The Children follow-up study from women with PCOS (CHOPS) was funded in part by the Child Health research programme of the University Medical Center Utrecht. A.M.V. Evelein being part of the Wheezing Illnesses Study Leidsche Rijn (WHISTLER) Study group received funding from The Netherlands Organisation for Health Research and Development, grant number 2100.0095 (ZonMw), the Dutch Asthma Foundation and from Glaxo Smith Kline (no personal grant). This does not alter our adherence to PLOS ONE policies on sharing data and materials. M.A. de Wilde, G.W. Dalmeijer, and M.P.H. Koster have nothing to declare.
To study metabolic/inflammatory biomarker risk profiles in women with PCOS and PCOS offspring.
Cross-sectional comparison of serum biomarkers.
University Medical Center Utrecht.
Hyperandrogenic PCOS women (HA-PCOS, n = 34), normoandrogenic PCOS women (NA-PCOS, n = 34), non-PCOS reference population (n = 32), PCOS offspring (n = 14, age 6–8 years), and a paedriatic reference population (n = 30).
Clustering profile of adipocytokines
The cluster analysis identified leptin, RBP-4, DPP-IV and adiponectin as potential discriminative markers for HA-PCOS with a specifically strong correlation in cases with increased BMI. Leptin (R2 = 0.219) and adiponectin (R2 = 0.182) showed the strongest correlation with the FAI. When comparing median protein concentrations adult PCOS women with or without hyperandrogenemia, the most profound differences were observed for leptin (P < 0.001), DPP-IV (P = 0.005), and adiponectin (P < 0.001). Adjusting for age, BMI and multiple testing attenuated all differences. In PCOS offspring, MMP-9 (P = 0.001) and S100A8 (P < 0.001) concentrations were significantly higher compared to a healthy matched reference population, even after correcting for age and BMI and adjustment for multiple testing.
In this preliminary investigation we observed significant differences in adipocytokines between women with or without hyperandrogenic PCOS and non-PCOS controls, mostly influenced by BMI. Leptin and adiponectin showed the strongest correlation with the FAI in adult women with PCOS. In PCOS offspring other inflammatory biomarkers (MMP-9, S100A8) were increased, suggesting that these children may exhibit increased chronic low-grade inflammation. Additional research is required to confirm results of the current exploratory investigation.
The polycystic ovary syndrome (PCOS) is the most common endocrinopathy amongst women of reproductive age, with a prevalence up to 15%.[
Insulin resistance along with hyperandrogenism appear to play pivotal roles in the pathophysiology of PCOS.[
Current research is therefore increasingly focusing on the discovery of novel biomarker profiles to further elucidate the complex pathophysiology of PCOS.[
The current explorative study was designed to compare metabolic and inflammatory biomarker risk profiles between women with different PCOS phenotypes, offspring of PCOS mothers and reference populations. We hypothesized that metabolic and inflammatory biomarkers may be increased in women with PCOS and PCOS offspring at a young age. In doing so, we focussed on a wide range of tailored biomarkers based on the recent literature also including various closely-related novel biomarkers.
Conduction of the current study was approved by the official Medical Ethical Committee Board of the University Medical Center Utrecht, and conducted according to the principles expressed in the Declaration of Helsinki. All included adult participants provided written informed consent, and written informed parental consent was obtained of all included children. Clinical trials were registered at
We included women with PCOS from a large prospective cohort study on menstrual cycle disturbances within the University Medical Center Utrecht. All women were evaluated through a standardized screening protocol which has been previously described in detail elsewhere.[
We included n = 34 hyperandrogenic women with PCOS (HA-PCOS), who exhibited ovulatory dysfunction, polycystic ovarian morphology and a free androgen index (FAI) > 4.5 [FAI: (Testosterone(nmol/L)/ SHBG(nmol/L)) x100)].[
We included n = 32 women without PCOS with regular menstrual cycles (21–35 days) from a cohort study regarding characteristics of women undergoing IVF/ICSI treatment within the University Medical Center Utrecht.All women included in the reference population were clinically evaluated and definitely classified as non-PCOS, hence composing a non-PCOS reference population. Serum samples were collected prior to the start of fertility treatment.
