help button home button Endocrine Society JCEM JCEM Call for Nominations for EIC
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Journal of Clinical Endocrinology & Metabolism, doi:10.1210/jc.2004-0569
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
90/4/2063    most recent
Author Manuscript (PDF)
Right arrow Submit a related Letter to the Editor
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow patientINFORMation
Right arrow Request Copyright Permission
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Raskauskiene, D.
Right arrow Articles by Clayton, R. N.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Raskauskiene, D.
Right arrow Articles by Clayton, R. N.
Related Collections
Right arrow Diabetes and Insulin
Right arrow Female Endocrinology
The Journal of Clinical Endocrinology & Metabolism Vol. 90, No. 4 2063-2067
Copyright © 2005 by The Endocrine Society

Do Polycystic Ovaries on Ultrasound Scan Indicate Decreased Insulin Sensitivity in Sisters of Women with Polycystic Ovary Syndrome?

D. Raskauskiene, P. W. Jones, A. Govind, M. Obhrai and R. N. Clayton

University Hospital of North Staffordshire, and School of Medicine (D.R., A.G., M.O., R.N.C.), and Department of Mathematics (P.W.J.), Keele University, Stoke on Trent, Staffordshire ST4 7QB, United Kingdom

Address all correspondence and requests for reprints to: Professor R. N. Clayton, School of Medicine, Thornburrow Drive, Hartshill, Stoke-on-Trent, Staffs ST4 7QB, United Kingdom. E-mail: r.n.clayton{at}keele.ac.uk.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Polycystic ovary syndrome (PCOS) is associated with hyperandrogenemia, insulin resistance, altered lipid profile, and therefore with subsequently increased risk for metabolic complications such as type 2 diabetes and cardiovascular diseases. It has been reported that sisters of probands with PCOS, who themselves had PCOS or hyperandrogenemia with normal menses, were more insulin resistant than unaffected sisters. We have previously reported that 60% of first-degree relatives (premenopausal mothers and sisters) of PCOS probands had polycystic ovaries (PCO) on ultrascan. Sisters with PCO were more likely to have oligomenorrhea and increased androgen levels than sisters without PCO. The aims of this study were to assess insulin sensitivity status [homeostasis model of assessment, quantitative insulin sensitivity check index, glucose to insulin ratio (G/I)] and lipid profiles in probands with PCOS and their sisters with PCO and without PCO on ultrascan. Mixed model hierarchical regression analysis, to accommodate the nonindependent nature of the subjects (family relationships), with the three groups together did not show significant differences in insulin sensitivity, calculated as quantitative insulin sensitivity check index, homeostasis model of assessment, and G/I for PCOS probands, through sisters with PCO on ultrascan, to sisters without PCO on ultrascan. There was a significant association of measures of insulin sensitivity with body mass index. Lipid parameters did not differ between the groups. These data suggest that presence of PCO on ultrasound scan per se does not predispose to reduced insulin sensitivity in sisters of women with PCOS. Because about 20% of premenopausal women in the general population have PCO on ultrascan, and obesity/overweight is becoming more prevalent, it is important that future studies take full account of the contribution made by obesity to risk factors for metabolic/vascular complications.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
POLYCYSTIC OVARY SYNDROME (PCOS) is a heterogenous and very common endocrine disorder, affecting between 6 and 8% of women of reproductive age (1). The syndrome is characterized by chronic anovulation plus signs of hyperandrogenism (2, 3, 4). PCOS is associated with increased insulin resistance and pancreatic ß-cell dysfunction independent of the frequent attendant obesity. These defects confer a substantially increased risk of impaired glucose tolerance and type 2 diabetes mellitus (5, 6, 7). Women with PCOS appear at increased cardiovascular risk due to increased prevalence of obesity, dyslipidemia (8, 9), and altered vascular function (10).

