The role of metformin in ovulation induction: Current status

Pathophysiological Effects of Contemporary Lifestyle on Evolutionary-Conserved Survival Mechanisms in Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is increasingly being characterized as an evolutionary mismatch disorder that presents with a complex mixture of metabolic and endocrine symptoms. The Evolutionary Model proposes that PCOS arises from a collection of inherited polymorphisms that have been consistently demonstrated in a variety of ethnic groups and races. In utero developmental programming of susceptible genomic variants are thought to predispose the offspring to develop PCOS. Postnatal exposure to lifestyle and environmental risk factors results in epigenetic activation of developmentally programmed genes and disturbance of the hallmarks of health. The resulting pathophysiological changes represent the consequences of poor-quality diet, sedentary behaviour, endocrine disrupting chemicals, stress, circadian disruption, and other lifestyle factors. Emerging evidence suggests that lifestyle-induced gastrointestinal dysbiosis plays a central role in the pathogenesis of PCOS. Lifestyle and environmental exposures initiate changes that result in disturbance of the gastrointestinal microbiome (dysbiosis), immune dysregulation (chronic inflammation), altered metabolism (insulin resistance), endocrine and reproductive imbalance (hyperandrogenism), and central nervous system dysfunction (neuroendocrine and autonomic nervous system). PCOS can be a progressive metabolic condition that leads to obesity, gestational diabetes, type two diabetes, metabolic-associated fatty liver disease, metabolic syndrome, cardiovascular disease, and cancer. This review explores the mechanisms that underpin the evolutionary mismatch between ancient survival pathways and contemporary lifestyle factors involved in the pathogenesis and pathophysiology of PCOS.

Prenatal testosterone exposure induces insulin resistance, uterine oxidative stress and pro-inflammatory status in rats

Prenatal androgen excess is considered one of the main causes of the development of polycystic ovary syndrome. In this study, we investigated the effect of prenatal hyperandrogenization (PH) on the physiology of the adult uterine tissue using a murine model of fetal programming caused by androgen excess in adult female rats. Pregnant rats were hyperandrogenized with testosterone and female offspring were studied when adult. Our results showed that PH leads to hyperglycemia and hyperinsulinemia. Consequently, PH developed insulin resistance and a systemic inflammatory state reflected by increased C-reactive protein. In the uterine tissue, levels of PPAR gamma-an important metabolic sensor in the endometrium-were found to be impaired. Moreover, PH induced a pro-inflammatory and an unbalanced oxidative state in the uterus reflected by increased COX-2, lipid peroxidation, and NF-κB. In summary, our results revealed that PH leads to a compromised metabolic state likely consequence of fetal reprogramming.

Gonadal hormones and stroke risk: PCOS as a case study

It is well known that stroke incidence and outcome is sex-dependent and influenced by age and gonadal hormones. In post-menopausal and/or aged females, declining estrogen levels increases stroke risk. However, women who experience early menopause also have an increase in stroke risk. This suggests that, regardless of age, gonadal hormones regulate stroke risk and severity. This review discusses prolonged gonadal hormone dysfunction in a common female endocrine disorder known as polycystic ovarian syndrome, PCOS, and the associated increased risk of stroke due to resulting hyperandrogenism and metabolic comorbidities.

Mini review: The FDA-approved prescription drugs that induce ovulation in women with ovulatory problems

Infertility is defined as not being able to become pregnant after 12 months or more of unprotected sexual intercourse. Female infertility as a serious health issue can result from ovulation disorders, menstrual cycle problems, structural problems, and environmental factors. Ovulation occurs once a month between the time of menarche and menopause. The release of a mature egg from the ovary is controlled with the hypothalamic-pituitary-ovarian axis. Several hormones such as gonadotropin-releasing hormone (GnRH), FSH (follicle-stimulating hormone), LH (luteinizing hormone), estrogen, and progesterone play fundamental roles in the ovulation process. Both FSH and LH are the main treatment for women with ovulation disorders. Depending on the reasons for infertility, several different types of treatment are available for infertile women. Fertility drugs as an important part of treatment work like the natural hormones to treat infertility. Several fertility drugs can regulate ovulation and the release of an egg from the ovary in women with polycystic ovary syndrome (PCOS) or undergoing in vitro fertilization (IVF) treatment. This mini-review is about the FDA-approved prescription drugs that induce ovulation in women with ovulatory problems.

Network-based approach for analyzing intra- and interfluid metabolite associations in human blood, urine, and saliva

Most studies investigating human metabolomics measurements are limited to a single biofluid, most often blood or urine. An organism's biochemical pool, however, comprises complex transboundary relationships, which can only be understood by investigating metabolic interactions and physiological processes spanning multiple parts of the human body. Therefore, we here propose a data-driven network-based approach to generate an integrated picture of metabolomics associations over multiple fluids. We performed an analysis of 2251 metabolites measured in plasma, urine, and saliva, from 374 participants of the Qatar Metabolomics Study on Diabetes (QMDiab). Gaussian graphical models (GGMs) were used to estimate metabolite-metabolite interactions on different subsets of the data set. First, we compared similarities and differences of the metabolome and the association networks between the three fluids. Second, we investigated the cross-talk between the fluids by analyzing correlations occurring between them. Third, we propose a framework for the analysis of medically relevant phenotypes by integrating type 2 diabetes, sex, age, and body mass index into our networks. In conclusion, we present a generic, data-driven network-based approach for structuring and visualizing metabolite correlations within and between multiple body fluids, enabling unbiased interpretation of metabolomics multifluid data.