We included n = 14 children (6–8 years of age) who were born to PCOS mothers, from a cohort study regarding child health of children born to PCOS mothers within the University Medical Center Utrecht. Included children underwent a standardized screening with study procedures identical to those performed in the reference population (see below).[
Fasting serum samples were collected from all participants included in the current study. Serum samples were stored within 4 hours after withdrawal in -80 degrees Celsius.
Serum samples were used to measure the concentrations of 22 proteins, being: IL-1b, IL-6, IL-13, IL-17, IL-18, TNF-α, adiponectin, adipsin, leptin, chemerin, resistin, retinol-binding protein 4 (RBP4), dipeptidyl peptidase IV (DPP-IV/sCD26), monocyte chemotactic protein 1 (CCL2/MCP-1), placental growth factor (PIGF), vascular endothelial growth factor (VEGF), soluble VEGF receptor-1 (sVEGF-R1), soluble intercellular adhesion molecule 1 (sICAM-1/sCD54), soluble vascular cell adhesion molecule 1 (sVCAM-1/sCD106), matrix metallopeptidase 9 (MMP-9), S100A8, Cathepsin S.
Laboratory measurements were performed using an in-house developed and validated multiplex immunoassay based on Luminex technology (xMAP, Luminex Austin TX USA). The assay was performed using previously described methods.[
Study sample size was determined according to availability of serum samples. Basic descriptive statistics were used to describe the patient population.
Kruskal Wallis tests were performed to compare patient characteristics and one-way ANOVA were performed to compare log-transformed biomarker values between HA-PCOS women, NA-PCOS women and non-PCOS women. When this resulted in a P-value < 0.05, pairwise Student’s T-test were used to calculate P-values between specific groups. Next, P-values were adjusted for age and BMI using general linear models, and false discovery rates (FDR) were calculated to correct for multiple testing. In the pediatric populations, Mann-Whitney U tests and Chi-square tests were used to compare baseline characteristics. Student’s t-tests were used to assess differences in log-transformed biomarker concentrations between both groups, including specific sub-analyses for gender. P-values were adjusted for age and BMI using general linear models and FDR was calculated to correct for multiple testing.
Before log-transformation, biomarker values that were below the lower limit of detection were imputed at 35% of the lower detection limit concentration. Values which were above the highest limit of detection were imputed as the highest value of detection concentration plus one pg/ml.
Finally, as described previously, an unsupervised hierarchal clustering analysis, with min-max normalization per protein, was performed to investigate the discriminative potential of a single or a combination of proteins [
All statistical analyses were performed with SPSS Statistics 21.0. Hierarchical cluster analyses were performed using Omniviz 6.1.2 (Instem Scientific).
First, we assessed whether protein concentrations differ between HA-PCOS, NA-PCOS and the non-PCOS reference group. Clinical baseline characteristics of involved study groups are shown in
HA-PCOS (n = 34) | NA-PCOS (n = 34) | non-PCOS (n = 32) | P-value | ||
---|---|---|---|---|---|
0.54 | |||||
Caucasian | 31 (91) | 33 (97) | 28 (90) | ||
Mediterranean | 1 (3) | - | 2 (7) | ||
Indian | 2 (6) | - | - | ||
Black | - | 1 (3) | - | ||
Asian | - | - | 1 (3) | ||
28.5 [23.5–32.5] | 28.8 [25.8–31.2] | 34.5 [30.7–37.7] | < 0.001 |
||
6.7 [5.0–10.2] | 2.0 [1.4–2.6] | - | |||
29.5 [23.3–35.6] | 21.8 [19.8–22.2] | 22.5 [21.2–24.5] | < 0.001 |
||
- | |||||
Idiopathic infertility | - | - | 13 (41) | ||
Male factor | - | - | 15 (47) | ||
Tubal factor | - | - | 2 (6) | ||
Low ovarian reserve | - | - | 1 (3) | ||
Donor semen | - | - | 1 (3) |
PCOS: polycystic ovary syndrome, NA: normoandrogenic, HA: hyperandrogenic, FAI: free androgen index (Testosterone/SHBG)x100), BMI: body mass index, ART: assisted reproduction technology. Values are depicted as medians [interquartile ranges], or absolute numbers (percentages). Depicted variables contained a maximum of 3% missing values. P-values were calculated using Kruskal Wallis ANOVA. When a P-value < 0.05 was detected pairwise Mann Whitney U tests were used to assess differences between specific groups.
