81:I[191445,["$4","$5","$6","$7","$8","$9","$a","$b","$c","$d","$e","$f","$10","$11","$12","$13","$14","$15","$16","$17","$18","$19","$1a","$1b","$1c","$1f","$20","$21","$22","$23","$24","$25","$26","$27","$28","$29","$2a","$2b"],"WorkTabProvider"] 82:I[649892,["$4","$5","$6","$7","$8","$9","$a","$b","$c","$d","$e","$f","$10","$11","$12","$13","$14","$15","$16","$17","$18","$19","$1a","$1b","$1c","$1f","$20","$21","$22","$23","$24","$25","$26","$27","$28","$29","$2a","$2b"],"WorkHeader"] 83:T4eac,Authors & AffiliationsBailey Smith, Avery Zhang, Faith Carter, Samiha Azgar, Marla LujanCornell University, Division of Nutritional SciencesAbstractLifestyle intervention aimed at weight loss is recommended to improve metabolic health and psychological wellbeing in women with PCOS and co-morbid obesity. Benefits of weight loss on ovarian follicle development and ovulation are unclear, and results of published studies are variable. Emerging data from our group suggests that this variability may reflect the degree to which folliculogenesis is impaired at baseline. Objective: The objective of this study was to contrast ovarian follicular growth and endocrine dynamics in overweight women with PCOS, normoandrogenic anovulation (NA-Anov), and regular cycles before and after a weight-loss intervention. Methods: 75 women ages 18-38 with overweight (BMI ≥ 25) will be recruited evenly across 3 categories: PCOS, NA-Anov, and regular cycles. Every other-day transvaginal ultrasonography and venipuncture will be conducted at an academic clinical research unit for 4 weeks at baseline and again at the end of a 24-week hypocaloric dietary intervention (intervention weeks 21 through 24). During intervention weeks' 1 through 20, ultrasound and venipuncture will occur biweekly to monitor ovulation. The number and size of all follicles will be assessed at each study visit, with individual growth profiles plotted retrospectively for follicles that grew to at least 7mm. Gonadotropin and ovarian steroid hormone concentrations will also be measured at each study visit. Reproductive, anthropometric status, body composition and metabolic status markers will be assessed at baseline and at the end of the intervention. Anticipated Results: By performing longitudinal assessments of ovarian morphology and endocrine parameters, we will define the physiologic basis for morphologic variations in anovulatory disorders and determine how those aberrations differentially respond to nutritional intervention. We anticipate that these results will usher new approaches for tailored interventions that account for the spectrum of disordered folliculogenesis across anovulatory disorders.IntroductionMotivationAffecting approximately one in eight women of reproductive age, polycystic ovary syndrome (PCOS) is considered the most prevalent endocrinopathy affecting women worldwide (1,2). Effects on women’s health are multi-dimensional, imparting both short- and long-term complications for reproductive, cardiometabolic and psychological health (3). PCOS has long been considered a leading cause of anovulatory infertility, with those achieving conception having higher rates of miscarriage, gestational diabetes, pregnancy-induced hypertension, and other pregnancy complications (4). Women with PCOS have higher risks for central obesity, impaired glucose tolerance, metabolic syndrome and type 2 diabetes when compared to age- and adiposity-matched controls (5–10). Understanding the relevance of polycystic ovaries (PCO) in the clinical presentation of PCOS has important implications for improving the efficacy of treatments for ovulatory dysfunction. Since obesity worsens the reproductive and metabolic phenotypes of PCOS (11), lifestyle intervention (diet and/or exercise) is recommended as the initial treatment in overweight and obese patients (12–14), Most clinical trials involving women with PCOS have reported improvements in gonadotropin secretion, hyperandrogenism and insulin sensitivity with weight loss of 5–10% (12,15,16). Many studies have also shown increased frequency of menses, sporadic ovulation and pregnancy with weight loss (12). However, data supporting the resumption of regular ovulatory cycles are sparse and unconvincing, as interventions have been limited in duration and by their use of insufficient markers to confirm ovulation (17). Impact/SignificanceOverall, improvements in reproductive outcomes have been noted in a wide range of patients (13–92%)(12) and could be interpreted to mean that lifestyle modification is not a universal solution for anovulation in PCOS (17). Factors that influence or predict the ovulatory response to weight loss are ill-defined. Improvements in the reproductive phenotype may depend on the degree of weight loss(18–22) or change in total/ regional adiposity (19–24). Weight loss may also fail to stimulate ovulation in those with greater severity of baseline endocrine abnormalities (21,24–26). To the best of our knowledge, morphologic predictors of the ovulatory response to weight loss have not been evaluated. Such predictors