|Year : 2022 | Volume
| Issue : 3 | Page : 250-258
Correlation of markers of inflammation with hormonal, metabolic parameters, insulin resistance and adiposity indices in first-degree relatives of patient with polycystic ovary syndrome.
Jeeban Pradhan1, Ipsita Mishra1, Roma Rattan2, Arun Kumar Choudhury1, Anoj Kumar Baliarsinha1
1 Department of Endocrinology, S.C.B Medical College, Cuttack, Odisha, India
2 Department of Biochemistry, S.C.B Medical College, Cuttack, Odisha, India
|Date of Submission||29-Jul-2022|
|Date of Decision||02-Sep-2022|
|Date of Acceptance||02-Sep-2022|
|Date of Web Publication||30-Sep-2022|
Dr. Ipsita Mishra
Department of Endocrinology, S.C.B Medical College, Cuttack - 753 007, Odisha
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Polycystic ovary syndrome (PCOS) is a state of chronic low-grade inflammation. Low-grade inflammation has been linked to the development of cardiovascular disease (CVD). There is evidence of clustering for metabolic syndrome, hypertension, dyslipidaemia in type 2 diabetes mellitus and insulin resistance (IR) in mothers, fathers, sisters and brothers of women with PCOS. Aims: The aim is to study the levels of inflammatory markers and IR in first-degree relatives of patients with PCOS and find any correlation with hormonal parameters, metabolic parameters and adiposity indices in them. Settings and Design: A total of 66 first-degree relatives of a patient with PCOS were included in this cross-sectional study. Materials and Methods: All participants underwent detailed clinical evaluation and biochemical investigations, including high-sensitivity C-reactive protein (hsCRP), interleukin 6 (IL-6), luteinising hormone (LH), follicle-stimulating hormone (FSH) and total testosterone (only in females). Homeostasis model assessment of IR (HOMA-IR), lipid accumulation product and visceral adiposity index were calculated using standard equations. Visceral adipose tissue thickness and subcutaneous adipose tissue thickness were assessed using ultrasonography. Statistical Analysis Used: Spearman's and Pearson's correlation coefficients were used to analyse the correlation between different non-parametric and parametric data, respectively. Multiple linear regression was used to correlate multiple dependent factors. Results: The mean hs-CRP level was 2.4 ± 1.1 mg/L, which is greater than the cut-off of 2 mg/L and hs-CRP >2 mg/L was found in 62% (n = 41) participants. The mean IL-6 (3.5 ± 1.1 pg/ml) and total white blood cell count (7244 ± 2190/mm3) were in the normal range. The mean HOMA-IR was 2.35 ± 0.76, which is elevated, considering HOMA IR >2 as a predictor of IR and metabolic syndrome. HOMA IR >2 was found in 64% (n = 42) of the participants. Inflammatory markers were significantly correlated with LH and HOMA IR, even after multiple linear regression was fitted for each marker individually. Conclusion: Apparently, healthy first-degree relatives of PCOS patients had evidence of chronic low-grade inflammation. The chronic inflammation in them correlated well with HOMA-IR and LH but was independent of body mass index. This low-grade inflammation may predispose the first-degree relatives of PCOS to CVD.
Keywords: First-degree relatives, Homeostasis model assessment of insulin resistance, high-sensitivity C-reactive protein, interleukin 6, polycystic ovary syndrome
|How to cite this article:|
Pradhan J, Mishra I, Rattan R, Choudhury AK, Baliarsinha AK. Correlation of markers of inflammation with hormonal, metabolic parameters, insulin resistance and adiposity indices in first-degree relatives of patient with polycystic ovary syndrome. J Hum Reprod Sci 2022;15:250-8
|How to cite this URL:|
Pradhan J, Mishra I, Rattan R, Choudhury AK, Baliarsinha AK. Correlation of markers of inflammation with hormonal, metabolic parameters, insulin resistance and adiposity indices in first-degree relatives of patient with polycystic ovary syndrome. J Hum Reprod Sci [serial online] 2022 [cited 2022 Nov 28];15:250-8. Available from: https://www.jhrsonline.org/text.asp?2022/15/3/250/357666
| Introduction|| |
Polycystic ovary syndrome (PCOS) is a heterogeneous disorder with a prevalence varying between 6% and 20%, possibly making this syndrome the most common endocrine and metabolic disorder in women of reproductive age.,, Various criteria have been laid to diagnose PCOS, out of which the most commonly used is the Rotterdam criteria, according to which, after excluding disorders which mimic PCOS, the diagnosis of PCOS is made if any 2 out of three following criteria are met: androgen excess, ovulatory dysfunction, or ultrasonographic appearance of polycystic ovarian morphology. The incidence of PCOS is on the rise and this is probably going to be the most common disorder leading to chronic anovulation.
