CLINICAL RESEARCH ARTICLE
Dysregulation of Placental miRNA in Maternal Obesity Is
Associated With Pre- and Postnatal Growth
Gemma Carreras-Badosa,
1
Alexandra Bonmat
´
ı,
2
Francisco-Jose Ortega,
3
Josep-Maria Mercader,
4
Marta Guindo-Mart
´
ınez,
4
David Torrents,
4,5
Anna Prats-Puig,
6
Jose-Maria Martinez-Calcerrada,
7
Francis de Zegher,
8
Lourdes Ib ´a
~
nez,
9,10
Jose-Manuel Fernandez-Real,
3
Abel Lopez-Bermejo,
1
and Judit Bassols
1
1
Pediatric Endocrinology Group, Girona Biomedical Research Institute (IDIBGI), Dr. Trueta University
Hospital, Girona 17007, Spain;
2
Department of Gynecology, Dr. Trueta University Hospital, Girona
17007, Spain;
3
Diabetes, Endocrinology and Nutrition Group, Girona Biomedical Research Institute (IDIBGI),
Dr. Trueta University Hospital, Centro de Investigaci ´on Biom ´edica en Red-Fisiopatolog
´
ıa de la Obesidad y
Nutrici ´on (CIBERobn), Girona 17007, Spain;
4
Joint Barcelona Supercomputing Center, Centre for Genomic
Regulation, Institute for Research in Biomedicine (BSC-CRG-IRB) Research Program in Computational
Biology, Barcelona Supercomputing Center, Barcelona 08028, Spain;
5
Instituci ´o Catalana de Recerca i
Estudis Avançats, 08010 Barcelona, Spain;
6
Department of Physical Therapy, Escola Universit `aria de la Salut
il’Esport, University of Girona, 17007 Girona, Spain;
7
Institute of Legal Medicine of Catalonia, 17001
Girona, Spain;
8
Department of Development and Regeneration, University of Leuven, 3000 Leuven, Belgium;
9
Endocrinology, Hospital Sant Joan de D´eu, University of Barcelona, 08950 Esplugues, Barcelona; and
10
Centro de Investigaci ´on Biom ´edica en Red de Diabetes y Enfermedades Metab ´olicas Asociadas
(CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28220 Madrid, Spain
Context: Human placenta exhibits a specific microRNA (miRNA) expression pattern. Some of these
miRNAs are dysregulated in pregnancy disorders such as preeclampsia and intrauterine growth
restriction and are potential biomarkers for these pathologies.
Objective: To study the placental miRNA profile in pregnant women with pregestational
overweight/obesity (preOB) or gestational obesity (gestOB) and explore the associations between
placental miRNAs dysregulated in maternal obesity and prenatal and postnatal growth.
Methods: TaqMan Low Density Arrays and real-time polymerase chain reaction were used to profile
the placental miRNAs in 70 pregnant women (20 preOB, 25 gestOB, and 25 control). Placentas and
newborns were weighed at delivery, and infants were weighed at 1, 4, and 12 months of age.
Results: Eight miRNAs were decreased in placentas from preOB or gestOB (miR-100, miR-1269, miR-
1285, miR-181, miR-185, miR-214, miR-296, and miR-487) (all P , 0.05). Among them, miR-100, miR-
1285, miR-296, and miR-487 were associated with maternal metabolic parameters (all P , 0.05) and
were predictors of lower birth weight (all P , 0.05; R
2
. 30%) and increased postnatal weight gain
(all P , 0.05; R
2
. 20%). In silico analysis showed that these miRNAs were related to cell proliferation
and insulin signaling pathways. miR-296 was also present in plasma samples and associated with
placental expression and prenatal and postnatal growth parameters (all P , 0.05).
Conclusions: We identified a specific placental miRNA profile in maternal obesity. Placental miRNAs
dysregulated in maternal obesity may be involved in mediation of growth-promoting effects of
maternal obesity on offspring and could be used as early markers of prenatal and postnatal growth.
(J Clin Endocrinol Metab 102: 2584–2594, 2017)
ISSN Print 0021-972X ISSN Online 1945-7197
Printed in USA
Copyright © 2017 Endocrine Society
Received 10 January 2017. Accepted 15 March 2017.
