Skip to main content
Erschienen in: Reproductive Biology and Endocrinology 1/2018

Open Access 01.12.2018 | Research

The monocyte counts to HDL cholesterol ratio in obese and lean patients with polycystic ovary syndrome

verfasst von: Akin Usta, Eyup Avci, Cagla Bahar Bulbul, Hasan Kadi, Ertan Adali

Erschienen in: Reproductive Biology and Endocrinology | Ausgabe 1/2018

Abstract

Background

Women with polycystic ovary syndrome are more likely to suffer from obesity, insulin resistance, and chronic low-grade inflammation. In fact, the excessive activation of monocytes exacerbates oxidative stress and inflammation. However, high-density lipoprotein cholesterol neutralizes the pro-inflammatory and pro-oxidant effects of monocytes. The aim of this study is to investigate whether monocyte counts to high-density lipoprotein cholesterol ratio can predict the inflammatory condition in patients with polycystic ovary syndrome.

Methods

In this cross-sectional study, a total of 124 women (61 of them with polycystic ovary syndrome and 63 age-matched healthy volunteers) were included in the study population. Obese polycystic ovary syndrome patients (n = 30) with a body mass index of ≥25 kg/m2 and lean polycystic ovary syndrome patients (n = 31) with a body mass index of < 25 kg/m2 were compared to age-and body mass index-matched healthy subjects (30 obese and 33 non-obese).

Results

The monocyte counts to high density lipoprotein cholesterol values in women with polycystic ovary syndrome were significantly higher than in control subjects (p = 0.0018). Moreover, a regression analysis revealed that body mass index, the homeostasis model assessment of insulin resistance and the high sensitivity C-reactive protein levels were confounding factors that affected the monocyte counts to high density lipoprotein cholesterol values. Additionally, a univariate and multivariate logistic regression analysis demonstrated that the increased monocyte counts to high density lipoprotein cholesterol values were more sensitive than the other known risk factors (such as increased body mass index, homeostasis model assessment of insulin resistance and high sensitive C-reactive protein levels) in the prediction of the inflammation in patients with polycystic ovary syndrome.

Conclusion

The present study demonstrated that the monocyte count to high density lipoprotein cholesterol may be a novel and useful predictor of the presence of polycystic ovary syndrome.
Abkürzungen
BMI
Body mass index
CVD
Cardiovascular disease
DM
Diabetes mellitus
E2
Estradiol
ELISA
Enzyme-linked immunosorbent assay
FSH
Follicle-stimulating hormone
HDL
High-density lipoprotein
HOMA-IR
Homeostatic model assessment for insulin resistance
hsCRP
High-sensitivity C-reactive protein
LDL
Low-density lipoprotein cholesterol
LH
Luteinizing hormone
MHR
Monocyte counts to high-density lipoprotein cholesterol ratio
OR
Odds ratio
PCOS
Polycystic ovary syndrome
SD
Standard deviation
STEMI
ST-segment elevation myocardial infarction
TSH
Thyroid-stimulating hormone

Background

Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects 6-20% of women of reproductive age [1, 2]. The disorder is characterized by oligo/anovulation, hormonal and/or clinical hyperandrogenism, and the appearance of polycystic ovaries on ultrasound [1, 2].
Women with PCOS are more likely to suffer from obesity, insulin resistance, glucose intolerance, endothelial dysfunction, hyperandrogenism, and chronic low-grade inflammation than are women without the condition. Chronic low-grade inflammation seems to have a stimulatory effect on the development and progression of endothelial dysfunction and atherosclerosis [3], and long-term complications include type 2 diabetes mellitus and cardiovascular disease [1, 2]. It is therefore important to understand the underlying molecular and cellular mechanisms of this syndrome.
The high-sensitivity C-reactive protein (hsCRP) has been found to be a highly sensitive inflammatory biomarker that is commonly used in the detection of subclinical inflammation in patients with PCOS [4]. The hsCRP test is also used to detect future cardiovascular disease risk [5]. Moreover, increased counts of leucocytes or related subgroups have been found to be additional independent markers as well as prognostic factors in the development of inflammation and atherosclerosis [6, 7]. Regarding the initiation and progression of the atherosclerotic process, several biochemical markers (to include hsCRP and leukocyte counts) associated with inflammatory conditions, oxidative stress, and endothelial dysfunction have been shown to reflect the severity and prognosis of cardiovascular disease risk.
Monocytes constitute roughly 3-8% of circulating leukocytes and-in conjunction with other granular and agranular cells such as eosinophils, basophils, neutrophils, and lymphocytes-are essential components of the innate immune system. In tissues, circulating monocytes and their differentiated forms, known as macrophages, play central roles in the initiation and resolution of inflammation; this is principally achieved via phagocytosis, the release of inflammatory cytokines, the presence of reactive oxygen species, and the activation of the acquired immune system [8]. However, the accumulation of monocytes exacerbates oxidative stress and inflammation. Thus the excessive activation of monocytes aggravates diseases such as atherosclerosis, arthritis, and multiple sclerosis, primarily affecting platelets and endothelial cells and leading to the activation of the prothrombotic pathway [9].
In contrast, high-density lipoprotein cholesterol (HDL-C) neutralizes the pro-inflammatory and pro-oxidant effects of monocytes by hindering the oxidation of low-density lipoprotein (LDL) molecules and the migration of macrophages as well as by promoting the efflux of cholesterol from these cells [10]. In addition to outlining the well-known anti-inflammatory and anti-oxidant actions of HDL-C particles, it has recently been claimed that these molecules play a suppressive role in the control of monocyte activation and in the proliferation and differentiation of the progenitor cells of monocytes [11].
Recognised as a recently-emerged inflammation-based marker, the monocyte count to HDL-C ratio (MHR) has been reported to be a new predictor and prognostic indicator of mortality and morbidity in many diseases [12, 13]. The MHR has also been found to be correlated with hsCRP levels in diseases that are associated with chronic inflammation, such as cardiovascular disease [14], chronic kidney disease [12], abdominal aortic aneurysm [15], intracerebral hemorrhage [16], hypertension [17], and metabolic syndromes [18].
According to the Rotterdam criteria [1], the prevalence of PCOS in Turkish women is approximately 20% [2]. Thus, a considerable number of Turkish women with PCOS are at an increased risk of developing diabetes and cardiovascular disease in the future. The early diagnosis and prevention of inflammatory conditions in the PCOS population is essential to maintain the long-term wellbeing of these women and will aid in the proper utilization of public health resources. To the best of our knowledge, no study has yet examined the association between PCOS and the MHR. Therefore, we aimed to investigate whether the MHR, a readily available inflammatory and oxidative stress marker, is associated with PCOS.