a P < 0.05 between HA PCOS and non PCOS.
b P < 0.05 between HA PCOS and NA PCOS.
c P < 0.05 between NA PCOS and non PCOS
In order to assess the discriminative potential of a single or a combination of any marker(s) in HA-PCOS, NA-PCOS and the non-PCOS group, we performed a hierarchical cluster analysis as described by van den Ham et al.[
PCOS: polycystic ovary syndrome, RBP-4: retinol-binding protein 4, DPP-IV/sCD26: dipeptidyl peptidase IV. Phenotype: black represents hyperandrogenic PCOS; White represents non-PCOS reference population. BMI: yellow represents low BMI, red represents high BMI.
RBP4: retinol-binding protein 4, DPP-IV/sCD26: dipeptidyl peptidase IV. PCOS: polycystic ovary syndrome, HA: hyperandrogenic, NA: normoandrogenic, IL: interleukin,, DPP-IV/sCD26: dipeptidyl peptidase IV.
Subsequently, we assessed the correlation between these four potential biomarkers and the FAI, being one of the clinical features of PCOS. The strongest correlations were found for leptin (R2 = 0.219) and adiponectin (R2 = 0.182) as shown in,
RBP-4: retinol-binding protein 4, DPP-IV/sCD26: dipeptidyl peptidase IV.
Next, we compared differences in median protein concentrations between adult PCOS groups (see Tables
HA-PCOS (n = 34) | NA-PCOS (n = 34) | non-PCOS (n = 32) | P-value | |
---|---|---|---|---|
4.5 [0.9–19.5] | 5.4 [1.5–29.2] | 0.9 [0.9–6.6] | ||
95 [52–135] | 75 [47–103] | 87 [61–116] | 0.53 | |
101 [83–139] | 111 [82–136] | 112 [80–152] | 0.25 | |
35 [18–46] | 28 [14–42] | 28 [15–44] | 0.33 | |
0.4 [0.3–0.5] | 0.3 [0.1–0.5] | 0.4 [0.2–0.7] | 0.34 | |
1.8 [1.2–3.1] | 1.3 [0.8–2.2] | 1.7 [0.8–2.4] | 0.16 | |
1.4 [1.2–1.7] | 1.5 [1.4–1.9] | 1.4 [1.1–1.6] | 0.053 | |
2.5 [1.2–4.5] | 0.9 [0.3–4.6] | 2.6 [0.7–5.3] | 0.19 | |
0.4 [0.2–0.4] | 0.3 [0.2–0.4] | 0.3 [0.2–0.4] | 0.31 | |
3.0 [1.4–7.9] | 0.4 [0.3–1.1] | 1.9 [0.7–2.9] | ||
38 [27–54] | 31 [24–39] | 35 [30–45] | ||
43 [39–49] | 41 [37–44] | 41 [36–45] | 0.10 | |
0.8 [0.7–1.0] | 0.9 [0.7–1.0] | 0.7 [0.6–0.8] | ||
0.3 [0.3–0.4] | 0.3 [0.3–0.4] | 0.3 [0.3–0.4] | 0.97 | |
3.7 [3.2–4.5] | 3.8 [3.2–4.5] | 4.0 [3.2–5.1] | 0.42 | |
13 [10–15] | 11 [9–12] | 11 [10–14] | ||
131 [111–219] | 258 [192–362] | 233 [204–285] |
Values represent median concentrations [interquartile ranges]. P-values were calculated with ANOVA on logtransformed values for difference between all groups. PCOS: polycystic ovary syndrome, HA: hyperandrogenic, NA: normoandrogenic, IL: interleukin, CCL2/MCP-1: monocyte chemoattractant protein-1, PIGF: placental growth factor, VEGF: vascular endothelial growth factor, MMP-9: matrix metallopeptidase 9, RBP-4: retinol-binding protein 4, DPP-IV/sCD26: dipeptidyl peptidase IV, sICAM: soluble intercellular adhesion molecule 1, sVCAM: soluble vascular cell adhesion molecule 1. IL-1b, IL-6, IL-17, TNF-α and chemerin are not shown as the majority of samples (>57%) were undetectable measurements evenly distributed amongst the study population.
