Blood-based lipidomic signature of severe obstructive sleep apnoea in Alzheimer’s disease

Alzheimer’s disease (AD) is the main cause of dementia and one of the main causes of disability and death after 75 years of age. Given the increase in life expectancy, its prevalence is expected to increase drastically in the coming years [1]. Currently, there is a lack of drugs that can cure or manage the disease long-term. Therefore, it is important to identify all the factors that we can modify to avoid both the appearance and progression of this disease.

In recent years, different sleep disorders, including their duration and quality, have been shown to be risk factors for the development of AD. Of all known sleep disturbances, the presence of obstructive sleep apnoea (OSA) has been consistently identified as a risk factor for AD in population studies AD [2, 3]. Studies on cognitively healthy elderly subjects with OSA have reported increased amyloid β-42 (Aβ-42) and phosphorylated tau (p-tau) levels as measured in the cerebrospinal fluid (CSF) or on positron emission tomography (PET) [4]. In addition, longitudinal studies have reported an increase in the speed of cerebral amyloid accumulation promoted by OSA [5]. Its prevalence in patients with AD ranges between 45 and 90%, presenting as severe OSA in up to 40% of AD patients [6].

Clinically, although some studies have shown that the presence of OSA advances the age of diagnosis of mild cognitive impairment (MCI) and AD, suggesting that it could accelerate the progression of these diseases in the early stages [7], and that continuous positive airway pressure (CPAP) can improve short-term cognitive performance [8], other longitudinal studies have not observed that the presence of OSA worsens the cognitive evolution of patients with mild–moderate AD [9].

The high prevalence of OSA in patients with AD makes the diagnosis of OSA essential, given that it is also a risk factor for hypertension, diabetes, heart failure, stroke or depression, all of which are risk factors for AD [10, 11]. However, the study of sleep in these patients is complex. Although polysomnography (PSG) is the technique of choice, the need to go to the hospital to sleep one or two nights often limits its usefulness in patients with AD and can generate sleep data that do not correspond to the patient’s usual routine at home [12]. In addition, simple screening questionnaires, including the STOP-Bang questionnaire (SBQ) [13] and the Berlin questionnaire (BQ) [14], have been shown to be insufficient for identifying subjects at risk of OSA in this type of population [15]. Thus, the search for new screening tools to detect OSA in this population remains.

Lipidomics is the science of the large-scale determination of individual lipid species in biological samples and has demonstrated great potential in the search for disease-associated biomarkers. OSA is a pathologic condition that is strongly associated with systemic lipid dyshomeostasis [16]. In addition, OSA can increase lipoxidation, as has been evidenced in both the brain and blood of AD patients [17, 18]. Therefore, the identification of systemic alterations in lipid species using high-performance lipidomic platforms could contribute to finding OSA-associated lipid profiles in AD and increase our understanding of the relationship between these two complex pathological conditions.

Therefore, the aim of our study was (i) to evaluate whether the expression pattern of circulating lipids is different between AD patients with and without severe OSA, which would be of great relevance for the practical and noninvasive screening of OSA among patients with AD; (ii) to investigate whether the severity of OSA is correlated with changes in plasma lipid levels; and (iii) to evaluate the diagnostic performance of lipidomics findings in joint use with classic screening tests such as the SBQ.

In this study, we identified a lipidomic profile associated with the presence of severe OSA in patients with AD. This lipidomic profile was significantly correlated with different polysomnographic measures related to sleep fragmentation and hypoxemia related to OSA severity. We identified 25 plasma lipids that were found in different amounts between AD patients with and without severe OSA, regardless of the incorporation of confounding factors. The differentially expressed lipids were mostly phospholipids, suggesting that cellular membranes are especially susceptible to OSA-mediated pathological alterations. In the machine learning multivariate analyses, the plasma levels of these lipid species allowed us to discriminate those subjects with severe OSA with a much greater capacity than through the use of the STOP-Bang screening questionnaire alone.

AD is a neurodegenerative disease whose appearance and evolution are associated with a number of factors, such as β-amyloid, tau, inflammation, arterial hypertension and diet [30]. In recent years, certain sleep disorders, such as OSA, have been shown to be risk factors that favour the accumulation of amyloid [5] and the appearance of the disease [2, 3]. Up to 40% of patients with mild–moderate AD present with severe OSA; however, the study of this association has not been generalized to memory units in the clinical setting [15].

No published data have shown that the presence of OSA in the dementia phase of AD indicates a worse prognosis at the cognitive level [9]. The underdiagnosis of chronic disorders such as OSA represents an additional cost for health systems compared to the adequate diagnosis and treatment of these diseases [31], and in the specific case of OSA, we know that it is associated with greater difficulties in the control of blood pressure, increased insulin resistance, metabolic syndrome or obesity, all factors that worsen the cognitive evolution of patients [32, 33]. Consequently, and because of the difficulties in performing PSG both due to its economic cost and the relative noncompliance of patients with cognitive impairment, together with the limited usefulness of screening tests [15] in this population, it is justified to explore new peripheral biomarkers that allow the detection of severe forms of OSA.

The brain is mainly composed of lipids, and alterations in lipid composition have been described in AD [34]. OSA has been shown to alter lipid composition at the systemic level and increase lipoxidation [35, 36]. For this reason, we performed an undirected lipidomic analysis with liquid chromatography-tandem mass spectrometry (LC–MS/MS) to robustly and reliably discover biomarkers, as has been done with a great variety of diseases [37, 38]. In our study, we observed how a signature composed of 4 lipid species could serve as a biomarker of severe OSA in patients with AD and be of significantly higher value than the STOP-Bang questionnaire alone, which, to date, has been the most effective screen tool for this population group [15]. These results could allow the identification of those subjects with AD with a high probability of presenting severe OSA and who therefore could be confirmed by PSG. These results would allow the personalized management of patients with AD with high suspicion of severe OSA.