PCOS not only includes disorders related to anovulation and reproduction but, association of various metabolic disorders, such as hyperinsulinaemia, insulin resistance (IR), glucose intolerance, dyslipidaemia, obesity and non-alcoholic fatty liver disease along with it., Recently, it has been observed that women with PCOS have raised levels of inflammatory markers. In these women, C-reactive protein (CRP), and various cytokines such as interleukin 6 (IL-6), interleukin 18, tumour necrosis factor-α, etc., were found to be elevated., Chronic low-grade inflammation, associated with obesity and IR has been implicated as a risk factor for endothelial dysfunction, atherosclerosis and coronary heart disease., Visceral obesity is associated with IR, glucose intolerance, diabetes mellitus, increase in androgen production rate and decreased levels of sex hormone-binding globulin that leads to increased levels of free testosterone. Visceral obesity, in contrast to general obesity, is a more specific risk factor for PCOS. However, IR and androgen excess are not confined to obese anovulatory women but also occur in nonobese anovulatory women. It has been observed that in comparison to women with isolated obesity and IR, women with PCOS along with obesity and IR have higher levels of inflammatory markers.
There is the clustering of PCOS in families, which suggests that it has an underlying genetic basis., Family studies of PCOS investigated mainly ovarian morphology, menstrual irregularities, symptoms of hyperandrogenism and hyperandrogenaemia.,,,,,,, In a Dutch twin-family study, the tetrachoric correlation between monozygotic twins for PCOS was 0.71, and for dizygotic twin or non-twin sister pairs, the correlation was 0.38. In the Han Chinese population, genome-wide PCOS association signals showed evidence of enrichment for candidate genes related to insulin signalling (INSR), gonadotropin receptors (FSHR, LHCGR), and type 2 diabetes (HMGA2, THADA, DENND1A). Few meta-analyses do show evidence of clustering for metabolic syndrome, hypertension, dyslipidaemia, type 2 diabetes mellitus (T2DM) and IR in mothers, fathers, sisters and brothers of women with PCOS.,
A recent study in India showed the presence of metabolic syndrome or related metabolic derangements to be high in the family members of women with PCOS. Although limited, the available evidence raises the hypothesis that first-degree relatives of women with PCOS are at risk of having increased markers of inflammation along with IR and altered hormonal profile. Thus, we propose this study to be the first of its kind to study the correlation of markers of inflammation and IR with hormonal, metabolic parameters and adiposity indices in first-degree relatives of a patient with PCOS.
| Materials and Methods|| |
Study design and population
This cross-sectional study was conducted at an academic institute. The study was approved by the institutional ethics committee (IEC Appln no. 248/26 August 2020). Ethical principles of the World Medical Association Declaration of Helsinki (2013) were adhered to while conducting the study.
Father, mother, brothers and sisters of patients with a confirmed diagnosis of PCOS by Rotterdam criteria, either newly diagnosed or on follow-up, who were accompanying the patient or were available for evaluation were screened for inclusion in the study.
Relatives with a diagnosis of diabetes mellitus, coronary artery disease, cerebrovascular disease, chronic kidney disease and chronic liver disease, presence of PCOS in sisters and mothers, any acute or chronic infection, any history of connective tissue disorders or other inflammatory disorder, relatives with any type of malignancy (ca. breast, ca. endometrium, ca. ovary, ca. prostate, ca. lungs, etc.), pregnant and lactating women, alcoholics and smokers were excluded from the study. Furthermore, relatives with current or previous use (within 6 months) of glucocorticoids, non-steroidal anti-inflammatory drugs, oral contraceptives, anti-androgens, anti-diabetics, statins or other hormonal drugs were excluded from the study.
