central obesity (2).
W
In previous work, we have found that elevated maternal
plasma levels of CRH were associated with increased central
obesity, but lower overall body mass index (BMI) in offspring at
age 3 yr (3). To further investigate the role of elevated levels of
CRH in the development of metabolism, it is important to study
ISSN Print 0021-972X ISSN Online 1945-7197
Printed in U.S.A.
Copyright © 2009 by The Endocrine Society
doi: 10.1210/jc.2008-1424 Received July 7, 2008. Accepted January 23, 2009.
First Published Online February 3, 2009
Abbreviations: AGA, Appropriate for gestational age; BMI, body mass index; CI, confidence
interval; SGA, small for gestational age; SS/TR, ratio of triceps and subscapular skin folds;
SS⫹TR, sum of triceps and subscapular skin folds.
J Clin Endocrinol Metab, April 2009, 94(4):1409 –1415
jcem.endojournals.org
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Fasting et al.
CRH and Offspring Adiponectin and Leptin
the impact of this exposure on the metabolic function of adipocytes in addition to measures of fatness and fat distribution (4).
Adiponectin and leptin are hormones produced by fat cells
and are markers for fat cell burden, and also influence related
metabolism. Adiponectin increases hepatic insulin sensitivity
and plays an important role in lipid metabolism (5, 6). Blood
levels of adiponectin are inversely associated with insulin resistance and obesity, in particular central obesity, in older children
and adults (6). However, in young children, the relationship is
less clear. There seems to be a direct association between indicators of obesity and adiponectin in newborns (7, 8), but no
association just after birth and up to 2 yr (9, 10). Few studies exist
among older children, but Cianflone et al. (11) found a weak
inverse association in 85 children aged 2– 6 yr. No studies have
addressed the association between maternal levels of CRH and
early childhood adiponectin levels.
Leptin mediates food intake and energy consumption (12),
and circulating leptin levels are positively associated with adiposity from infancy to adulthood (13, 14). No studies have addressed the association between maternal levels of CRH and
early childhood leptin levels.
To further study the relationship of maternal CRH on the
endocrine function of adipose tissue, we examined the associations of CRH levels in second-trimester maternal blood, with
blood levels of adiponectin and leptin in the offspring at 3 yr of
age, before and after adjusting for BMI and fat distribution. One
of our hypotheses was that higher maternal CRH levels would be
associated with decreased levels of adiponectin at age 3.This
hypothesis was based on the results of studies in animal models
(15, 16), our previous study (3), and results from studies in young
children (11). The other hypothesis was that higher maternal
CRH would be positively associated with offspring leptin, and
this hypothesis was based on our previous results (3), results
from animal models (17), and the positive correlation between
leptin and BMI (13, 14).
Subjects and Methods
Study sample
The study sample was drawn from Project Viva, a prospective prebirth study of pregnant mothers and their offspring. We recruited women
at their first prenatal visit at one of eight Harvard Vanguard Medical
Associates centers in eastern Massachusetts. Exclusion criteria were multiple gestation, inability to answer questions in English, plans to move
from the area before delivery, and gestational age over 22 wk at the initial
visit. Details on follow-up have been reported elsewhere (18). Of the
2128 women who delivered a live infant, 1579 were eligible for 3-yr
follow up by virtue of having completed prenatal nutritional assessments
and consenting for their children to be followed up. We collected follow-up information on 1401 (89% of 1579), including in-person examinations on 1293 (82%). For this analysis, we excluded 476 of the 1293
participants who did not have 3-yr child blood drawn, 88 missing leptin
or adiponectin values due to limited blood volume, 363 with no measure
of maternal CRH, one who had a second-trimester blood draw before 17
wk gestation, and 16 who had missing values for race/ethnicity, preeclampsia, or BMI, leaving a cohort for analysis of 349 mother-child pairs.
