Search

Abstract Background Obstructive sleep apnoea (OSA) has a high prevalence in patients with Alzheimer’s disease (AD). Both conditions have been shown to be associated with lipid dysregulation. However, the relationship between OSA severity and alterations in lipid metabolism in the brains of patients with AD has yet to be fully elucidated. In this context, we examined the cerebrospinal fluid (CSF) lipidome of patients with suspected OSA to identify potential diagnostic biomarkers and to provide insights into the pathophysiological mechanisms underlying the effect of OSA on AD. Methods The study included 91 consecutive AD patients who underwent overnight polysomnography (PSG) to diagnose severe OSA (apnoea-hypopnea index ≥ 30/h). The next morning, CSF samples were collected and analysed by liquid chromatography coupled to mass spectrometry in an LC-ESI-QTOF-MS/MS platform. Results The CSF levels of 11 lipid species were significantly different between AD patients with (N = 38) and without (N = 58) severe OSA. Five lipids (including oxidized triglyceride OxTG(57:2) and four unknown lipids) were significantly correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Our analyses revealed a 4-lipid signature (including oxidized ceramide OxCer(40:6) and three unknown lipids) that provided an accuracy of 0.80 (95% CI: 0.71–0.89) in the detection of severe OSA. These lipids increased the discriminative power of the STOP-Bang questionnaire in terms of the area under the curve (AUC) from 0.61 (0.50–0.74) to 0.85 (0.71–0.93). Conclusions Our results reveal a CSF lipidomic fingerprint that allows the identification of AD patients with severe OSA. Our findings suggest that an increase in central nervous system lipoxidation may be the principal mechanism underlying the association between OSA and AD.

Abstract Background Previous studies challenge the impact of obstructive sleep apnea (OSA) once patients are diagnosed with Alzheimer’s disease (AD). Nevertheless, OSA recognizably disrupts sleep, and relevant associations between sleep, AD pathological markers, and cognition have been demonstrated. We aimed to further explore this, evaluating the associations between each breathing cessation event that compose the apnea–hypopnea index (AHI) and the sleep structure to finally investigate whether this was related to increased levels of AD markers and higher cognitive decline. Methods Observational, prospective study, including consecutive patients diagnosed with mild-moderate AD. The participants were submitted to overnight polysomnography followed by a cerebrospinal fluid collection for AD pathological markers levels determination. Neuropsychological assessment was performed at baseline and after 12 months of follow-up. Results The cohort was composed of 116 patients (55.2% females) with a median [p25;p75] age of 76.0 [72.0;80.0] years and an AHI of 25.9 [15.1;48.5], which was mainly defined by the presence of hypopneas and obstructive apneas. These were distinctively associated with the sleep structure, with obstructive apneas being related to arousals and sleep lightening and hypopneas being related to an increased number of arousals only. Despite having a lower frequency, mixed and central apneas also presented associations with the sleep structure, particularly increasing the time spent in the lighter sleep stages. In relation to AD pathological markers, obstructive and mixed apneas were related to an augment in neurofilament light levels while hypopneas were associated with a higher phosphorylated-tau/amyloid-beta protein ratio. Hypopneas were the most important event for an increased cognitive decline at the 12-month follow-up. Conclusions Our findings highlight the importance of a patient-centered approach, with a comprehensive and detailed analysis of the AHI to effectively predict the different outcomes and tailor the appropriate therapeutic strategies.

Abstract Background Obstructive sleep apnoea (OSA) is the most frequent form of sleep-disordered breathing in patients with Alzheimer’s disease (AD). Available evidence demonstrates that both conditions are independently associated with alterations in lipid metabolism. However, it is unknown whether the expression of lipids is different between AD patients with and without severe OSA. In this context, we examined the plasma lipidome of patients with suspected OSA, aiming to identify potential diagnostic biomarkers and to provide insights into the pathophysiological mechanisms underlying the disease. Methods The study included 103 consecutive patients from the memory unit of our institution with a diagnosis of AD. The individuals were subjected to overnight polysomnography (PSG) to diagnose severe OSA (apnoea-hypopnea index ≥30/h), and blood was collected the following morning. Untargeted plasma lipidomic profiling was performed using liquid chromatography coupled with mass spectrometry. Results We identified a subset of 44 lipids (mainly phospholipids and glycerolipids) that were expressed differently between patients with AD and severe and nonsevere OSA. Among the lipids in this profile, 30 were significantly correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Machine learning analyses revealed a 4-lipid signature (phosphatidylcholine PC(35:4), cis-8,11,14,17-eicosatetraenoic acid and two oxidized triglycerides (OxTG(58:5) and OxTG(62:12)) that provided an accuracy (95% CI) of 0.78 (0.69–0.86) in the detection of OSA. These same lipids improved the predictive power of the STOP-Bang questionnaire in terms of the area under the curve (AUC) from 0.61 (0.50–0.74) to 0.80 (0.70–0.90). Conclusion Our results show a plasma lipidomic fingerprint that allows the identification of patients with AD and severe OSA, allowing the personalized management of these individuals. The findings suggest that oxidative stress and inflammation are potential prominent mechanisms underlying the association between OSA and AD.