After applying the above inclusion and exclusion criteria, 66 first-degree family members of PCOS patients could be enrolled in the current study. The number of participants in this study fulfilled the minimum number of samples needed for research in a health study of 30 samples. Hence, the data generated are expected to be normally distributed in calculating statistics. The study participants were explained in detail about the disorder of the patient, the implication of the same in first-degree relatives, purpose of the study and the work up plan. A valid consent was taken from the patients and relatives included, followed by a detailed history, physical examination and basic biochemical evaluation. After applying the exclusion criteria, the participants were qualified for further evaluation in inflammatory markers, hormonal parameters and USG to determine subcutaneous and visceral adiposity.
A detailed history was taken, including history suggestive of hyperandrogenism in female relatives and a history of early onset androgenetic alopecia in male relatives. History of all relevant diseases and medication use was obtained.
Physical examination included vitals, anthropometry, general examination and systemic examination. Height, weight, waist circumference (WC) and hip circumference were measured with participants in light clothes and without shoes using standard protocols. Body mass index (BMI) was calculated as weight in kg divided by the square of height in metres. Weight classification by BMI for Asians was used in the study; BMI <17.5 kg/m2 (underweight), 17.5–22.9 kg/m2 (normal weight), 23–27.4 kg/m2 (overweight) and ≥27.5 kg/m2 (obesity). Further obesity was classified as BMI 27.5–32.4 kg/m2 (Obesity Class I), 32.5–37.5 kg/m2 (Obesity Class II) and ≥ 37.5 kg/m2 (Obesity Class II).
Using the American Diabetic Association (ADA) recommendations, impaired fasting glucose (IFG) was defined as fasting plasma glucose (FPG) 100 mg/dL to 125 mg/dL and impaired glucose tolerance was defined as 2 h PGPG during 75-g OGTT as140 mg/dL to 199 mg/dL. Metabolic syndrome was defined by using revised NCEP ATP III criteria which require at least three of the following components: (1) abdominal obesity (WC ≥90 cm for men, or ≥80 cm for women); (2) triglycerides ≥150 mg/dL, and/or drug treatment for elevated triglycerides; (3) high-density lipoprotein (HDL)-cholesterol <40 mg/dL for men, or <50 mg/dL for women; (4) systolic blood pressure (BP) ≥130 mmHg or diastolic BP ≥85 mmHg or antihypertensive medication treatment, and/or a history of hypertension and (5) FPG ≥100 mg/dL. The cut-off point for homeostasis model assessment of IR (HOMA-IR) in non-diabetic individuals was considered two taking occurrence of metabolic syndrome in various studies.,, High-sensitivity CRP (hs-CRP) <2.0 mg/L was considered low risk for cardiovascular disease (CVD) based on recent guidelines.,
In all study participants, blood samples were collected for fasting insulin, fasting glucose, 2 h PGPG, fasting lipid profile, liver function test, renal function test, thyroid function test and complete blood count. After review of history, examination and basic biochemical evaluation those patients who qualified for further evaluation, for them blood samples were collected for hsCRP, IL-6, luteinising hormone (LH), follicle-stimulating hormone (FSH) and total testosterone (only in females). Hormonal evaluation was done on 2nd or 3rd days of menstrual cycle. Serum insulin, LH, FSH, total testosterone and IL-6 assay were measured using automated electrochemiluminescence immunoassay method (cobas e 411 analyser, Roche Diagnostics International Ltd). hs-CRP was measured by particle enhanced immunoturbidimetric test (AU480 Chemistry Analyzer, Beckman Coulter).
Trans-abdominal ultrasound was performed using a high-resolution B-mode Ultrasound system (SAMSUNG HS70A) by a single experienced investigator. On the same sitting adipose tissue depots were estimated. Both subcutaneous adipose tissue and visceral adipose tissue (VAT) were assessed twice and were calculated as the average of the two measurements.
- HOMA IR as a marker of IR was calculated as (FPG in mg/dl X fasting insulin in mU/L)/405.
- Lipid accumulation product (LAP) Index was calculated as:
- LAP for women = (WC [cm]-58) × (TG concentration [mmol/L]
- LAP for men = (WC [cm]-65) × (TG concentration [mmol/L])
- Visceral adiposity index (VAI) was calculated as:
where WC is in cm, BMI in Kg/m2, TG in mmol/L and HDL in mmol/L.
