Obstructive sleep apnea and type 2 diabetes: interacting epidemics

Current world literature

This bibliography is compiled by clinicians from the journals listed at the end of this publication. It is based on literature entered into our database between 1 February 2008 and 31 January 2009 (articles are generally added to the database about two and a half months after publication). In addition, the bibliography contains every paper annotated by reviewers; these references were obtained from a variety of bibliographic databases and published between the beginning of the review period and the time of going to press. The bibliography has been grouped into topics that relate to the reviews in this issue.

Obstructive sleep apnea in patients admitted for acute myocardial infarction. Prevalence, predictors, and effect on microvascular perfusion

BACKGROUND

We investigated the prevalence and predictors of obstructive sleep apnea (OSA) in patients admitted to the hospital for acute myocardial infarction and whether OSA has any association with microvascular perfusion after primary percutaneous coronary intervention (PCI).

METHODS

Recruited patients were scheduled to undergo an overnight sleep study between 2 and 5 days after primary PCI. An apnea-hypopnea index (AHI) of > or = 15 was considered diagnostic of OSA. Impaired microvascular perfusion after primary PCI was defined as an ST-segment resolution of < or = 70%, myocardial blush grade 0 or 1, or a corrected Thrombolysis in Myocardial Infarction (TIMI) [antegrade flow scale] frame count > 28.

RESULTS

Sleep study was performed in 120 patients and completed in 105 patients (study cohort, mean age 53 +/- 10 years, male 98%) with uncomplicated myocardial infarction. An AHI was > or = 15 in 69 patients (OSA-positive), giving a prevalence of 65.7%. Diabetes mellitus was found to be a significant risk factor for OSA (odds ratio, 2.86; 95% confidence interval, 1.06 to 8.24; p = 0.033). There were no differences between OSA-positive and OSA-negative groups with regard to the percentage of patients with < or = 70% ST-segment resolution (73% vs 64%, respectively; p = 0.411), myocardial blush grade 0 or 1 (39.1% vs 38.9%, respectively; p = 1.000), or corrected TIMI frame count > 28 (21.7% vs 25.0%, respectively; p = 0.807).

CONCLUSIONS

We found a high prevalence of previously undiagnosed OSA in patients admitted with acute myocardial infarction. Diabetes mellitus was independently associated with OSA. No evidence indicated that OSA is associated with impaired microvascular perfusion after primary PCI.

Validation of commonly used reference genes for sleep-related gene expression studies

Background

Sleep is a restorative process and is essential for maintenance of mental and physical health. In an attempt to understand the complexity of sleep, multidisciplinary strategies, including genetic approaches, have been applied to sleep research. Although quantitative real time PCR has been used in previous sleep-related gene expression studies, proper validation of reference genes is currently lacking. Thus, we examined the effect of total or paradoxical sleep deprivation (TSD or PSD) on the expression stability of the following frequently used reference genes in brain and blood: beta-actin (b-actin), beta-2-microglobulin (B2M), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and hypoxanthine guanine phosphoribosyl transferase (HPRT).

Results

Neither TSD nor PSD affected the expression stability of all tested genes in both tissues indicating that b-actin, B2M, GAPDH and HPRT are appropriate reference genes for the sleep-related gene expression studies. In order to further verify these results, the relative expression of brain derived neurotrophic factor (BDNF) and glycerol-3-phosphate dehydrogenase1 (GPD1) was evaluated in brain and blood, respectively. The normalization with each of four reference genes produced similar pattern of expression in control and sleep deprived rats, but subtle differences in the magnitude of expression fold change were observed which might affect the statistical significance.

Conclusion

This study demonstrated that sleep deprivation does not alter the expression stability of commonly used reference genes in brain and blood. Nonetheless, the use of multiple reference genes in quantitative RT-PCR is required for the accurate results.

Effects of poor and short sleep on glucose metabolism and obesity risk

The importance of sleep to hormones and glucose metabolism was first documented more than four decades ago. Since then, sleep curtailment has become an endemic behavior in modern society. In addition, the prevalence of sleep disorders, particularly obstructive sleep apnea (OSA), has increased. OSA is very common in endocrine and metabolic disorders, but often remains undiagnosed. This Review summarizes the laboratory and epidemiologic evidence that suggests how sleep loss, either behavioral or disease-related, and poor quality of sleep might promote the development of obesity and diabetes mellitus, and exacerbate existing endocrine conditions. Treatment of sleep disorders has the potential to improve glucose metabolism and energy balance. Screening for habitual sleep patterns and OSA might be critically important for patients with endocrine and metabolic disorders.