The first-degree relatives of patients with type 2 diabetes are known to be more insulin resistant than age- and body mass index (BMI)-matched controls (11). This applies even to nonobese (BMI < 25.0 kg/m2) and young (<40 yr old) first-degree relatives, indicating that this is a familial disorder and certain metabolic abnormalities related to diabetes are inherited (12). Likewise, it was recently reported that sisters of women with PCOS are more insulin resistant than controls matched for age and BMI (13, 14, 15). Familial clustering of PCOS is well documented, suggesting that there is a genetic susceptibility to the disorder (16, 17, 18, 19, 20). Presence of polycystic ovaries (PCO) on ultrasound is accepted as a separate and distinct female phenotype, and it was reported that first-degree relatives (premenopausal mothers and sisters) of PCOS probands have almost three times higher chance of having PCO on ultrasound scan in comparison to the general population (21). Moreover, it has been shown that 82% of women with type 2 diabetes mellitus have PCO on ultrasound scan but only 52% of them present clinical symptoms of the syndrome (22). Recently it has been reported that Asian women with PCO demonstrated insulin resistance independent of BMI and family history of diabetes (23) and their brothers also have insulin resistance, comparable to that associated with family history of type 2 diabetes mellitus (23). Thus, the aim of this study was to determine insulin sensitivity status and lipid profiles in sisters of women with PCOS, specifically to ascertain whether their ovarian morphology could predict metabolic status.


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Subjects

The individuals identified with PCOS are designated as probands. These postmenarchal and premenopausal women were recruited prospectively from the infertility and endocrine clinics at the North Staffordshire Hospital Centre. They presented with symptoms of PCOS, such as anovulatory oligomenorrhea, and/or hirsutism, together with raised serum testosterone, androstenedione, or both. The clinical and hormonal details of the study cohort have been reported previously (21). These criteria for PCOS proband assignment have been extensively used in the United Kingdom and elsewhere. No PCOS proband had hypothyroidism, late onset congenital adrenal hyperplasia, Cushing’s syndrome, prolactinoma, or ovarian or adrenal tumors. Each had PCO by pelvic ultrasound and was known to have at least one sister. Women with PCOS and their sisters agreed to take part after informed consent was obtained. This study was approved by the North Staffordshire District Ethical Committee.

All interviews, examinations, and tests were performed at one visit, after fasting from 2400 h. All blood samples from the female relatives were taken on the day of ultrasound, which was performed within 1–7 d of menstruation in those with less marked menstrual irregularity (intermenstrual interval < 3 months) and randomly in women with severe oligomenorrhea/amenorrhea.

Twenty-seven PCOS probands were of Caucasian origin, and two were of Asian origin. It was possible to perform biochemical analysis on 51 premenopausal sisters from 29 PCOS probands. Before entering the study, the female subjects (probands and their sisters) continued on hormonal preparations (i.e. combined oral contraceptive pill, Dianette, or Provera).

Assignment of status

Women were considered affected if they had bilateral PCO on transvaginal ultrasound scan. One sister with two ovaries and unilateral PCO was assigned as normal, but her results were excluded from additional calculations to avoid a possible discrepancy in interpretation.

The ultrasound scan was performed using a 6.5-MHz transducter (Hitachi EUB 515 Echo Scan machine; Sonotron, Bedford, UK) by one observer who recorded the images in all patients. The precision of assignment of PCO status was 97%, when the hard copies were checked randomly by independent observers unaware of the clinical and biochemical features. We included only those women whose scan showed unequivocal PCO, which fulfilled the strict criteria of Adams et al. (24) and Eden (25).

Anthropometric and biochemical measurements

BMI was calculated as weight (kilograms) divided by height (meters) squared. Waist and hip circumferences (centimeters) were measured with the individual standing upright. Waist to hip ratio was calculated as waist circumference divided by hip circumference. Blood glucose was measured by the glucose oxidase method; the interassay coefficient of variation (CV) was 4%. Plasma insulin was measured by the double-antibody RIA as previously described (8). The interassay CV was 12%. The intraassay variation was 2.4% at 15 mIU/liter and 5.1% at 50 mIU/liter. Fasting serum levels of triglycerides, total cholesterol, and free cholesterol were measured by commercial enzymatic methods (Roche Molecular Biochemicals, Lewes, UK) as previously described (8). Supernatants containing total high-density lipoproteins (HDLs) or the HDL3 subfraction were obtained by precipitation of the other lipoproteins with buffered polyethylene glycol (Quantolip; Immuno Ag, Vienna, Austria). The lipid determinations were made on the supernatants, but increased assay sensitivity was achieved by increasing the sample volume and adding tribromohydroxybenzoic acid to a concentration of 0.5 g/liter of the assay reagent (26). All lipid analyses were controlled using commercial quality control serum (Lyotrol N; BioMerieux, Marcy l’Etoile, France; and Pathonorm H; Nycomed, Oslo, Norway); all analyses gave interassay CVs less than 4%, except for HDL and triglycerides, which were 11 and 9%, respectively.