First Published Online 20 March 2017
Abbreviations: BMI, body mass index; gestOB, gestational obesity; HDL, high-density
lipoprotein; HMW, high molecular weight; HOMA-IR, homeostasis model for assessment
of insulin resistance; miRNA, microRNA; PCR, polymerase chain reaction; pregestBMI,
pregestational body mass index; preOB, pregestational overweight/obesity; RT, real time;
SDS, standard deviation score.
2584 https://academic.oup.com/jcem J Clin Endocrinol Metab, July 2017, 102(7):2584–2594 doi: 10.1210/jc.2017-00089
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F
etal development represents a critical period during
which perturbations to the intrauterine environment
as a result of various factors in the extrauterine envi-
ronment can have major effects, not only on the proper
growth and development of the fetus, but also on disease
risk later in life (1). One of the most common pertur-
bations during pregnancy is obesity.
Pregnancy in obese moth ers generat es an adverse in-
trauterine environment that causes a proinflammatory
milieu and a number of metabolic derangements. Obesity
influences the outcome of pregnancy per se, because it
is associated with hypertensive disorders, gestational dia-
betes, and thromboembolic events (2). In addition, maternal
obesity affects the fetus and newborn, resulting in large-for-
gestational-age and intrauterine growth–restricted infants,
and leads to subsequent complications in later life, includ-
ing obesity, cardiovascular disease, and diabetes as a result
of fetal programming (3).
Development of the human placenta is critical for em-
bryonic development and successful pregnancy. The pla-
centa serves the bidirectional connection between the mother
and the fetus and facilitates the exchange of nutrients, re-
spiratory gases, and waste products during pregnancy. It
is also an endocrine organ that produces hormones and
growth factors that are crucial for embryonic development
(4). The mechanisms by which in utero exposures may alter
the regulatory mechanisms of the placenta continue to be
studied. One mode of alteration may be through the aber-
rant expression of microRNAs (miRNAs). Alterations in
placental miRNA expression have been associated with
adverse pregnancy outcomes, including preeclampsia and
intrauterine growth restriction (5–12). No studies have been
performed in pregnancies with maternal obesity.
We aimed to study the placental miRNA profile in
pregnant women with prepregnancy overweight/obesity
(preOB) and gestational obesity (gestOB), and explore
the associations between placental miRNAs dysregulated
in maternal obesity and prenatal and postnatal growth.
Material and Methods
Subjects and study approval
The study population consisted of 70 pregnant white women
with uncomplicated pregnancies (other than pregestational
obesity or gestOB) delivering appropriate-for-gestational-age
term infants (gestational age between 37 and 42 weeks). Sub-
jects were consecutively recruited among those seen within a
setting of prenatal primary care in Girona (Spain). Women with
multiple pregnancies, gestational diabetes, preeclampsia, fetal
malformations, or asphyxia or drug use were excluded. Women
were grouped according to their pregestational body mass index
(pregestBMI) and their pregnancy weight gain into: (1) control
(pregestBMI, .18.5 and ,24.9; pregnancy weight gain, .11.5 kg
and ,16 kg); (2) preOB (pregestBMI, .25; pregnancy weight
gain, .7kgand,11.5 kg); and (3) gestOB (pregestBMI, .18. 5
and ,24.9; pregnancy weight gain, .16 kg), as previously de-
scribed by the Institute of Medicine (13). The protocol was ap-
proved by the Institutional Review Board of Dr. Josep Trueta
Hospital. Informed written consen t was obtained from the
women.
Clinical assessments
A close prenatal follow-up, consisting of clinical exams
according to standardized protocols, ultrasonograms, and
laboratory tests (urine and blood), was performed in all sub-
jects. Information on maternal pregnancy characteristics was
abstracted from standardized medical records. PregestBMI was
calculated as weight divided by height squared (kg/m
2
).
Newborns were weighed and measured after delivery using
a calibrated scale for weight and a measuring board for length.
Infants were followed for weight and length measurements at
1, 4 and 12 months of age.
The placentas were collected immediately after childbirth in
the delivery room or operating room to ensure sterility and
speed. Placentas were weighed and three, 1 cm
3
cuboidal sec-
tions were collected from the inner surface of the placenta
(maternal side) after removing the decidua layer, and thus
contained placental villous tissue. The samples were preserved
in RNA later and stored at –80°C until miRNA extraction. The
personnel handling the placenta and samples wore facial masks
and sterile gloves and used a sterile scalpel and instruments.