Descriptive statistical methods such as mean and standard deviation were applied to summarise continuous variables. Categorical data were summarised as percentages or proportion. Normality distribution of all parameters was checked using Shapiro–Wilk test. Parametric tests (independent t-test) and non-parametric test (Mann–Whitney U-test) were performed as required. Spearman's and Pearson's correlation coefficient were used to analyse correlation between different nonparametric and parametric data, respectively. Multiple linear regression was used to correlate multiple dependent factors. The data were analysed using IBM SPSS 26 statistical software. Graphs and charts were generated using IBM SPSS 26 software and Microsoft Excel 2019 (SPSS Inc., IBM Corporation, Armonk, New York, United States).
| Results|| |
A total of 66 participants were included in the study, of which 38% (n = 25) were male and 62% (n = 41) were female. The mean BMI of the study group was 25.9 ± 3.7 kg/m2. 23% (n = 15) of participants were found to have normal weight, 48% (n = 32) were overweight and 29% (n = 19) were obese [Table 1]. The mean SBP was 126.6 ± 10.77 mm of Hg and mean diastolic blood pressure (DBP) is 78.5 ± 6.9 mm of Hg. Systolic hypertension was present in 36% (n = 24) participants and diastolic hypertension was present in 20% (n = 13) of participants [Table 1]. Mean FPG and 2 h PGPG were 94.8 ± 11.3 mg/dl and 113.3 ± 21.7 mg/dl, respectively. 32% (n = 21) of participants had IFG and 15% (n = 10) of participants had impaired glucose tolerance [Table 1]. The mean lipid profile parameters were within normal range. In our study, 42% (n = 28) participants had metabolic syndrome. The mean HOMA-IR was 2.35 ± 0.76 which is elevated and HOMA-IR >2 was found in 64% (n = 42) of the participants, showing mild degree of IR [Table 1]. The mean LH and FSH were 7.5 ± 2.3 mIU/ml and 7.8 ± 1.9 mIU/ml, respectively, which are within normal range for female of reproductive age and males [Table 1]. The mean Total Testosterone levels in female participants was 30.5 ± 9.4 ng/dl [Table 1]. The mean hs-CRP level was 2.4 ± 1.1 mg/L which is greater than the cut off of 2 mg/L. The mean IL-6 was 3.5 ± 1.1 pg/ml and total white blood cell (TWBC) counts were 7244 ± 2190/ml which were in normal range though in the upper half of normal limits [Table 1].
|Table 1: Clinical, anthropometric, biochemical and hormonal parameters in study subjects|
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The study group was stratified according to BMI into normal weight, overweight and obese categories [Table 2]. The VAT thickness was higher in higher BMI categories and difference between the groups was statistically significant (P = 0.049). The LAP index was also higher in higher BMI categories and difference between the groups was statistically significant (P < 0.001). When the participants were grouped according to the hs-CRP cut off of 2 mg/L [Table 3], the HDL levels were significantly lower among those with hs-CRP levels ≥2 mg/L (P = 0.02). Fasting insulin levels and HOMA IR were significantly higher in the participants with hs-CRP levels ≥2 mg/L (P < 0.001) and (P = 0.001) respectively. We also found that mean serum LH was significantly higher in the participants with hs-CRP levels ≥2 mg/L (P = 0.001).
|Table 2: Comparison of Clinical, anthropometric, biochemical, hormonal parameters and adiposity indices between normal weight (body mass index 17.5-22.9), overweight (body mass index 23.0-27.4) and obese (body mass index ≥27.5) study subjects|
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|Table 3: Clinical, anthropometric, biochemical, hormonal parameters and adiposity indices with high sensitivity C-reactive protein cut-off of 2 mg/L|
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In our study, hs-CRP correlated negatively and significantly with HDL (r = −0.34, P = 0.005). There was significant positive correlation of hs-CRP with fasting Insulin (r = 0.59, P < 0.001), HOMA IR (r = 0.57, P < 0.001), LH (r = 0.58, P < 0.001) and VAI (r = 0.27, P = 0.028) [Table 4]. In multiple linear regression analysis with hs-CRP as dependent variable LH and HOMA-IR contributed significantly to the model (β=0.192, P = 0.004) and (β =0.485, P = 0.007), respectively, but HDL and VAI did not (β = −0.015, P = 0.377) and (β =0.061, P = 0.674), respectively [Table 5]. IL-6 correlated negatively and significantly with HDL (r = −0.24, P = 0.045). There was significant positive correlation of IL-6 with fasting insulin (r = 0.55, P < 0.001), HOMA IR (r = 0.55, P < 0.001) and LH (r = 0.49, P < 0.001) [Table 4]. In multiple linear regression analysis with IL-6 as dependent variable LH and HOMA IR contributed significantly to the model (β = 0.130, P = 0.043) and (β =0.601, P = 0.002) m respectively, but HDL did not (β = 0.001, P = 0.919) [Table 5]. There was significant positive correlation of TWBC count with fasting insulin (r = 0.48, P < 0.001), HOMA IR (r = 0.46, P < 0.001) and LH (r = 0.52, P < 0.001) [Table 4]. In multiple linear regression analysis with TWBC count as dependent variable LH contributed significantly to the model (β = 383, P = 0.004), but HOMA IR did not (β = 734, P = 0.055) [Table 5].