Background: Oxidative stress is considered to play an important role in the pathogenesis of Alzheimer's disease (AD). It has been observed that oxidative damage to specific protein targets affecting particular functional networks is one of the mechanisms by which oxidative stress contributes to neuronal failure and consequently loss of cognition and AD progression. Studies are lacking in which oxidative damage is measured at both systemic and central fluid levels and in the same cohort of patients. We aimed to determine the levels of both plasma and cerebrospinal fluid (CSF) nonenzymatic protein damage in patients in the continuum of AD and to evaluate the relation of this damage with clinical progression from mild cognitive impairment (MCI) to AD. Methods: Different markers of nonenzymatic post-translational protein modification, mostly from oxidative processes, were detected and quantified in plasma and CSF by isotope dilution gas chromatography‒mass spectrometry using selected ion monitoring (SIM-GC/MS) for 289 subjects: 103 AD, 92 MCI, and 94 control subjects. Characteristics of the study population such as age, sex, Mini-mental state examination, CSF AD biomarkers, and APOE ϵ4, were also considered. Results: Forty-seven (52.8%) MCI patients progressed to AD during follow-up (58 ± 12.5 months). After controlling for age, sex, and APOE ϵ4 allele, plasma and CSF concentrations of protein damage markers were not associated with either diagnosis of AD or MCI. The CSF levels of nonenzymatic protein damage markers were associated with none of the CSF AD biomarkers. In addition, neither in CSF nor in plasma were the levels of protein damage associated with the MCI to AD progression. Conclusion: The lack of association between both CSF and plasma concentrations of nonenzymatic protein damage markers and AD diagnosis and progression suggests that oxidative damage in AD is a pathogenic mechanism specifically expressed at the cell-tissue level, not in extracellular fluids.

BackgroundProgressive cognitive decline is the most relevant clinical symptom of Alzheimer’s disease (AD). However, the rate of cognitive decline is highly variable between patients. Synaptic deficits are the neuropathological event most correlated with cognitive impairment in AD. Considering the important role of microRNAs (miRNAs) in regulating synaptic plasticity, our objective was to identify the plasma miRNAs associated with the rate of cognitive decline in patients with mild AD.MethodsWe analyzed 754 plasma miRNAs from 19 women diagnosed with mild AD using TaqMan low-density array cards. The patients were grouped based on the rate of decline in the MMSE score after 2 years [

Manual ELISA assays are the most commonly used methods for quantification of biomarkers; however, they often show inter- and intra-laboratory variability that limits their wide use. Here, we compared the Innotest ELISA method with two fully automated platforms (Lumipulse and Elecsys) to determine whether these new methods can provide effective substitutes for ELISA assays. We included 149 patients with AD (n = 34), MCI (n = 94) and non-AD dementias (n = 21). Aβ42, T-tau, and P-tau were quantified using the ELISA method (Innotest, Fujirebio Europe), CLEIA method on a Lumipulse G600II (Fujirebio Diagnostics), and ECLIA method on a Cobas e 601 (Roche Diagnostics) instrument. We found a high correlation between the three methods, although there were systematic differences between biomarker values measured by each method. Both Lumipulse and Elecsys methods were highly concordant with clinical diagnoses, and the combination of Lumipulse Aβ42 and P-tau had the highest discriminating power (AUC 0.915, 95% CI 0.822–1.000). We also assessed the agreement of AT(N) classification for each method with AD diagnosis. Although differences were not significant, the use of Aβ42/Aβ40 ratio instead of Aβ42 alone in AT(N) classification enhanced the diagnostic accuracy (AUC 0.798, 95% CI 0.649–0.947 vs. AUC 0.778, 95% CI 0.617–0.939). We determined the cut-offs for the Lumipulse and Elecsys assays based on the Aβ42/Aβ40 ratio ± status as a marker of amyloid pathology, and these cut-offs were consistent with those recommended by manufacturers, which had been determined based on visual amyloid PET imaging or diagnostic accuracy. Finally, the biomarker ratios (P-tau/Aβ42 and T-tau/Aβ42) were more consistent with the Aβ42/Aβ40 ratio for both Lumipulse and Elecsys methods, and Elecsys P-tau/Aβ42 had the highest consistency with amyloid pathology (AUC 0.994, 95% CI 0.986–1.000 and OPA 96.4%) at the ≥0.024 cut-off. The Lumipulse and Elecsys cerebrospinal fluid (CSF) AD assays showed high analytical and clinical performances. As both automated platforms were standardized for reference samples, their use is recommended for the measurement of CSF AD biomarkers compared with unstandardized manual methods, such as Innotest ELISA, that have demonstrated a high inter and intra-laboratory variability.