Is the low AMH level associated with the risk of cardiovascular disease in obese pregnants?

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Is the low AMH level associated with the risk of

cardiovascular disease in obese pregnants?

Başak Güler, Sibel Özler, Nezaket Kadıoğlu, Eda Özkan, Merve Sibel

Güngören & Şevki Çelen

To cite this article:

Başak Güler, Sibel Özler, Nezaket Kadıoğlu, Eda Özkan, Merve Sibel

Güngören & Şevki Çelen (2020) Is the low AMH level associated with the risk of cardiovascular

disease in obese pregnants?, Journal of Obstetrics and Gynaecology, 40:7, 912-917, DOI:

10.1080/01443615.2019.1672633

To link to this article: https://doi.org/10.1080/01443615.2019.1672633

Published online: 06 Dec 2019.

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ORIGINAL ARTICLE

Is the low AMH level associated with the risk of cardiovascular disease in

obese pregnants?

Bas¸ak G€uler

, Sibel €

Ozler

, Nezaket Kad

ıoglu

, Eda €

Ozkan

, Merve Sibel G€ung€oren

and S¸evki C¸elen

a

Department of Health Science, Istinye University, Istanbul, Turkey;

Department of Perinatology, Selc¸uk University Medical School, Konya,

Turkey;

Department of Obstetr

ıcs and Gynecology in Liv Hospital, Ankara, Turkey;

Department of Obstetr

ıcs and Gynecology, €Oztan

Hospital, Usak, Turkey;

Department of Clinical Biochemistry, Duzen Laboratory, Ankara, Turkey;

Department of Perinatology, Zekai Tahir

Burak Women

’s Health Education and Research Hospital, Ankara, Turkey

ABSTRACT

Our aim was to investigate whether Antimullerian Hormone (AMH), complete blood count (CBC),

Homeostasis model assessment (HOMA-IR), systolic blood pressure (SBP), diastolic blood pressure (DBP),

and weight gain have any diagnostic value for the prediction of cardiovascular disease (CVD) in obese

and non-obese pregnant patients. A prospective, case-control study was carried out, including 187

patients (93 obese, and 94 non-obese). CVD risk for each patient was evaluated according to the

American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/

AHA). A multivariate logistic regression model was used to identify the independent risk factors of CVD

in obese and non-obese patients. The obese patients had significantly lower levels of AMH when

com-pared to the non-obese ones (

p ¼ .002). Insulin, HOMA-IR, HbA1c, and SBP were significantly higher in

obese patients than non-obese ones (

p < .001, p < .001 and p ¼ .001, respectively). Age, SBP, and

decreased AMH levels had significantly associated with risk factors of CVD in the obese group

(

p ¼ .001, p ¼ .002, and p ¼ .049, respectively). Our study suggests that decreased AMH levels, increased

age, and SBP are associated with CVD in obese patients. AMH may be used to evaluate CVD risk in

advanced aged, obese patients.

IMPACT STATEMENT

 What is already known on this subject? Obesity is one of the most common medical

complica-tions of pregnancy. Obesity increases maternal complicacomplica-tions such as preeclampsia, caesarean rate,

cardiovascular disease, obesity, and diabetes after pregnancy; and neonatal complications including

macrosomia, hypoglycaemia, hyperbilirubinemia, delivery trauma, shoulder dystocia, and

adult-onset obesity, and diabetes. Obese patients have lower serum AMH levels.

 What the results of this study add? A significant relationship between AMH levels and CVD risk

in obese pregnant women was observed.

 What are the implications of these findings for clinical practice and/or further research?

Based on this finding, we concluded that decreased AMH levels are predictive for CVD in obese

pregnant women.

KEYWORDS

Antimullerian hormone; obese pregnant; cardiovascular disease risk

Introduction

Obesity is a global disease, currently increasing in both

devel-oping and developed countries (Okorodudu et al.

2010

;

NCD-RisC

2017

). World Health Organisation (WHO) stated that 40%

of women, who are older than 18 years of age, are

over-weight, and prevalence of obesity has increased three times

from the year 1975 to 2016 (Ricci et al.