may best identify those likely to respond to treatment, since serum measures of endocrine status in women are technically challenging (particularly, androgens (27)) and ovarian morphology is a known predictor of the ovarian response to pharmacologic intervention (28).In the following proposal, we aim to refine the sonographic definition of PCO by establishing the specificity of these criteria against normoandrogenic anovulation (NA-Anov) in women with obesity. We will also clarify any ability of a serum marker [anti-Müllerian hormone (AMH)] to better inform the diagnosis or ovulatory response to weight loss in PCOS and NA-Anov compared to morphologic features. Our approach is rooted in using state-of-the-art ultrasound technology to reveal, for the first time, how antral follicle development is uniquely altered in PCOS and NA-Anov, and how these perturbations are further exacerbated by adiposity. By performing longitudinal assessments of ovarian morphology, we will define the physiologic basis for morphologic variations in anovulatory disorders and determine how those aberrations differentially respond to nutritional intervention. We anticipate that these results will usher new approaches for tailored interventions that account for the spectrum of disordered folliculogenesis across anovulatory disorders.Hypotheses/AimsSpecific Aim 1: To define aberrations in antral follicle development that account for unique aspects of PCO. Serial ovarian ultrasonography will be performed every other day for 4 weeks in order to contrast the kinetics of folliculogenesis in PCOS, NA-Anov and regular ovulatory cycles. Differences in key events of folliculogenesis (i.e. recruitment, selection and dominance) that account for morphologic features of PCO will be defined.Specific Aim 2: To determine the effectiveness of weight loss to normalize antral follicle development in overweight women with PCOS, NA-Anov and regular ovulatory cycles. Changes in folliculogenesis during a 24-week commercial diet program will be evaluated by serial ovarian ultrasonography in overweight women with PCOS, NA-Anov and regular ovulatory cycles. Improvements in the incidence of recruitment, selection, dominance and ovulation will be contrasted between groups.Specific Aim 3: To identify sonographic markers that predict the ovulatory response to weight loss. Baseline aspects of ovarian morphology will be modeled against metabolic and endocrine features to establish their potential to predict the likelihood of selection, dominance and ovulation during weight loss. Any differences between groups (PCOS, NA-Anov and regular cycles) will be determined.Materials/MethodsParticipants: We will recruit 75 women with overweight (BMI ≥ 25), including 25 women with PCOS, 25 with NA-Anov, and 25 with regular, ovulatory cycles (controls).Baseline: Participants will be evaluated at Cornell University by serial transvaginal ultrasonography every other day for 4 weeks. Ultrasound images of the ovaries will be evaluated off-line for the number and diameter of all follicles ≥2mm (29). Growth profiles of large follicles (≥7mm) will be ascertained with the Identity Method (30). Blood samples will be collected at each visit and used to measure changes in gonadotropins and ovarian hormones (FSH, LH, E2, P4). During the early follicular phase or when no dominant follicle is present, participants will undergo an evaluation of metabolic and endocrine status including: 1) a review of menstrual cycle history to determine the extent of cycle disturbance, 2) fasting blood tests to detect serum markers of metabolic syndrome (HDL, LDL, triglycerides), androgens (TT, A4, FT, FAI) and reproductive hormones (LH, FSH, E2, P4, AMH), 3) a physical exam to assess hirsutism (31), vitals and anthropometry, 4) a 2-hour 75g oral glucose tolerance test, and 5) a dual x-ray absorptiometry scan to measure body composition.Intervention: After this baseline evaluation of antral follicle dynamics, participants will begin a 24-week hypocaloric dietary intervention (Nutrisystem® D). Food diaries will be maintained to monitor compliance. An ultrasound, blood draw, and weight assessment will be performed biweekly. If a dominant follicle (≥10mm) grows to a diameter of 14–16mm, scans will be performed daily until its ovulation or regression and then return to biweekly. Sonographic evidence of ovulation will be corroborated by serum P4 levels. Response to Intervention: All baseline procedures will be repeated during weeks 20-24 of the intervention. Participants will also return 6 months post-intervention for a single visit to complete procedures 1-6 listed above.Study typeThis is a longitudinal case control study. We aim to recruit 75 overweight women split equally across three groups: PCOS, NA-Anov, and regular, ovulatory cycles (controls). All three groups will receive the same hypocaloric dietary intervention and effects of weight loss on ovulation and metabolism will be assessed. Existing dataRegistration prior to analysis of the dataExplanation of existing dataExisting data includes: menstrual