Analytical methods
Blood tests were performed under fasting conditions in all
womenbetween24and32weeksofgestation.Serumglucosewas
analyzed by the hexokinase method. Serum immunoreactive in-
sulin was measured by immunochemiluminescence (Immulite
2000; Diagnostic Products, Los Angeles, CA). Fasting insulin
sensitivity was estimated using the following formula: homeostasis
model for assessment of insulin resistance (HOMA-IR) = (fasting
insulin in mU/L) 3 (fasting glucose in mM) / 22.5. Glycosylated
hemoglobin was measured by high-performance liquid chroma-
tography (Bio-Rad, Muenchen, Germany) and a Jokoh HS-10
autoanalyzer (Bio-Rad). Serum C-peptide was measured by
immunochemiluminescence (IMMULITE 2000; Diagnostic
Products). Total serum triacylglycerol was measured by moni-
toring the reaction of glycerol-phosphate oxidase and peroxidase.
High-density lipoprotein (HDL) cholesterol was quantified by the
homogeneous method of selective detergent with accelerator.
Analysis of placental miRNAs
Placental miRNA extraction and reverse transcription
Total RNA (including miRNAs) was isolated from placental
samples with the mRNAeasy mini Kit (Qiagen, Madrid, Spain).
The quantity of isolated RNA was determined with a Nanodrop
ND-1000 spectrophotometer (Nanodrop Technologies, Wilmington,
DE), and the integrity of each RNA sample was checked with an
Agilent Bioanalyzer (Agilent Technologies, Palo Alto, CA). RNA
was reverse transcribed using TaqMan MicroRNA Reverse
Transcription Kit and Megaplex RT primers (human pool sets
A and B) (Applied Biosystems, Foster City, CA).
Placental miRNA profiling
We studied the placental miRNA profiles in 18 pregnant
women (six preOB, six gestOB, and six control) who were
randomly selected from the studied subjects. The sampling
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method was designed to ensure that the sample would be
representative of the study subjects, taking into account ma-
ternal BMI, age, and sex of the newborn. A TaqMan Array
Human MicroRNA Card Set (version 3.0; Applied Biosystems)
that enables accurate quantification of 723 human miRNAs was
used. Real-time polymerase chain rea ction (RT-PCR) was carried
out on an Applied BioSystems 7900HT thermocycler. Data were
analyzed with Sequence Detection Systems Relative Quantification
Software version 2.2.2 (Applied Biosystems ) and the R package SL
qpcrNorm (Bioconductor; https://www.bioconductor.org). The
placental miRNA profile was compared with the specific second-
trimester plasma profile that we previously described in the same
cohort using the same methodology (14).
Analysis of individual miRNAs
Individual TaqMan MicroRNA Assays (Applied Biosystems)
were used to study the presence of placental miRNA candidates
in the studied subjects: 70 pregnant women (20 with preOB, 25
with gestOB, and 25 women with normal pregnancies), in-
cluding the subjects previously studied to determine the miRNA
profile. Gene expression was assessed by RT-PCR using the
LightCycler 480 Real-Time PCR System (Roche Diagnostics, Indi-
anapolis, IN), as previously described (14). We performed DCt
normalization as implemented in the HTqPCR package (Bio-
conductor; https://www.bioconductor.org), using the three most
stable (rank-invariant) miRNAs in placenta (pool A: miR-52 3, miR-
532, miR-425-5p; pool B: miR-30e-3p, miR-519b-3p, miR-520d-
3p) as reference. Relative miRNA levels were calculated accord ing
to the 2
-DCt
method.
miRNA target prediction
Pathways targeted by our candidate miRNAs were predicted
using the Web-based tool, miRSystem (15). miRSystem in-
tegrates several databases (Kegg, Biocarta, Pathway Interac-
tion Database, Reactome, and GO molecular function; http://
mirsystem.cgm.ntu.edu.tw/) to enable prediction of gene targets
and targeted pathways.
Statistical analysis
Results are expressed as mean 6 standard error of the mean.
Nonparametric variables were logarithmically transformed to
improve symmetry. Unpaired t test or one-way analysis of vari-
ance were used to study differences in continuous variables among
groups. The relation between variables was analyzed by simple
correlation followed by multiple regression analysis in a stepwise
manner. Significance level was set at P , 0.05. Data analyses were
performed with SPSS (v. 22.0; SPSS, Chicago, IL) and R (http://
www.r-project.org/) statistic al softwa re. The SL qPCRNorm
Package (Bioconductor; https://www.bioconductor.org)wasalso
used for the analysis and normalization of miRNA data (16).