2018

). Obesity is

cor-related with many diseases having high morbidity, like

car-diovascular disease (CVD) and diabetes. Maternal obesity is

associated with serious morbidity and mortality of both the

mother and the foetus (Hochner et al.

2012

; Jornayvaz et al.

2016

). It is associated with increased risk of preeclampsia,

gestational diabetes, thromboembolism and caesarean

deliv-ery (Shaikh et al.

2010

) in the mother; and related to foetal

macrosomia, and preterm delivery (Li et al.

2013

). In the long

term, it has been shown to have long-term effects on the

foetus like CVD, diabetes, metabolic syndrome,

atheroscler-osis, and cancer (Matsuda and Shimomura

2013

). Obesity

itself is a major risk factor for hypertension, diabetes,

dyslipi-demia, hypercholesterolaemia, low high-density lipoprotein

(HDL) level, and smoking, which are the risk factors for CVD

(AHA

2005

). Gestational hypertension and preeclampsia,

which increase the CVD risk in pregnancy, may cause

mater-nal mortality (Say et al.

2014

).

Antimullerian hormone (AMH) is a glycoprotein member

of transforming growth factor-beta superfamily; and is

secreted by the granulosa cells of the ovarian follicles

(Fanchin et al.

2003

; Weenen et al.

2004

). Its levels decrease

with ovarian aging. Recent studies show that AMH has effects

on cardiovascular function, and is a potential risk factor for

CONTACTSibel Ozler sibel2ozler@gmail.com Department of Perinatology, Konya Education and Research Hospital, Konya, Turkey.

ß 2019 Informa UK Limited, trading as Taylor & Francis Group

2020, VOL. 40, NO. 7, 912_–917

CVD (Yarde et al.

2014

; de Kat et al.

2016

). It was shown that

AMH levels did not change during pregnancy and

pre-pregnancy periods (La Marca et al.

2005

). Nelson et al. (

2010

)

observed that AMH levels are decreased in all stages of

preg-nancy. Besides, Tokmak et al. (2014) reported that AMH was

significantly low in patients having preeclampsia when they

were compared to healthy controls; but it was not associated

with adverse pregnancy outcome. Similarly, Shand et al.

(

2014

) showed that women having very low levels of AMH in

early stages of their pregnancies, had increased risk for

hypertensive diseases of pregnancy; but they could not

observe a significant relation between AMH concentrations

and adverse neonatal or maternal outcomes.

As far as our knowledge, there has not been any study

investigating the relation of AMH levels and CVD in obese

pregnant patients. We aimed to study this relation in obese

and non- obese pregnant patients, and also observe if there

was any direct effect of AMH on CVD.

Materials and methods

A total of 187 patients were recruited consecutively from the

outpatient antenatal clinic of our hospital. Body mass index

(BMI), was calculated by dividing weight (kg) by the square

of height (m). The patients having BMI less than 18.5 kg/m

were categorised as underweight, the ones having BMI

between 18.5 and 24.9 kg/m

were normal- weight group,

the ones having BMI between 25 and 29.9 kg/m

were

over-weight; and the ones having BMI between 30 and 39.9 kg/m

were obese (Rasmussen and Yaktine

2009

). Ninety-four

preg-nant patients having pre-pregnancy BMI

<30 kg/m

were

non- obese; and 93 patients who had pre-pregnancy BMI

30 kg/m

_{were obese.}

Exclusion criteria for all participants included; multiple

pregnancies, foetal chromosomal aneuploidy and/or

malfor-mations, type I or II diabetes mellitus, chronic hypertension,

having previous history for polycystic ovary syndrome or

pre-mature ovarian failure, conceiving by assisted reproductive

techniques, use of aspirin or unfractionated heparin, CVD,

autoimmune disorders, hyper/hypothyroidism, chronic liver or

renal disease, having smoking and alcohol consumption,

pre-vious history of obesity surgery, disorders of lipid

metabol-ism, and use of medication for it, insulin resistance, and use

of metformin.

Patients, whose ages were in between 18 and 35, a

deliv-ery week more than 37th week, BMI in between 18.5 and 40,

and 50-g OGTT results were less than 140 mg/dL were

included in the study.

