Introduction

Obstructive sleep apnea (OSA) is characterized by complete collapses (apneas) or partial collapses (hypopneas) of the upper airway during sleep, leading to intermittent hypoxemia and increased sympathetic arousal. This condition, associated with symptoms of daytime dysfunction and other neurological impairments resulting from these sleep disruptions, is also referred to as obstructive sleep apnea–hypopnea syndrome (OSAHS) [1]. Patients with OSAHS exhibit significantly heterogeneous clinical features [2]. Although continuous positive airway pressure (CPAP) is the primary treatment for OSAHS, its effects on improving cognitive impairment can vary considerably among individuals. Regarding this heterogeneity, the cognitive improvement effects of CPAP therapy are more favorable in younger patients with OSAHS or those who have been using CPAP for an extended period [3,4,5]. However, CPAP it is less effective in older patients and those who cannot tolerate CPAP therapy [6].

A previous cohort study using polysomnography indicated that patients with severe OSA (defined as an apnea–hypopnea index ≥ 30 times/h) exhibit a 1.7 times higher risk of developing Alzheimer’s disease (AD) and a 2.4 times higher risk of developing dementia compared to individuals with no OSA [7]. Clinical studies revealed that sleep fragmentation and apnea are two important environmental factors contributing to cognitive impairment. Both of these factors can increase the levels of amyloid β peptide (Aβ) and phosphorylation of tau proteins, subsequently activating neuroinflammatory responses and affecting the pathological progression of cognitive impairment [8, 9]. Currently, although the specific mechanisms underlying cognitive impairment caused by OSAHS remain unclear, many researchers believe that hippocampal and white matter lesions may be the primary contributors to cognitive impairment in OSAHS [10]. Astrocytes, as essential components of the nervous system, play roles not only in regulating sleep homeostasis [11] but also in controlling respiratory frequency [12].

Recent studies have suggested that in central nervous system, astrocytes maintain mitochondrial homeostasis by regulating the Glucagon like peptide-1 receptor (GLP-1R) signaling and depend on fibroblast growth factor 21 (FGF21) to modulate glucose metabolism [13,14,15]. In addition, S100 calcium binding protein B (S100B) and brain derived neurotrophic factor (BDNF) have been considered as novel markers of brain nerve injury [16, 17]. Clinical studies have suggested that the levels of serum S100B and BDNF are elevated in patients with OSAHS, and BDNF is associated with cognitive impairment [18, 19].

Previous studies have revealed that many inflammatory indicators such as tumor necrosis factor-α (TNF-α) and inflammatory factors such as the interleukin (IL) family and C-reactive protein (CRP) are upregulated in OSAHS, and these factors may promote the occurrence and development of sleep structural disorders in OSAHS [20,21,22,23,24]. In addition, clinical studies have suggested that hypersensitive C-reactive protein (hsCRP) and TNF-α are involved in the aging process; interleukin-6 (IL-6) levels are also associated with cognitive impairment [25]. Therefore, we hypothesized that the abovementioned inflammatory factors could be involved in cognitive impairment in OSAHS.

In addition, obesity is not only one of the main risk factors for OSAHS but is also a risk factor for cognitive impairment. Previous studies have suggested that peripheral obesity can exacerbate apnea and contribute to the accumulation of high triglycerides/free fatty acids in the body. Moreover, dysfunction of the hypothalamic pituitary adrenal axis (HPA axis), chronic low-grade inflammatory response, alterations in blood–brain barrier permeability, and activation of immune cells in the brain (such as astrocytes and microglia) can further promote neuroinflammation and cognitive impairment in OSAHS. Non-obese and obese patients with OSAHS exhibited clinical similarities in the pathophysiological mechanisms of cognitive impairment. Both groups may develop cognitive impairment through dysregulations in respiratory arrest, glucose and lipid metabolism, inflammatory reactions, blood–brain barrier and astrocyte activation, but the etiology is heterogeneous. Therefore, in the second part of this study, the abovementioned serum indicators were selected, and further experiments were carried out to explore the correlation between cognitive impairment scores and these indicators in non-obese and obese patients with OSAHS.

Methods

Population sampling

Patients diagnosed with OSAHS at the Second Affiliated College of Chongqing Medical University from February 2013 to October 2021 were recruited for this study. They were divided into two groups: cases in the non-obese OSAHS group (BMI < 28 kg/m2) and cases in the obese OSAHS group (BMI ≥ 28 kg/m2) according to the diagnostic criteria of OSAHS [26]. The inclusion criteria for the OSAHS group were as follows: meeting the diagnostic criteria for OSAHS but not receiving respiratory-related treatment. The exclusion criteria included: (1) age < 18 years; (2) receiving respiratory-related treatment; (3) existing conditions such as severe acute cerebrovascular disease, dementia, severe liver and kidney disease, heart disease, and acute respiratory failure; (4) other types of sleep disorders; (5) individuals with missing data and incomplete case information. All participants received approval from the ethics committee of our hospital. 2021 Colum Review No. (18).