Compared with the 1230 women and children who were eligible for
3-yr follow-up but not included in these analyses, the 349 women and
children included in this study were similar with respect to several back-
J Clin Endocrinol Metab, April 2009, 94(4):1409 –1415
ground and pregnancy characteristics, i.e. maternal age, race/ethnicity,
socioeconomic status, and maternal education. However, the women
included in this study breastfed their children slightly longer (mean 6.7
vs. 6.1 months).
Ethics
We obtained informed consent from all mothers. Institutional review
boards of Harvard Pilgrim Health Care and affiliated institutions approved the study. All procedures were in accordance with the ethical
standards for human experimentation established by the Declaration of
Helsinki (19).
Exposure variable
The main exposure was maternal blood levels of CRH in midpregnancy. We collected blood from mothers at the time of routine midpregnancy blood draws (median 28.0 wk gestation, interquartile range 27.1–
28.6, minimum 24.9, maximum 37.4 wk). The blood samples were
refrigerated for up to 26 h and then transported on cold pack to a central
laboratory, where they were processed and stored at ⫺80 C. Later they
were assayed by RIA (Peninsula Laboratories Inc., San Carlos, CA) (20).
We have previously shown that this cooling and transportation protocol
is as valid as more rapid processing and freezing (21). Values below the
detection limit of 40 ␮g/ml were set to 20 ␮g/ml.
We first assayed 443 blood samples for CRH selected by risk factors
for preterm birth and depression and later assayed the remaining 564
samples. We included in this analysis 149 participants from the first
batch and 200 from the second batch whose children also had blood
collected at age 3 yr. Between the two analytic runs, both the technician
performing the analysis and the antibody changed. A comparison of the
results showed that the samples assayed in the first batch consistently
showed lower values than the samples assayed in the second batch. This
difference could not be explained by either socio-demographic or pregnancy differences in the two groups. Therefore, we added an adjustment
factor of 0.48, calculated by regression, to all the values in the second
group.
Outcome variables
We obtained blood samples from the 3-yr-old children and measured
leptin and adiponectin using RIA kits (Linco Research, Inc., St. Charles,
MO) as previously described (22). The lower detection limit was 0.5
ng/ml for leptin and 2 ␮g/ml for adiponectin. Values below these limits
were set to 0.25 ng/ml for leptin and 1 ␮g/ml for adiponectin.
At the 3-yr visit, trained research staff measured weight with a Seca
scale (model 881; Seca, Hanover, MD), height with a Shorr height board
(Shorr Productions, Olney, MD), and triceps and subscapular skin fold
thickness with a Holtain caliper (Holtain Ltd., Crosswell, Crymych,
Dyfed, Wales, UK). Every 6 months, an expert auxologist (Irwin Shorr,
MPH) trained or retrained the research assistants on volunteers in ages
similar to Viva participants. We calculated BMI (weight in kilograms/
height in square meters) and determined age- and sex-specific z-scores
based on 2000 Centers for Disease Control reference data (23), the sum
(SS⫹TR) and ratio (SS/TR) of triceps and subscapular skin folds.
Covariates and confounders
We abstracted birth weight from hospital medical records. We calculated gestational age from the first day of the last menstrual period, and
if this estimate differed by more than 10 d from the estimate from the
second-trimester ultrasound, we used the ultrasound estimate instead.
We calculated birth weight for gestational age z-score using U.S. national
reference data (23). Using a combination of mailed questionnaires and
interviews, we obtained information on maternal age at enrollment,
prepregnancy BMI, education, marital status, race/ethnicity, smoking in
pregnancy, household income, paternal BMI, and child duration of
breastfeeding at age 1 yr (18). In addition we obtained information on
television viewing and sleep during early childhood and consumption of
sugar-sweetened beverages at age 2 yr (18). To get information on weight
J Clin Endocrinol Metab, April 2009, 94(4):1409 –1415
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gain in pregnancy and preeclampsia, we used information recorded in the
mothers’ medical records (24).
