Cerebrospinal fluid lipidomic fingerprint of obstructive sleep apnoea in Alzheimer's disease

Combining static and dynamic functional connectivity analyses to identify male patients with obstructive sleep apnea and predict clinical symptoms

BACKGROUND AND PURPOSE

Patients with obstructive sleep apnea (OSA) experience chronic intermittent hypoxia and sleep fragmentation, leading to brain ischemia and neurological dysfunction. Therefore, it is important to identify features that can differentiate patients with OSA from healthy controls (HC) and provide insights into the underlying brain alterations associated with OSA. This study aimed to distinguish patients with OSA from healthy individuals and predict clinical symptom alterations using cerebellum-whole-brain static and dynamic functional connectivity (sFC and dFC, respectively), with the cerebellum as the seed region.

METHODS

Sixty male patients with OSA and 60 male HC matched for age, education level, and sex were included. Using 27 cerebellar seeds, sliding-window analysis was performed to calculate sFC and dFC between the cerebellum and the whole brain. The sFC and dFC values were then combined and used in multiple machine-learning models to distinguish patients with OSA from HC and predict the clinical symptoms of patients with OSA.

RESULTS

Patients with OSA showed increased dFC between cerebellar subregions and the superior and middle temporal gyri and decreased dFC with the middle frontal gyrus. Conversely, increased sFC was observed between cerebellar subregions and the cerebellar lobule VI, cingulate gyrus, middle frontal gyrus, inferior parietal lobules, insula, and superior temporal gyrus. Combined dynamic-static FC features demonstrated superior classification performance with a support vector machine in discriminating OSA from HC. In clinical symptom prediction, FC alterations contributed up to 30.11 % to cognitive impairment, 55.96 % to excessive sleepiness, and 27.94 % to anxiety and depression.

CONCLUSIONS

Combining cerebrocerebellar sFC and dFC analyses enables high-precision classification and prediction of OSA. Aberrant FC patterns reflect compensatory brain reorganization and disrupted cognitive network integration, highlighting potential neuroimaging markers for OSA.

The CSF lipid profile in patients with probable idiopathic normal pressure hydrocephalus differs from control but does not differ between shunt responders and non-responders

Idiopathic normal pressure hydrocephalus is a common form of hydrocephalus in the elderly, characterized by enlarged ventricles combined with clinical symptoms presenting as gait impairment, urinary incontinence, and dementia. Idiopathic normal pressure hydrocephalus may be difficult to differentiate clinically from other neurodegenerative disorders, and up to 80% of cases may remain unrecognized and thus untreated. Consequently, there is a pressing demand for biomarkers that can confirm the diagnosis of idiopathic normal pressure hydrocephalus. In this exploratory study, CSF was sampled from the lumbar compartment of 21 control individuals and 19 probable idiopathic normal pressure hydrocephalus patients and analyzed by an untargeted mass spectroscopy-based platform to reveal a complete CSF lipid profile in these samples. Two hundred forty-four lipids from 17 lipid classes were detected in CSF. Various lipid classes, and select individual lipids, were reduced in the CSF obtained from patients with probable idiopathic normal pressure hydrocephalus, whereas a range of lipids belonging to the class of triacylglycerols was elevated. We detected no difference in the CSF lipid profile between probable idiopathic normal pressure hydrocephalus patients with and without clinical improvement following CSF shunting. In conclusion, the lipidomic profile of the CSF in patients with probable idiopathic normal pressure hydrocephalus, therefore, may serve as a sought after biomarker of the pathology, which may be employed to complement the clinical diagnosis.

Does glial lipid dysregulation alter sleep in Alzheimer's and Parkinson's disease?

In this opinion article, we discuss potential connections between sleep disturbances observed in Alzheimer's disease (AD) and Parkinson's disease (PD) and the dysregulation of lipids in the brain. Research using Drosophila has highlighted the role of glial-mediated lipid metabolism in sleep and diurnal rhythms. Relevant to AD, the formation of lipid droplets in glia, which occurs in response to elevated neuronal reactive oxygen species (ROS), is required for sleep. In disease models, this process is disrupted, arguing a connection to sleep dysregulation. Relevant to PD, the degradation of neuronally synthesized glucosylceramides by glia requires glucocerebrosidase (GBA, a PD-associated risk factor) and this regulates sleep. Loss of GBA in glia causes an accumulation of glucosylceramides and neurodegeneration. Overall, research primarily using Drosophila has highlighted how dysregulation of glial lipid metabolism may underlie sleep disturbances in neurodegenerative diseases.