|Table 4: Correlation of Infl ammatory markers with clinical, anthropometric, biochemical, hormonal parameters and adiposity indices|
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| Discussion|| |
In our study, we have correlated the markers of inflammation with hormonal, metabolic parameters and adiposity indices in first-degree relatives of patient with PCOS. We found that inflammatory markers hs-CRP, IL-6 and TWBC all are elevated in first-degree relatives of PCOS patient. HOMA-IR was also elevated, showing the presence of IR. Inflammatory markers were significantly correlated with LH and HOMA-IR even after multiple linear regression was fitted for each marker individually which indicates that each of them individually contributes to the increased inflammation.
In our study, 52% of participants were either overweight or obese, similar findings were reported in studies by Sasidevi et al., Yildiz et al. and Shabir, et al.,, Systolic hypertension was present in 36% participants and diastolic hypertension was present in 20% of participants in our study population. In a meta-analysis by Yilmaz et al. mothers, sisters and brothers of PCOS patient had significantly higher SBP than control, whereas fathers had similar SBP to that of controls, whereas diastolic BP was comparable between all the first-degree relatives and controls. In the study by Shabir et al. SBP (>130 mmHg) was found in 27% and DBP (>85 mmHg) was found in 27% of first-degree relatives of PCOS patients. These findings suggest that first-degree relatives of PCOS patient are at predisposed to hypertension which increases the risk of CVD. In our study, the mean glycaemic parameters of FPG and 2 h PGPG were 94.8 ± 11.3 mg/dl and 113.3 ± 21.7 mg/dl, respectively. We found 32% of participants had IFG and 15% of participants had impaired glucose tolerance. As the study was designed to evaluate the low-grade chronic inflammation and other metabolic parameters in apparently healthy first-degree relatives of PCOS, all presenting diabetes mellitus patients were excluded. In a similar study by Yildiz et al. glucose intolerance in 33% of Motherpcos group, 31% of FatherPCOS group, 5% in SistersPCOS group, and 4% in the BrothersPCOS group were found. In another study by Yılmaz et al., the prevalence of any degree of glucose intolerance was 40% in MothersPCOS and 52% in FathersPCOS group. The above findings suggest that first-degree relatives of PCOS patient are having increased prevalence of IFG/IGT. According to ADA history of PCOS is considered criteria for screening of T2DM. Therefore, further large-scale studies are required to find out whether first-degree relatives having a family history of PCOS can be considered a screening criterion or not.
In our study, 42% of participants had metabolic syndrome. In a meta-analysis by Yilmaz et al., mothers, sisters and fathers of PCOS patients had a significantly higher prevalence of Metabolic syndrome than controls. Although brothers of PCOS had a higher prevalence of MetS yet, it did not reach statistical significance. In another Indian study by Shabir et al. at 46% of first-degree relatives of PCOS had Metabolic syndrome. In the study by Shabir et al., maximum participants (PCOS women as well as family members) had dyslipidaemia in the form of low HDL and high triglycerides. Increased levels of LDL cholesterol along with MetS in affected sisters of women with PCOS were reported by Sam et al., We found the mean HOMA IR was 2.35 ± 0.76, showing a mild presence of IR. In our study, HOMA IR >2 was found in 64% (n = 42) of the participants. Various studies have shown the presence of higher HOMA IR among first-degree relatives of PCOS patients in comparison to controls., We found among the study participants, 32% (n = 21) had acanthosis nigricans in neck and 44% (n = 29) had acanthosis nigricans in axilla. Thus, there was a higher prevalence of metabolic syndrome in first-degree relatives of PCOS patients.