Results
Placental miRNA profile
From the 723 human miRNAs screened by TaqMan
Low Density Arrays (TLDAs; specifically, the TaqMan
Array Human MicroRNA), 486 miRNAs were expressed
in the human placentas used in this study, which were cat-
egorized into three study groups, namely, normal placentas
(control), placentas from women with gestOB, and placentas
from women with preOB.
We first focused on the abundance of the miRNAs. miR-
517-3p, miR-1274b, miR-1243, miR-24-3p, miR-517c-3p,
miR-888-5p, miR-545-5p, miR-30 2a-3p, miR-126-3p, and
miR-223-3p were the 10 most abundant miRNAs in control
placentas. All of these miRNAs were also highly expressed
in preOB and gestOB placentas. miR-517-3p, miR-1274b,
miR-1243, miR-24-3p, and miR-517c-3p were the most
abundantly expressed in both groups. All of these miRNAs
were present in second-trimester plasma from all subjects,
except for miR-888, which was only present in the control
group, and miR-1274b and miR-545-5p, which were not
present in any of the studied groups. miR-1243 and miR-
223-3p were highly expressed in the second-trimester
plasma of all studied groups (Supplemental Table 1).
With respect to the chromosomal distribution, the
miRNAs found to be expressed in these placenta s were
located on all chromosomes except the Y chromosom e.
The predominant miRNAs were derived from chromo-
some 19 (about 15%), followed by chromosome 14 (about
11%) and chromosome X (about 11%).
We next directed our attention to the miRNAs expressed
in the different placental groups (Fig. 1; Supplemental
Table 2). Four hundred and four miRNAs were detected in
all studied groups. Fourteen miRNAs were only expressed
in control placentas; 15 miRNAs were only expressed in
placentas from gestOB subjects, and 13 miRNAs were only
expressed in placentas from preOB subjects. The majority
of the miRNAs were placental-specific miRNAs and were
not present in second-trimester plasma samples, except for
miR144-3p, which was highly expressed in p lacentas from
preOB subjects.
Figure 1. Venn diagram showing placental miRNA expression in
preOB, gestOB, and normal pregnancies (control).
2586 Carreras-Badosa et al Placental miRNA and Pre/Postnatal Growth J Clin Endocrinol Metab, July 2017, 102(7):2584–2594
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Differential miRNAs in maternal obesity
Among the 404 miR NAs detected in all studied
groups, we focused on 18 miRNAs which were up- or
downregulated by at least twofold in placentas from
preOB an d gestOB women compared with control sub-
jects (miR-100, miR-1269, miR-1271, miR-1285, miR-
181, miR-185, miR-19 1, miR-214, miR-23, miR-27,
miR-29, miR-296, miR-337, miR-339, miR-365, miR-
483, miR-487, and miR-520h). These 18 miRNAs were
chosen as candidates for miRNAs differentially regulated
by maternal obesity and were validated by RT-PCR in a
wider population consisting of 70 pregnant women (20
preOB, 25 gestOB, and 25 control) (Table 1).
Eight of the 18 miRNAs were confirmed to be dif-
ferentially expressed between placentas from women
with normal pregnancies and obese women. Among
them, miR-100, miR-185, and miR-487 were decreased
in gestOB compared with control, and miR-1269, miR-
1285, miR-181, miR-214, and miR-296 were decreased
in both preOB and gestOB compared with control (all
P , 0.03) (Table 1; Fig. 2).
Association with maternal metabolic parameters
Several of the placental miRNAs dysregulated in
maternal obesity were associated with maternal metabolic
parameters including decreased BMI, HOMA-IR, and
C-peptide and increased high-molecular-weight (HMW)
adiponectin and HDL cholesterol (Table 2). Significant
associations, after correcting for multiple comparisons,
included the association of miR-1269 with HMW adi-
ponectin, and miR-296 with HMW adiponectin and
HOMA-IR (all P # 0.006; Table 2). These associations
remained significant in multiple regression analysis ad-
justing for confounding variables including gestational
age, maternal age, pregestational BMI, maternal weight
gain, and sex of the newborn (Table 3).
