Retinol-Binding Protein 4 and Insulin Resistance in Polycystic Ovary Syndrome

OBJECTIVE—Polycystic ovary syndrome (PCOS) is an insulin-resistant state with insulin resistance being an established therapeutic target; however, measurement of insulin resistance remains challenging. We aimed to 1) determine serum retinol-binding protein 4 (RBP4) levels (purported to reflect insulin resistance) in women with PCOS and control subjects, 2) examine the relationship of RBP4 to conventional markers of insulin resistance, and 3) examine RBP4 changes with interventions modulating insulin resistance in overweight women with PCOS

Inflammatory and other biomarkers: role in pathophysiology and prediction of gestational diabetes mellitus

Understanding pathophysiology and identifying mothers at risk of major pregnancy complications is vital to effective prevention and optimal management. However, in current antenatal care, understanding of pathophysiology of complications is limited. In gestational diabetes mellitus (GDM), risk prediction is mostly based on maternal history and clinical risk factors and may not optimally identify high risk pregnancies. Hence, universal screening is widely recommended. Here, we will explore the literature on GDM and biomarkers including inflammatory markers, adipokines, endothelial function and lipids to advance understanding of pathophysiology and explore risk prediction, with a goal to guide prevention and treatment of GDM.Sally K. Abell, Barbora De Courten, Jacqueline A. Boyle and Helena J. Teed

Externally validated prediction models for pre‐eclampsia:systematic review and meta‐analysis

Objective: This systematic review and meta‐analysis aimed to evaluate the performance of existing externally validated prediction models for pre‐eclampsia (PE) (specifically, any‐onset, early‐onset, late‐onset and preterm PE). Methods: A systematic search was conducted in five databases (MEDLINE, EMBASE, Emcare, CINAHL and Maternity & Infant Care Database) and using Google Scholar/reference search to identify studies based on the Population, Index prediction model, Comparator, Outcome, Timing and Setting (PICOTS) approach until 20 May 2023. We extracted data using the CHARMS checklist and appraised the risk of bias using the PROBAST tool. A meta‐analysis of discrimination and calibration performance was conducted when appropriate. Results: Twenty‐three studies reported 52 externally validated prediction models for PE (one preterm, 20 any‐onset, 17 early‐onset and 14 late‐onset PE models). No model had the same set of predictors. Fifteen any‐onset PE models were validated externally once, two were validated twice and three were validated three times, while the Fetal Medicine Foundation (FMF) competing‐risks model for preterm PE prediction was validated widely in 16 different settings. The most common predictors were maternal characteristics (prepregnancy body mass index, prior PE, family history of PE, chronic medical conditions and ethnicity) and biomarkers (uterine artery pulsatility index and pregnancy‐associated plasma protein‐A). The FMF model for preterm PE (triple test plus maternal factors) had the best performance, with a pooled area under the receiver‐operating‐characteristics curve (AUC) of 0.90 (95% prediction interval (PI), 0.76–0.96), and was well calibrated. The other models generally had poor‐to‐good discrimination performance (median AUC, 0.66 (range, 0.53–0.77)) and were overfitted on external validation. Apart from the FMF model, only two models that were validated multiple times for any‐onset PE prediction, which were based on maternal characteristics only, produced reasonable pooled AUCs of 0.71 (95% PI, 0.66–0.76) and 0.73 (95% PI, 0.55–0.86). Conclusions: Existing externally validated prediction models for any‐, early‐ and late‐onset PE have limited discrimination and calibration performance, and include inconsistent input variables. The triple‐test FMF model had outstanding discrimination performance in predicting preterm PE in numerous settings, but the inclusion of specialized biomarkers may limit feasibility and implementation outside of high‐resource settings. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology

Endocrine and metabolic interactions in healthy pregnancies and hyperinsulinemic pregnancies affected by polycystic ovary syndrome, diabetes and obesity