cycle data, anthropometrics, hirsutism, vitals, body composition (DXA scans) and glucose values from pre- and post-intervention oral glucose tolerance tests. These data are only accessible to a handful of study team members. Serum testosterone has not yet been measured for all participants and the ultrasound scans have not all been analyzed, so an observer of the data would be unable to phenotype participants (i.e., categorize them as PCOS, NA-Anov, or control) in order to analyze group differences.Data collection proceduresParticipants will be recruited from Ithaca, NY and the surrounding area from June 2018 through June 2023 using flyers, list-serves, and social networking sites. Participants will receive a total of $2000 cash over the course of the 7-month study. Participants will also receive a free Fitbit at enrollment and 6 free months of Nutrisystem D beginning in month 2 of the study.Inclusion Criteria:Ages 18-38Have both a uterus and two ovariesNot taking any medications known or suspected to interfere with reproductive function, metabolism, and/or appetiteNo use of fertility medications, oral contraceptives, or hormonal IUD in the past 2 monthsNo known diagnosis of ovarian failure, endometriosis, or another disease (other than PCOS) known or suspected to interfere with reproductive functionNot pregnant, breastfeeding, or planning to become pregnant in the next 7 monthsNo known diagnosis of any of the following conditions:• Anorexia or Bulimia• Cancer (current or recent history)• Chronic Kidney Disease, Insufficiency, or Failure• Congestive Heart Failure or Ischemic Heart Disease• Depression• Diabetes• HIV• Hyperthyroidism• Inflammatory Bowel Disease, Achalasia, Gastroparesis, Pyloric Stenosis• Sarcoidosis• Severe Epilepsy• TuberculosisParticipants will be assigned an anonymous study ID at enrollment, and information linking the study ID to their name and identifying information will be stored on a protected server. Study procedures are listed in the methods section above. Participants will be asked to leave the study if they no longer meet inclusion criteria, if they lose an unsafe amount of weight (BMI falls below 18.5), or if they can no longer adhere to the study protocol. In these situations, participants will receive a prorated honorarium based on the duration of their study participation. At the end of the study, participants will receive a summary of their study results (i.e., DXA scan data, blood glucose values, ovarian ultrasound images, vitals, and anthropometrics).Sample sizeOur target samples size is 75, split equally across three groups: PCOS, NA-Anov, and regular, ovulatory cycles (controls).BudgetThis project is supported by NIH grant number 5R01HD093748-02 which funded all primary data collection and many of the hormone analyses. Funding from AthenaDAO and ResearchHub will be used to complete our assessments of serum metabolic and reproductive hormones pre- and post-intervention for the PCOS and control groups. The funding will also support a PhD student who will analyze these data as part of their dissertation. Total testosterone: $50/sample x 4 samples remaining = $200.00Lipid Panel: $22.32/sample x 27 samples remaining = $602.64AMH: $45/sample x 16 samples remaining = $720.00Graduate Student Stipend (this will cover one third of a summer stipend)= $3477.36TOTAL = $5000 References 1. March WA, Moore VM, Willson KJ, Phillips DIW, Norman RJ, Davies MJ. The prevalence of polycystic ovary syndrome in a community sample assessed under contrasting diagnostic criteria. Hum Reprod Oxf Engl. 2010 Feb;25(2):544–51.2. Bozdag G, Mumusoglu S, Zengin D, Karabulut E, Yildiz BO. The prevalence and phenotypic features of polycystic ovary syndrome: a systematic review and meta-analysis. Hum Reprod Oxf Engl. 2016 Dec;31(12):2841–55.3. Cooney LG, Dokras A. Beyond fertility: polycystic ovary syndrome and long-term health. Fertil Steril. 2018 Oct;110(5):794–809.4. Bahri Khomami M, Joham AE, Boyle JA, Piltonen T, Silagy M, Arora C, et al. Increased maternal pregnancy complications in polycystic ovary syndrome appear to be independent of obesity-A systematic review, meta-analysis, and meta-regression. Obes Rev Off J Int Assoc Study Obes. 2019 May;20(5):659–74.5. Wild S, Pierpoint T, McKeigue P, Jacobs H. Cardiovascular disease in women with polycystic ovary syndrome at long-term follow-up: a retrospective cohort study. Clin Endocrinol (Oxf). 2000 May;52(5):595–600.6. Wild RA, Rizzo M, Clifton S, Carmina E. Lipid levels in polycystic ovary syndrome: systematic review and meta-analysis. Fertil Steril. 2011 Mar 1;95(3):1073-1079.e1-11.7. Wild S, Pierpoint T, Jacobs H, McKeigue P. Long-term consequences of polycystic ovary syndrome: results of a 31 year follow-up study. Hum Fertil Camb Engl. 2000;3(2):101–5.8. Kakoly NS, Khomami MB, Joham AE, Cooray SD, Misso ML, Norman RJ, et al. Ethnicity, obesity and the prevalence of impaired glucose tolerance and type 2 diabetes in PCOS: a systematic review and meta-regression. Hum Reprod Update. 