Methods

A cross-sectional study was conducted at the Balikesir University, School of Medicine, Department of Obstetrics and Gynecology and Department of Cardiology between January 2017 and June 2017. The study was approved by the Ethics Committee of Balikesir University, and study protocols of were in accordance with the Helsinki Committee requirements. Informed consent was obtained from all participants.
In total, 124 women (61 with PCOS and 63 age-matched healthy volunteers) were included in the study population. Obese PCOS patients (n = 30) with a body mass index (BMI) of ≥25 kg/m2 and lean PCOS patients (n = 31) with a BMI of < 25 kg/m2 were compared to healthy age-and BMI-matched subjects (30 obese and 33 non-obese). All patients were aged between 18 and 40 years.
PCOS was diagnosed using the Rotterdam criteria [1]. According to these diagnostic criteria, the presence of oligomenorrhea (wherein menstrual cycles occur more than 35 days apart) or amenorrhea (wherein menstrual cycles ocur at least six months apart) was defined as oligoovulation, and the presence of at least 12 follicles measuring 2–9 mm in diameter and/or an ovarian volume greater than 10 cm3 in per ovary indicated the existence of polycystic ovaries; additionally, the presence of hirsutism was evaluated using the Ferriman–Gallwey scoring system [19]. Areas near the lip, chin, chest, upper and lower abdomen, upper arm, forearm and thigh were visually assessed and granded a score between zero (the absence of terminal hair) and four (the presence of male-pattern terminal hair). A score greater than or equal to six was defined as hirsutism.
Patients who were diagnosed with other disorders whose clinical features are similar to those of PCOS, to include Cushing’s syndrome, congenital adrenal hyperplasia and androgen-secreting tumors, were excluded from participation. Additionally, patients who took medicines, such as oral contraceptives, antilipidemic and/or antihypertensive medications, steroids, anti-diabetic medications, anticoagulants, or antiplatelet drugs were excluded from the study.
Each participant’s height (m) and weight (kg) were measured while the patient was dressed only in underwear clothing. Waist circumference was measured as the minimum distance between the iliac crest and the lateral costal margin. The waist-to-hip ratio (WHR) was calculated as the ratio of the waist measurement to that of the hip. BMI was calculated as the patient’s mass in kilograms divided by the square of the patient’s body height in meters (kg/m2). All participant data was recorded and stored in a computer database.
All PCOS and control patients were pooled from university’s gynecology clinic. Additionally, PCOS patients were reevaluated to determine whether they truly met the clinical, ultrasound scan (U/S), and biochemical criteria for PCOS based on the Rotterdam criteria. Physical and gynecological examinations, pelvic ultrasounds, and peripheral venous blood samplings were performed during Day 2 or 3 of a participant’s menstrual cycles or progestogen induced early follicular phase (Day 2 or 3) in subjects with amenorrhea. All women were examined, and pelvic ultrasound scans were performed using a 7.0 MHz vaginal transducer (Voluson 730, GE Healthcare, USA) by the same gynecologist.
During blood pressure measurements, the brachial artery was occluded by a cuff placed around the patient’s upper arm; the cuff was then inflated to above systolic pressure. As the cuff gradually deflated, pulsatile blood flow was reestablished and was accompanied by sounds that were able to be detected by a stethoscope held over the artery just below the cuff. The onset of the pulsatile blood flow sound (Korotkoff I) was recorded as systolic blood pressure and the disappearance of blood flow sounds (Korotkoff V) was recorded as diastolic blood pressure. All measurements were performed by healthcare professionals, who were blinded to the clinical diagnoses of the patients.

Biochemical evaluation

After overnight fasting, blood samples were collected from the antecubital vein of patients between the hours of 9 and 10 AM. Serum was collected following centrifugation at 2500 g for 10 min, and stored in deep freeze at − 80 °C to await biochemical and hormonal assessment. To avoid possible assay variability, all patient blood samples were analyzed together.
Complete blood counts were measured via Sysmex XE-2100 (Sysmex Corp. Kobe, Japan) using either the fluorescence flow cytometry or electrical impedance method. The serum levels of follicle-stimulating hormone (FSH), luteinizing hormone (LH), estradiol (E2), thyroid-stimulating hormone (TSH), and total testosterone were determined using commercially avaliable enzyme-linked immunosorbent assay (ELISA) kits (eBioscience, Austria) on a diagnostic instrument (BioTek, ELx 800, USA). 2nd International reference preparation was used for FSH and LH measurements. The levels of glucose, total cholesterol, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol were measured using commercially available kits on a chemistry AutoAnalyzer (Cobas Integra 800; Roche Diagnostics GmbH; Mannheim, Germany). Serum high sensitive C-reactive protein (hs CRP) was measured with chemiluminescent immunoassay using an ADVIA Centaur XP (Siemens Healthcare Diagnostics, NY, USA). The levels of fasting insulin were determined using commercial kits and an automatic hormone analyzer (Beckman Coulter; Unicel DXI 600; Access Immunoassay System). The homeostasis model assessment for insulin resistance (HOMA-IR) was defined as (insulin x glucose) / 22.5 as previously described [6].

Statistical analysis

The MedCalc Statistical Software Program version 17.2 (MedCalc, Belgium) was used for statistical analysis. Normally distributed data are described as mean ± standard deviation, otherwise, as median (minimum-maximum). Whether the distributions of continuous variables were normal or not was determined by Kolmogorov–Smirnov test. Also, the Levene test or F test was used for the evaluation of homogeneity of variances.
The student’s t test was used to compare normally distributed measurements for independent samples and the Mann–Whitney U test was applied for comparisons of the median values. The Chi-square test was used to compare categorical data. While the mean differences among more than two independent groups were analyzed by one-way ANOVA, the Kruskal–Wallis test was applied for comparisons of the median values. When the p value from one-way ANOVA or Kruskal–Wallis test statistics was statistically significant the Scheffé test or Post-Hoc analysis nonparametric multiple comparison test was used to determine which group differed from which others. The possible confounding factors that associated with MHR value were evaluated by using logistic regression analysis. In order to determine of the independent variables for presence of PCOS, the univariate and multivariate logistic regression analysis were performed. To evaluate model characteristics of fitness, Hosmer–Lemeshow tests were used. A p-value of < 0.05 was considered statistically significant.