During pregnancy, the fetoplacental unit is key in the pronounced physiological endocrine changes which support pregnancy, fetal development and survival, birth and lactation. In healthy women, pregnancy is characterized by changes in insulin sensitivity and increased maternal androgen levels. These are accompanied by a suite of mechanisms that support fetal growth, maintain glucose homeostasis and protect both mother and fetus from adverse effects of pregnancy induced insulin and androgen excess. In pregnancies affected by endocrine, metabolic disorders such as polycystic ovary syndrome (PCOS), diabetes and obesity, there is an imbalance of beneficial and adverse impacts of pregnancy induced endocrine changes. These inter-related conditions are characterized by an interplay of hyperinsulinemia and hyperandrogenism which influence fetoplacental function and are associated with adverse pregnancy outcomes including hypertensive disorders of pregnancy, macrosomia, preterm delivery and caesarean section. However, the exact underlying mechanisms and relationships of the endocrine and metabolic milieu in these disorders and the impact they have on the prenatal endocrine environment and developing fetus remain poorly understood. Here we aim to review the complex endocrine and metabolic interactions in healthy women during normal pregnancies and those in pregnancies complicated by hyperinsulinemic disorders (PCOS, diabetes and obesity). We also explore the relationships between these endocrine and metabolic differences and the fetoplacental unit, pregnancy outcomes and the developing fetus

Muscle Carnosine Is Associated with Cardiometabolic Risk Factors in Humans

Background Carnosine is a naturally present dipeptide abundant in skeletal muscle and an over-the counter food additive. Animal data suggest a role of carnosine supplementation in the prevention and treatment of obesity, insulin resistance, type 2 diabetes and cardiovascular disease but only limited human data exists. Methods and Results Samples of vastus lateralis muscle were obtained by needle biopsy. We measured muscle carnosine levels (high-performance liquid chromatography), % body fat (bioimpedance), abdominal subcutaneous and visceral adiposity (magnetic resonance imaging), insulin sensitivity (euglycaemic hyperinsulinemic clamp), resting energy expenditure (REE, indirect calorimetry), free-living ambulatory physical activity (accelerometers) and lipid profile in 36 sedentary non-vegetarian middle aged men (45±7 years) with varying degrees of adiposity and glucose tolerance. Muscle carnosine content was positively related to % body fat (r = 0.35, p = 0.04) and subcutaneous (r = 0.38, p = 0.02) but not visceral fat (r = 0.17, p = 0.33). Muscle carnosine content was inversely associated with insulin sensitivity (r = -0.44, p = 0.008), REE (r = -0.58, p<0.001) and HDL-cholesterol levels (r = -0.34, p = 0.048). Insulin sensitivity and physical activity were the best predictors of muscle carnosine content after adjustment for adiposity. Conclusion Our data shows that higher carnosine content in human skeletal muscle is positively associated with insulin resistance and fasting metabolic preference for glucose. Moreover, it is negatively associated with HDL-cholesterol and basal energy expenditure. Intervention studies targeting insulin resistance, metabolic and cardiovascular disease risk factors are necessary to evaluate its putative role in the prevention and management of type 2 diabetes and cardiovascular disease

Models Predicting Postpartum Glucose Intolerance Among Women with a History of Gestational Diabetes Mellitus: a Systematic Review

