Diabetes, Polycystic Ovarian Syndrome, Obstructive Sleep Apnea, and Obesity: A Systematic Review and Important Emerging Themes

Psychological symptoms and brain activity alterations in women with PCOS and their relation to the reduced quality of life: a narrative review

BACKGROUND

Polycystic ovary syndrome (PCOS) is the most common feminine endocrine disorder, characterized by androgen excess, ovulatory dysfunction, and polycystic ovarian morphology. The negative impact of symptoms on the quality of life (QoL) of patients is still not clear.

PURPOSE

The present review aimed at studying the impact of the symptoms, the psychological symptoms, and brain alterations in women with PCOS.

METHODS

A systematic search was undertaken for studies that assessed the impact of PCOS symptoms on QoL, psychological symptoms, and brain alterations in PCOS patients.

RESULTS

Most of the information about QoL came from psychometric studies, which used culture-based questionnaires. Alterations of sleep quality, body image, and mood disorders can negatively affect the QoL of the patients. Sexual satisfaction and desire were affected by PCOS. Brain imaging studies showed functional alterations that are associated with impairments of visuospatial working memory, episodic and verbal memory, attention, and executive function.

CONCLUSIONS

Several factors can negatively influence the quality of life of the patients, and they are directly related to hyperandrogenism and the risk of infertility. In particular, obesity, hirsutism, acne, and the fear of infertility can have a direct impact on self-esteem and sexual function. Metabolic and psychiatric comorbidities, such as mood, anxiety, and eating disorders, can affect the well-being of the patients. Moreover, specific cognitive alterations, such as impairments in attention and memory, can limit PCOS patients in a series of aspects of daily life.

Comorbidities in women with polycystic ovary syndrome: a sibling study

BACKGROUND

Polycystic ovary syndrome (PCOS) has previously been associated with several comorbidities that may have shared genetic, epigenetic, developmental or environmental origins. PCOS may be influenced by prenatal androgen excess, poor intrauterine or childhood environmental factors, childhood obesity and learned health risk behaviors. We analyzed the association between PCOS and several relevant comorbidities while adjusting for early-life biological and socioeconomic conditions, also investigating the extent to which the association is affected by familial risk factors.

METHODS

This total-population register-based cohort study included 333,999 full sisters, born between 1962 and 1980. PCOS and comorbidity diagnoses were measured at age 17-45 years through national hospital register data from 1997 to 2011, and complemented with information on the study subjects´ early-life and social characteristics. In the main analysis, sister fixed effects (FE) models were used to control for all time-invariant factors that are shared among sisters, thereby testing whether the association between PCOS and examined comorbidities is influenced by unobserved familial environmental, social or genetic factors.

RESULTS

Three thousand five hundred seventy women in the Sister sample were diagnosed with PCOS, of whom 14% had obesity, 8% had depression, 7% had anxiety and 4% experienced sleeping, sexual and eating disorders (SSE). Having PCOS increased the odds of obesity nearly 6-fold (adjusted OR (aOR): 5.9 [95% CI:5.4-6.5]). This association was attenuated in models accounting for unobserved characteristics shared between full sisters, but remained considerable in size (Sister FE: aOR: 4.5 [95% CI: 3.6-5.6]). For depression (Sister FE: aOR: 1.4 [95% CI: 1.2-1.8]) and anxiety (Sister FE: aOR: 1.5 [95% CI: 1.2-1.8), there was a small decrease in the aORs when controlling for factors shared between sisters. Being diagnosed with SSE disorders yielded a 2.4 aOR (95% CI:2.0-2.6) when controlling for a comprehensive set of individual-level confounders, which only decreased slightly when controlling for factors at the family level such as shared genes or parenting style. Accounting for differences between sisters in observed early-life circumstances influenced the estimated associations marginally.

CONCLUSION

Having been diagnosed with PCOS is associated with a markedly increased risk of obesity and sleeping, sexual and eating disorders, also after accounting for factors shared between sisters and early-life conditions.

Evaluation of daytime sleepiness and insomnia symptoms in OSA patients with a characterization of symptom-defined phenotypes and their involvement in depression comorbidity-a cross-sectional clinical study

Introduction

Recent research highlights the significance of insomnia and sleepiness, shifting from obstructive sleep apnea (OSA) severity and sleep structure, in defining OSA phenotypes.

Objectives

This study aimed to characterize insomnia and sleepiness associated with OSA phenotypes and assess their involvement in depression symptoms (DS) in OSA.