Results

A total of 124 women—61 with PCOS (30 obese, 31 non-obese) and 63 age- and BMI matched controls (30 obese, 33 non-obese)—were included in this study. The mean age of participants was 23.9 ± 4.9 in the PCOS group and 25.2 ± 5.1 in the control group; there was no statistically significant difference (p = 0.1566) between the groups. The mean BMI of participants was 26.6 ± 6.1 in the PCOS group, and 24.8 ± 5.3 in the control group (p = 0.0858).
As compared to the control subjects, PCOS patients had significantly higher WHRs, Ferriman Gallwey scores, diastolic blood pressure levels, insuline levels, HOMA-IR readings, hsCRP scores, total leucocytes counts, neutrophil counts, monocyte counts, total cholesterol levels, LDL levels, total testosterone levels, LH levels and MHRs (p < 0.05). However, HDL-C levels were lower in PCOS patients than in control subjects (p < 0.0001). The clinical, hormonal, and biochemical characteristics of the groups are summarized in Table 1.
Table 1
The clinical, hormonal, and biochemical characteristics of patients in tje PCOS and non-PCOS groups
 
PCOS
Non-PCOS
P value
Age (year)
23.9 ± 4.9
25.2 ± 5.1
0.1566
Body mass index (kg/m2)
26.6 ± 6.1
24.8 ± 5.3
0.0858
Waist to hip ratio (WHR) (cm)
0.80 ± 0.07
0.77 ± 0.06
0.0030
Ferriman–Gallwey score
5 (2-17)
3 (1-6)
<  0.0001
Systolic blood pressure (mmHg)
120 (90-150)
110 (90-130)
0.1195
Diastolic blood pressure (mmHg)
70 (60-110)
70 (60-80)
0.0115
Glucose (mg/dl)
88 (64-123)
81 (61-110)
0.0092
HOMA-IR
2.42 (0.6-13.8)
1.49(0.4-8.8)
0.0027
hsCRP (mg/l)
3.2 (0.3-29.0)
1.8 (0.2-7.8)
0.0074
Leucocytes (/mm3)
7.86 ± 2.28
6.92 ± 2.19
0.0208
Neutrophil (/mm3)
4.76 ± 1.68
4.08 ± 1.35
0.0150
Lymphocytes (/mm3)
2.48 ± 0.76
2.29 ± 0.65
0.0820
Monocyte (/mm3)
645.9 ± 205.8
510.9 ± 184.9
0.0002
Trigliserid (mg/dL)
95.0 (46.0-529.0)
78.0 (44.0-280.0)
0.1080
Total cholesterol (mg/dL)
180.1 ± 33.6
168.1 ± 28.5
0.0221
LDL (mg/dL)
102.1 ± 29.7
91.2 ± 25.6
0.0373
HDL (mg/dL)
47.5 ± 10.8
58.7 ± 13.4
<  0.0001
Total testosteron (ng/dl)
1.20 (0.10-4.71)
0.15 (0.07-0.90)
<  0.0001
FSH (IU/L)
5.86 ± 1.37
6.34 ± 1.68
0.0818
LH (IU/L)
9.15 (5.03-22.10)
6.40 (4.72-14.60)
<  0.0001
Estradiol (pg/ml)
45.32 ± 13.67
41.87 ± 14.21
0.1705
TSH (mIU/L)
2.15 ± 1.17
2.08 ± 1.03
0.7119
Prolaktin (ng/ml)
17.34 ± 8.17
16.27 ± 5.89
0.4072
Monocytes to HDL ratio
11.46 (3.70-30.50)
8.77 (3.31-24.19)
0.0018
Data was showed: mean ± standard deviation (SD) or median (min-max)
The biochemical parameters of obese and lean patients with or without PCOS are shown in Table 2. Obese PCOS patients had higher levels of diastolic blood pressure, HOMA-IR, hsCRP, monocytes, total cholesterol, and LDL-C but lower levels of HDL-C than did control participants (p <  0.05). Lean PCOS patients had higher levels of HOMA-IR, hsCRP, neutrophils, monocytes, and total testosterone but lower levels of HDL-C and lymphocytes than did control participants (p <  0.05).
Table 2
The clinical and laboratory parameters of obese and lean patients with or without PCOS
 