Purpose of Review: Despite the crucial role that prediction models play in guiding early risk stratifcation and timely intervention to prevent type 2 diabetes after gestational diabetes mellitus (GDM), their use is not widespread in clinical practice. The purpose of this review is to examine the methodological characteristics and quality of existing prognostic models predicting postpartum glucose intolerance following GDM. Recent Findings. A systematic review was conducted on relevant risk prediction models, resulting in 15 eligible publications from research groups in various countries. Our review found that traditional statistical models were more common than machine learning models, and only two were assessed to have a low risk of bias. Seven were internally validated, but none were externally validated. Model discrimination and calibration were done in 13 and four studies, respectively. Various predictors were identifed, including body mass index, fasting glucose concentration during pregnancy, maternal age, family history of diabetes, biochemical variables, oral glucose tolerance test, use of insulin in pregnancy, postnatal fasting glucose level, genetic risk factors, hemoglobin A1c, and weight. Summary: The existing prognostic models for glucose intolerance following GDM have various methodological shortcomings, with only a few models being assessed to have low risk of bias and validated internally. Future research should prioritize the development of robust, high-quality risk prediction models that follow appropriate guidelines, in order to advance this area and improve early risk stratifcation and intervention for glucose intolerance and type 2 diabetes among women who have had GDM.Yitayeh Belsti, Lisa Moran, Demelash Woldeyohannes Handiso, Vincent Versace, Rebecca Goldstein, Aya Mousa, Helena Teede, Joanne Enticot

Physical activity and mental health in women with polycystic ovary syndrome.

Physical activity is prescribed as a component of primary management for Polycystic Ovary Syndrome (PCOS). This study investigates the association between physical activity and mental health as well as the exercise barriers, motivators and support providers for younger women with and without PCOS to assist in physical activity uptake and prescription for these women

Impact of FTO genotypes on BMI and weight in polycystic ovary syndrome : a systematic review and meta-analysis

Aims/hypothesis FTO gene single nucleotide polymorphisms (SNPs) have been shown to be associated with obesity-related traits and type 2 diabetes. Several small studies have suggested a greater than expected effect of the FTO rs9939609 SNP on weight in polycystic ovary syndrome (PCOS). We therefore aimed to examine the impact of FTO genotype on BMI and weight in PCOS. Methods A systematic search of medical databases (PubMed, EMBASE and Cochrane CENTRAL) was conducted up to the end of April 2011. Seven studies describing eight distinct PCOS cohorts were retrieved; seven were genotyped for SNP rs9939609 and one for SNP rs1421085. The per allele effect on BMI and body weight increase was calculated and subjected to meta-analysis. Results A total of 2,548 women with PCOS were included in the study; 762 were TT homozygotes, 1,253 had an AT/CT genotype, and 533 were AA/CC homozygotes. Each additional copy of the effect allele (A/C) increased the BMI by a mean of 0.19 z score units (95% CI 0.13, 0.24; p = 2.26 × 10−11) and body weight by a mean of 0.20 z score units (95% CI 0.14, 0.26; p = 1.02 × 10−10). This translated into an approximately 3.3 kg/m2 increase in BMI and an approximately 9.6 kg gain in body weight between TT and AA/CC homozygotes. The association between FTO genotypes and BMI was stronger in the cohorts with PCOS than in the general female populations from large genome-wide association studies. Deviation from an additive genetic model was observed in heavier populations. Conclusions/interpretation The effect of FTO SNPs on obesity-related traits in PCOS seems to be more than two times greater than the effect found in large population-based studies. This suggests an interaction between FTO and the metabolic context or polygenic background of PCOS

Weight gain, overweight, and obesity: determinants and health outcomes from the Australian Longitudinal Study on Women’s Health

Recent estimates suggest that 35.3\ua0% of adult Australians are overweight and a further 27.5\ua0% are obese. The Australian Longitudinal Study on Women's Health (ALSWH) is a prospective study of women's health that commenced in Australia in 1996. The study recruited approximately 40,000 women in three birth cohorts, 1973-1978, 1946-1951 and 1921-1926, who have since been followed up approximately every three years using self-report surveys. Six surveys have been completed to date. This review aims to describe the changes in weight and weight status over time in the three ALSWH cohorts, and to review and summarise the published findings to date relating to the determinants and health consequences of weight gain, overweight and obesity. Future plans for the ALSWH include on-going surveys for all cohorts, with a seventh survey in 2013-2015, and establishment of a new cohort of women born in 1990-1995, which is currently being recruited