Homeostasis model of assessment (HOMA)

HOMA resistance index was used to estimate insulin action and was calculated as follows: HOMA = fasting glucose (mmol/liter) x fasting insulin (µIU/ml) /22.5 (27).

Quantitative insulin sensitivity check index (QUICKI)

QUICKI is an index of insulin sensitivity and was calculated as follows: QUICKI = 1/[log fasting insulin (µIU/ml) + log fasting glucose (mg/dl)] (28).

Glucose to insulin ratio (G/I)

G/I is an index of insulin sensitivity and was calculated as follows: G/I = fasting glucose (mg/dl)/fasting insulin (µIU/ml) (29).

Documentation of results and statistical analysis

The data obtained in the study were stored in a database using a PC-aided documentation system (Microsoft Excel spreadsheet).

Because several subjects are members of the same family, and therefore their measurements cannot be assumed to be independent of each other, standard regression analyses are not applicable. Consequently, analysis was carried out using multilevel models using the software MlwiN (Institute of Education, London, UK; version 1.10.0007). However, summary measures for the groups are given for information. This type of data is known as hierarchical or nested data and in this case measurements are nested within two levels, namely at the higher level, family, and at the lower level, individual. Mixed models, containing fixed and random elements for the measures of insulin sensitivity, were obtained with group and BMI as predictors. The intercept in the regression is allowed to be random at the family level and with a fixed slope for the group and BMI for all three insulin sensitivity measurements. Four separate analyses were carried out depending on how the group variable was expressed. First, the three groups were assigned indicator values: 1, PCOS probands; 2, sisters with PCO; 3, sisters without PCO; thereby assuming a linear trend as the group indicator value increased. Second, by expressing groups 2 and 3 as binary variables indicating group membership with group 1 as a comparator, and finally by using two separate analyses with group 1 against group 2 and group 1 against group 3. Results are reported as the mean ± SD for information. Differences were accepted as significant at P < 0.05.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
One of 29 PCOS probands was excluded from analysis because of having frank diabetes mellitus (fasting plasma glucose, 10.1 mmol/liter). As can be seen (Table 1Go), the three groups of PCOS probands (n = 28), sisters with PCO on scan (n = 36), and sisters without PCO (n = 14) were matched for age and waist to hip ratio, but PCOS probands had higher BMI compared with their sisters from both groups (28.1 ± 7.6 vs. 24.5 ± 4.8 and 23.6 ± 2.8 kg/m2), although the differences were not significant when analyzed by MlwiN with P = 0.08. Sisters with PCO and without PCO on scan were similar regarding BMI. Fasting plasma glucose and fasting insulin concentrations were similar in all groups.


View this table:
[in this window]
[in a new window]
  		TABLE 1. Anthropometric and metabolic characteristics

 
Lipid data are shown in Table 2Go. There were no significant differences among the three groups comparing fasting total cholesterol, low-density lipoprotein-cholesterol, HDL-cholesterol, triglycerides, and total cholesterol to HDL-cholesterol ratio.


View this table:
[in this window]
[in a new window]
  		TABLE 2. Comparison of lipids characteristics between the groups

 
Insulin sensitivity data for the three groups, HOMA, QUICKI, and fasting glucose to insulin (G/I) ratio are shown in Table 3Go. In none of the analyses was a significant association observed between group membership (i.e. ovarian morphology status) and insulin sensitivity measurements. In the first model (assumes linear relationship), HOMA, QUICKI, and G/I ratio were all significantly associated with BMI (P < 0.005 for all). In the second model, QUICKI and G/I ratio were associated with BMI (P < 0.005) although HOMA was not (P > 0.05). In the third models, in which PCOS probands were compared with sisters with PCO, BMI was significantly related to HOMA (P = 0.006), QUICKI (P = 0.003), and G/I ratio (P = 0.008), and in which PCOS probands were compared with sisters without PCO, BMI was significantly related to HOMA (P = 0.04), QUICKI (P = 0.003), and G/I ratio (P = 0.004). There were no significant differences in indices of insulin sensitivity between women on the oral contraceptive pill or not within each subgroup.