2018 Jul 1;24(4):455–67.9. Lim SS, Davies MJ, Norman RJ, Moran LJ. Overweight, obesity and central obesity in women with polycystic ovary syndrome: a systematic review and meta-analysis. Hum Reprod Update. 2012;18(6):618–37.10. Behboudi-Gandevani S, Amiri M, Bidhendi Yarandi R, Noroozzadeh M, Farahmand M, Rostami Dovom M, et al. The risk of metabolic syndrome in polycystic ovary syndrome: A systematic review and meta-analysis. Clin Endocrinol (Oxf). 2018 Feb;88(2):169–84.11. Lim S, Norman R, Davies M, Moran L. The effect of obesity on polycystic ovary syndrome: a systematic review and meta-analysis. Obes Rev. 2013;14(2):95–109.12. Moran L, Pasquali R, Teede H, Hoeger K, Norman R. Treatment of obesity in polycystic ovary syndrome: a position statement of the Androgen Excess and Polycystic Ovary Syndrome Society. Vol. 92, Fertility and Sterility. 2009. p. 1966–82.13. Fauser B, Tarlatzis B, Rebar R, Legro R, Balen A, 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(1):28–38.14. Legro R, Arslanian S, Ehrmann D, Hoeger K, Murad M, Pasquali R, et al. Diagnosis and treatment of polycystic ovary syndrome: an endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2013;98(12):4565–92.15. Moran L, Hutchison S, Norman R, Teede H. Lifestyle changes in women with polycystic ovary syndrome. Cochrane Database Syst Rev. 2011;(7):CD007506.16. Bützow T, Lehtovirta M, Siegberg R, Hovatta O, Koistinen R, Seppälä M, et al. The decrease in luteinizing hormone secretion in response to weight reduction is inversely related to the severity of insulin resistance in overweight women. J Clin Endocrinol Metab. 2000;85(9):3271–5.17. Jarrett B, Lujan M. Impact of hypocaloric dietary intervention on ovulation in obese women with PCOS. Reproduction. 2017;153(1):R15–27.18. Hoeger K, Kochman L, Wixom N, Craig K, Miller R, Guzick D. A randomized, 48-week, placebo- controlled trial of intensive lifestyle modification and/or metformin therapy in overweight women with polycystic ovary syndrome: a pilot study. Fertil Steril. 2004;82(2):421–9.19. Palomba S, Giallauria F, Falbo A, Russo T, Oppedisano R, Tolino A, et al. Structured exercise training programme versus hypocaloric hyperproteic diet in obese polycystic ovary syndrome patients with anovulatory infertility: a 24-week pilot study. Hum Reprod. 2008;23(3):642–50.20. Thomson R, Buckley J, Noakes M, Clifton P, Norman R, Brinkworth G. The effect of a hypocaloric diet with and without exercise training on body composition, cardiometabolic risk profile, and reproductive function in overweight and obese women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2008;93(9):3373–80.21. Thomson R, Buckley J, Moran L, Noakes M, Clifton P, Norman R, et al. The effect of weight loss on anti-Müllerian hormone levels in overweight and obese women with polycystic ovary syndrome and reproductive impairment. Hum Reprod. 2009;24(8):1976–81.22. Kuchenbecker W, Groen H, van Asselt S, Bolster J, Zwerver J, Slart R, et al. In women with polycystic ovary syndrome and obesity, loss of intra-abdominal fat is associated with resumption of ovulation. Hum Reprod. 2011;26(9):2505–12.23. Huber-Buchholz MM, Carey D, Norman R. Restoration of reproductive potential by lifestyle modification in obese polycystic ovary syndrome: role of insulin sensitivity and luteinizing hormone. J Clin Endocrinol Metab. 1999;84(4):1470–4.24. Pasquali R, Gambineri A, Cavazza C, Gasparini D, Ciampaglia W, Cognigni G, et al. Heterogeneity in the responsiveness to long-term lifestyle intervention and predictability in obese women with polycystic ovary syndrome. Eur J Endocrinol. 2011;164(1):53–60.25. van Dam E, Roelfsema F, Veldhuis J, Hogendoorn S, Westenberg J, Helmerhorst F, et al. Retention of estradiol negative feedback relationship to LH predicts ovulation in response to caloric restriction and weight loss in obese patients with polycystic ovary syndrome. Am J Physiol Endocrinol Metab. 2004;286:E615–20.26. Moran L, Noakes M, Clifton P, Norman R. The use of anti-mullerian hormone in predicting menstrual response after weight loss in overweight women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2007;92(10):3796–802.27. Rosner W, Auchus R, Azziz R, Sluss P, Raff H. Position statement: Utility, Limitations, and Pitfalls in Measuring Testosterone: An Endocrine Society Position Statement. J Clin Endocrinol Metab. 2007;92(2):405–13.28. Hendriks D, Mol B, Bancsi L, Te Velde E, Broekmans F. Antral follicle count in the prediction of poor ovarian response and pregnancy after in vitro fertilization: a meta-analysis and comparison with basal follicle-stimulating hormone level. Fertil Steril. 2005;83(2):291–301.29. Lujan M, Brooks E, Kepley A, Chizen D, Pierson R, Peppin A. Grid analysis improves reliability in follicle counts made by ultrasonography in women with polycystic ovary syndrome. Ultrasound Med Biol. 2010;36(5):712–8.30. Baerwald A, Adams G, Pierson R. A new model for ovarian follicular development during the human menstrual cycle. Fertil Steril. 2003;80(1):116–22.31. Ferriman D, Gallwey J. Clinical assessment of body hair growth in women. J Clin Endocrinol Metab. 1961;21:1440–7.84:T534b,