In our study, the mean LH and FSH were 7.5 ± 2.3 mIU/ml and 7.8 ± 1.9 mIU/ml, respectively, which are within the normal range for a female of reproductive age and males. The mean total testosterone levels in female participants, i.e., 30.5 ± 9.4 ng/dl. Our study was designed to exclude first-degree relatives who had PCOS in order to evaluate the metabolic parameters and inflammatory markers in the apparently healthy individual. Therefore, probably the gonadotropins and total testosterone were within the normal range in our study participants. Few of similar studies have shown higher LH and total testosterone in first-degree relatives of PCOS in comparison to controls, but those studies included all the participants irrespective of the presence of clinical features of PCOS in relatives, which could explain the variation from our results.,
Atherosclerosis is an inflammatory disease, and hs-CRP has been endorsed by multiple guidelines as a biomarker of atherosclerotic CVD risk., A large prospective clinical trial demonstrated significantly less cardiovascular risk for patients with hs-CRP <2.0 mg/L. In the present study, the mean hs-CRP level was 2.4 ± 1.1 mg/L, which is greater than the cut-off of 2 mg/L, showing the presence of a mild degree of inflammation. The mean IL-6 and TWBC counts in our study were in the normal range though in the upper half of normal limits. In a similar study by Vipin et al. from India, the mean hs-CRP levels were >2 mg/L in first-degree relatives of PCOS, but it was not significantly higher than in controls. These results show that the chronic inflammatory state of PCOS is heritable, and the factors responsible for this in PCOS patient are also present in the first-degree relatives of the same.
To the best of our knowledge, probably, this is the first Indian study to analyse the correlation of inflammatory markers with hormonal, metabolic parameters and adiposity indices in first-degree relatives of PCOS patients. Our findings show that inflammatory markers were significantly correlated with LH and HOMA IR even after multiple linear regression was fitted for each marker individually. This suggests that the higher LH levels (though within normal range) and IR are significant contributors to the state of chronic inflammation, though there is a possibility that these findings are due to intrinsic multigenic abnormality associated with PCOS.
The study had some limitations, one being the absence of a control group to compare and show that there is a significant difference in the findings. However, we were able to compare many key parameters with the established cut-off values available for the standard population. Second, was the small sample size of the study, but our sample size was similar to many of the published studies of similar nature. Third, was despite a proper history, examination and basic investigations done to rule out all causes of acute and chronic inflammatory state few rarer causes may have been missed, which may have affected the results. Fourth, the free androgen index could have been used to better represent the testosterone levels in female participants. Fifth, was the gold standard test for insulin sensitivity, i.e., hyperinsulinaemic euglycaemic clamp was not used in the study; instead, we relied on HOMA IR. However, many published studies have correlated well between the HOMA IR cut-off used in our study with metabolic syndrome, dysglycaemia and CVD. Despite the above limitations, our study was the first of its kind to correlate the various clinical, anthropometric, biochemical, hormonal parameters and adiposity indices in first-degree relatives of PCOS patients.
| Conclusions|| |
We demonstrated that first-degree relatives of PCOS patients had evidence of chronic low-grade inflammation. The chronic inflammation in them correlated well with HOMA IR and LH but were independent of BMI, suggesting the source of inflammation in these participants is not due to altered adipose tissue dysfunctions alone. This low-grade inflammation may predispose the first-degree relatives of PCOS to CVD and future well-controlled, larger studies are required to prove this association and find the mechanisms behind the above findings.
The authors would like to thank all participants for their cooperation.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
Data availability statement
The data that support the findings of the study are available from the author, upon reasonable request.
| References|| |
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 2012;27:3067-73.
Conway G, Dewailly D, Diamanti-Kandarakis E, Escobar-Morreale HF, Franks S, Gambineri A, et al.
The polycystic ovary syndrome: A position statement from the European Society of Endocrinology. Eur J Endocrinol 2014;171:P1-29.
Carmina E, Lobo RA. Polycystic ovary syndrome (PCOS): Arguably the most common endocrinopathy is associated with significant morbidity in women. J Clin Endocrinol Metab 1999;84:1897-9.
Legro RS, Arslanian SA, Ehrmann DA, Hoeger KM, Murad MH, Pasquali R, et al.
Diagnosis and treatment of polycystic ovary syndrome: An endocrine society clinical practice guideline. J Clin Endocrinol Metab 2013;98:4565-92.