Materials and methods

This cross-sectional, clinical study included 181 participants who underwent polysomnography (PSG) and filled out questionnaires, including the Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), and Beck Depression Index (BDI). They were categorized into phenotypes: insomnia-sleepiness (I + S; ESS ≥ 11; ISI ≥ 15; n = 20), sleepiness (S; ESS ≥ 11; ISI < 15; n = 22), insomnia (I; ESS < 11; ISI ≥ 15), and asymptomatic (A; ESS < 11; ISI<15; n=55).

Results

A linear regression model for the BDI score (R2 = 0.357, p < 0.001) included ISI score and subjective-to-objective sleep latency ratio. The ISI score was a predictive factor for mild and moderate DS [OR = 1.23 (95% CI: 1.09-1.38), p < 0.001 and OR = 1.39 (95% CI: 1.13-1.72), p = 0.002]. The I and I + S phenotypes are characterized by higher BDI scores (p < 0.001 and p = 0.02), longer subjective sleep latency (p = 0.008 and p = 0.04), and shorter subjective total sleep time (TST; p = 0.049 and p = 0.006) compared to A. Furthermore, the I and I + S groups had shorter subjective TST than S (p = 0.03 and p = 0.047). The I and I + S had higher BDI scores than A (p < 0.001 and p = 0.02, respectively) and S (p < 0.001 and p = 0.02, respectively). The I phenotype was associated with the risk of mild and moderate DS (OR = 5.61 (95% CI: 1.91-16.53), p < 0.001 and OR = 9.55 (95% CI: 1.81-50.48), p = 0.008 respectively). Moreover, the I + S phenotype presented an even greater risk for mild DS (OR = 10.29 (95% CI: 2.95-35.85), p < 0.001).

Conclusion

Using clinical features for OSA phenotyping holds promise for finding OSA individuals with increased risk for DS occurrence.

Approach the Patient With Obstructive Sleep Apnea and Obesity

Obstructive sleep apnea (OSA) and obesity are highly prevalent and bidirectionally associated. OSA is underrecognized, however, particularly in women. By mechanisms that overlap with those of obesity, OSA increases the risk of developing, or having poor outcomes from, comorbid chronic disorders and impairs quality of life. Using 2 illustrative cases, we discuss the relationships between OSA and obesity with type 2 diabetes, dyslipidemia, cardiovascular disease, cognitive disturbance, mood disorders, lower urinary tract symptoms, sexual function, and reproductive disorders. The differences in OSA between men and women, the phenotypic variability of OSA, and comorbid sleep disorders are highlighted. When the probability of OSA is high due to consistent symptoms, comorbidities, or both, a diagnostic sleep study is advisable. Continuous positive airway pressure or mandibular advancement splints improve symptoms. Benefits for comorbidities are variable depending on nightly duration of use. By contrast, weight loss and optimization of lifestyle behaviors are consistently beneficial.

Visceral Adiposity Index as an Indicator for Menstrual Disturbance, Hormonal and Metabolic Dysfunction in Polycystic Ovarian Syndrome

BACKGROUND

Increase in visceral adiposity is characteristic of polycystic ovarian syndrome (PCOS) and is the main cause of insulin resistance and hyperandrogenism. This study tried to compare the visceral adiposity index (VAI) in PCOS women and control population, thereby exploring its correlation with ovarian morphology, hormonal and metabolic dysfunction.

MATERIALS AND METHODS

Reproductive-age women who fulfilled the Rotterdam criteria for PCOS constituted the cases. Control population consisted of the same number of non-PCOS women. History of menstrual irregularity and features of hyperandrogenism were noted. Overnight fasting serum hormonal profile on second day of the cycle, oral glucose tolerance test (OGTT) and serum fasting insulin and lipid profile were obtained. Ultrasound evaluation was done simultaneously. Free androgen index (FAI), homeostatic model assessment of insulin resistance (HOMA-IR) and VAI were calculated.

RESULTS

Serum androgen levels and OGTT were greater in PCOS women. No significant difference was noted in serum fasting glucose, fasting insulin and lipid profile between cases and controls. Both systolic and diastolic blood pressures were significantly higher among women with PCOS. Mean ovarian volume, antral follicle count, FAI and HOMA-IR were higher in PCOS women. VAI was significantly higher in cases compared to controls. VAI demonstrated a strong negative correlation with number of menstrual cycles per year. Increasing VAI was associated with longer menstrual cycles and correlated positively with greater severity of anovulation. VAI also showed highly significant correlation with fasting blood glucose and statistically significant moderately strong positive correlation with OGTT values at two hours post glucose challenge, systolic blood pressure and mean ovarian volume. There was no demonstrable correlation between androgen levels or HOMA-IR values.

CONCLUSION

VAI is higher in women with PCOS. It correlates positively with features of disease severity and ovarian morphology. An assessment of VAI in PCOS women could be predictive of a greater propensity for development of classical metabolic risk factors.