Serological index tests

The levels of serum glucose (GLU), γ-glutamyl transferase (GGT), and triglycerides (TG) were measured using a Hitachi fully automated biochemical analyzer 7600. The glucose triglyceride index was calculated as TyG index = Ln[fasting triglyceride (mg/dl) × fasting glucose (md/dl)/2]. Blood samples were collected and kept for 30 min, and then they were centrifuged at 3000 r/min for 5 min at 4 ℃, and the serum was stored at − 80 ℃ until further use. The levels of GLP-1R, FGF21, S100B, BDNF, CRP, TNF-α, IL-4, and IL-6 in the serum samples were quantified using enzyme-linked immunosorbent assay (ELISA).

Polysomnography

Patients should avoid daytime napping and abstain from consuming foods or beverages that can negatively impact sleep, such as alcohol, coffee, and strong tea. A multi-channel sleep detector, consisting of the NicoletOne system produced in the United States and the Philips Wellcome Alice 6.0 system produced in the Netherlands, was employed for monitoring purposes. The following parameters were recorded: the apnea–hypopnea index (AHI), lowest oxygen saturation (L-SaO2), and average oxygen saturation (M-SaO2).

Statistical analysis

SPSS 25.0 was used for statistical analyses. The data conforming to normal distribution were presented as mean ± standard deviation (\(\overline{\chi }\)  ± s). In cases where the data did not conform to a normal distribution, it was presented as median (quartile interval), and percentages were used for categorical data. To examine the correlation between two variables, Pearson correlation analysis was applied for continuous variables with a normal distribution, while Spearman correlation analysis was used for those with a non-normal distribution. Backward linear regression analysis was performed with MMSE as the dependent variable, and a significance level of p < 0.05 was considered statistically significant.

Results

Overall baseline characteristics

A total of 34 patients with OSAHS were recruited, comprising 19 patients in the non-obese group and 15 patients in the obese group. When compared to non-obese patients, obese patients exhibited significantly higher AHI (p < 0.05). The differences in other clinical characteristic parameters were not statistically significant (p > 0.05). These results are presented in Table 1.

Table 1 Differences in general clinical characteristics between the non-obese OSAHS group and the obese OSAHS group (n = 34)
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Differences in serum markers between non-obese and obese OSAHS group

As shown in Table 2, the comparison of serological indicators between the obese and non-obese OSAHS groups indicated that the differences were not statistically significant (p > 0.05), and similarly, there were no statistically significant differences in scale scores (p > 0.05).

Table 2 Differences in serum markers between non-obese OSAHS and obese OSAHS groups
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Correlation of serum markers with cognitive scores in non-obese and obese OSAHS patients

In non-obese patients and; in obese patients, correlations are presented in Table 3.

Table 3 Correlation between serum markers and MMSE in obese and non-obese patients with OSAHS
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Correlation of other variables with cognitive scores in non-obese and obese patients with OSAHS

As indicated in Table 4, among non-obese patients, no other variables showed significant correlations with MMSE scores. However, in obese patients, age and BMI were both negatively correlated with MMSE scores.

Table 4 The correlation between other variables and MMSE in non-obese and obese patients with OSAHS
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Backward linear regression analyses of non-obese and obese OSAHS patients

When incorporating the significant indicators from Table 3 and Table 4 into the linear regression equation with MMSE as the dependent variable, the results showed the following significant correlations as presented in Table 5.

Table 5 Multiple linear regression analysis of MMSE in obese and non-obese patients with OSAHS
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Discussion

Mild cognitive impairment represents an early stage of cognitive decline that can progress to dementia over time, underscoring the significance of investigating cognitive impairment in OSAHS as a primary research focus.

Currently, most scholars have two distinct views on the mechanism of cognitive impairment caused by OSAHS. (1) endothelial dysfunction and blood–brain barrier (BBB) disruption: According to one view, patients with OSAHS experience repeated cycles of hypoxia and reoxygenation during sleep, which stimulate endothelial cells. This stimulation can lead to oxidative stress, resulting in the leakage of a significant amount of plasma proteins into the walls of small arteries and perivascular areas. Over time, this process can cause white matter damage, luminal infarction, and various clinicopathological manifestations such as macrophage accumulation, fibrosis of small artery walls, dysfunction of brain cells, neuronal apoptosis, and ultimately inflammation at the blood–brain barrier (BBB). This inflammation can alter the transport of molecules across the barrier, contributing to cognitive dysfunction [27, 28]. (2) Impaired perfusion regulation: The other view suggests that in OSAHS, sleep fragmentation and abnormal cerebral blood oxygenation can lead to impaired regulation of blood flow. This impairment can result in cerebral underperfusion in areas with limited collateral circulation, such as terminal arterial regions. Over time, this reduced blood flow can lead to lacunar infarctions, white matter damage, abnormalities in white matter fiber bundles, loss of gray matter, and ultimately cognitive impairment [29, 30]. These two views reflect ongoing research efforts to better understand the complex mechanisms underlying cognitive impairment in individuals with OSAHS.

