Sleep-disordered breathing in early pregnancy is associated with insulin resistance

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Sleep-disordered breathing in early pregnancy is associated with insulin resistance or difficulty clearing glucose from the blood, suggests a small study funded by the National Institutes of Health.

The results strengthen the link between sleep-disordered breathing, which includes pauses or slowing of breathing during sleep, and gestational diabetes.

They also suggest that screening pregnant women, particularly those with overweight or obesity, for sleep-disordered breathing could identify those who might benefit from early interventions to reduce their diabetes risk.

The study monitored the sleep of 221 pregnant women with overweight or obesity from the 11th through 15th week of their pregnancies and measured their insulin resistance.

The more frequently they experienced sleep-disordered breathing and the more often their blood oxygen levels dropped during sleep, the more likely they were to have insulin resistance and elevated fasting blood sugar levels. This risk persisted after the investigators considered participants’ age, body mass index and other factors.

Laura Sanapo, M.D., of the Women’s Medicine Collaborative and Brown University Providence, Rhode Island, and colleagues conducted the study, which appears in Sleep. The study was funded by NIH’s Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Heart, Lung and Blood Institute and National Institute of General Medical Sciences.


Obstructive sleep apnea (OSA) is characterized by repeated partial or complete pharyngeal collapse during sleep leading to intermittent hypoxia (IH), sleep fragmentation, and excessive daytime sleepiness [1]. In addition, IH enhances sympathetic tone leading to increase blood sugar levels by decreasing glucose effectiveness and insulin sensitivity [2].

The decrease in physical activity associated with daytime sleepiness and sleep deprivation can cause alterations in metabolic system such as insulin resistance (IR), and the increased pro-inflammatory states and cytokine levels may also lead to a severe state of IR in patients with OSA [3,4].

In addition, one proposed molecular mechanism is through the α-subunit of hypoxia-inducible factor 1 (HIF-1α), as the oxygen-sensitive protein has been suggested to be involved in the regulation of metabolic processes and development of IR [5]. These disruptions can trigger a series of events related to the activation of the sympathetic system, systemic inflammation, and oxidative stress, all of which can be important in increasing the risk of hypertension, metabolic syndrome, and type 2 diabetes mellitus (T2DM) [6].

Approximately 50% of obese people with metabolic syndrome have OSA [7]. The occurrence of OSA is even higher in obese patients with T2DM and severe obesity [8]. Although previous epidemiological studies suggest that OSA may be an independent risk factor for incident T2DM, there are some conflicting results on the association between OSA and IR, especially based on weight status [9].

Since IR is one of the characters of T2DM and can finally result in the development of T2DM, it is imperative to better understand its relationship with OSA [1]. Most studies evaluate the correlation between OSA and IR in only obese or T2DM patients, and few studies have evaluated this association in nondiabetic healthy people according to central obesity status.

Thus, we hypothesized that OSA and IR could affect not only obese or T2DM patients but also non-diabetic healthy people. Accordingly, we aimed to evaluate the relationship between OSA and IR in healthy non-diabetic adults with or without central obesity status.

Discussion

OSA is a very frequent sleep disorder related to cardiovascular disease and T2DM. Although obesity is a main determinant, and OSA is related to T2DM independent of obesity and other confounding factors such as sex, age, and BMI [9]. We tried to examine the relationship between AHI and parameters of metabolic syndrome in the general population and not in obese or T2DM patients.

Results showed that the parameters of metabolic syndrome, including WC, BP, HDL, and TG, were significantly different according to the groups that were divided based on the severity of AHI. Moreover, HOMA-IR was significantly greater in the moderate-to-severe OSA group than in the mild OSA group.

Because OSA is often accompanied by “metabolic syndrome”, the two conditions may causally correlate, and even “Z syndrome” was named for coexisting OSA and metabolic syndrome. Zhang et al. reported that OSA patients with lower SpO2 were more impressionable to IR, which could contribute the coexistence of OSA and metabolic syndrome [13].

The HOMA model is a commonly used method to measure IR. It is a model of the association between glucose and insulin dynamics that anticipates fasting steady-state glucose and insulin concentrations for a wide range of possible combinations of IR and β-cell function [14].

The HOMA model is an easy method for evaluating insulin sensitivity, and it is connected with the results of the glucose clamp test in patients with mild diabetes without hyperglycemia. Multiple studies show a reasonable correlation between HOMA-IR and the euglycemic clamp method that has been the gold standard [15]. Compared with the clamp method, HOMA-IR is simple and time-efficient because it only needs a single blood test assayed for basal state insulin and glucose.

Although mounting studies reported that OSA may be a risk factor for T2DM, previous epidemiological studies showed inconsistent findings regarding the association between OSA and FBG, fasting insulin, or HOMA-IR representing abnormal glucose metabolism. In a study involving 270 middle-aged adults (37–52 years old) without T2DM, Ip et al. found that AHI was a significant independent determinant of fasting insulin and HOMA-IR after controlling for BMI and age, but FBG level did not differ significantly according to the severity of AHI [16].