Obese PCOS n = 30
Lean PCOS n = 31
Obese Control n = 30
Lean Control n = 33
p value
Age (year)
24.6 ± 4.6
24.7 ± 4.9
23.4 ± 4.3
26.9 ± 5.3
0.059
Body mass index (kg/m2)
29.1 ± 4.2 a,c
22.3 ± 3.7 d
31.1 ± 4.6 f
21.4 ± 2.8
<  0.001
Waist to hip ratio (WHR) (cm)
0.85 ± 0.06 a,b,c
0.75 ± 0.04 d,e
0.80 ± 0.06 f
0.73 ± 0.03
<  0.001
Ferriman–Gallwey score
7 (3-17) a,b,c
4 (2-13) d,e
2 (1-5)
1 (1-4)
<  0.001
Systolic blood pressure (mmHg)
120 (90-150) a,c
110 (90-130)
110 (100-130)
110 (90-120)
0.011
Diastolic blood pressure (mmHg)
80 (60-110) a,b,c
70 (60-80)
70 (60-80)
70 (60-80)
0.006
Glucose (mg/dl)
92 (74-123) a,b,c
83 (64-112)
85 (65-110)
78 (61-98)
0.007
HOMA-IR
3.5 (1.4-13.8) a,b,c
2.2 (0.6-9.8)d,e
2.6 (1.1-8.8) f
1.2 (0.4-5.6)
<  0.001
hsCRP (mg/l)
4.1(1.2-29.1) a,b,c
1.5 (0.3-8.8) e
2.7 (0.9-7.8) f
0.9 (0.2-3.5)
<  0.001
Leucocytes (/mm3)
8.9 ± 2.3 a,c
6.9 ± 1.8 d
7.8 ± 2.6
6.2 ± 1.4
<  0.001
Neutrophil (/mm3)
5.1 ± 1.9 c
4.5 ± 1.3 e
4.5 ± 1.4
3.7 ± 1.2
0.005
Lymphocytes (/mm3)
2.3 ± 0.7
2.1 ± 0.6
2.5 ± 0.8
2.5 ± 0.7
0.158
Monocyte (/mm3)
657.7 ± 259.3 b,c
634.6 ± 139.1 d,e
517.4 ± 184.9
504.7 ± 187.9
0.005
Trigliserid (mg/dL)
145.5(46.0-529.0) a,c
69.0 (53.0-136.0) d
116.0 (58.0-280.0) f
64.0 (44.0-170.0)
<  0.001
Total cholesterol (mg/dL)
189.6 ± 32.1 a,b
164.1 ± 27.5
167.1 ± 26.2
172.2 ± 30.3
0.005
LDL (mg/dL)
110.7 ± 30.5 b,c
95.7 ± 34.6
94.9 ± 22.7
87.8 ± 26.5
0.015
HDL (mg/dL)
43.6 ± 8.9 a,b,c
51.2 ± 11.3 e
54.5 ± 9.9 f
62.8 ± 14.6
<  0.001
Total testosteron (ng/dl)
1.40 (0.32-4.71) a,b,c
1.04 (0.12-2.80) d,e
0.58 (0.07-0.98) f
0.11 (0.07-0.25)
<  0.001
FSH (IU/L)
5.75 ± 1.24
5.97 ± 1.49
6.22 ± 1.60
6.46 ± 1.77
0.302
LH (IU/L)
9.80 (5.03-22.1) b,c
9.15 (5.50-14.5) d,e
6.88 (4.76-14.6) f
5.70 (4.72-10.01)
<  0.001
Estradiol (pg/ml)
47.37 ± 22.64
43.35 ± 18.44
43.26 ± 21.03
41.60 ± 19.47
0.297
TSH (mIU/L)
2.03 ± 1.27
2.27 ± 1.07
1.92 ± 0.91
2.22 ± 1.13
0.564
Prolaktin (ng/ml)
16.42 ± 7.68
18.22 ± 8.42
15.65 ± 6.72
17.15 ± 6.10
0.442
Monocytes to HDL ratio
15.6 (3.7-30.5) a,b,c
9.6 (5.4-24.7) e
9.9 (3.8-20.9) f
7.9 (3.3-24.2)
<  0.001
Data was present: mean ± standard deviation (SD) or median (min-max)
a Obese PCOS vs. Nonobese PCOS (p <  0.05)
b Obese PCOS vs. Obese Control (p <  0.05)
c Obese PCOS vs. Nonobese Control (p <  0.05)
d Nonobese PCOS vs. Obese Control (p <  0.05)
e Nonobese PCOS vs Nonobese Control (p < 0.05)
f Obese Control vs. Nonobese Control (p < 0.05)
Interestingly, we found that obese PCOS patients had higher levels of systolic blood pressure, diastolic blood pressure, HOMA-IR, hsCRP, and total leucocytes but lower HDL-C levels than did lean PCOS patients (p <  0.05).
Importantly, we found that MHR values were significantly higher in patients with PCOS than in control subjects (p = 0.0018). Moreover, subgroup analysis showed that MHR values of obese PCOS patients were significantly higher than those of lean PCOS patients. Also, MHR values of obese control patients were significantly higher than lean control subjects.
A univariate regression analysis showed that BMI, diastolic blood pressure, HOMA-IR, and hsCRP, were possible confounding factors affecting MHR values (Table 3). Furthermore, in order to identify independent variables that might predict the presence of PCOS, univariate and multivariate logistic regression analyses were performed (Table 4). During the univariate logistic regression analysis, HOMA-IR (odds ratio [OR]: 1.3133 [95% CI: 1.0543–1.6358]; p = 0.0067), hsCRP (OR:1.2996 [95% CI: 1.0804–1.5634]; p = 0.0023) and the MHR (OR: 1.1006 [95% CI: 1.0314–1.1745]; p = 0.0020) reached statistical significance. In the multivariate logistic regression analysis, only the MHR (OR: 1.0755 [95% CI: 1.0010–1.1556]; p = 0.0470) was found to be an independent marker for the prediction of PCOS.
Table 3
Possible confounding factors associated with monocyte counts to HDL-C ratio
Variables
Univariate logistic regression analysis
 
OR
95% CI
P value
Age (year)
1.0566
0.9818 to 1.1370
0.1368
Body mass index (kg/m2)
1.1600
1.0758 to 1.2509
< 0.0001
Systolic blood pressure (mmHg)
1.0209
0.9930 to 1.0496
0.1370
Diastolic blood pressure (mmHg)
1.0986
1.0525 to 1.1468
< 0.0001
HOMA-IR
1.9183
1.3913 to 2.6449
< 0.0001
Glucose (mg/dl)
1.0033
0.9738 to 1.0336
0.8296
hsCRP (mg/l)
1.2107
1.0181 to 1.4396
0.0211
Leucocytes (/mm3)
1.4282
1.1749 to 1.7361
0.0001
Neutrophil (/mm3)
1.6002
1.1971 to 2.1389
0.0004
Lymphocytes (/mm3)
1.8149
1.0584 to 3.1119
0.0238
Trigliserid (mg/dL)
1.0020
0.9965 to 1.0074
0.4713
Total cholesterol (mg/dL)
1.0093
0.9968 to 1.0220
0.1406
LDL (mg/dL)
1.0192
1.0053 to 1.0333
0.0041
Total testosteron (ng/dl)
1.9936
1.2264 to 3.2408
0.0024
FSH (IU/L)
1.0346
0.8252 to 1.2972
0.7681
LH (IU/L)
1.3157
1.1552 to 1.4985
< 0.0001
Estradiol (pg/ml)
1.0203
0.9934 to 1.0480
0.1297
TSH (mIU/L)
0.9632
0.6983 to 1.3286
0.8192
Prolaktin (ng/ml)
0.9889
0.9407 to 1.0395
0.6599
Table 4
Univariate and multivariate logistic regression analysis showing the predictors for the presence of polycystic ovary syndrome
Variables
Univariate logistic regression analysis
Multivariate logistic regression analysis
 
OR
95% CI
P value
OR
95% CI
P value
Age (year)
0.9863
0.9199 to 1.0575
0.6977
Body mass index (kg/m2)
1.0594
0.9934 to 1.1298
0.0744
0.9838
0.9077 to 1.0663
0.6904
HOMA-IR
1.3133
1.0543 to 1.6358
0.0067
1.1212
0.8660 to 1.4515
0.3854
hsCRP (mg/l)
1.2996
1.0804 to 1.5634
0.0023
1.2271
0.9970 to 1.5102
0.0534
Leucocytes (/mm3)
1.1091
0.9481 to 1.2973
0.1894
MHR
1.1006
1.0314 to 1.1745
0.0020
1.0755
1.0010 to 1.1556
0.0470