Association of serum glucose and lipid metabolism with cognitive-behavioral impairment in OSAHS

Many scholars believe that glucose plays a significant role in cognitive impairment in OSAHS. There are several reasons for this: (1) vascular aging and reduced blood flow—hyperglycemia is thought to accelerate vascular aging and reduce cerebral blood flow, potentially leading to focal ischemic infarctions, diffusion abnormalities in white matter and basal ganglia, neuronal damage, apoptosis, and impaired executive cognitive function; (2) endothelial damage and inflammation—elevated blood sugar levels can harm the endothelial cells of small and medium-sized brain blood vessels, contributing to increased inflammation; (3) altered cerebral microvessels—high blood sugar may also alter the structure of cerebral microvessels, reducing the number of capillaries and increasing arteriovenous short circuits. This alteration can potentially affect the delivery of nutrients to neural tissue, making brain tissue more vulnerable to damage due to hypoxia when perfusion pressure or blood flow decreases.

In this study, an independent correlation between blood glucose and cognitive scores was observed in non-obese patients with OSAHS, suggesting that elevated blood glucose, insulin resistance, and increased endocrine function may be contributing factors. Interestingly, contrary to previous studies, this research found a significant positive correlation between triglycerides (TG) and MMSE scores in obese patients. Several potential explanations for this unexpected finding include the small sample size and potential selection bias. Additionally, triglycerides may further promote insulin resistance and metabolic disorders, which could, in turn, have a protective effect on cognitive function by balancing immune responses. Further research is needed to clarify these relationships.

Association of serum inflammatory factors with cognitive-behavioral impairment in OSAHS

Most scholars believe that targeting pro-inflammatory IL-6 signaling may be a strategy for alleviating memory impairment and metabolic issues. Ren et al. have demonstrated in several studies that IL-6 is significantly associated with peripheral metabolism and cognitive impairment in AD [25, 31] and may promote brain repair by regulating microglia/macrophage function. It is also the most notable promoter for M2 polarization in microglia and macrophages to date [32, 33].

In non-obese patients, this study found a significant negative correlation between glucose and cognitive scores and a significant positive correlation between IL-6 and cognitive scores, which aligns with previous findings. Interestingly, unlike prior research, this study discovered a significant negative correlation between IL-4 and cognitive scores in obese patients, suggesting that immune homeostasis imbalance may also play a role in the progression of cognitive impairment in obese patients.

Association of serum glial cell markers with cognitive-behavioral impairment in OSAHS

Brain-derived neurotrophic factors (BDNFs) play a crucial role in supporting the survival and growth of neurons, influencing synaptic differentiation, and participating in the regulation of neural plasticity [34]. Prolonged exposure to hypoxia can lead to hippocampal neuronal atrophy, reduced BDNF levels, and worsening cognitive impairment. However, after CPAP treatment, cognitive impairment often improves, suggesting that BDNF is a significant factor in the relationship between OSAHS and cognitive deficits [35].

The results of this study did not establish a clear association between BDNF and cognitive impairment, which contradicts previous findings. This inconsistency may be attributed to the inclusion of OSAHS patients with multiple systemic diseases in this study, as well as the presence of various factors that can influence serum BDNF levels. Therefore, it is possible that uncontrollable variables interfered with serum BDNF levels, potentially affecting the utility of serum BDNF levels as an indicator of cognitive impairment in OSAHS to some extent.

S100B is upregulated in serum and cerebrospinal fluid during various glial cell injuries [36], with its primary expression in the nervous system occurring in astrocytes. In animal models, the response of astrocytes may contribute to OSA-related neuroinflammation [37]. Unfortunately, this study did not identify an association between S100B and cognitive impairment in patients with OSAHS. In addition, other possible astrocyte related markers GLP-1R and FGF21 were not significantly associated with cognitive impairment. It is speculated that this study solely examined the correlation between serum indicators and cognitive impairment in patients, using a relatively limited methodology. As a result, it cannot definitively determine whether serum S100B and BDNF are secreted by astrocytes or microglia.

While this study has yielded some initial positive findings, there are several limitations that should be acknowledged: (1) small sample size and selective bias—the negative results observed in obese patients in this study may be attributed to the small sample size and potential selective bias. The limited sample size can weaken the study’s findings and may warrant further investigation in larger, multicenter studies. (2) Methodological simplicity—the study primarily focused on examining the correlation between patient serum indicators, polysomnography (PSG) results, and cognitive impairment. The methodology used in the study is relatively straightforward and cannot definitively establish whether the serum indicators originate from astrocytes or microglia. (3) Correlational nature—this study is of a correlational nature, and therefore, it cannot establish causality. It is unclear whether cognitive impairment in OSAHS is primarily driven by glucose and lipid metabolism issues or hypoxia. Future prospective cohort studies could consider incorporating additional indicators, such as cerebrospinal fluid measurements and imaging, to gain a more comprehensive understanding of the pathological progression in patients. Addressing these limitations in future research can provide a more robust and comprehensive understanding of the relationship between OSAHS, metabolic factors, hypoxia, and cognitive impairment.

Conclusions

The findings of this study suggest that in non-obese patients with OSAHS, both GLU and IL-6 were independently correlated with cognitive impairment, whereas in obese patients with OSAHS, age and IL-4 were independently associated with cognitive impairment. Recognizing this heterogeneity at an early stage may offer valuable theoretical support for further research.