Statistical methods
The distribution of CRH levels was positively skewed, so we used log
CRH in the statistical analyses. In addition, as expected, CRH was
strongly correlated with the gestational week of blood draw (Pearson’s
r ⫽ 0.30; P ⬍ 0.001). We therefore created a log CRH value adjusted for
gestational age by regressing log CRH on gestational week at blood draw
and adding back the mean value of log CRH. In all analyses, we used this
new variable, which was by design unrelated to gestational week of blood
draw (r ⫽ 0.00). We then created quartiles of adjusted log CRH to study
covariates and outcomes over different levels of CRH exposure.
We also calculated correlation coefficients among child anthropometric measures and adiponectin and leptin, all measured at age 3 yr,
using Spearman rank correlation test.
In the multivariable models describing the linear relationship of CRH
with adiponectin and leptin levels, we included in the first model only
TABLE 1.
1411
gestational age at blood draw-adjusted log CRH to assess its independent
effects on the outcomes. We also checked whether the estimate differed
between boys and girls; because it did not, we adjusted for sex in subsequent models. In a second model, we adjusted for child’s exact age at
the 3-yr assessment, and in the third model, we adjusted for maternal
race/ethnicity and pregnancy-induced hypertension because these were
the only covariates that changed the ␤ for log CRH by more than 10%.
To assess adiponectin production independent of fat mass and fat distribution, we adjusted separately for child BMI z-score and for both
SS/TR and BMI z-score. Additional adjustment for prepregnancy BMI,
gestational weight at birth, maternal education, marital status, smoking
in pregnancy, household income, paternal BMI, child duration of breastfeeding, television viewing, sleep during early childhood, consumption of
sugar-sweetened beverages at age 2 yr or weight gain did not alter the
observed relationship between adjusted log CRH and adiponectin or
leptin, and therefore we did not include these characteristics in our
models. In light of the strong evidence of different levels of CRH in
women with different race/ethnicity (25), we also performed multi-
Maternal and offspring characteristics related to quartiles of log CRH, adjusted for gestation length at blood draw
Quartiles of gestation-adjusted log CRH
Variables
Maternal CRH
CRH (pg/ml)
Gestation-adjusted log CRH (log pg/ml)
Maternal and paternal characteristics
Maternal age at enrollment (yr)
Maternal prepregnancy BMI (kg/m2)
Paternal BMI (kg/m2)
Household income ⬎$70,000
College graduate
Married or cohabitating
Maternal race/ethnicity
Caucasian
African-American
Other
Pregnancy characteristics
Weight gain in pregnancy (kg)
Gestational length (wk)
PIH or PE
Smoking in pregnancy
Never smokers
Former smokers
Smokers
Childbirth characteristics