Association with growth parameters
Some of the placental miRNAs dysregulated in maternal
obesity were also significantly associated with growth pa-
rameters at birth and thereafter during the 12 months of
follow-up, including negative associations with placental
weight, birth weight standard deviation score (SDS), and
birth length SDS, and positive associations with weight gain
SDS at 1, 4, and 1 2 months of age (Table 2; Supplemental
Figs. 1–2). Significant associations after correcting for
multiple comparisons include the association of miR-100,
miR-1285, and miR-487 with birth weight SDS and miR-
296 with birth weight SDS and increased weight gain SDS
at 4 and 12 months of age (all P # 0.006; Table 2).
In multiple regression analysis, miR-487 was an in-
dependent predictor of placental weight and explained
13% of its variance. miR-100, miR-1285, miR-296, and
miR-487 were independent predictors of birth weight an d
explained nearly 30% of its variance. miR-100, miR-1285,
and miR-487 were independent predictors of birth length
and explained nearly 30% of its variance. miR-100, miR-
1285, and miR-487 were independent predictors of weight
gain in the first month of life and explained nearly 15% of
its variance. miR-100, miR-296, and miR-487 were in-
dependent predictors of weight gain at 4 and 12 months
of age and explained nearly 20% of its variance (Table 3).
Predicted miRNA pathways
Given the association of miR-100, miR-1285, miR-296,
and miR-487 with growth parameters, we conducted an in
silico analysis to ascertain their associated pathways and
whether common mRNA targets were shared to a signifi-
cant extent by these miRNAs. Predictors using miRSystem
indicated that, excluding pathways in cancer, these four
miRNAs shared targets related to WNT, MAPK, mTOR,
and insulin/IGF-1 signaling pathways (Table 4).
Placenta-specific miRNAs in maternal plasma
Finally, we assessed the circulating levels of our pla-
cental, obesity-associated miRNAs in second-trimester, cell-
free maternal plasma of the studied subjects by quantitative
PCR. miR-100, miR-1269a, miR-1271, miR-1285, miR-
181a, and miR-27a were not expressed in plasma samples.
miR-23b and miR-483 were only expressed in controls.
Among the miRNAs expressed in plasma, miR-296
was decreased in preOB and gestOB compared with
control subjects (P = 0.001 and P = 0.04), and miR-520h
was increased in both groups compared with control
subjects (P
= 0.01 and P = 0.004).
Circulating miR-296 in second-trimester plasma was as-
sociated with placental miR-296 (r = 0.310; P = 0.008),
placental weight (r = 20.258; P = 0.03), birth weight SDS
(r = 20.297; P = 0.01), birth length SDS (r = 20.315; P =
0.008), and weight gain SDS at 12 months of age (r = 0.325;
P = 0.01). These associations with placental weight (b =
20.260; P = 0.03), bir th weight (b = 20.252; P = 0.03), birth
length (b = 20.326; P = 0.006), and weight gain at 12 months
(b = 0.206; P = 0.02) were maintained in multivariate analysis
after adjusting for maternal and newborn parameters.
Discussion
We have described the s pecific placental miRNA profile in
pregestational and gestOB and have shown how a number
of miRNAs dysregulated in maternal obesity (miR-100,
miR-1285, miR-296, and miR487) were predictors of de-
creased birth weight and increased weight gain at 1, 4, and/
or 12 months of life, independently of maternal obesity.