Although lipidomics has been used to study different aspects of AD, especially those related to the diagnosis and differential diagnosis with other types of dementia [39‐41], this technique has not been used in the search for biomarkers for the diagnosis of OSA in the AD population. In the population without cognitive impairment, there are also few studies on nondirected metabolomics/lipidomics in blood. Ferrarini et al. [42], in a sample of 33 subjects, identified 14 metabolites, including platelet-activating factor and lysophospholipids, together with some compounds related to the differential activity of the gut microflora (bile pigments and pipecolic acid), that distinguished the severity of OSA; however, they did not analyse the performance of these metabolites as biomarkers of OSA. Lebkuchen et al. [43] identified the differential plasma levels of 22 lipid species in subjects with an AHI> 15 events/hour. Pinilla et al. attempted to overcome some of the limitations of these studies, such as the low reliability due to small sample sizes, the cross-sectional designs and the lack of adjustment for confounding variables [44]. In their study, Pinilla et al. identified a plasma profile composed of 33 metabolites, including lipids, in OSA vs. non-OSA patients. In accordance with our results, in the latter study, PLs were the most affected group of lipids in OSA [45].

To our knowledge, our study is the first attempt to investigate the OSA-associated lipid profile in a population with a high prevalence of this pathological condition, such as patients with AD. Our analysis in an extensive cohort of subjects with mild–moderate AD revealed that despite adjusting for different covariates to eliminate the effect of confounding variables, there were significant alterations in plasma lipid levels due to the presence of severe OSA. In addition, the majority of differentially expressed lipids were also strongly correlated with different PSG measures, especially with variables related to hypoxemia and sleep fragmentation (AHI, mean SaO2, respiratory arousal index, minimum SaO2 and CT90).

The majority of identified lipid species associated with OSA severity were PLs. Pathway enrichment analysis revealed that the metabolism of these lipids was significantly dysregulated. PLs are major constituents of cellular membranes. They provide an optimal environment for the interaction of proteins, their trafficking and their function. The regulation of membrane lipid homeostasis is highly important in AD because amyloid precursor protein is a transmembrane protein, and membrane lipid dysregulation may affect the processing of this protein, leading to increased Aβ production [46]. OSA has been shown to increase oxidative stress [35]. Elevated lipid peroxidation is evidenced in both the brain and blood of AD patients [17, 18]. Therefore, OSA, by increasing lipid peroxidation, may disrupt membrane lipid homeostasis and contribute to AD pathogenesis. Supporting this notion, in our study, we found that several significantly altered lipid species were oxidized, which may have been caused by increased lipid peroxidation due to a more severe OSA. In addition, dysregulation regarding PL plasmalogens was also associated with the severity of OSA in AD. PL plasmalogens are a class of lipids enriched in cellular membranes that have been suggested to protect other membrane lipids against lipid peroxidation. Furthermore, our data also linked altered plasma levels of a cardiolipin (CL (78:2)) to OSA severity. CL is a mitochondria-exclusive PL that is essential for mitochondrial functionality. Mitochondria are the main producers of reactive oxygen species (ROS), and disruption of their functionality, which is evidenced in AD, has strongly been related to an increase in ROS [47]. Additionally, membrane PLs are a major source of lipid mediators that have a fundamental role in biological processes such as inflammation. Therefore, PL dyshomeostasis may also contribute to elevated systemic inflammation, which is characteristic of both AD and OSA [48, 49]. Our results also linked several TG species to OSA severity in AD patients. TGs are neutral lipids reserved in intracellular organelles named lipid droplets (LDs). At the systemic level, LDs are mainly produced in adipose tissue, but all cells can produce these organelles. In the periphery, LDs not only serve as a lipid storage and supply but also affect physiological processes, such as inflammation, cell signalling and redox homeostasis. For example, LDs in various immune cell types contain a large amount of arachidonic acid, which can serve as a precursor for eicosanoid synthesis [50]. Interestingly, our data also associated an eicosanoid (Cis-8,11,14,17-ETA) with the severity of OSA in AD, highlighting the possible role of OSA-derived systemic inflammation as a contributor to AD pathogenesis.

The present study has some limitations. Due to the incipient state of this field of research, an exploratory approach was carried out with the objective of obtaining new knowledge from which new hypotheses can be generated. Therefore, a targeted methodology is needed to determine the validity of our findings in an independent sample of individuals, especially in those with severe OSA. We included patients with MMSE scores > 20, so the results should be extrapolated cautiously for patients in more advanced stages of the disease. The main strength of this study was the use of PSG, which is the gold standard test, as the diagnostic method for OSA and allowed the performance of correlation analysis with different PSG variables related to the severity of OSA. Another strong point is that it included a relatively large sample of subjects who were recruited consecutively, which contributes to the generalization of the data. The patients were evaluated according to clinical criteria and specific CSF biomarkers of AD, so we can ensure that the patients had both clinically and biologically evident AD.

In this study, using undirected lipidomics, we identified a lipid profile in the plasma of severe OSA patients with mild–moderate AD that was correlated with different polysomnographic measures of OSA severity. PLs and GLs were the most dysregulated lipids concerning OSA severity in AD patients. The presence of several oxidized lipid species suggests that OSA may contribute to AD pathogenesis by increasing lipid peroxidation. In addition, we identified a lipidomic signature that allows the identification of subjects with AD and severe OSA in a population of AD with better accuracy than the STOP-Bang screening scale, which suggests that they could be used as plasma biomarkers for the management of OSA or for screening those patients who could subsequently benefit from undergoing a PSG in the face of a high suspicion of severe OSA.