Impact of PCOS status on ovulatory and metabolic changes with weight loss

Authors & Affiliations

Bailey Smith, Avery Zhang, Faith Carter, Samiha Azgar, Marla Lujan

Cornell University, Division of Nutritional Sciences

Abstract

Lifestyle intervention aimed at weight loss is recommended to improve metabolic health and psychological wellbeing in women with PCOS and co-morbid obesity. Benefits of weight loss on ovarian follicle development and ovulation are unclear, and results of published studies are variable. Emerging data from our group suggests that this variability may reflect the degree to which folliculogenesis is impaired at baseline. Objective: The objective of this study was to contrast ovarian follicular growth and endocrine dynamics in overweight women with PCOS, normoandrogenic anovulation (NA-Anov), and regular cycles before and after a weight-loss intervention. Methods: 75 women ages 18-38 with overweight (BMI ≥ 25) will be recruited evenly across 3 categories: PCOS, NA-Anov, and regular cycles. Every other-day transvaginal ultrasonography and venipuncture will be conducted at an academic clinical research unit for 4 weeks at baseline and again at the end of a 24-week hypocaloric dietary intervention (intervention weeks 21 through 24). During intervention weeks' 1 through 20, ultrasound and venipuncture will occur biweekly to monitor ovulation. The number and size of all follicles will be assessed at each study visit, with individual growth profiles plotted retrospectively for follicles that grew to at least 7mm. Gonadotropin and ovarian steroid hormone concentrations will also be measured at each study visit. Reproductive, anthropometric status, body composition and metabolic status markers will be assessed at baseline and at the end of the intervention. Anticipated Results: By performing longitudinal assessments of ovarian morphology and endocrine parameters, we will define the physiologic basis for morphologic variations in anovulatory disorders and determine how those aberrations differentially respond to nutritional intervention. We anticipate that these results will usher new approaches for tailored interventions that account for the spectrum of disordered folliculogenesis across anovulatory disorders.

Introduction

Motivation

Affecting approximately one in eight women of reproductive age, polycystic ovary syndrome (PCOS) is considered the most prevalent endocrinopathy affecting women worldwide (1,2). Effects on women’s health are multi-dimensional, imparting both short- and long-term complications for reproductive, cardiometabolic and psychological health (3). PCOS has long been considered a leading cause of anovulatory infertility, with those achieving conception having higher rates of miscarriage, gestational diabetes, pregnancy-induced hypertension, and other pregnancy complications (4). Women with PCOS have higher risks for central obesity, impaired glucose tolerance, metabolic syndrome and type 2 diabetes when compared to age- and adiposity-matched controls (5–10). Understanding the relevance of polycystic ovaries (PCO) in the clinical presentation of PCOS has important implications for improving the efficacy of treatments for ovulatory dysfunction. Since obesity worsens the reproductive and metabolic phenotypes of PCOS (11), lifestyle intervention (diet and/or exercise) is recommended as the initial treatment in overweight and obese patients (12–14), Most clinical trials involving women with PCOS have reported improvements in gonadotropin secretion, hyperandrogenism and insulin sensitivity with weight loss of 5–10% (12,15,16). Many studies have also shown increased frequency of menses, sporadic ovulation and pregnancy with weight loss (12). However, data supporting the resumption of regular ovulatory cycles are sparse and unconvincing, as interventions have been limited in duration and by their use of insufficient markers to confirm ovulation (17).

Impact/Significance

Overall, improvements in reproductive outcomes have been noted in a wide range of patients (13–92%)(12) and could be interpreted to mean that lifestyle modification is not a universal solution for anovulation in PCOS (17). Factors that influence or predict the ovulatory response to weight loss are ill-defined. Improvements in the reproductive phenotype may depend on the degree of weight loss(18–22) or change in total/ regional adiposity (19–24). Weight loss may also fail to stimulate ovulation in those with greater severity of baseline endocrine abnormalities (21,24–26). To the best of our knowledge, morphologic predictors of the ovulatory response to weight loss have not been evaluated. Such predictors may best identify those likely to respond to treatment, since serum measures of endocrine status in women are technically challenging (particularly, androgens (27)) and ovarian morphology is a known predictor of the ovarian response to pharmacologic intervention (28).

In the following proposal, we aim to refine the sonographic definition of PCO by establishing the specificity of these criteria against normoandrogenic anovulation (NA-Anov) in women with obesity. We will also clarify any ability of a serum marker [anti-Müllerian hormone (AMH)] to better inform the diagnosis or ovulatory response to weight loss in PCOS and NA-Anov compared to morphologic features. Our approach is rooted in using state-of-the-art ultrasound technology to reveal, for the first time, how antral follicle development is uniquely altered in PCOS and NA-Anov, and how these perturbations are further exacerbated by adiposity. By performing longitudinal assessments of ovarian morphology, we will define the physiologic basis for morphologic variations in anovulatory disorders and determine how those aberrations differentially respond to nutritional intervention. We anticipate that these results will usher new approaches for tailored interventions that account for the spectrum of disordered folliculogenesis across anovulatory disorders.