ANOVA all groups | HA-PCOS vs non-PCOS | HA-PCOS vs NA-PCOS | NA-PCOS vs non-PCOS | |||||||
---|---|---|---|---|---|---|---|---|---|---|
P-value | P-value | adjustedP-value | FDR | P-value | Adjusted P-value | FDR | P-value | Adjusted P-value | FDR | |
0.10 | 0.30 | 0.45 | 0.39 | 0.83 | 0.91 | 0.013 | 0.46 | 0.92 | ||
0.006 | 0.29 | 0.45 | <0.001 | 0.08 | 0.24 | 0.013 | 0.08 | 0.48 | ||
0.72 | 0.42 | 0.50 | 0.010 | 0.40 | 0.60 | 0.021 | 0.92 | 0.92 | ||
0.014 | 0.049 | 0.29 | 0.70 | 0.91 | 0.91 | 0.005 | 0.48 | 0.92 | ||
0.85 | 0.67 | 0.67 | 0.005 | 0.20 | 0.40 | 0.012 | 0.65 | 0.92 | ||
<0.001 | 0.15 | 0.45 | <0.001 | 0.07 | 0.24 | 0.38 | 0.85 | 0.92 |
When a P-value < 0.05 was detected in ANOVA, pairwise T-test on logtransformed biomarkers were used to calculate P-values between specific groups. Furthermore P-values were adjusted for age and BMI, and false discovery rates (FDR) were calculated to correct for multiple testing. PCOS: polycystic ovary syndrome, HA: hyperandrogenic, NA: normoandrogenic, IL: interleukin,, DPP-IV/sCD26: dipeptidyl peptidase IV.
Since such shifted protein profiles as well as certain clinical characteristics (e.g. BMI) are known to be associated with a predisposition for cardiovascular disease, we assessed the identical protein panel in a cross sectional cohort of PCOS offspring and paediatric reference cohort of comparable age and sex, based on the assumption that PCOS offspring may already exhibit an increased cardiometabolic risk at young age. The baseline characteristics of these two groups are shown in
PCOS offspring (n = 14) | Reference group (n = 30) | P-value | ||
---|---|---|---|---|
0.08 | ||||
None | 8 (57) | 25 (86) | ||
Hypertensive complications | 5 (36) | 2 (7) | ||
Gestational diabetes | 1 (7) | - | ||
Infection | 1 (7) | 2 (7) | ||
0.05 | ||||
Vaginal spontaneously | 7 (50) | 23 (79) | ||
Caesarean section | 5 (36) | 6 (21) | ||
Assisted vaginal delivery | 2 (14) | - | ||
40.1 [37.5–40.4] | 40.4 [39.4–41.2] | 0.19 | ||
0.15 | ||||
Yes | 1 (7) | - | ||
No | 13 (93) | 29 (100) | ||
3295 [3061–3651] | 3600 [3200–3940] | 0.27 | ||
Small for gestational age | 1 (7) | 1 (3) | 0.15 | |
Large for gestational age | 2 (14) | 2 (7) | 0.43 | |
0.98 | ||||
Male | 6 (43) | 13 (43) | ||
Female | 8 (57) | 17 (57) | ||
7.0 [6.6–8.1] | 7.8 [7.6–7.9] | 0.09 | ||
15.7 [14.5–16.8] | 14.9 [14.5–16.0] | 0.12 |
Values represent median values [interquartile range] or absolute numbers (percentages) Mann-Whitney U tests or Chi-square tests were used to calculate P-values. Variables contained a maximum of 3% missing values.