Weight for gestational age (z-score)
Duration of breastfeeding (months)
Boys
Childhood habits
Television watching (h/d)a
Sleep (h/d)a
Sugar sweetened beverages at age 2 yr (servings/d)
Child characteristics at 3-yr assessment
Age (months)
Height (cm)
Weight (kg)
BMI (z-score)
SS⫹TR (mm)
SS/TR
Adiponectin (␮g/ml)
Leptin (ng/ml)
Total
Q1 (n ⴝ 87)
Q2 (n ⴝ 87)
Q3 (n ⴝ 87)
Q4 (n ⴝ 87)
184 (192)
4.97 (0.62)
77 (29)
4.24 (0.38)
122 (19)
4.79 (0.09)
167 (41)
5.12 (0.11)
369 (311)
5.74 (0.42)
32.4 (5.2)
24.5 (5.1)
26.6 (3.8)
214 (65)
247 (71)
322 (93)
31.8 (5.7)
25.1 (5.8)
26.6 (4.0)
46 (59)
58 (67)
80 (92)
32.0 (5.1)
24.7 (4.6)
26.9 (3.5)
50 (60)
60 (69)
80 (92)
32.9 (5.2)
24.7 (6.0)
26.6 (3.9)
58 (69)
61 (69)
80 (92)
32.9 (4.9)
23.6 (3.9)
26.3 (3.9)
60 (71)
68 (78)
82 (94)
248 (71)
52 (15)
49 (14)
51 (59)
24 (28)
12 (14)
61 (70)
17 (20)
9 (10)
66 (75)
8 (9)
14 (16)
70 (80)
3 (3)
14 (16)
15.5 (5.5)
39.3 (1.8)
37 (11)
15.0 (5.3)
39.6 (1.7)
4 (5)
16.3 (5.8)
39.6 (1.6)
7 (8)
15.5 (5.1)
39.3 (1.8)
8 (9)
15.2 (5.7)
38.8 (2.0)
18 (21)
239 (70)
66 (19)
38 (11)
68 (80)
11 (13)
6 (7)
62 (72)
15 (17)
9 (10)
55 (63)
23 (26)
9 (10)
54 (64)
17 (20)
14 (16)
0.25 (0.96)
6.7 (4.5)
180 (52)
0.25 (0.93)
6.9 (4.5)
45 (52)
0.32 (1.01)
6.7 (4.6)
38 (44)
0.28 (0.88)
6.1 (4.3)
50 (57)
0.15 (1.00)
7.3 (4.7)
47 (54)
1.2 (1.0)
12.2 (1.1)
2.1 (1.7)
1.3 (0.9)
12.4 (1.0)
1.9 (1.5)
1.1 (1.1)
12.1 (1.1)
2.2 (1.9)
1.3 (1.2)
12.3 (1.2)
2.1 (1.4)
1.1 (0.9)
12.2 (1.0)
2.3 (1.9)
39.2 (4.3)
97.5 (4.5)
15.7 (2.5)
0.42 (1.08)
16.4 (4.2)
0.65 (0.16)
22.4 (5.8)
1.9 (1.8)
38.9 (3.2)
97.6 (4.1)
15.8 (2.3)
0.41 (1.12)
16.0 (4.2)
0.66 (0.14)
21.3 (6.1)
1.9 (1.8)
40.1 (6.4)
97.9 (5.6)
16.2 (3.5)
0.58 (1.19)
17.3 (5.4)
0.64 (0.18)
22.1 (6.3)
2.0 (1.9)
38.8 (3.5)
96.9 (3.9)
15.5 (1.7)
0.48 (0.95)
16.3 (3.6)
0.65 (0.18)
23.0 (5.4)
1.9 (2.2)
38.8 (3.1)
97.5 (4.4)
15.4 (2.0)
0.22 (1.04)
15.6 (3.2)
0.66 (0.14)
23.0 (5.1)
1.7 (1.1)
Data are from 349 mother-child pairs in Project Viva. Results are shown as mean (SD) or n (percent). GDM, Gestational diabetes mellitus; IGT, impaired glucose
tolerance; PE, preeclampsia; PIH, pregnancy-induced hypertension.
a
Weighted average from 6 months to 3 yr.
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Fasting et al.
CRH and Offspring Adiponectin and Leptin
TABLE 2. Spearman correlations (P values) among
adiponectin and leptin levels and anthropometric measures
among 349 children at age 3 yr
Leptin
Adiponectin
Leptin
BMI z-score
SS⫹TR
⫺0.01 (0.88)
BMI
z-score
0.07 (0.22)
0.22 (⬍0.001)
SSⴙTR
SS/TR
0.11 (0.04)
0.17 (0.002)
0.56 (⬍0.001)
⫺0.07 (0.19)
0.08 (0.14)
0.02 (0.65)
⫺0.9 (0.08)
Skin fold measurements were available in only 341 of the children.
variate analyses stratified by race/ethnicity. Finally, to control for
possible effects of adjusting the CRH values, we reanalyzed the data
stratified by analysis batch. We used SAS version 9.1 (SAS Institute,
Cary, NC) for all analyses.