Discussion

In the present study, we evaluated multiple clinical and biochemical variables in PCOS patients and compared them with those of age- and BMI-matched non-PCOS subjects. Our clinical and biochemical parameters confirmed that women with PCOS, had higher scores in terms of WHR, hirsutism, diastolic blood pressure, insulin, HOMA-IR, hsCRP, total cholesterol, LDL-C, total testosterone, and LH but also lower HDL-C values. Additionally, a subgroup analysis revealed that obese PCOS patients had higher levels of diastolic blood pressure, insulin, HOMA-IR, hsCRP, and monocytes, while members of the lean PCOS group had higher levels of diastolic blood pressure, insulin, HOMA-IR, hsCRP, neutrophils, lymphocytes, monocytes, and total testosterone as compared to age- and BMI-matched controls; notably, these findings were consistent with those of many previous studies [3, 2024]. Importantly, we found that the MHR was significantly higher in women with PCOS than in women in the control group. To the best of our knowledge, this is the first study to investigate the association between the MHR and PCOS.
PCOS is a complex endocrine and metabolic disease that is associated with obesity, insulin resistance, compensatory hyperinsulinemia, and chronic low-grade inflammation [3]. Previous studies have shown that various biomarker alterations are associated with insulin resistance and low-grade inflammation in patients with PCOS [21, 22]. Therefore, PCOS is linked to a combination of risk factors that may lead to the development of cardiovascular disease and type 2 diabetes mellitus. Indeed, low-grade inflammation, impaired glucose tolerance, central obesity, dyslipidemia, and hypertension in PCOS patients are associated with an increase in cardiovascular disease risk [20].
The activation of monocytes and their differentiated forms into lipid-laden macrophages plays a significant role in the promotion of immune defenses in patients with chronic inflammatory conditions; these actions also drive inflammation and cardiovascular disease. Johnsen et al. demonstrated that an elevated monocyte count can be used as an independent predictor of future plaque development in previously plaque-free arteries [25]. Moreover, the activation of monocytes and their differentiated forms into macrophages can be modulated by inflammatory cytokines [26]. However, HDL-C molecules have the ability to counteract macrophage migration and eliminate cholesterol from these cells. Classically known as an antiatherogenic lipoprotein, HDL-C promotes reverse cholesterol transport from the arterial wall-specifically from lipid-laden macrophages [27]. It has been suggested that HDL-C may play a protective role in atherogenesis via the regulation of endothelial adhesion molecule expression, thereby preventing the generation of oxidatively modified LDL-C and the stimulation of endothelial nitric oxide synthases [27]. Additionally, HDL-C has anti-inflammatory, anti-oxidant, and anti-thrombotic effects [10, 27]. The anti-inflammatory effect of HDL-C results from its interaction with both circulating cells, which have the ability to inhibit both leukocyte and platelet activations. HDL-C is highly effective in inhibiting the endothelial expression of adhesion molecules and in preventing monocyte recruitment to the artery wall [28]. As briefly mentioned above, higher monocyte counts and lower HDL-C levels seem to be indirect indicators of inflammation and of the development of atherosclerosis [26]. Indeed, the relationship between these two parameters provides a better understanding of concomitant inflammation.
Relevant literature contains a limited number of studies on the MHR and its role in predicting inflammation. A recent study conducted by Cetin et al. found that the MHR was a novel inflammation-based marker that could be used as an independent predictor of both the severity of coronary artery disease and the likelihood of future cardiovascular events in patients with acute coronary syndrome [14]. Similarly, increases in the MHR have been associated with more severe cardiovascular prognoses in patients with chronic kidney disease [12]. Additionally, the MHR was an independent variable for cardiovascular events within this population [28]. Cockerill et al. indicated that the MHR may be a predictor of stent thrombosis and mortality in ST elevated myocardial infarction (STEMI) patients [29]. Moreover, a recent study conducted by Vahit et al. demonstrated that an increased MHR score may be a useful indicator of metabolic syndromes [18]. Consistent with these studies, we found that the average MHR value of patients with PCOS was substantially higher than that of patients without PCOS. Moreover, the univariate regression analysis showed that BMI, diastolic blood pressure, HOMA-IR, and CRP, were possible confounding factors affecting MHR values in our study population. Also, in an effort to identify independent variables for the prediction of PCOS, univariate and multivariate logistic regression analyses were conducted; these analyses showed that the MHR was the only independent variable for women with PCOS. These results indicated that higher MHR values may be associated with ongoing inflammation in the pathophysiology of PCOS. In their entirely, these findings signaled the importance of the MHR with regard to systemic inflammatory conditions and endothelial dysfunction, both of which play crucial roles in the development of future cardiovascular disease.
Insulin resistance is a cornerstone of PCOS. Insulin resistance and compensatory hyperinsulinemia in PCOS patients seem to have a stimulatory effect on chronic low-grade inflammation. It is known that obesity is associated with insulin resistance and low-grade inflammation in the PCOS population [24]. Fat tissues, such as those found in endocrine organs, engage in metabolic and endocrinological activities whereby cytokines and other messenger proteins called adipokines are produced and secreted. Cytokines mediate many physiological and pathological metabolic processes, such as satiety and energy balance, inflammation, insulin resistance/sensitivity, angiogenesis, lipid metabolism, and atherosclerosis. Many previous studies have shown that early atherogenesis and subclinical atherosclerosis are more common in patients with PCOS than in control subjects [30]. In line with the existing literature, we found that obese PCOS patients had higher HOMA-IR, hsCRP, and total leucocyte counts but lower HDL-C levels than did lean PCOS patients [3, 2024]. Moreover, the MHR values of obese PCOS patients were significantly higher than those of lean PCOS patients. Additionally, the HOMA-IR and total leucocyte counts were significantly higher in obese control patients than lean control patients. As expected, the MHR values in obese control patients were higher than in lean control patients in our study population. These results clearly indicated that obese PCOS patients tend to be at a higher risk for the development of future cardiovascular disease than are other patients.