All the patients were homogenised for their ages in obese

and non- obese groups. The weights and heights of all

patients were recorded at the beginning of the study. The

single specialist evaluated the patients by ultrasonography

and recorded the measurements.

All participants provided written informed consent. The

study protocol was performed according to the principles of

the Declaration of Helsinki and approved by the Instructional

Review Board of our hospital.

The venous blood samples of the patients were taken

after 6 h of fasting in the outpatient clinic and centrifuged in

at most 1 h, in 5000 cycles, and for 10 min. The serum was

stored in

80 degrees Celcius after centrifugation, till the

end of the sample collection. All the patients were sampled

for fasting blood glucose, insulin, glycosylated haemoglobin

(HbA1c) [withUniCelDxI 800 Immunoassay System (Beckman

Coulter, Fullerton, CA, USA)], total cholesterol, low-density

cholesterol

(LDL),

HDL

[with

AU680

Chemistry

System

(Beckman Coulter)], and complete blood count (CBC)

parame-ters were measured by automated blood counter Cell-Dyn

3700 automated haemocytometer (Abbott, IL, USA)

simultan-eously. Systolic blood pressure (SBP) and diastolic blood

pres-sure (DBP) were meapres-sured for all of the patients, after at

least 15 min of resting. The results were recorded in

milli-meter-mercury (mm-Hg). The homeostasis model assessment

of insulin resistance (HOMA-IR) (insulin

 glycaemia in (mmol/

L)/22.5) was estimated.

The AMH levels were analysed using human AMH

enzyme-linked immunosorbent assay (ELISA) kit (Hangzhou

Eastbiopharm Co., Ltd.) with immunoassay (Immulite 2000)

device and presented in ng/mL.

We calculated the cardiovascular risk for each patient

according to the American College of Cardiology/American

Heart Association Task Force on Practice Guidelines (ACC/

AHA) risk score calculation (Goff et al.

2014

).

Statistical analysis

Data analysis was performed by using SPSS for Windows,

ver-sion 22 (SPSS Inc., Chicago, IL, United States). Whether the

distributions of continuous variables were normally or not

was determined by Kolmogorov Smirnov test, homogeneity

of variances was evaluated by the Levene test. Continuous

variables were shown as mean ± standard deviation (SD),

where applicable. While Student

’s t-test compared the mean

differences

between

obese

and

non-obese

groups.

Determining the best predictors which discriminate groups

from each other was analysed by Multiple Logistic Regression

analysis, where applicable. Any variable whose univariable

test had a

p-value < .05 was accepted as a candidate for the

multivariable model along with all variables of known clinical

importance. The correlations among numerical data were

analysed by the Pearson correlation coefficient (

r). Adjusted

odds ratios, 95% confidence intervals, and wald statistics

were calculated for each variable. A

p-value of less than .05

was considered statistically significant.

Results

A total of 187 patients (93 obese and 94 non-obese) were

enrolled in the study. The baseline anthropometric, clinical,

and laboratory characteristics of both groups are given in

Table 1

. There were no statistically significant differences for

age, white blood cell count (WBC), and

neutrophil/lympho-cyte ratio between the groups. Insulin, HOMA-IR index,

HbA1c, and SBP were significantly higher in obese patients

than the non-obese ones (

p < .001, p < .001 and p ¼ .001,

respectively).

The obese patients had significantly lower serum levels of

AMH when compared to the non-obese ones (

p ¼ .002)

(

Table 1

).

Multiple logistic regression analyses were used to

deter-mine the best predictors, which affect the increased risk of

CVD in obese patients. Any variable, whose univariable test

had a statistically significant

p-value, was accepted as a

can-didate for the multivariable model along with all variables of

known clinical importance. Multivariable logistic regression

analysis revealed, age (OR: 0.826, 95% CI: 0.735

–0.928), SBP

(OR: 1.058, 95% CI: 1.021

–1.097) and serum AMH levels

(OR: 1.770, 95% CI: 0.946

–3.310) had high predictive value for

CVD in the obese group (

p ¼ .001, p ¼ .002, and p ¼ .049,

respectively) (

Table 2

).