Results
The unadjusted mean (SD) value of CRH was 184 (192) pg/ml
(range 20 –2085 pg/ml). Mean (SD) adjusted log CRH was 4.97
(0.65) log pg/ml (Table 1). At the 3-yr assessment, the mean (SD)
adiponectin concentrations were 22.0 (6.0) ␮g/ml among boys
and 22.8 (5.5) ␮g/ml among girls, and the mean (SD) concentration of leptin was 1.53 (1.43) ng/ml among boys and 2.25 (2.09)
ng/ml among girls.
As expected, women with higher CRH had shorter gestation
length. Women in the highest quartile of adjusted log CRH were
also more likely to be Caucasian or have preeclampsia or pregnancy-induced hypertension (Table 1). There was no association
between adjusted log CRH and birth weight for gestational age
(Table 1).
At age 3 yr, in bivariate analyses, adiponectin was slightly
positively correlated with SS⫹TR but not with BMI or SS/TR
(Table 2). Leptin, on the other hand, was positively correlated
with BMI and SS⫹TR but not with SS/TR. As expected, SS⫹TR
and BMI z-score were highly correlated, whereas SS/TR was not
correlated with either measure. Adiponectin and leptin were
uncorrelated with each other (Table 2). Adiponectin was inversely
correlated with height (r ⫽ ⫺0.11; P ⫽ 0.05) but not with weight
(r ⫽ ⫺0.03; P ⫽ 0.64). Leptin was directly correlated with weight
(r ⫽ 0.14; P ⫽ 0.01) but not with height (r ⫽ 0.03; P ⫽ 0.55).
In bivariate analyses, a 1-unit increment of adjusted log CRH
was associated with 1.15 [95% confidence interval (CI) ⫽ 0.17–
2.13] ␮g/ml higher adiponectin. After adjusting for relevant covariates, each 1-unit increase of adjusted log CRH predicted an
TABLE 3.
J Clin Endocrinol Metab, April 2009, 94(4):1409 –1415
increase of mean adiponectin of 1.10 (95% CI ⫽ 0.06 –2.14)
␮g/ml. Adjusting for BMI z-score or both SS/TR and BMI z-score
strengthened the ␤-coefficients slightly, to 1.13 (95% CI ⫽ 0.09 –
2.17) or 1.13 (95% CI ⫽ 0.10 –2.16) (Table 3), respectively.
Including height or weight at 3 yr separately in the model did not
change these estimates (data not shown). Moreover, the trends
were essentially the same when we analyzed for each CRH-analysis batch separately, albeit not statistically significant within
each of these smaller groups (data not shown).
The relationship between adjusted log CRH and adiponectin
was largely similar between Caucasian and African-American
mother-children pairs (Fig. 1). Among Caucasian women, a
1-unit increase in adjusted log CRH was associated with a 1.20
(95% CI ⫽ 0.06 –2.35) ␮g/ml higher adiponectin in their offspring, and among African-American women, q 1-unit increase
in adjusted log CRH was associated with a 2.48 (95% CI ⫽
⫺1.25– 6.21) ␮g/ml higher adiponectin. After adjusting for the
same covariates as in the combined model, except for race/ethnicity, the ␤-coefficients remained similar: 1.32 (95% CI ⫽ 0.12–
2.52) and 2.66 (⫺1.15– 6.50) for Caucasian and African-American mother-child pairs, respectively.
We did not find any associations between adjusted log CRH
and leptin levels; the adjusted estimate was a change of ⫺0.08
(95% CI ⫽ ⫺0.40 – 0.24) ng/ml leptin per unit change in adjusted
log CRH. After taking BMI z-score or both SS/TR and BMI
z-score into account, the estimate was hardly changed (Table 3).
Adjusting for height or weight at 3 yr separately did not change
these estimates (data not shown). There was no evidence for any
differences in this relationship when the analysis was stratified by
race/ethnicity or by CRH-analysis batch.