Limitations

The main limitations of this study concerns its cross-sectional study design and its relatively small population size. Moreover, monocyte and lymphocyte counts were calculated automatically using peripheric blood samples. The absence of other inflammation and oxidation parameters, in conjunction with the lack of a comparison to other inflammation biomarkers, was another limitation of this study. Data regarding patients’ alcohol intake and smoking habits to include frequency of use and years of smoking history, both of which may affect the development of PCOS, were not included in our study due to the absence of records.

Conclusions

This study was the first to investigate the significance of the MHR in patients with PCOS. Our study demonstrated that patients with PCOS have higher MHR values than do women without the condition. The MHR may be used as a simple, low-cost, reproducible biochemical marker to be used in the detection of cardiovascular disease risk in PCOS patients; notably, it is also beneficial in the diagnosis of PCOS using other diagnostic criteria. The present study suggests that further prospective randomized studies be conducted in order to fully evaluate the association between the MHR and PCOS.

Acknowledgments

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or  materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Funding

Authors do not have any funds for this study.

Availability of data and materials

The data sets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Financial disclosure

The authors have no connection to any companies or products mentioned in this article.

Authors’contributions

AU, EA and HK designed the study. AU, EA, HK and CBB conducted the sample collection and compiled the data. AU, EA, CBB and EA analyzed the data. AU and EA performed statistical analysis and AU, EA, HK and EA generated the manuscript. EA: Critical review, control/supervision. All authors read and approved the final manuscript.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the Ethics Committee of Balikesir University (Approval no: 2017/112). All patients included gave their written agreement after informed consent.
Written informed consent for publication was obtained.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
Literatur
1.
Zurück zum Zitat Fauser BCJM, Tarlatzis BC, Rebar RW, Legro RS, Balen AH, Lobo R, et al. Consensus on women’s health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/ASRM-sponsored 3rd PCOS consensus workshop group. Fertil Steril. 2012;97:28–38. e25CrossRefPubMed Fauser BCJM, Tarlatzis BC, Rebar RW, Legro RS, Balen AH, Lobo R, et al. Consensus on women’s health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/ASRM-sponsored 3rd PCOS consensus workshop group. Fertil Steril. 2012;97:28–38. e25CrossRefPubMed
2.
Zurück zum Zitat Yildiz BO, Bozdag G, Yapici Z, Esinler I, Yarali H. Prevalence, phenotype and cardiometabolic risk of polycystic ovary syndrome under different diagnostic criteria. Hum Reprod Oxf Engl. 2012;27:3067–73.CrossRef Yildiz BO, Bozdag G, Yapici Z, Esinler I, Yarali H. Prevalence, phenotype and cardiometabolic risk of polycystic ovary syndrome under different diagnostic criteria. Hum Reprod Oxf Engl. 2012;27:3067–73.CrossRef
3.
Zurück zum Zitat Puder JJ, Varga S, Kraenzlin M, De Geyter C, Keller U, Müller B. Central fat excess in polycystic ovary syndrome: relation to low-grade inflammation and insulin resistance. J Clin Endocrinol Metab. 2005;90:6014–21.CrossRefPubMed Puder JJ, Varga S, Kraenzlin M, De Geyter C, Keller U, Müller B. Central fat excess in polycystic ovary syndrome: relation to low-grade inflammation and insulin resistance. J Clin Endocrinol Metab. 2005;90:6014–21.CrossRefPubMed
4.
Zurück zum Zitat Kim JW, Han JE, Kim YS, Won HJ, Yoon TK, Lee WS. High sensitivity C-reactive protein and its relationship with impaired glucose regulation in lean patients with polycystic ovary syndrome. Gynecol Endocrinol. 2012;28:259–63.CrossRefPubMed Kim JW, Han JE, Kim YS, Won HJ, Yoon TK, Lee WS. High sensitivity C-reactive protein and its relationship with impaired glucose regulation in lean patients with polycystic ovary syndrome. Gynecol Endocrinol. 2012;28:259–63.CrossRefPubMed
5.
Zurück zum Zitat Toulis KA, Goulis DG, Mintziori G, Kintiraki E, Eukarpidis E, Mouratoglou S-A, et al. Meta-analysis of cardiovascular disease risk markers in women with polycystic ovary syndrome. Hum Reprod Update. 2011;17:741–60.CrossRefPubMed Toulis KA, Goulis DG, Mintziori G, Kintiraki E, Eukarpidis E, Mouratoglou S-A, et al. Meta-analysis of cardiovascular disease risk markers in women with polycystic ovary syndrome. Hum Reprod Update. 2011;17:741–60.CrossRefPubMed
6.
Zurück zum Zitat Keskin Kurt R, Okyay AG, Hakverdi AU, Gungoren A, Dolapcioglu KS, Karateke A, et al. The effect of obesity on inflammatory markers in patients with PCOS: a BMI-matched case-control study. Arch Gynecol Obstet. 2014;290:315–9.CrossRefPubMed Keskin Kurt R, Okyay AG, Hakverdi AU, Gungoren A, Dolapcioglu KS, Karateke A, et al. The effect of obesity on inflammatory markers in patients with PCOS: a BMI-matched case-control study. Arch Gynecol Obstet. 2014;290:315–9.CrossRefPubMed
7.
Zurück zum Zitat Margolis KL, Manson JE, Greenland P, Rodabough RJ, Bray PF, Safford M, et al. Leukocyte count as a predictor of cardiovascular events and mortality in postmenopausal women: the Women’s health initiative observational study. Arch Intern Med. 2005;165:500–8.CrossRefPubMed Margolis KL, Manson JE, Greenland P, Rodabough RJ, Bray PF, Safford M, et al. Leukocyte count as a predictor of cardiovascular events and mortality in postmenopausal women: the Women’s health initiative observational study. Arch Intern Med. 2005;165:500–8.CrossRefPubMed