Multiple logistic regression analyses were also used in

non- obese group, too. Age (OR: 0.857, 95% CI: 0.798

–0.921)

and SBP (OR: 1.043, 95% CI: 1.018

–1.069) had significantly

high predictive value for CVD in the non- obese patients

(

p < .001 and p ¼ .001) (

Table 3

).

Further analysis was performed to determine whether the

serum AMH level was correlated with other variables. A

sig-nificant negative correlation was observed between AMH and

HbA1c, and total cholesterol (

p ¼ .026 and p ¼ .015), and a

positive correlation was observed between AMH and LDL in

obese patients (

p ¼ .013). No significant correlation was

observed between AMH, HOMA-IR, SBP, DBP, WBC,

neutro-phil/lymphocyte, HDL, and weight gain (

Table 4

).

Discussion

The main finding of the present study was that

concentra-tions of hormonal parameters (AMH) were significantly lower;

metabolic parameters (HOMA-IR, insulin, HbA1c) and clinical

parameters (like SBP) were significantly higher in obese

patients than non- obese ones. We expected HOMA-IR,

insu-lin, HbA1c, SBP to be positively and AMH to be negatively

associated with CVD risk in obese women, but this was

con-firmed only for AMH and SBP. The mechanisms by which

obesity and CVD affect ovarian functions, and in particular

AMH levels, remain largely unclear. Some of the studies have

reported a significant negative correlation between AMH

lev-els and BMI (van Dorp et al.

2013

; Sova et al.

2019

). Chen

et al. (

2008

), reported that AMH was negatively correlated to

BMI and HOMA-IR. AMH was found to be significantly low in

obese and overweight patients when they were compared to

normal-weight patients (Lefebvre et al.

2017

), whereas others

found no relationship between AMH and BMI (Shand et al.

2014

; Gupta et al.

2019

). The levels of AMH may change

dur-ing the menstrual cycle. The mean value of it in late follicular

phase is 3.19 [0.75

–9.59] ng/mL; 3.28 [0.82–7.56] ng/mL

in ovulatory phase; and 2.7 [0.65

–7.97] ng/mL) in early

luteal phase (Wunder et al.

2008

). Besides, the value of

maternal AMH may change during the gestational weeks.

Table 1. Baseline characteristics, anthropometric and laboratory parameters of obese and non-obese groups.

Obesen¼ 93 Non-obesen¼ 94 p Value Age (year) 28.67 ± 5.92 28.33 ± 5.91 .698 Gravidy Primigravidy 33 (35.1%) 30 (32.3%) .399 Multi gravity 61 (64.9%) 63 (67.7%) Laboratory parameters Fasting glucose (mg/dL) 85.15 ± 14.75 86.68 ± 11.38 .428 Insulin (lIU/mL) 9.43 ± 5.67 6.08 ± 5.58 <.001 HbA1c (%) 5.69 ± 0.62 5.37 ± 0.41 <.001 HOMA-IR 3.54 ± 0.22 2.38 ± 0.24 .001 WBC (mm3) 11.22 ± 2.95 10.95 ± 3.25 .545 Neutrophil/Lymphocyte 4.46 ± 1.90 4.97 ± 3.08 .178 Total cholesterol (mg/dL) 250.56 ± 47.24 262.59 ± 46.29 .080 LDL (mg/dL) 140.33 ± 38.16 152.31 ± 37.65 .032 HDL (mg/dL) 60.88 ± 11.73 63.59 ± 13.22 .140 SBP (mm Hg) 129.03 ± 15.90 119.72 ± 12.27 <.001 DBP (mm Hg) 74.73 ± 11.55 75.37 ± 9.31 .677 AMH (ng/mL) 1.29 ± 0.91 1.74 ± 1.00 .002 Postpartum variables Weight Gain (kg) 12.08 ± 4.45 13.14 ± 4.60 .111 Total foetal Weight (kg) 3318.55 ± 444.03 3227.39 ± 433.66 .157 Gestasyonel birth week 38.77 ± 1.60 38.73 ± 1.46 .852 Type of delivery Vaginal 62 (66 %) 67 (72%) .229 Caesarian 32 (34 %) 26 (28%) Gender Female 48 (51.1%) 49 (52.7%) .470 Male 46 (48.9%) 44 (47.3%)