View this table:
[in this window]
[in a new window]
  		TABLE 3. Insulin sensitivity tests in the three groups

 
There was no association between indices of insulin sensitivity and total testosterone, dehydroepiandrosterone sulfate (DHEAS), or androstenedione when tested using the multilevel model.


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
The relative importance of genetic and environmental factors in the etiology of PCOS is unclear. Several reports have stressed that PCOS is a familial disorder and various features of the syndrome may be differentially inherited (18). The polycystic ovary morphology (detected by ultrasound scan) has been reported to be inherited as an autosomal dominant trait, if premature balding is used as a male phenotype. Mothers and sisters, as well as brothers, of women with PCOS were found to be more insulin resistant compared with matched control subjects without family history of PCOS and diabetes (13, 14, 15). Furthermore, the mothers and sisters of women with PCOS had higher androgen levels compared with respective control groups, and 8% of mothers and 16% of sisters fulfilled diagnostic criteria of PCOS (15). It was already demonstrated that hyperandrogenemia is a common finding in female first-degree relatives of women with PCOS. Kahsar-Miller et al. (30) reported that 32% of sisters and 24% of mothers of patients with PCOS were affected by the syndrome, and those who had the syndrome demonstrated significantly higher mean testosterone, free testosterone, and DHEAS values (30). Legro et al. (31) found 22% of sisters of women with PCOS affected by the syndrome, whereas 24% of sisters with regular menstrual cycles had increased testosterone and DHEAS. Recently, it was reported that sisters of women with PCOS who fulfilled diagnostic criteria of the syndrome and sisters who had elevated androgen levels with regular menses were more insulin resistant compared with control group and sisters with normal androgen concentration and regular menses. These observations suggest that hyperandrogenemia and metabolic abnormalities are associated in PCOS families (14). However, in the aforementioned family studies there was no attempt to relate the hormonal profiles in the sisters of PCOS probands to the ovarian morphology.

Given the close familial association between insulin resistance and PCOS phenotype and the reports of higher insulin resistance in the first-degree relatives of PCOS probands, we wanted to determine whether the morphological appearance of PCO alone on ultrasound scan could confer insulin resistance. As already had been reported (21), sisters with PCO on ultrasound scan can have a significantly elevated rate of oligomenorrhea and higher androstenedione concentrations compared with the sisters with normal ovaries. These findings suggest that ovarian morphology, probably inherited as an autosomal dominant trait, is associated with hormonal and clinical abnormalities. In the present study we found that changes in ovarian morphology, when considered alone, seemed to show a relationship with insulin sensitivity. Thus, sisters with PCO appeared intermediate between their "normal" sisters and the proband PCOS sisters regarding their metabolic features. However, these differences disappeared when the analyses were carried out in a way that took into account the correlation of measurements within families and later BMI. Thus, in this, as in other subject groups, overweight/obesity is the major determinant of insulin sensitivity. Whether there is an additional contribution from PCO is still uncertain. Several of our patients were taking various estrogen-progestogen preparations at the time of study of insulin sensitivity and this may have influenced the results. The literature on this is divided and inconclusive (reviewed in Ref. 32). One long-term follow-up study of metabolic characteristics showed that oral contraceptive use prevented the deterioration in insulin sensitivity that occurred with time (32).

The various mathematical indices of insulin sensitivity used herein (HOMA, QUICKI, G/I ratio) have been used extensively in many studies of both type 2 diabetes and PCOS. However, caution must be exercised when using these parameters in comparison with the "gold-standard" clamp technology as has recently been highlighted by Diamanti-Kandarakis et al. (33). Nonetheless, as we were not so much interested in absolute changes from normal rather than comparison between three groups, we believe the indices are valid.