8.
Zurück zum Zitat Auffray C, Sieweke MH, Geissmann F. Blood monocytes: development, heterogeneity, and relationship with dendritic cells. Annu Rev Immunol. 2009;27:669–92.CrossRefPubMed Auffray C, Sieweke MH, Geissmann F. Blood monocytes: development, heterogeneity, and relationship with dendritic cells. Annu Rev Immunol. 2009;27:669–92.CrossRefPubMed
9.
Zurück zum Zitat Linker R, Gold R, Luhder F. Function of neurotrophic factors beyond the nervous system: inflammation and autoimmune demyelination. Crit Rev Immunol. 2009;29:43–68.CrossRefPubMed Linker R, Gold R, Luhder F. Function of neurotrophic factors beyond the nervous system: inflammation and autoimmune demyelination. Crit Rev Immunol. 2009;29:43–68.CrossRefPubMed
10.
Zurück zum Zitat Parthasarathy S, Barnett J, Fong LG. High-density lipoprotein inhibits the oxidative modification of low-density lipoprotein. Biochim Biophys Acta. 1990;1044:275–83.CrossRefPubMed Parthasarathy S, Barnett J, Fong LG. High-density lipoprotein inhibits the oxidative modification of low-density lipoprotein. Biochim Biophys Acta. 1990;1044:275–83.CrossRefPubMed
11.
Zurück zum Zitat Westerterp M, Gourion-Arsiquaud S, Murphy AJ, Shih A, Cremers S, Levine RL, et al. Regulation of hematopoietic stem and progenitor cell mobilization by cholesterol efflux pathways. Cell Stem Cell. 2012;11:195–206.CrossRefPubMedPubMedCentral Westerterp M, Gourion-Arsiquaud S, Murphy AJ, Shih A, Cremers S, Levine RL, et al. Regulation of hematopoietic stem and progenitor cell mobilization by cholesterol efflux pathways. Cell Stem Cell. 2012;11:195–206.CrossRefPubMedPubMedCentral
12.
Zurück zum Zitat Kanbay M, Solak Y, Unal HU, Kurt YG, Gok M, Cetinkaya H, et al. Monocyte count/HDL cholesterol ratio and cardiovascular events in patients with chronic kidney disease. Int Urol Nephrol. 2014;46:1619–25.CrossRefPubMed Kanbay M, Solak Y, Unal HU, Kurt YG, Gok M, Cetinkaya H, et al. Monocyte count/HDL cholesterol ratio and cardiovascular events in patients with chronic kidney disease. Int Urol Nephrol. 2014;46:1619–25.CrossRefPubMed
13.
Zurück zum Zitat Canpolat U, Çetin EH, Cetin S, Aydin S, Akboga MK, Yayla C, et al. Association of Monocyte-to-HDL cholesterol ratio with slow coronary flow is linked to systemic inflammation. Clin Appl Thromb. 2016;22:476–82.CrossRef Canpolat U, Çetin EH, Cetin S, Aydin S, Akboga MK, Yayla C, et al. Association of Monocyte-to-HDL cholesterol ratio with slow coronary flow is linked to systemic inflammation. Clin Appl Thromb. 2016;22:476–82.CrossRef
14.
Zurück zum Zitat Cetin MS, Ozcan Cetin EH, Kalender E, Aydin S, Topaloglu S, Kisacik HL, et al. Monocyte to HDL cholesterol ratio predicts coronary artery disease severity and future major cardiovascular adverse events in acute coronary syndrome. Heart Lung Circ. 2016;25:1077–86.CrossRefPubMed Cetin MS, Ozcan Cetin EH, Kalender E, Aydin S, Topaloglu S, Kisacik HL, et al. Monocyte to HDL cholesterol ratio predicts coronary artery disease severity and future major cardiovascular adverse events in acute coronary syndrome. Heart Lung Circ. 2016;25:1077–86.CrossRefPubMed
15.
Zurück zum Zitat Cagli K, Tok D, Turak O, Gunertem E, Yayla C, Lafci G, et al. Monocyte count-to-high-density lipoprotein-cholesterol ratio is associated with abdominal aortic aneurysm size. Biomark Med. 2016;10:1039–47.CrossRefPubMed Cagli K, Tok D, Turak O, Gunertem E, Yayla C, Lafci G, et al. Monocyte count-to-high-density lipoprotein-cholesterol ratio is associated with abdominal aortic aneurysm size. Biomark Med. 2016;10:1039–47.CrossRefPubMed
16.
Zurück zum Zitat You S, Zhong C, Zheng D, Xu J, Zhang X, Liu H, et al. Monocyte to HDL cholesterol ratio is associated with discharge and 3-month outcome in patients with acute intracerebral hemorrhage. J Neurol Sci. 2017;372:157–61.CrossRefPubMed You S, Zhong C, Zheng D, Xu J, Zhang X, Liu H, et al. Monocyte to HDL cholesterol ratio is associated with discharge and 3-month outcome in patients with acute intracerebral hemorrhage. J Neurol Sci. 2017;372:157–61.CrossRefPubMed
17.
Zurück zum Zitat Aydin E, Ates I, Fettah Arikan M, Yilmaz N, Dede F. The ratio of monocyte frequency to HDL cholesterol level as a predictor of asymptomatic organ damage in patients with primary hypertension. Hypertens Res. 2017;40:758–64.CrossRefPubMed Aydin E, Ates I, Fettah Arikan M, Yilmaz N, Dede F. The ratio of monocyte frequency to HDL cholesterol level as a predictor of asymptomatic organ damage in patients with primary hypertension. Hypertens Res. 2017;40:758–64.CrossRefPubMed
18.
Zurück zum Zitat Vahit D, Mehmet KA, Samet Y, Hüseyin E. Assessment of monocyte to high density lipoprotein cholesterol ratio and lymphocyte-to-monocyte ratio in patients with metabolic syndrome. Biomark Med. 2017;11:535–40.CrossRefPubMed Vahit D, Mehmet KA, Samet Y, Hüseyin E. Assessment of monocyte to high density lipoprotein cholesterol ratio and lymphocyte-to-monocyte ratio in patients with metabolic syndrome. Biomark Med. 2017;11:535–40.CrossRefPubMed
19.
Zurück zum Zitat Ferriman D, Gallwey JD. Clinical assessment of body hair growth in women. J Clin Endocrinol Metab. 1961;21:1440–7.CrossRefPubMed Ferriman D, Gallwey JD. Clinical assessment of body hair growth in women. J Clin Endocrinol Metab. 1961;21:1440–7.CrossRefPubMed
20.