PCOS offspring (n = 14) | Reference group (n = 30) | P-value | Adjusted P-value | FDR | |
---|---|---|---|---|---|
8.5 [0.9–37.7] | 16.5 [5.0–77.6] | 0.14 | 0.06 | 0.26 | |
134 [85–196] | 139 [107–188] | 0.64 | 0.73 | 0.78 | |
113 [88–138.] | 134 [100–159] | 0.18 | 0.22 | 0.47 | |
37 [32–59] | 31 [16–69] | 0.17 | 0.29 | 0.53 | |
0.3 [0.1–0.6] | 0.2 [0.1–0.5] | 0.59 | 0.65 | 0.74 | |
1.0 [0.6–2.2] | 0.2 [0.2–0.5] | ||||
1.4 [1.1–1.7] | 1.6 [1.1–2.0] | 0.47 | 0.46 | 0.71 | |
2.7 [0.7–3.1] | 0.0 [0.0–0.1] | ||||
0.3 [0.1–0.3] | 0.3 [0.2–0.3] | 0.71 | 0.96 | 0.96 | |
0.1 [0.0–0.5] | 0.0 [0.0–0.3] | 0.31 | 0.63 | 0.74 | |
26 [21–32] | 22 [19–36] | 0.53 | 0.18 | 0.44 | |
35 [32–37] | 35 [32–40] | 0.20 | 0.05 | 0.26 | |
2.2 [1.8–2.7] | 2.5 [2.0–3.1] | 0.19 | 0.08 | 0.27 | |
0.5[0.4–0.6] | 0.5 [0.4–0.6] | 0.50 | 0.50 | 0.71 | |
7.7 [6.5–10.3] | 6.9 [5.7–9.4] | 0.18 | 0.16 | 0.44 | |
12 [10–13] | 11 [11–13] | 0.42 | 0.31 | 0.53 | |
273 [215–312] | 258 [239–325] | 0.70 | 0.61 | 0.74 |
Values represent median concentrations [interquartile ranges]. P-values were calculated using T-tests on logtransformed biomarkers. Furthermore P-values were adjusted for age and BMI (general linear models), and false discovery rates (FDR) were calculated to correct for multiple testing. PCOS: polycystic ovary syndrome, CCL2/MCP-1: monocyte chemoattractant protein-1, PIGF: placental growth factor, VEGF: vascular endothelial growth factor, MMP-9: matrix metallopeptidase 9, RBP-4: retinol-binding protein 4, DPP-IV/sCD26: dipeptidyl peptidase IV, sICAM1/sCD54: soluble intercellular adhesion molecule 1, sVCAM: soluble vascular cell adhesion molecule 1. IL-1b, IL-6, IL-17, TNF-α and chemerin are not shown as the majority of samples (>57%) were undetectable measurements evenly distributed amongst the study population.