Association of antenatal diet and physical activity-based interventions with gestational weight gain and pregnancy outcomes: a systematic review and meta-analysis

Published online December 20, 2021.Importance: Excessive gestational weight gain (GWG) is common and associated with adverse pregnancy outcomes. Antenatal lifestyle interventions limit GWG; yet benefits of different intervention types and specific maternal and neonatal outcomes are unclear. Objective: To evaluate the association of different types of diet and physical activity–based antenatal lifestyle interventions with GWG and maternal and neonatal outcomes. Data Sources: A 2-stage systematic literature search of MEDLINE, Embase, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Cochrane Central Register of Controlled Trials, and Health Technology Assessment Database was conducted from February 1, 2017, to May 31, 2020. Search results from the present study were integrated with those from a previous systematic review from 1990 to February 2017. Study Selection: Randomized trials reporting GWG and maternal and neonatal outcomes. Data Extraction and Synthesis: Data were extracted for random-effects meta-analyses to calculate the summary effect estimates and 95% CIs. Main Outcomes and Measures: Outcomes were clinically prioritized, with mean GWG as the primary outcome. Secondary outcomes included gestational diabetes, hypertensive disorders of pregnancy, cesarean section, preterm delivery, large or small for gestational age neonates, neonatal intensive care unit admission, or fetal death. Results: A total of 117 randomized clinical trials of antenatal lifestyle interventions (involving 34 546 women) were included. Overall lifestyle intervention was associated with reduced GWG (−1.15 kg; 95% CI, −1.40 to −0.91), risk of gestational diabetes (odds ratio [OR], 0.79; 95% CI, 0.70-0.89), and total adverse maternal outcomes (OR, 0.89; 95% CI, 0.84-0.94) vs routine care. Compared with routine care, diet was associated with less GWG (−2.63 kg; 95% CI, −3.87 to −1.40) than physical activity (−1.04 kg; 95% CI, −1.33 to −0.74) or mixed interventions (eg, unstructured lifestyle support, written information with weight monitoring, or behavioral support alone) (−0.74 kg; 95% CI, −1.06 to −0.43). Diet was associated with reduced risk of gestational diabetes (OR, 0.61; 95% CI, 0.45-0.82), preterm delivery (OR, 0.43; 95% CI, 0.22-0.84), large for gestational age neonate (OR, 0.19; 95% CI, 0.08-0.47), neonatal intensive care admission (OR, 0.68; 95% CI, 0.48-0.95), and total adverse maternal (OR, 0.75; 95% CI, 0.61-0.92) and neonatal outcomes (OR, 0.44; 95% CI, 0.26-0.72). Physical activity was associated with reduced GWG and reduced risk of gestational diabetes (OR, 0.60; 95% CI, 0.47-0.75), hypertensive disorders (OR, 0.66; 95% CI, 0.48-0.90), cesarean section (OR, 0.85; 95% CI, 0.75-0.95), and total adverse maternal outcomes (OR, 0.78; 95% CI, 0.71-0.86). Diet with physical activity was associated with reduced GWG (−1.35 kg; 95% CI, −1.95 to −0.75) and reduced risk of gestational diabetes (OR, 0.72; 95% CI, 0.54-0.96) and total adverse maternal outcomes (OR, 0.81; 95% CI, 0.69-0.95). Mixed interventions were associated with reduced GWG only. Conclusions and Relevance: This systematic review and meta-analysis found level 1 evidence that antenatal structured diet and physical activity–based lifestyle interventions were associated with reduced GWG and lower risk of adverse maternal and neonatal outcomes. The findings support the implementation of such interventions in routine antenatal care and policy around the world.Helena J. Teede, Cate Bailey, Lisa J. Moran, Mahnaz Bahri Khomami, Joanne Enticott, Sanjeeva Ranasinha, Ewelina Rogozińska, Helen Skouteris, Jacqueline A. Boyle, Shakila Thangaratinam, Cheryce L. Harrison