Zurück zum Zitat Samy N, Hashim M, Sayed M, Said M. Clinical significance of inflammatory markers in polycystic ovary syndrome: their relationship to insulin resistance and body mass index. Dis Markers. 2009;26:163–70.CrossRefPubMedPubMedCentral Samy N, Hashim M, Sayed M, Said M. Clinical significance of inflammatory markers in polycystic ovary syndrome: their relationship to insulin resistance and body mass index. Dis Markers. 2009;26:163–70.CrossRefPubMedPubMedCentral
21.
Zurück zum Zitat Diamanti-Kandarakis E, Alexandraki K, Piperi C, Protogerou A, Katsikis I, Paterakis T, et al. Inflammatory and endothelial markers in women with polycystic ovary syndrome. Eur J Clin Investig. 2006;36:691–7.CrossRef Diamanti-Kandarakis E, Alexandraki K, Piperi C, Protogerou A, Katsikis I, Paterakis T, et al. Inflammatory and endothelial markers in women with polycystic ovary syndrome. Eur J Clin Investig. 2006;36:691–7.CrossRef
22.
Zurück zum Zitat Bayram F, Kocer D, Ozsan M, Muhtaroglu S. Evaluation of endothelial dysfunction, lipid metabolism in women with polycystic ovary syndrome: relationship of paraoxonase 1 activity, malondialdehyde levels, low-density lipoprotein subfractions, and endothelial dysfunction. Gynecol Endocrinol. 2012;28:497–501.CrossRefPubMed Bayram F, Kocer D, Ozsan M, Muhtaroglu S. Evaluation of endothelial dysfunction, lipid metabolism in women with polycystic ovary syndrome: relationship of paraoxonase 1 activity, malondialdehyde levels, low-density lipoprotein subfractions, and endothelial dysfunction. Gynecol Endocrinol. 2012;28:497–501.CrossRefPubMed
23.
Zurück zum Zitat Türkçüoğlu I, Kafkasli A, Meydanli MM, Ozyalin F, Taşkapan C. Independent predictors of cardiovascular risk in polycystic ovarian syndrome. Gynecol Endocrinol. 2011;27:915–9.CrossRefPubMed Türkçüoğlu I, Kafkasli A, Meydanli MM, Ozyalin F, Taşkapan C. Independent predictors of cardiovascular risk in polycystic ovarian syndrome. Gynecol Endocrinol. 2011;27:915–9.CrossRefPubMed
24.
Zurück zum Zitat Repaci A, Gambineri A, Pasquali R. The role of low-grade inflammation in the polycystic ovary syndrome. Mol Cell Endocrinol. 2011;335:30–41.CrossRefPubMed Repaci A, Gambineri A, Pasquali R. The role of low-grade inflammation in the polycystic ovary syndrome. Mol Cell Endocrinol. 2011;335:30–41.CrossRefPubMed
25.
Zurück zum Zitat Johnsen SH, Fosse E, Joakimsen O, Mathiesen EB, Stensland-Bugge E, Njølstad I, et al. Monocyte count is a predictor of novel plaque formation: a 7-year follow-up study of 2610 persons without carotid plaque at baseline the Tromsø study. Stroke. 2005;36:715–9.CrossRefPubMed Johnsen SH, Fosse E, Joakimsen O, Mathiesen EB, Stensland-Bugge E, Njølstad I, et al. Monocyte count is a predictor of novel plaque formation: a 7-year follow-up study of 2610 persons without carotid plaque at baseline the Tromsø study. Stroke. 2005;36:715–9.CrossRefPubMed
26.
Zurück zum Zitat Akboga MK, Balci KG, Maden O, Ertem AG, Kirbas O, Yayla C, et al. Usefulness of monocyte to HDL-cholesterol ratio to predict high SYNTAX score in patients with stable coronary artery disease. Biomark Med. 2016;10:375–83.CrossRefPubMed Akboga MK, Balci KG, Maden O, Ertem AG, Kirbas O, Yayla C, et al. Usefulness of monocyte to HDL-cholesterol ratio to predict high SYNTAX score in patients with stable coronary artery disease. Biomark Med. 2016;10:375–83.CrossRefPubMed
27.
Zurück zum Zitat Murphy AJ, Chin-Dusting JPF, Sviridov D, Woollard KJ. The anti inflammatory effects of high density lipoproteins. Curr Med Chem. 2009;16:667–75.CrossRefPubMed Murphy AJ, Chin-Dusting JPF, Sviridov D, Woollard KJ. The anti inflammatory effects of high density lipoproteins. Curr Med Chem. 2009;16:667–75.CrossRefPubMed
28.
Zurück zum Zitat Açıkgöz SK, Açıkgöz E, Şensoy B, Topal S, Aydoğdu S. Monocyte to high-density lipoprotein cholesterol ratio is predictive of in-hospital and five-year mortality in ST-segment elevation myocardial infarction. Cardiol J. 2016;23:505–12.PubMed Açıkgöz SK, Açıkgöz E, Şensoy B, Topal S, Aydoğdu S. Monocyte to high-density lipoprotein cholesterol ratio is predictive of in-hospital and five-year mortality in ST-segment elevation myocardial infarction. Cardiol J. 2016;23:505–12.PubMed
29.
Zurück zum Zitat Cockerill GW, Rye KA, Gamble JR, Vadas MA, Barter PJ. High-density lipoproteins inhibit cytokine-induced expression of endothelial cell adhesion molecules. Arterioscler Thromb Vasc Biol. 1995;15:1987–94.CrossRefPubMed Cockerill GW, Rye KA, Gamble JR, Vadas MA, Barter PJ. High-density lipoproteins inhibit cytokine-induced expression of endothelial cell adhesion molecules. Arterioscler Thromb Vasc Biol. 1995;15:1987–94.CrossRefPubMed
30.
Zurück zum Zitat Guleria AK, Syal SK, Kapoor A, Kumar S, Tiwari P, Dabadghao P. Cardiovascular disease risk in young Indian women with polycystic ovary syndrome. Gynecol Endocrinol. 2014;30:26–9.CrossRefPubMed Guleria AK, Syal SK, Kapoor A, Kumar S, Tiwari P, Dabadghao P. Cardiovascular disease risk in young Indian women with polycystic ovary syndrome. Gynecol Endocrinol. 2014;30:26–9.CrossRefPubMed
Metadaten
Titel
The monocyte counts to HDL cholesterol ratio in obese and lean patients with polycystic ovary syndrome
verfasst von
Akin Usta
Eyup Avci
Cagla Bahar Bulbul
Hasan Kadi
Ertan Adali
Publikationsdatum
01.12.2018
Verlag
BioMed Central
Erschienen in
Reproductive Biology and Endocrinology / Ausgabe 1/2018
Elektronische ISSN: 1477-7827
DOI
https://doi.org/10.1186/s12958-018-0351-0

Weitere Artikel der Ausgabe 1/2018

Reproductive Biology and Endocrinology 1/2018 Zur Ausgabe

Update Gynäkologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert – ganz bequem per eMail.