Apridonidze T, Essah PA, Iuorno MJ, Nestler JE. Prevalence and characteristics of the metabolic syndrome in women with polycystic ovary syndrome. J Clin Endocrinol Metab 2005;90:1929-35.
Rocha AL, Faria LC, Guimarães TC, Moreira GV, Cândido AL, Couto CA, et al.
Non-alcoholic fatty liver disease in women with polycystic ovary syndrome: Systematic review and meta-analysis. J Endocrinol Invest 2017;40:1279-88.
Kelly CC, Lyall H, Petrie JR, Gould GW, Connell JM, Sattar N. Low grade chronic inflammation in women with polycystic ovarian syndrome. J Clin Endocrinol Metab 2001;86:2453-5.
González F, Rote NS, Minium J, Kirwan JP. Reactive oxygen species-induced oxidative stress in the development of insulin resistance and hyperandrogenism in polycystic ovary syndrome. J Clin Endocrinol Metab 2006;91:336-40.
Kirschner MA, Samojlik E, Drejka M, Szmal E, Schneider G, Ertel N. Androgen-estrogen metabolism in women with upper body versus lower body obesity. J Clin Endocrinol Metab 1990;70:473-9.
Morales AJ, Laughlin GA, Bützow T, Maheshwari H, Baumann G, Yen SS. Insulin, somatotropic, and luteinizing hormone axes in lean and obese women with polycystic ovary syndrome: Common and distinct features. J Clin Endocrinol Metab 1996;81:2854-64.
Phelan N, O'Connor A, Kyaw Tun T, Correia N, Boran G, Roche HM, et al.
Leucocytosis in women with polycystic ovary syndrome (PCOS) is incompletely explained by obesity and insulin resistance. Clin Endocrinol (Oxf) 2013;78:107-13.
Cooper HE, Spellacy WN, Prem KA, Cohen WD. Hereditary factors in the Stein-Leventhal syndrome. Am J Obstet Gynecol 1968;100:371-87.
Ferriman D, Purdie AW. The inheritance of polycystic ovarian disease and a possible relationship to premature balding. Clin Endocrinol (Oxf) 1979;11:291-300.
Hague WM, Adams J, Reeders ST, Peto TE, Jacobs HS. Familial polycystic ovaries: A genetic disease? Clin Endocrinol (Oxf) 1988;29:593-605.
Franks S, Gharani N, Waterworth D, Batty S, White D, Williamson R, et al.
The genetic basis of polycystic ovary syndrome. Hum Reprod 1997;12:2641-8.
Lunde O, Magnus P, Sandvik L, Høglo S. Familial clustering in the polycystic ovarian syndrome. Gynecol Obstet Invest 1989;28:23-30.
Legro RS, Driscoll D, Strauss JF 3rd
, Fox J, Dunaif A. Evidence for a genetic basis for hyperandrogenemia in polycystic ovary syndrome. Proc Natl Acad Sci U S A 1998;95:14956-60.
Kahsar-Miller MD, Nixon C, Boots LR, Go RC, Azziz R. Prevalence of polycystic ovary syndrome (PCOS) in first-degree relatives of patients with PCOS. Fertil Steril 2001;75:53-8.
Govind A, Obhrai MS, Clayton RN. Polycystic ovaries are inherited as an autosomal dominant trait: Analysis of 29 polycystic ovary syndrome and 10 control families. J Clin Endocrinol Metab 1999;84:38-43.
Carey AH, Chan KL, Short F, White D, Williamson R, Franks S. Evidence for a single gene effect causing polycystic ovaries and male pattern baldness. Clin Endocrinol (Oxf) 1993;38:653-8.
Vink JM, Sadrzadeh S, Lambalk CB, Boomsma DI. Heritability of polycystic ovary syndrome in a Dutch twin-family study. J Clin Endocrinol Metab 2006;91:2100-4.
Shi Y, Zhao H, Shi Y, Cao Y, Yang D, Li Z, et al.
Genome-wide association study identifies eight new risk loci for polycystic ovary syndrome. Nat Genet 2012;44:1020-5.
Yilmaz B, Vellanki P, Ata B, Yildiz BO. Metabolic syndrome, hypertension, and hyperlipidemia in mothers, fathers, sisters, and brothers of women with polycystic ovary syndrome: A systematic review and meta-analysis. Fertil Steril 2018;109:356-64.e32.