Advances in clinical application of lipidomics in healthy ageing and healthy longevity medicine

It is imperative to optimise health and healthspan across the lifespan. The accumulation of reactive oxygen species (ROS) has been implicated in the hallmarks of ageing and inhibiting ROS production can potentially delay ageing whilst increasing healthy longevity. Lipids and lipid mediators (derivatives of lipids) are becoming increasingly recognized as central molecule in tissue and cellular function and are susceptible to peroxidation; hence linked with ageing. Lipid classes implicated in the ageing process include sterols, glycerophospholipids, sphingolipids and the oxidation products of polyunsaturated fatty acids but these are not yet translated into the clinic. Further mechanistic studies are required for the understanding of lipid classes in the ageing process. Lipidomics, the system level characterisation of lipid species with respect to metabolism and function, might provide a significant and useful biological age profiling tool through longitudinal studies. Lipid profiles in different ages among healthy individuals could be harnessed as lipid biomarkers of healthy ageing with potential integration for the development of lipid-based ageing clock (lipid clock). The potential of a lipid clock includes the prediction of future morbidity or mortality, which will promote precision and healthy longevity medicine.

Brain cholesterol and Alzheimer's disease: challenges and opportunities in probe and drug development

Cholesterol homeostasis is impaired in Alzheimer's disease; however, attempts to modulate brain cholesterol biology have not translated into tangible clinical benefits for patients to date. Several recent milestone developments have substantially improved our understanding of how excess neuronal cholesterol contributes to the pathophysiology of Alzheimer's disease. Indeed, neuronal cholesterol was linked to the formation of amyloid-β and neurofibrillary tangles through molecular pathways that were recently delineated in mechanistic studies. Furthermore, remarkable advances in translational molecular imaging have now made it possible to probe cholesterol metabolism in the living human brain with PET, which is an important prerequisite for future clinical trials that target the brain cholesterol machinery in Alzheimer's disease patients-with the ultimate aim being to develop disease-modifying treatments. This work summarizes current concepts of how the biosynthesis, transport and clearance of brain cholesterol are affected in Alzheimer's disease. Further, current strategies to reverse these alterations by pharmacotherapy are critically discussed in the wake of emerging translational research tools that support the assessment of brain cholesterol biology not only in animal models but also in patients with Alzheimer's disease.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Respiratory Dysfunction in Alzheimer's Disease-Consequence or Underlying Cause? Applying Animal Models to the Study of Respiratory Malfunctions

Alzheimer's disease (AD) is a neurodegenerative brain disease that is the most common cause of dementia among the elderly. In addition to dementia, which is the loss of cognitive function, including thinking, remembering, and reasoning, and behavioral abilities, AD patients also experience respiratory disturbances. The most common respiratory problems observed in AD patients are pneumonia, shortness of breath, respiratory muscle weakness, and obstructive sleep apnea (OSA). The latter is considered an outcome of Alzheimer's disease and is suggested to be a causative factor. While this narrative review addresses the bidirectional relationship between obstructive sleep apnea and Alzheimer's disease and reports on existing studies describing the most common respiratory disorders found in patients with Alzheimer's disease, its main purpose is to review all currently available studies using animal models of Alzheimer's disease to study respiratory impairments. These studies on animal models of AD are few in number but are crucial for establishing mechanisms, causation, implementing potential therapies for respiratory disorders, and ultimately applying these findings to clinical practice. This review summarizes what is already known in the context of research on respiratory disorders in animal models, while pointing out directions for future research.

Metabolipidomic Analysis in Patients with Obstructive Sleep Apnea Discloses a Circulating Metabotype of Non-Dipping Blood Pressure

A non-dipping blood pressure (BP) pattern, which is frequently present in patients with obstructive sleep apnea (OSA), confers high cardiovascular risk. The mechanisms connecting these two conditions remain unclear. In the present study we performed a comprehensive analysis of the blood metabolipidome that aims to provide new insights into the molecular link between OSA and the dysregulation of circadian BP rhythmicity. This was an observational prospective longitudinal study involving adults with suspected OSA who were subjected to full polysomnography (PSG). Patients with an apnea-hypopnea index ≥ 5 events/h were included. Fasting plasma samples were obtained the morning after PSG. Based on the dipping ratio (DR; ratio of night/day BP values) measured via 24 h ambulatory BP monitoring, two groups were established: dippers (DR ≤ 0.9) and non-dippers (DR > 0.9). Treatment recommendations for OSA followed the clinical guidelines. Untargeted metabolomic and lipidomic analyses were performed in plasma samples via liquid chromatography-tandem mass spectrometry. Non-dipper patients represented 53.7% of the cohort (88/164 patients). A set of 31 metabolic species and 13 lipidic species were differentially detected between OSA patients who present a physiologic nocturnal BP decrease and those with abnormal BP dipping. Among the 44 differentially abundant plasma compounds, 25 were putatively identified, notably glycerophospholipids, glycolipids, sterols, and fatty acid derivates. Multivariate analysis defined a specific metabotype of non-dipping BP, which showed a significant dose-response relationship with PSG parameters of OSA severity, and with BP dipping changes after 6 months of OSA treatment with continuous positive airway pressure (CPAP). Bioinformatic analyses revealed that the identified metabolipidomic profile was found to be implicated in multiple systemic biological pathways, with potential physiopathologic implications for the circadian control of BP among individuals with OSA.

Uncovering the Lipid Web: Discovering the Multifaceted Roles of Lipids in Human Diseases and Therapeutic Opportunities

Lipids, characterized by their hydrophobic nature, encompass a wide range of molecules with distinct properties and functions [...].