Up to 30% of the reproductive-age population may have PCO in large case studies (34, 35). As has been reported already, high prevalence of PCO (approaching 40%) in postmenopausal women was associated with increased cardiovascular risk factors such as hypertension, hypercholesterolemia, hypertriglyceridemia, and elevated waist to hip ratio (36). Moreover, women with PCOS were noted to have a calculated 7-fold increased risk for myocardial infarction (36). Another study has shown a clear link between type 2 diabetes mellitus and PCO, as 82% of women with type 2 diabetes had PCO on ultrasound scan. Nevertheless, only 52% of them had clinical evidence of PCOS (22). Recently it has been reported that Asian women with PCO and especially those with family history of type 2 diabetes mellitus are more insulin resistant than matched controls (23). Therefore, it might be suggested that asymptomatic women with PCO have some metabolic alterations related to increased cardiovascular risk and type 2 diabetes mellitus, which may be independent of a family history of PCOS or diabetes.

However, a word of caution about extrapolation of these data is warranted. Despite several studies demonstrating increased risk factors for vascular disease in women with PCOS and PCO on ultrasound scan, it remains to be shown, in prospective longitudinal studies, that these women will have increased morbidity and mortality from this cause. The only published data on this subject was a retrospective study with considerable heterogeneity in ascertainment of diagnosis of PCOS and death/morbidity certification and this did not show any increases in mortality rate from coronary heart diseases (37). Nevertheless, at long-term follow-up, history of nonfatal cerebrovascular disease and cardiovascular risk factors including diabetes were found to be more prevalent among women with PCOS (37).

In conclusion, the evidence reported herein suggests that the presence of PCO on ultrascan does not predispose women with a family history of PCOS to reduced insulin sensitivity. However, it is likely that if they become overweight/obese they will become insulin resistant, just like anyone else. Additional longitudinal studies are needed to determine whether the metabolic status of young women with ovarian morphology consistent with PCO changes with time in a different manner from those without PCO.


   Footnotes
 
First Published Online January 5, 2005

Abbreviations: BMI, Body mass index; CV, coefficient of variation; DHEAS, dehydroepiandrosterone sulfate; G/I, glucose to insulin ratio; HDL, high-density lipoprotein; HOMA, homeostasis model of assessment; PCO, polycystic ovaries; PCOS, polycystic ovary syndrome; QUICKI, quantitative insulin sensitivity check index.

Received March 25, 2004.