Yilmaz B, Vellanki P, Ata B, Yildiz BO. Diabetes mellitus and insulin resistance in mothers, fathers, sisters, and brothers of women with polycystic ovary syndrome: A systematic review and meta-analysis. Fertil Steril 2018;110:523-33.e14.
Shabir I, Ganie MA, Zargar MA, Bhat D, Mir MM, Jan A, et al.
Prevalence of metabolic syndrome in the family members of women with polycystic ovary syndrome from North India. Indian J Endocrinol Metab 2014;18:364-9.
Melmed S, Auchus RJ, Goldfine AB, Koenig R, Rosen CJ. Obesity. In: Williams Textbook of Endocrinology. 14th
ed., Vol. 2020. Philadelphia, PA: Elsevier; 2020. p. 1568.
American Diabetes Association Professional Practice Committee. 2. Classification and diagnosis of diabetes: Standards of medical care in diabetes-2022. Diabetes Care 2022;45:S17-38.
Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al.
Harmonizing the metabolic syndrome: A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009;120:1640-5.
Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, García F, De Francisco A, et al.
Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: Effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord 2013;13:47.
Esteghamati A, Ashraf H, Khalilzadeh O, Zandieh A, Nakhjavani M, Rashidi A, et al.
Optimal cut-off of homeostasis model assessment of insulin resistance (HOMA-IR) for the diagnosis of metabolic syndrome: Third national surveillance of risk factors of non-communicable diseases in Iran (SuRFNCD-2007). Nutr Metab (Lond) 2010;7:26.
Lee CH, Shih AZ, Woo YC, Fong CH, Leung OY, Janus E, et al.
Optimal cut-offs of homeostasis model assessment of insulin resistance (HOMA-IR) to identify dysglycemia and type 2 diabetes mellitus: A 15-year prospective study in Chinese. PLoS One 2016;11:e0163424.
Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, et al.
2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: Executive summary: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2019;140:e563-95.
Ridker PM, Danielson E, Fonseca FA, Genest J, Gotto AM Jr., Kastelein JJ, et al.
Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med 2008;359:2195-207.
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412-9.
Kahn HS. The “lipid accumulation product” performs better than the body mass index for recognizing cardiovascular risk: A population-based comparison. BMC Cardiovasc Disord 2005;5:26.
Androulakis II, Kandaraki E, Christakou C, Karachalios A, Marinakis E, Paterakis T, et al
. Visceral adiposity index (VAI) is related to the severity of anovulation and other clinical features in women with polycystic ovary syndrome. Clin Endocrinol (Oxf) 2014;81:426-31.
Yildiz BO, Yarali H, Oguz H, Bayraktar M. Glucose intolerance, insulin resistance, and hyperandrogenemia in first degree relatives of women with polycystic ovary syndrome. J Clin Endocrinol Metab 2003;88:2031-6.
Yilmaz M, Bukan N, Ersoy R, Karakoç A, Yetkin I, Ayvaz G, et al.
Glucose intolerance, insulin resistance and cardiovascular risk factors in first degree relatives of women with polycystic ovary syndrome. Hum Reprod 2005;20:2414-20.
Sam S, Legro RS, Bentley-Lewis R, Dunaif A. Dyslipidemia and metabolic syndrome in the sisters of women with polycystic ovary syndrome. J Clin Endocrinol Metab 2005;90:4797-802.
Legro RS, Roller RL, Dodson WC, Stetter CM, Kunselman AR, Dunaif A. Associations of birthweight and gestational age with reproductive and metabolic phenotypes in women with polycystic ovarian syndrome and their first-degree relatives. J Clin Endocrinol Metab 2010;95:789-99.
Legro RS, Bentley-Lewis R, Driscoll D, Wang SC, Dunaif A. Insulin resistance in the sisters of women with polycystic ovary syndrome: Association with hyperandrogenemia rather than menstrual irregularity. J Clin Endocrinol Metab 2002;87:2128-33.
Mach F, Baigent C, Catapano AL, Koskinas KC, Casula M, Badimon L, et al.
2019 ESC/EAS Guidelines for the management of dyslipidaemias: Lipid modification to reduce cardiovascular risk. Eur Heart J 2020;41:111-88.
Vipin VP, Dabadghao P, Shukla M, Kapoor A, Raghuvanshi AS, Ramesh V. Cardiovascular disease risk in first-degree relatives of women with polycystic ovary syndrome. Fertil Steril 2016;105:1338-44.e3.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]