; a p value < 0.05 is considered as statistically significant. Statistically, signifi-cant p values are marked as bold table. Independent sample-test, mean ± SD, HOMA-IR; Homeostasis Model Assessment of Insulin Resistance, HbA1c; Hemoglobin A1c, WBC; White Blood Cell, LDL; Low-Density Lipoprotein-Cholesterol, HDL; High-Density Lipoprotein- Lipoprotein-Cholesterol, SBP; systolic blood pressure, DBP; Diastolic blood pressure, AMH; Anti-Mullerian Hormone.

Table 2. Regression analysis for CVD risk prediction in obese patients.

Cardiovascular disease risk predictivity (ACC/AHA RISK SCORE) Univariate Multivariate OR (95%Cl) p Value OR (95%Cl) p Value Age (year) 0.859 (0.782–0.942) .001 0.826 (0.735–0.928) .001 WBC (mm3) 0.862 (0.729–1.019) .082 Neutrophil/Lymphocyte 0.921 (0.716–1.184) .521 HbA1c (%) 0.781 (0.342–1.786) .558 HOMA-IR 1.097 (0.902–1.334) .335 SBP (mm Hg) 1.048 (1.015–1.082) .004 1.058 (1.021–1.097) .002 DBP (mm Hg) 1.016 (0.976–1.057) .439 Weight Gain (kg) 0.940 (0.847–1.043) .243 Total foetal Weight (kg) 1.000 (0.999–1.001) .613 Delivery week 1.163 (0.870–1.556) .308

AMH (ng/mL) 1.697 (1.012–2.845) .045 1.770 (0.946–3.310) .049 ; a p value < 0.05 is considered as statistically significant. Statistically, significant p values are marked as bold table. OR; odds

ratio, CI; confidence interval, HOMA-IR; Homeostasis Model Assessment of Insulin Resistance, WBC; White Blood Cell, SBP; Systolic Blood Pressure, DBP; Diastolic Blood Pressure, AMH; Anti-Mullerian Hormone.

The maximum level of it was 0.62 ng/mL in the first trimester;

and was shown to increase up to 1.3 ng/mL in the following

gestational weeks (di Clemente et al.

2010

; Massague

2012

).

We observed decreased maternal serum levels of AMH in

obese patients when compared to non-obese ones.

Whether AMH directly affects CVD or indirectly via

changes in the ovarian reserve has been researched. Ricci

et al. (

2010

) demonstrated AMH receptor-specific mRNA in

the human heart and suggested a direct relationship. Tehrani

et al. (

2014

), in their 12-year longitudinal cohort study,

including 1015 women, showed that total cholesterol, LDL,

and HDL changed in time and correlation with AMH. They

suggested that these changes in AMH and lipid profile may

be evaluated as risk factors in CVD.

Aging is considered to be a risk factor for CVD,

independ-ently of chronological aging (Ebong et al.

2014

). Appt et al.

(

2012

) reported no relation between AMH and lipid profile in

their animal studies, but still observed a negative correlation

between AMH and risk of atherosclerosis. Other studies are

reporting no direct relation of AMH with CVD (de Kat et al.

2016

). However, low AMH level was found to be related to

CVD in patients having decreased ovarian reserve, and AMH

was shown to be an independent risk factor for CVD, just like

insulin resistance, and C reactive protein (Verit et al.

2016

).

We observed that independent from the lipid profile,

decrease in serum AMH, increase in SBP, and age were

related to CVD risk in obese patients.

AMH levels were inversely correlated to BMI and fasting

glucose, but not with other CVD risk factors in a large

cross-sectional population study (Cui et al.

2016

). Anderson et al.

(

2013

) reported no relation of AMH with some

cardiometa-bolic risk factors like lipids or insulin in adult women.

However, we observed that the low level of AMH in obese

patients was negatively related to total cholesterol and

HbA1c; and positively related to LDL. No relation was

detected between AMH and HOMA-IR in our study.