Accepted December 29, 2004.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

  1. Tsilchorozidou T, Overton C, Conway GS 2004 The pathology of polycystic ovary syndrome. Clin Endocrinol (Oxf) 60:1–17[CrossRef][Medline]
  2. Dunaif A, Givens JR, Haseltine FP, Merriam GR 1992 Current issues in endocrinology and metabolism: polycystic ovary syndrome. Boston: Blackwell
  3. Knochenhauer ES, Key TJ, Kahsar-Miller M, Waggoner W, Boots LR, Azziz R 1998 Prevalence of the polycystic ovary syndrome in unselected black and white women of the Southeastern United States: a prospective study. J Clin Endocrinol Metab 83:3078–3082[Abstract/Free Full Text]
  4. Asunction M, Clavo RM, San Millan JI, Sancho J, Avila S, Escobar-Morreale HF 2000 A prospective study of the prevalence of the polycystic ovary syndrome in unselected Caucasian women from Spain. J Clin Endocrinol Metab 85:2434–2438[Abstract/Free Full Text]
  5. Legro RS, Kunselman AR, Dodson WC, Dunauf A 1999 Prevalence and predictors of risk for type 2 diabetes mellitus and impaired glucose tolerance in polycystic ovary syndrome: a prospective, controlled study in 254 affected women. J Clin Endocrinol Metab 84:165–169[Abstract/Free Full Text]
  6. Norman RJ, Masters L, Milner CR, Wang JX, Davies MJ 2001 Relative risk of conversion from normoglycaemia to impaired glucose tolerance or non-insulin dependent diabetes mellitus in polycystic ovarian syndrome. Hum Reprod 9:1995–1998
  7. Palmert MR, Gordon CM, Kartashov AI, Legro RS, Emans SJ, Dunaif A 2002 Screening for abnormal glucose tolerance in adolescents with polycystic ovary syndrome. J Clin Endocrinol Metab 87:1017–1023[Abstract/Free Full Text]
  8. Rajkhowa M, Neary RH, Kumpatla P, Game FL, Jones PW, Obrai MS, Clayton RN 1997 Altered composition of high density lipoproteins in women with polycystic ovary syndrome. J Clin Endocrinol Metab 82:3389–3394[Abstract/Free Full Text]
  9. Mather KJ, Kwan F, Corenblum B 2000 Hyperinsulinemia in polycystic ovary syndrome correlated with increased cardiovascular risk independent of obesity. Fertil Steril 73:150–156[CrossRef][Medline]
  10. Kelly CJG, Speirs A, Gould GW, Petrie JR, Lyall H, Connell JMC 2002 Altered vascular function in young women with polycystic ovary syndrome. J Clin Endocrinol Metab 87:742–746[Abstract/Free Full Text]
  11. Volk A, Renn W, Overkamp D, Mehnert B, Maerker E, Jacob S, Balletshofer B, Haring HU, Rett K 1999 Insulin action and secretion in healthy, glucose tolerant first degree relatives of patients with type 2 diabetes mellitus. Influence of body weight. Exp Clin Endocrinol Diabetes 107:140–147[Medline]
  12. Raskauskiene D Reduced insulin sensitivity in healthy first degree relatives of patients with type 2 diabetes mellitus. The 22nd Joint Meeting of the British Endocrine Societies, Glasgow, United Kingdom, 2003, Vol 5, p. 93
  13. Norman RJ, Masters S, Hague W 1996 Hyperinsulinaemia is common in family members of women with polycystic ovary syndrome. Fertil Steril 66:942–947[Medline]
  14. Legro RS, Lewis RB, Driscoll D, Wang SC, Dunaif A 2002 Insulin resistance in the sisters of women with polycystic ovary syndrome: association with hyperandrogenemia rather than menstrual irregularity. J Clin Endocrinol Metab 87:2128–2133[Abstract/Free Full Text]
  15. Yildiz BO, Yarali H, Oguz H, Bayraktar M 2003 Glucose intolerance, insulin resistance, and hyperandrogenemia in first degree relatives of women with polycystic ovary syndrome. J Clin Endocrinol Metab 88:2031–2036[Abstract/Free Full Text]
  16. Lunde O, Magnus P, Sandvik L, Hoglo S 1989 Familial clustering in the polycystic ovary syndrome. Gynecol Obstet Invest 28:23–30[Medline]
  17. Hague WM, Adams J, Reeders ST, Petro TE, Jacobs HS 1988 Familial polycystic ovaries: a genetic disease? Clin Endocrinol (Oxf) 29:593–605[Medline]
  18. Carey AH, Chan KL, Short F, White D, Williamson R, Franks S 1993 Evidence for a single gene effect causing polycystic ovaries and male pattern baldness. Clin Endocrinol (Oxf) 38:653–658[Medline]
  19. Franks S, Gharani N, Waterworth D, Batty S, White D, Williamson R, McCarthy M 1997 The genetic basis of polycystic ovary syndrome. Hum Reprod 12:2641–2648[Abstract/Free Full Text]
  20. Legro RS, Spielman R, Urbanek M, Driscoll D, Straus III JF, Dunaif A 1998 Phenotype and genotype in polycystic ovary syndrome. Recent Prog Horm Res 53:217–256
  21. Govind A, Obhrai MS, Clayton RN 1999 Polycystic ovaries are inherited as an autosomal dominant trait: analysis of 29 polycystic ovary syndrome and 10 control families. J Clin Endocrinol Metab 84:38–43[Abstract/Free Full Text]