Diabetes is an independent risk factor for severe nocturnal hypoxemia in obese patients. A case-control study

BACKGROUND

Type 2 diabetes mellitus (T2DM) and obesity have become two of the main threats to public health in the Western world. In addition, obesity is the most important determinant of the sleep apnea-hypopnea syndrome (SAHS), a condition that adversely affects glucose metabolism. However, it is unknown whether patients with diabetes have more severe SAHS than non-diabetic subjects. The aim of this cross-sectional case-control study was to evaluate whether obese patients with T2DM are more prone to severe SAHS than obese non-diabetic subjects.

METHODOLOGY/PRINCIPAL FINDINGS

Thirty obese T2DM and 60 non-diabetic women closely matched by age, body mass index, waist circumference, and smoking status were recruited from the outpatient Obesity Unit of a university hospital. The exclusion criteria included chronic respiratory disease, smoking habit, neuromuscular and cerebrovascular disease, alcohol abuse, use of sedatives, and pregnancy. Examinations included a non-attended respiratory polygraphy, pulmonary function testing, and an awake arterial gasometry. Oxygen saturation measures included the percentage of time spent at saturations below 90% (CT90). A high prevalence of SAHS was found in both groups (T2DM:80%, nondiabetic:78.3%). No differences in the number of sleep apnea-hypopnea events between diabetic and non-diabetic patients were observed. However, in diabetic patients, a significantly increase in the CT90 was detected (20.2+/-30.2% vs. 6.8+/-13,5%; p = 0.027). In addition, residual volume (RV) was significantly higher in T2DM (percentage of predicted: 79.7+/-18.1 vs. 100.1+/-22.8; p<0.001). Multiple linear regression analyses showed that T2DM but not RV was independently associated with CT90.

CONCLUSIONS/SIGNIFICANCE

T2DM adversely affects breathing during sleep, becoming an independent risk factor for severe nocturnal hypoxemia in obese patients. Given that SAHS is a risk factor of cardiovascular disease, the screening for SAHS in T2DM patients seems mandatory.

The "etiome": identification and clustering of human disease etiological factors

Background

Both genetic and environmental factors contribute to human diseases. Most common diseases are influenced by a large number of genetic and environmental factors, most of which individually have only a modest effect on the disease. Though genetic contributions are relatively well characterized for some monogenetic diseases, there has been no effort at curating the extensive list of environmental etiological factors.

Results

From a comprehensive search of the MeSH annotation of MEDLINE articles, we identified 3,342 environmental etiological factors associated with 3,159 diseases. We also identified 1,100 genes associated with 1,034 complex diseases from the NIH Genetic Association Database (GAD), a database of genetic association studies. 863 diseases have both genetic and environmental etiological factors available. Integrating genetic and environmental factors results in the "etiome", which we define as the comprehensive compendium of disease etiology. Clustering of environmental factors may alert clinicians of the risks of added exposures, or synergy in interventions to alter these factors. Clustering of both genetic and environmental etiological factors puts genes in the context of environment in a quantitative manner.

Conclusion

In this paper, we obtained a comprehensive list of associations between disease and environmental factors using MeSH annotation of MEDLINE articles. It serves as a summary of current knowledge between etiological factors and diseases. By combining the environmental etiological factors and genetic factors from GAD, we computed the "etiome" profile for 863 diseases. Comparing diseases across these profiles may have utility for clinical medicine, basic science research, and population-based science.

Sleep and the epidemic of obesity in children and adults

Sleep is an important modulator of neuroendocrine function and glucose metabolism in children as well as in adults. In recent years, sleep curtailment has become a hallmark of modern society with both children and adults having shorter bedtimes than a few decades ago. This trend for shorter sleep duration has developed over the same time period as the dramatic increase in the prevalence of obesity. There is rapidly accumulating evidence from both laboratory and epidemiological studies to indicate that chronic partial sleep loss may increase the risk of obesity and weight gain. The present article reviews laboratory evidence indicating that sleep curtailment in young adults results in a constellation of metabolic and endocrine alterations, including decreased glucose tolerance, decreased insulin sensitivity, elevated sympathovagal balance, increased evening concentrations of cortisol, increased levels of ghrelin, decreased levels of leptin, and increased hunger and appetite. We also review cross-sectional epidemiological studies associating short sleep with increased body mass index and prospective epidemiological studies that have shown an increased risk of weight gain and obesity in children and young adults who are short sleepers. Altogether, the evidence points to a possible role of decreased sleep duration in the current epidemic of obesity.

Alterations in Glucose Disposal in Sleep-disordered Breathing

RATIONALE

It is well established that sleep-disordered breathing (SDB) is independently associated with insulin resistance, glucose intolerance, and type 2 diabetes mellitus. However, data on whether SDB alters in vivo kinetics of glucose and insulin are lacking.

OBJECTIVES

The primary goal of this study was to use the frequently sampled intravenous glucose tolerance test (FSIVGTT) in subjects with and without SDB to model the in vivo kinetics of glucose and insulin. Minimal model analysis of the FSIVGTT data was used to derive parameters of insulin sensitivity, glucose effectiveness (a measure of the ability of glucose to mediate its own disposal), and pancreatic beta-cell function.