In this group, we found a weaker association between adjusted log CRH and offspring BMI and central obesity at age 3
yr than we previously observed in a different subset of Project
Viva mother-children pairs (3). A 1-unit increment of adjusted
log CRH was associated with an increase of 0.02 (95% CI ⫽
⫺0.007– 0.05) in SS/TR and a decrease of ⫺0.12 (95% CI ⫽
⫺0.30 – 0.06) in BMI-Z-score after adjusting for the covariates
described previously (3).
Discussion
In contrast to our original hypothesis, in this study, we found that
higher maternal second-trimester CRH was associated with
higher adiponectin at 3 yr. The magnitude of this association was
Changes in 3-yr adiponectin and leptin for each 1-unit increase in adjusted log CRH
␤-Adjusted log CRH (95% CI)
Adjusted for
1) Gestational week at blood draw
2) 1 ⫹ Child age and sex
3) 2 ⫹ Maternal race/ethnicity and pregnancy induced hypertension
4) 3 ⫹ BMI z-score at age 3
5) 3 ⫹ SS/TR and BMI z-score at age 3
Adiponectin (␮g/ml)
Leptin (ng/ml)
1.15 (0.17–2.13)
1.15 (0.17–2.14)
1.10 (0.06 –2.14)
1.13 (0.09 –2.17)
1.13 (0.10 –2.16)
⫺0.13 (⫺0.44 – 0.19)
⫺0.13 (⫺0.43– 0.18)
⫺0.08 (⫺0.40 – 0.24)
⫺0.04 (⫺0.35– 0.27)
⫺0.03 (⫺0.32– 0.27)
Data are from 349 mother-child pairs from Project Viva. Only 341 subjects had information on SS/TR.
J Clin Endocrinol Metab, April 2009, 94(4):1409 –1415
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A
7
6
Adiponectin (ug/mL)
5
4
3
2
1
0
-1
-2
Caucasian
African/American
Race/Ethnicity
Combined
Caucasian
African/American
Race/Ethnicity
Combined
B7
6
5
Leptin (ng/mL)
4
3
2
1
0
-1
-2
FIG. 1. Relationship between 1 unit increase in maternal log CRH and offspring
3-yr adiponectin (A) and leptin (B) stratified by race/ethnicity and combined.
Adjusted for child age, sex, and pregnancy-induced hypertension. Data are from
349 mother-child pairs in Project Viva.
about 1 ␮g/ml, equivalent to an increment of about 0.2 SD, for
each 1-unit increment of log CRH. This estimate was essentially
unchanged after adjusting for BMI or fat distribution. In addition, we did not find a relationship between maternal levels of
CRH and leptin concentrations at 3 yr, even after adjusting for
BMI or fat distribution.
We are not aware of any previous studies on maternal levels
of CRH and offspring adiponectin, but we are not the first study
to report that adverse fetal influences can lead to increased adiponectin concentrations in the offspring. Lopez-Bermejo et al.
(26) compared 32 small-for-gestational-age (SGA) children with
37 appropriate-for-gestational-age (AGA) children approximately 5 yr after birth and found that the SGA children had
higher adiponectin (18.7 mg/liter) than the AGA children (14.5
mg/liter). Supporting this finding, Evagelidou et al. (27) found
that adiponectin at 6 – 8 yr was higher among 35 children born
SGA compared with 35 children born AGA (13.6 ␮g/ml vs. 10.8
␮g/ml). As expected, in both these studies, the SGA children had
higher insulin resistance than the AGA children (26, 27). Both
these findings and the results of our study seemingly disagree
1413
with the notion that high adiponectin is associated with a
healthy metabolic profile, at least among young children, because being born SGA and fetal glucocorticoid exposure are
both associated with later development of features of the metabolic syndrome (26 –28).