Hypotheses/Aims

Specific Aim 1: To define aberrations in antral follicle development that account for unique aspects of PCO. Serial ovarian ultrasonography will be performed every other day for 4 weeks in order to contrast the kinetics of folliculogenesis in PCOS, NA-Anov and regular ovulatory cycles. Differences in key events of folliculogenesis (i.e. recruitment, selection and dominance) that account for morphologic features of PCO will be defined.

Specific Aim 2: To determine the effectiveness of weight loss to normalize antral follicle development in overweight women with PCOS, NA-Anov and regular ovulatory cycles. Changes in folliculogenesis during a 24-week commercial diet program will be evaluated by serial ovarian ultrasonography in overweight women with PCOS, NA-Anov and regular ovulatory cycles. Improvements in the incidence of recruitment, selection, dominance and ovulation will be contrasted between groups.

Specific Aim 3: To identify sonographic markers that predict the ovulatory response to weight loss. Baseline aspects of ovarian morphology will be modeled against metabolic and endocrine features to establish their potential to predict the likelihood of selection, dominance and ovulation during weight loss. Any differences between groups (PCOS, NA-Anov and regular cycles) will be determined.

Materials/Methods

Participants: We will recruit 75 women with overweight (BMI ≥ 25), including 25 women with PCOS, 25 with NA-Anov, and 25 with regular, ovulatory cycles (controls).

Baseline: Participants will be evaluated at Cornell University by serial transvaginal ultrasonography every other day for 4 weeks. Ultrasound images of the ovaries will be evaluated off-line for the number and diameter of all follicles ≥2mm (29). Growth profiles of large follicles (≥7mm) will be ascertained with the Identity Method (30). Blood samples will be collected at each visit and used to measure changes in gonadotropins and ovarian hormones (FSH, LH, E2, P4). During the early follicular phase or when no dominant follicle is present, participants will undergo an evaluation of metabolic and endocrine status including: 1) a review of menstrual cycle history to determine the extent of cycle disturbance, 2) fasting blood tests to detect serum markers of metabolic syndrome (HDL, LDL, triglycerides), androgens (TT, A4, FT, FAI) and reproductive hormones (LH, FSH, E2, P4, AMH), 3) a physical exam to assess hirsutism (31), vitals and anthropometry, 4) a 2-hour 75g oral glucose tolerance test, and 5) a dual x-ray absorptiometry scan to measure body composition.

Intervention: After this baseline evaluation of antral follicle dynamics, participants will begin a 24-week hypocaloric dietary intervention (Nutrisystem® D). Food diaries will be maintained to monitor compliance. An ultrasound, blood draw, and weight assessment will be performed biweekly. If a dominant follicle (≥10mm) grows to a diameter of 14–16mm, scans will be performed daily until its ovulation or regression and then return to biweekly. Sonographic evidence of ovulation will be corroborated by serum P4 levels.

Response to Intervention: All baseline procedures will be repeated during weeks 20-24 of the intervention. Participants will also return 6 months post-intervention for a single visit to complete procedures 1-6 listed above.

Study type

This is a longitudinal case control study. We aim to recruit 75 overweight women split equally across three groups: PCOS, NA-Anov, and regular, ovulatory cycles (controls). All three groups will receive the same hypocaloric dietary intervention and effects of weight loss on ovulation and metabolism will be assessed.

Existing data

Registration prior to analysis of the data

Explanation of existing data

Existing data includes: menstrual cycle data, anthropometrics, hirsutism, vitals, body composition (DXA scans) and glucose values from pre- and post-intervention oral glucose tolerance tests. These data are only accessible to a handful of study team members. Serum testosterone has not yet been measured for all participants and the ultrasound scans have not all been analyzed, so an observer of the data would be unable to phenotype participants (i.e., categorize them as PCOS, NA-Anov, or control) in order to analyze group differences.

Data collection procedures

Participants will be recruited from Ithaca, NY and the surrounding area from June 2018 through June 2023 using flyers, list-serves, and social networking sites. Participants will receive a total of $2000 cash over the course of the 7-month study. Participants will also receive a free Fitbit at enrollment and 6 free months of Nutrisystem D beginning in month 2 of the study.