One previous study of 1344 adults (aged older than 40 years) displayed that FBG was significantly higher in non-obese participants with OSA than in those without OSA, while HOMA-IR and fasting insulin were higher in the obese OSA group than in the obese non-OSA group [17]. In a study involving predominantly non-obese adults, Kritikou et al. found that OSA was significantly associated with HOMA-IR [18].

Likewise with studies of IP et al. and Kritikou et al., our results showed that the relationship between OSA and HOMA-IR differed by weight status with significantly higher HOMA-IR only in the non-obese OSA group, implying that OSA affects insulin sensitivity without preexisting metabolic disturbances of obesity [17].

We supported this insight using quantifying excessive body fat with a variety of measures. Our study results agree with those of Ip et al., who revealed that AHI and Min-SpO2 could significantly determine the fasting insulin and HOMA-IR levels [16]. These inconsistent findings could be due to the difference in study populations and methodology. Instead of targeting only obese subjects or patients suspected of having OSA, our study examined the general population who underwent portable sleep apnea study as part of a preventive health examination program.

Several studies showed possible mechanisms for a causal relationship. Polka et al. reported that IH-induced IR impairs β-cell function, increases hepatocyte glucose output, and increases oxidative stress of the pancreas in C57BL6/J mice [19]. Newer evidence also revealed that chronic IH induced IR in lean mice by promoting the activation of skeletal muscle adenosine monophosphate (AMP)-activated protein kinase [20].

Furthermore, another mechanism proposed that hypoxia in adipose tissue may result in adipocyte cell death, thus causing a plasma free fatty acids increasing, favoring IR [21]. IH also induces an increase in blood TG concentration via reduced adipose tissue lipoprotein lipase activity and a consequent decrease in lipoprotein clearance [22].

From a biochemical molecular standpoint, HIF-1α may play a possible mediating role between OSA and IR. HIF-1α is a subunit of the heterodimeric transcription factor HIF-1 and is a crucial regulator of oxygen metabolism homeostasis. Many studies show substantiating evidence of HIF-1α participating in the inflammatory process caused by the intermittent hypoxia observed in OSA, with HIF-1α levels, significantly increased in severe OSA patients [23,24,25]. Gabryelska et al. even proposed the utilization of HIF-1α as a diagnostic marker of OSA, after excluding other disorders with chronic hypoxia [26].

Moreover, HIF-1α is not only involved in OSA, but it is also linked to IR and diabetes. A C → T non-synonymous single nucleotide polymorphism of HIF-1α gene has been indicated to having a protective effect against diabetes in the Japanese and Hungarian population [27,28]. An animal study showed that a HIF inhibitor may improve IR in high-fat diet mice [29], while in humans, a recent randomized controlled trial discovered that two weeks of eight hours nightly of continuous positive airway pressure increased insulin sensitivity in prediabetes [30].

Considering these results in conjunction with a study where increased serum levels of HIF-1α seen in severe OSA patients were decreased after two months of continuous positive air pressure (CPAP) therapy [25], treating hypoxia may be a putative treatment method for metabolic syndrome via the HIF-1α pathway. However, a pilot study revealed that just one night of CPAP was not sufficient to relieve such pathological changes, and this suggests that long-term CPAP treatment was needed for a protective effect [31].

Estimating hypoxia and the evaluation of OSA rely on polysomnography as ever. Min-SpO2 and AHI are known as crucial factors in the diagnosis of OSA. However, there are some limitations for AHI in investigating the total effect of apnea or hypopnea because AHI only represents the frequency of apneic and hypopnic events and does not reflect the specific duration of each event [32]. In this study, subjects of the low Min-SpO2 group showed significantly higher WC, HDL, TG, and HOMA-IR than those of the high Min-SpO2 group. Therefore, Min-SpO2 might be more clinically important in investigating the degree and results of OSA and metabolic syndrome.

The strength of the current study is that we evaluated a relatively large sample size with a suitable representation of general population, although it was a cross-sectional study. The major limitation of this study was that the results were based on correlation analysis, thus only demonstrating a superficial relationship among OSA severity, IR, and parameters of metabolic syndrome; moreover, it is far away from clarifying the exact relationship with each other.

The second limitation of this study was that we included only male subjects. Because the Healthcare Screening Center is visited by mostly male employees who work nearby, nearly 95% of the subjects who visited our center were men. We decided to exclude female subjects for a more homogenous study population. Further studies with both male and female subjects are needed to truly represent the general population.

reference link :https://www.ncbi.nlm.nih.gov/labs/pmc/articles/PMC8303242/


reference :

Sanapo, L., et al. Association between sleep disordered breathing in early pregnancy and glucose metabolism. Sleep. 2021.

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