The mechanism underlying the direct association between
maternal levels of CRH and offspring adiponectin is unclear.
Because a detailed metabolic assessment of the children studied
herein had not been performed at 3 yr of age, it remains unknown
whether adiponectin levels predict alterations in metabolic risk.
However, given the insulin-sensitizing properties of adiponectin
(5), it is tempting to speculate that the increase in adiponectin that
we observed is a compensatory response to increased insulin
resistance in the children with high maternal levels of CRH. This
idea was proposed by Evagelidou et al. (27) as a possible explanation of why the SGA children in that study had both higher
adiponectin and more insulin resistance, and this might be a
possible explanation for the current findings as well. Another
possibility is that adiponectin secretion might vary with age.
Adiponectin is secreted mainly by adipose tissue (29), but recent
evidence suggests that other tissues such as bone and skeletal and
cardiac muscle also secrete adiponectin (30 –33). In early childhood, it is possible that these sources may be a more important
source of adiponectin.
The increase in offspring adiponectin for each unit increment
in maternal adjusted log CRH was higher in African-Americans
than in Caucasians, which if confirmed in later studies will support the hypothesis that African-American women are more
sensitive to CRH than Caucasian women. Holzman et al. (34)
reported that even though CRH levels are lower among AfricanAmericans (25), African-Americans who had CRH levels above
1.5 times their group median had an odds ratio for preterm birth
of 5.0 compared with 2.3 for Caucasian women.
At age 3, we did not find any cross-sectional relationships of
blood levels of adiponectin with BMI or central obesity, an association that is also well known in older children and adults (6).
In fact, the relationship between adiponectin and overweight in
young children is still unclear. Studies have shown that cord
blood adiponectin is directly associated with birth weight and
obesity markers such as skin fold measurements in infants (7, 8,
10). However, in the study by Inami et al. (10), this positive
association disappeared when the same children were examined
1 month after birth. Iniguez et al. (9) measured height, weight,
and adiponectin on 85 children at ages 1 and 2 yr and did not find
any cross-sectional associations between adiponectin and BMI at
any of those time points. In a Chinese study of 124 children
between age 2 and 6 yr, Cianflone et al. (11) found that adiponectin was lower among obese than nonobese children
(11.2 ⫾ 3.5 vs. 12.5 ⫾ 4.3 mg/liter, P ⫽ 0.04). However, this
finding was small in magnitude and evident only when all the
children were pooled, but disappeared when they were stratified
by age. Thus, the available literature suggests that the association
between adiponectin and fat mass inverts during early childhood, with a direct association at birth and an inverse association
in later childhood and adulthood. The ratio of sc fat to visceral
fat decreases with age (35), and changes in body fat distribution
might contribute to the change from a direct to an inverse asso-
1414
Fasting et al.
CRH and Offspring Adiponectin and Leptin
ciation with weight. Longitudinal studies in animals have shown
that with increasing age, adiponectin secretion per gram of fat mass
initially increases, before it levels off and then starts decreasing,
possibly reflecting loss of mitochondria from adipocytes (36). The
children in the present study were 3 yr of age, which could be the
time of transition between a direct and an inverse association
between adiponectin and anthropometric measures. This
transition could explain the lack of association between adiponectin and the anthropometric measures at age 3 yr.