Inclusion Criteria:

Ages 18-38
Have both a uterus and two ovaries
Not taking any medications known or suspected to interfere with reproductive function, metabolism, and/or appetite
No use of fertility medications, oral contraceptives, or hormonal IUD in the past 2 months
No known diagnosis of ovarian failure, endometriosis, or another disease (other than PCOS) known or suspected to interfere with reproductive function
Not pregnant, breastfeeding, or planning to become pregnant in the next 7 months
No known diagnosis of any of the following conditions:
• Anorexia or Bulimia
• Cancer (current or recent history)
• Chronic Kidney Disease, Insufficiency, or Failure
• Congestive Heart Failure or Ischemic Heart Disease
• Depression
• Diabetes
• HIV
• Hyperthyroidism
• Inflammatory Bowel Disease, Achalasia, Gastroparesis, Pyloric Stenosis
• Sarcoidosis
• Severe Epilepsy
• Tuberculosis

Participants will be assigned an anonymous study ID at enrollment, and information linking the study ID to their name and identifying information will be stored on a protected server. Study procedures are listed in the methods section above. Participants will be asked to leave the study if they no longer meet inclusion criteria, if they lose an unsafe amount of weight (BMI falls below 18.5), or if they can no longer adhere to the study protocol. In these situations, participants will receive a prorated honorarium based on the duration of their study participation. At the end of the study, participants will receive a summary of their study results (i.e., DXA scan data, blood glucose values, ovarian ultrasound images, vitals, and anthropometrics).

Sample size

Our target samples size is 75, split equally across three groups: PCOS, NA-Anov, and regular, ovulatory cycles (controls).

Budget

This project is supported by NIH grant number 5R01HD093748-02 which funded all primary data collection and many of the hormone analyses. Funding from AthenaDAO and ResearchHub will be used to complete our assessments of serum metabolic and reproductive hormones pre- and post-intervention for the PCOS and control groups. The funding will also support a PhD student who will analyze these data as part of their dissertation.

Total testosterone: $50/sample x 4 samples remaining = $200.00
Lipid Panel: $22.32/sample x 27 samples remaining = $602.64
AMH: $45/sample x 16 samples remaining = $720.00
Graduate Student Stipend (this will cover one third of a summer stipend)= $3477.36
TOTAL = $5000

References

1. March WA, Moore VM, Willson KJ, Phillips DIW, Norman RJ, Davies MJ. The prevalence of polycystic ovary syndrome in a community sample assessed under contrasting diagnostic criteria. Hum Reprod Oxf Engl. 2010 Feb;25(2):544–51.

2. Bozdag G, Mumusoglu S, Zengin D, Karabulut E, Yildiz BO. The prevalence and phenotypic features of polycystic ovary syndrome: a systematic review and meta-analysis. Hum Reprod Oxf Engl. 2016 Dec;31(12):2841–55.

3. Cooney LG, Dokras A. Beyond fertility: polycystic ovary syndrome and long-term health. Fertil Steril. 2018 Oct;110(5):794–809.

4. Bahri Khomami M, Joham AE, Boyle JA, Piltonen T, Silagy M, Arora C, et al. Increased maternal pregnancy complications in polycystic ovary syndrome appear to be independent of obesity-A systematic review, meta-analysis, and meta-regression. Obes Rev Off J Int Assoc Study Obes. 2019 May;20(5):659–74.

5. Wild S, Pierpoint T, McKeigue P, Jacobs H. Cardiovascular disease in women with polycystic ovary syndrome at long-term follow-up: a retrospective cohort study. Clin Endocrinol (Oxf). 2000 May;52(5):595–600.

6. Wild RA, Rizzo M, Clifton S, Carmina E. Lipid levels in polycystic ovary syndrome: systematic review and meta-analysis. Fertil Steril. 2011 Mar 1;95(3):1073-1079.e1-11.

7. Wild S, Pierpoint T, Jacobs H, McKeigue P. Long-term consequences of polycystic ovary syndrome: results of a 31 year follow-up study. Hum Fertil Camb Engl. 2000;3(2):101–5.

8. Kakoly NS, Khomami MB, Joham AE, Cooray SD, Misso ML, Norman RJ, et al. Ethnicity, obesity and the prevalence of impaired glucose tolerance and type 2 diabetes in PCOS: a systematic review and meta-regression. Hum Reprod Update. 2018 Jul 1;24(4):455–67.

9. Lim SS, Davies MJ, Norman RJ, Moran LJ. Overweight, obesity and central obesity in women with polycystic ovary syndrome: a systematic review and meta-analysis. Hum Reprod Update. 2012;18(6):618–37.

10. Behboudi-Gandevani S, Amiri M, Bidhendi Yarandi R, Noroozzadeh M, Farahmand M, Rostami Dovom M, et al. The risk of metabolic syndrome in polycystic ovary syndrome: A systematic review and meta-analysis. Clin Endocrinol (Oxf). 2018 Feb;88(2):169–84.

11. Lim S, Norman R, Davies M, Moran L. The effect of obesity on polycystic ovary syndrome: a systematic review and meta-analysis. Obes Rev. 2013;14(2):95–109.

12. Moran L, Pasquali R, Teede H, Hoeger K, Norman R. Treatment of obesity in polycystic ovary syndrome: a position statement of the Androgen Excess and Polycystic Ovary Syndrome Society. Vol. 92, Fertility and Sterility. 2009. p. 1966–82.