AMH was found to be in lower levels in patients having

preeclampsia when they were compared to healthy pregnants

(Yarde et al.

2014

; Pergialiotis et al.

2017

). No relation of AMH

with gestational diabetes was shown (Villarroel et al.

2018

). As

far as our knowledge, our study is the first one examining the

relation of AMH with CVD risk in obese pregnant patients.

As a result, like the above- mentioned studies, we

observed decreased AMH levels in obese patients, and found

it to be a risk factor for CVD; like increased SBP, and

advanced maternal age. AMH has an informing role in

ovar-ian reserve. But it also effects on different mechanisms, and

become a risk factor for CVD in obese pregnant patients.

The low number of patients is the limit of our study.

Besides, development of CVD takes time and needs prolonged

observation. More other studies examining the mechanism of

AMH on increasing CVD risk in pregnancy are required.

Acknowledgments

We would like to thank the patients and staff who participated in the study.

Author

’s contribution

B. Gumus Guler and S. Ozler designed the study, followed the patients, gathered the raw data of the study, and contributed to writing the paper. M. Sibel Gungoren did the laboratory work and contributed to writing the essay part of the manuscript. N. Kadıoglu and E. Ozkan designed and followed the study and contributed to writing the manu-script. All authors read, edited, and ultimately approved the final manuscript.

Table 4. Correlation analysis between AMH, LDL, HDL, SBP, DBP, HbA1c in obese patients. AMH (ng/mL) r p Value Age (year) .026 .806 HbA1c (%) .230 .026 HOMA-IR .142 .172 WBC (mm3_{) .195 .059} Neutrophil/Lymphocyte .194 .060 Total cholesterol (mg/dL) .250 .015 LDL (mg/dL) .257 .013 HDL (mg/dL) .067 .520 SBP (mm Hg) .072 .492 DBP (mm Hg) .009 .931 Weight Gain (kg) .175 .093 Pearson Correlation Test were used <.05 statistically significant. Statistically

significant p values are marked as bold text. r: Correlation Coefficient; HOMA-IR: Homeostasis Model Assessment of Insulin Resistance; HbA1c: Haemoglobin A1c; WBC: White Blood Cell; LDL: Low-Density Lipoprotein-Cholesterol; HDL: High-Density Lipoprotein- Lipoprotein-Cholesterol; SBP: systolic blood pressure; DBP: Diastolic blood pressure; AMH: Anti-Mullerian Hormone.

Table 3. Regression analysis for CVD risk prediction in non-obese patients.

Cardiovascular risk disease predictivity (ACC/AHA RISK SCORE) Univariate Multivariate OR (95%Cl) p Value OR (95%Cl) p Value Age (year) 0.853 (0.795–0.914) <.001 0.857 (0.798–0.921) <.001 WBC (_–>mm3_{) 0.906 (0.777} –1.056) .206 Neutrophil/–>Lymphocyte 0.775 (0.600–1.001) .051 HbA1c (%) 1.094 (0.624–1.919) .753 HOMA-IR 1.001 (0.876–1.145) .984 SBP (mm Hg) 1.045 (1.022_{–1.069) <.001} 1.043 (1.018_{–1.069) .001} DBP (mm Hg) 1.031 (0.982–1.044) .421 Weight Gain (kg) 0.971 (0.905–1.042) .418 Total foetal Weight (kg) 1.000 (0.999–1.001) .803 Delivery week 1.225 (0.982_–1.529) .072 AMH (ng/mL) 1.357 (0.991–1.858) .057

; a p value < 0.05 is considered as statistically significant. Statistically, significant p values are marked as bold table. OR; odds ratio, CI; confidence interval, HOMA-IR; Homeostasis Model Assessment of Insulin Resistance, WBC; White Blood Cell, SBP; Systolic Blood Pressure, DBP; Diastolic Blood Pressure, AMH; Anti-Mullerian Hormone.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Bas¸ak G€uler http://orcid.org/0000-0002-0182-6774

Sibel €Ozler http://orcid.org/0000-0003-4577-8185

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