RESULTS

A total of 118 nondiabetic subjects underwent polysomnography, the FSIVGTT, and body composition measurements including determination of percent body fat. Compared with normal subjects (apnea-hypopnea index < 5 events/h), those with mild, moderate, and severe SDB displayed a 26.7, 36.5 and 43.7% reduction in insulin sensitivity, respectively, independent of age, sex, race, and percent body fat. The disposition index, an integrated measure of pancreatic beta-cell function, was also reduced in patients with moderate to severe SDB. The decrease in insulin sensitivity and the disposition index were correlated with the average degree of oxyhemoglobin desaturation. In contrast, glucose effectiveness was negatively correlated with the frequency of respiratory event-related arousals.

CONCLUSIONS

The results of this study suggest that, independent of adiposity, SDB is associated with impairments in insulin sensitivity, glucose effectiveness, and pancreatic beta-cell function. Collectively, these defects may increase the risk of glucose intolerance and type 2 diabetes mellitus in SDB.

Metabolic effects of the obstructive sleep apnea syndrome and cardiovascular risk

The obstructive sleep apnea syndrome (OSAS) is characterized by collapse of the upper airway during sleep, recurring apneas, intermittent hypoxemia and daytime somnolence. OSAS is often associated with obesity, and its prevalence is expected to rise due to the obesity epidemics worldwide. OSAS is associated with increased cardiovascular risk which appears to be normalized by treatment with nasal continuous positive airway pressure (nCPAP) during sleep, suggesting an independent role of OSAS in accelerating atherosclerosis. Insulin resistance (IR) and the metabolic syndrome (MetS) are often found in OSAS patients, but the relative role played by OSAS and obesity is still unclear. Both OSAS and MetS may exert negative synergistic effects on the cardiovascular system through multiple mechanisms (hypoxemia, sleep disruption, activation of the sympathetic nervous system, inflammatory activation). Besides nCPAP treatment, pharmacologic interventions to treat obesity and the MetS could improve cardiovascular prevention in OSAS.

Impact of obstructive sleep apnea on insulin resistance and glucose tolerance in women with polycystic ovary syndrome

CONTEXT

Insulin resistance, impaired glucose tolerance, and type 2 diabetes are common in women with polycystic ovary syndrome (PCOS). Obstructive sleep apnea (OSA) has been linked to metabolic dysfunction. We studied women with and without PCOS to determine the extent to which OSA is responsible for insulin resistance and glucose intolerance in PCOS.

METHODS

In a prospective design, 52 women with PCOS and 21 women without PCOS of similar age and body mass index had an overnight polysomnogram and a 75-g oral glucose tolerance test.

RESULTS

Twenty-nine women (56%) with PCOS had OSA compared with four controls (19%) (adjusted odds ratio 7.1; 95% confidence interval, 1.7-45.7; P = 0.01). PCOS women with OSA were more insulin resistant than those without OSA [homeostasis model assessment (HOMA) index 5.7 +/- 0.4 vs. 3.5 +/- 0.4; P = 0.006] after controlling for age, body mass index, and ethnicity. Impaired glucose tolerance was found in 16 of 29 (55%) PCOS women with OSA and only six of 23 (26%) of those without OSA (unadjusted P = 0.049). Insulin resistance and glucose intolerance were highly correlated with the presence and severity of OSA. Among PCOS women with normal glucose tolerance, the presence of OSA was associated with a nearly 2-fold higher fasting insulin level and HOMA index. The severity of OSA was a highly significant predictor of the fasting concentrations of glucose and insulin as well as the 2-h glucose concentration and HOMA index.

CONCLUSIONS

OSA is a highly prevalent and important determinant of insulin resistance, glucose intolerance, and type 2 diabetes in PCOS.

Polycystic Ovary Syndrome and Obstructive Sleep Apnea

Polycystic ovary syndrome (PCOS), the most common endocrine disorder of pre-menopausal women, is characterized by chronic hyperandrogenism, oligoanovulation, obesity and insulin resistance. Importantly, PCOS women are at increased risk for glucose intolerance, type 2 diabetes and cardiovascular disorders. Recent reports indicate an unexpectedly high prevalence of obstructive sleep apnea (OSA) in PCOS. Alterations in sex steroids (i.e. high androgen and low estrogen levels) and increased visceral adiposity in PCOS could potentially contribute to the increased prevalence of OSA in this disorder. There is some evidence to suggest that there may be strong associations between the presence and severity of OSA and the metabolic disturbances that characterize PCOS. Causal mechanisms in the link between PCOS and OSA remain to be elucidated. Clinicians who manage PCOS patients should be aware of the high prevalence of OSA in these patients and systematically evaluate these women for sleep disturbances.