13. Fauser B, Tarlatzis B, Rebar R, Legro R, Balen A, 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(1):28–38.

14. Legro R, Arslanian S, Ehrmann D, Hoeger K, Murad M, Pasquali R, et al. Diagnosis and treatment of polycystic ovary syndrome: an endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2013;98(12):4565–92.

15. Moran L, Hutchison S, Norman R, Teede H. Lifestyle changes in women with polycystic ovary syndrome. Cochrane Database Syst Rev. 2011;(7):CD007506.

16. Bützow T, Lehtovirta M, Siegberg R, Hovatta O, Koistinen R, Seppälä M, et al. The decrease in luteinizing hormone secretion in response to weight reduction is inversely related to the severity of insulin resistance in overweight women. J Clin Endocrinol Metab. 2000;85(9):3271–5.

17. Jarrett B, Lujan M. Impact of hypocaloric dietary intervention on ovulation in obese women with PCOS. Reproduction. 2017;153(1):R15–27.

18. Hoeger K, Kochman L, Wixom N, Craig K, Miller R, Guzick D. A randomized, 48-week, placebo- controlled trial of intensive lifestyle modification and/or metformin therapy in overweight women with polycystic ovary syndrome: a pilot study. Fertil Steril. 2004;82(2):421–9.

19. Palomba S, Giallauria F, Falbo A, Russo T, Oppedisano R, Tolino A, et al. Structured exercise training programme versus hypocaloric hyperproteic diet in obese polycystic ovary syndrome patients with anovulatory infertility: a 24-week pilot study. Hum Reprod. 2008;23(3):642–50.

20. Thomson R, Buckley J, Noakes M, Clifton P, Norman R, Brinkworth G. The effect of a hypocaloric diet with and without exercise training on body composition, cardiometabolic risk profile, and reproductive function in overweight and obese women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2008;93(9):3373–80.

21. Thomson R, Buckley J, Moran L, Noakes M, Clifton P, Norman R, et al. The effect of weight loss on anti-Müllerian hormone levels in overweight and obese women with polycystic ovary syndrome and reproductive impairment. Hum Reprod. 2009;24(8):1976–81.

22. Kuchenbecker W, Groen H, van Asselt S, Bolster J, Zwerver J, Slart R, et al. In women with polycystic ovary syndrome and obesity, loss of intra-abdominal fat is associated with resumption of ovulation. Hum Reprod. 2011;26(9):2505–12.

23. Huber-Buchholz MM, Carey D, Norman R. Restoration of reproductive potential by lifestyle modification in obese polycystic ovary syndrome: role of insulin sensitivity and luteinizing hormone. J Clin Endocrinol Metab. 1999;84(4):1470–4.

24. Pasquali R, Gambineri A, Cavazza C, Gasparini D, Ciampaglia W, Cognigni G, et al. Heterogeneity in the responsiveness to long-term lifestyle intervention and predictability in obese women with polycystic ovary syndrome. Eur J Endocrinol. 2011;164(1):53–60.

25. van Dam E, Roelfsema F, Veldhuis J, Hogendoorn S, Westenberg J, Helmerhorst F, et al. Retention of estradiol negative feedback relationship to LH predicts ovulation in response to caloric restriction and weight loss in obese patients with polycystic ovary syndrome. Am J Physiol Endocrinol Metab. 2004;286:E615–20.

26. Moran L, Noakes M, Clifton P, Norman R. The use of anti-mullerian hormone in predicting menstrual response after weight loss in overweight women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2007;92(10):3796–802.

27. Rosner W, Auchus R, Azziz R, Sluss P, Raff H. Position statement: Utility, Limitations, and Pitfalls in Measuring Testosterone: An Endocrine Society Position Statement. J Clin Endocrinol Metab. 2007;92(2):405–13.

28. Hendriks D, Mol B, Bancsi L, Te Velde E, Broekmans F. Antral follicle count in the prediction of poor ovarian response and pregnancy after in vitro fertilization: a meta-analysis and comparison with basal follicle-stimulating hormone level. Fertil Steril. 2005;83(2):291–301.

29. Lujan M, Brooks E, Kepley A, Chizen D, Pierson R, Peppin A. Grid analysis improves reliability in follicle counts made by ultrasonography in women with polycystic ovary syndrome. Ultrasound Med Biol. 2010;36(5):712–8.

30. Baerwald A, Adams G, Pierson R. A new model for ovarian follicular development during the human menstrual cycle. Fertil Steril. 2003;80(1):116–22.

31. Ferriman D, Gallwey J. Clinical assessment of body hair growth in women. J Clin Endocrinol Metab. 1961;21:1440–7.

85:T534b,

Drafts

Impact of PCOS status on ovulatory and metabolic changes with weight loss

Drafts

Drafts

Impact of PCOS status on ovulatory and metabolic changes with weight loss