We consider maternal blood levels of CRH during pregnancy
to be a proxy for fetal glucocorticoid exposure because of the
special physiological situation in pregnancy and because of support by epidemiological studies. During pregnancy, the fetal
membranes and the placenta release CRH in increasing amounts
from the end of the second trimester until delivery (37). Unlike
the negative feedback loop controlling the cortisol hypothalamus-pituitary-adrenal axis in the nonpregnant state, during
pregnancy, higher levels of cortisol stimulate increased placental
CRH synthesis, resulting in a feed-forward cycle (38). This hypothesis is supported in studies on humans. Sandman et al. (39)
studied 203 pregnant women (54.4% Caucasian) and found that
CRH measured in wk 31 of gestation correlated with maternal
levels of cortisol in blood in wk 15 (r ⫽ 0.487; P ⬍ 0.01) and wk
19 (r ⫽ 0.277; P ⬍ 0.01) but not in wk 25 (r ⫽ 0.078) and wk
31 (r ⫽ ⫺0.026). In another study from the same group, Glynn
et al. (25) studied the correlation of CRH stratified by race/
ethnicity measured in gestational wk 30 –32 with cortisol in gestational wk 18 –20 and found strong positive correlations for
both African-American (r ⫽ 0.38; P ⫽ 0.01) and Hispanic (r ⫽
0.31; P ⫽ 0.01) women but no correlation for non-Hispanic
white women (r ⫽ 0.09; P ⫽ 0.22).
We did not find a relationship between maternal levels of
CRH and offspring leptin levels. This is in line with the lack of
association between maternal levels of CRH and offspring BMI
and the strong correlation between BMI and leptin in this study.
Sugden et al. (17) reported that glucocorticoid exposure in late
pregnancy gave rise to elevated leptin concentrations in adulthood, without concomitant increase in fat mass in rats. However, Sugden et al. studied adult rats exposed to supraphysiological glucocorticoid concentrations in utero, thus making it
difficult to compare their study with ours. Leptin secretion in
humans follows a pulsatile and diurnal pattern with peak secretion during the night during sleep (40). This pattern of secretion
is different from rats, where leptin is elevated during feeding and
activity (41), which might make comparison between rats and
humans more difficult.
Somewhat surprisingly, we found a weaker association between maternal CRH and offspring measures of obesity than we
did previously (3), but there was a trend in the same direction.
The women included in the previous study were sampled on the
basis of high risk for preterm birth or depression (3) and might
be somewhat different from the women included in the current
study.
We were able to evaluate a large number of potential confounders, which makes it unlikely that the association between
maternal levels of CRH and offspring adiponectin was due to
confounding. In addition, the information was collected pro-
J Clin Endocrinol Metab, April 2009, 94(4):1409 –1415
spectively, and the eligible population was largely similar to the
total study population, suggesting that this result was not due to
bias. We cannot rule out that the results for adiponectin are due
to chance. Another possible limitation of this study is that we
measured only total adiponectin, whereas recent evidence suggests that the high-molecular-weight tetramer of adiponectin
might be the active form (42). However, most of the studies
showing an association of adiponectin with the metabolic syndrome have used total adiponectin (6, 27, 43). The small proportion of subjects in the original study eligible for these analyses
could incur a loss of generalizability. In addition, with this small
number of subjects, we could have missed a small association
between maternal CRH and offspring leptin levels. However,
due to the symmetrical and narrow confidence interval, we find
a large, relevant change in leptin unlikely.
Conclusions
In this study, we found that elevated maternal CRH in
pregnancy was associated with increased adiponectin and unchanged leptin levels at 3 yr of age. We did not find a crosssectional association between adiponectin and any of the adiposity measures with which it is known to be associated in
adulthood. In early childhood, adiponectin may play an important role in establishing a favorable metabolic milieu,
which protects against obesity-associated comorbidities.
However, longitudinal studies with longer duration of follow-up and markers of the metabolic syndrome will be needed
to explore the changing role of adiponectin from birth
throughout childhood.
Acknowledgments
Address all correspondence and requests for reprints to: Magnus H.
Fasting, Medisinsk Teknisk Forskningssenter, 7489 Trondheim, Norway.
E-mail: [email protected].
Project Viva is supported by grants from the National Institutes of
Health (HD 34568, HL 64925, HL 68041) and by Harvard Medical
School and the Harvard Pilgrim Health Care Foundation.
Disclosure Summary: M.H.F. was supported by a grant from the Joh.
H. Andresen research fund and the Norwegian Research Council. The
other authors have nothing to disclose.
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