The primary aim of this study was to compare metabolic/inflammatory biomarker risk profiles between women with different PCOS phenotypes, PCOS offspring and reference populations. We selected specific adipocytokines
Adipocytokines are known to affect vascular endothelium by stimulating the migration of monocytes into the vessel wall, and inducing the conversion of monocytes into macrophages.[
When comparing women with PCOS to a non-PCOS reference population, we found significant differences in several adipocytokines, which were mostly influenced by BMI. Leptin and adiponectin appeared the most discriminative markers in women with PCOS, both showing the strongest correlation with the FAI. This finding corroborates with previous studies in which these adipocytokines were correlated with metabolic complications in women with PCOS.[
Adiponectin is secreted in adipose tissue and exerts anti-atherogenic, anti-inflammatory and insulin-sensitizing effects.[
We observed no significant differences in other inflammatory biomarkers between women with and without PCOS (e.g. interleukins, TNF-α, resistin, MMP-2, MMP-9, MCP-1), as opposed to what has previously been reported by others.[
Contrary to adult PCOS, we did observe significantly higher concentrations of MMP-9 and S100A8 in PCOS offspring, compared to the reference population. Increased circulating MMP-9 concentrations have been previously reported in adult women with PCOS.[
To our knowledge, the possible role of circulating S100A8 in women with PCOS or PCOS offspring has not been previously addressed. S100A8 is known as a damage-associated molecular pattern (DAMP) molecule because of its pro-inflammatory actions, and is secreted in response to cell damage, death, and stress.[
In PCOS offspring we did not observe a difference in adipocytokines compared to the reference group. This might be due to an absence of overweight and insulin resistance in these young prepuberal children. As children enter puberty, insulin resistance may develop in response to growth hormone secretion which induces accelerated growth during puberty.[
To our knowledge, this is the first study in which metabolic/inflammatory biomarkers were simultaneously assessed both in adult women with PCOS as well as PCOS offspring. Further strengths of this study are the large tailored series of potentially relevant biomarkers which were assessed in a well-phenotyped patient population, and the use of a validated multiplex immunoassay with standardized technology which has been repeatedly described before.[
Limitations of the current study are the relatively small sample size, and the characteristics of the reference populations. The current study was performed with a relatively limited sample size, especially concerning PCOS offspring. Therefore, reported results in these children may be regarded as preliminary and require validation in a larger cohort. The adult reference population consisted of women who were planned to undergo IVF/ICSI treatment, and therefore might not be considered as entirely healthy controls despite the fact that these women had regular menstrual cycles. However, post-hoc analyses including only women with infertility due to a male factor did not significantly alter results (data not shown). Moreover, all women included in the adult reference population were clinically evaluated and definitely classified as non-PCOS. Although the paediatric reference population was clinically well defined, there was no detailed reproductive history data available of their mothers and therefore PCOS could not be excluded. Hence, it is possible that observed differences in protein concentrations between PCOS offspring and the reference group in the current study may be underestimated.
In summary, we observed differences in adipocytokines between women with normoandrogenic and hyperandrogenic PCOS and women without PCOS, which were influenced by BMI. Leptin and adiponectin showed the strongest correlation with the FAI. Since these biomarkers are directly correlated with more easy assessable classical risk factors such as obesity and insulin resistance, routine assessment of these markers at this point may contribute little to the conventional risk assessment in women with PCOS.
In PCOS offspring other inflammatory biomarkers were higher, suggesting that these young children may exhibit increased risk of chronic low-grade inflammation. Although these results require validation in a larger cohort study, these findings may be of importance for future appliance of primary prevention measures. Foremost,longitudinal follow-up studies with repeated measurements are needed in order to assess the potential association between biomarker profiles, the development of PCOS and actual cardiovascular disease in later life.
PCOS: polycystic ovary syndrome, IL: interleukin, CCL2/MCP-1: monocyte chemoattractant protein-1, PIGF: placental growth factor, VEGF: vascular endothelial growth factor, MMP-9: matrix metallopeptidase 9, RBP-4: retinol-binding protein 4, DPP-IV/sCD26: dipeptidyl peptidase IV, sICAM: soluble intercellular adhesion molecule 1, sVCAM: soluble vascular cell adhesion molecule 1. IL-1b, IL-6, IL-17, TNF-α and chemerin are not shown as the majority of samples (>57%) were undetectable measurements evenly distributed amongst the study population. Phenotype: black represents hyperandrogenic PCOS; White represents non-PCOS reference population. BMI: yellow represents low BMI, red represents high BMI.
(TIF)
PCOS: polycystic ovary syndrome, IL: interleukin, CCL2/MCP-1: monocyte chemoattractant protein-1, PIGF: placental growth factor, VEGF: vascular endothelial growth factor, MMP-9: matrix metallopeptidase 9, RBP-4: retinol-binding protein 4, DPP-IV/sCD26: dipeptidyl peptidase IV, sICAM: soluble intercellular adhesion molecule 1, sVCAM: soluble vascular cell adhesion molecule 1. IL-6, and chemerin are not shown as > 95% were undetectable measurements evenly distributed amongst the study population. Black represents PCOS offspring, white represents reference population.
(TIF)