  22. Conn JJ, Jacobs HS, Conway GS 2000 The prevalence of polycystic ovaries in women with type 2 diabetes mellitus. Clin Endocrinol (Oxf) 52:81–86[CrossRef][Medline]
  23. Kaushal R, Parchure N, Bano G, Kaski JC, Nussey SS 2004 Insulin resistance and endothelial dysfunction in the brothers of Indian subcontinent Asian women with polycystic ovaries. Clin Endocrinol (Oxf) 60:322–328[CrossRef][Medline]
  24. Adams J, Polson DW, Franks S 1986 Prevalence of polycystic ovaries in women with anovulation and idiopathic hirsutism. Br Med J 293:355–356
  25. Eden JA 1988 Which is the best test to detect polycystic ovary? Aust NZ J Obstet Gynaecol 96:806–815
  26. Trinder P, Webster D 1984 Determination of HDL-cholesterol using 2,3,4-tribromo-3-hydroxybenzoic acid with a commercial CHOD-PAP reagent. Ann Clin Biochem 21:430–433
  27. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC 1985 Homeostasis model assessment: insulin resistance and ß-cell function from fasting plasma glucose and insulin concentration in man. Diabetologia 28:412–419[CrossRef][Medline]
  28. Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ 2000 Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 85:2402–2410[Abstract/Free Full Text]
  29. Legro RS, Finegood D, Dunaif A 1998 A fasting glucose to insulin ratio is a useful measure of insulin sensitivity in women with polycystic ovary syndrome. J Clin Endocrinol Metab 83:2694–2698[Abstract/Free Full Text]
  30. Kahsar-Miller MD, Nixon C, Boots LR, Go RC, Azziz R 2001 Prevalence of polycystic ovary syndrome (PCOS) in first-degree relatives of patients with PCOS. Fertil Steril 75:53–58[CrossRef][Medline]
  31. Legro RS, Driscoll D, Strauss III JF, Fox J, Dunaif A 1998 Evidence for a genetic basis for hyperandrogenemia in polycystic ovary syndrome. Proc Natl Acad Sci USA 95:14956–14960[Abstract/Free Full Text]
  32. Pasquali R, Gambineri A, Anconetani B, Vicennati V, Colitta D, Caramelli E, Casimirri F, Morselli-Labate A 1999 The natural history of the metabolic syndrome in young women with the polycystic ovary syndrome and the effect of long-term oestrogen-progestagen treatment. Clin Endocrinol (Oxf) 50:517–527[CrossRef][Medline]
  33. Diamanti-Kandarakis E, Kouli C, Alexandraki K, Spina G 2004 Failure of mathematical indices to accurately assess insulin resistance in lean, overweight, or obese women with polycystic ovary syndrome. J Clin Endocrinol Metab 89:1273–1276[Abstract/Free Full Text]
  34. Farquhar CM, Birdsall M, Manning P, Mitchell JM, France JT 1994 The prevalence of polycystic ovaries on ultrasound scanning in a population of randomly selected women. Aust NZ J Obstet Gynaecol 34:67–72[Medline]
  35. Clayton RN, Ogden V, Hodgkinson J, Worswick L, Rodin DA, Dyer S 1992 How common are polycystic ovaries in normal women and their significance for the fertility of population? Clin Endocrinol (Oxf) 37:127–134[Medline]
  36. Dahlgren E, Janson PO, Johansson S, Lapidus L, Oden A 1992 Polycystic ovary syndrome and risk factors for myocardial infarction. Evaluated from a risk factor model on prospective population study of women. Acta Obstet Gynecol Scand 71:599–604[Medline]
  37. Wild S, Pierpoint T, McKeigue P, Jacobs H 2000 Cardiovascular disease in women with polycystic ovary syndrome at long-term follow-up: a retrospective cohort study. Clin Endocrinol (Oxf) 52:595–600[CrossRef][Medline]

Find additional patient-related information at:

Ovary Problems and Insulin Sensitivity


This article has been cited by other articles:


Home page
 J. Clin. Endocrinol. Metab.Home page
R. Azziz
Diagnosis of Polycystic Ovarian Syndrome: The Rotterdam Criteria Are Premature
J. Clin. Endocrinol. Metab., March 1, 2006; 91(3): 781 - 785.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
90/4/2063    most recent
Author Manuscript (PDF)
Right arrow Submit a related Letter to the Editor
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow patientINFORMation
Right arrow Request Copyright Permission
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Raskauskiene, D.
Right arrow Articles by Clayton, R. N.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Raskauskiene, D.
Right arrow Articles by Clayton, R. N.
Related Collections
Right arrow Diabetes and Insulin
Right arrow Female Endocrinology

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Endocrinology Endocrine Reviews J. Clin. End. & Metab.
Molecular Endocrinology Recent Prog. Horm. Res. All Endocrine Journals