miRNA expression profiling of the human placenta
by TLDAs
To date, more than 500 miRNAs have been reported
to be expressed by the human placenta. We detected 486
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Table 1. Clinical Characteristics of Pregnant Women Enrolled in the Study
Control (n = 25) PreOB (n = 20) GestOB (n = 25) P
Mother
Age, y 30 6 1316 1306 1NS
Pregestational BMI, kg/m
2
22 6 0.2 29 6 0.2
a,b
22 6 0.3 ,0.001
Delivery BMI, kg/m
2
27 6 0.3 33 6 0.6
a,b
30 6 0.4
a
,0.001
Weight gain, kg 12 6 0.5 8 6 0.5
a,b
22 6 1
a
,0.001
Preload glucose, mg/dL 78 6 1846 1796 1NS
Postload glucose, mg/dL 125 6 5 131 6 6 116 6 6 0.005
HbA1c, % 4.9 6 0.1 5.1 6 0.1 5.0 6 0.7 NS
Insulin, mIU/L 4.7 6 1.1 8.3 6 1.5 6.3 6 0.8 NS
HOMA-IR 0.9 6 0.2 1.7 6 0.3 1.2 6 0.2 NS
C-peptide, ng/mL 1.4 6 0.1 2.2 6 0.1
a,c
1.7 6 0.1 ,0.001
TG, mg/dL 143 6 7 196 6 13 167 6 18 NS
HDL-c, mg/dL 72 6 2706 2716 3NS
HMW adiponectin, mg/L 6.8 6 2.6 4.8 6 2.8
d
6.6 6 4.9 0.01
Newborn and placenta
Sex, % female 42.3 45.5 46.7 NS
Gestational age, wk 40 6 0.1 40 6 0.1 40 6 0.1 NS
Birth weight, g 3272 6 37 3441 6 65
d
3492 6 75 0.03
Birth weight SDS, z-score 20.07 6 0.1 0.3 6 0.2
d
0.5 6 0.2 0.02
Birth length, cm 49 6 0.2 50 6 0.4 50 6 0.3 NS
Birth length SDS, z-score 20.35 6 0.1 0.13 6 0.2 0.15 6 0.2 NS
Placental weight, g 576 6 16 650 6 20 642 6 29 NS
Weight at 1 mo, kg 4.3 6 0.1 4.2 6 0.1 4.3 6 0.1 NS
Increment weight at 1 mo, g 1.0 6 0.1 0.8 6 0.1 0.8 6 0.1 0.03
Increment weight 1 mo SDS, z-score 0.38 6 0.77 20.12 6 0.86 20.06 6 0.74 NS
Weight at 4 mo, kg 6.7 6 0.1 6.5 6 0.1 6.9 6 0.2 NS
Increment weight at 4 mo, g 3.5 6 0.1 3.1 6 0.1 3.5 6 0.2 NS
Increment weight at 4 mo SDS, z-score 0.13 6 1.02 20.43 6 0.78 0.11 6 1.4 NS
Weight at 12 mo, kg 9.8 6 0.2 9.3 6 0.2 9.8 6 0.2 NS
Increment weight at 12 mo, g 6.6 6 0.2 5.9 6 0.2 6.4 6 0.2 NS
Increment weight at 12 mo SDS, z-score 0.29 6 1.15 20.44 6 0.67 20.01 6 1.18 NS
miRNAs
miR-100-3p 0.01
6 0.01 0.01 6 0.01 0.007 6 0.007
d
0.04
miR-1269a 0.05 6 0.06 0.01 6 0.01
d
0.02 6 0.03
d
0.005
miR-1271-5p 0.01 6 0.01 0.009 6 0.005 0.010 6 0.009 NS
miR-1285-3p 0.18 6 0.19 0.06 6 0.05
a
0.08 6 0.05
d
0.002
miR-181a-3p 0.03 6 0.02 0.02 6 0.01
d
0.02 6 0.01
d
0.01
miR-185-5p 0.55 6 0.30 0.44 6 0.40 0.35 6 0.22
d
0.008
miR-191-3p 0.01 6 0.01 0.01 6 0.01 0.01 6 0.01 NS
miR-214-3p 5.51 6 4.41 3.12 6 1.89
d
2.92 6 2.23
d
0.002
miR-23b-3p 0.42 6 0.26 0.32 6 0.21 0.31 6 0.30 NS
miR-27a-5p 0.03 6 0.01 0.02 6 0.01 0.03 6 0.02 NS
miR-29b-3p 0.02 6 0.01 0.03 6 0.03 0.03 6 0.03 NS
miR-296-5p 0.03 6 0.01 0.02 6 0.01
d
0.02 6 0.01
d
0.04
miR-337-5p 0.24 6 0.10 0.23 6 0.18 0.21 6 0.13 NS
miR-339-5p 0.11 6 0.05 0.11 6 0.07 0.11 6 0.08 NS
miR-365a-3p 0.50 6 0.34 0.49 6 0.35 0.63 6 0.54 NS
miR-483-3p 0.03 6 0.07 0.05 6 0.03 0.08 6 0.17 NS
miR-487a-3p 0.41 6 0.43 0.30 6 0.18 0.22 6 0.13
d
0.04
miR-520h 2.29 6 1.57 1.74 6 0.94 1.99 6 1.21 NS
Data are shown as mean 6 standard error of the mean. miRNA values were obtained by quantitative PCR and are shown as relative expression (2
-DCt
).
Abbreviations: HDL-c, HDL cholesterol; TG, triglycerides.
a
P # 0.005 vs control subjects.
b
P # 0.005 vs gestOB subjects.
c
P # 0.05 vs gestOB subjects.
d
P # 0.05 vs control subjects.
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